Using a Bayesian Network to Develop Drilling Expert Systems

Abstract

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, completions, 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 reviews and expert 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 expert drilling systems. The plan of this study is to have a drilling advisory system to not only detect and predict unplanned events, but also to optimize drilling operations.

AAPG Datapages/Search and Discovery Article #90327 © 2018 AAPG Middle East Region GTW, Digital Subsurface Transformation, Dubai, UAE, May 7-8, 2018