Stimulation Influence on Production in the Haynesville Shale: A Playwide Examination
Notice bibliographique
Résumé
This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 148940, ’Stimulation Influence on Production in the Haynesville Shale: A Playwide Examination of Fracture-Treatment Variables That Affect Production,’ by Neil Modeland, SPE, Dan Buller, and King Kwee Chong, SPE, Halliburton, prepared for the 2011 Canadian Unconventional Resources Conference, Calgary, 15-17 November. The paper has not been peer reviewed. In most developing shale plays, there is a learning curve for determining which factors affect well production positively and are economical. Evaluating the reservoir on a playwide basis can expedite the ability to determine the optimal treatment method. By use of public production data with a database of stimulation treatments for several hundred wells in the Haynesville shale, variables such as pumping rate, volumes, proppant (type and volume), fracture-stage designs, base fluid, and surfactant use can be analyzed to determine which ones produce a positive effect on well production. Introduction The Haynesville-shale formation of eastern Texas and northern Louisiana is no exception to this learning-curve development process. By combining a database of completion variables from 359 wells completed after 1 January 2009 with public production data, a multioperator playwide sample was obtained to study variations in completion strategy and consequent effects on production. This study investigated only wells that were completed through 1 October 2010, and the well-sample subset constitutes approximately one-fourth of the Haynesville-shale horizontal wells completed during this time interval. Assumptions When associating only completion techniques to the actual production, several assumptions were made that will not always hold true. Though all of the wells in the analysis are Haynesville-shale producing laterals, underlying inequalities are introduced by several differentiators. Wellbore placement, lateral length, and overall well construction differ from well to well. The flowback methodology remains a potential influence on overall production that is not constant across the Haynesville-shale play. Several operators have suggested that flowing back wells less aggressively has increased the estimated ultimate recoveries. Also, when working with monthly production data from a public-domain source, excessive shut-ins of the wells might not be distinguishable in the data set and could portray wells as being lower quality than they really are. Therefore, certain apparent trends could be prone to masking when variations in well construction and flowback parameters are disregarded for this analysis. Production normalization was required in some instances to account for variations such as number of stages or perforation clusters to adequately single out a certain completion variable as the variable of focus.
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Prédiction distillée sur la base complète
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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 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 | 0,000 | 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».