Candidate wells selection and ranking based on data mining and multi-criteria decision analysis techniques
Author:
Funder
Consejo Nacional de Ciencia y Tecnología
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences,General Environmental Science
Link
https://link.springer.com/content/pdf/10.1007/s12517-021-08146-4.pdf
Reference41 articles.
1. Arévalo JA, Gutiérrez T (2007) A well productivity program in Pemex E&P increases oil production in short time and low cost. SPE. https://doi.org/10.2118/108633-MS
2. Aryanto A, Kasmungin S, Fathaddin F (2018) Hydraulic fracturing candidate-well selection using artificial intelligence approach. J Mech Eng Mechatron 2(02):53–59. https://doi.org/10.33021/jmem.v2i02.322
3. Barba RE (2009) A novel approach to identifying refracturing candidates and executing refracture treatments in multiple zone reservoirs. SPE. https://doi.org/10.2118/125008-MS
4. Bawazir M, Dallag M, Shukla S (2019) Real-time production logs surveillance: automated workflow technology allows synthetic sensing of oilfield downhole production. SPE. https://doi.org/10.2118/196390-MS
5. Bhandari D, Murthy CA, Pal SK (1996) Genetic algorithm with elitist model and its convergence. Int J Pattern Recognit Artif Intell 10(06):731–747. https://doi.org/10.1142/S0218001496000438
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