Case Study: Production Data and Pressure Transient Analysis of Horseshoe Canyon CBM Wells
Notice bibliographique
Résumé
Abstract The Horseshoe Canyon (HSC) CBM play of the Western Canadian Sedimentary Basin is unique to low-rank coal reservoirs because of lack of water production; the production characteristics are qualitatively similar to conventional low-pressure dry gas reservoirs. However, the complex geologic history of the coals and non-coal interbeds has imparted strong vertical and lateral heterogeneities that make the play difficult to characterize using conventional methods. For example, in a typical HSC well, there are often > 10 seams to complete, which may exhibit strong contrasts in initial pressure, gas content, thickness and permeability. Further, the lateral continuities of the individual seams vary, and are often not correlatable from well-to-well. Recently, advances in production data analysis (PDA) methodologies have been made for CBM wells; techniques developed for tight gas, and conventional oil and gas reservoirs have been adapted by incorporating some CBM reservoir properties. For example, the popular flowing material balance (FMB) technique, as well as production type-curve and pressure transient analysis (PTA) have been modified to include relatively simple CBM reservoir behavior (ex. equilibrium desorption). These methods, however, are primarily restricted to the analysis of single-layer reservoirs; significant errors in estimates of original-gas-in-place (OGIP) and other reservoir properties may occur if strong contrasts exist from layer-to-layer. In this work, multi-layer analysis tools are discussed, including analytical simulators that are used to history-match layer-allocated rates and pressures, and layer-specific FMB, which is used as a PDA method for individual layers. A study was undertaken to establish the applicability of advanced PDA methods to the quantitative assessment of HSC reserves. Single-layer and multi-layer analysis tools were first tested against artificial data created with a numerical simulator. Next, single-layer-equivalent analysis was performed on > 40 real wells using type-curve, FMB, and analytical simulation. Many of the wells exhibit an early "cleanup" period with inclining or flat production, precluding analysis of transient flow data. Finally, a more rigorous multi-layer analysis was performed on a subset of wells where spinner surveys, and individual-seam pressure buildup data, collected at several points in time during the producing life of the well, were available. Analysis of this subset of wells included PTA of the individual seams, individual seam material balance, and multi-layer (up to 6) analytical simulation history-matching of total commingled flow rates, individual coal zone rates estimated from spinner surveys, and shut-in pressures. The resulting reservoir property estimates (ex. total OGIP) were then compared to the single-layer-equivalent analysis; the single-layer-equivalent analysis appears to yield conservative estimates of OGIP. Future work will include continued comparisons of multi-layer vs. single-layer PDA, development of new PDA methods for analyzing multi-layer reservoirs, investigation of additional constraints on permeability and other reservoir properties that can be used in multi-layer history-matching process, and time-lapse PTA work to quantify changes in layer permeability and skin during depletion.
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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.
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| 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 | 0,000 |
| 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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