Fault identification based on multichannel adaptive waveforms matching pursuit
Deng Zhiwen1, Zhao Xianzheng2, Chen Yuhong3, Bai Xuming1, Fang Haifei1, Zhang Zheng1
1. BGP Inc., CNPC, Zhuozhou, Hebei 072751, China;
2. Dagang Oilfield Company, PetroChina, Dagang, Tianjin 300280, China;
3. Lanzhou Center of Oil and Gas Resources, Institute of Geology and Geophysics, CAS, Lanzhou, Gansu 730000, China
Abstract：In oil and gas exploration,coherence cube attributes are most used to identify faults. But this will introduce sometimes a variety of illusions and lost some useful information. In this paper,we propose a new approach of fault identification to avoid the problems. Seismic data can be represented as a sum of multi-group local plane waves (continuous reflection),discontinuous reflections,and random noises. An extraction of continuous reflection information from the sum would enhance discontinuous geological information. First,the coherence scanning is used to obtain initial information,like number of event groups,apparent dips of two directions of each group,arrival time and delay time,etc. Then objective functions are founded,and waveforms of continuous event group are obtained by inversion. Therefore waveforms obtained by the inversion have clearer physical meanings since atom dictionaries would not be set in advance. This approach can be regarded as multichannel matching pursuit. Real data tests demonstrate lots of benefits of the proposed approach. On one hand,since the extraction of continuous reflection information eliminate illusions caused by the interference of event groups,residual data volumes show better discontinuous linear geological features of twist events and more details (large-angle waves from fault surface) than conventional coherence cube. On the other hand,coherence cubes extracted from continuous reflection data volumes are clearer and with less noise than conventional data volumes,more reasonable fault combinations can also be identified.
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