摘要：Passive source location estimation technology plays an extremely important role in microseismic monitoring. However, the energy of microseismic signals is generally weak and prone to be interrupted as noise, which will affect the detection and location accuracy of microseismic events. Besides, the existing wave-equation-based source location estimation methods are not suitable for strongly heterogeneous strata, such as faults, salt bodies, fractures filled with proppant and other fluids, etc. These complex geological structures often trigger scattered waves. Thus, based on scattering theory, a high-resolution microseismic source location estimation method with a new grouping imaging condition is proposed by implementing a contrast source numerical simulation method in the process of wavefield backpropagation. First, the contrast source algorithm is used to perform wavefield extrapolation by solving the Helmholtz equation in the frequency domain, which can provide more comprehensive, effective information to get high-precision locations. Moreover, an optimized grouping imaging condition is proposed, which can improve the imaging resolution and computational efficiency. The effectiveness of the method we propose is illustrated using numerical examples. Compared with traditional source location estimation methods, including with low signal-to-noise ratio or multisource location estimation, this method results in strong energy focusing achieved in an effecient manner.

关键字：Image processing; Numerical modelling; Wave propagation

ISSN号：0956-540X

卷、期、页：卷232 期1 页548-568

发表日期：2022-10-03

影响因子：2.934100

期刊分区（SCI为中科院分区）：三区

收录情况：SCI（科学引文索引印刷版）,地学领域高质量科技期刊分级目录（国外T2）,EI（工程索引）,SCIE（科学引文索引网络版）

发表期刊名称：GEOPHYSICAL JOURNAL INTERNATIONAL

参与作者：黄广谭

通讯作者：魏书映

第一作者：陈小宏,李景叶,马继涛

论文类型：期刊论文

论文概要：魏书映,陈小宏,李景叶,马继涛,黄广谭，A high-resolution microseismic source location method based on contrast source algorithm，GEOPHYSICAL JOURNAL INTERNATIONAL，2022，卷232 期1 页548-568

论文题目：A high-resolution microseismic source location method based on contrast source algorithm