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Enregistrement W4240018922 · doi:10.2118/2000-095

Determination of Oil and Water Compositions of Oil/Water Emulsions Using Low Field NMR Relaxometry

2000· article· en· W4240018922 sur OpenAlexaff
K. Mirotchnik, K. Allsopp, A. Kantzas

Notice bibliographique

RevueCanadian International Petroleum Conference · 2000
Typearticle
Langueen
DomainePhysics and Astronomy
ThématiqueNMR spectroscopy and applications
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésRelaxometryOil fieldField (mathematics)Petroleum engineeringMaterials scienceChromatographyChemistryGeologyMathematicsMagnetic resonance imaging

Résumé

récupéré en direct d'OpenAlex

Abstract During production operations in heavy oil and bitumen formations where thermal recovery methods are applied, the fluids produced are often in the form of emulsions. This is also true in non-thermal recovery methods whenever oil and water are co-produced, but to a lower degree of severity. Conventional flow measuring devices are capable of measuring oil and water streams when they are segregated but they fail when oil-in-water or water-in-oil emulsions form. Conventional methods are also not reliable when there are solids flowing in the stream. Low field NMR relaxometry was successfully tested as a tool for accurately measuring the oil and water content of such streams with and without emulsions present in the samples. The method was proved to be at least as good as conventional extraction methods (i.e., Dean-Stark). The technology was tested with both artificially and naturally occurring emulsified streams with accuracy better than 96 percent. This extremely encouraging result lead to the design of an on-line NMR relaxometer for oil/water stream measurements under the conditions encountered in the production of heavy oil and bitumen. Introduction Low Field Nuclear Magnetic Resonance (NMR) relaxometry techniques were developed in the laboratory to enhance and support comparable NMR logging tools that are currently used downhole. Low field NMR relaxometry has shown that discrimination of water and oil saturation in core and ore can be easily determined. In such cases the NMR can detect the total water weight fraction and the total oil weight fraction, the viscosity of the oil, the amount of bound or mobile water and the amount of mobile or bound oil1–6. Since these measurements are done in-situ and the accuracy of the tools is at least as good as that of conventional extraction methods (i.e., Dean-Stark) NMR has emerged as a leading tool for heavy oil and bitumen characterization tool. Our research group proved that many techniques that are routinely used in conventional oil could now be extended in heavy oil and bitumen characterization1–6. This technology is now extended in the determination of oil and water content of specific hydrocarbon streams. Of particular interest are the streams that contain emulsified fluids (water-in-oil or oilin- water emulsions) which are currently very common in thermal production operations and are very difficult to handle. Test separators are currently used as the standard way of measuring the flow of thermally produced wells (CSS, SAGD, steam flooding). The test separators are inherently incapable of measuring emulsified flow. Other probe-type devices suffer from inaccuracies related to the presence of solids or gas, salinity, temperature, velocity, emulsion type, and range of cut. Low field NMR emerges as the only currently proven alternative to discriminate accurately and precisely the amount of oil and water in such streams. METHODOLOGY The NMR spectra of a mixture of heavy oil or bitumen with water consist of two sets of T2 relaxation peaks. The water peaks are at a range of 10-3000 ms, while the oil/bitumen peaks are in the range of 0.2–10 ms at the specific temperature of 30 °C.

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 enseignants0,195
Score d'incertitude au seuil0,995

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 ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0060,000

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 Opus0,010
Tête enseignante GPT0,275
Écart entre enseignants0,264 · 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

Citations6
Publié2000
Routes d'admission1
Résumé présentoui

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