Control of wellbore pressure during drilling operations has always been important in the oil industry as this can prevent the possibility of well blowout. The present research employs a combination of automatic process control and statistical process control for the first time for the identification, monitoring, and control of both random and special causes in drilling operations. To this end, by using automatic process control, control charts are applied to the output of the controlled process; subsequently, the points which are outside the predefined control limits are identified. This method is capable of using controllable input variables not used in automatic process control, such as changes in the mud weight, to fully control the process. Due to the dynamic nature of the process, adaptive model-based controllers have replaced feedback methods in automatic process control. Control charts have also been used to compare the performance of different automatic process control approaches. Based on this new criterion, the fuzzy adaptive approach is shown to have good performance in automatic process control. The results indicate that this approach can improve the limits of the automatic process control method by using statistical process control for controlling the bit pressure in an acceptable range.