4.7 Review

Research Developments and Prospects on Microseismic Source Location in Mines

Journal

ENGINEERING
Volume 4, Issue 5, Pages 653-660

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.eng.2018.08.004

Keywords

Microseismic source location; Influencing factors; Time-reversal imaging; Research progress; Prospects for development

Funding

  1. National Key Research and Development Program of China [2016YFC0801405, 2017YFC0804105]
  2. National Natural Science Foundation of China [51574250]

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Microseismic source location is the essential factor in microseismic monitoring technology, and its location precision has a large impact on the performance of the technique. Here, we discuss the problem of low-precision location identification for microseismic events in a mine, as may be obtained using conventional location methods that are based on arrival time. In this paper, microseismic location characteristics in mining are analyzed according to the characteristics of the mine's microseismic wavefield. We review research progress in mine-related microseismic source location methods in recent years, including the combination of the Geiger method with the linear method, combined microseismic event location method, optimization of relative location method, location method without pre-measured velocity, and location method without arrival time picking. The advantages and disadvantages of these methods are discussed, along with their feasible conditions. The influences of geophone distribution, first arrival time picking, and the velocity model on microseismic source location are analyzed, and measures are proposed to influence these factors. Approaches to solve the problem under study include adopting information fusion, combining and optimizing existing methods, and creating new methods to realize high-precision microseismic source location. Optimization of the velocity structure, along with applications of the time-reversal imaging technique, passive time-reversal mirror, and relative interferometric imaging, are expected to greatly improve microseismic location precision in mines. This paper also discusses the potential application of information fusion and deep learning methods in microseismic source location in mines. These new and innovative location methods for microseismic source location have extensive prospects for development. (C) 2018 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company.

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