Permeability Prediction and Hydraulic Rock Typing of a Heterogeneous Dolomite Reservoir Based on Centrifuge and NMR Data

Abstract

Permeability prediction and hydraulic rock typing in carbonate reservoirs remain challenging because similar porosity values may correspond to markedly different flow capacities controlled by pore throat size, connectivity, and capillary accessibility. This study aims to develop an integrated workflow for permeability prediction and petrophysical–hydraulic rock typing of a heterogeneous dolomite reservoir using parameters that directly characterize the drainable pore throat network. Routine core analysis, centrifuge-derived capillary pressure curves, nuclear magnetic resonance T2 spectra, electrical measurements, petrographic and SEM observations, and fractal descriptors were jointly analyzed. Capillary pressure curves were fitted with the Li–Horne model and transformed into equivalent pore throat radius distributions; characteristic radii Rq, Swanson and Capillary-Parachor parameters, irreducible water saturation, and fractal characteristics were calculated for subsequent regression analysis and rock typing. The conventional k−ϕ relationship showed limited predictive capability, whereas models incorporating R15−R21 provided a more reliable permeability estimate. The best-performing relationship was close to k∝R2ϕ, supporting the interpretation of R20 as a centrifuge-derived analog of the effective hydraulic radius. Comparison with FZI, Winland R35, NMR groups, and electrofacies showed that R20-based typing produced a compact separation of samples by hydraulic quality. The proposed workflow is presented as a single-well proof of concept and requires validation in independent wells before application to field-scale geological and hydrodynamic models.