... of these resources, has prompted the development and application of data-driven statistical models for predicting hydrocarbon production performance. More recently, machine learning algorithms have been widely studied in developing data-driven prediction models for unconventional reservoirs. These models often...

... characterization natural language energy economics knowledge canada government source model target data information source field transfer learning conv1d physics negative transfer classifier target domain artificial intelligence machine learning clastic rock null sedimentary rock data-driven...

... phenomenon—permeability jail. 1 7 2022 20 9 2022 14 9 2022 24 10 2022 12 4 2023 Copyright © 2023 Society of Petroleum Engineers neural network machine learning flow in porous media permeability upstream oil & gas pore fluid dynamics artificial intelligence...

... such as multiple wells and multiphase flow. 17 5 2022 7 10 2022 24 9 2022 24 10 2022 12 4 2023 Copyright © 2023 Society of Petroleum Engineers upstream oil & gas history matching complex reservoir hydraulic fracturing modeling & simulation machine learning...

... injection method miscible method optimization problem machine learning enhanced recovery co 2 upstream oil & gas artificial intelligence iteration vector bhp npv accuracy constraint proxy case-8 highbhp algorithm design variable fraction icv application ls-svr proxy high-fidelity...

... oversimplified assumptions and have high computational costs, especially when considering the impact of spatially correlated interbedded shales on the shear strength. A machine learning enhanced upscaling (MLEU) technique that leverages the accuracy of local numerical upscaling and the efficiency of artificial...

... Copyright © 2023 Society of Petroleum Engineers risk and uncertainty assessment upstream oil & gas research and development knowledge management evaluation artificial intelligence strategic planning and management demo risk management machine learning ptd deployment probability...

... 2022 28 10 2022 12 4 2023 Copyright © 2023 Society of Petroleum Engineers fluid dynamics artificial intelligence multiphase flow enhanced recovery machine learning production monitoring upstream oil & gas reservoir surveillance production logging production control...

... & gas deep learning asia government source domain drilling operation machine learning representation artificial intelligence target sample target domain international conference united states government neural network domain adaptation wd-muda data distribution drilling data domain...

... 2023 22 3 2023 Copyright © 2023 Society of Petroleum Engineers upstream oil & gas united states government africa government deep learning prediction artificial intelligence neural network data mining asia government europe government uae government machine learning map...

... of Petroleum Engineers upstream oil & gas united kingdom government deep learning neural network asia government reservoir surveillance artificial intelligence machine learning production control regression choke valve europe government simulation simulator united states government...

... and avoiding sudden stops during oil lifting. 24 11 2022 23 2 2023 11 2 2023 15 3 2023 Copyright © 2023 Society of Petroleum Engineers united states government machine learning subsystem upstream oil & gas evolutionary algorithm genetic algorithm competition...

... stability performance in crude oil was evaluated using six machine learning (ML) techniques, namely decision tree (DT), Naïve Bayes (NB), support vector machine (SVM), artificial neural networks (ANN), random forest (RF), and k-nearest neighbor (KNN). A large stability data containing 186 crude oil samples...

... 13 2 2023 8 2 2023 28 2 2023 Copyright © 2023 Society of Petroleum Engineers united states government expert system category beam pumping neural network diversity augmentation reservoir surveillance classification machine learning discriminator accuracy cgan asia...

... clay content prediction algorithm selected in each realization is written to the output sheet, so it can subsequently be used by machine-learning algorithms. Estimation of fault rock capillary threshold pressure from the predicted clay content. This is done using the published relationship...

... government norway government united states government data quality drilling data acquisition linear interpolation drilling measurement imputation interpolation upstream oil & gas artificial intelligence machine learning evaluation imputation method algorithm linear regression estimation...

...Xuechen Li; Xinfang Ma; Fengchao Xiao; Cong Xiao; Fei Wang; Shicheng Zhang Summary Relying on its strong nonlinear mapping ability, machine learning is found to be efficient and accurate for production prediction of fractured wells compared with conventional analytical methods, numerical...

... simulation flow in porous media machine learning boundary pressure field tilted oowc upstream oil & gas equation of state artificial intelligence interface united states government adjustment optimizer inverse problem boundary condition saudi arabia government sensitivity control...

... in practical operation has been the failure of PDHGs within the first few years of operation. In this work, a physics-based data-driven (PBDD) model and machine learning (ML) models are developed to predict PDHG pressure and temperature measurement from the wellhead and other measurements during well SI events...

... relaxivity log analysis vector-valued gp decay null 2 europe government null 1 null sim covariance matrix log 10 null null isw null well logging machine learning objective function relaxation time hyperparameter relaxivity null 0 diffusion coefficient susceptibility relaxation united...