Data & Analytics
The emerging vision is an industry where engineers focus on judgment, risk assessments, and accountability.
This paper presents the large-scale deployment and operational integration of an advanced, automated rheometer in the Ghawar gas field, one of the world’s most prolific and technically complex hydrocarbon developments.
This study demonstrates the transformative potential of physics-informed neural networks as a hybrid framework for multiphase flow measurement.
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Many business and digital corporations claim that between 100 billion and 200 billion devices could be connected by 2020. -
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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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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The big data approach will allow new types of data-driven models to bypass traditional bottlenecks. It is also expected to lead to different views of standard models, thus providing new and valuable insights in the process.
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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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Permanent downhole gauges (PDGs) provide vast amounts of pressure-transient and rate data which may be interpreted with improved pressure-transient-analysis (PTA) approaches to gain more knowledge about reservoir dynamics.
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This paper proposes a framework based on proxies and rejection sampling (filtering) to perform multiple history-matching runs with a manageable number of reservoir simulations.
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This paper describes the development of “digital-rocks” technology, in which high-resolution 3D image data are used in conjunction with advanced modeling and simulation methods to measure petrophysical rock properties.
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Imagine a machine that could make an automaker competitive by speeding product development, help a jet engine maker create unique parts for more efficient turbines, and allow a baker to quickly create a picture-perfect 3D replica of a flower made of sugar.
