Results 11 to 20 of about 6,541 (225)
Influence Evaluation of Sensor Coordinate Error on Microseismic Source Location
In microseismic (MS) source localization, it is usually assumed that the sensor coordinates are accurate. However, there are generally measurement errors for the sensor coordinates in practical engineering, which severely affect the location accuracy of ...
Tao Li +10 more
doaj +1 more source
Effect of Velocity Anisotropy in Shale on the Acoustic Emission Events Matching and Location
Accurate source event location is important in fracturing monitoring and characterization. Velocity anisotropy has a great influence on both events matching and events location. Failure to take into account the velocity anisotropy can lead to huge errors
Peng Wang, Feng Zhang, Xiang-Yang Li
doaj +1 more source
Transfer learning for self-supervised, blind-spot seismic denoising
Noise is ever present in seismic data and arises from numerous sources and is continually evolving, both spatially and temporally. The use of supervised deep learning procedures for denoising of seismic datasets often results in poor performance: this is
Claire Birnie, Tariq Alkhalifah
doaj +1 more source
Coalescence microseismic mapping [PDF]
Earthquakes are commonly located by linearized inversion of discrete arrival time picks made from signals recorded at a network of seismic stations. If mis-picks are made, these will contribute to the location, therefore causing potential bias. For data recorded by a dense seismic array, direct imaging methods can be applied instead.
Drew, J. +3 more
openaire +3 more sources
Microseismic Events Cause Significant pH Drops in Groundwater
Earthquakes cause rock fracturing, opening new flow pathways which can result in the mixing of previously isolated geofluids with differing geochemistries.
M. Stillings +6 more
doaj +1 more source
Microseismic monitoring has become a well-known technique for predicting the mechanisms of rock failure in deeply buried energy exploration, in which noise has a great influence on microseismic monitoring results.
Shibin Tang +4 more
doaj +1 more source
Wavelet Transform-Based Fuzzy Clustering Microseismic First-Arrival Picking Method
Microseismic arrival time picking serves as the foundation for microseismic source localization and holds significant importance in the field of microseismic monitoring.
Tingting Lin +3 more
doaj +1 more source
The robustness of seismic moment and magnitudes estimated using spectral analysis [PDF]
calculate seismic moment. This is an important topic for operators and regulators who require good magnitude estimates when monitoring induced seismicity.
Verdon, James P +5 more
core +1 more source
Quality Assessment of Microseismic P-Phase Arrival Picks and Its Application of Source Location in Coal Mining [PDF]
Correctly identifying abnormal and false P-phase arrival picks (P-pick) in underground coal mining is essential to microseismic source location. Manual judgement and identification are time-consuming with the increasingly growing monitoring data.
Lang Liu +4 more
core +1 more source
PSSegNet: Segmenting the P- and S-Phases in Microseismic Signals through Deep Learning
Microseismic P- and S-phase segmentation is an influential step that limits the accuracy of event location, parameter inversion, and mechanism analysis.
Zhengxiang He +5 more
doaj +1 more source

