... south africa government artificial intelligence machine learning reservoir characterization energy ratio source parameter mechanism sensor structural geology metals & mining merensky reef es ep gibowicz & kijko mendecki seismicity source mechanism arrival time geological...

... and the longitudinal velocity of the layer Vp, simply derived from differentiation of V = L/t: (Equation) upstream oil & gas deformation brazil government geologist united states government wellbore design fluid dynamics machine learning artificial intelligence geology lithotype geological...

... reservoir simulation mudrock shale gas geologist upstream oil & gas climate change interaction fissility asia government machine learning mechanical property united states government molecular dynamic equation of state mineral hydraulic fracturing reservoir characterization clay mineral...

... control machine learning p-wave velocity zheng annual technical conference ozbayoglu young symposium compressive strength exhibition stiffness tensor bedding inclination angle ARMA 23 0128 Experimental Study Of Anisotropic Strength Properties Of Shale Danzhu Zheng University of Tulsa, Tulsa...

... information upstream oil & gas deep learning artificial intelligence reservoir characterization formation pore pressure pressure prediction geologist united states government neural network log analysis machine learning neuron asia government formation pressure china government reservoir...

... for considerable improvements in performance, efficiency, and profitability. upstream oil & gas geologist artificial intelligence acoustic impedance seismic model reservoir geomechanics geological subdiscipline pore pressure united states government log analysis machine learning geology well...

... wave velocity shear wave velocity geological subdiscipline castagna equation university conventional well log shear wave velocity prediction information reservoir geomechanics machine learning correlation shear wave sonic log accuracy log analysis reservoir characterization wellington...

... ABSTRACT Multiscale datasets have long been difficult to integrate within the geosciences. We showcase workflows that leverage machine learning methods to integrate data from multiple scales including high resolution core scans, core plugs and log measurements. The trained models generate...

... ABSTRACT Currently, it is challenging to determine the geological parameters of natural caves in deep reservoirs accurately. By inheriting the advantages of Machine Learning (ML) method and physics modelling, a novel ML-Physics method is developed to determine the geological parameters...

... fluids and materials well logging drilling fluid property drilling fluid selection and formulation drilling fluid formulation drilling operation prediction model bit selection reservoir characterization horizontal well reservoir geomechanics drilling fluid chemistry machine learning rop...

... operation well logging artificial intelligence algorithm machine learning asia government drillability data mining geology china government log analysis novel rock drillability characterization quantization error rop drillability grade neuron evaluation unsupervised clustering algorithm...

... & disposal machine learning clastic rock united states government rock type artificial intelligence reservoir geomechanics fracture barite field stress fip circulation null null null wellbore pressure particle mudcake wellbore wall null null null null ozbayoglu miska null null null...

... learning information artificial intelligence geological subdiscipline china government reservoir characterization knowledge geologist asia government formation pressure machine learning calculation pore pressure lstm well depth domain knowledge prediction model physical characterization...

... attention mechanism precision coefficient drilling fluids and materials machine learning attention mechanism characterization parameter characteristic potential correlation ARMA 23 0093 Intelligent Lost Circulation Early Warning Method Based on HALSTM Network H.T. Wang, X. Wen Kunlun Number...

... government artificial intelligence discontinuity discontinuity trace mapping rock surface geology geologist neural network deep learning machine learning rock mass point cloud data south korea government deep learning model rock discontinuity trace information rock discontinuity trace mapping...

... is limited. asia government united states government china government artificial intelligence deep learning machine learning accuracy data enhancement formula generation model countermeasure network vdl-wgan upstream oil & gas neural network variable density image adversarial...

... characterization wellbore stability sensitivity parameter long-time case sensitivity analysis reservoir geomechanics fracture pressure pore pressure cumulative probability distribution geomechanical parameter short-time case geological subdiscipline collapse pressure machine learning stability...

... the early-stage, near-field rock blasting process and forms a synthetic dataset based on realistic explosive data to train a machine learning model. Key parameters, such as expanded hole diameter, burden velocity, and time-dependent gas pressure, are readily obtained from the constructed machine learning...

... pressure rock type reservoir geomechanics geological subdiscipline ann 4 10 horizontal stress zoback wellbore design wellbore integrity machine learning drilling fluids and materials prediction ann 6 10 dataset predict pore pressure reservoir characterization drilling parameter correlation...

... intelligence human computer interaction real time system machine learning rock movement ground condition reservoir geomechanics virtual environment monitoring underground excavation engineer geological subdiscipline split section rock mass new decline assessment monitoring instability...