USING ARTIFICIAL NEURAL NETWORKS TO PREDICT THE RHEOLOGICAL BEHAVIOR OF DRILLING FLUIDS

Abstract

Drilling fluids are essential factor in the success of the drilling operations as they perform many functions from controlling the well, lubricating and cooling the drill bit. Lately, the petroleum field has shown a grown interest in enhancing the properties of the drilling fluids using nanoparticles.

In this research, two nanoparticles (MgO and ZnO) have been used to enhance the behavior of three types of drilling fluids. The obtained experimental results in addition to data from literature have been used to build artificial neural network (ANN) models that can predict the rheological properties of the drilling fluids.

The two nanoparticles have shown improvements and promising effects on the behavior of the drilling fluids. Also, ANN models were able to predict the rheological properties of the drilling fluids based on their composition with high accuracy which paves the way to the mechanization of the drilling operations.