Maturing CCS Technology through Demonstration - Quest: Learning from CCS Implementation In Canada
Notice bibliographique
Résumé
Abstract Quest is the world's first commercial-scale CCS project in the oil sands. Quest is an important proof-point for Shell, demonstrating integrated CCS operations as model for advancing and deploying CCS technology and supporting our commitment on action on climate change. Objective CO2 management is becoming increasingly more important in a carbon constrained world and implementation of Carbon Capture and Storage (CCS) adds cost to already cost constrained operations. However, cost reduction through deployment is expected and the First-of-a-Kind (FOAK) projects provide the perfect opportunity to optimize the integration of CCS into oil and gas projects and overcome some of the initial challenges all new processes face. This paper will discuss the approach to CCS projects taken by Shell and share some of the key findings from forthcoming start-up of the FOAK Quest project. Method Shell has developed a global portfolio of CCS demonstration projects driven by the recognition that carbon capture and storage is currently the only technology available to mitigate emissions from large scale fossil fuel use. Shell's projects cover a wide range of technologies and consist of targeted applications that are of relevance to the wider oil and gas industry. The Shell commercial and project portfolio includes Peterhead, Quest, Technology Centre Mongstad and Gorgon commercial scale projects. Shell Cansolv technology is also already in use at SaskPower's Boundary Dam CCS project. These projects have demonstrated that the approach required when implementing a CCS project is similar to that of any major oil and gas project. However, the focus on capturing, and sharing, the learnings is critical to ensuring that follow on projects can benefit from the current portfolio of demonstration projects. Observations The Quest project is the first carbon capture and storage project of a commercial scale in the heavy oil industry. CO2 will be captured from three hydrogen manufacturing units (HMU) of the Shell Scotford Upgrader, a facility that uses hydrogen to upgrade the bitumen from the mines to synthetic crude. The CO2 will be compressed, dehydrated and transported ~64 km for injection into a saline aquifer for storage. The CO2 capture technology, ADIP-X, is a common process within gas processing and LNG. However, the successful integration of the capture plant into the HMU operation is a critical component and a key focus of the knowledge management/sharing initiative implemented for the Quest project. In addition, it is expected that the start-up and operation of the facilities - including the integrally geared CO2 compressor, the CO2 dehydration plant, CO2 pipeline and wells first injection - will provide key learnings that can be implemented in future projects for risk and cost reduction and also unit optimization. In conclusion, First-of-a-Kind projects offer significant opportunities to capture key learnings for future project cost reduction and design optimization. Hence, Shell has implemented a dedicated knowledge capturing and dissemination process for the Quest CCS project, of which some results will be presented here.
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Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,007 | 0,003 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».