Data & Analytics
This research focuses on combining physics-based expert rules with machine learning to improve the detection of failure-related events in electrical submersible pumps.
A combination of physics principles and machine-learning techniques is used in this work to develop a virtual flowmeter for oil-production optimization in electrical-submersible-pump-lifted oil wells, resulting in reliable generalization.
This paper presents the deployment of an artificial intelligence-enabled autonomous gas lift optimization system, integrating real-time centralized advanced process control with cloud-based analytics to enhance artificial gas lift performance in producer wells.
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This paper presents the design and development of a prototype intelligent water-injection and smart allocation tool aimed at achieving autonomous waterflood operations. -
This paper addresses the challenges of integrating huge amounts of data and developing model frameworks and systematic workflows to identify opportunities for production enhancement by choosing the best candidate wells.
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This paper described the use of digital twin technology to identify design modifications required at an onshore site and visualize proposed offshore assets for a Trinidad and Tobago development.
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Developing alternative power supplies with wide-scale reliability, dependability, and minimization or elimination of GHG emissions within feasible capex/opex scenarios is the brass ring of sustainability and energy security—and data are helping us get there.
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In the pursuit of sustainable industrial operations, three pivotal objectives emerge: risk reduction, safety assurance, and cost minimization. Integrating these objectives into digital transformation strategies enables operators to effectively manage emissions and achieve success.
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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.
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The combined effort aims to reduce the time necessary for and increase the detail and accuracy of seismic interpretation, including for carbon sequestration studies.
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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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Stakeholders in the UK offshore sector will be asked to commit to a set of principles to help the sector achieve the energy transition through digitalization.
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The national oil company credits lean operating practices and AI for making the three-well, 45,000 B/D project economically viable.
