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Enregistrement W2063778491 · doi:10.2523/iptc-13346-ms

Staged design of an EOR pilot

2009· article· en· W2063778491 sur OpenAlex
Bhargaw Adibhatla, Robert Chick Wattenbarger

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Notice bibliographique

RevueInternational Petroleum Technology Conference · 2009
Typearticle
Langueen
DomaineEngineering
ThématiqueReservoir Engineering and Simulation Methods
Établissements canadiensnon disponible
Organismes subventionnairesExxon Mobil Corporation
Mots-clésProcess (computing)Computer scienceScheduleEnhanced oil recoveryLead (geology)Risk analysis (engineering)Systems engineeringPilot plantEngineeringPetroleum engineering

Résumé

récupéré en direct d'OpenAlex

Abstract Due to the complexity and uncertainty associated with most enhanced oil recovery (EOR) processes, a small-scale pilot is often needed to demonstrate the successful application of an EOR process within a specific reservoir prior to wider commercial implementation. To help manage the complexity and competing cost, schedule, and technical priorities of a pilot, a systematic approach to planning and designing a pilot has been developed. The approach, which is described in this paper, covers various subsurface activities necessary for design of an EOR pilot. Issues related to facilities and other aspects critical to pilot success are also addressed, but in less detail. The sequence of these activities is described and managed in defined stages. The relationship between various activities within a given stage is described using an activity matrix. The activity matrix has proven to be a useful tool for planning and prioritizing various pilot activities. Examples of specific items in the staged approach to EOR pilot design are provided. Introduction A well-designed pilot can be a key element in the successful commercial application of an EOR process. A poorly designed pilot can be costly and lead to an incorrect commercial decision, long delays, or a failed implementation. To help manage the complexity and challenges associated with EOR pilots, guidelines were developed that describe various recommended activities for pilot design. The guidelines, which are summarized in this paper, are designed to be fairly broad and describe recommended activities that are applicable to most EOR pilots (e.g., thermal, gas, chemical). As such, the guidelines serve as a starting point for project-specific guidelines that should be customized for the specific process, field, and pilot business needs. The staged process for pilot design reflects experiences from ExxonMobil's own studies and applications of EOR pilots as well as the published experiences of others. ExxonMobil has piloted several EOR processes throughout the last 40 years. Some examples include chemical processes at the Loudon field1–7 in the United States, the Pembina field8 in Canada, the West Yellow Creek field9 in the United States, steamflood and LASER applications10–12, steam-foam applications13–14, CO2 flooding at the Means field in the United States15, Solid Stabilized Emulsions (SSE)16 in Canada, piloting of miscible gas injection at Judy Creek17–18 in Canada, and others19–21. The material presented in this paper builds upon the lessons learned from these pilots. This paper is not intended to describe the overall process for evaluating and implementing an EOR process, nor is it meant to summarize best practices for EOR pilots. These are described elsewhere22–23. Rather, the approach to pilot design described in this paper is meant to serve as an overall guide to planning and properly sequencing the activities associated with EOR pilot design. These activities include the cross-functional interaction between reservoir engineers, facilities engineers, surveillance engineers, geoscientists, and other disciplines expected in any field development activity. As much as possible, the guidelines focus on the activities that are specific to EOR pilots, leveraging as much as possible existing project management procedures and best practices. EOR Staged Evaluation and Development Process Pilot design and implementation is part of a broader workflow for evaluating and implementing an EOR process for a particular field. The overall process, which has been described in earlier publications22–23, is briefly summarized in the next section. An overview of a staged process to evaluate and implement EOR processes for a specific field is shown in Figure 1.22 EOR evaluation starts with initial data collection, identification of potential EOR recovery processes, and screening economics. After initial screening, promising EOR processes are evaluated in greater detail through laboratory experiments and detailed modeling studies. If the results of the in-depth analysis indicate economic benefit, a field pilot may be performed to address key uncertainties. The decision to pilot, requirements of a successful pilot, types of field pilots, and other piloting best practices have been described elsewhere22. If the pilot is successful and the EOR process remains economically attractive, then the pilot is followed by commercial application of the EOR process on a wider scale.

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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: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,453
Score d'incertitude au seuil0,499

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,032
Tête enseignante GPT0,285
Écart entre enseignants0,254 · 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