Prediction of Thermal Conductivity of Oil Sands Based on Particle Size Distribution

ABSTRACT

Heavy oil and bitumen are of a great interest for Canadian economics. Thermal recovery techniques are widely used across Alberta. To produce heavy oil its viscosity should be significantly decreased. One of the approaches is to heat the reservoir. Effective thermal conductivity of oil sands is an important parameter in reservoir simulation of thermal recovery processes such as steam assisted gravity drainage (SAGD). There are several mixing rules available in the literature, which allow for calculating effective thermal conductivity of porous material based on porosity and thermal conductivities of their components (matrix and fluid).

Most of them use a so-called structural approach, which assumes that porous media consist of certain structures for each of which effective thermal conductivity can be calculated analytically. The other class of models uses statistical techniques. In all predictive equations, the overall thermal conductivity of the oil sands is calculated by knowing the individual properties of the fluids and the rock. The fluid properties are measured relatively easy. However, the thermal conductivity of sand is more challenging. When measuring the thermal conductivity of an oil sand sample, the obtained value is not only based on the fluid and solid properties but also on the structure of the pore space. Thus composite oil sand experimental measurements need to be complemented by predictive modeling that addresses the effects of pore structure.

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