Liquid Addition to Steam for Enhancing Recovery (LASER) of Bitumen with CSS: Evolution of Technology from Research Concept to a Field Pilot at Cold Lake
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Bibliographic record
Abstract
Abstract This paper describes the process of injecting a liquid (C5+) hydrocarbon as a steam additive in a CSS mode of operations. The process has been termed LASER, for "Liquid Addition to Steam for Enhancing Recovery". The process concept was first tested in a 3D physical model apparatus using Cold Lake bitumen. A sustained uplift in bitumen production was observed in later CSS cycles when compared to other tests conducted without liquid addition. Based on numerical simulations, these effects can be attributed to additional viscosity reduction of heated bitumen when contacted with solvent. For bitumen-diluent mixtures, Shuh’s method of viscosity prediction of bitumen with liquid hydrocarbons is adequate to make realistic viscosity predictions based on actual measurements. Field-scale simulations were used to support LASER performance trends from the physical model and establish the optimal timing for applying the technology in the field. The key recovery performance indicators for LASER technology are (1) bitumen uplift over continued CSS performance and (2) fractional recovery of the injected diluent. A field pilot has been designed based on expectations of (1) an improvement of 33% in the cycle Oil-Steam Ratio (OSR) and (2) diluent recovery of 66% using 6% v/v of diluent injection with steam. The pilot location was chosen based on various factors, including improved characterization of historical performance within and around the pilot location. This was achieved by developing a novel multivariate analysis technique to correlate current OSR field performance and reduce associated background noise. An extensive monitoring program has been developed for the pilot. This program is critical for developing a reliable characterization of the diluent recovery. Diluent injection began in April 2002, and the pilot is expected to last approximately 2 years, corresponding to the average length of CSS cycle 7 at Cold Lake.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it