Improved Conductivity and Proppant Applications in the Bakken Formation
Notice bibliographique
Résumé
This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 163849, ’Investigation of Improved Conductivity and Proppant Applications in the Bakken Formation,’ by Bethany Kurz, SPE, Energy and Environmental Research Center, Darren Schmidt, SPE, and Phil Cortese, SPE, Weatherford, prepared for the 2013 SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, USA, 4-6 February. The paper has not been peer reviewed. Production from the Bakken and Three Forks formations within the Williston basin is continuing to climb as a result of applied horizontal drilling and hydraulic fracturing. Key to increased oil production is the evolution of reservoir-stimulation techniques, such as fracturing-fluid systems and proppant types. This study evaluated the key factors that may result in conductivity loss within the Bakken and Three Forks reservoirs. The results of this work suggest that certain fluids may affect both rock and proppant strength and, therefore, require consideration. Introduction This work was conducted in an effort to answer questions regarding reservoir stimulation in the Bakken petroleum system, specifically with respect to conductivity loss in hydraulic fractures over time. The key questions that were evaluated include Can conductivity loss be attributed to proppant degradation, rock strength, or both? What role do fluids have in affecting propped-fracture conductivity? To what extent does fluid exposure affect the degradation of rock strength and proppant performance? How do various proppants perform relative to one another under stress using actual core samples from the Bakken petroleum system? Laboratory tests were conducted to evaluate the sensitivity of Bakken and Three Forks formation cores to various fluids; to evaluate the strength of Ottawa sand, an unspecified premium precured resin-coated sand (RCS), and a lightweight ceramic proppant (Econoprop) with respect to various fluids; and to measure the relative laboratory conductivity performance of propped fractures using actual rock core. Fluids used in experiments to examine potential strength degradation for both rock and proppant included the following: Slickwater—a mixture of polyacrylamide and fresh water Crosslinked gel—guar-polymer thickening agent, borate crosslinker, and fresh water Gelled diesel—diesel fuel and phosphate ester Bakken-formation crude—crude oil Bakken-formation brine—highly concentrated saltwater The fluids were selected on the basis of the most common fluids expected to be encountered in the Bakken formation. Embedment Brinell-hardness-index testing is a measure of rock strength that is determined by embedding a metal ball into formation rock at a given applied load. This type of index testing was used to gauge the relative strength of Bakken and Three Forks samples before and after exposure to formation and hydraulic-fracturing fluids. Core samples used to study rock strength originated from the North Dakota Industrial Commission (NDIC) #16771 well, located in the Manitou field of Mountrail County. Rock strength was measured with a Brinell-hardness-test apparatus. Publicly available hardness data were available from two wells in proximity, including NDIC #15986, Robinson Lake field, Mountrail County, approximately 10 miles to the southeast NDIC #16083, Capa field, Williams County, approximately 10 miles to the southwest
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 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 ».