Abstract This study aims to develop a robust static reservoir model for the Shuaiba Formation in the Field ‘X’, Onshore, Abu Dhabi. The formation exhibits complex depositional environments—ranging from platform interiors to basinal settings—necessitating an integrated geological, petrophysical, and geophysical approach. The objective is to capture geological heterogeneities and generate reliable models for porosity, permeability, and facies distribution, thereby enabling improved reservoir understanding, accurate volumetric assessment, and development planning. A multi-disciplinary workflow was implemented, integrating seismic interpretation, core description, petrophysical analysis, and well log data. The 3D grid model (50×50m cell size) was structurally constrained by clinoform surfaces interpreted from reprocessed seismic and tied to sequence tops. The reservoir was divided into four clinoform-based zones. Facies modeling utilized rock-typed well data, thickness trends, and vertical proportion curves to guide Sequential Indicator Simulation (SIS). Rudist facies (RT1) were further constrained using RMS and Coherency blended seismic volume. Porosity was populated using Gaussian Random Function Simulation, honoring core-log relationships. A pseudo cloud transform methodology was implemented to model permeability. This involved generating synthetic porosity-permeability cross-plots (pseudo clouds) based on core data relationships within each rock type. These pseudo clouds were statistically transformed and used to guide the Sequential Gaussian Simulation (SGS), allowing the permeability distribution to reflect both spatial trends and the observed scatter in core-derived poro-perm relationships. Water saturation was estimated via a saturation-height function calibrated for each rock type. The facies model effectively captured lateral heterogeneity from reefal grainstones to deeper water mudstones. High-quality reservoir facies (RT1, RT2) dominate the upper clinoform tops, while poorer rock types increase basin-ward. The porosity model aligned closely with core-log trends, preserving heterogeneity and histograms. Permeability models successfully incorporated high-permeability streaks and preserved the observed scatter with porosity. Saturation modeling revealed consistent agreement with log-derived values, validating the approach.
Sundriyal et al. (Mon,) studied this question.