DSDE: In Theory

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.

Can a camera on the drill floor, or one on a mobile phone, measure what is going on during drilling or evaluate drill-bit wear more consistently than a human?

The scale of the recent Colonial Pipeline ransomware attack demonstrates why cyber risk should be assessed as a business risk by organizations’ C-suite, going beyond the narrower view of IT/OT network risk.

Airborne drones with magnetometers have worked well in trials and are ready for more widespread use, potentially revealing thousands of previously unknown wells.

To develop improved predictive models of complex real-world problems, one needs to pursue a balanced perspective. Ultimately, the physics we know needs to rely on data to unmask the physics that we do not yet know.