Case Study: Data Science for Reservoir Characterization and Field Development Decision-Making

The upstream oil and gas industry generates a large amount of data, and data science promises to unlock tremendous value through its analysis.

Multi-disciplinary, high-resolution models are being used to make field development decisions; yet, subsurface data are often sparse, difficult to interpret, and scattered across different storage media and locations. We urgently need new data sources and more efficient, accurate measurements to reduce uncertainties and render our models more effective.

In this case study we discuss:

• Faster, lower-cost approaches to core analysis
• Drill cuttings as an under-appreciated source of rock property data
• New approaches to generating and sharing data that can lead to transformative performance for the companies willing to adopt and embrace them