波场相位相关时移全波形反演  

Wavefield phase correlation shifting full waveform inversion

作　　者：杨贺龙[1] 韩立国[1] 陈雪[1] 

机构地区：[1]吉林大学地球探测科学与技术学院,吉林长春130026

出　　处：《石油物探》2016年第4期568-575,共8页Geophysical Prospecting For Petroleum

基　　金：国家科技重大专项(2011ZX05025-001-04)资助~~

摘　　要：全波形反演(FWI)算法对低频信息和初始模型的依赖比较严重,容易发生周波跳跃现象而陷入局部极小点。为减少周波跳跃现象对全波形反演的影响,提出了波场相位相关时移全波形反演算法,在反演之前对模拟数据进行处理,提高观测数据和模拟数据的匹配程度;同时为减少初始模型对FWI的影响,利用Curvelet变换的多尺度特性,在反演的不同阶段选择不同尺度的数据参与反演,从而改善全波形反演因初始模型误差较大而出现周波跳跃的问题。利用Marmousi模型对波场相位相关时移全波形反演算法进行了测试,结果表明,该反演算法以及利用Curvelet变换多尺度数据参与反演可以明显改善FWI对低频信息和初始模型的依赖,得到较好的反演结果。Full waveform inversion（FWI）is sensitive to low frequency information and initial model and is easy to fall into local minima because of cycle-skipping issue.To reduce the effect of cycle-skipping,we propose wavefield phase correlation shifting FWI method.By processing the simulated data before inversion,we improve the matching degree between observed data and simulated data.We also exploit the multi-scale characteristics of Curvelet transform to reduce the effect of initial model by selecting observed data of different scales information during inversion.Test of frequency-domain FWI based on Marmousi model shows that the inversion result has a better stability,and both of the wavefield phase correlation shifting FWI and the multi-scale Curvelet transform FWI can reduce the dependence of low frequency information and initial model.

关 键 词：频率域全波形反演 波场相位相关 CURVELET变换 多尺度 

分 类 号：P631[天文地球—地质矿产勘探]