Using Bayesian Network to Develop Drilling Expert Systems

Abstract

Abstract Long years of experience in the field and sometimes in the lab are required to develop consultants, Saudi ARAMCO is currently looking into the establishment of a new method to develop a drilling expert system that can be used as a training tool for young engineers or as a consultation system in various drilling engineering concepts such as well control, underbalanced drilling, drilling fluids, completion, and cementing practices. This method is done by proposing a set of guidelines for the optimal drilling operations in different focus areas, by integrating current best practices through a decision-making system based on Artificial Bayesian Intelligence. Optimum practices collected from literature review and experts’ opinions, are integrated into a Bayesian Network BN to simulate likely scenarios of its use that will honor efficient practices when dictated by varying certain parameters. The advantage of the artificial Bayesian intelligence method is that it can be updated easily when dealing with different opinions. To the best of our knowledge, this study is the first to show a flexible systematic method to design drilling expert systems. The future plan of this study is to integrate the resultant software with real time operation center within Saudi Aramco. Currently, a validation team of drilling consultants are reviewing and editing the systems.