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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Artificial intelligence tools present many opportunities for the energy industry, and, as technological concepts leave the realm of science fiction, companies have started to grasp what is possible. What roles do culture and ethics play in helping companies understand the digital revolution? -
Partnerships with big tech, tech startups, and innovative service companies—and the merging of their data, cloud, and software applications—are proving essential for operators in the scaling phase of digital deployment. Equinor, Microsoft, and Halliburton are among those joining forces.
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A case study in the deepwater Gulf of Mexico in which pressure transient analysis, fractional flow, and production logging tools were integrated to identify correctly the cause of, and execute an effective remedy for, a well’s productivity deterioration.
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Digital technologies serve as a primary theme of this year’s group, with a few environmentally conscious firms included in the mix.
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This article discusses the role of data management in the context of exploration and production from the 1990s, when building centralized databases was the mainstream, to the end of the second decade of the 2000s.
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Most industries measure digital transformation by accelerated, highly visible outcomes—from new business models and efficient processes to experiences that wow customers and employees alike. But not the oil and gas industry. In fact, it may be following a completely different playbook.
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Two firms have announced new partnerships to perform unmanned-aircraft-systems-based missions for oil and gas clients in the US and abroad.
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The service company said it will make its data ecosystem available to the platform that is designed to bring together exploration, development, and wells data from across the industry. This will allow Schlumberger to integrate its solutions with its clients who have already joined the platform.
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At times, it may seem that machine learning can be performed without a sound statistical background, but this does not take in to account many difficult nuances. Code written to make machine learning easier does not negate the need for an in-depth understanding of the problem.
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The upstream sector is witnessing comparatively more implementation of the industrial Internet of things compared with other sectors of the oil and gas industry. This is driven by the need to reduce risk and maximize returns through digitalization, according to data and analytics company GlobalData.
