Data & Analytics
Supervised learning was used to develop an ensemble of models that account for historical production data, geolocation parameters, and completion parameters to forecast production behavior of oil and gas wells.
The combined effort aims to reduce the time necessary for and increase the detail and accuracy of seismic interpretation, including for carbon sequestration studies.
The 2023 Offshore Energy Digital and Data Maturity Survey report aims to deepen understanding of how organizations are applying data and digital technologies to help transform the UK energy system to achieve net zero targets.
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Artificial intelligence is increasingly being used to assist in the development of materials, including metal-organic frameworks (MOFs), to advance carbon capture technologies. Researchers assembled more than 120,000 new MOF candidates within 30 minutes. -
Early adopters of large language models praise the technology’s promise to advance upstream research and software development while also offering cautionary notes.
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The company plans to overlay data from the MethaneSAT satellite onto its Google maps to assist in understanding which types of oil and gas equipment tend to leak most.
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This article describes how Oxy developed an in-house application to handle critical production operations tasks including surveillance, optimization, downtime entry, and well testing. The application, called Nexus, allows well analysts and production engineers to manage twice the number of wells they were able to manage just 5 years ago.
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SEG and SPE join forces to offer access to a robust research portal that harnesses the power of AI and ML.
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This article explores the effect of quantum computing on data science and AI, looking at the fundamental concepts of quantum computing and the key terms used in the field. It also covers the challenges that lie ahead for quantum computing and how they can be overcome.
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The Taiwanese company is upgrading its ships in an effort to improve its ability to work with companies pursuing offshore renewable energy.
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This paper addresses the challenges related to well control and the successful implementation of deep-transient-test operations in an offshore well in Southeast Asia carried out with the help of a dynamic well-control-simulation platform.
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The authors of this paper propose an artificial-intelligence-assisted work flow that uses machine-learning techniques to identify sweet spots in carbonate reservoirs.
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This paper presents an approach for automatic daily-drilling-report classification that incorporates new techniques of artificial intelligence.
