Continuous surface distributed acoustic sensing for subsurface hydraulic fracturing source localization and near-surface scatterer imaging: A case study in the Caojiatan Mine

ABSTRACT Distributed acoustic sensing (DAS) technology is a high-density seismic data acquisition technology that has developed rapidly in geophysical monitoring. Compared with traditional geophones, DAS offers advantages such as lower cost, higher spatial resolution, and real-time dynamic monitoring, making it a novel approach for hydraulic fracturing source localization and fault zone imaging. Based on the ground surface experimental DAS data from hydraulic fracturing of the underground horizontal wells at the Caojiatan Mine, we develop a DAS-based workflow for hydraulic fracturing microseismic localization and near-surface scatterer imaging. First, various physical methods are used to achieve fracturing event identification and weak P- and S-wave arrivals signal enhancement, targeting the removal of high-frequency and inherent banding noise. Then, we apply the time reversal mirrors (TRM) and multiscale natural migration (NM) approaches to locate the hydrofracture sources and image the shallow scattering structure, respectively, which is not dependent on the velocity model. The TRM method achieves a source localization accuracy exceeding 80%. In addition, in response to the apparent scattered S waves in DAS data and the sensitivity to depth-dependent velocity anomalies, the NM method can effectively image near-surface heterogeneities at approximately one-third of the maximum wavelength. The Caojiatan Mine field data results indicate that continuous surface DAS monitoring provides an efficient and reliable technological solution for downhole source localization and shallow structural imaging, offering significant potential for comprehensive mine monitoring.