A Holistic Approach to Characterize Mud Loss Using Dynamic Mud Filtration Data

Abstract

Drilling mud loss in highly porous media and fractured formations has been one of the industry's focuses in the past decades. Wellbore dynamics and lithology complexities continue to push for more research into accurate quantification and mitigation strategies for lost circulation and mud filtration. Conventional methods of characterizing mud loss with filtration data for field application can be time-consuming, particularly because of the interaction between several factors that impact mud loss and filtration. This paper presents a holistic engineering approach for characterizing lost circulation using pore-scale dynamic water-based mud (WBM) filtration data. The approaches used in this study include: factorial design of experiment (DoE), hypothesis testing, analysis of variance (ANOVA), and multiple regression analysis. The results show that an increase in temperature and rotary speed can increase dynamic mud filtration significantly. An increase in lost circulation material (LCM) concentration showed a significant decrease dynamic mud filtration. A combination of LCM concentration and rotary speed showed a significant decrease in dynamic mud filtration, while a combination of LCM concentration and temperature revealed a significant increase in dynamic mud filtration. Rotary speed and temperature combination showed an increase in dynamic mud filtration. The combined effect of these three factors was not significant in increasing or decreasing dynamic mud filtration. For the experimental conditions in this study, the regression analysis for one of the rocks showed that dynamic mud filtration can be predicted from changes in LCM concentration and rotary speed. The results and approach from this study can provide reliable information for drilling fluids design and selecting operating conditions for field application.