Estimating free-fluid porosity from microtomography images erosion: A case study of coquinas from the Morro do Chaves Formation

Resumo

Free fluid porosity (FFI) is a key petrophysical parameter for reservoir characterization, representing the fraction of the porous volume that contains potentially producible fluids. It is commonly estimated from transverse relaxation time (T₂) distributions derived from Nuclear Magnetic Resonance (NMR), using a cutoff value to distinguish free (mobile) fluids from irreducible ones. The latter are retained within micropores due to capillary forces or adsorption onto mineral surfaces. Precise quantification of free fluid porosity is critical for estimating recoverable hydrocarbon volumes, particularly in hybrid carbonate reservoirs with mixed siliciclastic and carbonate facies, where standard NMR interpretations may be limited. This study investigates a novel approach based on digital erosion of segmented X-ray micro-computed tomography (µCT) images to estimate free fluid porosity in hybrid carbonate rocks, using coquinas from the Morro do Chaves Formation as a case study. In addition, the image-derived FFI was integrated with NMR measurements to assess its potential as an input for permeability estimation using the Timur-Coates model. The dataset includes six segmented pore space images from coquina samples that were previously centrifuged to determine irreducible water saturation (Swirr) and establish T₂ cutoff values. The digital erosion technique was applied using Avizo software, applying successive layers of fixed thickness to the segmented pore space. The goal was to determine an optimal erosion width that approximates the average mobile fluid layer, maximizing the correlation between µCT-derived porosity and NMR-based FFP. This estimated porosity was subsequently used as input to the Timur-Coates permeability model, and the resulting predictions were compared to absolute permeability values measured by gas flow on corresponding core plugs. The results confirmed the existence of an optimal erosion width that maximizes the correlation between µCT-derived and NMR-derived FFI. Furthermore, the Density Equation (DE) approach was applied to differentiate between macropores (associated with mobile fluids) and micropores (associated with bound fluids), providing an additional comparative framework alongside the digital erosion technique. This integrated method provides a robust, non-destructive workflow to estimate FFI, improving petrophysical characterization and modeling of complex porous media, especially in hybrid carbonate reservoirs.