Nuclear Magnetic Resonance Logging-Based Permeability Classification Modeling for Tight Sandstone Reservoirs

The Upper Paleozoic tight sandstone reservoirs on the eastern margin of the Ordos Basin exhibit strong heterogeneity and complex pore structures, leading to poor correlation between porosity and permeability and insufficient accuracy in permeability calculations to meet the requirements of reservoir...

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Bibliographic Details
Published in:Processes 2024-07, Vol.12 (7), p.1309
Main Authors: Liang, Zhongkui, Li, Xueying, Sun, Aiyan, Hou, Fang, Zhai, Zhiwei, Sui, Qiang
Format: Article
Language:English
Subjects:
Capillary flow
Capillary pressure
Classification
Data logging
Error analysis
Flow characteristics
Heterogeneity
Lithic
Lithology
Magnetic permeability
Membrane permeability
Minerals
Modelling
NMR
Nuclear magnetic resonance
Paleozoic
Permeability
Physical properties
Porosity
Probability distribution
Quartz
Reservoirs
Sandstone
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Summary:The Upper Paleozoic tight sandstone reservoirs on the eastern margin of the Ordos Basin exhibit strong heterogeneity and complex pore structures, leading to poor correlation between porosity and permeability and insufficient accuracy in permeability calculations to meet the requirements of reservoir fine evaluation. Therefore, a new method for high-precision permeability calculation based on flow zone index (FZI) reservoir classification is proposed. This method determines the number of reservoir classifications based on the characteristics of the FZI normal probability distribution plot and establishes FZI division criteria for reservoir types. Classified reservoirs exhibit similar flow characteristics, significantly improving the correlation between permeability and porosity. Based on nuclear magnetic resonance (NMR) combined with mercury injection capillary pressure (MICP) experiments, a modeling method for calculating the flow zone index based on the geometric mean of NMR T2 is proposed. This method realizes continuous calculation of FZI based on NMR logging, reservoir classification, and permeability for the entire wellbore, thereby constructing a new permeability prediction method for tight sandstone reservoirs based on NMR logging and FZI classification. Actual application results demonstrate that the permeability calculated using NMR logging is in high agreement with the permeability analyzed from core data, with an average relative error of 45.8%, proving the effectiveness of the proposed method in this study.
ISSN:2227-9717
2227-9717
DOI:10.3390/pr12071309