Pre-stack-texture-based reservoir characteristics and seismic facies analysis
Song Cheng-Yun1, Liu Zhi-Ning1, Cai Han-Peng2, Qian Feng1, and Hu Guang-Min2
1. School of Communication and Information Engineering, University of Electronic and Technology of China, Chengdu 610000, China.
2. School of Resources and Environment, University of Electronic and Technology of China, Chengdu 610000, China.
Abstract：
Seismic texture attributes are closely related to seismic facies and reservoir characteristics and are thus widely used in seismic data interpretation. However, information is mislaid in the stacking process when traditional texture attributes are extracted from post-stack data, which is detrimental to complex reservoir description. In this study, pre-stack texture attributes are introduced, these attributes can not only capable of precisely depicting the lateral continuity of waveforms between different reflection points but also reflect amplitude versus offset, anisotropy, and heterogeneity in the medium. Due to its strong ability to represent stratigraphics, a pre-stack-data-based seismic facies analysis method is proposed using the self-organizing map algorithm. This method is tested on wide azimuth seismic data from China, and the advantages of pre-stack texture attributes in the description of stratum lateral changes are verified, in addition to the method’s ability to reveal anisotropy and heterogeneity characteristics. The pre-stack texture classification results effectively distinguish different seismic reflection patterns, thereby providing reliable evidence for use in seismic facies analysis.
Song Cheng-Yun,Liu Zhi-Ning,Cai Han-Peng et al. Pre-stack-texture-based reservoir characteristics and seismic facies analysis[J]. APPLIED GEOPHYSICS, 2016, 13(1): 69-79.
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2016, Vol. 13 
