modeling

This paper provides insight into designing advanced well completions offshore West Africa with autonomous inflow control devices that enable maximizing the producing life of the wells under various challenging reservoir conditions.

One hydraulic fracturing job can stimulate two wells, but economic success hinges on doing it in the right place for the right price.

Collaboration agreement lays foundation for advancing tech and know-how for harsh environment operations.

The industry is balancing brains and bots as it squeezes out barrels of oil production.

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

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.

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.

This paper discusses the ecosystem challenges that face the development of nonmetallic tubulars, ranging from academia and research institutes to material suppliers and manufacturing facilities for pipe prototyping.

The authors of this paper review the advantages of machine learning in complex compositional reservoir simulations to determine fluid properties such as critical temperature and saturation pressure.