modeling

Broad consensus is forming on the need for a massive expansion in global carbon capture and storage (CCS) capacity. But what are the uncertainties, bottlenecks, and opportunities in the subsurface that await CCS planners?

The authors develop a representative geostatistically based 3D model that preserves geological elements and eliminates uncertainty of reservoir properties and volumetric estimates for a Libyan field.

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 complete paper demonstrates the benefits of honoring data measurements from a multitude of potential sources to help engineers do a better job of including more diagnostics into routine operations to provide additional insight and result in improved models and completion designs.

An AI-based application enabled operators to preempt ESP failures while optimizing production.

Using the supplied data set of cone penetration test results, competing teams had to predict the number of hammer blows required to drive the pile a given unit of depth in the North Sea.

This paper updates a previous case study and presents the results of actual implementation of an optimized steam-injection plan based on the model framework.

Data-driven methods offer significant advantages in the industry, under certain conditions, over conventional methods. But reservations still exist about their use. The paper serves to bridge the gap between unclear understanding of these methods and their successful acceptance and implementation.

By measuring which tests best predicted the fractures observed at the Hydraulic Fracturing Test Site, Laredo Petroleum developed a method it hopes will improve fracture modeling in other places.