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Record W7014240455

Phase Field Theory Modeling of CH4 and CO2 Fluxes from Exposed Natural Gas Hydrate Reserviors

2009· dissertation· en· W7014240455 on OpenAlexaboutno aff

Bibliographic record

VenueBergen Open Research Archive (BORA) (University of Bergen) · 2009
Typedissertation
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsClathrate hydrateHydrateNatural gasOutcropArcticSedimentOil shaleMethaneCarbon dioxideHydrocarbon
DOInot available

Abstract

fetched live from OpenAlex

Natural gas hydrates are widely distributed in sediments along continental margins, and harbor enormous amounts of energy. Gas hydrates are crystalline solids which occur when water molecules form a cage like structure around a non-polar or slightly polar (eg. CO2, H2S) molecule. These enclathrated molecules are called guest molecules and obviously have to fit into the cavities in terms of volume. Massive hydrates that outcrop the sea floor have been reported in the Gulf of Mexico (MacDonald, et al., 1994). Hydrate accumulations have also been found in the upper sediment layers of Hydrate ridge, off the coast of Oregon and a fishing trawler off Vancouver Island recently recovered a bulk of hydrate of approximately 1000kg (Rehder, et al., 2004). Håkon Mosby Mud Volcano of Bear Island in the Barents Sea with hydrates openly exposed at the sea bottom (Egorov, Crane, Vogt, Rozhkov, & Shirshov, 1999). In oil and gas industry the most common guest molecules are methane, ethane, propane, butane, carbon dioxide and hydrogen sulfide. But hydrocarbons with up to seven carbons can create hydrate. The worldwide energy contained in hydrates is huge. But at the same time many of the natural hydrate resources are not well trapped below clay and shale layers and dissociate through contact with under saturated water. Arctic hydrates may be covered by ordinary geological trapping mechanisms and ice layers of varying thickness. The integrity of the geological trappings in these areas are, to a large extent unknown and many potential scenarios can occur when the ice is shrinking in these areas. One of the largest environmental problems facing mankind in the 21st century is the impacts on global weather patterns due to greenhouse gases like methane, carbon dioxide and chlorofluorocarbons. It also effects the distribution of ecosystems and sea level change due to the impact of increased temperature on the melting of arctic ice and the shrinking of other permafrost ice like for instance glaciers. As a greenhouse gas CH4 is in the order of 25 times as aggressive as carbon dioxide. It is therefore an important global challenge to be able to make reasonable predictions of the dissociation flux of exposed hydrate reservoirs, and the associated CH4 that escapes to the atmosphere after biological consumption and conversion through inorganic and organic reactions. There are several possible methods for reduction and stabilization of the CO2 content in the atmosphere, ocean disposal and storage stands out as one solution. There are several options for this (different depths). The seafloor lake alternative, which implies disposal of CO2 at depths for which the density of CO2 is higher than that of seawater, might be the most promising. None of the ocean storage options for CO2 are permanent. But the presence of a CO2 hydrate film at the interface between water and CO2 in the seafloor lake will significantly reduce the dissolution of CO2 into the ocean water. The primary focus in this thesis is on the dissociation of methane and carbon dioxide hydrates due to thermodynamic instabilities through direct contact with under saturated water. For this purpose Phase Field Theory (PFT) was chosen as the scientific method. This is the first work on these types of systems with this level of theoretical methods and the scope have initially been limited to PFT without hydrodynamics. This puts an inherent limit on the types of...

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.650
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.034
GPT teacher head0.301
Teacher spread0.267 · 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.

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

Citations2
Published2009
Admission routes1
Has abstractyes

Explore more

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