In this paper we describe a simulation model for computing the formation damage imposed on the formation during overbalanced drilling. The main parts modelled are filter cake build-up under both static and dynamic conditions, fluid loss to the formation, transport of solids and polymers inside the formation including effects of pore lining retention and pore throat plugging, and salinity effects on fines stability and clay swelling. The developed model can handle multi-component water-based mud systems at both the core scale (linear model) and the field scale (2D radial model). Among the computed results are fluid-loss versus time, internal damage distribution and productivity calculations for both the entire well and individual sections.

The simulation model works in part independent on fluid loss experiments, e.g., we do not use fluid leakoff coefficients, but instead we compute the filter cake buildup and its flow resistance from properties ascribed to the individual components in the mud. Some of these properties can be measured directly, such as particle size distribution of solids, effect of polymers on fluid viscosity and formation permeability and porosity. Other properties, which must be determined by tuning the results of the numerical model against fluid loss experiments, are still assumed to be rather case independent, and once determined they can be used in simulations at altered conditions as well as with different mud formulations. A detailed description of the filter cake model is given in the paper.

We present simulations of several static and dynamic fluid loss experiments. The particle transport model is used to simulate a dilute particle injection experiment taken from the literature. Finally, we demonstrate the model's applicability at the field scale and present computational results from an actual well drilled in the North Sea. These results are analysed and it is concluded that the potential impact of the mechanistic modelling approach used is (a) increased understanding of damage mechanisms, (b) improved design of experiments used in the selection process and (c) better predictions at the well scale. This allows for a more efficient and more realistic pre-screening of drilling fluids than traditional core plug testing.

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