Characterization of complex fluvial architecture through outcrop studies – dealing with intrinsic data bias at multiple scales in the pursuit of a representative geomodel
Notice bibliographique
Résumé
Abstract The practice of building analog models and training images from outcrop exposures is an important tool in better predicting subsurface facies distribution in the petroleum industry. As with subsurface data, however, incomplete information and data bias can lead to inaccurate characterization of outcrop geology at multiple scales. Cretaceous fluvial strata of Wyoming offers excellent exposure of two systems — the sand-rich and highly amalgamated Trail Member of the Ericson Sandstone and the sand-poor, isolated channels of the Dry Hollow Member of the Frontier Formation. For each system, multiple outcrops were characterized through the traditional means of stratigraphic column measurement, as well as through photogrammetric survey acquisition and interpretation. We saw in both studies that, despite an effort to measure sections that were representative of the entire outcrop, measured sections consistently overestimated the reservoir proportions. Ten measured sections within the Trail Member show a Net-to-Gross (NTG) ranging from 50–80% sandstone, with an average of 72%. A more complete spatial characterization of the entire outcrop through photogrammetric interpretation suggests a much lower NTG of 53%. Similarly, for the Dry Hollow Member fluvial strata, measured sections show NTG ranges of 8–50% with an average of 37% sandstone, while the photogrammetric model shows a NTG of only 16%. These differences are significant and lead to very different reservoir models. Further, the assumption is commonly made that the outcrop, if well characterized, is representative of the formation at a larger scale. Models of the Dry Hollow Member at Cumberland Gap show that this is a tenuous assumption and can lead to models that are not representative of the system. Outcrops of the Dry Hollow are sparse and often discontinuous, and extrapolation of calculated facies proportions between two well-exposed outcrops at Cumberland Gap led to significant placement of sands between the outcrops, where the lack of exposure leads to a lack of control data in the model. This resulted in increased reservoir connectivity that is not representative of the system, and shows that even on a sub-kilometer scale, the extrapolation of detailed, quantitative facies proportions can be inappropriate, and if done blindly can lead to an inaccurate characterization of the system. Through detailed characterization of the Trail and Dry Hollow fluvial systems, it is shown that building quantitative geomodels from outcrop exposures, even using modern techniques such as photogrammetric analysis, can be subject to significant bias and mischaracterization at multiple scales and for multiple reasons if care is not taken.
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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».