The Value of Oil, Natural Gas, and By-Product Reserves
Notice bibliographique
Résumé
Abstract The value of oil, natural gas, and by-product reserves varies significantly across the Western Canadian Sedimentary Basin. The differences in composition of crude oil, natural gas, and associated by-products result in differences in the values of the reserves. The variation in the capital and operating costs necessary to develop and maintain production also impacts the values. Contrasting provincial and freehold royalties, compounded by federal and provincial income taxes, further add to the differences. All of these factors must be considered when evaluating reserves -beware of short cuts. This paper summarizes selected evaluations of the values of oil and gas reserves obtained from Sproule Associates Limited's database of its most recent year-end evaluation work. These data are grouped according to province, geological setting, type of reserve, cost of recovery, and operational procedure. The information lends itself to establishing several profitability and benchmarking indices, all of which are presented. These indices should be very valuable to all stakeholders involved in the oil and gas industry. Introduction Every year, particularly during the winter months, engineers and geologists prepare estimates and evaluations of oil and gas reserves. Companies undertake this work internally using their own technical staff and/or externally using independent consulting firms. The evaluations are prepared for all types of entrepreneurs and companies involved in producing oil, gas, and by-products, including mineral owners (freehold, provincial, and federal), oil and gas producers (individual entrepreneurs and minor and major companies), and government agencies (provincial, state, and federal). The evaluations are used for corporate reserves management, acquisition and divestment, equity financing, lending and borrowing, estate settlement, regulatory control, and litigation. The evaluation procedure is universal for establishing the value of upstream oil and gas assets, thus, everyone engaged in oil and gas activities relies on this information. Technical professionals require evaluations for planning and development of oil and gas fields and transportation facilities. Financial officers use them for establishing value and making business decisions. Accountants require them when auditing the financial statements of oil and gas companies. Bankers set their lending value on independent evaluations. Securities Commissions and Stock Exchanges require evaluations to regulate filings in the equity markets. Because of the accelerated business in the oil and gas industry in the past 20 years, the demand for independent evaluation services has increased significantly. As a result, these independents have created large databases of reserve estimates and financial information. This paper presents the results of a study undertaken by several staff members of Sproule Associates Limited to develop unit values of reserves across the Western Canadian Sedimentary Basin using Sproule's database that was created during the 1997 – 1998 evaluation season. In addition to using this information for Sproule's internal uses, this paper makes the data available to the industry. There are many dangers in using this type of financial information, expressed as a unit of reserves basis; but, if the process is understood, it can be very valuable. The advantages and disadvantages of using these data are discussed in this paper.
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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,005 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».