Notice bibliographique
Résumé
Technology Update Microbial growth in oil and gas systems can cause numerous problems that result in production downtime, lost revenue, and safety concerns. Unfortunately, microbial populations are ubiquitous in many oil and gas production zones and minimizing their impact is challenging. The most common effects of microbial growth are corrosion, hydrogen sulfide (H2S) production, and biofouling. The ability to minimize the negative impact of microbes is confounded by the current field monitoring technology, which is unable to detect many of the organisms. These monitoring technologies are culture-based, meaning that organisms must be grown in culture to be detected and quantified. It is well documented in many systems that less than 1% of the total organisms present are culturable. In addition, the culture-based methods commonly take days or weeks to produce a result. Thus, operators must wait a considerable time before taking control measures, and the impact of microbial populations can increase during the long period of undetection. New Development in Monitoring Method Two essential parameters for any new field monitoring technology are the ability to obtain a result in real time and the ability to detect all organisms, not just the ones that can be grown in culture. The industry has evaluated several of these technologies over the years, including a first-generation adenosine triphosphate (ATP) assay in which the level of ATP is used to measure the number of actively growing microbes in a sample. ATP is the molecule used by cells to drive any process that requires energy. This includes metabolism, protein translation, DNA repair, and cell division. Although there are differences in the absolute quantity of ATP in different species or organisms, it is assumed that actively growing bacterial cells hold relatively similar amounts of ATP, and a calculation has been determined to quantify microbial cell numbers based on a measurement of ATP. The major challenge of using this technology in oilfield systems is that the enzymatic assay used to quantify ATP is very sensitive to the quality of the fluids tested. This means that many oilfield fluids such as oil, emulsions, produced water with significant solids, high-salinity fluids, and fluids contaminated with certain chemicals would not yield meaningful results. As an example, the first-generation ATP test was not generally accepted by oilfield operators and has been little used. However, a second-generation ATP test that addresses the concerns has been developed recently. Specifically, additional steps were developed to enable accurate testing of fluids that contain oil, high salinity, residual chemicals, and solids. This technology also meets the other necessary criteria—real-time results and detection of all microbes, not only those that grow in culture.
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,003 |
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 ».