Digital oilfield
This paper presents a multifaceted approach leveraging precise rig control, physics models, and machine-learning techniques to deliver consistently high performance in a scalable manner for sliding.
This paper proposes a novel approach toward drilling maximum-reservoir-contact wells by integrating automated drilling and geosteering software to control the downhole bottomhole assembly, thereby minimizing the need for human intervention.
This paper offers an exploration into the field applications of multiphase flowmeters (MPFMs) across global contexts and the lessons learned from implementation in a smart oil field that uses several types of MPFM.
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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. -
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.
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An investigator from the US National Energy Technology Laboratory examines the role remotely operated vehicles played in flow rate estimation from the Macondo well.
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A real-time production-surveillance and -optimization system has been developed to integrate available surveillance data with the objective of driving routine production optimization.
