Investigating the possibility of locating microseismic sources using distributed sensor networks

Junzhe Sun, Tieyuan Zhu, Sergey Fomel, Wen Zhan Song

Research output: Contribution to journalConference articlepeer-review

50 Citations (SciVal)

Abstract

Distributed sensor networks are designed to provide computation in-situ and in real-time. The conventional time-reversal imaging approach for microseismic event location may not be optimal for such an environment. To address this challenge, we develop a methodology of locating multiple microseismic events with unknown start times based on the cross-correlation imaging condition borrowed from active-source seismic imaging. The imaging principle states that a true microseismic source must correspond to the location where all the backward-propagated events coincide in both space and time. Instead of simply stacking the backward-propagated seismic wavefields, as suggested by time-reversal imaging, we perform multiplication reduction to compute a high-resolution microseismicity map. The map has an extra dimension of time, indicating the start times of different events. Combined with a distributed sensor network, our method is designed for monitoring microseismic activities and mapping fracture development during hydraulic fracturing in-situ and in real-time. We use numerical examples to test the ability of the proposed technique to produce high-resolution images of microseismic locations.

Original languageEnglish (US)
Pages (from-to)2485-2490
Number of pages6
JournalSEG Technical Program Expanded Abstracts
Volume34
DOIs
StatePublished - 2015
EventSEG New Orleans Annual Meeting, SEG 2015 - New Orleans, United States
Duration: Oct 18 2011Oct 23 2011

All Science Journal Classification (ASJC) codes

  • Geotechnical Engineering and Engineering Geology
  • Geophysics

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