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Record W2046024882 · doi:10.2118/102915-ms

Magnetic Resonance Imaging of Methane—Carbon Dioxide Hydrate Reactions in Sandstone Pores

2006· article· en· W2046024882 on OpenAlexaff
A. Graue, Bjørn Kvamme, Bernard A. Baldwin, James Stevens, James Howard, Geir Ersland, Jarle Husebø, D. R. Zornes

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsHydrateMethaneClathrate hydrateCarbon dioxidePorous mediumPorosityChemistryPermeability (electromagnetism)Carbon fibersChemical engineeringMineralogyMaterials scienceOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Abstract Formation and growth of methane hydrates in porous sandstone was monitored using Magnetic Resonance Imaging (MRI). A series of 3-D MRI images collected during these experiments illustrated patterns of hydrate growth. Calibrated MRI intensity changes that occured during the hydrate growth correlated with methane gas consumption and gave dynamic and quantitative in-situ information on hydrate formation rate and spatial distribution of the hydrate formed. Gas permeability was measured at various hydrate saturations and during hydrate growth. Experimentally it was verified that methane hydrate in porous sandstone spontaneously converted to CO2 hydrate when exposed to liquid CO2 at high pressure and low temperature. It has experimentally been determined that without heating, an exchange process between CO2 and methane occured allowing the injected CO2 to be stored as hydrate resulting in spontaneous production of methane, with no associated water production. The MRI images provided quantitative information on the methane production rates and amounts of methane released during the CH4-CO2 hydrate exchange reaction. Thermodynamic simulations based on Phase Field theory supported the measured results and predicted similar methane production rates observed in several reproduced experiments.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.829
Threshold uncertainty score0.546

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 head0.009
GPT teacher head0.229
Teacher spread0.220 · 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

Citations25
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueSPE Annual Technical Conference and ExhibitionSame topicMethane Hydrates and Related PhenomenaFrench-language works237,207