Estimating Capillary Pressure from NMR Measurements Using a Pore-Size-Dependent Fluid Substitution Method
- You Wang (The University of Texas at Austin) | David Medellin (The University of Texas at Austin) | Carlos Torres-Verdín (The University of Texas at Austin)
- Document ID
- Society of Petrophysicists and Well-Log Analysts
- SPWLA 60th Annual Logging Symposium, 15-19 June, The Woodlands, Texas, USA
- Publication Date
- Document Type
- Conference Paper
- 2019. held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors
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We introduce a workflow to calculate capillary pressure curves from NMR transverse relaxation time (T2) distributions of partially hydrocarbon-saturated measurements. First, we develop a pore-size-dependent fluid-substitution (PSDFS) joint inversion method to correct T2 distributions for hydrocarbon effects in partially hydrocarbon-saturated rocks. A PSDFS joint inversion on the T2 distributions of samples at different hydrocarbon saturations is used to estimate input parameters for fluid substitution and to reconstruct the fully water-saturated T2 distribution. Next, we convert the T2 distribution of the fully water saturated sample to a pore-size distribution using an estimated surface relaxivity. Finally, assuming a linear relationship between pore and throat size distributions, we estimate the capillary pressure curve using a triangular tube model.
We validate the PSDFS joint inversion on NMR measurements of Berea sandstone samples with different values of hydrocarbon saturation. The feasibility of our joint inversion method is confirmed by comparing the calculated fully water-saturated T2 distribution to the T2 distribution of the measured fully water-saturated rock sample. We derive the capillary pressure curves from fluid-substituted fully water-saturated T2 distributions and compare them to mercury injection capillary pressure (MICP) measurements. Capillary pressure curves derived with the PSDFS method agree well with MICP measurements.
Capillary pressure vs saturation (Pc-Sat) curves are commonly measured in the laboratory through MICP, porous plate, or centrifuge methods. These methods, however, are expensive and time-consuming because they must be performed under restrictive laboratory conditions.
NMR-based methods have been proposed as alternative procedures to estimate Pc-Sat curves. There are, in general, two approaches for calculating Pc-Sat curves from NMR T2 distributions: empirical approaches where the cumulative NMR porosity is calibrated to match the Pc-Sat curve, and physical approaches where physical models are used to convert the NMR T2 distribution into a Pc-Sat curve.
In empirical approaches, the resemblance of the shape of the Pc-Sat curve and the cumulative T2 distribution is used to calculate the Pc-Sat curve (Xiao and Zhang, 2008; Gao et al., 2011; Xiao, Mao, et al., 2016; Xiao, Zou, et al., 2016). Although these methods work well for rocks with uniform throat-size distributions, they lack physical support and can require substantial data to calibrate.
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