Hydraulic fracturing distributed acoustic sensing monitoring data source mechanism inversion: A Hessian-based method

Abstract

Distributed acoustic sensing (DAS) microseismic monitoring during hydraulic fracturing provides microseismic data with high spatial samplings for fracturing zones. However, sources located perpendicular to the single horizontal well of the DAS acquisition system have limited source-receiver geometries with extremely poor azimuthal coverage, resulting in high uncertainty in source mechanism inversion. To address this problem, we introduce the Hessian matrix, which governs the blurring effect caused by the source-receiver geometry, into the DAS microseismic source mechanism inversion. Our Hessian-based source mechanism inversion method consists of three main steps: (1) construct the Hessian matrix of the source mechanism based on the source-receiver geometry, (2) obtain an initial source mechanism using a conventional source mechanism inversion method, and (3) update the initial source mechanism using a Hessian-based [Formula: see text]-regularized least-squares algorithm. We assess the robustness of our method using synthetic DAS microseismic data with the consideration of noise, source location error, and different regularization parameters, and we compare the results with those of the conventional method. The results demonstrate that the Hessian-based method has a remarkable ability to mitigate the blurring effect of the Hessian matrix caused by limited DAS source-receiver geometry with poor azimuthal coverage, thereby reducing the uncertainty of the inverted source mechanism even in the presence of real noise and/or source location error. Finally, we use our method to invert the source mechanism of a real DAS microseismic event acquired during hydraulic fracturing. Our Hessian-based method provides low uncertainty in the source mechanism inversion of the real DAS microseismic data.