Electrical Submersible Pump Survival Analysis
ELECTRICAL SUBMERSIBLE PUMP SURVIVAL ANALYSIS
MICHELLE PFLUEGER Petroleum Engineer, Chevron Corp. & Masters Degree Candidate
Advisor Dr. Jianhua Huang With help from PHD Candidate Sophia Chen
Department of Statistics, Texas A&M, College Station
MARCH 2011
ABSTRACT
A common metric in Petroleum Engineering is “Mean Time Between Failures” or “Average Run Life”. It is used to characterize wells and artificial lift types, as a metric to compare production conditions, as well as a measure of the performance of a given surveillance & monitoring program. Although survival curve analysis has been in existence for many years, the more rigorous analyses are relatively new in the area of Petroleum Engineering. This paper describes the basic theory behind survival analysis and the application of those techniques to the particular problem of Electrical Submersible Pump (ESP) Run Life. In addition to the general application of these techniques to an ESP data set, this paper also attempts to answer: Is there a significant difference between the survival curves of an ESP system with and without emulsion present in the well? Of the variables collected, which variables best describe the survival function? Do the variables collected in the dataset capture the variation in the survival function?
TABLE OF CONTENTS
Survival Analysis in Petroleum Engineering ................................................................................4 Theory of Survival Analysis .........................................................................................................4 Kaplan Meier (Non-Parametric) ...............................................................................................4 Cox Proportional Hazard (Semi-Parametric) ............................................................................6 Weibull (Parametric) ................................................................................................................7 Stepwise Cox & Weibull
MICHELLE PFLUEGER Petroleum Engineer, Chevron Corp. & Masters Degree Candidate
Advisor Dr. Jianhua Huang With help from PHD Candidate Sophia Chen
Department of Statistics, Texas A&M, College Station
MARCH 2011
ABSTRACT
A common metric in Petroleum Engineering is “Mean Time Between Failures” or “Average Run Life”. It is used to characterize wells and artificial lift types, as a metric to compare production conditions, as well as a measure of the performance of a given surveillance & monitoring program. Although survival curve analysis has been in existence for many years, the more rigorous analyses are relatively new in the area of Petroleum Engineering. This paper describes the basic theory behind survival analysis and the application of those techniques to the particular problem of Electrical Submersible Pump (ESP) Run Life. In addition to the general application of these techniques to an ESP data set, this paper also attempts to answer: Is there a significant difference between the survival curves of an ESP system with and without emulsion present in the well? Of the variables collected, which variables best describe the survival function? Do the variables collected in the dataset capture the variation in the survival function?
TABLE OF CONTENTS
Survival Analysis in Petroleum Engineering ................................................................................4 Theory of Survival Analysis .........................................................................................................4 Kaplan Meier (Non-Parametric) ...............................................................................................4 Cox Proportional Hazard (Semi-Parametric) ............................................................................6 Weibull (Parametric) ................................................................................................................7 Stepwise Cox & Weibull