Assessment of the Reliability of Reserves Estimates of Public Companies in the US and Canada
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Notice bibliographique
Résumé
Estimation of reserves is a process used to quantify the volumes of hydrocarbon fluids that can be recovered economically from a reservoir, field, area or region, from a given date forward. A considerable level of uncertainty is involved throughout the reserves-estimation process. Unfortunately, individuals are poor at assessing uncertainty, with a common tendency for overconfidence (underestimation of uncertainty) and optimism. \nThere are a few studies that address the reliability of reserves estimates, but none of them quantify the reliability of these estimates. This research aims to assess quantitatively the reliability of reserves estimates of public companies filing in the U.S. and Canada. To do this I measured biases in reported reserves estimates for 34 companies filing in Canada and 32 companies filing in the U.S. over the time period 2007 to 2017. \nCanadian companies explicitly report technical revisions of proved (1P) and proved-plus-probable (2P) reserves. U.S. companies do not report “technical revisions,” but instead report “revisions of previous estimates” and revisions due to price changes of proved (1P) reserves separately. I calculated Revisions Other Than Price (ROTP) by subtraction for U.S. companies and assumed the difference was the same as “technical revisions.” \nBased on probabilistic reserves definitions, it is reasonable to assume that proved reserves estimates are expected to have positive technical revisions 90% of the time, while proved- plus-probable reserves estimates are expected to have positive revisions 50% of the time. The reliability of proved and proved-plus-probable reserves estimates was assessed using calibration plots, in which the frequency of positive technical revisions is plotted against the estimate probability. Calibration plots can be used to measure confidence bias, ranging from underconfidence to complete overconfidence, and directional bias, ranging from complete pessimism to complete optimism. \n“Technical revisions” reported by 34 Canadian companies for the 11-year period were positive an average of 72% for 1P reserves and an average of 54% for 2P reserves, whereas the expected values were 90% and 50%, respectively. Thus, on average over this time period, filers in Canada overestimated 1P reserves and underestimated 2P reserves. Considering the entire reserves distributions, bias measurements indicate that filers in Canada were moderately overconfident and slightly pessimistic. Revisions Other Than Price (ROTP) calculated for 32 U.S. companies for the 11-year period were positive an average of only 51% for 1P reserves, compared to an expected 90%. Thus, on average over this time period, filers in the U.S. overestimated 1P reserves significantly. Considering the entire reserves distributions, bias measurements indicate that filers in the U.S. were somewhere between complete overconfidence and neutral directional bias, and moderate overconfidence and complete optimism. The biases in reserves estimates filed in both Canada and the U.S. suggest that adjustments in reserves estimation procedures are warranted. \nThree groups of professionals can benefit from this study: (1) estimators, who can use the methodology to track their technical revisions over time, calibrate them, and use this information to adjust future estimation procedures; (2) investors, who can analyze reported reserves estimates to compare volumes fairly; and (3) regulators, who can ensure that filers are complying with appropriate criteria for 1P and 2P reserves.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 découle