Testing page for app

This study compares seven imputation techniques for predicting missing core-measured horizontal and vertical permeability and porosity data in two wells drilled in the North Rumaila oil field in southern Iraq.

The integration of AI within the oil and gas industry is rapidly gaining momentum. With ongoing advancements, the future of formation evaluation promises transformative changes, leading to more-efficient and accurate reservoir characterization methodologies.

The Earth has huge capacity to store carbon dioxide emitted from energy production. This article discusses the technology of carbon capture, utilization, and storage (CCUS) and its challenges.

This paper describes an approach that combines rock typing and machine-learning neural-network techniques to predict the permeability of heterogeneous carbonate formations accurately.

This study describes the performance of machine-learning models generated by the self-organizing-map technique to predict electrical rock properties in the Saman field in northern Colombia.

SPE President Terry Palisch is joined by his son Austin Palisch, staff engineer at Liberty Energy, to recap Terry’s year as president.

Based on 6 years of firsthand experience, refrac experts share some of their biggest insights into where the US market is headed and how to identify the best candidates.

A special Legends of Artificial Lift Luncheon on 20 August at the SPE Artificial Lift Conference and Exhibition celebrated six individuals for their outstanding contributions to the technical knowledge in this field: Ali Hernandez, Louis Ray, Francisco Alhanati, James Hall, Lawrence Camilleri, and Toby Pugh.

The new frontier of production improvement combines surveillance techniques and analysis to determine which variables boost output.

The selected papers confirm that subsea systems will continue to play a significant role in providing reliable, affordable, stable, secure, and sustainable energy across the globe and will continue to grow for many decades.