Muthanna Journal of Engineering and Technology
Volume (14), Issue (3), Year (2026), Pages (38-56)
DOI:10.52113/3/eng/mjet/2026-14-03-/38-56
Research Article By:
Mohammed elan Mohammed
Corresponding author E-mail: moh96elan@gmail.com
ABSTRACT
Carbonate reservoirs are home to over 60% of the world’s conventional hydrocarbons; however, the complexity of carbonate reservoirs at the pore level creates a very weak correlation between porosity and permeability (ɸ-k). Current models do not account for variations in pore types that affect production rates and thus lead to inaccurate placement of oil wells and inaccurate production forecasts. This research presents a new quantitative method to evaluate variations in ɸ-k in relation to production through the integration of core analysis, wellbore data, and dynamic reservoir simulation. Data used in this study has been compiled from three carbonate oil fields, the Middle East, North America, and Europe, with more than 500 core plugs that were obtained between 1970 and 1999, resulting in analyses of helium porosity and Klinkenberg-corrected permeability (of the cores). Additional characterization was performed on these plug samples using thin-section petrography, micro-CT, and mercury injection capillary pressure. Different groups of pore types were identified and then numerical multi-phase modelling simulating gas-to-oil relative permeability conditions (using the CMG IMEX program), as well as two different statistical regression methodologies (including power law and Kozeny-Carman) were conducted using varying degrees of ɸ-k throughout the reservoirs.
Secondary porosity (such as vugs and fractures) often governs the production of hydrocarbons. However, degradation of porosity-permeability predictability arises from more than simply their existence; it is also caused by factors affecting pore connectivity (such as throat size and throat size distribution) and the continuity of the network. The inclusion of empirical coefficients for vug connectivity will improve hydrocarbon production predictions. For carbonate reservoirs with permeability > 10 mD, hydrocarbon production sensitivity to permeable rock mass will be approximately three times greater than that of porous rock mass. (Experimenting showed that vug network connectivity will enhance the modelling of production rate as a result). The current research applies a class of empirical formulations based on different classes of pore type to modify Darcy’s equation and makes completion recommendations for reservoir engineers. The resulting multivariate regression (R² = 0.81, MAPE = 18%) provides a superior predictive capability over existing models and presents a credible physical model for reservoir engineers to use.
Keywords:
Carbonate reservoirs, porosity–permeability relationship, oil production rate, pore‑type classification, carbonate productivity index.