--> Multi-Component Characterization of Carbonate Reservoirs

AAPG Annual Convention and Exhibition

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Multi-Component Characterization of Carbonate Reservoirs

Abstract

Combined and simultaneous interpretation of compressional wave (P-wave) and shear wave (S-wave) data can improve subsurface images and estimation of reservoir and fluid properties. The improvement is possible because P-waves and S-waves respond differently to solids and fluids. Recent advances made to quantify relationships between P-wave velocity (Vp) and S-wave velocity (Vs) have led to using the relationships predictably, and to the technical development of petrophysical models for quantitative reservoir characterization, especially in carbonate reservoirs. Development of predictive petrophysical models is based on a family of linear equations relating Vp, Vs and porosity at different levels of effective stress. Multiple parameters extracted from the slopes and intercepts of the linear equations exhibit special uniqueness for carbonates and are superior to the traditional use of the Vp/Vs ratio for lithology prediction. They also show that S-waves “see” carbonate porosity and pore fluids better than P-waves, and that effective stress or rock competence is an important factor when interpreting multi-component data. Examples are shown, using core data, where linear-linear crossplots and the parameters derived from the family of equations can be used to discriminate pore fluids and carbonate rock-types, determine carbonate reservoir heterogeneity, and distinguish carbonates from sandstones. These results provide a new knowledge base and systematic technical development and understanding of applications of multi-component data. The results can further unleash new technologies in the emerging area of seismic petrophysics, and in monitoring carbon dioxide (CO2) flood front during injection or sequestration. Other potential outcomes include improved estimation of rock mechanical properties, “manufacture” of Vs from Vp, and use of S-wave data to refine porosity and fluid estimation.

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