Production
This paper aims to establish a set of best practices for generating particle-size-distribution data from core samples.
Unlike traditional AI approaches that rely primarily on historical data, physics-based AI integrates physical laws, engineering expertise, and operational constraints directly into the learning process. Three recent SPE papers illustrate how this paradigm is transforming the industry through intelligent condition monitoring, virtual sensing, and autonomous production …
This research focuses on combining physics-based expert rules with machine learning to improve the detection of failure-related events in electrical submersible pumps.
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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. -
Onshore and offshore production in Texas and the Gulf of Mexico continues to recover to pre-Hurricane Harvey levels as inspections and assessments of damages are done. Operators have not reported major damages resulting in extended shut-ins.
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Oil and gas production in the Gulf of Mexico have each gone up 10% since yesterday as Harvey continues to weaken and move northeast toward the Ohio Valley. Widespread flooding is expected to continue in Texas and toward the Louisiana border through the weekend.
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The effects of Harvey are lingering for the operators in the Gulf of Mexico. Oil and gas shut-ins are fluctuating, but overall show slow improvement, according to the BSEE. As Harvey moves over the Ohio Valley in the next 72 hours, the cyclone aspect will diminish.
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The BSEE report shows that since yesterday, oil production has improved slightly, while gas production has decreased slightly in the Gulf of Mexico as a result of Hurricane/Tropical Storm Harvey’s ongoing effects.
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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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In unconventional plays, comparing the effect of different completion designs or well-management strategies on well performance remains a challenge because of the relatively brief production history and lack of long-term field analogs of these plays.
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With multistage operations becoming the industry norm, operators need easily deployable diversion technologies that will protect previously stimulated perforations and enable addition of new ones. This paper reviews several aspects of the use of in-stage diversion.
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This paper focuses on a fit-for-purpose methodology to evaluate well-production performance for a wide range of artificial-lift techniques.
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This paper presents an artificial-lift selection process to maximize the value of unconventional oil and gas assets.
