Comparison of High-resolution P- and SH-wave Reflection Seismic Data in Alluvial and Pyroclastic Deposits in Indonesia

Author(s):  
C.M. Krawczyk ◽  
W. Wiyono ◽  
U. Polom
2013 ◽  
Vol 167 ◽  
pp. 72-83 ◽  
Author(s):  
J.S. L'Heureux ◽  
M. Long ◽  
M. Vanneste ◽  
G. Sauvin ◽  
L. Hansen ◽  
...  

2020 ◽  
Author(s):  
Hao Zhang ◽  
Jianguang Han ◽  
Heng Zhang ◽  
Yi Zhang

<p>The seismic waves exhibit various types of attenuation while propagating through the subsurface, which is strongly related to the complexity of the earth. Anelasticity of the subsurface medium, which is quantified by the quality factor Q, causes dissipation of seismic energy. Attenuation distorts the phase of the seismic data and decays the higher frequencies in the data more than lower frequencies. Strong attenuation effect resulting from geology such as gas pocket is a notoriously challenging problem for high resolution imaging because it strongly reduces the amplitude and downgrade the imaging quality of deeper events. To compensate this attenuation effect, first we need to accurately estimate the attenuation model (Q). However, it is challenging to directly derive a laterally and vertically varying attenuation model in depth domain from the surface reflection seismic data. This research paper proposes a method to derive the anomalous Q model corresponding to strong attenuative media from marine reflection seismic data using a deep-learning approach, the convolutional neural network (CNN). We treat Q anomaly detection problem as a semantic segmentation task and train an encoder-decoder CNN (U-Net) to perform a pixel-by-pixel prediction on the seismic section to invert a pixel group belongs to different level of attenuation probability which can help to build up the attenuation model. The proposed method in this paper uses a volume of marine 3D reflection seismic data for network training and validation, which needs only a very small amount of data as the training set due to the feature of U-Net, a specific encoder-decoder CNN architecture in semantic segmentation task. Finally, in order to evaluate the attenuation model result predicted by the proposed method, we validate the predicted heterogeneous Q model using de-absorption pre-stack depth migration (Q-PSDM), a high-resolution depth imaging result with reasonable compensation is obtained.</p>


Geophysics ◽  
1994 ◽  
Vol 59 (5) ◽  
pp. 753-765 ◽  
Author(s):  
J. S. Kim ◽  
Wooil M. Moon ◽  
Ganpat Lodha ◽  
Mulu Serzu ◽  
Nash Soonawala

The high‐resolution reflection seismic technique is being used increasingly to address geologic exploration and engineering problems. There are, however, a number of problems in applying reflection seismic techniques in a crystalline rock environment. The reflection seismic data collected over a fractured crystalline rock environment are often characterized by low signal‐to‐noise ratios (S/N) and inconsistent reflection events. Thus it is important to develop data processing strategies and correlation schemes for the imaging of fracture zones in crystalline rocks. Two sets of very low S/N, high‐resolution seismic data, previously collected by two different contractors in Pinawa, Canada, and the island of Äspö, Sweden, were reprocessed and analyzed, with special emphasis on the shallow reflection events occurring at depths as shallow as 60–100 m. The processing strategy included enhancing the signals hidden behind large‐amplitude noise, including clipped ground roll. The pre‐ and poststack processing includes shot f-k filtering, residual statics, careful muting after NMO correction, energy balance, and coherency filtering. The final processed seismic sections indicate that reflected energy in these data sets is closely related to rock quality in Äspö data and fracturing in Atomic Energy of Canada, Ltd. (AECL) data. The lithologic boundaries are not clearly mappable in these data. When thickness of the reflection zone is of the order of a wavelength, the top and bottom of the zone may be resolved. The major fracture zones in crystalline rocks correlate closely with the well‐log data and are usually characterized by very low velocity and produce low‐acoustic‐impedance contrasts compared to those of surrounding rocks. Because the incidence angles vary rapidly for shallow‐reflection geometries, segments of major fracture zones can effectively be analyzed in terms of reflectivity. Reflection images of each fracture zone were investigated in the common‐offset section, where each focused event was associated with a consistent incidence angle on the reflectivity map. The complex attributes of the data indicate that strong reflectors at shallow depth coincide with intensely fractured zones. These correlate well with instantaneous amplitude plots and instantaneous frequency plots. The instantaneous phase plot also identifies the major and minor fractures.


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