The main type of oil reservoir in Bohai A oilfield is fault reservoir,and high-precision fault identification is great significance for the deployment and optimization of development wells in A oilfield.However,the existing seismic data in oilfield A has poor quality and cannot be used for precise fault identification,which seriously affecting the deployment and optimization of oilfield development wells.This article optimizes the fault detection process to achieve precise characterization of faults.The original seismic data is processed by structure-oriented filtering,which effectively preserves the edge information of the event while suppressing random noise;The high precision three-parameter wavelet transform is used to perform frequency division processing on the denoised seismic data;The data volume with a center frequency slightly higher than the main frequency of the original seismic data is selected for coherent operation to obtain a high-precision fault detection data volume.The comparative analysis results with the original coherent data show that the method proposed in this paper can effectively improve the accuracy of fault identification in Bohai A oilfield,providing effective guidance for well deployment and optimization.
structure-oriented filteringthree-parameter wavelet transformfrequency division coherencefault fine identificationBohai A oilfield
万方数据
维普
