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• W2317507975 abstract "This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 170702, “Optimizing the Selection of Lateral-Re-Entry Wells Through Data-Driven Analytics,” by Andrei S. Popa, SPE, Chevron, prepared for the 2014 SPE Annual Technical Conference and Exhibition, Amsterdam, 27–29 October. The paper has not been peer reviewed. A new intelligent model that successfully learns from high-dimensional data and effectively identifies high-production areas and optimum lateral-re-entry candidates is presented. The model is entirely data driven and uses Wang-Mendel (WM) rules extraction, fuzzy logic (FL), pattern recognition, and Voronoi mapping. The authors applied their model to a large field with thousands of wells and multiple production layers, finding that it outperformed previous methodologies significantly. Introduction This paper demonstrates the application of data-driven-modeling technology to a relatively new domain, petroleum engineering—in particular, to production-opportunity identification and well-work optimization. The Kern River field is the single largest producing onshore heavy-oil asset in North America. The structure is homoclinal, dipping southwest into the basin, with nine distinctive productive formations. The field has been produced with vertical wells through a combination of primary recovery and thermal enhanced recovery. The horizontal-well program was initiated in the Kern River field in 2007; because of its success, the program witnessed a significant growth year after year. An intelligent approach using fuzzy logic was introduced in 2012, which allowed identification of new horizontal-well opportunities previously missed by conventional methodology. More than 500 horizontal wells have been drilled in the field. This large number of wells provided an ideal data set for extracting reservoir knowledge for future optimization. Observation and Project Opportunity The average Kern River production per vertical well is currently under 7 BOPD. Analytics run on production data showed that more than 3,900 wells produce less than 3 BOPD, while approximately 2,200 produce below 1 BOPD. This observation creates a significant opportunity for production improvement. The large amount of poorly performing vertical wells contrasted with the success of the horizontal wells and led to the idea of reusing the existing wellbores by drilling lateral sections into zones with remaining opportunity. If successful, these new lateral drills would not only improve production output but also would help drain remaining reserves more efficiently. These sidetracks were named “re-entry laterals.” Re-entry-lateral sidetracks are directionally drilled high-angle sections (15°/100-ft dogleg severity) aiming at maximizing reservoir-contact area. The wells are completed with slotted liners and penetrate several target sands offering higher well exposure to each formation intersected. In contrast to the horizontal wells, which can reach horizontal sections of 2,000 ft or greater, the reentry laterals would extend no more than 400–500 ft at very high angle (85°) into formations. As with horizontal-well placement, lateral-re-entry wells are intended to target the remaining hot oil existing at the base of high-quality sand formations. Thus, the horizontal sections of the wells could penetrate multiple formations for a significantly longer section compared with vertical entries, thus maximizing the formation exposure to the well. For a discussion of the technological background of this project, including discussions of the WM method, FL systems, and Voronoi diagrams, please see the complete paper." @default.
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• W2317507975 date "2015-05-01" @default.
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• W2317507975 title "Optimizing Selection of Lateral-Re-Entry Wells Through Data-Driven Analytics" @default.
• W2317507975 doi "https://doi.org/10.2118/0515-0108-jpt" @default.
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