Prediction of cementation factor using different methods of reservoir rock classification in heterogeneous carbonate reservoirs.

Cementation exponent or factor is one of most crucial factors in the Archie's equations that should be estimated precisely in order to accurately determine relevant petrophysical characteristics of the reservoir. Inaccurate estimation of this factor leads to incorrect petrophysical analysis and inaccurate determination of water saturation which is highly important for the economic forecasting of hydrocarbon reservoirs. An alternative to the cementation factor precise estimation is to classify rocks based on a common petrophysical property such as permeability. This research aims to investigate the cementation factor in different rock types and eventually to provide a suitable model for estimating this parameter based on different approaches of rock classification. In this paper, first, conventional methods of rock classification (e.g., current zone indicator (CZI), flow zone indicator (FZI), permeability and electrical efficiency) have been used for cementation factor estimation. Then, the data, taken from Regnet et al. (J Geophys Res Solid Earth 120:790–811, 2015), have been analyzed by these methods in order to find the best way of rock classification. The analyzed data show that only electrical efficiency method is accurate enough to classify rocks into different groups as high values of determination coefficient (i.e., 0.9828 and 0.9725) are obtained as a result of classification by this method in which the data are classified into distinct groups. The obtained values of determination coefficient as a result of classification by permeability, FZI and CZI methods are 0.805, 0.809 and 0.7568 respectively. Due to this result and high scattering of the classified data, it can be concluded that these three methods have not been precise enough for rock classification of the data. In addition to the above-mentioned existing methods, a new rock classification method based on tortuosity coefficient or factor has also been proposed in this paper. This new method has been proven to be accurate due to low scattering of the data results and falling them into distinct groups in addition to obtaining high values of determination coefficient (i.e., 0.9996, 0.9986 and 0.9951) in the classification by this new method. [ABSTRACT FROM AUTHOR]