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Record W2313431356 · doi:10.2118/176127-ms

R&D Technologies for Acid Gases Extraction from Natural Gases

2015· article· en· W2313431356 on OpenAlexaboutno aff
Lev A. Bagirov, Salavat Z. Imaev, Vasily E. Borisov

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSpacecraft and Cryogenic Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsNatural gasSeparator (oil production)Supersonic speedNozzleProcess engineeringExtraction (chemistry)Natural-gas processingGas separationIndustrial gasChoked flowAir separationMaterials scienceEnvironmental scienceMembraneWaste managementChemistryMechanical engineeringEngineeringChromatographyGas turbinesAerospace engineeringThermodynamicsPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract This paper describes main processes used for removal of CO2 from natural gases and some results of under R&D technologies of acid gases extraction from natural gases, including the method of 3S-technology (SuperSonic Separation technology). There are various methods of acid components extraction from the natural gas: adsorptive, adsorptive, membrane, cryogenic and their various combinations. All mentioned technologies are notable for necessity to use a large number of accessory equipment, including bulky one that leads to the high capital investment costs and great operational costs, and also to the costs for restoration of adsorbents/absorbents, clearing of membranes, etc. These circumstances make the existing technologies inapplicable in terms of cost efficiency. At the same time, a significant progress was recently being made in the development of new low-temperature processes of extracting CO2 from natural gas. Low-temperature processes are specially promising in processing of gases with high CO2 content. Several low-temperature processes of CO2 removal are presently known: –Ryan Holmes method;–Controlled freeze zone method (CFZ);–Cryocell method (Cryocell);–Sprex method (Sprex);–Gasdynamic separation of gas mixtures (3S-separation). All 5 above mentioned low-temperature processes of acid components extraction will be considered and analysed in this paper. While the main focus is on the analysis of 3S-separation technology. 3S-separator is a low-temperature supersonic separator, based on natural gas cooling in a supersonic swirling flow. Supersonic flow is implemented using a convergent-divergent Laval nozzle. In this nozzle, rapid cooling of gas takes place due to the conversion of flow potential energy into kinetic energy. This workcontains a detailed description of 3S-technology. Someexistential schematic diagrams of devises based on 3S-separation will be presented in this paper. The advantages and limitations of this technologyhave been investigated during the study. Currently3S-separators have been successfully operatedat severalgas processing facilities. Experimental studiesof CO2 separation from naturalgaswere carried out onthe test unitwith the3S-separator, designed for 6000 nm3/hour gas flow. Duringtests it has been shownthat the technologymakes possible theseparation of CO2 inthe carbon dioxide crystallization zone. The performed tests demonstrated that it is possible to achieve less than 3% mol CO2 concentration in the inlet gas.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.004

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 head0.263
Teacher spread0.229 · 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 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

Citations7
Published2015
Admission routes1
Has abstractyes

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