modeling

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.

In the complete paper, a new, fully coupled implicit tool was used to model an onshore Omani asset with multiple reservoirs, each featuring different fluids and multiple networks.

The complete paper aims at a better understanding of the effect of channel content in complex fluvial channel systems on well-test-derivative responses.

A computational fluid dynamics model is proposed to analyze the effect of hydrate flow in pipelines using multiphase-flow-modeling techniques. The results will identify the cause of pipeline failure, regions of maximum stress in the pipeline, and plastic deformation of the pipeline.