Use of a Numerical Petroleum Reservoir Simulator to Model Aspects of Environmental Contamination and Remediation Processes
Notice bibliographique
Résumé
Abstract The use of numerical simulation to assess the productive response of petroleum reservoirs under various development operations is a powerful and valuable tool for the economic exploitation of oil and gas bearing reservoirs. The computational power and software coding has advanced to such a level that nowadays, that it is imprudent to develop most petroleum reservoirs without some use of numerical simulation to examine the optimality of various development opportunities. In this paper, we examine the application of numerical simulation, using Eclipse-100(1), to model the processes of contamination of soil by a light hydrocarbon, and also the subsequent remediation of the contamination using water and air displacement. Some insight into what sort of data acquisition program is required to model the likely contaminant plume is provided. A better understanding of the process of contamination under various geologic scenarios, and how the remediation operation must be tailored to the situation, is demonstrated. Last, some thoughts on extending such numerical simulation models to better suit some of the key mechanisms of remediation are listed. Introduction Fiscal Justification In our modern world, one of the consequences of industrial development is an impact on our surrounding environment. Such an impact is pollution and contaminant release of some form. Consider only the production, refining, and distribution of gasoline and kerosene fuel products. Pollution occurs at the well head, or even in the well bore as the fluid is produced from the petroleum reservoir. And as the crude is transported from the well head, to the processing facility, to the refinery tank farm, through the distillation and refining equipment, and on to the service station for distribution to the consumer, pollution is always a possibility. If the refined product at the service station is stored in a carbon steel underground storage tank ("UST") that has corroded and therefore is leaking, a large volume of fluid can be released over time. Indeed, before 1982, the underground storage tanks were not even designed with anticorrosion methods(2). So decades of exposure can result is very large release volumes. The hydrocarbon spill would migrate down into the soil. It could then spread out, and impact a large area, and impinge on the other surrounding infrastructures, such as housing or school buildings. It is estimated(2) that in the United States alone, there are over 1.6 million underground storage tanks in use or retired from use. It is further estimated that about 20% of these are releasing (or have released) some of their contents into the soil. The clean up cost for an individual site can range from $10 thousand to $125 thousand (in terms of 1994 U.S. dollars). It is more likely that the cost will be on the high end of the estimate as more complex sites are treated, and as regulatory constraints become more stringent. An average cost can be derived from a detailed probability distribution.
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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) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».