Relationships between observed pore and pore-throat geometries, measured porosity and permeability, and indirect measures of pore volume by nuclear magnetic resonance
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Carbonate reservoirs are a network of pores and connecting pore-throats that contain at least half of the world's oil. Genetic classification of carbonate pores enables one to map the pore types that have greatest influence on reservoir performance. Though NMR logging has been used to estimate pore sizes, it has not been used to identify genetic pore types or to aid in determinations of reservoir quality for different pore assemblages. Five genetic pore types identified in 40 carbonate and 7 sandstone samples were subjected to NMR measurements. Results reveal close correspondence between NMRderived pore volumes and 2-D pore size and shape gleaned from petrographic image analysis. Comparisons of real and synthetic pore shapes showed that shapes of all pore types in the medium size range of 0.02-0.5mm can be reliably compared with synthetic varieties, but such comparisons were unreliable for vuggy pores smaller than 0.5mm. T2 relaxation times for depositional pores exhibit low amplitude, narrow wavelength responses. Moldic pores produced medium amplitude, asymmetrical wavelength responses, and intercrystalline pores show high amplitude, narrow wavelength responses. NMR-derived pore volumes on pores with ferroan dolomite interiors underestimated pore diameter by up to 3 orders of magnitude. Calculated pore-throat sizes from MICP data correlate strongly with measured permeability. Samples with high, intermediate, or low poroperm values displayed characteristic T2 curves confirming that reservoir quality can be estimated from NMR measurements. Future work is expected to show that NMR logging can estimate reservoir quality at field scale and aid in mapping flow units in compartmentalized reservoirs.
Adams, Aaron J. (2005). Relationships between observed pore and pore-throat geometries, measured porosity and permeability, and indirect measures of pore volume by nuclear magnetic resonance. Doctoral dissertation, Texas A&M University. Texas A&M University. Available electronically from