Affiliation:
1. Technische Universität Clausthal, Institut für Geophysik, Clausthal-Zellerfeld 38678, Germany.(corresponding author).
Abstract
The mercury injection capillary pressure (MICP) method and nuclear magnetic resonance (NMR) relaxometry provide insight into the pore radius distribution (PRD) either of pore throats (MICP) or pore bodies (NMR) of rocks. One variety of permeability ( k) prediction models is based on the knowledge of the PRD. We have evaluated the quality of k-prediction models using a sample set of Eocene sandstones with known values of measured permeability. The Swanson method relates the apex point of the capillary pressure curve to k. Although this widely acknowledged method uses only a single point of the PRD, it provides a predictive quality with an average ratio between the measured and predicted permeability lower than a factor of three. The pore throat radius of the apex point proves to be a good proxy of the effective hydraulic radius. We determine that an improved k prediction can be achieved if a larger section of the PRD is considered in our generalized model. Using reliable values of surface relaxivity, the NMR relaxation time distribution is transformed into a PRD. We find that a characteristic apex point can be determined from NMR data, too. This characteristic point enables a good k prediction for the set of Eocene sandstone samples. In contrast to MICP, the predictive quality cannot be improved by applying an integration over a larger section of the PRD. Further tests with samples of different pore structure and lithology should demonstrate the potential of our models.
Publisher
Society of Exploration Geophysicists
Subject
Geochemistry and Petrology,Geophysics
Reference45 articles.
1. American Society for Testing and Materials (ASTM), 1998, Standard test method for determination of pore volume and pore volume distribution of soil and rock by mercury intrusion porosimetry: vol. 04.08 Soil and Rock, Section 4, D4404-84, 579–583.
2. The Development and Application of a New Semi-Analytical Model to Estimate Permeability from Mercury Injection Capillary Pressure
3. Validation of Permeability and Relative Permeability Data Using Mercury Injection Capillary Pressure Data
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