Experimental Study of High-Pressure Oxy-Fired Direct Contact Steam Generation (HiPrOx-DCSG) with Steam-Assisted Gravity Drainage (SAGD) Produced Water
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Direct contact steam generation (DCSG) produces steam-rich gas by directly contacting combustion gases with sprayed water. This water is typically produced water (i.e., recovered condensate) from a process that has already extracted heat from the steam-rich gas. DCSG enables the reuse of produced water for steam generation without the extensive treatment required by conventional boiler systems, making it suitable for applications where a high steam purity is not essential. Key challenges in DCSG include managing impurities during combustion and matching the flue gas pressure with the elevated downstream process pressure, often necessitating pressurized combustion. This requirement becomes advantageous when integrated with carbon capture and storage (CCS), especially with oxy-fired combustion where flue gas, following H 2 O condensation, yields a pressurized CO 2 -rich stream requiring less energy for downstream capture and compression. This study tested a pilot-scale high-pressure oxy-fired (HiPrOx) DCSG system operating at pressures of 80, 55, and 30 barg and temperatures between 1000 and 1250 °C, using steam-assisted gravity drainage (SAGD) produced water. The system successfully generated a pressurized steam-rich gas containing approximately 90% steam, balanced by CO 2 and trace gases, suitable for CO 2 coinjection into SAGD wells. Oxy-fired combustion effectively removed solids and impurities from the SAGD water; however, burner surface deposition was severe at 80 barg. Deposition was significantly reduced and acceptable at 55 barg and minimal at 30 barg. The results demonstrate the feasibility of HiPrOx-DCSG for utilizing highly contaminated water for steam generation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".