Pilot Program in Mexico Classifies Oil and Gas Projects Using UN Framework
Notice bibliographique
Résumé
This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 196566, “Mexico Pilot Project To Classify Oil and Gas Projects Using United Nations Framework Classification,” by Satinder Purewal, SPE, Imperial College, and Fidel Juárez Toquero, SPE, and Eduardo Simón Burgos, National Hydrocarbons Commission of Mexico, et al., prepared for the 2019 SPE Annual Technical Conference and Exhibition, Calgary, 30 September-2 October. The paper has not been peer reviewed. A pilot project was initiated to classify oil and gas projects in Mexico using the United Nations Framework Classification (UNFC). The UNFC assists in identifying key social and environmental factors that could impede the movement of oil and gas volumes higher up the value chain. To the authors’ knowledge, this is a unique project with significant value-adding outcomes that can be replicated in other countries. Mexico’s Perspective For proper assessment of discovered and undiscovered hydrocarbon volumes, Mexico adopted the Petroleum Resources Management System (PRMS) as its official classification framework. The country features a wide spectrum of cultures, indigenous identities, and social organizations, and in some cases, industry activities could represent a threat to these aspects of Mexican life. As an effect of the nation’s geographical location, a diversity of ecosystems exists, from deserts to regions rich in flora and fauna such as rainforests and wetlands. This reality emphasizes the need for robust legislation guaranteeing the protection of the environment. UNFC The UNFC is a system for classifying resources including petroleum, minerals, and renewables. Quantities are classified on the basis of a 3D, three-axis system (Fig. 1). Each axis assesses different factors on the basis of three fundamental criteria: economic and social viability (E), field project status and feasibility (F), and geological knowledge (G), using a numerical coding system. Categories and subcategories of each axis are the building blocks of the system and are combined in the form of classes. A class is defined by a combination of categories or subcategories sourced from each of the three criteria. A classification made according to the UNFC will be expressed with a three-digit code providing the location of the project in the 3D system, starting with the E, then the F, and finally the G axis. Additionally, the three-digit code can be expressed in terms of categories (E1, F1, G1) which will be read as classes, as well as in terms of subcategories that are read as subclasses. The three-digit code provides information on the maturity status of a project. When category level is used, projects can be classified as Commercial, Potentially Commercial, Noncommercial, Exploration, and Additional Quantities in Place associated with known and potential deposits. When the subcategory level is used, projects can be subclassified. The relationship between the PRMS and the UNFC can be explained better in terms of the linkage between the evaluation processes of the range of uncertainty and chance of commerciality in both systems. The PRMS categorizes the volumes to size the range of uncertainty present in the estimates, while the UNFC does the same through G-axis evaluation.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».