modeling

This paper describes an automated workflow that helps mitigate sanding caused by excessive drawdown by determining the minimum tubinghead pressure.

This paper presents a closed-loop iterative well-by-well gas lift optimization workflow deployed to more than 1,300 operator wells in the Permian Basin.

This paper explores the use of machine learning in predicting pump statuses, offering probabilistic assessments for each dynacard, automating real-time analysis, and facilitating early detection of pump damage.

This paper focuses on developing a model that can be used in an automated, end-to-end flare-smoke detection, alert, and distribution-control solution that leverages existing flare closed-circuit television cameras at manufacturing facilities.

This paper describes an alternative lower-completion concept for developing Lower Wilcox reservoirs referred to as high-angle multifractured well design.

This study explores the feasibility of implementing in-situ carbon dioxide recycling for sequestration as a fit-for-purpose developmental strategy for a Malaysian gas field characterized by an initial carbon-dioxide content of approximately 60%.

In today’s era of asset management, digital twins are changing risk management, optimizing operations, and benefitting the bottom line.

This study assesses the advantages, constraints, and necessary enhancements of both passive and active electromagnetic techniques in the context of carbon capture and storage.

This paper presents a novel workflow with multiobjective optimization techniques to assess the integration of pressure-management methodologies for permanent geological carbon dioxide storage in saline aquifers.

This study integrates physics-based constraints into machine-learning models, thereby improving their predictive accuracy and robustness.