scholarly journals Metode Seismik dalam Pemodelan Fisis Letusan Gunung Lumpur Bledug Kuwu

2019 ◽  
Vol 2 (2) ◽  
pp. 61-66
Author(s):  
Ahmad Fauzi Pohan ◽  
Rusnoviandi Rusnoviandi
Keyword(s):  
Wave Velocity ◽  
Physical Modeling ◽  
Vertical Component ◽  
Dominant Frequency ◽  
P Wave ◽  
Physical Parameters ◽  
S Wave ◽  
Interesting Phenomenon ◽  
Central Java ◽  
P Wave Velocity

Aktivitas gunung lumpur Bledug Kuwu di Jawa  Tengah merupakan fenomena yang menarik dikaji menggunakan pemodelan fisis. Tujuan penelitian ini adalah mengetahui parameter dari medium gunung lumpur Bledug Kuwu. Adapun pemodelan fisis yang dilakukan dengan menggunakan media fisis akuarium berukuran 59 × 59 × 37,3 cm yang diisi material dari lumpur Bledug Kuwu. Sumber letusan dihasilkan dari tekanan kompresor yang dapat diatur kedalaman (10.5, 13, dan 15.5 cm) dan sudut (30o, 45o dan 60o) sumbernya. Sensor yang digunakan geophone komponen vertikal sebanyak 3 buah dengan durasi perekaman selama 5 dan 2,5 detik. Data diambil dengan frekuensi sampel 2 dan 4 kHz untuk masing-masing durasi perekaman. Konfigurasi sumber dan geophone dibuat sesuai dengan pemodelan fisisnya. Pengukuran desnsitas lumpur menunjukkan angka sebesar 1200 kg/m3. Berdasarkan hasil analisis seismogram model fisis diperoleh kecepatan perambatan gelombang-P pada medium lumpur Bledug Kuwu adalah sebesar 48,74 m/s,dan gelombang-S sebesar 28,14 m/s dengan frekuensi dominan antara 20 sampai 25 Hz.   Bledug Kuwu mud volcano activity in Central Java is an interesting phenomenon to be studied using both physical  modeling. The objective of this study was to determine the physical parameters of the medium of Bledug Kuwu. The Physical model was an aquarium with a dimension of 59 × 59 × 37.3 cm filled with Bledug Kuwu’s mud. The eruption source is generated by a compressor pressure that can be controled both the depth(10.5, 13, and 15.5 cm) and the angel of the source (30o, 45o and 60o). The resulting seismic signals were recorded by using 3 vertical component geophones for 10 and 5 seconds durations at a frequency of 2 and 4 kHz respectivel, mud density 1200 kg/m3 . The physical modeling shows that the P-wave velocity of the Bledug Kuwu’s medium is 48.7 m/s, S-wave velocity of Bledug Kuwu’s is 28,14 m/s  with a dominant frequency of 20 to 25 Hz.

scholarly journals Metode Seismik dalam Pemodelan Fisis Letusan Gunung Lumpur Bledug Kuwu

2019 ◽  
Vol 2 (2) ◽  
pp. 61-66
Author(s):  
Ahmad Fauzi Pohan ◽  
Rusnoviandi Rusnoviandi
Keyword(s):  
Wave Velocity ◽  
Physical Modeling ◽  
Vertical Component ◽  
Dominant Frequency ◽  
P Wave ◽  
Physical Parameters ◽  
S Wave ◽  
Interesting Phenomenon ◽  
Central Java ◽  
P Wave Velocity

Bledug Kuwu mud volcano activity in Central Java is an interesting phenomenon to be studied using both physical modeling. The objective of this study was to determine the physical parameters of the medium of Bledug Kuwu. The Physical model was an aquarium with a dimension of 59 × 59 × 37.3 cm filled with Bledug Kuwu’s mud. The eruption source is generated by a compressor pressure that can be controled both the depth(10.5, 13, and 15.5 cm) and the angel of the source  (30o, 45o  and 60o). The resulting seismic signals were recorded by using 3 vertical component geophones for 10 and 5 seconds durations at a frequency of 2 and 4 kHz respectivel, mud density 1200 kg/m3 . The physical modeling shows that the P-wave velocity of the Bledug Kuwu’s medium is 48.7 m/s, S-wave velocity of Bledug Kuwu’s is 28,14 m/s  with a dominant frequency of 20 to 25 Hz.

scholarly journals Interparameter trade-off quantification for isotropic-elastic full-waveform inversion with various model parameterizations

Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. R185-R206 ◽  
Author(s):  
Wenyong Pan ◽  
Kristopher A. Innanen ◽  
Yu Geng ◽  
Junxiao Li
Keyword(s):  
Wave Velocity ◽  
Waveform Inversion ◽  
P Wave ◽  
Physical Parameters ◽  
Full Waveform Inversion ◽  
S Wave ◽  
Trade Off ◽  
Full Waveform ◽  
Trade Offs ◽  
P Wave Velocity

Simultaneous determination of multiple physical parameters using full-waveform inversion (FWI) suffers from interparameter trade-off difficulties. Analyzing the interparameter trade-offs in different model parameterizations of isotropic-elastic FWI, and thus determining the appropriate model parameterization, are critical for efficient inversion and obtaining reliable inverted models. Five different model parameterizations are considered and compared including velocity-density, modulus-density, impedance-density, and two velocity-impedance parameterizations. The scattering radiation patterns are first used for interparameter trade-off analysis. Furthermore, a new framework is developed to evaluate the interparameter trade-off based upon multiparameter Hessian-vector products: Multiparameter point spread functions (MPSFs) and interparameter contamination sensitivity kernels (ICSKs), which provide quantitative, second-order measurements of the interparameter contaminations. In the numerical experiments, the interparameter trade-offs in various model parameterizations are evaluated using the MPSFs and ICSKs. Inversion experiments are carried out with simple Gaussian-anomaly models and a complex Marmousi model. Overall, the parameterization of the P-wave velocity, S-wave velocity, and density, and the parameterization of the P-wave velocity, S-wave velocity, and S-wave impedance perform best for reconstructing all of the physical parameters. Isotropic-elastic FWI of the Hussar low-frequency data set with various model parameterizations verifies our conclusions.

scholarly journals Delineation of Geothermal Manifestation in Sangubanyu Area Based on Microtremor HVSR Method

2019 ◽  
Vol 125 ◽  
pp. 14012
Author(s):  
Dwi Sudarmawan Sudjono ◽  
Udi Harmoko ◽  
Gatot Yuliyanto
Keyword(s):  
Wave Velocity ◽  
Hot Springs ◽  
Amplification Factor ◽  
Hot Spring ◽  
Dominant Frequency ◽  
P Wave ◽  
Normal Faults ◽  
S Wave ◽  
Central Java ◽  
Hvsr Method

The aims of this study is to describe the distribution of P wave velocity and S wave velocity value and Vp/Vs ratio based on microtremor HVSR method and its relationship with the appearance of hot spring at Sangubanyu Village. Geothermal manifestations in the Sangubanyu area are located in Bawang sub-district, Batang regency, and Plantungan sub-district, Kendal regency, Central Java province. HVSR method is used to process microtremor data which produces the dominant frequency value and amplification factor then do inversion on the H/V curve to get the value of the Vp and Vs. The results of the microtremor HVSR processing obtained the distribution of the dominant frequency values in the study area between 0.62 to 0.73 Hz and amplification factor values 1.09 to 1.39, the inversion results on the H/V curve obtained the distribution of Vp values between 131.76 m/s to 2181.19 m/s, Vs values between 76.61 to 1129.42 m/s, Vp/Vs ratio 1.64 – 3.35. Based on the results of the analysis and wave velocity interpretation, the subsurface structure of manifestation area of Sangubanyu is composed of tuffaceous sandstone and volcanic breccia, the normal faults with southern blocks relatively downthrown, that cause the appearance of hot springs.

Using Seismic Data to Predict Shale Pore Pressure and Overpressure Sweet Spots: A Case Study from the Lower Silurian Longmaxi Formation in Sichuan Basin, China

2021 ◽  
Author(s):  
Sheng Chen ◽  
Qingcai Zeng ◽  
Xiujiao Wang ◽  
Qing Yang ◽  
Chunmeng Dai ◽  
...  
Keyword(s):  
Prediction Model ◽  
Wave Velocity ◽  
Shale Gas ◽  
Seismic Data ◽  
P Wave ◽  
Formation Pressure ◽  
S Wave ◽  
P Wave Velocity ◽  
New Formation ◽  
Sweet Spots

Abstract Practices of marine shale gas exploration and development in south China have proved that formation overpressure is the main controlling factor of shale gas enrichment and an indicator of good preservation condition. Accurate prediction of formation pressure before drilling is necessary for drilling safety and important for sweet spots predicting and horizontal wells deploying. However, the existing prediction methods of formation pore pressures all have defects, the prediction accuracy unsatisfactory for shale gas development. By means of rock mechanics analysis and related formulas, we derived a formula for calculating formation pore pressures. Through regional rock physical analysis, we determined and optimized the relevant parameters in the formula, and established a new formation pressure prediction model considering P-wave velocity, S-wave velocity and density. Based on regional exploration wells and 3D seismic data, we carried out pre-stack seismic inversion to obtain high-precision P-wave velocity, S-wave velocity and density data volumes. We utilized the new formation pressure prediction model to predict the pressure and the spatial distribution of overpressure sweet spots. Then, we applied the measured pressure data of three new wells to verify the predicted formation pressure by seismic data. The result shows that the new method has a higher accuracy. This method is qualified for safe drilling and prediction of overpressure sweet spots for shale gas development, so it is worthy of promotion.

Nonlinear two‐dimensional elastic inversion of multioffset seismic data

Geophysics ◽  
1987 ◽  
Vol 52 (9) ◽  
pp. 1211-1228 ◽  
Author(s):  
Peter Mora
Keyword(s):  
Wave Equation ◽  
Wave Velocity ◽  
A Priori ◽  
Gaussian Model ◽  
Wave Impedance ◽  
P Wave ◽  
S Wave ◽  
Elastic Wave Equation ◽  
Gradient Direction ◽  
P Wave Velocity

The treatment of multioffset seismic data as an acoustic wave field is becoming increasingly disturbing to many geophysicists who see a multitude of wave phenomena, such as amplitude‐offset variations and shearwave events, which can only be explained by using the more correct elastic wave equation. Not only are such phenomena ignored by acoustic theory, but they are also treated as undesirable noise when they should be used to provide extra information, such as S‐wave velocity, about the subsurface. The problems of using the conventional acoustic wave equation approach can be eliminated via an elastic approach. In this paper, equations have been derived to perform an inversion for P‐wave velocity, S‐wave velocity, and density as well as the P‐wave impedance, S‐wave impedance, and density. These are better resolved than the Lamé parameters. The inversion is based on nonlinear least squares and proceeds by iteratively updating the earth parameters until a good fit is achieved between the observed data and the modeled data corresponding to these earth parameters. The iterations are based on the preconditioned conjugate gradient algorithm. The fundamental requirement of such a least‐squares algorithm is the gradient direction which tells how to update the model parameters. The gradient direction can be derived directly from the wave equation and it may be computed by several wave propagations. Although in principle any scheme could be chosen to perform the wave propagations, the elastic finite‐ difference method is used because it directly simulates the elastic wave equation and can handle complex, and thus realistic, distributions of elastic parameters. This method of inversion is costly since it is similar to an iterative prestack shot‐profile migration. However, it has greater power than any migration since it solves for the P‐wave velocity, S‐wave velocity, and density and can handle very general situations including transmission problems. Three main weaknesses of this technique are that it requires fairly accurate a priori knowledge of the low‐ wavenumber velocity model, it assumes Gaussian model statistics, and it is very computer‐intensive. All these problems seem surmountable. The low‐wavenumber information can be obtained either by a prior tomographic step, by the conventional normal‐moveout method, by a priori knowledge and empirical relationships, or by adding an additional inversion step for low wavenumbers to each iteration. The Gaussian statistics can be altered by preconditioning the gradient direction, perhaps to make the solution blocky in appearance like well logs, or by using large model variances in the inversion to reduce the effect of the Gaussian model constraints. Moreover, with some improvements to the algorithm and more parallel computers, it is hoped the technique will soon become routinely feasible.

Physical Properties and Structure of the Near Subsurface in the Săcel Area, Romania, from Shallow Seismic Measurements

2019 ◽  
Vol 24 (1) ◽  
pp. 151-158
Author(s):  
Ionelia Panea
Keyword(s):  
Wave Velocity ◽  
Signal To Noise Ratio ◽  
Soil Surface ◽  
Geological Structure ◽  
P Wave ◽  
S Wave ◽  
Sedimentary Deposits ◽  
Shallow Seismic ◽  
P Wave Velocity ◽  
Good Signal

Results are presented for shallow seismic reflection measurements performed southwest of Săcel village in Romania for the purpose of obtaining information about the geological structure in the near subsurface. The P-wave and S-wave velocity distributions were also obtained below the soil surface. The measurements were performed along a nearly linear profile on the top of an elongated hill. Most of the shot gathers were characterized by a good signal-to-noise ratio. A depth-converted migrated section was obtained after the processing of shot gathers, on which an image of sedimentary deposits with various thicknesses, separated by shallow faults until a depth of about 80 m, were observed. The P-wave and S-wave velocity-depth models for two segments were of considerable interest for a geotechnical study proposed for the construction of a windmill park. The two- and three-layered P-wave velocity-depth models were comparable until depths of about 10 m after first-arrival traveltime inversions. The lateral variations in the subsurface geological structure and lithology reflected the variations in the P-wave velocity values from both models. The S-wave velocity-depth models for comparable depth intervals were similar to those from the P-wave velocity-depth models. Reliable S-wave velocity distributions were obtained after inversion of fundamental-mode and higher-mode surface waves.

scholarly journals Determination of vp/vs on Bali Province: Case of Bali Earthquake March 22, 2017

2018 ◽  
Vol 19 (2) ◽  
pp. 73
Author(s):  
Febi Niswatul Auliyah ◽  
Komang Ngurah Suarbawa ◽  
Indira Indira
Keyword(s):  
Case Studies ◽  
Wave Velocity ◽  
P Wave ◽  
S Wave ◽  
Diagram Method ◽  
P Wave Velocity ◽  
Before And After ◽  
Earthquake Data

P-wave velocity and S-wave velocity have been investigated in the Bali Province by using earthquake case studies on March 22, 2017. The study was focused on finding out whether there were anomalies in the values of vp/vs before and after the earthquake. Earthquake data was obtained from the Meteorology, Climatology and Geophysics Agency (BMKG) Region III Denpasar, which consisted of the main earthquake on March 22, 2017 and earthquake data in August 2016 to May 2017. Data was processed using the wadati diagram method, obtained that the vp/vs on SRBI, IGBI, DNP and RTBI stations are shifted from 1.5062 to 1.8261. Before the earthquake occurred the anomaly of the value of vp/vs was found on the four stations, at the SRBI station at 10.35%, at the IGBI station at 16.16%, at DNP station at 12.27% and at RTBI station at 4.62%.

scholarly journals Time–frequency windowing in multiparameter elastic FWI of shallow seismic wavefield

2020 ◽  
Vol 222 (2) ◽  
pp. 1164-1177
Author(s):  
Nikolaos Athanasopoulos ◽  
Edgar Manukyan ◽  
Thomas Bohlen ◽  
Hansruedi Maurer
Keyword(s):  
Wave Velocity ◽  
Time Window ◽  
Mass Density ◽  
Waveform Inversion ◽  
P Wave ◽  
S Wave ◽  
Time Frequency ◽  
Full Waveform ◽  
Shallow Seismic ◽  
P Wave Velocity

SUMMARY Full-waveform inversion of shallow seismic wavefields is a promising method to infer multiparameter models of elastic material properties (S-wave velocity, P-wave velocity and mass density) of the shallow subsurface with high resolution. Previous studies used either the refracted Pwaves to reconstructed models of P-wave velocity or the high-amplitude Rayleigh waves to infer the S-wave velocity structure. In this work, we propose a combination of both wavefields using continuous time–frequency windowing. We start with the contribution of refracted P waves and gradually increase the time window to account for scattered body waves, higher mode Rayleigh waves and finally the fundamental Rayleigh wave mode. The opening of the time window is combined with opening the frequency bandwidth of input signals to avoid cycle skipping. Synthetic reconstruction tests revealed that the reconstruction of P-wave velocity model and mass density can be improved. The S-wave velocity reconstruction is still accurate and robust and is slightly benefitted by time–frequency windowing. In a field data application, we observed that time–frequency windowing improves the consistency of multiparameter models. The inferred models are in good agreement with independent geophysical information obtained from ground-penetrating radar and full-waveform inversion of SH waves.

scholarly journals The Local Earthquake Tomography of Erzurum (Turkey) Geothermal Area

2019 ◽  
Vol 23 (3) ◽  
pp. 209-223 ◽  
Author(s):  
Caglar Ozer ◽  
Mehmet Ozyazicioglu
Keyword(s):  
Wave Velocity ◽  
Seismic Velocity ◽  
Three Dimensional ◽  
P Wave ◽  
Geothermal Area ◽  
S Wave ◽  
Velocity Models ◽  
Local Earthquake Tomography ◽  
P Wave Velocity ◽  
Local Earthquake

Erzurum and its surroundings are one of the seismically active and hydrothermal areas in the Eastern part of Turkey. This study is the first approach to characterize the crust by seismic features by using the local earthquake tomography method. The earthquake source location and the three dimensional seismic velocity structures are solved simultaneously by an iterative tomographic algorithm, LOTOS-12. Data from a combined permanent network comprising comprises of 59 seismometers which was installed by Ataturk University-Earthquake Research Center and Earthquake Department of the Disaster and Emergency Management Authority  to monitor the seismic activity in the Eastern Anatolia, In this paper, three-dimensional Vp and Vp/Vs characteristics of Erzurum geothermal area were investigated down to 30 km by using 1685 well-located earthquakes with 29.894 arrival times, consisting of 17.298 P- wave and 12.596 S- wave arrivals. We develop new high-resolution depth-cross sections through Erzurum and its surroundings to provide the subsurface geological structure of seismogenic layers and geothermal areas. We applied various size horizontal and vertical checkerboard resolution tests to determine the quality of our inversion process. The basin models are traceable down to 3 km depth, in terms of P-wave velocity models. The higher P-wave velocity areas in surface layers are related to the metamorphic and magmatic compact materials. We report that the low Vp and high Vp/Vs values are observed in Yedisu, Kaynarpinar, Askale, Cimenozu, Kaplica, Ovacik, Yigitler, E part of Icmeler, Koprukoy, Uzunahmet, Budakli, Soylemez, Koprukoy, Gunduzu, Karayazi, Icmesu, E part of Horasan and Kaynak regions indicated geothermal reservoir.

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