Maturing CCS Technology through Demonstration - Quest: Learning from CCS Implementation In Canada
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".