Results 161 to 170 of about 682,043 (283)

Fluid‐induced slip on a rate‐and‐state fault during co‐ and post‐injection: The interplay of fluid pressure diffusion and poroelastic stress

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

Integrated geophysical, geological, and machine learning approach for structural characterization of the Balakot-Bagh fault zone associated with the 2005 Mw 7.6 Kashmir earthquake. [PDF]

Sci Rep
Noor S, Khan MY, Turab SA, Doyoro YG, Lin CP, Farooq M.   +5 more
europepmc   +1 more source

Uniaxial compressive strength prediction and ratio parameter optimization of titanium tailings composite backfill materials using intelligent hybrid models

Deep Underground Science and Engineering, EarlyView.
Based on the 90 datasets, ERT and four optimization algorithms were used to build four hybrid models to predict the UCS of the backfill body. The SMA‐ERT model was the most effective model, and it can reliably guide the design of the backfill ratio parameters. Abstract This study analyzed the feasibility of using titanium (Ti) tailings as a backfilling
Weijun Liu, Zida Liu, Zhixiang Liu
wiley   +1 more source

Research on geological hazard susceptibility evaluation using an information value-modified entropy weight combined model. [PDF]

Sci Rep
Qin M, Chen B, Zhu J, Lv J, Lin M, Lin M, Wang Y.   +6 more
europepmc   +1 more source

Probabilistic prediction of rate‐dependent rock strength using natural gradient boosting and Gaussian process regression

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

Geological mapping of the Adrar Souttouf mafic complex in the Northern West African Craton using remote sensing and geophysical data. [PDF]

Sci Rep
Haous EHE, Fekkak A, Houali Y, Haidatte S, Bouasria A, Boumehdi M, Achkouch L, Genske F, Haissen F, Jouhari A, Berrada I, Berkat NE, Errami A, Sadki O, Shebl A.   +14 more
europepmc   +1 more source

Rock mechanical properties under reconstructed deep in situ thermo–hydro–mechanical conditions: Implications for CO₂‐related injection scenarios

Deep Underground Science and Engineering, EarlyView.
The graphical abstract illustrates a reconstructed in situ thermo‐hydro‐mechanical (THM) framework in which porosity serves as the central variable linking stress, pore pressure, and temperature to evolving mechanical properties of rocks. Under burial conditions, in situ stress, pore pressure, and temperature jointly govern volumetric strain and ...
Mingyuan Lu, Jun Wang, Zixiong Qi, Ruixuan Chen, Hongtao Wang, Hongwei Zhou   +5 more
wiley   +1 more source

Correction: Insights into Sudbury's deep architecture: a revised geodynamic model for Earth's largest ore-bearing impact structure. [PDF]

Sci Rep
Haugaard R, Spray JG, Adetunji AQ, Vayavur R, Hamilton MA, Snyder D, Cheraghi S, Ayer J, Henry K, Jørgensen TRC, Serafini G, Smith R, Gibson L.   +12 more
europepmc   +1 more source

Explainable hybrid stacking ensemble method for hard rock pillar stability prediction and engineering applications

Deep Underground Science and Engineering, EarlyView.
This research proposes an interpretable hybrid stacking ensemble framework, optimized by the Sparrow Search Algorithm, to enhance hard rock pillar stability prediction. By integrating six machine learning models—k‐nearest neighbors, support vector machines, random forests, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, and Light Gradient ...
Ning Wang, Guoyan Zhao, Meng Wang, Taraka Pattela   +3 more
wiley   +1 more source

Enhancing groundwater potential mapping in arid regions through integrated microwave remote sensing, statistical analysis, and geophysical-based modeling. [PDF]

Sci Rep
Youssef YM, Gemail KS, Abdel Aziz NA, Senosy MM, El-Qady G, Atia HM.   +5 more
europepmc   +1 more source