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AAPG Bulletin, V.
1University of Miami, Rosenstiel School of Marine and Atmospheric Science, Division of Marine Geology and Geophysics, 4600 Rickenbacker Causeway, Miami, Florida 33129; [email protected]
2University of Miami, Rosenstiel School of Marine and Atmospheric Science, Division of Marine Geology and Geophysics, 4600 Rickenbacker Causeway, Miami, Florida 33129; [email protected]
3University of Miami, Rosenstiel School of Marine and Atmospheric Science, Division of Marine Geology and Geophysics, 4600 Rickenbacker Causeway, Miami, Florida 33129
4Gerencia Geologia y Estudios Integrados, Direccion Exploracion y Desarrollo de Negocio, Macacha Guemes 515, (C1106BKK), Puerto Madero, Buenos Aires, Argentina
5Department of Geology and Geophysics, Texas AM University, College Station, Texas 77843
Carbonate rocks commonly contain a variety of pore types that can vary in size over several orders of magnitude. Traditional pore-type classifications describe these pore structures but are inadequate for correlations to the rock's physical properties. We introduce a digital image analysis (DIA) method that produces quantitative pore-space parameters, which can be linked to physical properties in carbonates, in particular sonic velocity and permeability.
The DIA parameters, derived from thin sections, capture two-dimensional pore size (DomSize), roundness (), aspect ratio (AR), and pore network complexity (PoA). Comparing these DIA parameters to porosity, permeability, and P-wave velocity shows that, in addition to porosity, the combined effect of microporosity, the pore network complexity, and pore size of the macropores is most influential for the acoustic behavior. Combining these parameters with porosity improves the coefficient of determination (R2) velocity estimates from 0.542 to 0.840. The analysis shows that samples with large simple pores and a small amount of microporosity display higher acoustic velocity at a given porosity than samples with small, complicated pores. Estimates of permeability from porosity alone are very ineffective (R2 = 0.143) but can be improved when pore geometry information PoA (R2 = 0.415) and DomSize (R2 = 0.383) are incorporated.
Furthermore, results from the correlation of DIA parameters to acoustic data reveal that (1) intergrain and/or intercrystalline and separate-vug porosity cannot always be separated using sonic logs, (2) P-wave velocity is not solely controlled by the percentage of spherical porosity, and (3) quantitative pore geometry characteristics can be estimated from acoustic data and used to improve permeability estimates.
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