New concepts in dynamic fluid-loss modeling of fracturing fluids

The fluid-loss problem has been successfully reformulated to make it amenable to modeling by dimensionless groups of variables. Starting with a basic formulation relating laboratory fluid-loss volume to other process variables such as core area and permeability, applied differential pressure, fluid apparent viscosity, shear rate, and shear time, we obtained a functional equation relating a dimensionless fluid-loss term ν1/A√k to other rock- and fluid-based dimensionless groups of variables. The effects of polymer loading, fluid-loss additive (FLA) concentration and temperature were investigated through a system of shift factors which were defined to show quantitatively the combined effects of these variables on apparent viscosity. ive laboratory experimentation was required to determine the parameters of the resulting functional equation. The fann model 90 was used to conduct the dynamic fluid-loss experiments, and the fann model 50c was used to measure the apparent viscosities at temperatures and pressures utilized in the dynamic fluid-loss component. The filter media were natural Ohio sandstone cores having permeabilities of 0.01–0.3 mD, and ceramic cores of 750-mD permeability (this is the least permeable medium available from the manufacturer). per demonstrates that certain previously reported three-parameter dynamic fluid-loss equations may only be applicable to low-permeability filter media. Rather than using the parameters of these equations to characterize the fluid-loss control effectiveness, as was previously proposed, a new parameter based on the ratio of the slope of the equilibrium-state line to the cake-build-up rate is defined and shown to be a more consistent discriminant. thod outlined in the paper constitutes a significant departure from previous methods which have, in general, attempted to curve-fit experimental data of fluid-loss volume vs. time. It is shown that this method is limited only by the scope of reported data when one is analyzing previously conducted experimentation.