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
Machine Learning Improves Accuracy of Virtual Flowmetering and Back-Allocation
In this study, the authors investigated a fully data-driven approach using artificial neural networks (ANNs) for real-time virtual flowmetering and back-allocation in production wells.
Permanent Fiber-Optic System Monitors Oil-Rim Movement
In this paper, the authors describe a project to design, field trial, and qualify an alternative solution for real-time monitoring of the oil rim in carbonate reservoirs that overcomes these disadvantages.
Surface-to-Borehole Electromagnetics Hold Promise for 3D Waterflood Monitoring
The authors detail the development of a technique based on surface-to-borehole controlled-source electromagnetics (CSEM), which exploits the large contrast in resistivity between injected water and oil to derive 3D resistivity distributions, proportional to saturations, in the reservoir.
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25 March 2019
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