Latest News

SPE welcomes 199 members into the Legion of Honor recognizing 50 years of consecutive membership in the Society.

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

Oil and gas leaders identified the upcoming US presidential election and economic uncertainty as significant drivers of their decision making for 2025.

Over the past 75 years, drillers have gone from the Stone Age to the Space Age when it comes to technological improvements in well construction methods. Yesterday’s crude wood and iron drilling techniques have given way to today’s video game-inspired controls and robotic assistance—much of which migrated from offshore applications. These advancements have driven costs…

In this vodcast and column, Olivier Houzé explores the polarized views among SPE's members about the energy transition, highlighting the geographic and demographic differences. He examines historical perspectives on energy transitions, evaluates future scenarios, and discusses how SPE can adapt its mission to stay relevant.

This paper delves into the evolving landscape of drilling automation, emphasizing the imperative for these systems to go beyond novelty and deliver quantifiable financial value.

This paper describes a new application that leverages advanced machine-learning techniques in conjunction with metocean forecasts to predict vessel motions and thruster loads.

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 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.

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