Quantitative Analysis of Mud Losses in Naturally Fractured Reservoirs: The Effect of Rheology

Abstract

Abstract Significant fluid loss while drilling through fractured formations is a major problem for drilling operations. From field experience we know that the type and rheological parameters of the drilling fluid have a strong impact upon the rate and volume of losses. In this work, a mathematical model for flow of Yield-Power-Law (Herschel-Bulkley) fluids in fractures is presented. The governing equation is derived using the principles of conservation of mass and linear momentum for transient radial flow in a fracture. Results are obtained based on numerical solutions and plotted in terms of mud loss volumes versus time for a given drilling fluid under certain operational conditions. Results show how the rheological properties of drilling fluid such as yield stress and flow behavior index ( shear-thinning/thickening effect), influence mud losses in fractured formations. According to this model the yield stress of drilling fluids tremendously decreases the potential for mud losses. The effect of yield stress on reducing mud losses is the same as the effect of overbalance pressure on increasing losses. The shear thinning effect of drilling fluids can also greatly increase the rate of losses. Therefore, mud losses in fractures can be minimized by properly optimizing the rheology of the drilling fluid. Using this model, quantitative analysis of losses that take into account fluid rheology in order to characterize the fracture can be achieved. One can obtain the hydraulic aperture of conductive fractures by continuously monitoring mud losses and fitting field records of mud losses to the model. For general applications, type-curves are provided that describe drilling fluid loss of Yield-Power-Law fluids into fractures. Newtonian, Bingham Plastic and Power Law fluids are special cases. The proposed model is very useful not only for drilling applications but also for well completion design and fractured reservoir characterization. Field data measurements are used to demonstrate the practical application of the proposed technique. Good agreement between the model and field data confirms the validity and applicability of the model.