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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Beiyuan Liang,Jianli Wang
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DOI:10.17265/2162-5298/2026.04.003
GeoImage LLC, San Francisco, 94118, USA
The two important characteristics of microseismic are: tiny, and rupture with mainly shear dislocation mechanism. The monitoring characteristics obtained by the features are: often the signal-to-noise ratio is <1 from a few hundred meters away so that the traditional location fails, one dislocated hypocenter radiates longitudinal and transverse waves into space, and the amplitude and polarity of the waves change with different directions. This is the essence or first principle of microseismic monitoring. Based on previous overview of the current status of microseismic monitoring, this article analyzes the specific reasons why many microseismic monitoring efforts have not made breakthrough progress, and provides corresponding solutions. We can find that many people: (1) adhere to traditional relocation, such as relying on borehole proximity monitoring, or sustain but effectively-limited denoising, but fail to coexist with the residual noise after effective denoising, and implement DMS (data migration and stacking) to discover the microseismic information implied in the noise. (2) Simply use DMS, but the seismic wave vectors are not (correctly) extracted from the 3-component records, based on the far-field displacements generated by the shear force couple at a hypocenter, especially the shear wave vectors SV and SH with large amplitude, slow attenuation, and propagating far distance. And (3) ignore that the wave arrival amplitude and polarity at different receiving places are functions of the coming direction of an earthquake, that is, the focal mechanism of passive or natural earthquakes, the stress-strain constitutive relationship in elastic mechanics, and the Anderson discussion in tectonic geology or rock mechanics, which should be used to guide the whole process of DMS and microseismicity interpretation, and which may be generally called as the equivalent microseismic focal mechanism. These problems are evident in the detections of surface, borehole, mine safety, inversion for velocity models, and small earthquake precursors before destructive earthquakes. This paper takes the research and development of VS (Vector Stacking) as an example, based on the characteristics of far-field microseismic monitoring, to illustrate how to solve the above problems. In order to ensure the reliability of microseismic monitoring with high probability, and the establishment of expert systematic automation, many necessary conditions have to be followed. VS greatly expands the distance range and improves the quality of microseismic monitoring. It can also unify data processing and interpretation of both S/N > 1 and <1 using the spatiotemporal distribution of seismically released energy. It has paved the way for microseismologists to develop microseismology, including microseismometry, study the microseismicity, and apply microseismic monitoring in energy field and earthquake forecast.
Microseismic, microseismometry, signal-to-noise-ratio, vector-processing, focal- mechanism.
Beiyuan Liang,Jianli Wang.Far-Field Microseismic Monitoring—Low Signal-to-Noise Ratio, Wave Vector Extraction, and Equivalent Focal Mechanism.
Journal of Environmental Science and Engineering A 15 (2026) 139-150
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