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Record W2371030617

Applications of incinerators in well test of high sour gas wells at Puguang gas field

2009· article· en· W2371030617 on OpenAlexaboutno aff
Wenchang Zhang

Bibliographic record

VenueTianranqi gongye · 2009
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSour gasCombustionFuel gasNozzlePetroleum engineeringEngineeringWaste managementAcid gasNatural gasChemistryMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

Presently,the combustion cylinder is commonly used for well test at high sour gas wells. However,it often results in low combustion efficiency,incomplete H2S combustion,excessive SO2 emission and short gas well test time,so it's difficult to accurately evaluate gas production capacity. This paper hereby introduces the Q3000 incinerator which is designed and manufactured by a specialized corporation in Canada. The working principles,calculation methods of diffusion model and main technical indexes are introduced. The arranged nozzle design and logical control procedures can create a high velocity vortex and high combustion temperature ranging from 1090℃ to 1630℃,which can ensure complete combustion of high sour gas,adequate diffusion of sulfur dioxide. Six incinerators are connected in parallel so as to meet the demand of well test at high sour gas wells. The design capacity is 60×104m3/d. The accumulation hours of gas combustion in well test are 240 hours. The incinerators represent favorable combustion performances with long period,high efficiency and full load. The environmental monitoring results indicate that monitoring indicators can meet the requirement. System test in high sour gas wells is realized successfully,which provides scientific underpinnings for gas reservoir development.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.331
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.004
GPT teacher head0.200
Teacher spread0.196 · 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 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

Citations0
Published2009
Admission routes1
Has abstractyes

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