Meng, Xiao-BoChen, Hai-ChaoNiu, Feng-LinDu, Yi-Jing2023-01-272023-01-272022Meng, Xiao-Bo, Chen, Hai-Chao, Niu, Feng-Lin, et al.. "Master event based backazimuth estimation and its application to downhole microseismic monitoring." <i>Petroleum Science,</i> 19, no. 6 (2022) Elsevier: 2675-2682. https://doi.org/10.1016/j.petsci.2022.06.002.https://hdl.handle.net/1911/114243Microseismic monitoring provides a valuable tool for evaluating the effectiveness of hydraulic fracturing operations. However, robust detection and accurate location of microseismic events are challenging due to the low signal to noise ratio (SNR) of their signals on seismograms. In a downhole monitoring setting, P-wave polarization direction measured from 3-component records is usually considered as the backazimuth of the microseismic event, i.e., the direction of the event. The direction and arrival time difference between the P and S waves is used to locate the seismic event. When SNR is low, an accurate estimate of event backazimuth becomes very challenging with the traditional covariance matrix method. Here we propose to employ a master event and use a grid search method to find the backazimuth of a target event that maximizes the dot product of the two backazimuthal vectors of the master and target events. We compared the backazimuths measured with the proposed grid-search and the conventional covariance-matrix methods using a large synthetic dataset. We found that the grid-search method yields more accurate backazimuth estimates from low SNR records when measurements are made at single geophone level. When array data are combined, the proposed method also has some advantage over the covariance-matrix method, especially when the number of geophones is low. We also applied the method to a microseismic dataset acquired by a hydraulic fracturing project at a shale play site in southwestern China and found that the relocated microseismic events tend to align along existing faults more tightly than those in the original catalog.engThis is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Journal article1-s2-0-S1995822622001339-mainhttps://doi.org/10.1016/j.petsci.2022.06.002