Digital oilfield
This paper presents a case study highlighting the demonstration, refinement, and implementation of a machine-learning algorithm to optimize multiple electrical-submersible-pump wells in the Permian Basin.
This paper presents a closed-loop iterative well-by-well gas lift optimization workflow deployed to more than 1,300 operator wells in the Permian Basin.
This paper explores the use of machine learning in predicting pump statuses, offering probabilistic assessments for each dynacard, automating real-time analysis, and facilitating early detection of pump damage.
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This paper highlights a new online system for monitoring drilling fluids, enabling intelligent control of drilling-fluid performance. -
This paper investigates the use of machine-learning techniques to forecast drilling-fluid gel strength.
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This paper describes the suite of cloud-based digital twin tools that the operator has developed and is integrating into its operations, providing online, real-time calculation of scale risk and deployed barrier health to manage risk on a well-by-well basis.
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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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Aker BP plans to use a software platform from TGS as a process data server designed to improve field operations.
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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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This paper presents the processes of identifying production enhancement opportunities, as well as the methodology used to identify underperforming candidates and analyze well-integrity issues, in a brownfield offshore Malaysia.
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In this exclusive Q&A, Giovanni Cristofoli, senior vice president of bp Solutions, shares insights into how his team is redefining operational strategies and fostering agility to bridge competitive gaps and enhance efficiency. Highlights include the integration of digital tools, data science, and a unified approach to tackling complex problems.
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This paper describes the development of a comprehensive digital solution for well surveillance and field-production optimization for an offshore field consisting of four stacked reservoirs, each containing near-critical fluids.
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This paper describes a new integrated workflow for automated well monitoring using pressure and rate measurements obtained with permanent gauges and flowmeters.
