Data mining/analysis
A roundtable discussion during CERAWeek pointed to the necessity of a mindset shift for the oil and gas industry to tap into AI’s true potential.
Technology and partnerships play a pivotal role in how the oil industry finds and produces energy from frontier regions and brownfields, both now and in the future.
The authors make the case that data science captures value in well construction when data-analysis methods, such as machine learning, are underpinned by first principles derived from physics and engineering and supported by deep domain expertise.
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Health, safety, and environment operations can be greatly enhanced by using artificial intelligence (AI) techniques on HSE data. One important aspect inherent in this process is the need to establish trust in the AI system among the users. -
The seismic and well data investigation tool integrates work flows to provide a consistent analysis of reservoirs.
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Premier Corex and Teverra will be combining their efforts to aggregate data for companies involved in large-scale geothermal projects.
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This paper proposes a series of work flows to simplify model deployment and set up an automatic advisory system to provide insight in justifying an engineer’s day-to-day engineering decisions.
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This paper introduces a measurement system that is agile for transport and can be installed anywhere with a small footprint while delivering reasonably accurate results.
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This paper describes how a surveillance, analysis, and optimization plan was used to resolve subsurface uncertainties and optimize a reservoir development plan and provides lessons learned and best practices.
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The complete paper describes a combination of best practices and innovative techniques that help to provide rig-based and rigless opportunities by estimating potential and risk in a naturally fractured reservoir.
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The authors of this paper describe the development and implementation of a data-streaming solution that allows for real-time processing and interpretation of fiber-optics data.
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The authors of this paper present a system, developed to achieve data transmission using a time-division approach, that includes sealed chambers for microchip storage, a power-release device, and a circuit.
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This paper presents agile technologies that integrate data management, data-quality assessment, and predictive machine learning to maximize asset value using underused legacy core data.
