Digital Oil Field
This paper explores how artificial intelligence (AI), cognitive models, and integrated digital tools can transform readiness from periodic drills into a continuous, measurable capability.
This paper presents a competency-centered, data-driven approach implemented to strengthen control-room emergency-response capability through a cloud-hosted, scenario-based virtual plant simulator.
This paper presents an autonomous, data-driven solution designed specifically for intermittent well optimization.
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The digitalization of oil and gas facilities is becoming a new technical arena. Effective solutions can be used to convert data into information and knowledge, which can then be used to improve maintenance operations. -
With only about 3% of data from industrial assets used for decision making or meaningful purpose, vessel, rig, and fleet owners are looking at ways to connect existing networks and assets to achieve optimized operational performance.
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Supervisory control and data acquisition systems no longer simply monitor operations and produce large volumes of data in static displays, but now collect production data from all operation data sources and contextualize and present them to workers in real time as meaningful, actionable information.
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Sensor systems for pipeline inspections from Ingu and Rheidiant are among the initial selections to receive funding under Chevron’s CTV Catalyst Program.
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Rockwell Automation’s Luis Gamboa explains his company’s new solution designed to allow operators to collect, sort, and reconcile the quality and quantity of data from multiple sources to optimize field data.
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As E&P companies slowly ramp up drilling and production activities while adjusting to a new period of “lower for longer” prices, the time is right for widespread adoption of the IoT.
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Digitization in oil and gas is entering a new era thanks to the increased capabilities and lower cost of huge computing power
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With the availability of more-complex smart-well instrumentation, immediate evaluation of the well response is possible as changes in the reservoir or well occur.
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The complete paper evaluates optimization techniques to develop, or support, business cases for intelligent or smart wells.
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The most-competitive emerging systems blend artificial intelligence to bring better efficiency to the human work that results in good business decisions. As a result, we waste less time and fewer resources finding and manipulating data and focus more on complex engineering judgment.
