Guidelines for Optimum Underbalanced Drilling Practices Using Artificial Bayesian Intelligence

摘要

Many underbalanced drilling operations have been analyzed, resulting in the optimum practices, as outlined in this paper. To the best of the authors' knowledge, there are no systematic guidelines for underbalanced drilling.rnThe objective of this paper is to propose a set of guidelines for the optimal underbalanced drilling operations, by integrating current best practices through a decision-making system based on Artificial Bayesian Intelligence. Optimum underbalanced drilling practices collected from data, models, 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 such as formation pressure and operation. The proposed decision-making model follows a causal and an uncertainty-based approach capable of simulating realistic conditions on the use of underbalanced drilling operations. For instance, by varying the type of UBD (flow, aerated, etc), operation and formation properties the system will show optimum tripping and connection procedure.rnThe developed model also acknowledged UBD drilling techniques in different scenarios such as fractured formations, low permeability and high permeability formations. The model also shows optimum solutions to problems related to underbalance drilling such as well control, completion, equipment associated with drilling.rnExperts' opinions were considered in building up the model in this paper. The advantage of the artificial Bayesian intelligence method is that it can be updated easily when dealing with different opinions. The outcome of this paper is user-friendly software, where you can easily find the specific subject of interest, and by the click of a button, get the related information you are seeking.