Conventional OTSG Development for Heavy Liquid Fuel Firing in Thermal Applications
Bibliographic record
Abstract
Abstract The large expansion in future Canadian extra heavy oil in situ thermal production (e.g. SAGD) projects will dramatically increase the demand for natural gas, the current predominant fuel used for the associated steam generation. For thermal (SAGD) applications, depending on the Steam Oil Ratio (SOR), approximately 40,000 T/day of steam CWE (Cold Water Equivalent) is injected to produce 100,000 bpd of bitumen, requiring some 100 M SCF/day of natural gas to be fired in Once Through Steam Generators (OTSG's.) Potential natural gas shortages and related price volatility dictate that operators consider alternative fuels for the projected near future growth in Alberta's in situ thermal production. This paper targets the use of bitumen from upstream sites and derivative residues from upgrading activities as the most convenient alternative fuel sources for thermal operators of established ‘horizontal type’ gas fired OTSG's. Past attempts to adapt / convert existing gas fired OTSG's to heavy liquid firing were unsuccessful because the conversions were made in haste, without properly addressing and resolving the many fundamental technical challenges involved. In consequence extensive operating problems and resultant poor reliability caused the trials to be abandoned. Furthermore at that time a cost saving benefit in displacing gas burn against heavy liquid was not consistently evident to support the further investment required. Hence only ‘new design’ OTSG units can be sensibly considered for alternative heavy liquid fuels, also, retaining natural gas as a fuel option gives the Oil & Gas Operator a Multi Fuel OTSG, and some choice in the fuel market place. This paper presents the methodology, the issues associated with bitumen / residue burning and the related technical solutions in development for this Multi Fuel OTSG product - natural gas firing being retained as an option and for start up. The concepts and details of the largest transportable OTSG modules are considered, based on manufacturer TIW Western Inc's (TIWW) established gas fired designs, addressing changes necessary for heavy liquid fuel firing. Combustion, furnace and convection section configurations and materials of construction have been selected for optimal performance / availability, whilst taking due accounts of fouling, cleaning and erosion issues, and both high and low temperature corrosion factors. Recognising that liquid fuel combustion increases CO2 and other emissions over natural gas firing the technical options for mitigation are being addressed in parallel studies.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".