data mining
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A recently launched joint industry project (JIP) is working to improve petrophysical analysis methods to reduce the time and expense of characterizing tight sandstone gas reservoirs for exploration, appraisal, and production.
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Young Technology Showcase—Top-Down Modeling: A Shift in Building Full-Field Models for Mature FieldsData-driven, or top-down, modeling uses machine learning and data mining to develop reservoir models based on measurements, rather than solutions of governing equations.
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Failure to prioritize objectives and improper selection of candidate wells can have significant implications for both derived value and potential risk.
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Data mining for production optimization in unconventional reservoirs brings together data from multiple sources with varying levels of aggregation, detail, and quality.
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A data-driven approach to successfully analyze and evaluate production-fluid impact during facility system divert events is presented. The work flow effectively identifies opportunities for prompt event mitigation and system optimization.
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The challenges facing the oil and gas industry require crossover technologies from other industries such as aerospace, automotive, and medicine to help drive efficiency, boost productivity, and optimize performance.
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