deep learning
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This study presents a novel hybrid approach to enhance fraud detection in scanned financial documents. -
This research aims to harness the advanced capabilities of artificial intelligence, specifically deep learning and large language models, to develop a comprehensive system for detecting and explaining oil spills.
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This paper introduces a technology for offshore pipeline inspection centered on an autonomous robotic system equipped with underwater computer vision and edge-computing capabilities.
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This article presents a comparative study evaluating four machine-learning approaches, including three deep-learning methods, for forecasting gas and condensate production over a 5-year horizon.
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This paper describes a deep-learning image-processing model that uses videos captured by a specialized optical gas-imaging camera to detect natural gas leaks.
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In this study, a deep-neural-network-based workflow with enhanced efficiency and scalability is developed for solving complex history-matching problems.
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This study presents a production-optimization method that uses a deep-learning-based proxy model for the prediction of state variables and well outputs to solve nonlinearly constrained optimization with geological uncertainty.
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This paper introduces a novel optimization framework to address CO2 injection strategies under geomechanical risks using a Fourier neural operator-based deep-learning model.
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This paper presents a workflow that combines probabilistic modeling and deep-learning models trained on an ensemble of physics models to improve scalability and reliability for shale and tight-reservoir forecasting.
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SponsoredDive into TAQA’s digitalization and deep learning initiatives that are shaping the company's new approach to its Journey Management System. This innovative concept minimizes transportation-related risks in a period of rapid operations expansion.
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