Testing page for app

Shale Ingenuity’s first pilot used common natural gas liquids to boost daily output 30-fold from a low-producing horizontal well in Texas.

The Energy & Environmental Research Center in North Dakota outlines the difficulty that the oil and gas industry faces in pinpointing sources of H2S production.

These papers underscore the need for strategic adaptation of automation systems to the specific challenges of offshore environments. The success of predictive machine learning in this context depends on its ability to offer measurable financial benefits, improve safety, and drive operational efficiency.

The industry’s vast untapped data resources have the potential to change how our industry works—if we can piece it together.

This paper presents the processes of identifying production enhancement opportunities, as well as the methodology used to identify underperforming candidates and analyze well-integrity issues, in a brownfield offshore Malaysia.

This paper describes an optimized multizone single-trip gravel-pack system developed and implemented successfully in Brunei.

This paper describes the qualification of a multilayer, open-cell matrix polymer system for the first horizontal deployment in an offshore gas well.

This work presents the results of several failure analyses of gas lift valves retrieved from subsea wells that were unable to prevent backflow from tubing to annulus

This paper describes installation of autonomous inflow control valves in the Bretaña Norte field in Peru, enabling effective water control even though the trial well was placed in the flank, close to the oil/water contact.

This paper presents a workflow that combines probabilistic modeling and deep-learning models trained on an ensemble of physics models to improve scalability and reliability for shale and tight-reservoir forecasting.