石油物探2018，Vol.57Issue(3)：404-418,15.DOI:10.3969/j.issn.1000-1441.2018.03.010
高效逆时偏移角度道集生成方法研究
Efficient generation of reverse time migration angle gathers
摘要
Abstract
Angle domain common image gathers(ADCIGs) are the high-dimensional forms for the result of prestack depth migration,and very important for further reservoir characterization.Efficiency and fidelity are the focus aspects on the generation of ADCIGs.For generation of RTM-ADCIGs,two methods were reviewed,namely direction vector-based method and local wavefield decomposition method.Direction vector based method is efficient,but it is too sensitive to noise and difficult to handle the overlapping events.Moreover,its output gathers are mostly with low qualities if no additional regularizations are applied.Local wavefield decomposition method generates high-quality gathers,but with low efficiency.In view of the situation,a hybrid approach is proposed for obtaining the common image gathers based on RTM.Firstly,the wavefront orientations are obtained by local wavefield decompositions.Then,the Poynting vectors are used to determine propagation directions and to achieve a good compromise between the efficiency and quality.The eigenvalues of structure tensor are used to identify the wavefield overlapping events.In the region of overlapping wavefronts,the hybrid method is employed to extract one or more local plane wavefield.In other regions,the propagation directions are calculated by means of efficient direction vector-based method to further improve the efficiency.Tests on Sigsbee model and layered model data showed that this approach can generate ADCIGs efficiently with high accuracy and high fidelity.关键词
逆时偏移/角度道集/坡印廷矢量/局部平面波分解/结构张量Key words
RTM/angle gathers/Poynting vector/local wavefield decomposition/structure tensor分类
天文与地球科学引用本文复制引用
吴成梁,周阳,胡江涛,王华忠,孙荣..高效逆时偏移角度道集生成方法研究[J].石油物探,2018,57(3):404-418,15.基金项目
国家自然科学基金(41774126)和国家科技重大专项(2016ZX05024-001,2016ZX05006-002)联合资助.This research is financially supported by the Natural Science Foundation of China(Grant No.41774126) and the National Science and Technology Major Project of China (Grant Nos.2016ZX05024-001,2016ZX05006-002). （41774126）
