A new method for predicting casing wear in highly deviated wells using mud logging data

Abstract

Casing wear is an essential and complex phenomenon in oil and gas wells. Research has been conducted to predict this phenomenon. This study was conducted at a well in southwestern part of Iran. In this paper, the forces exerted on the drill string are primarily studied. Next, the contact force between the drill string and the casing is calculated. Finally, the wear volume and the depth of the wear groove are determined. These calculations were performed using MATLAB and Python software. In addition, to achieve high accuracy of coding, mud log data was used to make the results more precise. It has also been shown that increasing RPM increases the depth of wear and attempts to drill a highly deviated wells as a sliding mode. Finally, the obtained results were compared and matched with the wireline logs recorded from the well.