摘要
Marchenko地震成像通过求解Marchenko方程重构完整的单程格林函数来对地下反射界面成像,能压制常规成像方法中的层间多次波偏移假像,且该成像方法可以仅对指定的目标区域成像。速度模型的正确与否会影响成像点到地面的直达波估计,从而导致求解Marchenko方程得到的单程格林函数不精确,影响最终的Marchenko成像结果。针对该问题,本文基于等旅行时原则提出了自适应走时校正的Marchenko成像方法。该成像方法基于等时原则计算速度模型不准确引起的直达波旅行时时差偏移量,并根据该偏移量直接校正不正确的直达波,重构正确的格林函数,从而使得成像结果在一定程度上不受错误速度模型的影响,提高了在速度模型不准确情况下的Marchenko成像质量。通过合成数据测试实验,对比分析了常规Marchenko成像和改进的Marchenko成像的结果,验证了在速度模型不正确的情况下,自适应走时校正的Marchenko成像方法能在一定程度上将地震波场归位,得到相对正确的地质结构。
Marchenko imaging obtains the subsurface reflectors using one-way Green’s functions,which are retrieved by solving the Marchenko equation.This method generates an image that is free of spurious artifacts due to internal multiples.The Marchenko imaging method is a target-oriented technique;thus,it can image a user specified area.In the traditional Marchenko method,an accurate velocity model is critical for estimating direct waves from imaging points to the surface.An error in the velocity model results in the inaccurate estimation of direct waves.In turn,this leads to errors in computation of one-way Green’s functions,which then affects the final Marchenko images.To solve this problem,in this paper,we propose a self-adaptive traveltime updating technique based on the principle of equal traveltime to improve the Marchenko imaging method.The proposed method calculates the time shift of direct waves caused by the error in the velocity model,and corrects the wrong direct wave according to the time shift and reconstructs the correct Green’s functions.The proposed method improves the results of imaging using an inaccurate velocity model.By comparing the results from traditional Marchenko and the new method using synthetic data experiments,we demonstrated that the adaptive traveltime updating Marchenko imaging method could restore the image of geological structures to their true positions.
作者
陈小春
胡叶正
黄旭日
张厚柱
曹卫平
徐云贵
唐静
Chen Xiao-Chun;Hu Ye-Zheng;Huang Xu-Ri;Zhang Hou-Zhu;Cao Wei-Ping;Xu Yun-Gui;Tang Jing(State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation,Southwest Petroleum University,Chengdu 610500,China;School of Geosciences and Technology,Southwest Petroleum University,Chengdu 610500,China;Aramco Services Company,Houston Research Center,Houston,Texas,USA)
基金
supported by the National Natural Science Foundation of China(No.41874167)
the National Science and Technology Major Project of China(No.2017YFB0202904)
the National Natural Science Foundation of China(No.41904130)。