Risk and Reward: Big Data and the Next Big Thing
- Janeen Judah (2017 SPE President)
- Document ID
- Society of Petroleum Engineers
- Journal of Petroleum Technology
- Publication Date
- November 2016
- Document Type
- Journal Paper
- 10 - 11
- 2016. Copyright is retained by the author. This document is distributed by SPE with the permission of the author. Contact the author for permission to use material from this document.
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SPE presidents are asked a lot of questions, and I suppose that’s true of anyone who stands in front of an audience as an authority figure. I have learned to expect many of the same questions, no matter the audience: What will the price of oil do? When will the industry turn around? How is the industry managing post-Big Crew Change? What are you going to do to “fix” the situation of women in the industry? What is your view on climate change?
But my favorite question is: What’s the Next Big Thing? As I travel around as SPE President, I see a lot of new and different technologies, operators, and ideas. But my view on the Next Big Thing has been consistent for the last few years: I believe that we are not only entering the era of universal big data, but also the era of more intelligent software to help us make better decisions. The software will help us be better engineers by preserving knowledge and improving decision making.
I believe the Next Big Thing will be infinite big data and intelligent machines to interpret it. Cheaper and more robust sensors will allow us to collect data not only on expensive deepwater completions and big compressors, but also on every isolated onshore well. Cheaper computing power, universal communications, and learning algorithms will allow engineers to use and interpret those large amounts of data to manage assets more efficiently. I believe operators and service providers will be able to reduce risk by using the full value of knowledge and experience to optimize asset management.
I learned to be an engineer in the analog world of the late 1970s and early 1980s. Ours was a world of hand-drawn maps and handwritten columns of figures on green engineering paper. Programmable handheld calculators replaced the slide rule. Data capture was infrequent, monthly at best, and analysis was slow and tedious.
Enter the PC. I vividly remember first getting a PC at work in 1985 after I made the pitch to our district engineer to purchase an IBM PC Model XT for our six-person team. Before then, only special programs could be run on the mainframe at the faraway research center. Our group managed several Permian Basin waterfloods, and we had been doing very tedious calculations by hand. When I was pitching to the district engineer, his first question to me was “how many engineers will this PC replace?” What he didn’t see was that computational power would help the same number of engineers create better analysis and help drive better decisions. Since those ancient days of more than 30 years ago, better, faster, cheaper computing power is everywhere. We haven’t replaced engineers with PCs, but we have created new opportunities for better technical and economic evaluations.
Enter the Internet. When I left ARCO in June 1994, engineers did not have email or Internet access. Three years later, I was emailing work across the Atlantic every day so that teams in Houston and London could collaborate. Now, especially for those of us in global companies, our workflows are completely dependent on instant global communications. But I believe we are only beginning to take advantage of the full potential of the globally connected computing world. The Internet, or Cloud, of Things is coming for all of us.
Another question I’m often asked when I speak is: How will we manage the Big Crew Change? What will the industry do when all these people retire? How are we retaining the knowledge of all those experienced practitioners? I believe that many of my peers who are retiring or have retired as part of the Big Crew Change will continue to consult or work part-time on their own terms. But I think the greatest value will be for these experienced practitioners to help teach not just the next generation of human staff, but also the next generation of intelligent software. Their knowledge can be preserved forever in software that has learned how to duplicate, and eventually improve, their decisions.
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