Modeling the Influence of Mud Rheology on Drill Bit Behavior in Algerian Borehole: A Numerical Study Using CFD Approach

The drill bit is a crucial device in oil companies, and it is quite expensive. Therefore, studying its mechanical behavior is essential for preserving this device and reducing its maintenance costs. The drilling mud is among the practical things that influence the bit's performance during the drilling operation. This article presents a numerical study of mud rheology in Algerian oil and gas wells using computational fluid dynamics (CFD) analysis. This study aims to optimize the rheological and dynamic properties around the polycrystalline diamond compact (PDC) drill bit of 244 mm diameter in the Algerian borehole. The drilling mud used is a mixture of water, 0.15% of hydroxyethyl cellulose (HEC), and an Algerian bentonite base. The Herschel–Bulkley model has been used to characterize the rheological behavior of this drilling mud because it is a non-Newtonian fluid. The three-dimensional (3D) model of the PDC drill bit was meticulously designed using SolidWorks (version 24, 2016). Additionally, the dynamic behavior of the PDC drill bit in the presence of drilling mud was modeled and simulated using ANSYS Fluent software (version 19.0, 2018). The results indicate that although mud density has minimal impact on annular velocity, it significantly affects the pressure drop across the drill bit. In contrast, the drill bit's rotational speed directly influences annular velocity, which plays a critical role in mitigating stick–slip phenomena. This mitigation is achieved through the enhancement of cuttings transport from the bottom hole to the surface, thereby preventing accumulation around the drill bit, a primary contributor to stick–slip vibrations. These findings support previous studies that have established the influence of mud density on pressure drop and the critical role of rotational speed in mitigating stick–slip phenomena. The numerical results for fluid parameters at the nozzle, obtained using ANSYS Fluent, were validated against established oilfield empirical correlations, demonstrating satisfactory agreement.