An improved one-step 3D CRS stacking method based on hybrid optimization algorithm
SUN Xiaodong1,2, HOU Mengrui1, REN Lijuan3, WANG Weiqi1, LI Zhenchun1
1. Key Laboratory of Deep Oil & gas, China University of Petroleum(East China), Qingdao, Shandong 266580, China; 2. Shandong Provincial Key Laboratory of Reservoir Geology, China University of Petroleum(East China), Qingdao, Shandong 266580, China; 3. Nanhai Western Petroleum Research Institute, Zhanjiang Branch, CNOOC, Zhanjiang, Guangdong 524000, China
Abstract:Common reflection surface (CRS) stacking makes full use of seismic data within the range of a Fresnel radius, and maximizes the signal-to-noise ratio without reducing the resolution. It is a po-werful imaging means of the seismic data with low signal-to-noise ratio. At the same time, CRS stacking takes into account the inclination and local curvature of the underground reflector, so the imaging accuracy is higher. In conventional three-dimensional CRS stacking, the accuracy of the eight parameters obtained sequentially in multiple steps is low, and affects the final stacking effect. We propose a one-step three-dimensional CRS stacking strategy which combines the rapid search of genetic algorithm and the global convergence of simulated annealing algorithm. It uses a multi-group hierarchical hybrid parallel optimization algorithm that mixes the two algorithms, that is, a thermal slot method is used to generate initial population in the top layer, the middle layer executes a parallel genetic iterative algorithm to achieve population evolution, and the bottom layer uses a simulated annealing algorithm to achieve global optimization, and the genetic and simulated annealing hybrid algorithm is used for hierarchical parallel computing. The CRS stacking method and the design of the hybrid algorithm significantly improve the optimization cost and accuracy of parameters. Tests on real data have verified the practicability of the one-step 3D CRS stacking method.
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