石油物探2018，Vol.57Issue(2)：254-261,273,9.DOI:10.3969/j.issn.1000-1441.2018.02.011
联合结构张量与运动学反偏移的立体层析数据空间提取与反演策略研究Ⅱ:实践
Inversion strategy and data space extraction for stereo-tomography based on a combination of structure tensor and kinematic demigration, Ⅱ :practice
摘要
Abstract
In stereo-tomographic inversion,diffractions,multiples and side waves have adverse impact upon optimal data space extraction (source position,receiver position,source P parameter,receiver P parameter,travel time).This paper proposes a two-step scheme to counter that.First,Prestack depth migration (PSDM) is implemented using initial velocity.Then,kinematic demigration is implemented to extract the data space parameter.We used a 3D structure tensor,with the 2D pre-stack depth-migrated dataset used as a 3D volume,to obtain residual move-out (RMO) and structural dip for kinematic demigration.For field data,a set of key horizons were selected manually in several select depth-migrated common offset gathers,and these were extrapolated along the offset axis based on the RMO chosen in advance to produce reliable and well-distributed initial high-density data points.Finally,kinematic demigration was implemented to inverse the kinematic information of selected data points to obtain a refined data space for stereo-tomography.We applied the strategy to 2D field data from the South China Sea.A migration velocity model was built based on the data space achieved using the proposed scheme and then PSDM was implemented.The migration results demonstrate that the strategy is effective for achieving best data space for stereo-tomographic inversion.关键词
立体层析反演/三维结构张量/运动学反偏移/两步法/构造倾角/剩余曲率Key words
stereo-tomographic inversion/3D structure tensor/kinematic demigration/two-step scheme/structural dip/residual move-out (RMO)分类
天文与地球科学引用本文复制引用
熊凯,杨锴,邢逢源,叶云飞,薛冬..联合结构张量与运动学反偏移的立体层析数据空间提取与反演策略研究Ⅱ:实践[J].石油物探,2018,57(2):254-261,273,9.基金项目
国家自然科学基金面上项目(41574098和41630964)、国家科技重大专项子课题(2016ZX05026-001-03)联合资助.This research is financially supported by the National Natural Science Foundation of China (Grant Nos.41574098,41630964) and the National Science and Technology Major Project of China (Grant No.2016ZX05026-001-03). （41574098和41630964）
