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Enregistrement W2295731246 · doi:10.14288/1.0100048

The economics of industry petroleum exploration

2010· article· en· W2295731246 sur OpenAlexaboutno aff
Peter Cheston Eglington

Notice bibliographique

RevuecIRcle (University of British Columbia) · 2010
Typearticle
Langueen
DomaineEngineering
ThématiqueReservoir Engineering and Simulation Methods
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPetroleum industryPetroleum explorationPetroleumNatural resource economicsEconomicsBusinessGeology

Résumé

récupéré en direct d'OpenAlex

This thesis examines various features of the market for petroleum reserves, in theory and empirically for the time period 1947-1970 in Alberta, Canada. The main thrust of analysis is directed towards the industry supply process in the reserves market which results from the activities of exploration companies. In particular the thesis focusses attention on the activity of New Field Wildcatting. A totally new data bank regarding oil and gas exploration in Alberta is established, containing many items of information which have net previously been available and whose lack was considered a major stumbling block in analysing the petroleum exploration process. For example, the data files show the direction of search of exploratory wells, towards either oil or gas, the class of well which discovered each petroleum pool, the company which was the principal operator of the discovery well, the cost of wells, etc. Thus, it was possible to analyse the discovery sequence from well class, etc. to the discovered pool and its detailed reserves characteristics. With this data bank an original and unique approach amongst studies of oil and gas supply and exploration was possible. The study isolates the geological and economic factors which contribute to the incentives and costs of participants in the market for reserves. It should be noted that the data bank, on computer tape and described in a 130 page manual, can be obtained upon request from the author. The hitherto unavailable detail of this data invites further analysis. On the demand side of the reserves market, data was generated which allowed a detailed estimation of the price incentive to explore for reserves. This included consideration of production delays, expected well productivities, royalties, operating costs, joint products, income taxes, etc. It is established that New Field Wildcat wells may be viewed as the primary discovery activity of the petroleum reserves market. A main objective of the thesis is to define the components of the economic market for reserves so that empirical tests may be conducted to demonstrate the economic linkages between the incentives to explore for oil and gas and the rates of wildcat drilling and subsequent reserves discovered. This objective is met by providing an extensive descriptive and statistical backdrop of the oil and natural gas industry in Alberta, developing theoretical economic models of petroleum exploration and production, and then fitting econometric equations to estimate the elasticity and shifting of the industry' s short run petroleum reserves supply function. It is shown that the short run elasticity between the reserves price incentive to explore and New Field Wildcatting for oil averaged between 0.3 and 0.4 during the period in Alberta. The comparable elasticity for natural gas was around 0.1. We stress, however, that these elasticities may be rather unimportant out of their context of a shifting supply function. They do not remain constant as a region is depleted and the rate at which the supply function shifts as a region is explored will be more significant in determining the longer run petroleum supply than the short run elasticity. Such shifting of the supply function is also estimated. Secondary objectives are to examine the exploration characteristics of large companies compared to the others. Statistical analysis shows that the "Big Eight" companies have realized higher success ratios in New Field Wildcatting, have discovered much larger oil and gas pools and have done considerably more geophysics on their land holdings than other companies. Many other features of the petroleum discovery process, such as the statistical nature of the populations of pools discovered in sequential time periods, are also examined.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,705
Score d'incertitude au seuil0,990

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,010
Tête enseignante GPT0,181
Écart entre enseignants0,171 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations5
Publié2010
Routes d'admission1
Résumé présentoui

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