Big Data, Big Decisions: Capturing the Power of Data in Operations and Business
There are certain developments in the world that are far bigger than our industry, let alone the facilities component of the oil and gas industry, which is the part of our industry that most of us are dealing with on a daily basis. Every now and then I focus on one of those developments, and then select some papers that provide a good overview in the hope that readers are tempted to read them to gain a better understanding of that issue. A good example is nanotechnology, a topic highlighted previously, and if you missed it, I encourage you to take a look at the related synopses and papers.
This time I want to draw your attention to big data. In recent months, this topic came up in numerous ways. The University of Berkeley announced earlier this year that they would create a division to study the science of mining digital information, and their fastest-growing class is Data Science 101, which deals with mining the increasing amount of data. This should not come as a major surprise, as almost everybody has heard of big data.
Yet in our industry we are somewhat slow to adopt this data mining process, as was outlined in a 2018 OTC paper. The authors made a very interesting observation: there is a need industrywide to adapt our culture and business models to create an environment that fosters innovation, collaboration, and readily adopts new ways of working.
Obviously there are plenty of examples where this is already practiced in our industry, as was highlighted in another OTC paper that dealt with a low-manned platform [video] in a remote area. But the fact remains that we are not in the forefront, and that may in part be due to the ethical issues associated with data mining, an issue that was explored in a paper presented at the SPE Western Regional Meeting in April of this year.
A paper that is more theoretical evaluates the status of data-driven methods, but it provides a good overview of the modeling techniques that are applied, and gives examples of applications of those techniques in our industry. It then closes with a discussion on the acceptance in the oil and gas industry, where the authors conclude that many oil and gas companies are still reluctant to adopt these technologies, which reiterates the finding of the first paper.
Finally, a paper describing the data management and digitization of subsea assets [video], which is lagging behind compared to topside facilities, is included.
I hope that you will read (or watch) some of these selected items, not just to get a better understanding of the big data topic, but to explore how each of us can do our part in creating an environment that fosters innovation and adopting new ways of working. And if you have seen good examples, let me know and I would be happy to showcase them in a future follow-up.
This Month's Technical Paper Synopses
Artificial Intelligence Gains Traction Across the Industry
Artificial intelligence is already part of the work done in an office near you, and before you know it, it will be in your office as well. Gaining familiarity and an understanding of it will serve you well.
Artificial Intelligence Improves Business Outcomes for Offshore E&P
Despite streams of data being available on platforms about the condition of topside and drilling equipment, most experts agree that only a small fraction of such data is used. Whether for a fleet or single platform, AI can transform an offshore enterprise.
DNV GL Launches Pilot To Quantify Quality and Integrity of Digital Twins
In partnership with TechnipFMC, DNV GL opened a pilot project for the international collaboration of operators and the supply chain. Many digital twins represent an asset’s initial form and struggle to reflect developments in their physical counterparts as the asset matures.
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20 May 2020
20 May 2020