Results 171 to 180 of about 6,521,310 (287)

Oil-Water Flow Monitoring in Wellbores with Inflow Control Valves Using Distributed Acoustic Sensing. [PDF]

Sensors (Basel)
Xiao C, Jin G, Fan Y.
europepmc   +1 more source

Real‐time lithology identification while drilling based on drill cuttings image analysis with ensemble learning

Deep Underground Science and Engineering, EarlyView.
A lithology identification while drilling method was developed, integrating an automated cuttings sampling system, a smart drilling rig, and an ensemble learning model. Underground trials achieved 97.42% accuracy in real‐time identification of cuttings lithology and composition, enhancing hazard management and supporting unmanned drilling technology in
Kun Li, Ting Ren, Ningping Yao, Jon Roberts, Haitao Song, Zhongbei Li, Xueqiu He, Liang Zhao   +7 more
wiley   +1 more source

Functional response of bacterial communities in surface sediments of qingshitan reservoir to anthropogenic disturbance. [PDF]

Sci Rep
Feng X, Xiang-Ling T, ZhiJie G.
europepmc   +1 more source

Fracture evolution of a thick soft protection layer and the water inrush mechanism in overburden under longwall mining

Deep Underground Science and Engineering, EarlyView.
Through shear–tensile creep tests and viscoelastic modeling, the fracture evolution of thick soft protective layers is clarified. Results show thickness‐dependent rheological failure modes that govern four types of roof water inrush, providing a mechanism‐based framework for hazard prediction and control. Abstract In the Jurassic coal‐bearing strata of
Mengnan Liu, Wei Qiao, Xianggang Cheng, Xiangsheng Meng, Peichao Feng   +4 more
wiley   +1 more source

Enhancing the understanding of environmental microbiomes through topic modeling: a quantitative and qualitative analysis. [PDF]

Environ Microbiome
Kujat AS, Hassenrück C, Lüdtke S, Labrenz M, Sperlea T.   +4 more
europepmc   +1 more source

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

Deep Underground Science and Engineering, EarlyView.
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li, Huiyong Yin, Fangying Dong, Tao Wu, Chao Zhang   +4 more
wiley   +1 more source

Physics-guided networks for probabilistic hydrodynamic forecasting in canal systems. [PDF]

Environ Sci Ecotechnol
Liu W, Guan G, Chen X, Shi L, Fu G, Savic D.   +5 more
europepmc   +1 more source

Modeling proppant transport and settling in a 3D propagating fracture

Deep Underground Science and Engineering, EarlyView.
A versatile multiphysics tool is presented for simulating the complex processes involved in hydraulic fracturing treatments. The model couples fracture opening and propagation, variable‐density slurry flow, and proppant particle transport within the multiphysics object‐oriented simulation environment framework, based on two‐phase mixture equations and ...
Robert Egert, Aimé Fournier, Wencheng Jin   +2 more
wiley   +1 more source

Dynamics of internal bore migration within turbidity currents under variable dam slopes. [PDF]

Sci Rep
Lee FZ, Lai JS, Imtiyaz N.
europepmc   +1 more source

Major engineering breakthrough of Well XA‐1, the deepest ten‐thousand‐meter well in a global sedimentary basin

Deep Underground Science and Engineering, EarlyView.
Well XA‐1, completed at a true vertical depth of 11 156 m in the Shawan Sag of the Junggar Basin, is the deepest predominantly near‐vertical well drilled in a sedimentary basin. The figure shows the basin's tectonic framework and well location (a), a structural cross‐section spanning the Shawan Sag and adjacent uplifts (b), and the stratigraphic column
Fangkai Liu, Qingwen Tan, Sen Zhu, Guangyou Zhu   +3 more
wiley   +1 more source