Integration of Microseismic and Other Post-Fracture Surveillance With Production Analysis: A Tight Gas Study
Notice bibliographique
Résumé
This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 131786, ’Integration of Microseismic and Other Post-Fracture Surveillance With Production Analysis: A Tight Gas Study,’ by C.R. Clarkson, SPE, University of Calgary, and J.J. Beierle, SPE, Talisman Energy, prepared for the 2010 SPE Unconventional Gas Conference, Pittsburgh, Pennsylvania, 23-25 February. The paper has not been peer reviewed. Quantitative production analysis of tight gas reservoirs is a challenge because of complex reservoir characteristics, induced-hydraulic-fracture properties in vertical wells, operational complexities, and data quality. These challenges make extracting reservoir and hydraulic-fracture properties (i.e., fracture half-length, xf, and fracture conductivity) solely from production and flowing-pressure data difficult, often resulting in nonunique answers. Many tight gas reservoirs are exploited with horizontal wells, often stimulated with multiple hydraulic fractures, imparting greater complexity to the analysis. Flow-regime identification, which is critical to correct analysis, becomes more complicated because of the variety of flow regimes that could be encountered in such wells. Introduction Development of tight gas, shale gas, and coalbed methane (collectively referred to as unconventional gas reservoirs) benefits from advances in drilling, completions, and stimulation technology; formation evaluation; and during-/post-stimulation-surveillance technology. Formation-evaluation techniques enable determining critical parameters such as matrix permeability in ultratight rock from cores, and adsorbed- and free-gas content in shale and coalbed methane from cores and cuttings. During-/post-fracture-stimulation-surveillance technology (such as microseismic monitoring) aids identifying the hydraulic-fracture geometry created in unconventional reservoirs (hydraulic-fracture growth), particularly in coals and shales. Predicting hydraulic-fracture geometries is complicated by heterogeneities, such as natural fractures (healed or open) and layering (with associated contrasts in mechanical properties), and in some cases, by nonlinear elastic behavior. Advanced production-analysis techniques, such as production type curves, supplement reservoir and stimulation information obtained from pressure-transient analysis (well testing) in conventional oil and gas reservoirs and even some unconventional reservoirs such as coalbed methane and tight gas. However, applying these methods to tight gas and shale reservoirs that are produced through multifractured horizontal wells has been difficult because of the complexity of the system, poor quality of flowing-pressure and rate data, and the lack of sufficient data to characterize the system fully. Even if the production and flowing-pressure data were of sufficient quality to identify flow regimes, as in pressure-transient analysis, without additional surveillance information, it is difficult to ascertain how the flow regimes relate to the reservoir and hydraulic-fracture system. If the flow regimes are misinterpreted, then the extracted information will be incorrect. A workflow is proposed to improve the quality of information extracted from production-data analysis (PDA) of hydraulically fractured horizontal wells completed in tight gas reservoirs.
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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
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