Shale lithofacies modeling of the Bakken Formation in the Williston basin, North Dakota
Notice bibliographique
Résumé
The Bakken petroleum system (Devonian-Mississippian) in the Williston basin of North Dakota and Montana in the United States, and Saskatchewan and Manitoba in Canada is one of the largest unconventional oil plays in North America. The Bakken Formation consists of three members: upper, middle, and lower. Both upper and lower members are shale (source rocks), whereas the middle member (reservoir rock) is composed of mixed lithologies, including sandstone, dolostone, and limestone. Underlying the lower Bakken shale member, the Three Forks Formation is another target for hydrocarbon exploration.;Although the middle Bakken member along with the Three Forks Formation have been the targets for horizontal drilling and hydraulic stimulation throughout the basin, several uncertainties remain, including facies variation due to depositional and diagenetic controls on mineral composition and organic matter content in the Bakken shale members, which could play a significant role in hydrocarbon generation and production. Although the Bakken shale members may look homogeneous in the appearance, they are significantly heterogeneous and complex mixture of quartz, smectite, illite, carbonate, pyrite, and kerogen in varying proportions. Improved characterization of the Bakken shale lithofacies is important to better understand depositional environment, lithofacies distribution, and their potential influence on hydrocarbon production.;The main objective of this work is to investigate vertical and lateral heterogeneities of the Bakken shale lithofacies, based on mineralogy and organic matter richness. Secondly, if the Bakken shale members are composed of different lithofacies, can they be associated with different depositional and/or diagenetic conditions, which could influence source, transportation, and preservation of organic matter and sediment in the Williston basin.;Core data (such as X-ray diffraction, X-ray fluorescence, and Total Organic Carbon content), conventional borehole geophysical logs (such as gamma, resistivity, bulk density, neutron porosity, and photo-electric factor), and advanced petrophysical logs (such as Spectral Gamma and Pulsed Neutron Spectroscopy) are used and integrated together to classify the Bakken shale lithofacies and build models of lithofacies distribution at multiple scales. Usually there are minimal core data, scattered advanced well logs, and ubiquitous conventional well log suites in a petroliferous basin, which hinders lithofacies analysis and petrophysical modeling. Therefore, a significant effort of this work is geared towards developing and applying cost-effective mathematical algorithms (such as Support Vector Machine and Artificial Neural Network etc.) and geostatistical techniques (such as Sequential Indicator Simulation) to classify, predict, and interpolate shale lithofacies with high accuracy, using conventional well log-derived petrophysical parameters from several wells.;The results show that
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| 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 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 ».