Application of Reservoir Classification and Permeability Elaborate Evaluation with MRGC Method

The conventional reservoir permeability evaluation methods often ignore the difference in seepage characteristics for different flowing units within sand layer, resulting in large precision error during permeability evaluation. In this paper, on the basis of seepage mechanics principle, from the Kozeny-Carman equation of correction, we divide the reservoir into six types by using three reservoir physical parameters which can comprehensively reflect the different pore and throat characteristics of reservoir, and establish classification standard with the flow unit index FZI value. Derived by formula, the new idea of dividing flow unit with FZI value as slope was proposed. With image multi resolution clustering analysis method (MRGC), an extrapolate model was established with well log data and FZI of core values. Through analyzing the correlation of reservoir porosity and permeability for different reservoir types, fine permeability evaluation model for different flow units are established. The study results show that the calculation precision is improved obviously compared with the traditional regression method, with stronger practicability and popularized application from the aspects of theory and operational method.