Results 41 to 50 of about 3,283 (222)
Genetic Programming-Based Prediction Model for Microseismic Data
Geofluids, 2022 Microseismic monitoring is a rock breakdown monitoring technology, and it has become a major technical tool for underground disaster warning and prevention.
Man Wang +5 more
doaj +1 more source
Introduction to this special section: Microseismic [PDF]
, 2017 This month in The Leading Edge, we present a selection of papers on microseismic technology that captures recent trends in microseismic data processing, acquisition, and interpretation.
Julie Shemeta, James Rutledge
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An optimizing microseismic method for rock burst early warning based on mining production process
Deep Underground Science and Engineering, EarlyView.A classification early warning method of rock burst based on hourly microseismic data is proposed, which can be combined with the on‐site production process to provide more timely warning. Abstract Microseismic (MS) events have been reported in nearly every coal mining country, which could well lead to rock burst in underground coal mines.
Zepeng Han +6 more
wiley +1 more source
Conditional Diffusion Model for Robust 3-D Microseismic Event Localization from Noisy Waveforms [PDF]
Locating microseismic events is crucial to monitoring fracking activities, CO2 injection, and reservoirs in general. However, the process of locating such events is challenging, especially in low signal-to-noise scenarios.
Wamriew, Daniel, Alkhalifah, Tariq Ali
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Fast first arrival picking algorithm for noisy microseismic data [PDF]
, 2017 Most microseismic events occur during hydraulic fracturing. Thus microseismic monitoring, by recording seismic waves from microseismic events, is one of the best methods for locating the positions of hydraulic fractures.
변중무
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Deep convolutional neural network for microseismic signal detection and classification [PDF]
, 2020 Reliable automatic microseismic waveform detection with high efficiency, precision, and adaptability is the basis of stability analysis of the surrounding rock mass. In this paper, a convolutional neural network (CNN)-based microseismic detection network
Pazzi V. +4 more
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Deep Underground Science and Engineering, EarlyView.Through shear–tensile creep tests and viscoelastic modeling, the fracture evolution of thick soft protective layers is clarified. Results show thickness‐dependent rheological failure modes that govern four types of roof water inrush, providing a mechanism‐based framework for hazard prediction and control. Abstract In the Jurassic coal‐bearing strata of
Mengnan Liu +4 more
wiley +1 more source
Microseismic data of the HDR injection test [PDF]
<p>Microseismic data associated with the submitted paper on HDR injection test</p ...
Xie, Jingyu, Zhao, Zhengguang, Li, Lei
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Frontiers in Earth Science, 2022 Microseismic events can be used to analyze the risk of tunnel collapse, rock burst, and other mine hazards in space and time. In practice, the artificial activities and other signals at the mining site can seriously interfere with the microseismic ...
Da Zhang +20 more
doaj +1 more source
Deep Underground Science and Engineering, EarlyView.The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li +4 more
wiley +1 more source