LAUSR

Abstract Drilling fluid loss and mud filtration occur concurrently during overbalanced drilling. Characterization of fluid loss is mostly done via experimental studies with several types of setups and porous media. The first part of this study has been conducted on pore-scale homogenous and heterogenous media. Sequel to the study, this paper presents fracture-scale characterization of drilling fluid loss using experimental and statistical methods. The statistical methods that were used in this study include: experiment design, hypothesis testing, analysis of variance (ANOVA), and multiple linear regression analysis. Dynamic fluid loss experiments were conducted with a setup capable of simulating drillpipe rotation inside thick-walled cylindrical fracture slots that represents natural fractures. The results show that temperature, fracture size and orientation, and type/concentration of lost circulation material (LCM) are the critical factors that influences dynamic fluid loss in fractures. The results from testing the filter cake stability showed that the filter cake layer ruptured on three of the experiments out of the nine that were conducted. For the experimental conditions with the vertical fractures, the regression analysis showed that dynamic fluid loss can be predicted from changes in LCM concentration and fracture width with a considerably high R2 and adjusted R2 values. The R2 value is a parameter that is used to quantify the predictability of an empirical model. The effect of fracture positioning and orientation was also observed and recorded. The originality in this experimental method is the application of thick-walled cylindrical fracture slots (simulating natural fractures) to characterize dynamic drilling fluid loss. Temperature, drillpipe rotation, and pressure conditions were programed to simulate dynamic wellbore conditions under which fluid loss, filter cake evolution, and plastering occur. The methods used in this study can be employed in mud design for wellbore strengthening application and selection of operating conditions.