Coherent attribute enhanced fault recognition method based on histogram homogenization
Qing Zhou, Rui Wu, Chengcheng Xu, Yong Chen · 2024
It is difficult to identify small faults in structural interpretation, especially in the area where the formation occurrence changes greatly and the signal-to-noise ratio of seismic data is low. The common fault identification method is mainly coherent attribute, and the influence of formation dip must be taken into account when calculating the coherent body when the formation occurrence changes greatly, while the low signal-to-noise ratio of seismic data will cause the formation dip cannot be accurately obtained. On the other hand, the seismic response of small faults is weak, and the noise resistance of conventional coherence algorithm is low, which is not conducive to the identification of small faults. To solve this problem, a coherent enhanced small fault identification method based on analytic channel with horizon constraint is proposed. Firstly, the similar coherence algorithm is improved by using the analytic channel, and the analysis time window is used to calculate the similar coherence attribute based on the analytic channel, and then the histogram homogenization technique is introduced to enhance the response of the small fault attribute and improve the identification ability of the small fault. The method was applied to the Dongying Formation reservoir of C oilfield in Bohai Sea, China, and three small faults were identified in the oilfield, which solved the problem of inconsistent oilwater interface and reduced the development risk.