DSDE: In Theory

Artificial intelligence and machine learning are gaining acceptance quickly in the oil and gas industry. This article presents key industry applications for these technologies as well as the critical role private cellular networks play in leveraging them successfully.

The authors present an artificial-intelligence and machine-learning technology to obtain a high-level, comprehensive view of all equipment in a facility to detect and map corrosion.

This paper introduces methods to fully couple reservoir simulation with wellbore flow models in fractured injection wells.

This paper provides an alternative solution to identifying, classifying, and vertically distributing fractures and a lateral distribution method for reservoir modeling.

This paper describes a method to determine rig state from camera footage using machine-learning-based vision-analytics approaches.

This study explores pitfalls experienced when using capacitance/resistance modeling as a plug-and-play technique for waterflood optimization and discusses workarounds and mitigations to improve its reliability.

This paper describes the current challenges faced by energy companies, the implications of observable industry trends, the characteristics that potential cybersecurity solutions must meet, and how artificial intelligence (AI) and machine learning (ML) can meet these requirements.

The advantages of merging the realms of information technology (IT) and operational technology (OT) are obvious: cost reduction, improved capabilities, and greater efficiency. These advantages, however, come with a cost because they have affected the way that industrial control systems operate and have increased the exposure of industrial control systems to cyber risk…

An integrated multidisciplinary work flow can improve the assessment of pipeline slugging fatigue for offshore field developments.

This paper presents an integrated work flow to model mechanical properties at sufficiently high resolution to honor accurately rock fabric and its effects on height and complexity and, thus, production.