Study on the expansion characteristics of oil-based drilling fluid in HTHP wellbore

Accurate prediction of oil-based drilling fluid (OBD) behavior under high-temperature, high-pressure (HTHP) conditions in ultra-deep wells is essential for ensuring well control safety. However, research on the volumetric expansion of OBD in HTHP wellbores remains limited. This study develops a mathematical model to predict the expansion characteristics of OBD in HTHP wellbores, incorporating temperature- and pressure-dependent variations in rheological properties, thermophysical parameters, and density. The model is solved using discretization and the successive over-relaxation (SOR) method. Laboratory experiments were conducted to measure the rheology and density of OBD at different initial densities under varying temperature and pressure conditions. Binary mathematical models describing density and rheology as functions of temperature and pressure were established. The results indicate that the rheological properties of OBD exhibit consistent trends across different initial densities. Apparent viscosity (AV) and plastic viscosity (PV) decrease with increasing temperature and gradually stabilize, while both increase with rising pressure. The density of OBD decreases due to thermal expansion at elevated temperatures and increases due to thermal contraction at lower temperatures. Temperature exerts a greater effect on OBD density than pressure. Model validation using field data from an ultra-deep well confirms the accuracy of the proposed approach. During drilling and tripping operations, changes in mud pit volume occur due to temperature fluctuations; however, these changes are relatively slow compared to the rapid volume changes associated with wellbore influx. It is recommended to suspend the use of drilling fluid cooling devices before pulling out of hole (POOH) operations to minimize mud pit volume fluctuations. These findings provide theoretical guidance for accurate bottom-hole temperature prediction and improved drilling strategy optimization.