Intelligent Fields Technology
I’m sure you’ve seen it very obviously happening all around us. Yet, looking at the details still surprises. While reviewing the papers published in the intelligent-fields area this year, I was struck by the contrast I saw compared with just 3 years ago. Novel and niche are giving way to systemic and pervasive. What only recently was the domain of academics and research types with larger operators and service companies has broadened to an amazing diversity of practitioners.
The papers mirror what I see and hear in many of the companies I interact with. Yes, our companies have hired more people with formalized training in data science, but what I find impressive is the number of people who were hiding in normal discipline jobs only a few years ago who are coming out of the closet with their Python scripts. And, it’s working. In many ways, order is coming to the mess, efficiency is coming to tiresome manual activities, and richness is coming to our decisions.
So, what changed that we are more rapidly seeing the promised progress?
I associate much of the acceleration to what I would call an open-source mentality, an approach that prefers to find an appropriate, available solution that is easily accessible, rather than developing or buying something fit-for-purpose. “There’s an app for that” has evolved to marketplace models, not only on your smart phone but also now in the Jupyter notebook on your desktop or in the marketplace of your cloud environment. As a result, or perhaps as a driving part of the changes, tech giants such as Amazon and Microsoft are finding their part in the energy sector by providing convenient and efficient marketplaces supporting integration of open-source and proprietary technologies. Smaller companies and startups can deliver low-cost solutions to such environments, and cooperative developments such as the Open Earth Consortium will bring further efficiencies by delivering standard oil-and-gas-specific frameworks. Instead of armies of developers delivering the next generation over 5 or 10 years, a capable community is emerging that can deliver a multitude of small advances that build on synergies of existing capabilities.
I hope to see you at the SPE workshop on Smart Integration in Production System Modeling on 19–20 June in Galveston, Texas, USA.
This Month's Technical Papers
Intelligent Fields Technology
John Hudson, SPE, Americas Regional Support and Development Manager, Shell
01 May 2018
How Southeast Asian Upstream Operators Are Digitalizing
Malaysia’s Petronas, Shell Malaysia, and Thailand’s PTTEP are now in the midst of full-scale digital adoption. The companies are beginning to see results, but none is counting on a “big bang” in development of the technology soon.
Analytics Solution Helps Identify Rod-Pump Failure at the Wellhead
This paper presents an analytics solution for identifying rod-pump failure capable of automated dynacard recognition at the wellhead that uses an ensemble of ML models.
Augmented Artificial Intelligence Improves Data Analytics in Heavy-Oil Reservoirs
The authors of this paper propose a novel work flow for the problem of building intelligent data analytics in heavy-oil fields.
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