Carbonate-Rock-Physics Issues

Abstract

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper IPTC 13850, ’Carbonate-Rock Physics Issues,’ by Enru Liu, Michael A.Payne, Shiyu Xu, Gregor Baechle, and Christopher E. Harris, ExxonMobil Upstream Research, prepared for the 2009 International Petroleum Technology Conference, Doha, Qatar, 7-9 December. Limestone and dolomite reservoirs account for approximately half of oil and gas production worldwide, yet seismic responses in carbonate rocks are poorly understood. Development of a carbonate-rock-physics model is extremely difficult because the pore systems are more complex in carbonates than in clastics. In addition to pore types and shapes, other factors that need to be included in a physics-based rock model include lithology, grain shapes, multiphase-fluid and wetting effects, rock/fluid interactions (poroelasticity), stress effects, anisotropy, heterogeneity and scale effects, chemical changes to the framework, and corrections for environmental effects for logging conditions. The effect and validation of several of these factors are presented. Introduction Carbonates can have a variety of pore types, such as moldic, vuggy, interparticle, or intraparticle. The complex pore system creates significant scatter in the porosity/velocity relationship. Pore shape appears to be the dominant factor in carbonate-rock physics. Moldic, intraframe, and vuggy pores tend to be rounded and make the rock stronger (faster) than pores that are interparticle. Micropores (e.g., microcracks) tend to be flat and make the rock weaker. To characterize carbonate reservoir rocks effectively, it is critical to develop a rock-physics model that is capable of handling different pore types. Any rock-physics model should be calibrated and validated with controlled laboratory experiments, field measurements, and computational rock physics. Carbonate-Rock Physics Model An analytical-rock-physics model was selected rather than an empirical one because of the analytical model’s predictive power without the need to acquire considerable analog data and because it is physics based. Empirical rock-physics models often are used because of their simplicity in fitting a relationship between parameters. With an analytical model, once parameters that describe the physical controlling factors are determined, the model can be applied anywhere that the controlling parameters can be estimated. This method achieves better predictions and a deeper understanding of the subsurface than empirical models, with less data. Nonlinear physics-based inclusion models are attractive because they handle various factors that affect seismic response in an internally consistent manner.