This study presents a comprehensive petrographic and petrophysical methodology aimed at quantitatively assessing the influence of diagenetic processes on the elastic properties of the Asmari carbonate reservoir. Thirty core plugs from five wells (A-E) underwent CT-scan imaging to reconstruct pore and fracture geometries with high resolution, in addition to transmitted-light and SEM-EDS petrography, helium porosimetry, mercury injection, gas and Klinkenberg permeability tests, and ultrasonic P- and S-wave velocity measurements. The dataset, consisting of 28 plugs for elastic testing, yields average P- and S-wave velocities of 2,880 m/s and 1,675 m/s, respectively. Regression analysis indicates a strong negative correlation (R2 = 0.85, p < 0.01) between total porosity and P-wave velocity. Principal component analysis (PCA) identifies two components that capture 62% (PC1) and 14% (PC2) of the variance. Cementation and dolomitization exhibit positive loading on PC1 (> 0.75), resulting in 8–12% increases in elastic moduli, while dissolution and fracturing load negatively, leading to reductions in velocities of 10–15%. PCA highlights cementation and dolomitization as critical factors for mechanical stiffening, whereas dissolution and fracturing decrease seismic velocities. Interpolating the resultant PC score grids generates depth-dependent diagenetic–elasticity maps that clarify the spatial variability of these factors within stratigraphic frameworks, providing essential parameters for seismic inversion and reservoir simulation, and enhancing seismic impedance and amplitude versus offset (AVO) facies predictions by approximately 10% compared to conventional workflows. These findings demonstrate that quantitative diagenetic indices can be directly linked to elasticproperty variations and deployed as seismic-inversion attributes. These results highlight the significant role of diagenetic processes in governing reservoir heterogeneity and quality, emphasizing the imperative to integrate advanced petrographic characterization with quantitative petrophysical data for robust reservoir evaluation. By elucidating spatial heterogeneity and elastic property variations, this investigation advances the understanding of carbonate reservoir behavior and informs strategic approaches to optimize hydrocarbon recovery in geologically complex environments.

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