Notice bibliographique
Résumé
This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 173713, “Corrosion and Scale Formation in High-Temperature Sour- Gas Wells: Chemistry and Field Practice,” by Sunder Ramachandran, SPE, Aramco Service Company, and Ghaithan Al-Muntasheri, SPE, Jairo Leal, SPE, and Qiwei Wang, SPE, Saudi Aramco, prepared for the 2015 SPE International Symposium on Oilfield Chemistry, The Woodlands, Texas, USA, 13–15 April. The paper has not been peer reviewed. Sour gas is being produced from a number of carbon-steel-completed wells in the US, Canada, France, and Saudi Arabia. The gas stream contains various levels of hydrogen sulfide and carbon dioxide (CO2) and is produced from high-temperature reservoirs with temperatures ranging from 160 to 410°F. The combination of hydrogen sulfide with high temperatures introduces challenges related to corrosion and iron sulfide (FeS) scale formation. FeS Scales FeS is found naturally in different forms. The gas-production systems studied in this paper have large concentrations of hydrogen sulfide, so iron is a limiting reactant in these systems. FeS formation is favored thermodynamically. In anoxic conditions, the solubility of the ferrous ion is aided by the formation of aqueous iron sulfide complexes. As FeS scales sulfidize, they become increasingly difficult to dissolve with acid. Source of Iron. Iron can come from reservoir rock, drilling fluids, and corrosion during acidization and production. Many reservoir rocks contain small amounts of iron. Contamination and corrosion during the drilling process also could lead to high iron content in drilling fluids. Acidization has been considered to be a primary source of reprecipitated FeS. FeS scale has been found in well tubulars following acid treatments of deep sour-gas wells. Sour Corrosion The corrosion of iron tubulars forms one source for iron scale. General corrosion rates of mild steel in sour systems are less when compared with sweet corrosion. FeS scales are less dense than iron, so sour corrosion is associated often with FeS deposits three to five times thicker than the corroded iron. Corrosion monitoring is important in operating a sourgas production facility. Corrosion inhibition has been used by different producers to prevent sour corrosion and the associated buildup of FeS scale. Corrosion Monitoring. It is essential to monitor corrosion and scale formation. This is often assisted by measuring various operational parameters that can give insight into the scaling condition of a gas well. Corrosion coupons are weighed samples of metal representative of the metallurgy of the well or pipe that are introduced into the process and later removed, cleaned of all corrosion products, and weighed. Electrical-resistance probes measure the electrical resistance of a wire made of material similar to the metallurgy of the well or pipe that is placed in a well or pipe. As the wire corrodes, its electrical resistance increases, allowing one to measure the general corrosion of the wire, which should be similar to that of the pipe or well.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».