Data mining/analysis
Earlier this year, 19 teams competed in a machine-learning contest held by the Data Analytics Study Group of SPE’s Gulf Coast Section. The was the first competition of its kind for SPE. Here, the organizers of the contest present some of the techniques used and lessons learned from the Machine Learning Challenge 2021.
“What is the drilling state” has become an important question among data scientists and automation experts. The simplest definition of a complicated concept is that it is what the driller is doing at the time.
The digital repository will use a hybrid cloud architecture to provide subsurface data for the Norwegian Petroleum Directorate.
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GeoMark’s RFDbase contains raw data from every major petroleum basin in the world that can be used in training models to link subsurface characteristics to wellhead performance. -
The oil industry’s rush to capitalize on digital change has scrambled relations with service providers big and small, giving the oil companies a greater say in the process.
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This column is intended to provide a starting point and a roadmap for professionals who want to learn data science and are struggling with the question, “Where do I start?”
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The complete paper uses 3,782 unconventional horizontal wells to analyze the effect of proppant volume and the length of the perforated lateral on short- and long-term well productivity across the Permian Basin.
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Eni and IBM developed a cognitive engine exploiting a deep-learning approach to scan documents, searching for basin geology concepts and extracting information about petroleum system elements.
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Where there are data generated and collected, there is analysis of the data. The ongoing digital transformation in the industry has opened many opportunities for professionals skilled in data analytics.
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Technology company Proserv Controls has formed an alliance with software engineering firm Intelligent Plant in an effort to combine their expertise to improve control systems and data analysis.
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Emerson has launched cloud-native software designed to find opportunities for field development through data mining and automation. The software, called SpeedWise Reservoir Opportunity, was developed in collaboration with Quantum Reservoir Impact.
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The complete paper presents a methodology designed for optimally matching drill bits, mud motors, and bottomhole-assembly components for reduced failure risks and improved drilling performance.
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A recent datathon and the team that took home the grand prize help paint a picture of both the industry’s’ digital transformation and how oil and gas engineers are embracing it to navigate uncertain times.
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