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Record W2164621666 · doi:10.2118/07-10-04

Effect of Hydrates on Sustaining Reservoir Pressure in a Hydrate-Capped Gas Reservoir

2007· article· en· W2164621666 on OpenAlexaffabout
Shahab Gerami, M. Pooladi‐Darvish

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsHydrateClathrate hydrateEndothermic processPetroleum engineeringDecompositionNatural gasThermodynamicsHeat transferMethaneFluid dynamicsChemistryGeology

Abstract

fetched live from OpenAlex

Abstract A hydrate-capped gas reservoir is defined here as a reservoir that consists of a hydrate-bearing layer underlain by a two-phase zone involving mobile gas. In such a reservoir, hydrates at the top contribute to the produced gas stream once the reservoir pressure is reduced by gas production from the free-gas zone. Large gas reservoirs of this type are known to exist in Alaska and Siberia and are expected to exist in the Mackenzie Delta of the Northwest Territories in Canada. Gas production from a hydrate-capped gas reservoir is a process governed by a combination of mechanisms of heat transfer, fluid flow, thermodynamics and kinetics of hydrate decomposition. Using a comprehensive numerical simulator, an extensive simulation study indicates that some of the non-linear processes involved in gas production from hydrate reservoirs (i.e. the convective heat transfer and the kinetics of hydrate decomposition) have a negligible effect on the overall physics of the process. This significantly reduces the complexity of the heat and fluid flow equations and legitimizes the construction and use of simplified models. In this work, we invoke the above approximations and develop a generalized gas material balance equation. This equation has two significant differences from the material-balance equation for conventional gas reservoirs, including the incorporation of:the effect of cooling due to endothermic decomposition of the hydrate; andthe effect of generated gas and water from the hydrate decomposition. In this model, it is assumed that a mobile phase exists in the hydrate zone; thus, no sharp hydrate dissociation interface is assumed. Considering the sensible heat of the hydrate zone and heat transfer from cap and base rocks, the gas and water generation rates are determined on the basis of the equilibrium rate of the decomposition process. Verification of the solution is obtained by comparing results with those of a comprehensive hydrate reservoir numerical simulator. The model developed here can be used as an approximate engineering tool for evaluating the role of hydrates in improving the productivity and extending the life of hydrate-capped gas reservoirs. Introduction Natural gas hydrates are solid molecular compounds of water with natural gas that are formed under certain thermodynamic conditions. There is evidence that enormous amounts of natural gas exist in the form of hydrate deposits in many regions of the world(1). These deposits occur in sub-oceanic sediments as well as in arctic regions. Every unit volume of gas hydrate has the potential to contain 170 to 180 volumes of gas at standard conditions, making the energy content of one cubic metre of a hydrate reservoir more than other types of unconventional gas reservoirs(2). In view of the large untapped resources of natural gas hydrates, extensive research and development work is underway to determine what fraction of this resource is recoverable. A number of recovery processes have been suggested for producing gas from hydrates in sediments. Sloan(3) and Makogan(4) have presented an extensive review of the suggested methods including depressurization, thermal stimulation and inhibitor injection.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.228
Teacher spread0.222 · 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 designObservational
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

Citations17
Published2007
Admission routes2
Has abstractyes

Explore more

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