Uncertainty in surface microseismic monitoring

Mueller, Mike; Thornton, Michael; Eisner, Leo

doi:10.1071/aseg2013ab320

Cited by 5 publications

(2 citation statements)

References 6 publications

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“…To signal detection, the function D must exceed a certain threshold. The threshold is chosen by the user, and it was shown by Thornton and Eisner (2011) that a threshold should be at least three times higher than the noise level of the detection function D to avoid a high number of false detections. The origin time is the time sample at which the maximum value of the D function is found.…”

Section: Migration-based Detection and Locationmentioning

confidence: 99%

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

Trojanowski

Eisner

2016

Geophysical Prospecting

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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.

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Section: Migration-based Detection and Locationmentioning

confidence: 99%

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

Trojanowski

Eisner

2016

Geophysical Prospecting

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“…However, the surface monitoring for SSA may encounter some uncertainty challenges, such as low S/R and polarity reversal. Because of the weak energy of the microseismic event and strong attenuation of shallow weathering layers, the S/N of the recordings may be such small that the estimation of the final location is affected severely (Eisner et al, 2009;Thornton et al, 2011). In the diffraction stacking based methods, the problem of changing polarities (due to the radiation pattern of source mechanism) remains unavoidable.…”

Section: Introductionmentioning

confidence: 99%

Automatic microseismic stacking location with a multi-cross-correlation imaging condition

Yuan¹,

Zhang²,

Zhang³

2020

Preprint

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Back‐projection stacking of P‐ and S‐waves to determine location and focal mechanism of microseismic events recorded by a surface array

Vlček

Fischer

Vilhelm

2015

Geophysical Prospecting

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A B S T R A C TWe present an automatic method of processing microseismic data acquired at the surface by a star-like array. The back-projection approach allows successive determination of the hypocenter position of each event and of its focal mechanisms. One-component vertical geophone groups and three-component accelerometers are employed to monitor both P-and S-waves. Hypocenter coordinates are determined in a grid by back-projection stacking of the short-time-average-to-long-time-average ratio of absolute amplitudes at vertical components and polarization norm derived from horizontal components of the P-and S-waves, respectively. To make the location process more efficient, calculation is started with a coarse grid and zoomed to the optimum hypocenter using an oct-tree algorithm. The focal mechanism is then determined by stacking the vertical component seismograms corrected for the theoretical P-wave polarity of the focal mechanism. The mechanism is resolved in the coordinate space of strike, dip, and rake angles. The method is tested on 34 selected events of a dataset of hydraulic fracture monitoring of a shale gas play in North America. It was found that, by including S-waves, the vertical accuracy of locations improved by a factor of two and is equal to approximately the horizontal location error. A twofold enhancement of horizontal location accuracy is achieved if a denser array of geophone groups is used instead of the sparse array of three-component seismometers. The determined focal mechanisms are similar to those obtained by other methods applied to the same dataset.

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Uncertainty in surface microseismic monitoring

Cited by 5 publications

References 6 publications

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

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

Automatic microseismic stacking location with a multi-cross-correlation imaging condition

Back‐projection stacking of P‐ and S‐waves to determine location and focal mechanism of microseismic events recorded by a surface array

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