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Record W4253177429 · doi:10.2118/2002-098

Using Low-Field NMR to Determine Wettability of, and Monitor Fluid Uptake in, Coated and Uncoated Sands

2002· article· en· W4253177429 on OpenAlexaff
F. Manalo, Apostolos Kantzas

Bibliographic record

VenueCanadian International Petroleum Conference · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNMR spectroscopy and applications
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsWettingField (mathematics)Materials sciencePetroleum engineeringGeologyComposite materialMathematics

Abstract

fetched live from OpenAlex

Abstract Methods commonly used to measure the wettability of unconsolidated porous media are quick and easy to perform, but these tests do not provide reproducible results. This paper outlines the use of low-field nuclear magnetic resonance (NMR) as an alternative method of wettability assessment due to this tool's ability to discriminate bound fluid from bulk fluid. Water bound to the grain surfaces of water-wet samples relaxes quickly and produces signal amplitude peaks at low transverse relaxation (T2) values. Bulk water, on the other hand, relaxes much more slowly and signal amplitude peaks consequently appear at higher T2 values. It is expected that the contribution of surface-bound water in waterrepellent samples is lower than in water-wet samples. NMR measurements performed on water-wet sand and on the same sand coated with organic matter clearly show significant differences in solid-fluid interactions between water and sands of different wettabilities. Numerous NMR measurements were obtained over time to monitor relaxation shifts because it was expected that the resulting spectra would provide insight into the rate of fluid uptake in sands of varying wettability. Water uptake appears to be spontaneous in water-wet samples and much slower in water-repellent samples, however all samples will eventually reach the same equilibrium endpoint regardless of wettability. NMR spectra also show that the results from water in uncoated and coated sands closely resemble that from water in wettable and water-repellent soils. Consequently, uncoated and coated sands can be used to analyse wettability mechanisms in unconsolidated porous media. The results also show that causative agents of soil water repellency include asphaltenes that are insoluble to n-pentane. Introduction Wettability is defined as "the tendency of one fluid to spread on or adhere to a solid surface in the presence of other immiscible fluids"1. This parameter is not a fixed and constant property2 due to factors such as saturation and climate history as well as sample handling3. Wetting and non-wetting fluids interact with a porous medium differently and these differences can be detected by low-field nuclear magnetic resonance (NMR)4–6. One can infer the state of fluids within a porous medium from looking at NMR spectra based on type-specific transverse relaxation time (T2) cutoffs7–9. Contributions to spectra at values of T2 that are lower than the cutoff are considered due to bound water while contributions at higher T2 values are considered due to water in the bulk phase7,10. Amplitude peaks at progressively lower T2 values indicate the presence of fluid in progressively smaller pores. The location of the amplitude peaks in NMR spectra can be used to infer sample wettability11. While this has been done in porous media such as sandstones, carbonates and chalk12–15, no work has been done on soils. NMR can be a viable tool for assessing soils wettability because other wettability measurements such as the contact angle are impossible to make in unconsolidated porous media. While tests such as the molarity of ethanoldroplet (MED)16 and water droplet penetration time (WDPT)2,3,17 tests are quick and simple to perform, these values usually are not well correlated for a given sample.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.300
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2002
Admission routes1
Has abstractyes

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