Bridging the Gap Between Seismic and Well- Derived Porosity in Stacked Carbonate Reservoirs: Lessons from a Mature Oil Field

Abstract

Reservoir characterization is essential for optimizing hydrocarbon production, as it enables accurate determination of subsurface properties such as porosity, permeability, and fluid saturation. Traditionally, this process relied on the accurate interpretation of well logs, seismic data, and core samples through physics-based methodologies. Nonetheless, these conventional techniques can be limited when dealing with complex datasets and heterogeneous reservoir characteristics. In the context of reservoir modelling, precise porosity estimation is particularly important because it directly affects storage capacity (STOIIP), fluid flow dynamics, and overall reservoir productivity. Accurate porosity calculation is essential to reservoir characterization and is a key focus of this study. This study reports the results of two seismic inversion approaches—post-stack deterministic seismic inversion and simultaneous inversion—with a focus on porosity calibration. It investigates the causes of discrepancies between inversion derived and well derived porosity in carbonate reservoirs within a mature offshore oil field. Reservoirs in the study area are shallow water platform carbonates, covering part of inner to outer ramp deposition and variable thicknesses. All potential limiting factors, whether acting alone or in combination, have been identified as causes for the differences observed between porosity values derived from seismic data and those obtained from well measurements. The study also incorporates supporting modelling techniques, including wedge modelling, forward modelling, Amplitude Variation with Offset (AVO) analysis, fluid substitution modelling, and seismic attribute analysis, to aid in the evaluation of these limiting factors and quantification of their contribution. The study found that both post-stack deterministic seismic inversion and simultaneous inversion methodologies can estimate porosity in stacked carbonate reservoirs, but notable discrepancies exist between seismic-derived and well-based porosity values. These uncertainties result from the complex interplay among various interdependent factors, including geological conditions, data quality, and technological capabilities. The research identified six key limiting factors (reservoir heterogeneity, tuning & variable thickness, fluid effects, scale dependency, seismic/logs data quality and technology) that contribute to reduce the reliability of seismic porosity predictions. Supporting modeling techniques—like wedge modeling, forward modeling, AVO analysis, fluid substitution, and seismic attribute analysis—were used to better understand and evaluate percentage error from each factor. The risk matrix summarizes the relative percentage error from each factor in porosity determination. Upper limits are not defined in the risk matrix as they may vary based on the geographic location, reservoir properties and data quality. The percentage errors provided in this study are based on models and data from carbonate oil reservoirs in the Middle East. The study is novel in systematically identifying and analyzing the combined effects of multiple limiting factors on the accuracy of seismic-derived porosity estimates in stacked carbonate reservoirs, using advanced modeling and analysis techniques to provide a more comprehensive understanding of porosity prediction challenges in complex carbonate settings.