Comparison of migration‐based location and detection methods for microseismic events

Abstract

Microseismic monitoring in the oil and gas industry commonly uses migration‐based methods to locate very weak microseismic events. The objective of this study is to compare the most popular migration‐based methods on a synthetic dataset that simulates a strike‐slip source mechanism event with a low signal‐to‐noise ratio recorded by surface receivers (vertical components). The results show the significance of accounting for the known source mechanism in the event detection and location procedures. For detection and location without such a correction, the ability to detect weak events is reduced. We show both numerically and theoretically that neglecting the source mechanism by using only absolute values of the amplitudes reduces noise suppression during stacking and, consequently, limits the possibility to retrieve weak microseismic events. On the other hand, even a simple correction to the data polarization used with otherwise ineffective methods can significantly improve detections and locations. A simple stacking of the data with a polarization correction provided clear event detection and location, but even better results were obtained for those data combined with methods that are based on semblance and cross‐correlation.

Microseismic Monitoring of Stimulating Shale Gas Reservoir in SW China: 1. An Improved Matching and Locating Technique for Downhole Monitoring

“…The migration‐based technique, also known as the source‐scanning algorithm (SSA), detects events based on the stacked energy of a characteristic function (e.g., envelope and Short‐time average over long‐time average (STA/LTA) function of continuous waveforms) over gridded potential source locations and origin times (Gharti et al, ; Grigoli et al, , ; Kao & Shan, ; Liao et al, ). It provides robust location estimates of microseismic events even in the presence of strong ambient noise and thereby has been extensively used in surface microseismic monitoring (Drew et al, ; Pesicek et al, ; Trojanowski & Eisner, ). Nevertheless, it is still subject to high false alarm rates, and the location accuracy strongly depends on the local velocity structure.…”

Recent Advances and Challenges of Waveform‐Based Seismic Location Methods at Multiple Scales

“…Seismic source location is the most crucial step of microseismic processing, and it is needed for subsequent source mechanism inversion and geomechanical analysis. A multitude of studies have been dedicated to the improvement of waveform‐based microseismic location during the past decade (e.g., Anikiev et al, ; Cesca & Grigoli, ; Trojanowski & Eisner, ; L. Li et al, ; Diekmann et al, ; see also Table for a more representative list of references). The main motivation of these studies is to improve locations of the weak microseismic events as the Gutenberg‐Richter (Gutenberg & Richter, ) empirical law implies exponential increase of the number of events if we can locate weaker events.…”

“…Cesca and Grigoli () investigated the location performance of different CFs with both synthetic and field mining‐induced seismicity and concluded that kurtosis traces are sensitive with respect to noise, envelope traces produce more stable results but lower imaging resolution, and STA/LTA traces have a better overall performance of location resolution and noise resistance. Trojanowski and Eisner () tested the performance of several CFs with diffraction stacking and cross‐correlation stacking operators, showed the semblance and cross‐correlation stacking have better enhancement of the quality of the stacking profiles, and demonstrated that accounting for the source mechanism by polarization correction improves most efficiently the capability of noise suppression and retrieving weak microseismic events. Beskardes et al () compared the performance of envelope, STA/LTA, and kurtosis with raw waveforms for local earthquakes detection and location.…”

“…One potential solution is adding perturbations to the theoretical traveltime table. Given the short development course of waveform‐based methods and the difference of location uncertainty estimation between the two types of methods, more systematic benchmarking studies of seismic source location algorithms are in demand, though several recent comparisons of microseismic waveform‐based and traveltime‐based location algorithms can be found in recent literature (e.g., Pesicek et al, ; Trojanowski & Eisner, ; L. Li et al, ; Wuestefeld et al, ; Grigoli, Scarabello, et al, ). Note that full waveform‐based methods have more sources of uncertainty from, for example, density, S wave velocity, and attenuation models.…”

“…Cross‐correlation stacking shares the same principle of exploiting differential traveltimes at pair‐wise stations from common events, with master‐station method and station‐pair method mentioned above. This method has been applied to microseismic monitoring in the oil and gas industry (Eisner et al, ; Grandi & Oates, ; L. Li et al, ; Trojanowski & Eisner, ; Shi et al, ), volcanic tremor data (Droznin et al, ; K. L. Li et al, ; K. L. Li et al, ), mining‐induced seismicity (Dales, ; L. Li et al, ), and slow (tectonic tremor and low‐frequency earthquakes) and regular earthquake (Poiata et al, ; Ruigrok et al, ; Shi et al, ). In this study, we will call it interferometric‐type method.…”