Results 11 to 20 of about 23,608,882 (224)
Data-Driven Signal–Noise Classification for Microseismic Data Using Machine Learning
Energies, 2021 It is necessary to monitor, acquire, preprocess, and classify microseismic data to understand active faults or other causes of earthquakes, thereby facilitating the preparation of early-warning earthquake systems.
Sungil Kim +3 more
doaj +2 more sources
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 +5 more sources
Historic microseismic data and their relation to the wave-climate in the North Atlantic
Meteorologische Zeitschrift, 2005 Microseismic data from observatories in Europe, which have been continuously recorded since about 100 years, contain information on the wave-climate in the North Atlantic. They can potentially be used as additional constraints in high-resolution temporal
Torsten Dahm +3 more
doaj +2 more sources
, 2020 This is the data set and label set of microseismic monitoring, including forward modeling seismic signals and measured microseismic ...
zhang, J (via Mendeley Data)
core +2 more sources
Automatic picking method of microseismic first arrival time based on improved support vector machine
Gong-kuang zidonghua, 2023 The microseismic first arrival time picking is an important prerequisite for the high-precision positioning of the microseismic source. The traditional manual picking method is inefficient.
LI Tieniu +9 more
doaj +1 more source
High-accuracy real-time microseismic analysis platform : case study based on the super-sauze mud-based landslide [PDF]
, 2020 Understanding the evolution of landslide and other subsurface processes via microseismic monitoring and analysis is of paramount importance in predicting or even avoiding an imminent slope failure (via an early warning system).
Stankovic, L. +3 more
core +3 more sources
Investigation of Microseismic Characteristics of Rock Burst Based on Fractal Theory
Applied Sciences, 2023 Microseismic monitoring is a common monitoring tool in the mining production process; for supervising a huge amount of microseismic data, effective analysis tools are necessary.
Ping Wang, Ze Zhao, Da Zhang, Zeng Chen
doaj +1 more source
Remote Sensing, 2023 Numerous microseismic signals are produced by rock mass fracture during earthquakes, geological disasters, or underground excavations. Moreover, a large amount of noise signals are captured during microseismic signal monitoring.
Chunchi Ma +8 more
doaj +1 more source
Prediction of microseismic events in rock burst mines based on MEA-BP neural network
Scientific Reports, 2023 Microseismic monitoring is an important tool for predicting and preventing rock burst incidents in mines, as it provides precursor information on rock burst.
Tianwei Lan +3 more
doaj +1 more source
Frontiers in Physics, 2023 Microseismic monitoring data may be seriously contaminated by complex and nonstationary interference noises produced by mechanical vibration, which significantly impact the data quality and subsequent data-processing procedure.
Zhichao Yu +5 more
doaj +1 more source