Reservoir evaluation is one of the critical tasks of any reservoir exploration and field development plan. Water saturation calculated from open-hole resistivity measurements is a primary input to hydrocarbon reserves evaluation. Archie's equation is the water saturation model for the determination of water saturation. Application of Archie equation in carbonate reservoir is not easy due to high dependency of its parameters on carbonate characteristics. Determination techniques of Archie's parameters are relatively well known and validated for sandstone reservoirs, while carbonates are heterogeneous and a correct estimation of Archie' parameter is important in their evaluation. In the case of carbonate rocks, there are considerable variations in texture and pore type, so, Archie's parameters become more sensitive to pores pattern distribution, lithofacies properties and wettability. Uncertainty in Archie's parameters will lead to non-acceptable errors in the water saturation values. Uncertainty analysis has shown that in calculating water saturation and initial oil in place, the Archie's parameters (a, m, n) have the largest influence and R t and R w are the least important. The main objective of this study was to measure Archie's parameters on 29 natural carbonate core plugs at reservoir conditions, using live oil, these core samples were taken from three wells. For this purpose, three techniques were implemented to determine Archie's parameters; conventional technique, core Archie's parameters estimate technique and three-dimensional technique. Water saturation profiles were generated using the different Archie parameters determined by the three techniques. These profiles have shown a significant difference in water saturation values and such difference could be mainly attributed to the uncertainty level for the calculated Archie parameters. These results highlight the importance of having accurate core analysis's measurements performed on core samples that yield representative a, m and n values that highly influence the water saturation values.
Carbonate reservoir rocks are considered heterogeneous and the distribution of reservoir quality in carbonates depends primarily upon how diagenetic processes are modifying the rock microstructure, leading to significant petrophysical heterogeneity and anisotropy. Water saturation determination in carbonate reservoirs is crucial parameter to determine initial reserve of given an oil field. Water saturation determination using electrical measurements is based on Archie’s formula. Consequently, accuracy of Archie’s formula parameters affects seriously water saturation values. Determination of Archie’s parameters (a, m and n) is proceeded by three techniques conventional, CAPE and 3-D. This work introduces the hybrid system of parallel self-organizing neural network (PSONN) targeting an accepted value of Archie’s parameters and consequently reliable water saturation values. This work focuses on calculation of water saturation using Archie’s formula. Different determination techniques of Archie’s parameters such as conventional technique, CAPE technique and 3-D technique have been tested and then water saturation was calculated using Archie’s formula with the calculated parameters (a, m and n). This study introduced parallel self-organizing neural network (PSONN) algorithm predict Archie’s parameters and determination of water saturation. Results have shown that predicted Arche’s parameters (a, m and n) are highly accepted with statistical analysis lower statistical error and higher correlation coefficient than conventional determination techniques. The developed PSONN algorithm used big number of measurement points from core plugs of carbonate reservoir rocks. PSONN algorithm provided reliable water saturation values. We believe that PSONN can be supplement or even replacement of the conventional techniques to determine Archie’s parameters and then water saturation of carbonate reservoirs.
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