MétaCan
Menu
Retour à la cohorte
Enregistrement W3116813531 · doi:10.11575/prism/38486

Water content of liquid acid gas and liquid propane in the presence of a hydrate phase

2020· dissertation· en· W3116813531 sur OpenAlexfundno aff
Kayode I. Adeniyi

Notice bibliographique

RevueOpen MIND · 2020
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueMethane Hydrates and Related Phenomena
Établissements canadiensnon disponible
Organismes subventionnairesNatural Sciences and Engineering Research Council of Canada
Mots-clésPropaneHydrateClathrate hydrateChemistryPhase (matter)Gas phaseLiquid phaseChromatographyChemical engineeringOrganic chemistryEngineeringThermodynamicsPhysics

Résumé

récupéré en direct d'OpenAlex

Natural gas coexists with water in subsurface reservoirs. Other impurities such as hydrogen sulfide (H2S) and carbon dioxide (CO2) can also be present depending on location and source. Many issues are associated with the presence of water and the acid gas (H2S and CO2) impurities during production, processing and transportation of natural gas such as solid hydrate blockage, corrosion and safety concerns. Before sale to consumers, water and the acid gas impurities are removed or reduced to meet sales and pipeline specifications. One of the viable strategies for managing the removed acid gas is injection (AGI) into underground formations either for sequestration, pressure maintenance or enhanced oil recovery. After acid gas removal, in some cases, natural gas liquid (NGL) are separated from the treated natural gas streams for use as a fuel or chemical feedstock. NGL are separated from the methane (CH4) in a cryogenic separation process, where the presence of water is highly undesirable because it can cause the formation of solid clathrate hydrates. Propane (C3H8) is a principal component of NGL and a sII hydrate former; hence, conditions at which its hydrate will form in the presence of saturated and unsaturated water are important to avoid their formation or determine how much dehydration is required. Because of the toxicity of H2S (100 ppm is the immediate dangerous to life and health concentration), there are limited dissociation data for its hydrate in the presence of water reported in the literature. Also, prior to this work, there were no water content data in equilibrium with only hydrate reported in the literature for H2S. On the other hand, hydrate formation/dissociation conditions for pure CO2 are well studied; however, analysis of the literature water content data at hydrate forming regions shows some variation regarding the pressure dependence of the measurements. These data are necessary to accurately calculate and prevent hydrate formation conditions in sour natural gas production, as well as to define the dehydration requirements for acid gas during transportation to injection facilities. In this work, the dissociation conditions for pure CO2 and pure H2S hydrates in the presence of water rich phase was measured using the phase boundary dissociation method. Also, the water content of pure CO2, pure H2S and pure C3H8 in equilibrium with their respective hydrate were measured using a tunable diode laser spectroscopy technique. These results were modelled using the reference quality Helmholtz energy equations of state for the fluid phases, and the van der Waal and Platteeuw model for the hydrate phases. The calculated results were compared to few available literature, where a good agreement was mostly observed. A thermodynamic model capable of calculating the water content and three phase loci independently using the same optimized parameters, was successfully developed for CO2. However, a single equilibrium model was not successfully found for H2S and C3H8 fluids, hence two different models were recommended for both the water content and three phase loci calculation. In conclusion, the pressure dependence of water content of these gases in equilibrium with their respective hydrates are very weak, but the water content increases as the temperature increases.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,023
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,040
Tête enseignante GPT0,289
Écart entre enseignants0,249 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2020
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueOpen MINDMême sujetMethane Hydrates and Related PhenomenaTravaux en français237 207