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Keywords: machine learning
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Journal Articles
J Pet Technol 74 (10): 46–51.
Paper Number: SPE-1022-0046-JPT
Published: 01 October 2022
...), is a startup called Xecta Digital Labs. Founded in 2019 by a team of experienced oil and gas technologists, the firm has proposed a proprietary hybrid model as the way forward. It combines a reduced-physics approach with artificial intelligence and machine learning (AI/ML) techniques to issue daily estimates...
Journal Articles
J Pet Technol 74 (10): 83–85.
Paper Number: SPE-1022-0083-JPT
Published: 01 October 2022
...Chris Carpenter _ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 205134, “Machine-Learning Application for Gas Lift Performance and Well Integrity,” by Mostafa Sa’eed Yakoot, SPE, Gulf of Suez Petroleum; Adel M.S. Ragab, SPE, Suez University...
Journal Articles
J Pet Technol 74 (10): 89–90.
Paper Number: SPE-1022-0089-JPT
Published: 01 October 2022
... with the permission of the author. Contact the author for permission to use material from this document. social responsibility neural network sustainability artificial intelligence oruganti machine learning engineering emission sustainable development data analytic scientist storage upstream oil...
Journal Articles
J Pet Technol 74 (10): 91–93.
Paper Number: SPE-1022-0091-JPT
Published: 01 October 2022
... composed of various parameters of oil wells measured during exploitation. By tuning machine-learning models for a single well (ignoring the effect of neighboring wells) on open-source field data sets, the authors of the paper demonstrate that the transformer-based method outperforms recurrent neural...
Journal Articles
J Pet Technol 74 (10): 97–99.
Paper Number: SPE-1022-0097-JPT
Published: 01 October 2022
...Chris Carpenter _ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 31419, “Bringing Huge Core-Analysis Legacy Data to Life Using Machine Learning,” by Siti N.F. Zulkipli, SPE, Benard Ralphie, and Jamari M. Shah, SPE, Petronas, et al. The paper has...
Journal Articles
J Pet Technol 74 (10): 100–101.
Paper Number: SPE-1022-0100-JPT
Published: 01 October 2022
.... In paper SPE 207193, the authors propose a fast and accurate machine-learning algorithm to predict the onset of sanding in sandstone formations. The algorithm uses 11 geological and reservoir parameters that directly affect sand production. The answer is binary (i.e., sand production will or will not occur...
Journal Articles
J Pet Technol 74 (09): 64–65.
Paper Number: SPE-0922-0064-JPT
Published: 01 September 2022
... the Permian Basin. Recommended additional reading at OnePetro: www.onepetro.org. OTC 31151 - Autonomous Subsea Field Development—Value Proposition, Technology Needs, and Gaps for Future Advancement by Giorgio Arcangeletti, Saipem, et al. SPE 206533 - Field Development Optimization Using Machine-Learning...
Journal Articles
J Pet Technol 74 (09): 66–68.
Paper Number: SPE-0922-0066-JPT
Published: 01 September 2022
...-a realization injector optimization problem optima machine learning dqn sfdo spmi TECHNICAL PAPERS | Field Development Field-Development Optimization Method Benchmarked, Field Tested Recently, a novel distributed quasi-Newton (DQN) derivative-free optimization (DFO) method was developed for generic...
Journal Articles
J Pet Technol 74 (08): 75–77.
Paper Number: SPE-0822-0075-JPT
Published: 01 August 2022
...Chris Carpenter This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 208689, “Coupling Psychological Factors With Machine Learning To Improve Rig Technical Training,” by Francesco Curina, Elia Abdo, and Ajith Asokan, Drillmec, et al. The paper has...
Journal Articles
J Pet Technol 74 (08): 83–85.
Paper Number: SPE-0822-0083-JPT
Published: 01 August 2022
...Chris Carpenter This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 31758, “Downhole Pressure Prediction for Deepwater Gas Reservoirs Using Physics-Based and Machine-Learning Models,” by Jincong He, SPE, Matthew Avent, and Mathieu Muller, Chevron, et al...
Journal Articles
J Pet Technol 74 (07): 49–51.
Paper Number: SPE-0722-0049-JPT
Published: 01 July 2022
...Chris Carpenter This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 203941, “Bridging the Gap Between Material Balance and Reservoir Simulation for History Matching and Probabilistic Forecasting Using Machine Learning,” by Nigel H. Goodwin, Essence...
Journal Articles
J Pet Technol 74 (07): 52–54.
Paper Number: SPE-0722-0052-JPT
Published: 01 July 2022
... Copyright 2020, Society of Petroleum Engineers fluid dynamics neural network waterflooding artificial intelligence deep learning enhanced recovery machine learning multiphase parameter hyperbolic pde diffusive term network help predict fluid flow pinn complete paper upstream oil & gas...
Journal Articles
J Pet Technol 74 (07): 55–57.
Paper Number: SPE-0722-0055-JPT
Published: 01 July 2022
... hypothesis modeling work flow artificial intelligence hypothesis study identify dynamic data literature graph-network model reservoir modeling work flow algorithm upstream oil & gas machine learning work flow information assimilation true model component 1 7 2022 1 7 2022...
Journal Articles
J Pet Technol 74 (07): 77–79.
Paper Number: SPE-0722-0077-JPT
Published: 01 July 2022
...Chris Carpenter This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 200360, “Production Optimization of the CO2 Huff-n-Puff Process in an Unconventional Reservoir Using a Machine-Learning-Based Proxy,” by Azad Almasov, SPE, Mustafa Onur, SPE, and Albert...
Journal Articles
J Pet Technol 74 (06): 78–81.
Paper Number: SPE-0622-0078-JPT
Published: 01 June 2022
...Chris Carpenter This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 204145, “Employing a Suite of Machine-Learning Algorithms in a Holistic Approach to Trouble Stage Recognition and Failure Diagnostics,” by Jessica Iriarte, SPE, Well Data Labs; Matthew...
Journal Articles
J Pet Technol 74 (05): 85–87.
Paper Number: SPE-0522-0085-JPT
Published: 01 May 2022
... properties in the fracturing simulations. 1 5 2022 1 5 2022 1 5 2022 1 5 2022 Copyright 2020, Society of Petroleum Engineers hydraulic fracturing artificial intelligence drilling operation fracturing fluid machine learning proppant upstream oil & gas data-driven...
Journal Articles
J Pet Technol 74 (05): 73–76.
Paper Number: SPE-0522-0073-JPT
Published: 01 May 2022
... paper. One approach was to simplify the code set and to make it easier for teams to pick the right codes. Successes of machine-learning techniques may inspire efforts to remove the human from the equation immediately and rely solely on machine learning to provide a classification of well activities...
Journal Articles
J Pet Technol 74 (05): 82–84.
Paper Number: SPE-0522-0082-JPT
Published: 01 May 2022
...Chris Carpenter This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 206516, “Stuck-Pipe Early Detection in Extended-Reach Wells Using Ensemble Method of Machine Learning,” by Rushad Ravilievich Rakhimov, SPE, Schlumberger, and Oleg Valerievich Zhdaneev...
Journal Articles
J Pet Technol 74 (05): 80–81.
Paper Number: SPE-0522-0080-JPT
Published: 01 May 2022
... to evolve under the volatile oil market pricing conditions and the stride of digital transformation. The technology front is shifting from marching toward longer and more-complex wells to smarter wells with better return on investment (ROI). Artificial intelligence (AI) and machine learning, which can...
Journal Articles
J Pet Technol 74 (04): 66–68.
Paper Number: SPE-0422-0066-JPT
Published: 01 April 2022
...-effective solution. This tool collects both high-resolution acoustic amplitudes and triaxial accelerations. drilling measurement data quality neural network drilling data acquisition calculation deep learning wavelet transform upstream oil & gas fourier transform machine learning artificial...

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