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Determination of the Absolute Adsorption Isotherms of CH<sub>4</sub> on Shale with Low-Field Nuclear Magnetic Resonance

2018· article· en· W2783819812 on OpenAlexaff
Yueliang Liu, Chen Wang

Bibliographic record

VenueEnergy & Fuels · 2018
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Alberta
FundersXi'an Shiyou UniversityChengdu University of TechnologyChina Scholarship Council
KeywordsAdsorptionOil shaleChemistryPhase (matter)Analytical Chemistry (journal)ThermodynamicsPhysical chemistryChromatographyGeologyPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Understanding of the absolute adsorption behavior of CH 4 on shale is critically important in estimating shale gas storage in shale gas reservoirs. In this work, two approaches are applied to obtain the absolute adsorption isotherms of CH 4 on shale samples. In the first approach, we first measure the excess adsorption isotherms of CH 4 on two shale samples at the temperature of 298.15 K and pressures up to 12.0 MPa. Then, grand canonical Monte Carlo (GCMC) simulations are used to calculate the adsorption-phase density; such density values are consequently applied to calibrate the measured excess adsorption and obtain the accurate absolute adsorption isotherms. As for the second approach, we apply the low-field nuclear magnetic resonance (NMR) method to describe the absolute adsorption of CH 4 on shale. A NMR-based setup is designed to measure the T 2 spectrum distributions in shale samples by injecting CH 4 into dry shale samples. The injecting pressure is set up to 12.0 MPa, which is similar to the conditions used in the excess adsorption measurements. On the basis of the measured T 2 spectrum and the injected molar amount of CH 4, the adsorbed molar quantity of CH 4 can be assessed on the shale samples under specific conditions. We then compare the absolute adsorption isotherms obtained from both methods and evaluate the capability of the NMR approach in determining the absolute adsorption of CH 4 on shale. With GCMC simulations, we find that the calculated adsorption-phase density strongly correlates with the system pressure and temperature. By taking into consideration the adsorption-phase density, the absolute adsorption isotherm is always higher than the measured excess adsorption curves; that is, the measured excess adsorption underestimates the actual adsorption capacity on shale. On the basis of the comparison results, the adsorption isotherms obtained from the NMR method have a good agreement with the corresponding absolute adsorption isotherms after calibrating with the adsorption-phase density; it indicates that the low-field NMR-based setup is a good tool in obtaining the absolute adsorption isotherms of CH 4 on shale.

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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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.277

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)0.0000.000

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 head0.005
GPT teacher head0.183
Teacher spread0.178 · 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 designBench or experimental
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

Citations40
Published2018
Admission routes1
Has abstractyes

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