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A well-pattern-design work flow proved able to identify substantially better patterns than the traditional approach for a giant mature field.

Over the course of 2 days, top energy and non-energy executives join OTC Board members to dissect and discuss future and current challenges facing an industry in the beginnings of substantial change.

This paper describes an artificial intelligence deep Q network for field-development plan optimization.

In this paper, the authors describe a model that uses augmented artificial intelligence to optimize well spacing by use of data sculpting, domain and feature engineering, and machine learning.

The outcome of the authors’ experiments revealed that the tertiary injection of nanoparticles results in additional oil recovery beyond the limit of low-salinity water.

The addition of human-factors questions to the pool of questions will provide future engineers across the energy sector with an opportunity to gain more knowledge on human factors, human-factors-related regulation, industry guidance, and organizations promoting human factors.

The paper focuses on a process developed to identify, evaluate, and eliminate interdependent bottlenecks on the Constitution platform and its flowline network.

The complete paper discusses structural assessments for gravity-based structures, a topic that the authors write is underrepresented in the literature.

Russia’s Nord Stream 2 pipeline is now complete, although gas will not be flowing until regulators issue various approvals, expected by the end of the year.

In a perspective piece that appears in the journal Science, Elaine Hill, an economist in the University of Rochester Medical Center Department of Public Health Sciences, calls for tighter regulation and monitoring of unconventional oil and gas development as more evidence points to the negative health consequences of the practice.