Jointly deriving NMR surface relaxivity and pore size distributions by NMR relaxation experiments on partially desaturated rocks
This page lists all metadata that was entered for this dataset. Only registered users of the TR32DB may download this file.
Feature
Request download
Citation
Citation Options
Identification
Title: | Main Title: Jointly deriving NMR surface relaxivity and pore size distributions by NMR relaxation experiments on partially desaturated rocks |
Description: | Abstract: Nuclear magnetic resonance (NMR) relaxometry is a geophysical method widely used in borehole and laboratory applications to nondestructively infer transport and storage properties of rocks and soils as it is directly sensitive to the water/oil content and pore sizes. However, for inferring pore sizes, NMR relaxometry data need to be calibrated with respect to a surface interaction parameter, surface relaxivity, which depends on the type and mineral constituents of the investigated rock. This study introduces an inexpensive and quick alternative to the classical calibration methods, e.g., mercury injection, pulsed field gradient (PFG) NMR, or grain size analysis, which allows for jointly estimating NMR surface relaxivity and pore size distributions using NMR relaxometry data from partially desaturated rocks. Hereby, NMR relaxation experiments are performed on the fully saturated sample and on a sample partially drained at a known differential pressure. Based on these data, the (capillary) pore radius distribution and surface relaxivity are derived by joint optimization of the Brownstein-Tarr and the Young-Laplace equation assuming parallel capillaries. Moreover, the resulting pore size distributions can be used to predict water retention curves. This inverse modeling approach—tested and validated using NMR relaxometry data measured on synthetic porous borosilicate samples with known petrophysical properties (i.e., permeability, porosity, inner surfaces, pore size distributions)—yields consistent and reproducible estimates of surface relaxivity and pore radii distributions. Also, subsequently calculated water retention curves generally correlate well with measured water retention curves. |
Identifier: | 10.1002/2014WR015282 (DOI) |
Citation Advice: | Mohnke, O., 2014. Jointly deriving NMR surface relaxivity and pore size distributions by NMR relaxation experiments on partially desaturated rocks. Water Resources Research, 50 (6), 5309 - 5321. DOI: 10.1002/2014WR015282. |
Responsible Party
Creator: | Oliver Mohnke (Author) |
Publisher: | Wiley Online Library |
Publication Year: | 2014 |
Topic
TR32 Topic: | Soil |
Related Subproject: | A2 |
Subjects: | Keywords: NMR, Surface Relaxivity, Pore-Size Distribution, Modelling |
File Details
Filename: | Mohnke_WRR_2014a.pdf |
Data Type: | Text - Article |
Size: | 13 Pages |
File Size: | 1.6 MB |
Date: | Available: 20.06.2014 |
Mime Type: | application/pdf |
Data Format: | |
Language: | English |
Status: | Completed |
Constraints
Download Permission: | Only Project Members |
General Access and Use Conditions: | According to the TR32DB data policy agreement. |
Access Limitations: | According to the TR32DB data policy agreement. |
Licence: | [TR32DB] Data policy agreement |
Geographic
Specific Information - Publication
Publication Status: | Published |
Review Status: | Peer reviewed |
Publication Type: | Article |
Article Type: | Journal |
Source: | Water Resources Research |
Source Website: | http://onlinelibrary.wiley.com |
Issue: | 6 |
Volume: | 50 |
Number of Pages: | 13 (5309 - 5321) |
Metadata Details
Metadata Creator: | Tanja Kramm |
Metadata Created: | 01.09.2014 |
Metadata Last Updated: | 01.09.2014 |
Subproject: | A2 |
Funding Phase: | 2 |
Metadata Language: | English |
Metadata Version: | V50 |
Metadata Export
Metadata Schema: |
Dataset Statistics
Page Visits: | 1375 |
Metadata Downloads: | 0 |
Dataset Downloads: | 0 |
Dataset Activity
Feature
Download
By downloading this dataset you accept the license terms of [TR32DB] Data policy agreement and TR32DB Data Protection Statement
Adequate reference when this dataset will be discussed or used in any publication or presentation is mandatory. In this case please contact the dataset creator.
Adequate reference when this dataset will be discussed or used in any publication or presentation is mandatory. In this case please contact the dataset creator.