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Keywords: machine learning
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Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221951-MS
... safety knowledge management adnoc international petroleum exhibition & conference human factor incident investigation oil and ga industry tree analysis incident investigation process machine learning investigation process incident investigation methodology abu dhabi international...
Proceedings Papers

Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221813-MS
... timesteps, not perfect match at well level, etc. The objective of this study is to develop a combined AI and physics driven method for fast and robust procedure to estimate reservoir pressure in space and time, based on a hybrid approach using production injection data, machine learning and material...
Proceedings Papers

Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221825-MS
... and, with the integration of machine learning algorithms, have been extended to applications in gas, gas-alternating-water injection, and other enhanced oil recovery mechanisms. In this paper, we introduce a novel data-driven formulation that reduces the number of optimization parameters by 50% compared to traditional CRM...
Proceedings Papers

Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221877-MS
... Driving the Need for Change Several tailwinds are propelling the necessity for a micro-credentials-based curriculum in petroleum engineering: Technological Advancements: Rapid advancements in technology, including artificial intelligence, machine learning, and automation, are revolutionizing...
Proceedings Papers

Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-222438-MS
... , Arévalo et al. 2022 ), among others, have prepared the ground for a more accurate detection of downhole hazards, such as conditions leading to stuck pipe. This paper presents the utilization of machine learning (ML) to analyze surface data, detect stuck pipe events and classify such events into categories...
Proceedings Papers

Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-222485-MS
... Abstract There are various types of available data, with different data structures, dimensions, and intervals. Conventional big data algorithms can lead to poor interpretability. In this study, novel methods are proposed based on big data analysis and machine learning. First, the data...
Proceedings Papers

Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-222508-MS
... to revolutionize the efficiency, safety, and sustainability of maritime operations, presenting transformative insights for the industry's advancement. machine learning artificial intelligence efficiency maritime operation maritime industry operation safety value chain maintenance sustainability...
Proceedings Papers

Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-222306-MS
... also lead to insufficient injection rate, post-breakdown, to place proppant. A machine-learning (ML) model based on in-depth multidomain analysis can assist in such cases in the design and execution phase. Part I of the paper here covers the extensive ML modeling. The following Part II will cover...
Proceedings Papers

Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-222406-MS
... operator and transfer learning fno model machine learning neural operator transfer learning computational cost dataset fourier neural operator saturation prediction operational condition INTRODUCTION The growing concern over climate change has led to an increased focus on strategies...
Proceedings Papers

Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221862-MS
... critical issues, and capture knowledge for future wells, all while overcoming the challenges of accessing and interpreting large SQL databases. deep learning large language model natural language machine learning artificial intelligence sql query engineer empowering drilling and optimization...
Proceedings Papers

Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221872-MS
... graph with the help from a LLM by augmenting its capabilities using contextual information. Retrieval Augmented Generation Based LLM prompting for Causal Graph Data-driven process management coupled with machine learning have been successful in driving commercial value to oil and gas operators...
Proceedings Papers

Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221883-MS
... operation machine learning natural language decision-making abu dhabi international petroleum exhibition engineer international petroleum exhibition & conference drilling database application drilling report dataset query generative ai Introduction Drilling industry in oil and gas...

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