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.
-
The authors of this paper present a machine-learning-based solution that predicts pertinent gas-injection studies from known fluid properties such as fluid composition and black-oil properties. -
The authors of this paper describe a suite of technologies that enables enhanced well robustness and performance modeling and monitoring of carbon storage facilities.
-
The authors of this paper describe an approach in which all available technologies are combined to improve understanding of reservoir depositional environments.
-
The authors of this paper describe a project aimed at automating the task of cuttings descriptions with machine-learning and artificial-intelligence techniques, in terms of both lithology identification and quantitative estimation of lithology abundances.
-
Finding and producing crude and natural gas is far, far removed from the days of acting on a geologist’s hunch or a wildcatter’s gut feeling.
-
The digital twin aims to allow Petrobras to optimize system settings to maximize production, increase recovery, and reduce risk.
-
The memorandum of understanding aims to improve digital work flows in the emerging carbon capture and storage industry.
-
It is imperative for energy companies to assess potential legal ramifications of integrating artificial intelligence into their operations.
-
For today’s oil and gas companies, digital twins offer untapped potential to decarbonize the leading source of their emissions—field production.
-
The combined firm aims to create a stronger and more diversified geophysical company and energy data provider.
