AI/machine learning
This paper explores how artificial intelligence (AI), cognitive models, and integrated digital tools can transform readiness from periodic drills into a continuous, measurable capability.
This paper presents an autonomous, data-driven solution designed specifically for intermittent well optimization.
From AI-enabled walking rigs to subsea drones and autonomous inspection robots, robotics is rapidly moving from pilot projects to field deployment. The technology promises not only greater efficiency but also a fundamental shift in how the industry approaches safety and asset management.
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The USGS has said up to 19 million tons of lithium resource is contained in the briny waters of the Smackover formation in Arkansas. -
Subject-matter experts from industry and academia advanced distributed fiber-optic sensing technologies and their implementation in flow measurement during a special session.
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This paper investigates the use of machine-learning techniques to forecast drilling-fluid gel strength.
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Technology uptake aimed at optimizing resources, delivering consistency, and augmenting what humans can do.
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Machine learning and a decade of gas composition records helped the operator identify wells that were most likely to produce paraffins.
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The companies plan to develop new artificial-intelligence-powered processes and workflows to optimize oil and gas production.
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Routine status reporting often presents a challenge because of its intimidating and time-consuming nature for both employees and supervisors. With large language models, a system was developed to generate coherent artificial-intelligence-driven reports. The goal is to enhance the understanding of overall insights and reduce the time required for individual report read…
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This paper aims to emphasize the importance of decision-making based on quantitative monitoring outputs, from both a business perspective and an ecosystem-service perspective, in future offshore projects.
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Experts at SPE’s Annual Technical Conference and Exhibition say that despite AI’s great potential, it’s important to be realistic about AI’s capabilities and to remember that successful projects solve specific business problems.
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The industry’s vast untapped data resources have the potential to change how our industry works—if we can piece it together.
