IT and the Digital Oilfield: "Operations Intelligence" Skills Needed

After attending the Intelligent Energy Conference in Amsterdam last February, I was struck by Karl Jeffrey’s Letter from the Editor in the April/May 2008 issue of Digital Energy Journal. Much of what he says in “Please can we call this IT again?” is accurate.

There is a lot of confusion around the terms “Digital Oilfield”, “Smart Fields”, and “Fields of the Future”. Understandably, the vision of improving production and operations efficiency using sophisticated data collection, communication, analysis, and decision support tools is compelling. However, there does not appear to be a consensus or model describing the necessary components to support the digital oilfield.

Take, for example, use of the term “optimization”. To some, this means determining the best way to deplete a reservoir. To others, it is a way of automating the use of pumps, valves, and other control systems to ensure reliability and “optimal” flow of product along a system or pipeline. And, to others, it represents a branch of mathematics that can be used to support decision making for challenges in scheduling, planning, blending, and asset management.

Indeed, if you try to use Google to educate yourself about this phenomenon, you will quickly become frustrated. Choosing an effective search term is very difficult. Do you use “oil field optimization”, “intelligent oil field”, “digital oilfield”? Try it and see what you find.

Mr. Jeffrey makes the point that all of this should fall under the rubric of “information technology”. I agree, but with some qualifications.

Information technology (IT) usually connotes a group within a company and not a discipline per se. Its organizational origin dates from the days of the data processing group. Today, the challenges extend far beyond data collection and data management. In turn, the IT skills required go beyond selection of hardware software, systems analysis, application design and development, and systems management. Often missing from typical IT teams are people with domain-specific knowledge (rig scheduling, reservoir planning, etc.) and people with relevant background in decision-making sciences such as operations research and artificial intelligence. These skills are necessary to develop solutions that provide true decision support as opposed to solutions that simply collect, store, and manage data.

Mr. Jeffrey’s suggestion that we should halt the separation of IT from “digital oilfield” groups makes sense. I would simply add that solving “digital oilfield” challenges requires multi-disciplinary teams comprising members with specialized domain knowledge, people with IT skills, and people with appropriate mathematical backgrounds in decision-making sciences. Ideally, these teams should focus on providing actionable operational intelligence to their organizations. What we call it is less important than how we do it, and doing it well requires more than most IT groups can provide.