A Novel Methodology for Monitoring and Control of Non-Stationary Processes Using Model-based Control Charts (Case Study: bottomhole Pressure during Drilling Operations)

This study applies two methods for the monitoring and control of autocorrelated processes based on time series modeling. the first method involves the simultaneous monitoring of common and assignable causes. this method includes the application of five steps of data gathering, normality test, autocorrelation test, model selection, and control chart selection on all non-stationary process observations. the second method is a novel method for the separate monitoring and control of common and assignable causes. in this method, the process was divided into parts with and without assignable causes. the first method was greatly non-stationary for not separating common and assignable causes. the application of this method also implied that common causes were hidden in the process. the novel method used for the separate monitoring of common and assignable causes could turn the process into a stationary one, leading to identifying, monitoring, and controlling common causes without any interference from the assignable causes. the results showed that, unlike the first method, the second method could be very sensitive to the common causes; it could, therefore, suitably monitor, identify, and control both assignable and common causes. the current work aimed to use control charts to monitor and control the bottomhole pressure during the drilling operation