Development of a Neural Fuzzy System for Advanced Prediction of Bottomhole Circulating Pressure in Underbalanced Drilling Operations

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Abstract
Precise prediction of bottomhole circulating pressure (BHCP) is the major concern in the designing stage of an underbalanced drilling (UBD) operation. A successful UBD operation hinges tightly on the accurate control of downhole pressures. In order to predict the pressure gradient, complex two-phase flow correlations are employed and the flow pattern is defined. The problems arising from such methods are the significant errors relative to the nature of a UBD and the need for localization of the parameters or the shift from one correlation to another from case to case. In this study, different types of fuzzy inference systems are developed to construct new models. The resulting average percentage relative error (APE) of 13.83% for a Sugeno model and 13.11% for a Mamdani model indicated that the generated fuzzy models have the capability of precise BHCP prediction with higher accuracies in comparison with the popular mechanistic models.

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