Prediction of Scales in Boilers of Thermal Recovery Projects
Notice bibliographique
Résumé
Abstract The production of silica in thermal petroleum recovery projects is a well known phenomenon, and considerable efforts at its control are a common feature of facilities engineering in such projects. In solutions of high pH, such as boiler feedwater and blowdown, however, the silicates of iron, calcium, magnesium and sodium are of greater interest than silica itself. Scaling by such silicates is usually predictable by means of computer programs that rely on free energy minimizations. Where instabilities for scaling are predicted in this way, often a large range of potential mineral deposits are identified as potential scale deposits. The reality is, however, that only one or two such minerals are ever found in the analysis of pigging solids. A simple method, that permits the prediction by non-chemists of both type and quantity of preferential scales, is derived and its use in SAGD water management and recycling schemes is illustrated. The effect of the presence of chelants in boiler feedwater may not prevent silicate scales, but merely shift the preferred scale. Sample recovery and handling, on the other hand, may cause a shift in scale preference under laboratory conditions, as opposed to facility conditions. Introduction The observation of scaling by metal silicates, rather than amorphous silica, is a phenomenon in SAGD operations that recognized relatively recently. A variety of alkaline earth silicates and mixed silicates have been observed1,2 in various unit operations of SAGD plants, including boiler tubes, production headers, and separation facilities. Analyses of fluid interactions in disposal wells also often predict formation damage due to precipitation of such silicates. The prediction or thermodynamic confirmation of the scales found analytically is usually accomplished by water chemistry software that is based on free energy minimization. The program used in this work is the well known SOLMINEQ program developed by the Alberta Research Council. Silicate Scales in SAGD A number of scales have been observed by various authors in the past few years. Table 1 provides a summary of silicate scale type and references. The most commonly encountered scales appear to be Talc, a magnesium silicate, and Tremolite, a more complex calcium magnesium silicate of the asbestos variety. From time to time, isomorphic substitutions are reported, among them Richterite, where one of the calcium atoms in Tremolite is replaced by sodium atoms. In general it is found that the predictive programs, when run with a given analysis, tend to predict a range of metal silicates. Given that waters in SAGD operations are generally quite soft, only one or two of the scales predicted will be found in practice, however. The purpose of this paper is to provide a simple method of predicting which of the predicted scales will be the preferred one. The importance of this work is the prediction of scale quantity. The predictive programs are able to predict a scaling index, which is not necessarily related to quantity. Demonstration Calculation Suppose we have an example fluid of the composition given in Table 2.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».