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Record W3140836594

SCHEMES OF GAS PRODUCTION FROM NATURAL GAS HYDRATES

2003· article· en· W3140836594 on OpenAlexaboutno aff
Chen Yue-ming

Bibliographic record

VenueChemical Industry and Engineering · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsNatural gasClathrate hydratePetroleum engineeringCabin pressurizationFossil fuelCoalHydrateEnvironmental sciencePetroleumGeologyChemistryMaterials science
DOInot available

Abstract

fetched live from OpenAlex

Natural gas hydrates are a kind of nonpolluting and high quality energy resources for future, the reserves of which are about twice of the carbon of the current fossil energy (petroleum, natural gas and coal) on the earth. And it will be the most important energy for the 21st century. The energy balance and numerical simulation are applied to study the schemes of the natural gas hydrates production in this paper, and it is considered that both depressurization and thermal stimulation are effective methods for exploiting natural gas hydrates, and that the gas production of the thermal stimulation is higher than that of the depressurization. But thermal stimulation is non-economic because it requires large amounts of energy. Therefore the combination of the two methods is a preferable method for the current development of the natural gas hydrates. The main factors which influence the production of natural gas hydrates are: the temperature of injected water, the injection rate, the initial saturation of the hydrates and the initial temperature of the reservoir which is the most important factor. 1 Lei Huaiyan, Wang Xianbin. Current Situation of Gas Hydrates Research and Challenges for Future. Acta Sedimentological Sinica, 1999, 17 (3) 2 Shi Dou, Zheng Junwei. The Status and Prospects of Research and Exploitation of Natural Gas Hydrate in the World. Advance in Earth Sciences, 1999, 14 (4) 3 Chen Huifan4g. Prediction of the Conditions for the Forming of Natural Gas Hydrate. Journal of Xi'an Petroleum Institute, 1994, 9 (1) 4 Yao Yucheng, Yin Fushan. Progressin Study of Natural Gas Hydrates. Progress in Chemistry, 1997, 9 (3) 5 Zhao Shengeai. Current Situation of Gas Hydrate and Our ??Country's Policy. Advancein Earth Sciences, 2002, 17 (3) 6 Zhou Huaiyang, Peng Xiaotong. Development in Technology of Prospecting and Exploitation for Gas Hydrates. Geology and Prospecting, 2001, 38 (1) 7 Zhu Yuenian, Shi Buqing. Control Effects of Natural Gas Hydrates on Oil and Gas Accumulation and Reservoir Preservation. Natural Gas Industry, 2000, 20 (3) 8 Wim J A M Swinkels, Rik J J Drenth. Thermal Reservoir Simulation Model of Production from Naturally Occurring Gas Hydrate Accumulations. SPE 56550 9 Moridis G J, Collett T S, Dallimore S R, Tohru Satoh. Numerical Studies of Gas Production from Several CH_4-Hydrate Zones at the Mallik Site. LBNL 50257. Mackenzie Delta, Canada

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 science0.0000.001
Research integrity0.0000.000
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 head0.007
GPT teacher head0.186
Teacher spread0.179 · 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 designNot applicable
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

Citations0
Published2003
Admission routes1
Has abstractyes

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