Grinding Out Big Data From Tiny Samples

Topics: Completions Reservoir characterization
Courtesy of Ingrain.
An image of a microscopic rock sample shows the different sources of oil and gas. There is kerogen (green) making up 22% of the volume, while pores with kerogen in them (red) make up 8.6%, and water filled pores (blue) 0.2%. The permeability is from 0.3 to 0.9 microdarcy.

When describing what Ingrain does for oilfield clients, the rock-testing company’s director of unconventional technology, Joel Walls, points out that it is “not just for science.”

He brings it up repeatedly because the company, known for being a pioneer in methods built on imaging ultratight rock at the core level, has built a business testing drilling cuttings to help identify productive, fracturable rock to help operators design better completions.

The pricing and turnaround time is designed to fit into the industry’s need to sharply increase the productivity of wells using better diagnostic testing at a time when drilling has greatly slowed.

“The asset teams and technology that remain in these (operating) companies are some of the best in the industry,” Walls said. With the slowdown there is time to consider what they need to do, plan, and do more testing. The testing is guided by the realization that production performance varies widely from well to well, and from stage to stage due to unpredictable variations in the rock.

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Grinding Out Big Data From Tiny Samples

Stephen Rassenfoss, JPT Emerging Technology Senior Editor

01 May 2016

Volume: 68 | Issue: 5