Results 211 to 220 of about 144,758 (313)

Tectonic evolution of Southeast Asia [PDF]

open access: yesBulletin of the Geological Society of Malaysia, 2014
openaire   +1 more source

Machine Learning‐Driven Classification and Production Capacity Prediction of Tight Sandstone Reservoirs: A Case Study of the Taiyuan Formation, Ordos Basin

open access: yesEnergy Science &Engineering, EarlyView.
On the basis of core and log data, a Bayesian‐Optimized Random Forest model achieved 92.76% accuracy in classifying tight sandstone reservoirs. A gray relational analysis‐derived evaluation index shows > 80% consistency with actual gas zones. ABSTRACT Tight sandstone gas (TSG), an unconventional oil–gas resource, has heterogeneous reservoirs ...
Yin Yuan   +8 more
wiley   +1 more source

Study on Damage Characteristics and Evolution Law of Macro‐Meso Structure of Surrounding Rock Under Mining Stress

open access: yesEnergy Science &Engineering, EarlyView.
Investigating the differential impact of mining stress on roadways, we find that in horizontally stressed environments, the inner surrounding rock exhibits more pronounced macro‐meso damage compared to the outer side. ABSTRACT The control of surrounding rocks in dynamic pressure roadways has consistently been one of the challenging predicaments in the ...
Fan Lei   +4 more
wiley   +1 more source

Experimental Investigation of Sensitivity for Coal and Gas Outburst Risk Prediction Indexes in Raw and Tectonic Composite Coal Seams

open access: yesEnergy Science &Engineering, EarlyView.
A comparative study was conducted on gas desorption laws of raw and tectonic coals. The sensitivity of regional and local outburst prediction indexes was compared. Gas content is more sensitive than gas pressure for composite coal seams. K1 can more accurately predict the outburst danger than Δh2 $\Delta {h}_{2}$ in composite coal seams.
Haijun Guo   +4 more
wiley   +1 more source

Interpretable Tree‐Based Models for Predicting Short‐Term Rockburst Risk Considering Multiple Factors

open access: yesEnergy Science &Engineering, EarlyView.
Interpretable tree‐based models integrate microseismic, geological, and mining indicators to predict short‐term rockburst risk. SHAP analysis reveals the dominant role of energy‐related features and clarifies nonlinear factor interactions, enabling transparent and reliable early‐warning in deep coal mines.
Shuai Chen   +4 more
wiley   +1 more source

Home - About - Disclaimer - Privacy