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Enregistrement W2923190916 · doi:10.2118/0419-0027-jpt

To Solve Frac Hits, Unconventional Engineering Must Revolve Around Them

2019· article· en· W2923190916 sur OpenAlex

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Notice bibliographique

RevueJournal of Petroleum Technology · 2019
Typearticle
Langueen
DomaineEngineering
ThématiqueHydraulic Fracturing and Reservoir Analysis
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésOil shaleHydraulic fracturingDrillingEngineeringSession (web analytics)Order (exchange)BusinessMining engineeringGeologyPetroleum engineeringFinanceAdvertisingMechanical engineering

Résumé

récupéré en direct d'OpenAlex

Hydraulic fracturing as it is now executed in North American shale plays may have to be replaced with a much more intricate scheme—one that better matches the complex fabric of tight reservoirs. The impetus for an engineering overhaul is being forced by the prevalent well-to-well fracture interactions known as frac hits. These events are the subject of intensifying study by US and Canadian shale producers that have attributed them to lowering oil recovery factors from new child wells by 20–40% while inflicting even higher losses on older, yet less productive, parent wells. How the industry manages the impact of frac hits going forward is likely to define its future growth rate. “They’re not going away—we’re only going to be drilling more and more child wells,” said Brendan Elliot, a senior completions engineer with Devon Energy, as he advised a large gathering of petrotechnical colleagues that they need to “quantify the risk” of frac hits as early as possible in order to know what to do next. Elliot provided a rare look into how a large shale operator is dealing with the problem during the opening session of SPE’s Hydraulic Fracturing Technology Conference (HFTC) held recently in The Woodlands, Texas. His outline highlighted the extent to which the Oklahoma City-based producer is revolving its infill development programs around frac hits. “The things you really want to look at are where the positive and negative events are occurring,” he explained while showing an analysis program that Devon has spent the past couple of years building to visualize those outcomes. The tool, which analyzes data from more than 2,000 frac hit events, has led the company to realize that what determines whether a frac hit will benefit or hurt production comes down to time and production volumes. While this relationship was not a new learning, Devon has quantified it to 10 months and 100,000 bbl. Once both limits have been surpassed, the expectation is that frac hits will have negative consequences on pad production. Elliot elaborated on how this trend is acted upon using the company’s three-pronged approach. Its component pieces include the design of infill wells, addressing reservoir depletion through pressure management (e.g., repressurizing tactics), and then zooming out to adjust the wider field development program. The sum of these parts is a new playbook for unconventional completions, one that stands in stark contrast to the “cookie cutter” designs that gave rise to the shale revolution. Its methodical approach to decision making is aimed at gaining control over fracture growth and maximizing production from child wells. This can be done by adjusting fluid rates in a single well scenario, or altering an entire field development plan based on the risk that frac hits pose. In just a few slides, Elliot succinctly linked together years of accumulated knowledge into a workflow that could feasibly be replicated by other companies struggling with the sector’s most pressing reservoir management issue. “These full-life cycle workflows—don’t get me wrong—these will be lengthy processes, and large projects, so we need to improve as an industry,” cautioned Elliot. “Every mitigation strategy has a risk, it’s going to be specific to each reservoir, it’s going to be variable in the black oil window and your volatile gas window, and you really must cater to the asset value and the value to protect [the resource] in place.”

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Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,653
Score d'incertitude au seuil0,660

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,005
Tête enseignante GPT0,194
Écart entre enseignants0,189 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle