bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bayesian Inference of Centroid Moment Tensors of the 2019 Ambon (Mw 6.5) Aftershock Earthquake Sequence, Indonesia: A Preliminary Result
Authors: Baskara A W , Sahara D P , Nugraha A D , Muhari A , Rusdin A A , Rosalia S , Priyono A , Zulfakriza Z , Widiantoro S , Puspito N T , Lesmana A , Kusumawati D , Ardianto A , Halauwet Y 
Published: November 2021

Abstract
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.
Site characterizations of BMKG seismic network, Indonesia, based on HVSR analysis
Authors: Muzli Muzli , Kambali R A P , Nugraha J , Sulastri S , Hakim A R , Rohadi S , Triyono R , Riama N F , Karnawati D 
Published: November 2021

AbstractIn 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.
Elastic Property Modeling, Extended Elastic Impedance (EEI) and Curve-Pseudo Elastic Impedance (CPEI) Inversion for Pore Type Analysis and Hydrocarbon Distribution in Carbonate Reservoir, Kujung I Formation, “Humaira” Field, North East Java Basin
Authors: Kumalasari I N , Winardhi I S 
Published: November 2021

Abstract
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.
Analysis of Source Mechanism and Coulomb Stress Change (Case Study: Molucca Sea Earthquakes November 15th, 2014 and November 14th, 2019)
Authors: Purba Indra Josua , Suardi Iman , Daniarsyad Gatut , Lasmita Defni 
Published: November 2021

AbstractOn 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.
Indonesian Earth’s Lithospheric Magnetic Field modelling using Spherical Cap Harmonic Analysis Method
Authors: Ilham  , Syirojudin M , Margiono R , Marsono A , Ardiana N 
Published: November 2021

Abstract
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.
Optimization of 2-D Magnetotelluric (MT) Modes Based on Data Dimensionality to Delineate Potential Area for Shale Gas Prospect in Kutai Basin, East Kalimantan, Indonesia
Authors: Hidayat  , Lucky Junursyah G.M , Setiawan Ahmad , Pradana Andrawan Erlang 
Published: November 2021

Abstract
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.
Peak Ground Acceleration (PGA) and Peak Ground Velocity (PGV) Analyze for Microzonation of Earthquake Hazard Area: Case Study in West Nusa Tenggara
Authors: Razin T , Khatimah K , Annisa Y , Hamzah A , Massinai M F I 
Published: November 2021

Abstract
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.
Fault rupture in Baribis Fault possibly related to the 1847 major earthquake event in the Cirebon area
Authors: Daryono Mudrik Rahmawan , Natawidjaja Danny Hilman , Puji Anggraini Rizkita , Aribowo Sonny 
Published: November 2021

AbstractBaribis 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.
Preliminary Results of Receiver Function Forward Velocity Modelling at Merapi Volcano
Authors: Auly M F R , Ilahi A K , Madrinovella I , Widyanti S , Suhardja S K , Fatimah D Y , Nugraha A D , Zulfakriza Z , Widiyantoro S , Métaxian J-P , Ramdhan M 
Published: November 2021

AbstractThe 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.
An Attempt to Pick Teleseismic P Wave Arrival Using Envelope and Artificial Neural Network Algorithm
Authors: Lobo R K , Gaol Y H L , Fatimah D Y , Abdullah A , Zaky D A , Suhardja S K , Nugraha A D , Zulfakriza Z , Widiyantoro S , Ramdhan M , Palgunadi K H , Mujihardi B 
Published: November 2021

Abstract
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.
Preliminary Results of Automatic P-Wave Regional Earthquake Arrival Time Picking Using Machine Learning with STA/LTA As the Input Parameters
Authors: Lumban Gaol Y H , Lobo R K , Angkasa S S , Abdullah A , Madrinovella I , Widyanti S , Priyono A , Suhardja S K , Nugraha A D , Zulfakriza Z , Widiyantoro S , Hakim M Luqman , Palgunadi K H 
Published: November 2021

Abstract
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.
Pyroclastic Deposits Identification using Near-Surface Seismic Refraction Tomography in Rawa Dano Volcanic Complex, Banten, Indonesia
Authors: Maryadi Maryadi , Ilahi Bisgar Nanda Aminy , Yufajjiru Luthfi , Rizqulloh Rifqi , Fatih Ghozy El , Jabbar Gamma Abdul 
Published: November 2021

Abstract
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.
Preliminary Model of P-Wave Tomography Beneath Central Java using FMTOMO
Authors: Yasir M , Brilianti P T , Angkasa S S , Widyanti S , Herawati I , Pranowo W , Satiawan S , Suhardja S K , Priyono A , Widiyantoro S , Ramdhan M 
Published: November 2021

Abstract
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.