Low-field (1) H NMR was used in this work for the analysis of mixtures involving crude oils and water. CPMG experiments were performed to determine the transverse relaxation time (T2 ) distribution curves, which were computed by the inverse Laplace transform of the echo decay data. The instrument's ability of quantifying water and petroleum in biphasic mixtures following different methodologies was tested. For mixtures between deionized water and petroleum, one achieved excellent results, with root mean squared error of cross-validation (RMSECV) of 0.8% for a regression between the water content (wt %) and the relative area of the water peak in the T2 distribution curve, or a standard deviation of 0.9% for the relationship between the water content and the relative water peak area, corrected by the relative hydrogen index of the crude. In the case of biphasic mixtures of Mn(2+) -doped water and crude oils, the best result of RMSECV = 1.6% was achieved by using the raw magnetization decay data for a partial least squares regression.

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Rock-pore-space geometry and network topology have a great impact on dynamic reservoir characteristics, in particular on capillary pressure and relative permeability curves. Hydraulic tortuosity is a key independent measurement relating the pore-space geometry and topology to the rock's effective porosity and absolute permeability. Therefore, hydraulic tortuosity can be an important concept for dynamic reservoir characterization and reservoir simulation. Our objectives are to recommend a new dynamic rock-typing process and to assess the corresponding improvement on reservoir simulation processes. We introduce an innovative dynamic reservoir-rock-typing (DRRT) index, using absolute permeability, porosity and hydraulic tortuosity data, derived from mercury-injection capillary pressure (MICP) experiments. For correlation purposes, we also derived electric tortuosity data from formation-resistivity experiments. We used the experimental data from the Worldwide Rock Catalog (WWRC) provided by a joint-industry project (Core Lab, 2014), for both carbonate and clastic rocks. Based on the new proposed DRRT index and on corresponding dynamic reservoir properties, we prepared a comprehensive sensitivity study on the impact of hydraulic tortuosity heterogeneity on oil recovery results. This sensitivity study was done by incorporating the concept of hydraulic tortuosity in a synthetic carbonate- reservoir simulation model. The analysis of the MICP and formation-resistivity data showed both greater average tortuosity and greater tortuosity variability for carbonates, when compared with clastic rocks. It also showed good correlation between hydraulic and electric tortuosity values. The sensitivity study results showed a significant impact of hydraulic tortuosity heterogeneity on oil in place and reserves estimates for improved oil recovery (IOR) / enhanced oil recovery (EOR) processes in typical complex carbonate reservoirs, such as the ones found in the Brazilian Pre-Salt. It also showed the importance of applying proper corrections while deriving dynamic reservoir properties from capillary pressure and relative permeability experiments. The new DRRT index shows a much stronger correlation with pore-space geometry when compared with traditional reservoir-quality (RQI) and flow-zone (FZI) indexes. Therefore, it has clear potential to enhance the dynamic rock-typing process for reservoir simulation of IOR / EOR in complex carbonate rocks. We also discuss the importance of an integrated laboratory test and well log program to enable the proper characterization, population, and upscaling of dynamic rock properties. In complex carbonate reservoirs under IOR / EOR, overlooking the rock-pore-space geometry and network topology may result in significant errors in reservoir characterization and simulation processes. In this context, proper DRRT in carbonates, including tortuosity, is therefore crucial for reservoir simulation; enabling correspondence between core, well log and reservoir-scale dynamic properties. The presented correlation between hydraulic and electric tortuosity significantly increases the potential of dielectric measurements for dynamic reservoir characterization of complex carbonates on both core and well log scales.

Spin relaxation based nuclear magnetic resonance (NMR) methods have been used extensively to determine pore size distributions in a variety of materials. This approach is based on the assumption that each pore is in the fast diffusion limit but that diffusion between pores can be neglected. However, in complex materials these assumptions may be violated and the relaxation time distribution is not easily interpreted. We present a 2D NMR technique and an associated data analysis that allow us to work directly with the time dependent experimental data without Laplace inversion to identify the signature of diffusive coupling between different pores. Measurements on microporous glass beads and numerical simulations are used to illustrate the technique.

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