Results 71 to 80 of about 23,849,149 (246)
Deep Underground Science and Engineering, EarlyView.The tensile strength of granite, a proposed host for nuclear waste, degrades severely above 400°C. We link this to specific microcracking patterns captured by acoustic emission, establishing a scientific basis for assessing repository safety under thermal load.
Wei Zeng +7 more
wiley +1 more source
Deep Underground Science and Engineering, EarlyView.Fault slip can occur ahead of the injection pressure front due to poroelastic stress. Our model captures the interaction of pressure, stress, and friction, providing new insights into injection‐induced seismicity and post‐injection fault slip. Shut‐in operations can either mitigate or accelerate seismic events depending on fault conditions and ...
Qifeng Xie, Lei Wang, Qi Li
wiley +1 more source
Measuring the Fractal Properties of Reservoirs for Use in Modeling CCUS Potential
Earth and Space ScienceThe injection of CO2 underground into reservoirs for carbon capture and underground storage (CCUS) is highly sensitive to heterogeneity and anisotropy. Although conventional geological modeling cannot take explicit account of heterogeneity or anisotropy ...
Mehdi Yaghoobpour +3 more
doaj +1 more source
Community Seismic Network Earthquake Dataset: http://csn.caltech.edu/data/
Acceleration waveform time series recorded by Community Seismic Network (CSN) strong-motion stations for select California and global earthquakes. The data can be downloaded from the Community Seismic Network's publicly-available website: http://csn ...
Community Seismic Network
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Deep Underground Science and Engineering, EarlyView.Probabilistic natural gradient boosting and Gaussian process regression models accurately predict rate‐dependent rock strength across lithologies. Static strength and strain rate dominate, while geometric factors have minimal influence, enabling interpretable and uncertainty‐aware predictions for dynamic geomechanical applications. Abstract The dynamic
Hadi Fathipour‐Azar
wiley +1 more source
Transformer and Convolutional Hybrid Neural Network for Seismic Impedance Inversion
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingThe inversion of elastic parameters especially P-wave impedance is an essential task in seismic exploration. Over the years, deep learning methods have made significant achievements in seismic impedance inversion, and convolutional neural networks (CNNs)
Chunyu Ning, Bangyu Wu, Baohai Wu
doaj +1 more source
Deep Underground Science and Engineering, EarlyView.This study reveals the failure evolution characteristics of deep cross‐fault roadway surrounding rock under excavation support and periodic weighting. Periodic weighting readily induces fault activation, with the spatial distribution of failed rock masses being controlled by the fault strike and dip.
Tiezhu Li +4 more
wiley +1 more source
Multi-Scale Acoustic Velocity Inversion Based on a Convolutional Neural Network
Remote SensingThe full waveform inversion at this stage still has many problems in the recovery of deep background velocities. Velocity modeling based on end-to-end deep learning usually lacks a generalization capability.
Wenda Li, Tianqi Wu, Hong Liu
doaj +1 more source
Tau-p mapping and interpretation of seismic reflection data from the western Isles region of Scotland [PDF]
, 1982 Seismic data are conventionally recorded, processed and displayed in the X-T domain, where X is the source-receiver. offset and T is the two-way traveltime.
Lambert, Mark E.
core
Deep Underground Science and Engineering, EarlyView.The graphical abstract depicts the workflow for porous‐ and fractured‐media simulations, where stochastically generated discrete natural fractures are required for the fracture‐media simulation. Abstract CO 2 ${\text{CO}}_{2}$ leakage is one of the main risks and barriers to geologic carbon storage. However, under the high‐temperature and high‐pressure
Christoph Scherounigg +3 more
wiley +1 more source