Minimum semblance weighted stacking with polarity correction for surface microseismic data processing

Abstract

Diffraction-stack-based algorithms are the most popular microseismic location methods for surface microseismic data. They can accommodate microseismic data with low signal-to-noise ratio by stacking a large number of traces. However, changes in waveform polarity across the receiver line due to source mechanisms may prevent stacking methods from locating the true source. Imaging functions based on simple stacks have low resolution, producing large uncertainty in the final location result. To solve these issues, we introduce a minimum semblance weighted stacking method with polarity correction, which uses an amplitude trend least-squares fitting algorithm to correct the polarity across the receiver line. We adapt the semblance weighted stacking for better coherency measure to improve the imaging resolution. Moreover, the minimum semblance is used to further improve the resolution of location results. Application to both synthetic and real data sets demonstrates good performance of our proposed location method.

A Novel Polarity Correction Method Developed on Cross Correlation Analysis for Downhole Migration-Based Location of Microseismic Events

“…However, the waveform polarity corrected either by focal mechanism estimation or by artificial intelligence methods can considerably increase the computational cost. Recently, Xu et al presented an amplitude trend least-squares fitting approach to correct the polarity changes for surface monitoring with regular recording arrays [37,38]. Kim et al determined the P-wave first-motion polarity by using cross correlation analysis between two different waveforms [39].…”