International Petroleum Technology Conference 2019
DOI: 10.2523/19311-ms
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Data Mining Approaches for Casing Failure Prediction and Prevention

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Cited by 17 publications
(5 citation statements)
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References 14 publications
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“…This late release is a relevant characteristic where the application requires materials staying inside the carrier for long periods, such as underwater structures. [ 182–185 ] Also, further studies should be performed, aiming to improve the self‐healing materials here presented.…”
Section: Resultsmentioning
confidence: 99%
“…This late release is a relevant characteristic where the application requires materials staying inside the carrier for long periods, such as underwater structures. [ 182–185 ] Also, further studies should be performed, aiming to improve the self‐healing materials here presented.…”
Section: Resultsmentioning
confidence: 99%
“…Mainly for applications focused on infrastructure, underwater materials, and construction in general. [ 55–58 ] Thus, this single procedure for the preparation of a self‐healing agent is very auspicious, mainly because it allows to obtain quickly, efficiently and affordably, self‐healing materials that can significantly improve the living conditions of the neediest populations, especially in countries developing countries, where the saving of resources must always be pursued.…”
Section: Resultsmentioning
confidence: 99%
“…The work of Noshi, et al (2018) and Noshi et al (2019) made an excellent attempt using machine learning and data analytics to identify possible factors that may have been responsible for casing failure. They employ artificial neural network (ANN) and python coding, descriptive and predictive analytic to process casing failure in Granite Wash Play of Western Anadarko basin.…”
Section: Machine Learningmentioning
confidence: 99%