Digital Oil Field

This paper presents a case study highlighting the demonstration, refinement, and implementation of a machine-learning algorithm to optimize multiple electrical-submersible-pump wells in the Permian Basin.

This paper presents a closed-loop iterative well-by-well gas lift optimization workflow deployed to more than 1,300 operator wells in the Permian Basin.

This paper explores the use of machine learning in predicting pump statuses, offering probabilistic assessments for each dynacard, automating real-time analysis, and facilitating early detection of pump damage.

Digitalization and advanced analytics have enabled drilling automation that is changing the way wells are executed to deliver more production earlier.

Real-time wellhead monitoring aims to help Romania meet new EU methane emission regulations.

The paper describes the deployment of fiber-optic monitoring of CO₂ injection and containment in a carbonate saline aquifer onshore Abu Dhabi.

Intelligent completions could improve many of the world’s oil and gas wells, but not all are suited to the technology. There is another option.

This article explores how the pursuit of a "perfect" reservoir model may be hindering progress in an industry increasingly shaped by data, uncertainty, and AI.

Operators that demand control of their future position in global energy production are forging ahead into new territory by digitally transforming their operations at a time that still feels relatively comfortable. They’ve recognized that, while traditional approaches served the industry well for many decades, the chance to reimagine how they do things is not something…