Development and application of casing damage risk predict and control software for oil and gas wells
Aiming at the problems of complex casing damage mechanism,difficult to clarify the main control factors and unscientific formulation of prevention and control measures,a data-driven casing damage risk assessment and early warning prevention and control strategy research was carried out.Preprocess the basic oil well data and casing damage samples,and analyze the factor correlation and main control factors.Using machine learning algorithm to train samples,establish casing damage"binary classification"prediction model,prediction the probability of casing damage,and optimize oil and gas well completion and production parameters,and formulate prevention and control strategies for oil and gas well casing dam-age.The software of risk evaluation,early warning and prevention and control optimization of oil well casing damage based on B/S architecture is developed,and A2 database is linked to realize the real-time early warning and optimization of casing damage prevention and control in 2 400 well layers of an oilfield.The research and application show that the established prediction model and software can form the cognition of the causes and prevention strategies of casing damage in oil and gas wells,and can realize the optimization of casing damage prevention countermeasures in active wells,new wells and wells to be repaired.
oil and gas well casing damage"binary classification"predictionprevention and controlsoftware
NETL
NSTL
万方数据
维普
