The Power of Cognitive Technology
Authors: Quesada Santiago 
Published: January 2017

Management

It has been over a year since Repsol and IBM announced their plans to jointly develop cognitive technologies that would allow human decision makers operating in the oil and gas industry to interact with computers more effectively, enhancing the industry’s ability to source, analyze, and filter big data to make it more consumable.

Building on what is commonly referred to as artificial intelligence, experts in this field are developing “super computers,” which are able to understand, learn from, and interact with humans. Many different companies in various sectors are currently developing cognitive technologies for specific activities, with the most pioneering being applied to the exploration and production (E&P) sector of oil and gas.

In an environment of low oil prices and ever tighter margins, cognitive technology can help energy companies increase the productivity of their oil and gas fields and minimize exploration risk when searching for new resources. The objectives of Repsol’s collaboration with IBM were twofold: to leverage cognitive computing capabilities to specifically help Repsol reduce the risk and uncertainty of future oil field acquisitions and to maximize the yield of existing oil fields—both of which can have a significant impact on the efficiency of global E&P operations of Repsol and other oil and gas companies.

Currently, offshore E&P is a capital-intensive exercise. The drilling of a single well can cost up to USD 400 million and the data used to determine the best location to search and drill for oil are often extremely limited and inaccurate. By developing these cognitive technologies, Repsol and IBM have been able to bring decision makers together, helping them to share insights, gather data sets from multiple sources more easily, and enable better, more prescriptive analysis. The ability to overcome limitations posed by big data has led to less uncertainty and, ultimately, reduced operational risk.

Optimizing Reservoir Production

Looking specifically to the optimization of reservoir production, a cognitive environment can adapt to the individual needs of a varied set of technical experts, equipping them with the tools needed to enhance their abilities to analyze data from varied sources. Technicians have also been able to tie in existing production models with the analyzed data and adjust them to more accurately match current production as time goes on.

Inspiration came in part from Repsol’s Excalibur project, launched with the objective of optimizing deposits. The project, tested in remote offshore fields in Ecuador and Brazil, was a combination of tools developed at the Repsol Technology Center. Excalibur uses mathematical techniques to comprehensively identify and evaluate deposits, optimize their development, and minimize risk. The tool enables a deposit portfolio to be quickly and accurately ranked and new investment opportunities to be identified that are difficult to detect using traditional techniques. In the tests carried out on a North Sea deposit, Excalibur achieved an improvement of 9% on the best solution published to date by other research companies and institutions.