Statistics of petroleum exploration in the world outside the United States and Canada through 2015
Notice bibliographique
Résumé
First posted June 17, 2019 For additional information, contact: Director, Eastern Energy Resources Science CenterU.S. Geological SurveyMail Stop 95612201 Sunrise Valley DriveReston, VA 20192 The world’s future oil and gas supplies depend on existing reserves and the additions to those reserves that may result, in part, from ongoing exploration and new discoveries. This Circular summarizes available oil and gas exploration data for the world outside the United States and Canada (the study area) through 2015. It updates U.S. Geological Survey Circulars 981, 1096, and 1288 (by D.H. Root, E.D. Attanasi, and R.L. Turner, 1987; E.D. Attanasi and D.H. Root, 1993; and E.D. Attanasi, P.A. Freeman, and J.A. Glovier, 2007). The exploration measures focus on the search for undiscovered conventional oil and gas accumulations.The goal of this compilation, presentation, and analysis of exploration and discovery data is to identify, at the reconnaissance level, the areas explored for oil and gas and to characterize their degree of exploration maturity. Maps and graphs provide a visual summary of the exploration maturity of an area. The maps include both land and offshore areas. The maps show delineated prospective areas, which are the industry-defined areas of interest in the search for undiscovered conventional oil and gas accumulations. The maps also show explored areas, which are areas where the density of exploration and development drilling rules out new discoveries of large conventional petroleum accumulations.Whereas the maps show the static state of oil and gas exploration, the dynamic measures of exploration progress are characterized graphically. The graphs show the growth in the delineated prospective and explored areas as a function of wildcat drilling. The relation between the expansion of the delineated prospective area and the rate of wildcat drilling is determined by the siting of the wildcat wells. Additional graphs show the magnitude of discoveries tied to specific delineated prospective areas. These graphs provide a way to evaluate the quality, in terms of discovered oil and gas, of areas identified by the dates when each area became prospective.From 2006 through 2015, the delineated prospective area within the study area expanded at a rate of about 48,100 square miles per year. This is slightly above the expansion rate of 46,200 square miles per year from 1996 through 2005. From 2006 through 2015, the explored area expanded at a rate of about 12,900 square miles per year, which is somewhat greater than the rate of 11,300 square miles per year for the period from 1996 through 2005. The delineated prospective area established by 1970 accounts for 35 percent of the delineated prospective area established through 2015 but contains 70 percent of the oil and 52 percent of the natural gas discovered through 2015. From 2006 through 2015, offshore discoveries accounted for 71 percent of the oil and 78 percent of the gas discovered in the study area and 40 percent of the offshore wildcat wells were drilled in deep offshore areas (deeper than 200 meters water depth).The delineated prospective area and explored area calculated with oil and gas wells and fields at depths of at least 10,000 feet are less than half of the respective areas calculated with all oil and gas wells and fields. The discovery histories of most regions indicate that average discovery sizes are generally larger in deeper geologic horizons. To correctly interpret the exploration maturity of a deep horizon, drilling and discovery data must be considered in the context of the geology of the area. Such analyses should be prepared at the level of the petroleum basin or subbasin.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 tête enseignante, 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 ».