Petroleum Science > 2012(2 ) :190-194 DOI:
Optimization of the seismic processing phase-shift plus finite-difference migration operator based on a hybrid genetic and simulated annealing algorithm Open Access
文章信息
作者:Migration operator, phase-shift plus finite-difference, hybrid algorithm, genetic and simulated annealing algorithm, optimization coefficient
作者单位:Luo Renze,Huang Yuanyi,Liang Xianghao,Luo Jun and Cao YingState Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, Sichuan 610500, China;Geophysics Development Department of BGP, Hebei 072751, China;Exploration and Exploitation Department of Tarim Oilfield Company, PetroChina, Korla, Xinjiang 418000, China;Changqing Oilfield Company, PetroChina, Ningxia 750000, China;Changqing Oilfield Company, PetroChina, Ningxia 750000, China
收稿日期:
出版日期:2012-06-18 00:00:00.0
引用方式:
文章摘要
Although the phase-shift seismic processing method has characteristics of high accuracy, good stability, high efficiency, and high-dip imaging, it is not able to adapt to strong lateral velocity variation. To overcome this defect, a finite-difference method in the frequency-space domain is introduced in the migration process, because it can adapt to strong lateral velocity variation and the coefficient is optimized by a hybrid genetic and simulated annealing algorithm. The two measures improve the precision of the approximation dispersion equation. Thus, the imaging effect is improved for areas of high-dip structure and strong lateral velocity variation. The migration imaging of a 2-D SEG/EAGE salt dome model proves that a better imaging effect in these areas is achieved by optimized phase-shift migration operator plus a finite-difference method based on a hybrid genetic and simulated annealing algorithm. The method proposed in this paper is better than conventional methods in imaging of areas of high-dip angle and strong lateral velocity variation.
英文关键词
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Migration operator, phase-shift plus finite-difference, hybrid algorithm, genetic and simulated annealing algorithm, optimization coefficient