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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The authors of this paper describe the development of a continuous monitoring solution throughout its deployment. -
Whether buying or selling, quality, non-production data can help operators achieve improved margins and less downtime, unlocking the true potential of their wells.
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SponsoredEach well drilled, stimulated, and completed represents a significant investment in time, resources, and expenses. From artificial lift system design to maintenance scheduling, maximize your investment by ensuring optimal flow and production throughout the life cycle.
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The company revealed programs for managing production and industrial asset performance. It also announced a collaboration aimed at enhancing rig visualization.
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SPE Data Science and Engineering Analytics Technical Director Silviu Livescu and SPE Reservoir Technical Director Rodolfo Camacho address some of the challenges in the application of data analytics, artificial intelligence, and machine learning to several reservoir engineering problems.
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The company used an uncrewed surface vessel and an electric remotely operated vehicle to conduct a survey for TAQA in the North Sea.
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The use of artificial intelligence in the clean energy sector increases the availability and accessibility of clean energy, making it a more viable and cost-effective alternative to traditional energy sources.
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This paper introduces a measurement system that is agile for transport and can be installed anywhere with a small footprint while delivering reasonably accurate results.
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This paper describes how a surveillance, analysis, and optimization plan was used to resolve subsurface uncertainties and optimize a reservoir development plan and provides lessons learned and best practices.
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The authors of this paper present an autonomous directional-drilling framework built on intelligent planning and execution capabilities and supported by surface and downhole automation technologies.
