In carbonate reservoirs, permeability prediction is often difficult due to the influence of various geological variables that control fluid flow. Many attempts have been made to estimate permeability from porosity by using theoretical and empirical equations. The suggested permeability models have been questionable in carbonates due to inherent heterogeneity and complex pore systems. The main objective of this paper is to provide a workflow to improve the use of existing models (e.g., Kozeny, Lucia, and Winland) to predict permeability in carbonate reservoirs.
More than 1,000 core plugs were studied from seven different carbonate reservoirs across the Middle East: mainly Cretaceous reservoirs. The plugs were carefully selected to represent a wide range of properties within the cored intervals. The data set available included laboratory-measured helium porosity, gas permeability, thin-section photomicrographs, and high-pressure mercury injection. Rock textures were analyzed in the thin-section photomicrographs and were classified based on their content as grainy, muddy, and mixed. Special attention was given to the diagenesis effects, mainly compaction, cementation, and dissolution.
The texture information was plotted in the porosity-permeability domain and was found to produce three distinct porosity-permeability relationships. Each texture gave a unique porosity-permeability trend, where the extent of the trend was controlled by diagenesis. Rock types were defined on each trend by detailed texture analysis and capillary pressure. Three different permeability equations (Kozeny, Winland, and Lucia) were evaluated to study their effectiveness in complex carbonate reservoirs. Both Kozeny and Lucia models honored the geology of the samples and showed similar trends to the porosity-permeability relationships, whereas the Winland model gave different slopes to the experimental data. The prediction of the permeability was improved by using different model parameters per RRT within each texture.
This work presents a systematic approach to construct correlations between porosity and permeability in complex carbonate reservoirs. Model parameters (i.e., FZI, RFN, and r35) were suggested within different geological rock types to estimate permeability. Based on the workflow presented in the paper, the predicted permeability was improved to less than a factor of 2 compared to the measured values. Moreover, the same workflow was applied using the data from seven different reservoirs, and the same rock typing scheme was applicable to all the reservoirs. Such work is not abundant in the literature and would serve to improve permeability prediction in heterogeneous carbonate reservoirs, which is one of the main uncertainties in modeling carbonates.