Spe-192002-ms case Study Applied Machine Learning to Optimise pcp completion Design in a cbm field
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spe-192002-ms
Document Outline
Case Study Applied Machine Learning to Optimise PCP Completion
Design in a CBM Field
Introduction
PCP Pump Failures
Data Requirements / SCADA /
Completion Data
Stationary representations of a CBM Well
Material
Balance Modeling
Stationary Representation
GPR for PCP Runlife
Covariance
and Hyper-parameters
Likelihood and Bayesian Inference
Discussion
Censored data
and multiple failure modes
Data Exploration and Feature Importance
Grid
Search Optimisation
Conclusions
References
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