scholarly journals Delineation of sedimentary basin structure beneath the Banyumas Basin, Central Java, Indonesia, using ambient seismic noise tomography

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ahmad Setiawan ◽  
Zulfakriza Zulfakriza ◽  
Andri Dian Nugraha ◽  
Shindy Rosalia ◽  
Awali Priyono ◽  
...  
Keyword(s):  
Seismic Noise ◽  
Sedimentary Basin ◽  
Sedimentary Rocks ◽  
Vertical Component ◽  
Seismic Exploration ◽  
Ambient Seismic Noise ◽  
Central Java ◽  
Sediment Deposits ◽  
Cross Correlations ◽  
Grid Points

AbstractSubsurface images of an area with a thick volcanic layer generally cannot be well-imaged with conventional seismic exploration (seismic reflection) due to seismic wave scattering. Another method is needed to obtain an accurate subsurface image in a thick volcanic layer area. In this study, we applied ambient noise tomography (ANT) to image the shear-wave velocity (Vs) structure in the Banyumas Basin, Central Java, Indonesia, which has relatively thick volcanic layers. We aimed to delineate the sediment deposits and the sedimentary thickness in this area through the utilization of ambient seismic noise. The application of cross-correlations from ambient seismic noise has been widely applied in numerous locations to obtain a greater understanding of subsurface structures. In this study, more than 1000 pairs of vertical component cross-correlations were used to estimate the Green's Function of the Rayleigh wave. The Neighbourhood Algorithm (NA) was utilized to invert the dispersion curves at 121 grid points which were used to obtain a vertical depth profile of 1D Vs. The Vs map results show that the low Vs tend to trend in a northwest–southeast direction associated with two areas: the Majenang low, and the Citanduy low. The presence of low Vs values corresponds with Middle Miocene–Pliocene sedimentary rocks. Meanwhile, the high Vs values in this area might correspond with Oligocene–Early Miocene volcanic products and Eocene sediment. Our study was also able to reveal the thickness of sedimentary rocks in the Banyumas sedimentary basin, which is believed to have hydrocarbon potential.

scholarly journals Delineation of Sedimentary Basin Structure beneath the Banyumas Basin, Central Java, Indonesia, Using Ambient Seismic Noise Tomography

2021 ◽  
Author(s):  
Ahmad Setiawan ◽  
Zulfakriza Zulfakriza ◽  
Andri Dian Nugraha ◽  
Shindy Rosalia ◽  
Awali Priyono ◽  
...  
Keyword(s):  
Ambient Noise ◽  
Sedimentary Basin ◽  
Sedimentary Rocks ◽  
Vertical Component ◽  
Dispersion Curves ◽  
Seismic Exploration ◽  
Time Frequency ◽  
Central Java ◽  
Cross Correlations ◽  
Grid Points

Abstract Subsurface images of an area with a thick volcanic layer generally can not be well-imaged with conventional seismic exploration (seismic reflection) due to seismic wave scattering. Another method is needed to obtain an accurate subsurface image in a thick volcanic layer area. In this study, we applied Ambient Noise Tomography (ANT) to image the shear-wave velocity (Vs) structure in the Banyumas Basin, Central Java, Indonesia, which has relatively thick volcanic layers. We aimed to delineate the sediment deposits and the sedimentary thickness in this area. Although this method has limited application for subsurface imaging with a thick volcanic layer area, the application of cross-correlations from ambient noise has been widely applied in numerous locations to obtain greater understanding of subsurface structures. In this study, more than 1,000 pairs of vertical component cross-correlations were used to estimate the Green's Function of the Rayleigh wave. The Multiple Filter Technique (MFT) was used as a Time-Frequency Analysis and 1,291 dispersion curves were obtained. The Neighbourhood Algorithm (NA) was utilized to inverse the dispersion curves at 121 grid points which were used to obtain a vertical depth profile of 1D Vs. The Vs map results show that the low Vs tend to trend in a northwest-southeast direction associated with two areas: the Majenang low, and the Citanduy low. The presence of low Vs values corresponds with Middle Miocene–Pliocene sedimentary rocks. Meanwhile, the high Vs value in this area might correspond with Oligocene–Early Miocene volcanic products and Eocene sediment. Our study was also able to reveal the thickness of sedimentary rocks in the the Banyumas sedimentary basin, which is believed to have hydrocarbon potential.

Shallow Crustal Structure in the DehDasht Region (SW Iran) from Ambient Seismic Noise Tomography

2021 ◽  
Author(s):  
Nastaran Shakeri ◽  
Taghi Shirzad ◽  
Shobeir Ashkpour Motlagh ◽  
Siavash Norouzi
Keyword(s):  
Crustal Structure ◽  
High Velocity ◽  
Seismic Noise ◽  
Seismic Exploration ◽  
Propagation Path ◽  
Ambient Seismic Noise ◽  
Fast Marching Method ◽  
Fast Marching ◽  
Main Challenge ◽  
Sw Iran

<p>Zagros continental collision zone (S-SW Iran) is tectonically active and extends over 1800 km contained most part of hydrocarbon reservoirs worldwide. The DehDasht region is located in the southeast of the Dezful embayment in the Zagros fold-and-thrust belt. The existence of an evaporation layer with high velocity features is the main challenge to apply classical seismic exploration in this region. However, ambient seismic noise carries valuable information about the propagation path; hence it could be a useful tool for studying crustal structure in the DehDasht region. For this purpose, we used up to 9 months of continuous data recorded by 107 stations in the area with ~16 × ~24 km<sup>2</sup>. All stations are equipped with broadband (120s) sensors recording at 100 sps. The standard ambient seismic noise processing was done as outlined by Bensen et al. (2007), and optimize empirical Green’s function (EGF) was retrieved based on the WRMS stacking method. Afterward, Rayleigh wave dispersion measurements were calculated using the FTAN approach in the period range of 0.1-5.0 s, then the inversion procedure was performed by the Fast-Marching Method with an inversion cell size of 2×2 km. Our group velocity tomographic maps show a high velocity anomaly in the Khaviz Mountain belt (west part of the study area) is generally linked to the older, consolidated bodies while two low velocity anomalies are related to the presence of fluids and or younger structures.</p>

Rayleigh group velocity extraction from ambient seismic noise to map the south Eastern Cape Karoo region, South Africa

2017 ◽  
Vol 120 (3) ◽  
pp. 341-350 ◽  
Author(s):  
L.J. Bezuidenhout ◽  
M. Doucouré ◽  
V. Wagener ◽  
M. de Wit ◽  
A. Mordret ◽  
...  
Keyword(s):  
South Africa ◽  
Surface Waves ◽  
Group Velocity ◽  
Seismic Noise ◽  
Vertical Component ◽  
Ambient Seismic Noise ◽  
Seismic Signals ◽  
The South ◽  
Velocity Anomaly ◽  
Rayleigh Surface Waves

Abstract The Karoo region of South Africa is an ideal laboratory to use ambient seismic signals to map the shallow subsurface, as it is a quiet and pristine environment with a geology that is relatively well known. Ambient seismic signals were continuously recorded for a ten week period between August and October 2015. The ambient seismic noise network consisted of two groups of 17 temporary, stand-alone seismic stations each. These were installed in the southeastern Cape Karoo region, near the town of Jansenville. Here we present data on the retrieval and coherency of Rayleigh surface waves extracted from the vertical component recordings. We reconstruct and show, for the first time in the southeastern Cape Karoo, estimates of Green's function from cross-correlating ambient noise data between stations pairs, which can be successfully used to image the subsurface. The stacked cross-correlations between all station pairs show clear arrivals of the Rayleigh surface waves. The group velocities of the Rayleigh waves in the 3 to 7 seconds period range were picked and inverted to compute the 2-D group velocity maps. The resulting 2-D group velocity maps at different periods resulted in a group velocity model from approximately 2 to 7 km depth, which shows a high velocity anomaly in the north of the study area, most likely imaging the denser, thick sedimentary basin of the Karoo (Carboniferous-Permian). To the south, the low velocity anomaly could correspond to the overlying Jurassic-Cretaceous sedimentary sequences of the younger Algoa Basin (Uitenhage Group).

scholarly journals Reflection images from ambient seismic noise

Geophysics ◽  
2009 ◽  
Vol 74 (5) ◽  
pp. A63-A67 ◽  
Author(s):  
Deyan Draganov ◽  
Xander Campman ◽  
Jan Thorbecke ◽  
Arie Verdel ◽  
Kees Wapenaar
Keyword(s):  
Surface Wave ◽  
Green’S Function ◽  
Green's Function ◽  
Seismic Noise ◽  
Seismic Exploration ◽  
Ambient Seismic Noise ◽  
Reflection Data ◽  
Parallel Lines ◽  
Reflection Image ◽  
Sirte Basin

One application of seismic interferometry is to retrieve the impulse response (Green’s function) from crosscorrelation of ambient seismic noise. Various researchers show results for retrieving the surface-wave part of the Green’s function. However, reflection retrieval has proven more challenging. We crosscorrelate ambient seismic noise, recorded along eight parallel lines in the Sirte basin east of Ajdabeya, Libya, to obtain shot gathers that contain reflections. We take advantage of geophone groups to suppress part of the undesired surface-wave noise and apply frequency-wavenumber filtering before crosscorrelation to suppress surface waves further. After comparing the retrieved results with data from an active seismic exploration survey along the same lines, we use the retrieved reflection data to obtain a migrated reflection image of the subsurface.

scholarly journals Seismic exploration-scale velocities and structure from ambient seismic noise (>1 Hz)

2013 ◽  
Vol 118 (8) ◽  
pp. 4345-4360 ◽  
Author(s):  
Deyan Draganov ◽  
Xander Campman ◽  
Jan Thorbecke ◽  
Arie Verdel ◽  
Kees Wapenaar
Keyword(s):  
Seismic Noise ◽  
Seismic Exploration ◽  
Ambient Seismic Noise

scholarly journals Determining OBS clock drift using ambient seismic noise 

2021 ◽  
Author(s):  
David Naranjo ◽  
Laura Parisi ◽  
Philippe Jousset ◽  
Cornelis Weemstra ◽  
Sigurjón Jónsson
Keyword(s):  
Seismic Noise ◽  
Temperature Drop ◽  
Time Lapse ◽  
Ambient Seismic Noise ◽  
Ocean Bottom ◽  
Timing Error ◽  
Clock Drift ◽  
Ocean Bottom Seismometers ◽  
Cross Correlations ◽  
Reykjanes Peninsula

<p>Accurate timing of seismic records is essential for almost all applications in seismology. Wrong timing of the waveforms may result in incorrect Earth models and/or inaccurate earthquake locations. As such, it may render interpretations of underground processes incorrect. Ocean bottom seismometers (OBSs) experience clock drifts due to their inability to synchronize with a GNSS signal (with the correct reference time), since electromagnetic signals are unable to propagate efficiently in water. As OBSs generally operate in relatively stable ambient temperature, the timing deviation is usually assumed to be linear. Therefore, the time corrections can be estimated through GPS synchronization before deployment and after recovery of the instrument. However, if the instrument has run out of power prior to recovery (i.e., due to the battery being dead at the time of recovery), the timing error at the end of the deployment cannot be determined. In addition, the drift may not be linear, e.g., due to rapid temperature drop while the OBS sinks to the seabed. Here we present an algorithm that recovers the linear clock drift, as well as a potential timing error at the onset.</p><p>The algorithm presented in this study exploits seismic interferometry (SI). Specifically, time-lapse (averaged) cross-correlations of ambient seismic noise are computed. As such, virtual-source responses, which are generally dominated by the recorded surface waves, are retrieved. These interferometric responses generate two virtual sources: a causal wave (arriving at a positive time) and an acausal wave (arriving at a negative time). Under favorable conditions, both interferometric responses approach the surface-wave part of the medium's Green's function. Therefore, it is possible to calculate the clock drift for each station by exploiting the time-symmetry between the causal and acausal waves. For this purpose, the clock drift is calculated by measuring the differential arrival times of the causal and acausal waves for a large number of receiver-receiver pairs and computing the drift by carrying-out a least-squares inversion. The methodology described is applied to time-lapse cross-correlations of ambient seismic noise recorded on and around the Reykjanes peninsula, SW Iceland. The stations used for the analysis were deployed in the context of IMAGE (Integrated Methods for Advanced Geothermal Exploration) and consisted of 30 on-land stations and 24 ocean bottom seismometers (OBSs).  The seismic activity was recorded from spring 2014 until August 2015 on an area of around 100 km in diameter (from the tip of the Reykjanes peninsula).</p>

scholarly journals Source location of the 26 sec microseism from cross-correlations of ambient seismic noise

2006 ◽  
Vol 33 (18) ◽  
pp. n/a-n/a ◽  
Author(s):  
N. M. Shapiro ◽  
M. H. Ritzwoller ◽  
G. D. Bensen
Keyword(s):  
Seismic Noise ◽  
Source Location ◽  
Ambient Seismic Noise ◽  
Cross Correlations
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