Prediction of thermal conductivity in reservoir rocks using fabric theory
An accurate prediction of the thermal conductivity of reservoir rocks in the subsurface is extremely important for a quantitative analysis of basin thermal history and hydrocarbon maturation. A model for calculating the thermal conductivity of reservoir rocks as a function of mineral composition, porosity, fluid type, and temperature has been developed based on fabric theory and experimental data. The study indicates that thermal conductivities of reservoir rocks are dependent on the volume fraction of components (minerals, porosity, and fluids), the temperature, and the fraction of series elements (FSE) which represents the way that the mineral components aggregate. The sensitivity test of the fabric model shows that quartz is the most sensitive mineral for the thermal conductivity of clastic rocks. The study results indicate that the FSE value is very critical. Different lithologies have different optimum FSE values because of different textures and sedimentary structures. The optimum FSE values are defined as those which result in the least error in the model computation of the thermal conductivity of the rocks. These values are 0.444 for water-saturated clay rocks, 0.498 for water-saturated sandstones, and 0.337 for water-saturated carbonates. Compared with the geometric mean model, the fabric model yields better results for the thermal conductivity, largely because the model parameters can be adjusted to satisfy different lithologies and to minimize the mean errors. The fabric model provides a good approach for estimating paleothermal conductivity in complex rock systems based on the mineral composition and pore fluid saturation of the rocks. © 1994.
Journal of Applied Geophysics
Prediction of thermal conductivity in reservoir rocks using fabric theory.
Journal of Applied Geophysics,
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