Table of contents

The issue of IOP Conference Series: Earth and Environmental Science contains the outstanding papers presented at Southeast Asian Conference on Geophysics (SEACG) 2020. Due to Covid-19 Pandemic, the 3rd SEACG 2020 Conference was held online on 3 – 5 November 2020.

List of Committees SEACG 2020, Documetation, Images are available in this pdf.

The 3^rd Southeast Asian Conference on Geophysics (SEACG) 2020

All papers published in this volume of IOP Conference Series: Earth and Environmental Science have been peer reviewed through processes administered by the editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

• Type of peer review: Single blind

• Conference submission management system: Conference web submission system

• Number of submission Received: 151 manuscripts received

• Number of submission sent for review: 110 manuscripts sent for review

• Number of submission accepted: 102 manuscript accepted by editor

• Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): (102/151) x 100 = 67.5 %

• Average number of reviews per paper: Average 2 reviewers of each paper

• Total number of reviewers involved: 45 reviewers

• Any additional info on review process:

– We did plagiarism check for each paper using licenced Turnitin online software. And we accepted the level of plagiarism each manuscript below 20 %.

– The review process was conducted using google form that integrated with conference secretariat email. We sent a review invitation to reviewer by official email of SEACG 2020 and the reviewers conducted review process based on 4 sections:

• Technical Criteria

• Scientific merit of the manuscript: notably scientific rigour, accuracy and correctness.

• Clarity of expression; communication of ideas; readability and discussion of concepts.

• Sufficient discussion of the context of the work, and suitable referencing.

• Quality Criteria

• Originality: Is the work relevant and novel?

• Motivation: Does the problem considered have a sound motivation? All papers should clearly demonstrate the scientific interest of the results.

• Repetition: Have significant parts of the manuscript already been published?

• Length: Is the content of the work of sufficient scientific interest to justify its length?

• Presentation Criteria

• Title: Is it adequate and appropriate for the content of the article?

• Abstract: Does it contain the essential information of the article? Is it complete? Is it suitable for inclusion by itself in an abstracting service?

• Diagrams, figures, tables and captions: Are they essential and clear?

• Text and mathematics: Are they brief but still clear? If you recommend shortening, please suggest what should be omitted.

• Conclusion: Does the paper contain a carefully written conclusion, summarizing what has been learned and why it is interesting and useful?

• Decision

• Reviewer comment

• Suggestion

∘ Ready to publish

∘ Minor correction

∘ Major correction

∘ Reject

– All the comments by reviewers were sent to the author to make the correction and revision within 20 days. The editor will check each revised manuscript carefully and make sure the authors have addressed the questions and comments from reviewer. If the manuscript need to do revision for 2^nd circle, the editor would send it back to the authors.

• Contact person for queries:

Dr. Zulfakriza

Geophysical Engineering Dept.

Faculty of Mining and Petroleum Engineering

Bandung Institute of Technology, Indonesia

zulfakriza@itb.ac.id

On September 26, 2019, an earthquake (Mw 6.5) occurred in the northern part of Ambon Island, Molucca, East Indonesia. The National Authority show this earthquake caused infrastructures damage and 28 fatalities. Up to October 31, 2019, the Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG) seismic network had recorded 479 aftershock events. We have relocated 463 out of the 479 aftershocks using the double-difference method. Our results show that some improvements in the hypocenter locations, where the focal depths of initial earthquakes fixed at 10 km have been updated to ~9.8 km depth on average. There are two aftershock clusters in a North-South direction of ~35 km length between Ambon Island and Haruku Island and in a West-East direction of ~30 km length in the Ambon Island, each with a width of ~8 km.

Earthquake swarms commonly come approximately active tectonic and volcanic area. Interestingly, the swarm events occurred ~23 km southwest from Mt. Salak-Bogor, West Java, Indonesia, from August 10 to November 24, 2019, and were recorded by local/regional network of the Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG). Our previous study showed that in this area a destructive M_L 4.6 earthquake with thrust faulting occurred on September 8, 2012. The double-difference method was applied to update the hypocenter locations from the BMKG data. In the time period of ~3.5 months, we relocated 79 swarm events with ~9.4 km depth average for local magnitude (M_L) 2.2 to 4.2. The source mechanism result for selected events shows a strike-slip faulting. Our interpretation is that these swarm events are probably related to stress change due to volcano-tectonic activity.

This study analyses the P wave velocity (Vp) and Vp/Vs based on 3D seismic tomography in West Sumatra. Seismic tomography is a method of reconstructing the image of the subsurface structure of the earth using travel time data. This research uses secondary data obtained from the Incorporated Research Institutions for Seismology (IRIS) from January 2010 to December 2017. The data obtained were 472 earthquake events and 21 seismic stations that recorded the earthquake events. This research consists of are the hypocenter relocation, which will simultaneously renew the 1D velocity model using VELEST software, and tomographic inversion using SIMULPS12 software. The minimum anomaly of Vp/Vs value is around 1.39, while the maximum anomaly Vp/Vs value is around 2.05. The Vp distribution results have low and high Vp/Vs values around Sumatra Fault Zone and Mentawai Fault Zone. Anomaly results from the tomogram of these areas have an association with saturated pressure sedimentary areas and the presence of fractures which will further contribute to earthquake events.

The 1900 km long Great Sumatran Fault is a complex active fault system that is divided into segments that include the Sumani and Sianok segments in a rather densely populated area of the West Sumatra Province. Major earthquakes have occurred in these two segments that include the March 2007 Sumatra earthquake. Mitigating future risks requires a better understanding of these complex segments. To identify the subsurface structures beneath the Sumani and Sianok segments, we are conducting combined geophysical study that include gravity and magnetic. Gravity data were obtained from the published regional Bouguer anomaly map of the area around these two segments. The measurements from which the map was derived were rather sparse. Thus, more detailed magnetic measurements were carried out in this study. Magnetic measurements were also expected to be more sensitive as the predominant rocks in the study area are volcanic as well as other type of intrusive rocks. These gravity and magnetic analyses were complemented by seismicity data that include relocated seismicity data that will enhance the modelling of subsurface structures. Progress of this study will be reported. Challenges and obstacles will also be presented.

Seismic vulnerability index is one of the key factors in mitigation that shows the vulnerability of the soil layer beneath when passed through with a wave, the more vulnerable the soil layer, the more damage it done when an earthquake happens. Seismic vulnerability is calculated using two variables, that is dominant frequencies and amplification that are obtained by analyzing HVSR curve. HVSR are used to determine the dominant frequency by determining the maximum amplification in that area. HVSR curve is obtained by measuring microbemor data in 163 spots with 30 minutes-minimum duration in Cilacap with a portable seismograph. Mierotremor is a natural vibration that is caused by continuous vibration that come from beneath the surface, sometimes mixed up by the vibrabon that is caused by human activities such as pipe-flow, vehicles, etc. Thus, the purposes of this research are to determine which area is more vulnerable than others, based on the seismic vulnerability index, so it could be a reference for regional development to classified is it safe or unsafe to build in that area, remembering Cilacap is one of the most developed Districts in Central Java.

The geographical position of Indonesia, which is flanked by several subduction zones and the presence of active faults in the sea and land make Indonesian territory prone to earthquakes and tsunamis which can result in many deaths and damaged. There are several efforts we can do to minimize the occurrence of earthquakes, including developing earthquake resistant buildings, increasing the ability/capacity of the community, and predicting earthquakes or better known as earthquake precursors. The BMKG Research Centre began conducting research on earthquake prediction using several methods, including the Radon monitoring method. Monitoring of Radon gas concentrations for earthquake precursors has several advantages, including the presence of radioactive gas which is abundant in ground water that has a half-life of 3.2 days. Radon is the result of decay of uranium 278U which is abundant in the earth's crust rock so that when rock friction occurs, the Radon gas can be detached. Based on the results of Radon monitoring at Tadulako and Palolo stations - Southeast Sulawesi province, there was a change in the pattern of radon gas concentration and water level rising up and down drastically and a gradual decrease in ground water temperature before the earthquake on 28 September 2018. In addition to Central Sulawesi, since 2012 the Centre for Research and Development of BMKG has been conducting research to monitor radon gas concentrations in the DI Yogyakarta region precisely in Piyungan and Pundong districts with the aim of monitoring radon gas concentrations in the Opak fault. In 2021, the BMKG Research and Development Centre added a new radon gas monitoring network in the active fault areas of Cimandiri and Lembang in the West Java province. There are 1 station in the Cimandiri fault segment and 2 stations in the Lembang fault section. It is hoped that in the future the results of monitoring can reduce the impact caused by the earthquake disaster in Indonesia.

Sinabung is a volcano located in the Karo Highlands, Karo District, North Sumatra, Indonesia, with the highest peak of 2460 meters mean sea level. Volcanic earthquake is an earthquake that occurs due to volcanic activity. This is caused by the movement of magma upwards in the volcano. This study aims to determine the type of earthquake, hypocenter position and epicenter of volcanic earthquakes in Sinabung volcano in April-July 2016. The principle of this study was carried out by analyzing volcanic earthquake data in Sinabung volcano in April-July 2016. The data is recorded data (seismogram) or in other words is secondary data from Sinabung volcano on 7 seismometer stations namely Sukanalu, Lau Kawar, Sigarang-Garang, Mardinding, Gamber, Sibayak, and Kebayaken stations. Earthquake data in April-July 2016 revealed that there were 24 earthquake events in a period of 3 months which were the results of picking up the P and S waves, where volcanic earthquakes were obtained only in the form of volcanic earthquake type A and type B volcanic earthquake. Sinabung volcano has an earthquake activity that high enough so that the status of Sinabung volcano is still at level III (standby) status. Based on the hypocenter of several VA and VB earthquakes that occurred in April-July 2016, it can be concluded that the distribution of the hypocenter of the volcanic earthquake shows that the maximum depth of the volcanic earthquake is 10.000 meters and the position of the earthquake is spread at the point between Sinabung volcano and Mount Sibayak.

The study on the fore-arc sedimentary basin for hydrocarbon exploration is rare because of the more complicated geological structures, and conventional seismic methods cannot optimally penetrate the rock layers as there are many volcanic and limestone rocks. One of the natural resources potential in the Southern part of the East Java region, especially in Malang and its surrounding areas is the possibility of hydrocarbons in the fore-arc basin, so research is needed to know the existence of these sedimentary basins. The gravity method is one of the geophysical methods used to assess sedimentary basins based on physical parameters of mass density. The aims of this research are to delineate the sedimentary sub-basin, to find out its structure pattern, interpret subsurface geological and basement configuration. The data analysis approach used in this study involves spectral analysis, upward continuation filter, and 3D inverse modeling. The maximum height for the optimum upward continuation filter is 3000 m, which results in regional and residual anomalies. There were five sedimentary sub-basins identified based on residual gravity anomaly, and the gravity anomalies can also detect structure patterns such as basement high, lineament, and fault pattern. The bedrock is supposed as an intermediate igneous rock with a mass density of around 2.7 gr/cc according to the results of 3D inverse modeling. Deposition from bottom to upward is Mandalika, Nampol, and Wonosari Formations and completed by the uppermost are quaternary volcanic rocks. The inversion modeling results show that the Malang and surrounding areas have thick sedimentary rocks covered by volcanic deposits, which is impressive for further investigation to explore the possibility of the hydrocarbon existence in these areas.

Bukittinggi city area is exposed substantial risk of both, close to seismic source line and site amplification due to soft surface sediment / soil layer. The Great Sumateran Fault (GSF) which is crossing this area, notorious as a very active seismic source. Its responsible to some major earthquake in the vicinity of the fault line. Generally, Bukittinggi area is covered by volcanic product as pumiceous tuff. We applied combined array and single station microtremor measurement to characterize near surface sediment in this area. Based on analysis microtremor single station and array using spatial autocorrelation (SPAC) method, weathered surface layer thickness is in the range of 0-108 m with shear wave velocity in the range of 62-190 m/s, while the fresh pumiceous tuff is in the range of 375-629 m/s. The estimation of site amplification in this area which is indicated by mean amplification is in the range of 1-1.95. The high amplification zone is occupies the northernmost area and some area locally in the southern part of Bukittinggi city.

Banda arc is a complex tectonic structure manifests by high seismicity due to the collision of a continent and an intra-oceanic island arc. Using the relocated earthquakes data from ISC-EHB and BMKG catalogues from the time period of 1960 to 2018, we have conducted a spatial and temporal variation of b-value using the Guttenberg-Richter formula in the area. Our results show that the spatial distribution of low b-values located in the south of Ambon Island and southeast of Buru Island. On the other hand, the temporal variation of b-value shows a decrease in the northern part of the Banda sea probably high potential to produce large earthquakes in the future. Therefore, further mitigation is needed to minimize the impact of earthquakes in the area.

The inland seismic activity in Great Sumatran Fault (GSF) has significantly increased over the past several decades after the occurrence of historical large interplate earthquakes along the plate boundary. This condition led to some occurrences of historical intraplate earthquakes along Sumatran fault. To quantitatively examine the physical mechanisms between intraplate earthquakes and interplate earthquakes, we estimated the static coseismic stress changes of Coulomb failure function (ΔCFF) using receiver fault approach from large historical-recorded interplate earthquakes and the increase in tectonic stress rates. We examined this research in the central part of GSF since this zone is assumed to have the most heterogeneous stress field and thus became our focus study area. The cumulative ΔCFF models showed almost all segments in the central part of GSF suffered negative changes (<-0.1 MPa) which assumed to be unlikely to rupture in short time. However, the preliminary analysis of the increase in tectonic stress rate indicated that large intraplate earthquakes occurred on Angkola and Siulak segments were dominantly influenced by the increase in interseismic stress rate just after the series of large subduction earthquake occurrences, apart from the decreased stress changes from those major interplate earthquakes.

Pore pressure estimation is crucial in drilling wells for safety purposes also a very effective method for dealing with drilling accidents. Determination of overpressure is the main foundation in the evaluation to minimize the non-productive time (NPT). Here we present several models to generate pore pressure analysis of well from Jambi Sub-basin, South Sumatera, Indonesia. The model for estimation pore pressure is carried out by 3 methods: Eaton, Yan & Han, and Kan & Swan. Those methods will be compared to gain a more accurate model estimation within the study area. Kan and Swan's model show the best fit for estimation because this method is suitable for the formation of tester like MDT/DST on higher frequency with parameter of C1 = 0.001 and C2 = 0.0003 for Jambi Sub-basin. The velocity data to construct the 3D pore pressure model was also validated with well data using multi-attribute analysis. The multi-attribute analysis used 2 algorithms, namely step-wise regression and probabilistic neural network (PNN). The analysis show that PNN has a better correlation compared to step-wise regression. The analysis shows the overpressure zone depth is ranges from 1700 – 2000m on Gumai Formation with maximum pressure around 6500 psi. The peak of overpressure dominated by Gumai and Talang Akar formation is caused by the loading mechanism because the rate of sedimentation on thick shale sequence is higher than the rate of dewatering on those formations.

The area of Ambon, Maluku is located in the subduction zone in bands where the Australian plate meets the Eurasian plate, thus causing tectonic activities. The Ambon earthquake on 26th September 2019 with 6.5 Magnitude, while the Epicentral coordinates of the earthquake were determined as 3,53° S and 128,39° E and a focal depth of 10 km, according to the Agency for Meteorology Climatology and Geophysics, Indonesia. This earthquake was strongly felt at the biggest shock was felt with intensity VI-VII as unified in Ambon City, while several other areas are reported to have experienced small shaking, such as Intensity V in Masohi, and Intensity IV in Namlea and Namrole. We used a dataset of 24 waveforms of seven sensors, we determine a tabular solution, which have a large moment of 0.4573 x 1019 N-m, the depth is 6 km by minimizing the inversion residual. The method resulting strike and rake fault, with strike: 341.8°; dip; 81.5°; rake: 158.4°, and second nodal plane strike: 75.1°; dip; 68.6°; rake: 9.14°. The mechanisms were compared with those from other agency in agreement. The time decay intervals between mainshocks and significant aftershocks follow Mogi and Utsu's Law but with a relatively faster rate of decay than that of aftershocks in general.

Initial identification on an earthquake record (seismogram) is something that needs to be done precisely and accurately. Moreover, the discovery of a series of unexpected successive earthquake events has caused unpreparedness for the community and related agencies in tackling these events. Determining the arrival time of the P and S waves becomes an important parameter to finding the location of the earthquake source (hypocenter) as well as further information related to the earthquake event. However, manual steps that are currently often used are considered to be less effective, because it requires a lot of time in the process. Continuous Wavelet Transform (CWT) analysis can be a solution for this problem. With further CWT analysis in the form of a scalogram, can help to determine the arrival time of P and S waves automatically (automatic picking) becomes simpler. In addition, further CWT analysis can also be utilized to help identify the sequence of earthquake events (foreshock, mainshock, aftershock) through the resulting scalogram pattern.

Mount Dempo is the highest volcano in South Sumatra, which lies between the Bukit Barisan mountains and Gumai. The mountain located in Dempo Makmur Village, Sub-district of Pagar Alam, Lahat Regency, South Sumatra is located at an altitude of 3173 meters above sea level with coordinates of 4.03 ° S 103.13 °E. Mount Dempo's morphology is formed by pyroclastic deposits consisting of Tuff and Sand rocks. Mount Dempo's vegetation is dominated by Cassia sp. and Camellia sinensis for upper vegetation, while Strobilanthes hamiltoniana and Strophanthus membranifolium dominate the undergrowth. The purpose of this study is to identify geological structures to predict geothermal prospect areas by integrating remote sensing data and TOPEX Gravity Satellite Data. The remote sensing data used in this study is Landsat 8. This data is used to analyze Land Surface Temperature (LST) from a single thermal infrared band, surface emissivity based on Normalization Difference Vegetation Index (NDVI) from the study area and determine structure delineation. Gravity Satellite Data is used to map gravity anomalies in the volcanic complex of Mount Dempo. Gravity data processing produces a high anomaly zone in the northern part of the study area and is predicted as a prospect area because it is assumed to be related to the plutonic body. High density contrast indicates that there is an error in that area. In line with the error, there are several hot springs because the error serves as a pathway for geothermal fluid to rise to the surface. The study believes that with all the facts stated above, the spots which are located in Tanjung Sakti, Mount Dempo district are very prospective to be developed as a geotourism complex, in which could also increase the welfare of the local citizens.

Soil contains lithogenic components as well as anthropogenic components including combustion residues from traffic activities. The high traffic activities in major cities such as Bandung have caused the air pollution level to increase significantly. These activities might also produce significant combustion residues that accumulate, among others, in the topsoils. Compared with lithogenic components in topsoil, the anthropogenic combustion residues might have different magnetic signatures that could be detected by magnetic measurements. In this study, 38 topsoil samples from 19 roadside sampling points in Bandung City were collected and magnetically analysed to map the magnetic signatures due to traffic activities. The samples were measured for magnetic susceptibility using Bartington MS2B Susceptibility Meter and hysteresis parameter analysed from Vibrating Sample Magnetometer (VSM). The results show that the values of mass-specific magnetic susceptibility (χ_LF) vary from 391.20 to 1835.20×10^-8 m³/kg with the average value of 1012.16 × 10^-8 m³/kg while the values of frequency dependent susceptibility (χ_FD%) vary from 0.54% to 4.48% with the average value of 1.9%. The relatively high value of magnetic susceptibility indicates higher concentration of magnetic minerals compared to that of pristine topsoil around Bandung. This is in agreement with similar studies on roadside topsoil elsewhere. The poor correlation between mass-specific magnetic susceptibility and frequency dependent magnetic susceptibility infers that the magnetic minerals are predominantly non superparamagnetic. This finding is supported by magnetic hysteresis parameters showing that the predominant grains are likely to be pseudo-single domain (PSD) if magnetite is assumed to be the predominant magnetic mineral. Similar studies in German and China reported that the predominant magnetic mineral is mixture of single domain to multi domain magnetite.

Regional and residual Separation anomaly is one thing that must do in gravity processing data. It is important before calculating the depth of anomaly by power spectrum. There are several ways to do this, one of them is using 2D Fast Fourier Transform (FFT). 2D FFT will calculate the two-dimensional power of the gravity map (Bouger anomaly) to change the spatial domain into the wavenumber domain. 2D FFT result has no unit because it works in the wavenumber domain. Power spectrum do in wavenumber domain map. Besides that, to make the wavenumber map in the frequency domain, it should be convolved with some filter (high–pass filter) and then inverse to separate the regional and the residual map. The design of the filter matrix depends on the number of the data and the location of anomalies will be enhanced. It will influence the separation result. The best result gets from the trial and error process. 2D FFT is act like Upward Continuation or Polynomial Fitting in the gravity method with the simple process. In this paper, the process fully done in Python. Python is an effective and simple language programming because it has many modules to support the processing and covering the big data. It also gives the flexibility to the researcher to determine the specific location that will be enhanced

Inversion of schlumberger sounding curve is non-linear, and multi-minimum. All linear inversion strategies can produce local optimum, and depend on the initial model. Meanwhile, the non-linear bionic method for inversion problems does not require an initial model, simple, flexible, derivation-free mechanism and can avoid local optimum. One of the new algorithm of the non-linear bionic method for geophysical inversion problem is the Flower Pollination Algorithm (FPA). The FPA is used for the inversion of schlumberger sounding curve. This algorithm was stimulated by the pollination process for blooming plants. The applicability of the present algorithm was tested on synthetic models A-type and KH-type curve. Numerical tests in MATLAB R2013a for the synthetic data and the observed data show that FPA can find the global minimum. For further study, inverted results using the FPA are contrasted with the damped least-square (DLSQR) inversion program, Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO). The outcomes of the comparison reveal that FPA performs better than the DLSQR inversion program, PSO, and GWO.

Tanjung Berikat Coast in Central Bangka, is a part of the Southeast Asian tin belt. We conducted four Ground-Penetrating Radar (GPR) survey lines and 13 hand auger coring to understand sediment deposition and composition. Two similar units were determined from GPR lines BLG 01–BLG 03: Unit A at the top part, reflected by parallel and continuous reflector configuration, weak–strong electromagnetic wave. Underneath Unit A is Unit B, characterized by subparallel configuration, not continuous–chaotic, weak–medium electromagnetic wave. Unit B is absent in BLG 04. We identify another two units from BLG 04 and BLG 03, Unit C, characterized by subparallel reflector configuration, not continuous– chaotic, weak–strong electromagnetic wave. It exhibits distinctive modulating contact with Unit D. Unit D is characterized by chaotic reflector configuration, relatively stronger electromagnetic wave that might be correlated to the granite intrusion Tanjung Klabat. Sediment deposit is composed of fine–coarse sand, consisting mostly of clastic plutonic and clastic biogenic (coral and mollusk fragments), which increase downward. This indicates marine-fluvial influence, which suggests that sea-level changes strongly influence sedimentation process. Unit A from GPR is correlated to these sediment deposits, the other three units might be correlated to weathering of older insitu deposit.

Barakan Sub-basin is assessed as potential basin for hydrocarbon reserves in the eastern region of Indonesia because it is adjacent to Masela block giant gas field. Reservoir rocks in this sub-basin are sandstones from Middle Jurassic (Lower Flamengo Formation) until Oligocene (Adi member Formation). Main sandstone reservoir rocks are knowingly studied to have good porosity in Upper Flamengo, Kopae, Ekmai and Adi member Formations. But, there is no significant study to determine sandstone reservoir distribution that have good porosity quality. Therefore, an integrated method of inversion and rock physics study are needed to determine sandstone reservoir quality. This study uses 2D marine seismic post-stack time migration and 2 wells namely Barakan-1 and Koba-1 wells. Sensitivity analysis with cross-plot of gamma ray log versus acoustic impedance values range of 20-60 API and 9000-42000 (ft/s)*(g/cc) shows a strong correlation of good porosity sandstone to low impedance in Ekmai Formation of both wells. Model based of post-stack inversion reveals sandstone distribution in Ekmai Formation of both wells. Time structure maps of top and bottom horizons in Ekmai Formation indicates Barakan-1 well within anticline height structure and Koba-1 well are deposited in a middle of sub-littoral environment.

Anak Krakatau Volcano is located in the Sunda Strait known for its paroxysmal eruption in 1883. During the January - November 2019 period, seismicity was dominated by types of quakes which indicated the occurrence of magma supply (VA and VB), near-surface volcanic activity (LF, Hybrid, Harmonic Tremors), and volcanic activity above the volcanic surface (eruptions, emission, and continuous tremors). In the period December 2019 - July 2020, there was an increase in the types of quakes near the surface (LF, Hybrid) and the types of quakes on the surface (emission and continuous tremors). Volcanic deformation monitors changes in tilt over the 2019-2020 period associated with pressure releases before, during and after the eruption. The results of GPS data modeling, the shallow pressure source is at a depth of 0.22 km below sea level. Volcanic activity until July 2020 was dominated by activity near and above the volcanic surface associated with the growth of lava domes. The volcanic system of Anak Krakatau is currently an open system, with the potential for eruptions. Strengthening the early warning system for the eruption of Anak Krakatau is important in mitigating efforts and understanding its eruption potential

The Ambon Mw 6.5 earthquake on September 26th, 2019, had contributed to give severe damages and significantly increased seismicity around Ambon Island and surrounding areas. Mainshock was followed by aftershocks with spatial distribution added to the impact of destructions in this region. We investigated aftershocks sequences to reveal the effect of mainshock toward the change in the in-situ stress field, including the possibility of the existing faults reactivation and the generation of aftershocks. We inferred centroid moment tensor (CMT) for significant aftershock events with Mw more than 4.0 using waveform data recorded from October 18th to December 15th, 2019. The aftershock focal mechanism was determined using the Bayesian full-waveform inversion code ISOLA-Obspy. This approach provides the uncertainty of the CMT model parameters. From ten CMT solution we had inferred in three seismic clusters, we found that majority of events have a strike-slip mechanism. Four events located on the south of the N-S trendings have a dextral strike-slip fault type, reflected the rupture of the mainshocks fault plane. Three events in the cluster of Ambon Island are dextral strike-slip, confirming the presence of the fault reactivation. Meanwhile, three CMT solutions in the north show the dextral strike-slip faulting and may belong to the mainshock main fault, connected with the cluster in the south.

The island of Ambon lies on complex tectonics, part of Banda Arc which is driven by the Australia – Eurasia collision. Historical earthquake data show that an earthquake resulting the greatest tsunami in Indonesia had occurred at Ambon Island. On 26 September 2019, Ambon was shaken by an M 6.5 earthquake at a depth of 10 km (BMKG). In this study, we use ambient noise data from 11 temporary stations deployed by ITB and 4 permanent stations owned BMKG which are recorded from October until December 2019. Here, we purely use the vertical component of seismogram to retrieve the Empirical Green's Function of Rayleigh waves. Cross-correlations were obtained from the daily data series and stacked the day-by-day cross-correlation data into one inter-station cross-correlation. The Empirical Green's Function is seen at the band period 1-15 s. As a part of our study, we analyze the Green's Function with frequency-time analysis (FTAN) to get Rayleigh wave group velocity. The group velocity of Rayleigh waves varies from 1.04 km/s – 3.75 km/s. Low group velocity might be indicated the presence of sediment or volcanic deposits and high group velocity might be indicated metamorphic rocks. The result of this study might give a finer velocity model of the shallow crustal beneath Ambon Island and the surrounding area.

Being located on the Pacific Ring of Fire and a tectonically active country, Indonesia has to cope with the constant risk of volcanic eruptions, earthquakes, floods and landslides. Landslides and other mass movements are serious geo-environmental hazards in Indonesia. Following report from the Indonesia National Disaster Management Authority (BNPB), landslides are among high disaster death toll throughout the archipelago. It claimed 248 lives last year alone. The number of landslides in Indonesia increase steadily to 376 in 2014 from 291 in 2012. Hence, landslide monitoring system is required to determine style of landslide movement, for risk and even emergency risk management assessments and to assist with the design of mitigation works. A landslide instrumentation program including an inclinometer is designed for landslide monitoring. The inclinometer, or tilt sensor, is an instrument used for measuring slope, tilt, or inclination. In this paper we use Micro Electromechanical System (MEMS) as a sensor to measure changes in an angle. Then information is transferred to a central server soon after real-time accelerations are monitored. A data logger also used as a data recording. With low-cost MEMS accelerometers, the results show this instrument is able to provide reliable ground-motion data in network-scale deployments.

In the last few years BMKG (Agency for Meteorology Climatology and Geophysics) has increased the number of seismic stations significantly. Until mid-2020, when this study was conducted, the number of BMKG stations has reached 339 units. Development of the network is aimed to improve the data quality, speed of earthquake data processing and information dissemination to the public, accuracy of the hypocenter, as well as the magnitude. The objective of this study is to identify the site characteristics of the network. We analysed the noise recorded at BMKG stations throughout Indonesia using the HVSR (Horizontal to Vertical Spectral Ratio) method. The results of HVSR analysis were used to classify the site conditions of each station. We got the number of stations with the classification of hard rock, rock, hard soil, medium soil, and soft soil, 47, 57, 52, 30, and 84, respectively. This site condition represents the stations characteristics and affects the quality of seismic waveform data.

Molucca Sea collision zone is a region which has very complex geology and tectonic setting, producing high seismicity and volcanoes activities. In this study, we have determined hypocenter location around the region using local & regional network of Agency of Meteorology, Climatology, and Geophysics, Indonesia (BMKG). We used 1,647 events that recorded by 32 seismic stations. We repicked the P-and S-phase manually and have been succesfully determined ~17,628 P and ~17,628 S arrival times. The P- and S-arrival times are used to determine the hypocenter location by applying NonLinLoc method which estimating the probability density function (PDF) using the oct-tree importance sampling algorithm. Our preliminary results show that the seismicity beneath the Molucca Sea collision zone forming a double subduction pattern which is dipping westward under the Sangihe Arc, reaching a depth of ~ 600 km and eastward under the Halmahera Arc, reaching a depth of ~ 250 km. The seismicity pattern under the Sangihe Arc deepens to the north and the deep earthquake events increase in number. The seismicity is related to the Molucca Sea Plate which is dipping into west and east direction beneath Sangihe-Halmahera Arc. To have a further understanding of the complex tectonic activity in this area, our future work will focus on conducting a seismic tomographic inversion to determine the 3D seismic velocities structure around the Molucca Sea collision zone.

A three-dimensional geomagnetic modeling is proposed to obtain information about a magnetization over topographic area from magnetic total force from land data survey. The model is divided into three-dimensional mesh grid of rectangular prisms that cover a finite depth below topographic elevation. The model parameter is assigned to each prism describing magnetization. A set of linear equations was formulated in terms of volume magnetization for each prism. The inverse calculation is obtained using the solution of over-determined problems. In this inverse calculation over three-dimensional mesh grid, the weighted matrix will be used to determine distribution of volume magnetization in the subsurface and keep the zero value of volume magnetization above the surface. A computer program has been tested with artificial topographic data and applied to digital elevation model of Bandung. The result of the inversion shows the comparison between synthetic model and inverse model to provide several analysis of algorithm performance. The high magnetization value can be characterize using inverse model up to 77% of volume area with average success recovery of model parameter value up to 56%.

The complexity of the pore shape in carbonate rocks causes the need for a special strategy to characterize carbonate reservoir. The more information used, the more accurate the reservoir characterization will be. Pore type analysis is the important study because it relates to the fluid flow properties. The elastic property modeling show a good match to the actual data. The results of the well log and petrophysical data analysis show that the gas zone is located at the upper side of Kujung I Formation. Based on rock physics modeling result, the possible pore type developing in the Kujung I Formation is reference pore with the dominance of the aspect ratio value of about 0.17-0.19. The carbonate layer containing hydrocarbons is characterized by low Lamda-Rho, Lamda/Mu values and a low Poisson ratio. Porous carbonate layer, characterized by a low Mu-Rho value. The slice results show that the gaseous area is located on the anticline. The zone that has good porosity indicated by low Mu-Rho. In the IN-3 well there are no hydrocarbons, this analysis is in accordance with the geological condition of the IN-3 well which is in a low area on the time structure map. The inversion results show a good match between CPEI against water saturation log and CPEI against porosity log.

On November 15, 2014, and November 14, 2019, two major earthquakes occurred in the Molucca Sea with a moment magnitude of Mw 7.0 and Mw 7.1, respectively. These earthquakes were caused by the convergence activity between the Sunda Plate and the Philippine Sea Plate which form a double subduction zone in the Molucca Sea. We carried out the moment tensor inversion using Kiwi Tools to analyze the source mechanism for both of the earthquakes. The results show a thrust fault mechanism with the strike, dip, and rake of the ruptured fault planes are 187°, 63°, 85° and 196°, 43°, 83°, for the first and second events, respectively. We refine the location of the two mainshocks and their aftershocks by performing hypocenter relocation using the double difference method. This resulted in NE-SW aftershocks distribution for both events which occured close to the Molucca Sea Plate boundaries with the mainshocks location are relatively close to each other (± 50.32 km). Finally, we calculate the Coulomb stress changes to analyze the triggering effect between the two major events and between the mainshock and its aftershocks for each event. The results show that the hypocenter of the November 14, 2019 earthquake is in the increased zone of Coulomb stress changes produced by the November 15, 2014 earthquake with the value of 1.2 bar. The aftershocks of both events also occurred in the increased Coulomb stress changes with the range value of 0.5 - 1.8 bar for the first event and 0.2 - 0.8 bar for the second event.

The earth's lithospheric magnetic field is part of the main earth's magnetic field. The lithospheric field has a very small value compared to the Earth's main magnetic field, approximately less than 1%, and this field is generated at the earth's crust and upper mantle. Modelling of lithospheric field is useful mainly for predicting the distribution of the value of lithospheric fields and to determine the magnetic anomaly. In this research, modelling the Earth's lithospheric magnetic field uses Spherical Cap Harmonic Analysis (SCHA) method and this method can do modelling using regional magnetic data. The data used for the modelling are magnetic repeat station data in Indonesia region (BMKG's Epoch) and SWARM satellite data. The results of the modelling using integrated SWARM satellite and repeat station data produce RMSE values of 64.0834 nT and the expansion of index K is 70. In addition, the results of the modelling resolution is 1.5⁰. The value's range of modelling's result are -987.192 – 998.239 nT for X component, -968.189 – 949.438 nT for Y component, -981.266 – 608.676 nT for Z component, and -904.151 – 997.389 nT for total intensity are.

The north arm of Sulawesi has a fairly high level of seismicity. The North Sulawesi arm is bounded in the south by the Palu-Koro Fault, the northern part is bounded by the North Sulawesi Trench and the Molluca Sea Thrust in the east. Therefore, this study aims to analyze the characteristic of the 2010-2020 earthquakes in the north arm of Sulawesi by analyzing the earthquake's focal mechanism and mapping the b-value using the maximum likelihood method. From this study, we obtained the focal mechanism consist of thrust and strike-slip, this is due to the activity of faults and subduction zones in the North arm of Sulawesi such as the Palu-koro fault, the Gorontalo Fault, North Sulawesi Trench, Molucca Sea Collision, and several other faults that affect the seismicity of this region. The variation of the b-value ranging from 0.5-1.1 These studies indicate that thrust fault regions have lower b-values, while strike-slip fault regions have intermediate b-values. Meanwhile, areas with active volcanoes tend to have high b-values. The results of this research can be used as a basis for decision making related to earthquake mitigation in this area in the future.

On September 25th, 2019, an Mw 6.5 earthquake occurred in Ambon, Maluku Province, Indonesia, and caused casualties and infrastructures damages. The epicenter located in a tectonically active region with the potential strike-slip and thrust faulting earthquake sources, yet the responsible fault is still not well understood. Based on focal mechanism solutions from available seismological agencies, i.e. USGS, GFZ, GCMT, and BMKG, the earthquake has a similar strike-slip focal mechanism, although there are discrepancies on detailed source parameters. To provide a better understanding of the earthquake mechanism and seismotectonic, we apply the Cut-and-Paste (CAP) focal mechanism inversion method to broadband seismic waveforms from regional and teleseismic distances. The CAP inversion results on the regional data grouped in different distance ranges show a robust strike-slip solution. We then refine the earthquake focal depth by performing the CAPtele inversion and resulted in a depth of 12 km with similar fault plane solution as the regionals. The ruptured fault plane is resolved by a directivity analysis using azimuthal pattern of the apparent source durations, which indicates an obvious unilateral rupture propagation toward SSE direction. Our result suggests the NNW-SSE orientated fault is the ruptured fault plane, which is also consistent with the near N-S distributed aftershocks. This fault is located in a narrow sea between Seram, Ambon and Haruku island and was not reported yet in previous studies. The Coulomb failure stress (CFS) changes analysis of the mainshock shows that the Ambon earthquake has promoted the off-fault aftershocks which occurred to the west of the ruptured fault.

On September 28, 2018, the Palu-Koro fault released the accumulated stress that caused the earthquake. An earthquake with magnitude 7.5 caused large and massive damage around Palu. There were many aftershocks along the Palu-Koro fault. This research aims to calculate a model of spatial Coulomb stress based on this event to find a correlation between mainshock and the aftershocks. The slip distribution was used as an input of the spatial stress Coulomb modeling to increase the accuracy. We use the Teleseismic Body-Wave Inversion method to calculate slip distribution along the fault plane. As a result, this earthquake was generated by the Palu-Koro fault movement with Mw 7.48, strike 350°, dip angle 67°, and rake -9°. There are three asperity zones along the fault plane located in the north and southern parts of the fault plane. The location of the most energy discharge is in the south asperity zone of the fault plane model with a maximum slip value of 1.65 meters. The spatial Coulomb stress change of this event shows that aftershocks concentration are in areas experiencing increased stress after the earthquake.

The development of population and development activities in big cities in Indonesia, especially in the city of Jakarta and surrounding areas is very rapid. From several land subsidence studies, several factors have been identified that cause land subsidence, namely: excessive groundwater extraction, reduction due to building/infrastructure loads, subsidence due to natural consolidation of soft soil layers, and subsidence due to tectonic forces. At present the exploitation of ground water for industrial and residential needs is at a level that needs attention. Excessive pumping of groundwater will cause a decrease in the quantity of ground water, entry of seawater into the land (sea water intrusion) and land subsidence. Symptoms of the negative impact of land subsidence have been felt in several areas, especially in industrial areas located in the northern part of Jakarta. This land subsidence can be measured by GPS or satellite geodetic method, which have begun to develop in Indonesia in the past two decades. Measurements were made using the radial method at 53 GPS points in 2015 up to 100 measurement points in 2019 in Jakarta Groundwater Basin. The result of these campaign GPS surveys that is northern part of Jakarta relatively had higher subsidence rate than the southern. The largest subsidence almost reached 6.2 cm/year in Muara Baru in northern area which is southern area only suffered an average rate of 1.16 cm/year.

Indonesia has a high level of seismic vulnerability because located in the junction area of four large plates, namely the Eurasian plate, Indo-Australian plate, Pacific plate, and Philippine Plate, and also the number of active faults that stretch throughout its regions. One of the efforts to mitigate earthquake disasters is to conduct seismic hazard microzonation efforts. The Research and Development Center of BMKG has carried out ongoing research in the field of seismic microzonation to obtain information on the level of seismic hazard in some regions based on microtremor parameter values, including in the Sukabumi (2009), Bantul (2010), Padang (2011), Cilacap (2012), Kulonprogo (2014), Tasikmalaya (2017), Garut (2018) and Pangandaran (2019). This study tries to prototype the seismic microzonation information system in a web-based spatial information system called InaSMIS (Indonesia Seismic Microzonation Information System). InaSIMS contains information about the analysis of microtremor survey results, including the value of the dominant period (T0), Ground Shear Strain (GSS), and USGS Vs30, which states the level of seismic hazard in an area. InaSMIS is still being developed in the research stage and is not yet an operational service for BMKG. In the future, InaSMIS expected to be a source of public information to determine seismic hazards in Indonesian regions.

Prospective reservoirs in the Tarakan Basin are mostly deposited in the Middle Miocene to Pliocene and related to the change of depositional environment from transgressive to regressive sedimentary environment. Log sequence stratigraphic analysis in well AST 1 shows that transgressive and lowstand system tracts were deposited during the study area. Hashin-Shtrikman method is used in the rock physics analysis to identify the relative rock hardness and integrated with gamma ray log, NPHI, and resistivity data analysis. The result show that potential reservoir exist at the depth range of 7650-7725 feets and associates with low velocity, low gamma ray, low NPHI, high resistivity values. The potential reservoir interval was deposited under low stand system tract of slope depositional environment. The acoustic impedance (AI) map shows that the low AI's are mostly located in the northwestern part of the study area.

The Tarakan Basin is one hydrocarbon basin in Indonesia with approximately 40 discoveries and more than 1000 MBOE reserves. This study discusses an approach to integrate the sequence stratigraphy, rock physics and acoustic impedance (AI) inversion analysis to determine the prospective reservoirs in the basin. PRG-1 well data is used in the sequence stratigraphy and rock physic analysis. The sequence stratigraphy analysis of PRG-1 shows that there are three system tracts: transgressive, low stand tract and high stand system tracts. The integration of sequence stratigraphy, rock physics and log data analysis show that the prospective reservoir interval in PRG-1 well is located at a depth of 4730-4780 feet. It is characterized by low gamma ray, low NPHI, low density and high resistivity. The prospective interval was deposited in early Pliocene as Tarakan Formation in the low stand system tract of shelf depositional environment. The AI map shows that the distribution of the prospective is around the PRG-1 and in the eastern part of the area.

The seismic far-offset data plays important role in seismic subsurface imaging and reservoir parameters derivation, however, it is often distorted by the hockey stick effect due to improper correction of the Vertical Transverse Isotropy (VTI) during the seismic velocity analysis. The anisotropy parameter η is needed to properly correct the VTI effect. The anisotropy parameters of ε and δ obtained from log and core measurements, can be used to estimate the η values, however, the upscaling effects due to the different frequencies of the wave sources used in the measurements must be carefully taken into account. The objective is to get better understanding on the proper uses of anisotropy parameters in the the velocity analysis of deepwater seismic gather data. To achieve the objective, the anisotropy parameters from ultrasonic core measurements and dipole sonic log were used to model the seismic CDP gathers. The upscaling effects is reflected by the big difference of measured anisotropy values, in which the core measurement value is about 40 times higher than the log measurement value. The CDP gathers modelling results show that, due to the upscaling effect, the log and core-based models show significant differences of far-offset amplitude and hockey sticks responses. The differences can be minimized by scaling-down the log anisotropy values to core anisotropy values by using equations established from core – log anisotropy values cross-plot. The study emphasizes the importances of integrating anisotropy parameters from core and log data to minimize the upscaling effect to get the best η for the VTI correction in seismic velocity analysis.

We conducted a study using the magnetotelluric method in the Kutai Basin, which is one of the largest and deepest tertiary sedimentary basin located in the province of East Kalimantan, Indonesia. The Kutai Basin, which is one of the sedimentary basin that is proven to produce hydrocarbons in Indonesia, also has the potential for shale gas with all the complexities of its geological structure. Inversion of 2-D MT can generally be done in three modes with different sensitivity. We perform data processing objectively to obtain the best quality data. We continued our data processing to the inversion process with a range from 80.78% to 97.09% coherency data. We also performed sensitivity skewness calculations to determine the dimensionality of our data. The map of sensitivity skewness is shown for the vertical path A – A' with direction N – S in our study area. Based on the calculation results, the skewness value below 0.3 is obtained around the frequency 320 - 0.002 Hz, and associated with the 2-D structure while value above 0.3 are obtained around the frequency 0.00198 - 0.00034 Hz at KT34 and KT36 stations. Based on dimensionality calculations, it is concluded that the MT data in the Kutai Basin is dominated by 2-D structural responses, so that the TE + TM (invariant) mode is the best measurement mode for inversion modeling. We also performed calculations to obtain the optimum smoothness factor (tau) using a trade-off curve. Based on the results of the inversion with the optimization of these data parameters, we obtained a subsurface geological structure pattern such as fault and fold structure along the vertical path of A – A'. The low resistivity anomaly is interpreted as a response to the presence of black shale which is part of the Pamaluan Formation. The top of the Pamaluan Formation is estimated at the depth that varies from 2000m to 4000m below the surface along the A – A' vertical cross-section.

A simple design for modeling shallow subsurface density redistribution due to land subsidence is designed to obtain the time-lapse microgravity response. The subsurface model at each point of gravity observation is represented by a rectangular prism. A numerical example of computational modeling is performed to estimate the effect of land subsidence to the data of a time-lapse microgravity. Simple numerical simulations with an initial model that have flat topography, homogeneous density, and homogeneous compaction thickness are carried out in variations of geological and hydrological information that are often found in a study area. Additional algorithms to accommodate information on topographic variations, density variations, and compaction thickness variations in the horizontal direction also shown with illustration. Field data application for this study utilize rough estimation of the geology and the land subsidence rate in Bandung Basin. The estimation results with numerical simulations give time-lapse microgravity anomaly 0.78 to 28.61 μGal/m and field data application give an anomaly up to 10 μGal.

In recent years, siltation has become quite a problem. It has been the main cause of flooding and a rapid decline in water quality. It is usually caused by a high river sedimentation rate and/or uncontrolled waste disposal. The increased rate of erosion also means that river sedimentation occurs faster than normal and could lead to environmental hazards, wildlife deaths, and the disruption of food and drinking water supply among other things. The question is how to monitor the sedimentation process of rivers without damaging the river itself. The suitable geophysical method is GPR. GPR is an active, non-intrusive geophysical method in which electromagnetic radiation and the reflected signals in the form of radar pulses are used for subsurface imaging. The objective is to investigate river sedimentation using GPR, we created the synthetic models based on geological models of rivers with different depths to create their 2-D radargrams to predict the actual model. We set up the first model RSM-I as control which consists of a layer of freshwater with ρ = 16 Ωm, k = 81 and μ_r = 1 of depth 5 m, two layers of sandstone with ρ = 850 Ωm, k = 2.5 and μ_r = 1 of total depth 4 m, and a layer of claystone with ρ = 120 Ωm, k = 11 and μ_r = 1 of depth 1 m. RSM-II and III are added with a buildup of saturated sediment with ρ = 30 Ωm, k = 15, and μ_r = 1 of depth 2.5 and 4 m, respectively. The radargrams' reflector for each model shows a two-way travel time of 300-350, 150-200, and 60-90 ns in their respective order. GPR models can differentiate between the saturated sediment and freshwater, it shows good results regarding sediment investigation in rivers.

This paper aims to identify the oil distribution using 4-D seismic below a complex 3-D surface in Hugin Formation using machine learning and geobody detection. The exploration well 15/9-19-SR, drilled to the Theta Vest structure, was based on the interpretation of reprocessed ST8215R 3-D seismic survey data from 1991 in the Sleipner area, encountered oil in the Jurassic Hugin Formation. The drills stem test showed outstanding production capacities through time, with low water cut and low GOR. 4-D seismic has all the traditional benefits of 3-D seismic. A significant additional potential benefit is that fluid-flow processes can be directly imaged. The 4-D seismic analysis was conducted in 2012 to repeat the 3-D seismic surveys and analyze images in time-lapse mode to monitor time-varying fluid-flow processes during reservoir production. A comprehensive study of the structure and the discovery has been performed and is reported. The DNN method to predict facies far away from existing production wells by using facies log well to supervise seismic inversion created by the Seismic Color Inversion method. It can detect some oil pockets distribution and risk the well planning and the right candidate for new proposed wells.

During the last one hundred years, there are no shallow seismicity in the north of Java. This area is dominated by intermediate and deep focus earthquakes due to the subducted Indo-Australian slab. An earthquake with magnitude M_L 4.5 struck Indramayu, north of West Java on August 1, 2020. According to the Agency for Meteorology, Climatology, and Geophysics (BMKG), the earthquake was felt III MMI scale in Indramayu and its vicinity. We used waveform data from BMKG seismic station in West Java, then we picked P-and S-waves arrival times from each station and hypocenter location was determined by Geiger method. We have detected Pn before Pg phase on four BMKG seismic stations, indicating a shallow crustal earthquake. Our inversion show that the earthquake occurred in 6.1805° S, 108.2612° E with 5 km focus depth at 16:24:38 GMT+7. Our focal mechanism solution was determined by using moment tensor inversion shows a strike-slip faulting, which corresponds to the active fault in the north of Indramayu.

Gedebage district is presently experiencing rapid and mass infrastructure development and becoming one of the developed districts in Bandung, Indonesia. A football stadium, several luxury housing, the grand mosque of West Java province, and a business center have been built in this district. However, it is well known that the Gedebage district has turned into one of the Bandung districts that suffers from land subsidence phenomena. Since 2000, the Gedebage district has suffered land subsidence at an average rate of 10 cm per year and becoming one of the fastest sinking districts in Bandung. This fast land subsidence phenomenon is suspected of affecting the infrastructure in this district. Therefore, this work aims to capture the current subsidence rate in the Gedebage district using the geodetic approach of the combination of the Global Navigation Satellite System (GNSS) with Interferometric Synthetic Aperture Radar (InSAR) and investigate the impact of land subsidence on infrastructures in Gedebage district. We use GNSS campaign datasets from the years 2016 and 2019. Each GNSS campaign was performed at least 10-12 hours of observations. We also utilize a similar period of 2016 to 2019 for the InSAR datasets. Utilizing both GNSS and InSAR datasets, we can capture the subsidence with the rate reaching 4 -15 cm per year between 2016 and 2019, and it occurs uniformly in this district. The impact of land subsidence occurred in almost all urban areas in the Gedebage district. These impacts include cracks in buildings, bridges and roads, and also tilted buildings.

To use the Global Navigation Satellite System (GNSS) correctly, the height information should be transformed into orthometric height by subtracting geoid undulation from it. This orthometric height is commonly used for practical purposes. In 2015 geoid of Jakarta has been produced, and it has an accuracy of 0.076 m. In the year 2019, airborne gravimetry has been done for the entire Java Island. The area of DKI Province cannot be measured because there is inhibition from Airnav. For this reason, terrestrial gravimetric measurements are carried out in this region by adding points outside the previously measured area. To compute the geoid in the Jakarta region is needed the Global Geopotential Model (GGM). In this paper, the GMM used is gif48. The "remove and restore" method will be used in calculating the geoid in this Jakarta region. Besides that in this geoid calculation also uses Stokes kernel and FFT to speed up the calculation. The verification of the resulting geoid is carried with 11 points in DKI Jakarta Province. This verification produces a standard deviation of 0.116 m and a root mean square of 0.411 m.

The Lombok region is located around a complex tectonic zone with an Indo-Australian oceanic crust transition zone with Australian continental crust in the west and Sundanese arc in the east. This complexity makes some area in West Nusa Tenggara have a high level of earthquake vulnerability and to determine the potential level of seismic damage risk this study was conducted by analyzing Peak Ground Acceleration (PGA) and Peak Ground Velocity (PGV) using earthquake data since 2000 - March 2020 with an intensity more than M4.5. Earthquake data are analyzed using the Yin-Min Yu formula to get the relationship between Peak Ground Acceleration (PGA), Peak Ground Velocity (PGV), and earthquake intensity, so areas with risk level of earthquake damage can be mapped as preliminary earthquake mitigation schemes. The results of the study show that the highest PGA value in West Nusa Tenggara is 74.73 gal at the bedrock and when it on the surface, the PGA value can increase due to amplification of local soil conditions. Likewise PGV value about 32.21 gal where this maximum value is located in East Lombok Regency and North Lombok Regency. According to the classification of PGA and PGV values, the study area has a potential high-risk level of earthquake damage.

In an open channel flow, the characteristics of flow resistance are greatly affected by the roughness of the base and the walls of the channel. The existence of an object or other material, including gravel, also influenced the resistance of flow, therefore the purpose of this study is to examine the flow characteristics (flow velocity and flow resistance) in gravel open channel by using experimental study. A laboratory study to explore the effect of channel bed in terms of roughness of types of sediment on the hydraulics flow in 8 m length x 40 cm width a rectangular channel is presented. The study consists of an extensive set of rectangular flume experiments for flows with certain slope and sediment bed. The study was using the Before After Control Impact (BACI) method by set up five different scenarios. The results show that the lowest flow velocity (v=0.3041 m/sec) was occurred in the scenario 3 (50%sand and 50% gravel). Based on the Manning' coefficient (n), it was also found that at the 100% discharge flow condition, the highest value of friction factor (f=0.0780) within 5 scenarios was scenario 3 with the sediment consisted of 50%sand and 50%gravel. Whereas the value of the lowest friction factor(f=0.0652) was scenario 1 with the sediment only gravel within. It concluded that the results gave the lower value of Manning' coefficient (n) compared to the table of Manning's coefficient (f= 0.04) for the channel with gravel base condition.

The province of West Papua in Indonesia is an area crossed by three major faults, including Sorong, Koor, and Ransiki, leading to the collision of Australia, the Pacific, and Eurasia. In the past, there have been strong and damaging earthquakes on these faults, manly Ransiki fault in the South Manokwari regency. Identification of the Ransiki fault segment was conducted by geological subsurface modeling using the earth gravity field of the Global Gravity Map (GGM) based on satellite measurements implicates for earthquake source parameters. The GGM is seen as a solution for the unavailability of direct measurements in the region. The gravity field analysis begins with data reduction using SRTM2gravity as modern terrain correction to obtain a complete Bouguer anomaly. Furthermore, the gravity gradient approach through vertical and horizontal gradients, analytical signal, and the tilt angle are applied to emphasize a contact or fault structures that are not visible using a 2D fast Fourier transform. Overall, the gravity gradient analysis obtained results that were compatible with the alignment of the Ransiki fault segment which direction of the northwest to south. The gravity inversion produces a geological subsurface model that clearly shows the Ransiki fault segment, associated with a low rock density distribution, thought to the Befoor formation and quaternary sediments, located between high-density rocks correlated to Arfak volcanic rocks as a basement.

The study of field camp geophysics in Karangsambung has been done since 1996 until 2019 by geophysical engineering ITB. During the field activities, students was assigned with several data acquisition using various geophysical methods. One of the most common method to conducted alongside with surface geological mapping is gravity. Compilation of gravity data during the activities will be presented in this work. There are two categories of data compilation during 24 years: data compilation 1996-2004, and 2005-2019. The observation conducted using relative gravimeter with data distribution already cover geological surface map in the study area (Luk-Ulo Melange Complex, Karangsambung Formation, Totogan Formation, and Diabas Intrusion). The pattern of gravity observation shows correlated with topographic variation. Range gravity observation from this study is about 62 mGal.

The Lower Kutei Basin which contains several giant oil and gas fields is located on the East Kalimantan, Indonesia. This paper discusses the identification and mapping of oil-filled reservoirs and their depositional facies by integrating seismic stratigraphy, attributes, and AI (Acoustic Impedance) inversion methods. The log data cross-plots show that AI can be used to distinguish oil-sands from wet sands and shale, and to derive the total porosity of the sands. However, AI and amplitude values are greatly affected by the oil, porosity and tuning effects, hence they cannot be used to identify the facies containing the oil-bearing sands. Therefore, to map the facies containing the oil-filled sands, the AI map is combined with the variance and sweetness maps. It can be seen clearly from the variance and sweetness maps that the oil-sands suggested by the AI map are contained in a narrow and elongate meander-like geometry which is typical of channel facies. The variance and sweetness maps suggest that there are two channels in the study area. To determine which channel is thicker, spectral decomposition RGB map was made. The result suggests that the right channel is more prospective as it associates with thicker sand deposits. The combination of variance, sweetness and RGB maps strongly indicate that the channels in the study area are in upper-slope environment, and the thicker oil-sands are located in the eastward of the study area.

Kutei Basin has the second largest hydrocarbon reserve in Indonesia. In addition to the Miocene inversion related structural traps, slope-fan and channel stratigraphic traps are also important traps in this basin. To guide stratigraphic traps explorations in the basin, the seismic stratigraphy, attributes, and AI inversion methods are integrated to identify and map the reservoir seismic facies, porosity, and pore-fluid. Well data indicates that the studied reservoirs are filled by gas. Seismic data shows that there are two main gas-sand reservoirs corresponding to strong amplitude anomaly. Seismic stratigraphy analysis, guided by seismic attributes, shows that these gas-sand reservoirs were deposited in the channel and local fan facies. The AI inversion is applied to identify and map the porosity and pore-fluid of these two sand reservoirs. Future well locations are identified by integrating the facies, porosity, and pore-fluid maps.

Baribis Fault is a recently identified active fault known to have thrust movement which located along the northern part of the West Java area. This E-W striking fault runs across high-populated areas, including Cirebon, Indramayu, Sumedang, and Subang area (with a probability of continuing to Jakarta and Banten areas). The last major historical earthquake occurred on November 16th, 1847 around the fault line with a radius of shaking area up to 400 km. The available high-resolution Digital Elevation Model from Geospatial Information Agency, called DEMNAS, has about 7.5-m grid data resolution but still not adequate to be used for identifying fault ruptures of this event. Hence, we conducted an Unmanned Aerial Vehicle (UAV) 3D Photogrammetry survey flown in the lower latitude (~100-m high) in the suspected sites. This study identified clear fault scarp associated with stream-valley offsets indicating strike-slip movement in the Ujung Jaya subdistrict, Sumedang. The trace of fault rupture has a 5±1-meter sinistral offset. This sharp fault deformation feature is possibly related to the 1847 earthquake in this area. This fact is different from regional morphology, which shows that the Baribis Fault is a thrust. Further study is necessary to get more detailed and precise information.

Sulawesi Island crossed by the importance active faults of the Palukoro Fault in the western part and the Matano Fault in the eastern part. Pamsoa Segment, the fourth of six-segments of the Matano Fault (from west to east), located near importance Sorowako mining city, Sulawesi. Pamsoa segment has a 38 km length, oriented N295°E, and has an obvious 475 m sinistral river offset. A reconnaissance survey conduct in this segment along the fault crosses the mining dirt road. Two fault rupture existed on the Holocene river terrace. Accelerated Mass Spectrometry (AMS) carbon dating shows age about 5218 BP and 4446 BP on the soil samples. Nice slicken-side on red soil shows as a fresh fault rupture. This rupture shows a possible two earthquake event on the Pamsoa Segment. The Matano fault has potency similar to the 2018 Palu earthquake. If the fault has similar multi fault rupture earthquake characteristic, the Matano Fault is also classified as a Magnitude 7+ class earthquake. Further research is needed to get precise earthquake geology parameters and ideal charcoal samples.

We studied the February 23rd, 1969 M7.0 Majene, Sulawesi earthquake and tsunami. It was followed by tsunami reported at five locations. At least 64 people were killed and severe damage on infrastructures were reported in Majene region. Based on damage data, we estimated that the maximum intensity of the earthquake was MMI VIII. Focal mechanisms, derived using first motion polarity analysis, indicated that the earthquake had a thrust mechanism. Furthermore, we built hypothetical earthquake scenarios based on a rectangular fault plane of 40 km × 20 km with a homogeneous slip model of 1.5 m. We run the Open Quake and the JAGURS code to validate the macroseismic and tsunami observation data, respectively. Our best-fitted earthquake model generates maximum intensity of 8+ which is in line with the reported macroseismic data. However, the maximum simulated tsunami height from all scenario earthquakes is 2.25 m which is smaller than the 4 m tsunami height observed at Pelattoang. The possibility of contribution of another mechanism to tsunami generation requires further investigation.

The receiver function method is a method to image the earth subsurface by utilizing Ps conversion waves that are formed due to the velocity boundary. In general, the receiver function method estimates depth of structures such as the mantle-crust boundary by deconvoluting the vertical component from the horizontal component. Typical receiver function data processing is done in the frequency domain where the deconvolution process can be seen as a division between two components. In this study, we tried to reprocess the data using a deconvolution technique in time domain, popularly known as iterative time-domain deconvolution. The principle of iterative time domain deconvolution consists of iterative cross-correlation between the horizontal and vertical component. We use data from the DOMERAPI seismic station network located in the vicinity of Mt Merapi and Mt Merbabu. Mt Merapi is one of the most active volcanoes in the world with frequent eruptions and located at the ring of fire chain volcano in Indonesia. Note that the previous receiver function study in this region showed complex signals at some stations that may be related to sediment at shallow sediment and possible layers of low velocity zone that interfering main signal for a crust-mantle boundary. Our current results show iterative time domain RFs have clearer and smoother signal than the frequency domain that help interpreting the waveform signals. We estimate a range of crust thickness between 26-31 km near Mt Merapi. However, we noticed that iterative time domain calculation requires longer computation time and input signal.

The tectonic setting of Java island, located at southwestern edge of the Eurasia continent, is dominated by the subduction of Indo-Australia plate. One of the characteristics of active subduction is active seismicity, the generation of arc magmatism and volcanic activity. Mt. Merapi is one example of active volcano related with the subduction process. It is one of the most active volcanoes with location close to high population area. To better understand this area, we employed the Receiver Function technique, a method to image sub surface structure by removing the vertical component from horizontal component. First, we collected high magnitude events and processed RF with water level deconvolution method. Then, we constructed synthetic model with initial velocity input from previous tomography model. Note that we used reflectivity method in generating synthetic model with input parameters matched with parameters from real data processing. Next, we adjusted velocity inputs mainly on tops sediments (1-3 km) to include sediment layers and volcanic rocks, mid-depth low velocity zone that may be related with magma chamber and depth of crust-mantle boundary. Current forward velocity models show a relatively good agreement from 3 stations (ME25, ME32 and ME36). We estimate a thin layer of sediments followed a zone of velocity layer at a depth of 10-15 km and crust-mantle boundary ranging from 26-29 km. In this study, simulated that the signal of sediments layer and low velocity layers interfere main crust mantle boundary that supposed to be highest signal after the P wave in the typical receiver function study.

Our study area is located near island Sumbawa, Sumba, Flores, West Timor, Indonesia and East Timor, popularly known as Sunda-Banda arc transition zone. The tectonic setting is mainly controlled by the movement of the oceanic lithosphere Indo-Australian plate subducting the Eurasian plate and Northward migration of Australian continental lithosphere into western Banda-arc in the region of Flores, Sumba and Timor island. We tried to image velocity structure beneath these regions using regional events and tomography inversion model. We collected 5 years of regional events from the Indonesian Agency of Meteorology, Climatology and Geophysics. In total, we reserved 3186 events recorded on 29 stations. For data processing, we used fast marching method as ray tracing between sources and receiver. We then employed subspace inversion as the tomography procedure to estimate the best velocity model representing the tectonic model in the region. Hypocenter data distribution is concentrated on shallow parts of the region and along the Benioff zone down to a maximum depth of 400 km. One of challenge of this study is that although events are abundance, the stations used are mostly located onshore and does not extend in the south-north direction that leads us to under determined problem in the inversion process. However, checker-board models show most our target area can be retrieved to its initial model with sign of smearing effects shown start from a depth of 50 km. After six iteration and optimized selection of damping and smoothing parameters, we observed low velocity anomaly under Bali, Lombok, Sumba, East Nusa Tenggara at shallow depth that may be related with volcanic activity. Deeper low anomaly can also be seen that may be related with partial melting process. A band of fast velocity is clearly seen that goes deepen to the north depicting subducting slabs own to a depth of 300 km. We also observed a possible of fast velocity in the northern part of our stations at shallow depth that we believe may represent the back arc thrust.

The tectonic setting of our study area is located between the Island of Java and Timor Leste. The complexity of this region is started with two different plates, The Indo-Australian plate and the Eurasian plate that move with different orientations and convergence rate. This area also shows active seismic activity and has a series of active volcanoes as a product of subduction and collision. To deepen understand this area, we perform delay time tomography using FMTOMO package that includes 3-D finite-difference based ray tracing and sub-space inversion procedure. We used two different sets of data, the first one is 4 years data catalog from the Indonesian Agency of Meteorology, Climatology and Geophysics, and the second one is 47 years of data from the International Seismological Centre. Data from the local Indonesian show agency shows a fewer number of events but more focus clusters. Meanwhile, the data from ISC catalog has more events and evenly distributed data. However, we also noticed that data from ISC has cluster events located at the same depth that can be improved with events relocation for better depth estimation. The Checkerboard models from both data set show a comparable result, though data from ISC show a better recovered model at a deeper depth and shallow part in the eastern area. The checkerboard from the local Agency shows slightly better results in the shallow part. Next, we invert delay time for each data set using we optimized damping and smoothing parameters. Final tomogram models show that data from the local Agency show a more continuous fast velocity band representing a downgoing subducting slab and possible back-arc thrust while results from the ISC data show a more detached fast velocity band that could be contributed from fixed depth problem in the data set. However, we noticed that data from ISC show a higher amplitude low-velocity anomaly especially in the shallow depth

Seismic events detection and phase picking play an essential role in earthquake studies. Typical event detection is done visually or manually on recorded seismogram by choosing a series of higher amplitude signals recorded on at least 4 stations. More sophisticated methods have been used in event detection and picking with additional attributes such as Short Time Average over Long Time Average (STA/LTA). This method is based on average number sampled at multiple predefined windows. However, STA/LTA is dependent on the window size which becomes its drawback. In this study, we explore one derivative attribute, popularly known as envelope or instantaneous amplitude. It has been extensively used in seismic reflection and refraction method. In principle, this method uses the Hilbert Transform to calculate complex seismic trace and take the magnitude of complex seismic trace as envelope amplitude that can be used to analyze P wave arrival time. We employed one of the machine learning methods, Artificial Neural Network (ANN). The ANN method works by analyzing various inputs and training them to recognize patterns in P wave arrival signals. We started our study by applying envelope attribute to synthetic data with noise addition. We found that with noisy data the envelope attribute still gives a clear signal for first-time arrival. Next, we trained 300 seismograms of teleseismic events recorded on IRIS-US networks and tested our trained program on 20 seismograms as a blind test. To compare performance between the two methods, we calculated the difference between the results of automatic picking and manual picking. The final calculation shows an average deviation of 0.355 seconds. Twenty-five percent of testing data (5 samples) has a deviation above 0.5 seconds, and 75% of the remainder (15 samples) already had a deviation under 0.5 seconds. The more significant deviations of the P wave picks are likely due to noisy signals in the data set and complex arrival signals. This study shows that the combination of envelope attribute and machine learning method is promising to distinguish teleseismic P wave arrival and automatically pick them.

The Short Term Averaging/Long Term Averaging (STA/LTA) has been widely used to detect earthquake arrival time. The method simply calculates the ratio of moving average of the waveform amplitude at short and long-time windows. However, although STA/LTA signals can distinguish between real events and noise, we still recognize some lack of accuracies in first P wave arrival pickings. In this study, we attempt to implement one machine learning method popularly, Artificial Neural Network (ANN) that employ input, hidden and output layer similar as human brain works. Note that in this study, we also try to add input parameters with another derivative signal attributes such as Recursive STA/LTA and Carl STA/LTA. The processing step started by collecting event waveforms from the Agency of Meteorology, Climatology and Geophysics. We chose regional events with moment magnitude higher than 3 in the Maluku region Indonesia. Next, we apply all STA/LTA attributes to the input waveforms. We also tested our STA/LTA with synthetic data and additional noise. Further step, we manually picked the arrival of P wave events and used this as the output for ANN. In total, we used 100 events for arrival data training in P wave phases. In the validation process, an accuracy of more than 0.98 can be obtained after 200 iterations. Final outputs showed, that in average, the difference between manual picking and automatic picking from ANN is 0.45 s. We are able to increase the accuracy by band pass filter (0.1 – 3 Hz) all signal and improve the mean into 0.15s difference between manual picking and ANN picks.

The traditional method in determining first arrival time of earthquake dataset is time consuming process due to waveform manual inspection. Additional waveform attributes can help determine events detection. One of the widely used attribute is The Short Term Averaging/Long Term Averaging (STA/LTA) which is simply division moving average of waveform amplitude between short time and longer time. Alternatively, waveform attribute can also be built using kurtosis and skewness. The kurtosis attribute is defined as sharpness of data distribution. By definition, the maximum signal should be at or close to the P wave arrival. The skewness is typically used to show normal distribution of the data. The uniqueness of this method is that it has an ability to determine whether the first P wave arrival has positive of negative number. The skewness calculation is similar to kurtosis but it uses the power of 3 instead of 4. With the objective of generating efficient scheme to pick first time arrival, we explore use artificial neural network and a combination of kurtosis and skewness attributes. We use a collection of magnitude events with moment magnitude larger than 3 located close to Moluccas island, Indonesia. We collected all events information from the Indonesian Agency of Meteorology, Climatology and Geophysics. The process is started with manually pick all P wave arrivals using manual inspection. Next, we trained the artificial neural network with attributes numbers as inputs and arrival time we manually picked as the output. In total we used 100 regional events that has clear P wave phases. Then, we validated the results until reaching 0.99 accuracy. In the last step, we tested the once trained procedures on new waveforms contained events. Current result shows an average of 0.4s different between manual pick and trained picked from machine learning. The accuracy can be improved by applying a band pass 0.1-2 Hz filtering with an average of 0.2s.

Rawa Dano is a caldera lake which resulted from Dano Purba Volcano's massive eruption, and it produced a huge amount of pyroclastic deposits that typically formed complex volcaniclastic series. Due to the lack of information regarding the subsurface properties of Rawa Dano area, therefore in this study, a low-energy seismic refraction survey was carried out to identify the distribution of pyroclastic deposits resulted from intensive volcanic eruptions. The data were acquired from two lines in two different sites. Variations of longitudinal velocity in the seismic vertical cross-section suggest that there are more than one type of deposits existed in the area. The results show two main refractors which are related to the deposition of different facies. The seismic velocity shown in the upper part of the seismic tomography model indicates that the pyroclastic deposit has a great thickness. This finding suggests that the eruptions happened massively. By combining the results from both sites, it could be inferred that the preceding one is even bigger in magnitude. The result is in agreement with the earlier surface geological study, which explains a similar conclusion. This research demonstrates the capability of seismic refraction tomography to map the distribution and condition of volcanic deposits around Rawa Dano Volcanic Complex.

Earthquake parameters such as the hypocenter location and the magnitude size are important in the development of reliable Earthquake Early Warning (EEW) and Tsunami Early Warning System (TEWS). The Global Navigation Satellitte System (GNSS) data have been used to estimate the earthquake parameters rapidly over the last 15 years. In this study, we present the result and analysis of the scaling properties of Peak Ground Displacement (PGD) as measured by high-rate (sampled at 1 Hz or higher) GPS recordings from Lombok earthquake on August 05^th, 2018. The earthquake magnitude from the kinematic solution of CMAT GNSS station is equal to Mw 6.8. This value is achieved between 15 - 20 seconds after the origin time of the earthquake. Our result shows that the displacements from kinematic GNSS data can be used to rapidly determine the earthquake magnitude, typically within the first minute of rupture initiation. Rapid earthquake magnitude determination will be very useful to support EEW and TEWS.

The tectonic setting of Java Island is mainly controlled by the collision of Indo-Australian plate subducting the Eurasian plate. The high collision activity of Eurasian and Indo-Australian plates often causes megathrust earthquakes and the rise of arc magmatism that includes volcanic eruption. This study aims to determine the tectonic pattern beneath Central Java based on P-wave tomography inversion. We used the fast-marching method as ray tracing and subspace inversion to image subsurface velocity model to a depth of 150 km. The data used in this study are catalogue events data derived from a temporary seismometer network MERAMEX installed around central Java and DOMERAPI installed surround Mt. Merapi and Mt. Merbabu. We also include events collected from the International Seismological Centre. In total, we processed 563 earthquake events to illustrate velocity structures under central Java. The checker-board model shows that good resolutions can be identified at shallow depth, including offshore south Java contributed from Ocean Bottom Seismometer data. In vertical axis, good resolution models can be expected down to a depth 150 km following rich events from the Benioff zone. Current P wave model show a distinct low velocity zone under Mt Merapi that can be seen down to a depth of 40 km, suggesting a possible separated deep magma reservoir. To the south of Mt Merapi area also shows a low-velocity band that may be related with the southern mountain arc. Additionally, the northern part of Mt. Merapi displays a band of strong low-velocity anomaly to the East and West with the anomaly in the Eastern Part seems to have a deeper extension to a depth of ~50 km. We related this anomaly with Merapi Lawu Anomaly and Kendeng basin. Our results show a similar result with the previous tomography models in this region.

The plate movement, geological structure, magmatism, and seismic activity in the area of Bali to East Nusa Tenggara are mainly related with the subducting of Indo-Australian Plate underneath the Eurasian plate. The complexity is added with the recent collision of Australian continent lithosphere with the western Banda arc, along the islands of Flores, Sumba and Timor island. Our study area is known as the Sunda-Banda arc transition. With the aim of imaging subsurface structure, we perform seismic tomography inversion using regional events. We collected 5 years of earthquake data (January 2015 – December 2019) from the Indonesian Agency of Meteorology, Climatology, and Geophysics (BMKG). The output of our data processing is not limited to only P wave velocity model, but also relocated seismicity pattern in the region. In general, seismicity pattern shows dominant shallow events in the south that progressively shift into deeper events in the north down to a few 500 km, marking a dipping subduction zone in this region. A group of shallow events down to a depth of 50 km is also seen at the norther region that may relate to back-arc thrust activity. P wave tomogram model show a lower velocity perturbation at a depth of 30 km that could be associated with magmatic activity along the volcanic front line. Higher P wave perturbation model are spotted at two different zones, the first one is marking a dipping Indo-Australian plate down to depth of 400 km. We noticed that the angle of dipping is steeper in the Eastern part compared to the Western part. The second a relatively flat at shallow depth at the northern region from the island of Lombok to Nusa Tenggara Timur that may mark the back-arc thrust region

The Seram Trough is located in the northern part of Indonesia and has a complex tectonic setting. The uniqueness of these regions lies in the U-shape subduction system. Several models have been proposed in this region, such as one subduction system that has been rotated 90° or 180°, two subduction systems, and one subduction that having a slab roll-back that causes extension systems. In this study, we try to invert velocity and seismicity using double-difference tomography with the target of better imaging the sub-surface structure in the region. We use data catalogue collection from the Indonesian Agency of Meteorology, Climatology, and Geophysics. The length of data is 4 years from January 2015 to December 2019 from 16 permanent stations. Earthquake relocations show a focused hypocenter distribution at shallow depth, and we interpreted some of these shallow depth events are related to the magmatic activity. Event distribution also displays a steep angle of seismicity pattern that represents the dipping subduction slab. Inverted Tomography models show a band of faster velocity models that dip from North to South, suggesting a subductions slab. We also observe a possibility of a tear in the slab from the seismicity pattern and tomogram model. The slower velocity perturbation is seen at shallow depth that may associate with magmatic and frequent shallow seismicity. A possibility of partial melting is also seen with low-velocity zone at a depth of 70 km next to the fast dipping velocity.

The Sunda-Arc transition to the Banda Arc is located on the south of the Flores Island, Indonesia, where the Australian lithosphere is moving to the north direction. On-going subduction process dictates the tectonic setting though some studies also suggest a collision and obduction may occur in the past due to of plate buoyancy. This area has active seismicity with frequent large magnitude events. To better understand the tectonic system in this region, we performed double-difference tomography inversion using regional events. We obtained the data catalog from the Indonesian Agency of Meteorology, Climatology, and Geophysics ranging from 116° to 125° east longitude and -6.5° to 12.5° latitude. We collected 4312 events data, detected from 15 stations from January 2015 to December 2019. Final relocated hypocenters showed a reduced fixed-depth problem and a more clustered event, although some deep events disappear. Most events are related to the subducting Benioff zone with some clustered events in the northern area may be related to back-arc thrust. We also observed clustered events near active volcano region and reduced shallow seismicity region to the west of the Timor Island. Resolution test using the checkerboard and Derivative weigh Sum (DWS) shows that fair P wave resolution can be achieved until 300 km, although a smearing start to show at a deeper depth. However, due to lack of arrival S wave data, the resolution test suggest good resolution can only be seen until a depth of 100 km. Tomogram P and S wave models show a clear dipping subducting slab from south to North down to a 250 km. We also spot a fast velocity band near the Timor Island area that similar to the previous tomography study, interpreted as sliver forearm. We spotted a band of lower Vp, lower Vs and higher Vp/Vs at shallow depth close to the volcanic line and we interpreted this as a zone of higher temperature, that may relate to magmatic activity in this region. We also noticed a zone of low velocity and higher Vp/Vs that may relate with dehydration and partial melting. However, we feel this still uncertain due to low Vs resolution.

The tectonic system of Eastern Indonesia is controlled by several major and minor plates, such as Indo-Australian, Australian plate, and Pacific plates. This area is known for its complexity, and high seismic activity. This study tries to image the complex structures beneath this region by employing regional events data and seismic tomography methods. We used five years of regional events catalog provided by the Indonesian Agency of Meteorology, Climatology, and Geophysics. We have sorted 7336 events recorded between 120° – 136° longitude and 0° – 13°(-) latitude consisting of 46446 P and 15467 S wave arrival data. Relocated hypocenter map shows a better constrain location on seismicity along outer Bandar Arc. A dipping pattern of seismicity is seen that is going deeper to the Banda Sea. The seismicity map also images a steep angle pattern of seismicity that could be related to the subduction slab roll-back model at North of Wetar island. Interestingly, we spotted a seismicity gap in West Seram that could be linked with slab tear zone. The checker-board test suggests a proper resolution is still reliable to a depth of 200 km with a less interpretable model at a depth of 300 km. P-wave tomographic models image the high velocity dipping down going slab. The Banda slab is seen to subduct from south Timor Island to the north, from east Tanimbar and Aru Island to west part, and from north Seram Island to south. We observed the down-going slab meet from all directions at about 300 km beneath the Banda sea. P wave tomogram also shows the Timor Island slab has a steeper dip that agrees with the seismicity pattern. Near the Seram island, we identify a low-velocity anomaly zone infiltrate the Banda slab beneath the shallow part of West Seram, which was previously interpreted as slab tear zone. This study also noticed a higher velocity tomogram model at North of Wetar island that might indicate a back-arc thrust. Lastly, a low-velocity band is also exposed at a shallow depth close to the volcano chain along that Banda volcanic arc.

The detailed mechanisms of volcanic eruptions happened around Rawa Dano, Banten, Indonesia, remain undiscovered. One of the key features to this geological event is the presence of a 13.7 km × 6.5 km caldera-like morphology in the middle of Banten tuff deposits. Surface geological investigation in the area indicates that the eruptions are massive and occurred in several periods. Low-frequency ground-penetrating radar (GPR) signals are used as an aid to identify the unexposed part of the deposits in this volcanological study. Common-offset GPR surveys were carried out along three measurement lines traversing over the deposit outcrops. An outcrop which is exposed after sand mining activities at one of the survey locations shows dipping interfaces between the upper pyroclastic flow deposits, pumice-rich deposits, paleosol, and the lower pyroclastic fall deposits. These stratigraphic contacts are detected as well under the surface which are clearly recognizable in radar images. The GPR cross-section also shows some other reflections due to different deposit types. The overall results of the GPR profiles give the idea about the thickness of each type of volcanic deposits and the paleotopography in the surrounding area.

The 2020 Sumbawa earthquake of moderate magnitude (M 5.3) produced very significant aftershocks. Based on the computation of Utsu's method, those aftershocks would be ended after the 20th day. Those earthquakes along 20 days were relocated using double-difference method. The relocation results show the southwest-northeast orientation and getting deeper into the northwest direction. Those two directions show the strike and the dip from the fault plane of the earthquake which was consistent with the focal mechanism released by the Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG). Those results showed the majority of earthquakes occurred at a depth of shallower than 20 km. Those earthquake depths were fit with the previous study showing the crustal thickness beneath Sumbawa Island that was about 28 km. We also found that those earthquakes occurred at splay faults propagating to decollement structure. This study is beneficial for earthquake disaster mitigation especially in updating active faults on Sumbawa Island.

The 2018 Mw 7.5 earthquake in Palu, Central Sulawesi, resulting in ~2,000 fatalities and estimated economic losses of ~22.8 trillion Indonesian Rupiah, according to the report of BAPPENAS and Central Sulawesi Provincial-Government. Therefore, it is necessary to prevent similar disaster in the future by further detailed studies of any other potential sources that are capable of generating such hazards. Palu City is in the vast depression valley bordered by mountains in its eastern and western margins. The 2018 earthquake source is the Palukoro Fault, which runs through the western margin of onshore Palu Valley then continued under the bay. Along the eastern margin of the valley, we also identified a wide zone of many potentially active faults strands orienting N-S and NW-SE, showing predominantly normal faulting. These faults are observed from their normal fault scarps as inspected from Light Detection and Ranging Digital Terrain Model (LiDAR DTM) data with 90-cm resolution and field ground checks. The faults deformed the old terrace sediments (Late Pleistocene, ~125 kya), but it is unclear whether they also cut the Holocene young alluvial like the ruptured fault of 2018 event. Further paleoseismology investigation is then necessary to obtain further information about these potentially-active normal faults, including their slip-rate and the past ruptures.

The addition of seismic stations to the seismic network of BMKG in 2019 has successfully located some local earthquakes. In the early 2020 occurred significant earthquakes around Cirata Dam, West Java. During a period of January-March 2020, there have been 5 earthquakes with magnitude ranging from 1.8-3.7. Those earthquakes caused ground shaking up to III MMI intensity scale around the epicenters area. The relocation of the hypocenter using the Teletomo-DD method is applied in this study so that the data can be interpreted to show the fault geometry in this area. The relocated epicenters distribute in the east side of the dam elongated in SSW-NNE direction. Vertical distribution of relocated hypocenters show that the earthquake occurred at 1.1 km down to 14.5 km depth. Hypocenter depths are getting deeper to the north direction, this suggest dip orientation of the fault plane. The reconstructed dip orientation is consistent with nodal plane resulted from moment tensor inversion results, that shown fault planes oriented in N 229⁰ –272⁰ E direction and dip 49⁰–50⁰ to the north direction.

The pull-up effect is the condition of lithology elevated in seismic imaging because of rapid seismic wave propagation through carbonate build-up on it. Pull-up effect conditions can lead to misinterpretation, so it needs to be corrected until the actual geological conditions are obtained. This research was conducted in the JAX-field working area of PT Pertamina Hulu Energi ONWJ. The target reservoirs of this study are in the Main (Upper Cibulakan) Formation under the Carbonate Parigi Formation. The reflectors of the target reservoirs show pull-up effect in time domain seismic data. Thus, building a velocity model for velocity anomaly correction is needed to reduce uncertainty for structure maps and oil in place calculation. The method of correcting the pull-up effect in this study uses three variations of the velocity model: variation structurally controlled model, variation RMS velocity with well control, variation calibrated RMS velocities model. The three variations of the velocity model result can correct the pull-up effect on JAX-Field. Velocity model with variation RMS velocity with well control had the lowest error with 17,31 feet average of depth difference with actual depth from well. Based on three velocity models, the value of original oil in place on the JAX-32 reservoir surface had a range of 59,14-84,59 mmbo, while on the JAX-35A surface has a range of 27,77-31,23 mmbo. These values can be considered in reserve calculation sensitivity.

The area of Sulawesi, especially along the Palu Koro Fault, is an area that is largely influenced by the confluence and movement of plates as well as regional fault activity pathways with high levels of seismicity. Determining the location of the hypocenter accurately through relocation is required in identifying the detailed tectonic structures in the area. Relocation of the hypocenter using the Modified Joint Hypocenter Determination (MJHD) method using the IASP91 velocity model in the period August to October 2018 with the arrival time data from BMKG catalog. The results of hypocenter relocation using the MJHD method show that from 132 earthquake distribution points to 63 earthquake hypocenter points after the relocation. The change in the location of the hypocenter was much denser along the Palu Koro Fault route than before the relocation as evidenced by the mean value of rms (root mean square) before relocation was 1.31 and after relocation it became smaller (0.61). Changes in parameter values after relocation using the MJHD method caused the distribution of the earthquake hypocenter to be tighter towards the Palu Koro fault than before the relocation, where the distribution had a random and scattered pattern.

Ironsand deposits might contain Fe as well as other valuable elements and minerals that could be used in a variety of applications. Often, high Fe content deposits are preferable for exploration. An earlier study shows that the highest Fe content is found in the very fine sand (VFS) size. In this study, seven VFS samples from Anoi Itam were subjected to magnetic measurements as well as X-Ray florescence (XRF), X-Ray diffraction (XRD), and correlation analyses to investigate further characteristics and how magnetic susceptibility correlates with the elemental composition of ironsand. Magnetic susceptibility varies from 2207.77 × 10^-8 m³ kg^-1 to 4476.68 × 10^-8 m³ kg^-1. The main elements contained in the sample are Fe, Ti, Si, and Al. Meanwhile, other elements have small concentrations (<2%). Based on XRD analyses, magnetite and ilmenite are the main minerals with varying concentrations in each sample. The correlation analysis shows that magnetic susceptibility has a weak correlation with Fe probably because Fe forms minerals with very different magnetism, namely magnetite and ilmenite.

Cirebon is a densely populated port city which has ironsand deposits at its coastal area. Due to its vicinity to the port and the estuary, these deposits might contain anthropogenic pollutants including, heavy metals. Magnetic measurements, X-Ray diffraction (XRD) as well as X-Ray fluorescence (XRF) analyses were carried out on iron sand samples from three sites along the Cirebon coastal area to identify the anthropogenic pollutants. The samples were separated based on the grain size before the measurement and analyses. Preliminary results show that the ironsand is less magnetic and has smaller frequency-dependent magnetic susceptibility values than ironsand found on Bayuran Beach in Central Java. Combined XRD result and the regional geological map shows that most of the minerals were originated from eroded volcanic rocks. The XRF results show that the samples have a relatively high content of Si. XRF analyses also show relatively high concentrations of Cr and Zn, the Geoaccumulation Index shows that the sediment is moderately to heavily polluted by Cr and Zn indicating the possibility of anthropogenic origin. The Cr and Zn content exceeds the stipulated value in the Sediment Quality Guidelines (SQGS).

The arc magmatism and volcanic activity in Java are dominated by the subducting plate of Indo-Australian into the Eurasian plate. Merapi volcano is located in Central Java and known as one of the most active volcanoes in the world. Several studies have tried to estimate the magma reservoir zone in Mt. Merapi and suggested multiple layers of reservoirs with the shallow one at 1-2 km and a deeper at 6 -9 km or 15 km. The Low-Frequency Passive Seismic is one method to analyze the frequency spectrum below the recording station. Previous related studies show a promising a relation between hydrocarbon reservoir and higher amplitude at vertical component at a frequency between 0.1 – 6 Hz. An observation at the volcano sites have also been reported to display a different spectrum amplitude at the vertical component. This study exploited the same method in LFPS to analyze the frequency spectrum at Mt. Merapi and Mt. Merbabu. We use seismic data from the DOMERAPI temporary seismic network installed in the neighborhood of Merapi and Merbabu volcano. We analyze 53 broad-band seismometers data from October 2013 to mid-April 2015. We also add several stations from MERAMEX network instruments to compare spectrum analysis outside the Merapi and Merbabu volcano. We also removed some tele-seismic and regional events from the data to better analyze the LFPS signal. We have seen a higher amplitude in vertical component near Mt. Merapi and will proceed to analyze all stations.

Land Subsidence became recent issue in environmental management in Indonesia. Large cities in Indonesia, especially in Java Island, are well known to suffer from fast rate land subsidence such as Jakarta, Bandung, and Semarang. However, the phenomena is presumed to also happen in other cities which have large industries and located on the deposit or clay soil layer. The effect of land subsidence may be different in some location, but the coastal zone will have more impact since land subsidence will also induce tidal flood and may cause land area reduction. In this study, we use more than 70 Sentinel-1 data, range from year 2016 to 2020 to map the land subsidence in the Java North Coast. The interferograms are selected based on Small Baseline Subset (SBAS) algorithm. National Digital Elevation Model (DEMNAS) is used in differential InSAR process. Our result shows that many cities along the Java North Coast suffer land subsidence. Jakarta, experience has maximum subsidence more than 5 cm/year. In Central Java, Pekalongan experience up to 7 cm/year of land subsidence, while Semarang and Demak has subsidence rate up to 8 cm/year.

We conducted azimuthal resistivity survey (ARS) at laboratory scale to study apparent resistivity patterns due to fracture existing in subsurface through physical modeling using test objects buried in a sandbox as well as in a test location outside laboratory building. This survey was divided into 2 experiments, i.e. experiment A and experiment B. In experiment A the survey is implemented on 2.50 m x 1.5 m x 0.81 m sandbox, made of 10mm thick glass plates. Sandstone was used as medium representing quasi homogenous medium. Clay roof tiles as well as steel plates as test objects were buried in the sandbox with three different deep angles: 90°, 45° and 0°. In experiment B this survey was conducted outside laboratory building on the grass field and implemented on 2.50 m x 2.5 m x 1.0 m soil body. Vertical single glass plate as well as vertical double glass plates at 30 cm distance were buried in the soil body. Azimuthal resistivity measurements at 15° angular step using Wenner and dipole-dipole configuration were carried out in both experiments located at 1 point just above anomalous object for experiment A and at 3 points at 15 cm distance from anomalous object for experiment B. As a compliment to ARS we acquired profiling data from two lines parallel and perpendicular to horizontal axis of anomalous object. Our results show that the apparent resistivity pattern can show the direction of anomalous object for both configurations and experiments with a little deviation.

On May 27, 2006, 05:54 am local time, a moderate crustal earthquake of magnitude Mw 6,3 struck the Yogyakarta province, especially in the Bantul regency in the south part of the province. The earthquake damaged or destroyed more than 400,000 houses and buildings and caused more than 5,700 people killed. Several earthquake stations recorded the ground vibration caused by the mainshock very well, except at the stations closest to the earthquake source, namely YOGI in Gamping, West of Yogyakarta, which experienced saturation due to significant vibration. Therefore, information about the maximum ground acceleration near the source is yet not known. We model the ground vibrations near the earthquake source using a stochastic Green's Function approach to obtain information about the ground motions' maximum amplitude. The earthquake source parameters we referred to is the moment tensor solution from the Harvard Moment Tensor. The calculations show that the amplitude is consistent with observations recorded at the BJI Banjarnegara (0.04g) and YOGI Yogyakarta (0.3g).

The remaining alluvial tin reserves around large ex-mining area can be an opportunity to optimize the potential reserves using a small-scale mining system. One of the latest breakthroughs in the mining system for the remaining alluvial tin reserves on land is the borehole mining (BHM) method. However, mining operations using BHM have several environmental impacts especially related to its former holes. This study aims to identify the changes in geometry of the former holes both on the surface and below the surface through direct field observations and measurements using geophysical methods. The study site is in the large ex-mining area of Air Nudur Block in South Bangka Regency, Bangka Belitung Islands Province. The geophysical methods used to identify the changes in the geometry of the BHM holes are GPR (ground penetrating radar) and IP (induced polarization). The GPR method has high resolution subsurface visual capabilities at shallow depths and this method can distinguish between stable and unstable layers. The IP method is used to determine the overburden layer and the condition of the alluvial layer where some of it has become a hole. These two methods will mutually reinforce in interpreting the change in the geometry of the BHM holes. Changes in hole diameter and depth were measured directly in the field within 2 (two) months from the completion of mining operations using the BHM method followed by the periodic topographic measurements using UAV (unmanned aerial vehicle). The results of observations on changes in the elevation of the ground surface around the former BHM hole indicated that the land level subsided by about 1 m. Meanwhile, the results of GPR data processing showed changes in the hole geometry with the hummocky radargram pattern into chaotic. Interpretation of IP data processing shows resistivity values of 250 - 1700 ohm.m and chargeability of 15 - 25 ms in the disturbed alluvial layer around the former BHM holes.

The Self-Potential (SP) method is passive method in geophysics which works based on the natural presence of an electric field on the surface due to anomalies below the surface. SP value on surface can be generated by fluid flow through rock pores or fractures. We study fluid flow movement in subsurface using the velocity value of fluid flow derived from SP values measured on surface. For that purpose, we carried out mathematical modelling, connecting the Helmholtz-Smoluchovsky's electrokinetic potential gradient equation with Darcy's law. The velocity of fluid flow depends on the intrinsic permeability of rocks, electrokinetic potential gradient and electrohydrolic conductivity constant. We tested derived velocity of fluid flow on the SP data from a pilot project test site. Study results show that fluid flow in vertical direction can be identified from SP data at locations where there are significant changes of positive and negative SP values. Fluid flows from a high SP value to a low SP value and this flow is opposite the positive SP gradient. The SP value at study site lie in the range -80mV to -160mV, whereas the value of the water flow velocity lie in the range 0.08 cm/s - 0.21 cm/s.

The purpose of this study is to utilize satellite gravity data for free to interpret subsurface conditions. The data can be obtained from the topex site with a latitude range is +/-80,738. The author tries to interpret the gravity data for Lake Toba, North Sumatra. The area is attractive because it has a sizeable geological object in the form of a large lake and a fault called the Sumatran fault. This gravity data is processed like ordinary gravity processing so that Complete Bouguer Anomaly (CBA) is obtained, then regional-residual separation is carried out using a moving average. From CBA, it can be seen that there are two closures just below Lake Toba. There are two possible chambers under Lake Toba, namely the central and southern parts. In addition, it is also clear that the lineament of the Sumatran fault is also visible, as well as three other lineaments which may be faults that are not identified from the surface. So, we can take advantage of this free gravity satellite data for interpretation of sizeable geological objects that can be applied to other areas. It is helpful to know the general picture of regional geology before conducting a more detailed survey.

Indonesia is an earthquake-prone country located in the junction of four tectonic plates, namely the Indo-Australian, Eurasian, Philippine, and Pacific. The convergent boundary between tectonic plates is also called a subduction zone that can produce great earthquakes in the future. One of the subduction zones in Indonesia is the Sunda Strait subduction zone which predicted can release a M7.8 earthquake. Previous research stated that there is a change in tectonic plate velocity after an earthquake ruptured. It is likely that this could happen in the Sunda Strait area which has experienced several large earthquakes. In this study, we conducted research to find out the information on the tectonic plate velocity changes in the Sunda Strait. We used Global Positioning System (GPS) time-series data provided by Indonesia Geospatial Information Agency (BIG). The time series data is used to calculate the earthquake displacement, the changes in GPS velocity of before and after earthquake, and the changes in velocity of each time interval. Our results show that the horizontal displacement due to the earthquake at all GPS stations ranged from 3.34 mm to 7.36 mm in the north-south direction and -27.45 mm to 0.18 mm in the east-west direction. Furthermore, the result of the changes in GPS velocity before and after an earthquake ranged from 2.25 mm/year to 12.60 mm/year and 1.80 mm/year to 13.35 mm/year. The pattern of change in velocity is likely due to post-seismic deformation from the 2012 Indian Ocean earthquake, the 2016 Sumatra earthquake, and also other tectonic factors.

Tasikmalaya City is one of the regions in West Java Province that is often hit by earthquakes due to its location near the Indo-Australian Plate subduction zone towards the Eurasian Plate. The surface deposits in this city are alluvium and weakly consolidated step deposits which can cause wave amplification during an earthquake. As a mitigation effort, seismic zoning needs to be carried out to map the areas that will experience heavy damage when an earthquake occurs. This study uses the Horizontal to Vertical Spectral Ratio (HVSR) method which is applied to the microtremor recording data to obtain spatial variations in the predominant frequency and amplification values that can explain the characteristics of the geological layer beneath the surface. Based on the obtained results, the predominant frequency ranging from 0.7 to 9.5 Hz with the lowest frequency distribution in the eastern and northwestern parts, which indicates a thicker sediment layer. Amplification ranging from 1.2 to 12.6 with the distribution of higher values in the eastern, southeastern, and northwestern parts. The inversion of the HVSR curves was carried out to determine the value of shear wave velocity (V_s) in order to obtain a more detailed subsurface geological structure that can be used to determine the level of vulnerability of earthquake hazards. The Neighborhood Algorithm is used to find an optimum model. Based on the results of the inversion process, the V_s ranging from 150 - 3054 m/s with lower V_s values in the eastern, southeastern, and northwestern parts at depth of about 25 meters. The average value of shear wave velocity at a depth of 30 meters (V_s³⁰) can also be used to determine the type of soil for geotechnical study. From the obtained V_s³⁰data, the types of soil in the research area are classified into moderate soil, hard soil, and rocks.

The existence of seismic wave velocity difference in the Earth crust and mantle creates the possibility to use earthquake data for estimating the crustal thickness utilizing the Ps conversion phase in the boundary. The radial component signal was deconvolved from the vertical component in the frequency domain to estimate receiver function for Indonesia region. We implemented the water level deconvolution techniques with a Gaussian filter of 2.5 Hz to eliminate the high frequency noise in the receiver function. The H-k stacking technique was performed to all receiver functions from each event to predict the crustal thickness and the Vp/Vs ratio below the stations. We analyzed ten azimuthally distributed teleseismic earthquakes recorded by 108 stations of BMKG. The result shows that the crustal thickness in Indonesia varies from 20 to 39.9 km. The western part of Sumatera, northern part of Sulawesi Island, and North Maluku region show generally thinner crust with value about 20 to 25 km. The North Sumatera, Central Java, and East Java show a considerably thicker crust of up to 36 km. Furthermore, our result also reveals a difference of crustal thickness about 5 km with the previous studies.

Landslide susceptibility modeling using neural network (ANN) are applied to semi detailed volcanic-sedimentary water catchment. Annually landslide occurred in catchment area frequently in unconsolidated and weathered material combined with uncertainty in rainfall pattern that complicated landslide occurrence. Data used for analysis including landslide inventory, geology, digital elevation related data, distance to stream, and several other available data. Results show that machine learning method yield fair result data based on evaluation on Area under Curve (AUC). Thus, it can be suggested that machine learning methods for landslide susceptibility model could still be develop to produce robust prediction model with different characterization of parameter data and machine learning parameters.

Rongga District is located on West Bandung Regency, West Java, which is prone to landslide disaster. Morphological conditions in the form of steep hills become the one of landslide controlling factors. There are many landslide occurrences happen in this area, such as Nyomplong, Cibitung Village on March 23, 2020. The incident was triggered by heavy rain and strong winds. This area was chosen to assess the landslide susceptibility using the Weight of Evidence (WoE) Method. WoE is probabilistic bivariate method which connecting parameters causes landslide against distribution of landslide in research area. Landslide data which generated from direct observation in the field and satellite imagery morphology are 572 landslide events. The data is divided into two groups, the analysis data set (70%) and the validation data set (30%). The parameters used in the analysis are land use, slope, slope direction, curvature, elevation, rainfall, lithology, NDWI, NDVI, distance from road, distance from the river, distance to lineament, flow direction, lineament density, stream density and river density. The parameters validated by determining the value of the area under curve (AUC). AUC value> 0.6 will be used in the landslide susceptibility zonation next analysis. Validation of landslide susceptibility zonation was carried out using 172 landslide events. The result of the WoE validation shows the AUC success rate of 0.70 and AUC prediction rate of 0.76. The value of AUC shows that the modelling is good and acceptable.

Eastern Indonesia lies in a complex tectonic region due to the interaction of four major tectonic plates: the Australian Plate, Pacific Plate, Philippine Sea Plate, and Sunda Block. Therefore, this region hosted some destructive seismic activities as well as tectonic deformation, such as the Mw 7.5 Palu Earthquake, the sequences of the 2018 Lombok Earthquake, and the Mw 6.5 Ambon Earthquake in 2019. Our work proposes a recent study on crustal deformation in Eastern Indonesia inferred from Global Positioning System (GPS) velocity field. We used GPS data from the observations of 49 permanent and 61 campaign stations from 2010 to 2018. Here, our velocity field result represents long-term tectonic deformation regions in Eastern Indonesia continuously, from Bali in the west to Papua in the east, demonstrated both in the ITRF 2008 and the Sunda reference frames. The spatial pattern of velocity field map collected from this research will give an initial insight into the present-day tectonic condition in Eastern Indonesia and then can be used to improve our ability to assess this area's earthquake potential.

Mapping of subsurface infrastructure such as pipelines, pipe ducts as well as man-made objects located below the earth surface is a difficult task in geotechnical engineering due to the need to direct contact to the object. Ground-Penetrating Radar (GPR) method as one of geophysical methods is an appropriate technique to solve such problems due to its capability to effectively provide the existence, the location and the depth of buried shallow objects. Despite many advantages, the application of GPR method is limited by achieved depth and resolution range that is frequency dependent. To overcome such problems, the so-called multi-frequency compositing method with Optimal Spectral Whitening (OSW) technique is studied and applied on real data acquired in the Muarakarang Combined Cycle Power Plant area located in the Northern part of Jakarta, the Capitol of Indonesia. Datasets from GPR measurement with 100 MHz and 250 MHz was used. Each radargram from the same path was processed individually and then joined to become multiple composite radargram. The resulted composite radargram from a GPR line we studied has shown clearer image for interpretation rather than individual interpretation. The applicability of this multi-frequency compositing recommend further study to solve some facing problems in geotechnical engineering.

The Lombok earthquake in 2018 was unique, the shocks occurred sequentially. Several major earthquakes were followed by thousands of aftershocks. The earthquake caused a devastating disaster which destroyed many homes, buildings including wells as the main fresh water supply in the Lombok Island. The focal mechanism of main earthquake shows a thrust fault mechanism. Lombok Island is originally a volcano Island which is still growing actively. Therefore surface of Island is dominated by volcanic materials, such as: volcanic rock, volcanic ash, pumice. This paper describes the phenomenon of sanding wells in Lombok, including the physical mechanisms among rock's grains when vibrating earthquake waves. These earthquake waves can eliminate static friction between grains and reduce cohesion between grains of rock. Some subsurface images shows a strong correlation between damage grade and the existence of loose sand and hard rock.

Gravity method is one of the geophysical methods that's using variation of gravity value caused by density variation of subsurface. Gravity method has been utilized for many purposes such as understanding the geological information about one area or understanding the subsurface structure. This study is using gravity method to identify the heat source from the geothermal manifestation (hot spring) which is located in the non-volcanic region in North Java. Gravity data was obtained from WGM 2012 satellite data that can be downloaded at BGI website and processed using Oasis Montaj software. Data processed using horizontal derivative method to enhance the boundaries resolution of the possibility geological structures location in the study area that is predicted to be the way of the heat source of hot spring manifestation. The result of this study shows that the heat source of the hot spring in Northern East Java is probably coming from Lasem Volcano's heat source. The result can be proven by the similarity of the Bouguer Anomalies value between the Lasem Volcano region and the manifestations distribution area, which varies in 174-185 mGal. Besides that, Lasem Volcano is the closest volcano from the manifestation with a distance of approximately around 27 km.

Tsunami warning is one of many important reports to save lives and reduce the damage for local peoples. A moment magnitude of P-wave (Mwp) and the rupture time duration (Tdur) can be used as the quickly parameters to diseminate the tsunami warning. In this paper, we analyze the seismic waveform from global network to get Mwp and Tdur of South-West Coast of Sumatera earthquake. Mwp was calculated using automatic and manual phase picking of P phase. The results of this study show a well-analyzed relationship between P wave from automatic and manual picking, Mwp and time duration, respectively. The result also give an encouraging studies for the early warning system that will be set up in the future in the region.

Airborne measurements are very useful to cover very large areas. Nine month after the Aceh Tsunami and Earthquake in 2004, BGR (Federal Institute for Geoscience and Natural Resources) conducted a fresh water supply exploration survey within a project called Helicopter Project Aceh (HELP ACEH). The helicopter-borne electromagnetic (HEM) device operates at five frequencies. The HEM can estimate the 1D resistivity models down to a depth of 150 m for the high electrical resistivity areas and 50 m for low electrical resistivity areas. In this paper, the airborne data of 2005 are compared with resistivity data acquired in Banda Aceh basin in 2018. The HEM output consists of 1D resistivity models derived by inversion of the processed data. These 1D resistivity models are compared with the 2D resistivity models derived from ground-based resistivity measurements. However, the 2D models on the ground are transformed into 1D resistivity models so it can be used for comparison. The transformation is conducted by averaging the resistivity values in the each layer, so every layer only has one resistivity value. Both methods are influenced by many factors. For example, resistivity on the ground is affected by local conditions. The airborne measurements are also influenced by objects that are at the surface of the ground. In some cases, the airborne resistivity models have some differences in absolute resistivity values, but they often have the same structural pattern compared with the ground-based resistivity models.

The Lidar technology is widely used in various studies for mapping needs. In this study was to extract land cover using Lidar data by incorporating a support vector machine (SVM) approach. The study was located in the city of Lombok, Nusa Tenggara Barat. Image extraction was performed on single wavelength Lidar data to produce intensity and elevation (Digital Surface Model) features. Feature extraction of Lidar data was implemented by using a pixel-based approach. The extracted features used as an attribute for training data to generate the SVM prediction model. The prediction model to predict the types of land cover in the study area such as buildings, trees, roads, bare soil, and low vegetations. For accuracy assessment purposes, we used topographic map available in shapefile format as the reference map and estimated the accuracies of the resulted classifications. In this study, land cover classification used combination bands which improved the overall accuracy by approximately 20%. The use of the intensity data in this band combination was the reason for the increasing accuracy.

Ambient seismic noise tomography is one of the most widely used methods in seismological studies today, especially after a comprehensive Earth noise model was published and noise analysis was performed on the IRIS Global Seismographic Network. Furthermore, the Power Spectral Density technique was introduced to identify background seismic noise in the United States. Many studies have been carried out using the ambient seismic noise tomography method which can be broadly grouped into several groups based on the objectives and research targets, such as to determine the structure of the earth's crust and the upper mantle, to know the thickness of the sedimentary basins, to know the tectonic settings and geological structures, to know volcanic systems and geothermal systems, knowing near-surface geological features and as a monitoring effort the Ambient Noise Tomography method carried out by repeated measurements or time lapse. In this study, we investigate the characteristics of the ambient noise seismic tomography method, both its advantages and limitations of the method by utilizing synthetic data modeling using a simple geological model. Synthetic data is generated based on 1D dispersion curve forward modelling and the forward modeling of surface waves travel time for each period, which is then convoluted with the wavelets of each periods, then doing reverse correlation using a reference signal to produce synthetic recording data. We found that the estimate target depth and vertical resolution depend on the recorded data periods and the synthetic data modeling can be used as a basis in determining the acquisition design.

The crust, when viewed over a long period, moves towards one another. Crusts might experience sudden slip on a fault plane and caused fractures or cracks. There are three different types of faults, normal, reverse, and strike-slip faults. Induced stress due to sudden rupture on fault planes capable of creating stress and need to be measured quantitatively to comprehend the earthquake process. To understand the stress that occurs in strike-slip faults in the earth's crust, the previous researchers study the use of elastic materials as the material of the earth's crust, so that the earth crust's deformation is elastic. However, elastic material has linear stress and strain relationship that results in reversible deformations or returns to their original shape. This material is not suitable for modeling the earth's crust's long-term deformation, where the deformation of the earth's crust can be permanent, so a model is needed to solve this problem. In this study, we will compare the stress in the strike-slip fault in the upper crust with elastic materials, while the lower crust and upper mantle have viscoelastic materials compared to purely elastic materials through numerical simulations. This comparison is made to see the comparison between the two approaches with the earth's layers' actual state. The two models is chosen to represent the different failure processes of the earth crust, i.e. the elastic deformation part describes the response to stress in a short period, and the viscous deformation can explain the response over a more extended period. The study of both materials above is based on plate tectonic theory, in which the lithosphere plates will relatively move to each other because the layer material underneath is solid but can flow like a liquid for a long period.

Agung is one of active volcanoes in Indonesia, located on island of Bali. Since 1963, Agung has not had significant activity, until in September 2017 the volcano was active again which was marked by increased seismic activity and eruptions in November 2017. Therefore, to analyze the dynamics and processes of active volcanic eruptions requires an understanding of the structure of the volcano, especially the position of the magma reservoir and its path. The depiction of the structure of this volcano can be analyzed by determining the location of the earthquake due to volcanic activity, especially Volcano-Tectonic (VT) earthquake. In this study, we determined the location of the hypocenter around the Agung using the non-linear location method. VT earthquakes have similar characteristics to tectonic earthquakes so this method can be used to determine the initial hypocenter. The data used in this study came from 8 PVMBG seismographs from October to December 2017. We manually picking arrival time of P- and S-waves from the 3948 VT events found. Pair of P and S wave phases with 18741 P-wave phases and 17237 S-wave phases, plotted in a wadati diagram resulting in a vp/vs ratio of 1.7117. We use 1D velocity models derived from Koulakov with the assumption that the geology of the study area is not much different from the volcanoes in Central Java. The resulting hypocenter distribution shows a very random location and has uncertain X, Y, and Z directions from a range of 0 to 91 km. This study limits this uncertainty to 5 km resulting in a more reliable earthquakes distribution of 3050 events. The results indicate 2 clustered events, a swarm of VT events that occur every month at a depth of 8 to 15 km and there are 2 paths that lead to the top of Agung and SW of that swarm. These preliminary results will be used to update 1D velocity model and relocate the events beneath Agung region for further studies.

Hypocenter relocation is one of the keys to success in the analysis of seismicity induction in underground mines. Overburden thickness, topography, geological complexity, and mining activities can result in newly induced seismicity that can endanger the safety of underground mine workers. The relatively narrow underground mine area requires the most accurate hypocenter location information possible. The double-difference algorithm approach is one of the keys to overcoming this problem. The double-difference method is a relative location method that tries to minimize the residuals between the observed and calculated travel time differences for pairs of microseismic events at each station, by adjusting the differences between all pairs of events at each station repeatedly. In this study, we utilized microseismic measurement data in the deepest underground mine in Indonesia. A total of 1783 seismic events were successfully relocated. The relocation results show the rock mass stress which is illustrated by the distribution of events around the cave, especially the abutment area and underground mining tunnels.

Present day Molucca or Maluku sea plate in the eastern of Indonesia possesses a complex tectonic setting. This complex tectonic setting has been formed due to the collision of an actively moving Eurasian plate and Philippine sea plate toward the Maluku sea plate. At the west, Maluku sea plate is subducting beneath Sangihe arc, which began in the early Miocene. While at the east, Maluku sea plate is subducting under Halmahera arc, since in the middle Miocene. These subduction processes take place up to the present. Therefore, it has formed Maluku sea plate into an inverted U-shape slab under a thickening accretionary complex. Seismicity distribution has clearly shown the U-shape slab. Earthquake events take place on the subducting slab, and interestingly on the above accretionary complex as well. Maluku sea plate might pose hazards to surrounding islands: northern Sulawesi, Halmahera island, Sangihe island and Talaud island. The possible hazard, for instance, a thrusting earthquake which may generate tsunami to the nearby islands. Hence, understanding its tectonic and seismicity signature, especially at the shallow part, are indeed important in the Maluku sea region. Faulting regime could be analyzed using focal mechanism ternary diagram analysis, by categorizing the focal mechanisms' strike, dip and rake values. Thus, in this study we aim to analyze faulting regime and hazard potential in the complex. Maluku setting using ternary diagram analysis.

Shear-wave splitting (SWS), or the propagation of two independent shear waves, can be used as an indicator of seismic anisotropy. In this study, we utilize this concept using aftershock data of the 2018 Lombok earthquake which had been acquired in period of August 4 – September 9, 2018. The goal of this research is to better understand the crack distribution related to the rupture zone of the 2018 Lombok earthquake. After applying instrument correction to the data, the waveform data were then windowed in each P and S arrival time. To determine the SWS parameters, we performed rotation in each horizontal seismogram components. The horizontal components were rotated from azimuth 0° to 180° with an increment of 1°. Cross-correlation coefficient (CCC) was determined for each rotation angle. The polarization direction and the SWS delay time were chosen from the parameters shown in the highest value of CCC.

The existence of anisotropy phenomena in the subsurface will affect the image quality of seismic data. Hence a prior knowledge of the type of anisotropy is quite essential, especially when dealing with deep water targets. The preliminary result of the anisotropy of the well-based modelling in deep water exploration and development is discussed in this study. Anisotropy types are modelled for Vertical Transverse Isotropy (VTI) and Horizontal Transverse Isotropy (HTI) based on Thomsen Parameters of ε and γ. The parameters are obtained from DSI Logging paired with reference δ value for modelling. Three initial conditions are then analysed. The first assumption is isotropic, in which the P-Wave Velocity, S-Wave Velocity, and Density Log modelled at their in-situ condition. The second and third assumptions are anisotropy models that are VTI and HTI. In terms of HTI, the result shows that the model of CDP Gather in the offset domain has a weak distortion in Amplitude Variation with Azimuth (AVAz). However, another finding shows a relatively strong hockey effect in far offset, which indicates that the target level is a VTI dominated type. It is supported by the geomechanical analysis result in which vertical stress acts as the maximum principal axis while horizontal stress is close to isotropic one. To sum up, this prior anisotropy knowledge obtained based on this study could guide the efficiency guidance in exploring the deep water environment.