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Record W2608940261 · doi:10.1002/2016jb013503

Physical mechanisms for multiphase flow associated with hydrate formation

2017· article· en· W2608940261 on OpenAlexaff
Javad Behseresht, Steven L. Bryant

Bibliographic record

VenueJournal of Geophysical Research Solid Earth · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of Calgary
FundersDepartment of Mechanical Engineering, University of Texas at AustinU.S. Department of Energy
KeywordsClathrate hydrateHydrateSaturation (graph theory)GeologyCapillary pressureMethanePetrologyMineralogyGeotechnical engineeringChemistryPorous mediumPorosity

Abstract

fetched live from OpenAlex

Abstract Many Arctic hydrate reservoirs such as those of the Prudhoe Bay and Kuparuk River area on the Alaska North Slope (ANS) are believed originally to be natural gas accumulations converted to hydrate accumulations after being placed in the gas hydrate stability zone (GHSZ) in response to ancient climate cooling. In this work, the implications of a previously described mechanistic model for the transport of gaseous and aqueous phases are studied using a transient 1‐D transport model during the conversion of a gas reservoir to a hydrate reservoir. The mechanistic model predicts/explains the vertical profile of hydrate saturation in “converted free gas” hydrate reservoirs. The initial gas phase saturation with depth is estimated from the profile of capillary entry pressure, which is estimated from grain size distributions measured in cores. The gas accumulation is assumed to be disconnected from its original source so that methane transport occurs only within it. As the base of the GHSZ descends through the sediment, hydrate forms within the GHSZ. The net volume reduction associated with hydrate formation creates a “sink” which drives flow of gaseous and aqueous phases to the hydrate formation zone. Mechanisms by which this fluid movement could have occurred are analyzed. Flow driven by saturation gradients plays a key role in creating reservoirs of large hydrate saturations, as observed in Mount Elbert stratigraphic test well in the Milne Point Unit of Alaska North Slope (ANS). Viscous‐dominated pressure‐driven flow of gaseous and aqueous phases cannot explain large hydrate saturations originated from large‐saturation gas accumulations. The mode of hydrate formation for a wide range of rate of hydrate formation, the rate of descent of the base of GHSZ, and host sediment characteristics are analyzed and characterized based on dimensionless groups. The proposed transport model is also consistent with field data from hydrate‐bearing sand units in Mount Elbert well. Results show that not only the petrophysical properties of the host sediment but also the rate of hydrate formation and the rate of temperature cooling at the surface contribute greatly to the final hydrate saturation profiles.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.042
GPT teacher head0.343
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2017
Admission routes1
Has abstractyes

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