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Record W2119630728 · doi:10.2118/137439-pa

Numerical Study of Gas Evolution and Transport Behaviours in Natural Gas-Hydrate Reservoirs

2011· article· en· W2119630728 on OpenAlexaffabout
Fred Wright, Dennis Coombe

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsNatural Resources CanadaAlberta Innovates
Fundersnot available
KeywordsNatural gasHydrateBubbleRelative permeabilityPorous mediumClathrate hydrateMultiphase flowCabin pressurizationGas bubbleNatural gas fieldKinetic energyReservoir simulationPetroleum engineeringDissociation (chemistry)ThermodynamicsWork (physics)MechanicsChemistryGeologyPorosityMaterials scienceGeotechnical engineeringPhysics

Abstract

fetched live from OpenAlex

Summary Gas hydrates are a potentially vast untapped source of natural gas. Recent numerical and field studies suggest the Mallik gas-hydrate field in Canada's Mackenzie Delta may represent a technically producible and potentially economically viable reservoir of natural gas. Our initial reservoir simulations using a kinetic reaction approach indicate that gas evolution and transport within porous geologic reservoirs have a significant effect on fluid production characteristics, while field and laboratory data suggest that significant amounts of evolved gas can be trapped for some time within the reservoir, depending on the field operation. In this work, we invoke modelling concepts extensively employed in quantifying gas ex-solution from viscous oils to further assess the kinetic behaviour of gas-hydrate ex-solution through depressurization. Here, the gas bubbles can be categorized into three groups with explicit transport behaviour: small bubbles (water phase), large bubbles (immobile) and connected bubbles (or free gas). These concepts allow the development of a new set of kinetic reactions for hydrate dissociation: one representing the (possibly delayed) conversion of hydrate into water and dispersed gas bubble phases, and one representing the evolution from dispersed bubbles to connected bubbles. These reactions can effectively capture the nonequilibrium fluid-flow behaviour observed in field production tests. For modelling of the transport phenomenon, we assumed two explicit mobility formulations: (1) trapped bubbles (no mobility) and a flowing water phase and (2) large connected gas bubbles and flowing water (with relative mobility). Relative mobility can be estimated by using traditional gridblock-relative permeability curves. We then develop a simple mechanistic gas bubble trapping tool as a function of the capillary number, which can easily be incorporated into our numerical simulator. This entrapment of the nonwetting gas-phase results in higher values of critical gas saturation. Two case studies based on alternative representations of a Mallik-like gas-hydrate reservoir demonstrate that significant errors can result in reservoir modelling if these fluid transport phenomena are not adequately represented in numerical simulations. Aspects of the model developed here have been applied to history matching and prediction of natural gas recovery from a clastic, sand-dominated reservoir at the Mallik site.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.201
Teacher spread0.191 · 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 designSimulation or modeling
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

Citations30
Published2011
Admission routes2
Has abstractyes

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