DSDE: In Theory

The outcome of the authors’ experiments revealed that the tertiary injection of nanoparticles results in additional oil recovery beyond the limit of low-salinity water.

This paper describes a technique used to derive stresses for a gas-storage field and then calibrate the 1D mechanical earth model of the field.

The authors report that nanopolysilicon can be used effectively as a depressurizing, injection-increasing agent.

A well-pattern-design work flow proved able to identify substantially better patterns than the traditional approach for a giant mature field.

The larger data set is expected to provide critical insight for wind resource assessment in the New York Bight lease sale.

The authors examine a theory that low resistivity in a Chinese reservoir is caused by bound water trapped in clay minerals and develop an improved model for production prediction of offset wells.

The oil and gas industry can benefit from the operational insights that IT/OT convergence provides. Predictive maintenance, in particular, helps improve safety and control costs.

Four CEOs describe what goes into turning a world of data into a data-driven world.

The authors demonstrate how artificial intelligence and machine learning can help build a purely data-driven reservoir simulation model that successfully history matches dynamic variables for wells in a complex offshore field and that can be used for production forecasting.

The paper describes an end-to-end deep surrogate model capable of modeling field and individual-well production rates given arbitrary sequences of actions.