Production

Unlike traditional AI approaches that rely primarily on historical data, physics-based AI integrates physical laws, engineering expertise, and operational constraints directly into the learning process. Three recent SPE papers illustrate how this paradigm is transforming the industry through intelligent condition monitoring, virtual sensing, and autonomous production …

A combination of physics principles and machine-learning techniques is used in this work to develop a virtual flowmeter for oil-production optimization in electrical-submersible-pump-lifted oil wells, resulting in reliable generalization.

This study explores the carbon-capture and mineralization potential of ultramafic rock powders when exposed to flue gases generated from combustion of crude oil and mesquite-derived charcoal.

This paper presents the deployment of an artificial intelligence-enabled autonomous gas lift optimization system, integrating real-time centralized advanced process control with cloud-based analytics to enhance artificial gas lift performance in producer wells.

As the pace of new discoveries slows and high-quality prospects become harder to find, oil companies may need to rely more heavily on mature fields to maintain production and support future supply.

The solvent-based technology involves a modular treatment process that uses a proprietary catalyst designed to safely and sustainably remove hydrogen sulfide (H₂S) from sour gas streams using either produced water or an alkaline water as the treating media.

With confidence in subsea boosting performance growing, BP is incorporating pumping systems into both greenfield developments and brownfield expansions.

The legacy of per- and polyfluoroalkyl substances (PFAS) is a persistent problem in many industries, including upstream oil and gas. In this Q&A, remediation expert Grant Scott presents the trouble with these “forever chemicals” and the mitigating efforts being used.

At the inaugural SPE/ICoTA Asia Pacific Well Intervention and P&A Conference and Exhibition in Kuala Lumpur, industry leaders highlighted how high-fidelity well data, real-time diagnostics, and predictive technologies are reshaping intervention planning and execution to improve well performance, reduce risk, and optimize late-life asset management.