Application of soft computing approaches for modeling fluid transport ratio of slim-hole wells in one of Iranian central oil fields

In order to have a better control over the drilling process and reduce the overall cost of this drilling operation, engineers have tried to use soft computing (SC) techniques to conduct the preestimation of drilling events. It is critically important to estimate the annular pressure losses (APL) for non-Newtonian drilling muds within annulus in order to specify pump rates and also to be able to choose the most appropriate mud pump systems while conducting the drilling operations. To develop the vigorous and exact models to enable the prediction of APL, two popular models were employed, i.e., multilayer perceptron (MLP) [optimized by levenbergmarquardt (LM), bayesian regularization (BR), scaled conjugate gradient (SCG), Resilient back propagation (RB), and broyden fletcher goldfarb shanno (BFGS)] and radial basis function (RBF). Subsequently, applying a committee machine intelligent system (CMIS), the four top models were combined into a unit paradigm. Several tools such as error distribution diagram, cross plot, trend analysis, and cumulative frequency diagram were used in conjunction with statistical calculation to assess the efficiency of models. Consequently, the CMIS model was introduced as the most exact technique which has the greatest coefficient of determination (R 2 close to one) as well as the lowest root mean square error (RMSE close to zero) for the tested dataset.

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Application of soft computing approaches for modeling annular pressure loss of slim-hole wells in one of Iranian central oil fields

Jafarifar

Simi

Abbasi

et al. 2023

Soft Comput

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Optimization of glycol–water-based drilling fluid for drilling slim-hole wells in one of Iranian central oil fields

Jafarifar

Norouzi-Apourvari²,

Schaffie³

et al. 2023

Arab J Geosci

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Application of soft computing approaches for modeling fluid transport ratio of slim-hole wells in one of Iranian central oil fields

Cited by 2 publications

References 58 publications

Application of soft computing approaches for modeling annular pressure loss of slim-hole wells in one of Iranian central oil fields

Application of soft computing approaches for modeling annular pressure loss of slim-hole wells in one of Iranian central oil fields

Optimization of glycol–water-based drilling fluid for drilling slim-hole wells in one of Iranian central oil fields

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