Three-Dimensional Geological Characterization and Modeling of Fine-Grained Petroleum Reservoirs: An Evaluation of the Montney Formation in Westcentral Alberta and Bakken Formation in Southeastern Saskatchewan, Canada
Notice bibliographique
Résumé
In Canada, tight and shale plays such as the Montney, Bakken, and Duvernay (to mention but a few) have over the past decade become the focus of exploration and development activities. However, despite the successes recorded in drilling and completing multi-fractured horizontal wells (MFHws) in Canada and the United States of America (USA), the geological characteristics of shale and tight reservoirs remain poorly understood; evidenced by frequent production and development challenges faced by operators. These challenges include (but are not limited to) rapid well decline rates, parent-child well production interference, and difficulty in reconciling multi-scale geological heterogeneities. The challenge of unconventional reservoir (this terminology is used in this thesis to solely refer to shale and tight reservoirs) development is further compounded when there is a lack of data such as three dimensional (3D) seismic, microseismic, borehole imagery, or well logs suites in MFHw laterals (to mention but a few) to support integrated reservoir studies and dynamic simulation. Given the above, the aim of this dissertation was two-pronged: (1) to develop novel approaches for geologically characterizing tight reservoirs such that the importance of understanding nano to macro-scale heterogeneity is demonstrated through reconciliation with production data or validation using independent complementary datasets (2) to develop geological characterization and modeling techniques that can be used in the absence of traditional geological and geophysical datasets (as earlier mentioned). The Montney Formation in west-central Alberta and the Bakken Formation in southeastern Saskatchewan Canada were used as case studies to demonstrate how commonly acquired datasets such as well logs can be leveraged to improve the geological characterization of tight reservoirs. Seismic data available in the Bakken Formation was used to validate the applicability of a new well log to seismic inversion workflow that was developed and applied in the Montney Formation. New insights on the role of the dominant pore throat size control on fluid distribution and influence on production variation in tight reservoirs are presented. Furthermore, in the Bakken Formation, a natural fracture zone identification technique was developed, along with a new subdivision of the Middle Bakken producing interval into five geomechanical zones based on dynamic elastic properties. The Bakken natural fracture zone identification technique was facilitated by neural network modeling and a newly developed multi-log attribute relation. The natural fracture zones identified were shown to be consistent with independent results from seismic attribute analysis. Finally, this work expands the paradigm of unconventional resource exploitation (which is primarily driven by the intent to increase production) to include the consideration of exploration and development drilling pathways that can potentially reduce the pre-production greenhouse gas emission of MFHws. Where available, core and field data were used for quality-controlling and validating results.
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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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».