This research work predicts capillary pressure curves at primary drainage from the transverse T2 relaxation times of the NMR pore size distributions with ninety percent accuracy, which could do the trick in reservoir applications. The capillary pressure-water saturation curves are important instructions to reservoir simulators for predicting the dynamic properties of the reservoir as well the fluid saturations at different depths. This study originated from the challenges in forecasting the initial saturations from an NMR logged well. The procedure is a simple and non-damaging construction of capillary pressure curves from plug samples measurements. Dynamic rock typing was used to assign the capillary pressure data to different layers in the reservoir. Laboratory Nuclear Magnetic Resonance (NMR) equipment has been proven to produce information on pore size distribution and varieties of methods was found in the literature to predict capillary pressure curves from borehole NMR logs. The proposed idea of integrating drainage capillary pressure from centrifuge to T2 distributions from NMR enables rapid synthesis of capillary pressure from plugs and interpretation of logs. A scaling factor k, is adopted in the T2-Pc conversion. The optimum scaling factors for most research work is built upon the results. Water saturation at certain pressures, is often estimated from capillary pressure curves. It can therefore be argued that the perfect procedure of estimating the best scale factors is to recreate the saturations by the capillary pressure curves developed from NMR. In this research work, the range of pressures and T2 relaxation time was 0 – 500 psi and 1 – 10000 ms respectively. Due to different geological facies usually described by the capillary pressure curves of different formations, the capillary pressure curves of the completely cored reservoir were reconstructed to get the average scaling constant, k of 4 psi.s with a low standard deviation of 0.02. The capillary pressure versus T2 curve tend to fit a power regression with a coefficient of determination of R2= 1, signifying that the regression line analysis fits perfectly with the data for the 18 core samples. With the T2-Pc conversion established, the capillary pressure data can be predicted continuously in the whole section of the reservoir. The procedure is more accurate compared to others since it takes cognizance of the pore structure from NMR distribution, and it is applicable to T2 distributions estimated at various water saturations. Previous methods are applicable to 100% brine saturated plugs, which nullifies their predicted capillary pressure curves.

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In the present study a core analysis program including NMR measurements were performed to get a better petrophysical characterization of carbonate reservoir transition zone in the Abu Dhabi region. The results reveal three distinct rock types with average NMR-T2 cutoffs of 292 ms, 164 ms and 63 ms for the topmost, middle and lowermost samples of the reservoir respectively. Electrical resistivity and capillary pressure-water saturation were also measured at ambient and reservoir (2500 psi and 85 °C) conditions using a DCI Pc-RI system mimicking drainage and imbibition to investigate the hysteresis and variation in saturation exponent. It was found that the cementation exponent increases from 1.9 to 2.3 under overburden conditions and decreases in a stepwise manner during reduction of overburden, but not to the initial value due to hysteresis. This implies that the electrical parameters at ambient condition would lead to underestimation of water saturation. The saturation exponents estimated during drainage and spontaneous imbibition at reservoir conditions range from 1.6 – 7.5 for the different rock types tested in this study. New saturation functions were developed for each rock type from the measured electrical parameters at reservoir conditions by using the modified Archie’s and Skelt Harrison’s equation for the transition zone of this carbonate reservoir. The outcomes of the present study lead to a correction of the field resistivity log data that, overestimate the water saturation and hence predictions of saturation distributions, mobility and original oil in place.