AI/machine learning
This article is the third in a Q&A series from the SPE Research and Development Technical Section focusing on emerging energy technologies. In this piece, Zikri Bayraktar, a senior machine learning engineer with SLB’s Software Technology and Innovation Center, discusses the expanding use of artificial intelligence in the upstream sector.
This article presents a results-driven case study from an ongoing collaboration between a midstream oil and gas company and Neuralix Inc.
As carbon capture scales up worldwide, the real challenge lies deep underground—where smart reservoir management determines whether CO₂ stays put for good.
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The complete paper provides an approach using machine-learning and sequence-mining algorithms for predicting and classifying the next operation based on textual descriptions. -
The complete paper describes an automated machine-learning approach to determine the spatial variation in decline type curves for shale gas production, based on existing data of production, completion, and geological parameters.
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In addition to the well-recognized elements of digital transformation such as real-time monitoring, remote intelligence, and extraction of insights from data, there is a need to evolve the industry hardware through application of enhanced edge computing.
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Deep learning is routinely used in products and services that affect hundreds of millions of lives, despite the fact that no one quite understands how it works. Now, the Office of Naval Research has awarded a $7.5 million grant to a group of researchers who think they can unravel the mystery.
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“Being mindful is about being intentional,” said Ahmer Inam, chief AI officer at technology consulting firm Pactera Edge. “Mindful AI is about being aware and purposeful about the intention of, and emotions we hope to evoke through, an artificially intelligent experience.”
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Advanced machine-learning methods combined with aspects of game theory are helping operators understand the drivers of water production and improve forecasting and economics in unconventional basins.
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The complete paper discusses optimization of a development plan involving low-salinity water injection.
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Decline-curve analysis is one of the more widely used forms of data analysis that evaluates well behavior and forecasts production and reserves. This paper presents technologies that apply DCA methods to wells in an unbiased, systematic, intelligent, and automated fashion.
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Using 3D and artificial intelligence technologies, a digital map of all three bridge-linked jackets was captured, enabling Neptune to detect asset-integrity issues early and plan fabric maintenance work on Cygnus.
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This story reviews well-adopted ideas that have stood the test of time, presenting a small set of techniques that covers a lot of basic knowledge necessary to understand modern deep learning research.
