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Microseismicity based short term rockburst prediction using non linear support vector machine

Jin Aibing, Basnet Prabhat Man Singh, Mahtab Shakil

Acta Geophysica

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2022

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Vol. 70, no 4

1717--1736

EN

Microseismic (MS) monitoring is a short-term rockburst prediction technique that foretells the source, time and damage scale inside a rock mass during the rock fracturing process; however, due to the complex underground environment and mechanism of rockburst it is always hard to reliably predict the damage scale (severity) of rockburst manually; therefore, this paper introduces machine learning (ML) approach using nonlinear support vector machine (Nonlinear-SVM) to predict the short-term rockburst. Six indicators, cumulative number of events (N), cumulative seismic energy (E), cumulative apparent volume(V), event rate (NR), seismic energy rate (ER) and apparent volume rate (VR), are selected as an input indices for Nonlinear-SVM which is trained and tested with randomly selected 85 and 22 samples of rockburst cases, respectively, collected from different literature. The constructed model was employed to predict the short-term rockburst severity. After data standardisation, cross-validation and hyperparameter optimisation, the prediction accuracy reached 86% for the test sample. The predicted rockburst result truly matches the actual situation with few misclassifcations. Therefore, the proposed method has potential value for the short-term rockburst prediction task.

2

Small-aperture array as a tool to monitor fluid injectionand extraction‑induced microseismicity: applications and recommendations

Karamzadeh Nasim, Kühn Daniela, Kriegerowski Marius, Lopez-Comino José Ángel, Cesca Simone, Dahm Torsten

Acta Geophysica

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2019

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Vol. 67, no. 1

311--326

EN

The monitoring of microseismicity during temporary human activities such as fluid injections for hydrofracturing, hydrothermal stimulations or wastewater disposal is a difficult task. The seismic stations often cannot be installed on hard rock, and at quiet places, noise is strongly increased during the operation itself and the installation of sensors in deep wells is costly and often not feasible. The combination of small-aperture seismic arrays with shallow borehole sensors offers a solution. We tested this monitoring approach at two different sites: (1) accompanying a fracking experiment in sedimentary shale at 4 km depth and (2) above a gas field under depletion. The small-aperture arrays were planned according to theoretical wavenumber studies combined with simulations considering the local noise conditions. We compared array recordings with recordings available from shallow borehole sensors and give examples of detection and location performance. Although the high-frequency noise on the 50-m-deep borehole sensors was smaller compared to the surface noise before the injection experiment, the signals were highly contaminated during injection by the pumping activities. Therefore, a set of three small-aperture arrays at different azimuths was more suited to detect small events, since noise recorded on these arrays is uncorrelated with each other. Further, we developed recommendations for the adaptation of the monitoring concept to other sites experiencing induced seismicity.

3

Detection of the Long Period Long Duration (LPLD) Events in Time- and Frequency-Domain

Kwietniak A.

Acta Geophysica

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2015

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Vol. 63, no. 1

201--213

EN

Long Period Long Duration (LPLD) signals are unusual seismic events that can be observed during hydraulic fracturing. These events are very similar in appearance to tectonic tremors sequences, which were first observed in subduction zones. Their nature is not well known. LPLD might be related to the productivity of the reservoir. Different methods of the LPLD events’ detection recorded during hydraulic fracturing are presented. The author applied two methods for LPLD detection – Butterworth filtering and Continuous Wavelet Transform (CWT). Additionally, a new approach to LPLD events detection – instantaneous seismic attributes – was used, common in a classical seismic interpretation but not in microseismic monitoring.