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This paper describes an intelligent completion system in the context of multiple wells that, by electrifying the process, replaces the conventional electrohydraulic systems that have been in use for decades.

This paper aims to present thoroughly the application of subsurface safety injection valves in extremely high-temperature environments.

This paper aims to provide insights to address the challenge of identifying the optimal point within the gas-processing lineup for recovering a high-purity CO₂ stream suitable for sequestration.

Recently, artificial intelligence (AI), deep learning (DL), and machine learning (ML) have taken natural gas processing and handling on a new trajectory, replacing complex simulation runs.

Most sustainability efforts have been put into alternative or renewable energy research and development and in reducing flaring and venting intensity. While the industry has shown great progress in these areas, there are still many areas that could contribute to sustainability aspirations, one of them being well completions.

The era of refracs as mere experiments is long gone; today, they’re a strategic necessity fueling portfolio growth.

After 5 years of in-depth diagnostic research, the Oklahoma City-based operator shares more insights on fracture behavior.

In this study, a deep-neural-network-based workflow with enhanced efficiency and scalability is developed for solving complex history-matching problems.

This study presents a production-optimization method that uses a deep-learning-based proxy model for the prediction of state variables and well outputs to solve nonlinearly constrained optimization with geological uncertainty.

New case studies highlight how artificial intelligence, advanced hardware, and innovative business models are enabling success in drilling automation.