Pore-size data in petrophysics: a perspective on the measurement of pore geometry

被引:46
作者
Basan, PB
Lowden, BD
Whattler, PR
Attard, JJ
机构
[1] Applied Reservoir Technology Ltd., Moat Farm, Milden, Ipswich IP7 7AF, Church Road
[2] Enterprise Oil Plc., Grand Buildings, London WC2N 5EJ, Trafalgar Square
[3] SINTEF Unimed, N-7034, Trondheim
来源
DEVELOPMENTS IN PETROPHYSICS | 1997年 / 122期
关键词
D O I
10.1144/GSL.SP.1997.122.01.05
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Mercury injection capillary pressure (MICP), backscattered electron images (BSEI) and nuclear magnetic resonance (NMR) provide pore-geometry parameters useful for understanding Variations in rock properties. MICP pore size is an area-equivalent diameter of the throats connecting the pore system. The MICP distribution contains a point (the turning point) that reveals where mercury first encounters the permeable network. This point identifies both critical pore size and connected porosity. BSEI measure pore area and diameter. Both parameters are unrelated to any specific morphological element. NMR pore size is a derivative of the pore-surface:volume ratio. Like BSEI, NMR pore size is unrelated to morphological elements. Like MICP, NMR provides a pore-size distribution that represents the entire sample volume. All three techniques provide a data distribution suitable for cross-correlation. Matching distributions determines the character of the permeable pore system. NMR and MICP distributions compare through the entire time and pressure spectra, matching best in the central part of the distributions. The match suggests pore-throats merge with the pore channels in the permeable part of the system. BSEI distributions match only with the low-pressure, stow-time parts of the other distributions. However, image porosity has a stronger correlation with permeability than any of the other parameters, suggesting that the BSEI distribution is near the turning point.
引用
收藏
页码:47 / 67
页数:21
相关论文
共 42 条
[1]  
Akkurt R., Vineger H.J., Tutunjian P.N., Guillory A.J., NMR logging in natural gas reservoirs, Annual Symposium, (1995)
[2]  
Archie G.E., The electrical resistivity log as an aid in determining some reservoir characteristics, AIME Petroleum Technology, pp. 54-62, (1942)
[3]  
Electrical resistivity: An aid in core analysis interpretation, American Association of Petroleum Geologists Bulletin, 31, pp. 350-366, (1947)
[4]  
Brown R.J.S., Gamson B.W., Nuclear magnetism logging, Journal of Petroleum Technology, 219, pp. 199-201, (1960)
[5]  
Brownstein K.R., Tarr C.E., Importance of classical diffusion in NMR studies of water in biological cells, Physics Reviews A, 19, pp. 2446-2453, (1979)
[6]  
Coates G.R., Miller M., Gillen M., Hender-Son G., The MRIL in Conoco 33-1, an investigation of a new magnetic resonance imaging log, Annual Symposium, (1991)
[7]  
The magnetic resonance imaging log characterized by comparison with petrophysical properties and laboratory core data, Annual Technology Conference and Exhibition, Dallas, pp. 627-635, (1991)
[8]  
Delesse M.A., Procede mechanique pour determiner la composition des roches, Comptes Rendus de L'academie des Sciences. Paris, 25, (1847)
[9]  
Dullien F.A.L., Porous Media-fluid Transport and Pore Structure, (1979)
[10]  
Ehrlich R., Crabtree S.J., Horkoswitz K.O., Horkoswitz J.P., Petrography and reservoir physics 1: Objective classification of reservoir porosity, American Association of Petroleum Geologists Bulletin, 75, pp. 1547-1562, (1991)