This paper describes an approach to creating a digital, interconnected workspace that aligns sensor data with operational context to place the completions engineer back into a central role.

This paper demonstrates how the integration of multiphysics downhole imaging with machine-learning techniques provides a significant advance in perforation-erosion analysis.

Data centers could add up to 6 Bcf/D of US gas demand by 2030, creating a new opportunity for producers and reshaping how oil companies think about electricity supply.

This paper presents a workflow that leverages a multiagent conversational system to integrate data, analytics, and domain expertise for improved completion strategies.

Two examples from ONGC show how supervised AI-driven automation scaled well modeling across hundreds of offshore wells, saving more than 1,000 engineering hours.

Examples demonstrate how an Integrated Operations Center as a Service (IOCaaS) model, powered by artificial intelligence, reduced costs by 5% and increased production by 6% in Canada.

The three featured papers illustrate how emerging computational methods—ranging from gradient-based optimization to data-driven proxies—are reshaping reservoir characterization, uncertainty assessment, and real-time decision support across diverse subsurface applications.

This paper demonstrates the effectiveness of integrating dynamic gas separation with existing gas-avoidance methods within the same electrical submersible pump string to address these issues.

The operator developed a solution that has kept the well at stable production for over a year after treatment.

Leaders of SPE’s Artificial Lift Technical Section outline the group’s mission, recent technical highlights, and a growing slate of global events shaping the future of artificial lift.