Results 1 to 10 of about 701 (138)
Tracking cave shape development with microseismic data [PDF]
Proceedings of the Fourth International Symposium on Block and Sublevel Caving, 2018 Microseismic monitoring is routinely used by block and panel caving mines worldwide to track cave shape development. The standard practice is to use the cloud of seismic event locations as a proxy for cave growth below. Careful seismic sensor array planning overcomes problems with event location reliability due to seismicray bending around the unknown ...
Richard Lynch +3 more
openaire +1 more source
Resonance in downhole microseismic data and its removal [PDF]
SEG Technical Program Expanded Abstracts 2016, 2016 Author(s): Zhang, Z; Rector, JW; Nava, MJ | Abstract: We identified resonance due to poor geophone-borehole cou- pling in downhole microseismic data and proposed to use spik- ing deconvolution and relative spectrum analysis to remove its effect. The resonance may hinder the arrival time picking and contaminate microseismic waveform spectrum.
Zhang, Z, Rector, JW, Nava, MJ
openaire +3 more sources
Field data of microseismic hydraulic fracturing
, 2023 That is a field data of microseismic hydraulic ...
openaire +2 more sources
Exploring wave propagation behaviors in rock: A grain‐based perspective on mineral structures
Deep Underground Science and Engineering, EarlyView.This study investigates wave propagation in rock at the grain scale using a grain‐based model, revealing that mineral elastic modulus significantly influences wave attenuation while grain size and distribution have limited effects. A novel peak particle velocity attenuation prediction model is proposed and validated for grain‐scale wave propagation ...
Zhiyi Liao +3 more
wiley +1 more source
A Nonparametric Method for Automatic Denoising of Microseismic Data [PDF]
Shock and Vibration, 2018 Noise suppression or signal‐to‐noise ratio (SNR) enhancement is often desired for better processing results from a microseismic dataset. In this paper, we proposed a nonparametric automatic denoising algorithm for microseismic data. The method consists of three major steps: (1) applying a two‐step AIC algorithm to pick P‐wave arrival; (2) subtracting ...
Pingan Peng, Liguan Wang
openaire +2 more sources
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
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
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
Microseismicity data for hydrofracture experiment
, 2020 Microseismicity locations in a local coordinate system in the plane of the fracture. Each of the files VascoEtAl_JGR_2020.*minutes.dat represents the seismicity during a 10 minute increment measured from the start of injection. The file VascoEtAl_JGR_2012.times.moments.xy contains the event moment magnitudes as a function of time since the start of ...
openaire +2 more sources
Deep Underground Science and Engineering, EarlyView.This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu +4 more
wiley +1 more source