Estimating Drilling Parameters for Diamond Bit Drilling Operations Using Artificial Neural Networks

Abstract

Diamond bit drilling is one of the most widely used and preferable drilling techniques because of its higher rate of penetration and core recovery in the hardest rocks, the ability to drill in any direction with less deviation, and the ability to drill with greater precision in coring and prospecting drilling. Conventional bit analysis techniques include mathematical methods such as specific energy and formation drillability. In this study, artificial neural network (ANN) analysis as opposed to conventional mathematical techniques is used to estimate major drilling parameters for diamond bit drilling, i.e., weight on bit, rotational speed, and bit type. The use of the proposed methodology is demonstrated using an ANN trained with information obtained from