Laboratory Experimental Testing and Development of an Efficient Low Pressure ES-SAGD Process
Bibliographic record
Abstract
Abstract Certain Athabasca reservoirs have low pressures because they have been depleted due to production of overlying gas. Other reservoirs are naturally occurring low pressure shallow bitumen reservoirs. Hence, there is a need to develop or investigate recovery processes under which such low pressure reservoirs can be developed. As a result of this, experiments were initiated to extend the Expanding Solvent-SAGD (ES-SAGD) process application to low pressure Athabasca reservoirs in order to evaluate oil recovery from such reservoirs. The goal of these experiments is to develop a low pressure ES-SAGD process with better performance than, or comparable performance to, that of the high pressure SAGD process. This paper describes five sets of laboratory experiments examining recovery processes, which includes a low pressure (500 kPag +/- 50 kPag) SAGD experiment, a propane-SAGD experiment, multi-component ES-SAGD (at low and high concentrations) experiments and a high pressure (2,100 kPag +/- 50 kPag) SAGD experiment. The results of these experiments are presented and analyzed in order to evaluate the performance of low pressure ES-SAGD in comparison to SAGD (at low and high pressure) and propane-SAGD at low pressure. The processes were assessed for recovery, recovery time, heat loss, steam chamber growth and energy efficiency. The principal conclusion is that the low pressure multi-component ES-SAGD at the right concentration (mostly at low concentration) is fairly competitive with SAGD at a high pressure. The energy consumption in the steam or steam/solvent zone per oil recovered (ECDZ) for low pressure multi-component ES-SAGD experiments is much lower than the low pressure and high pressure SAGD tests. The propane-SAGD test recovery is very low, even at higher energy consumption, than that of the ES-SAGD experiment at low concentration. The work presented in this paper shows that the application of a multi-component ES-SAGD process in the field at low pressure is a practical option. It also shows that bitumen/heavy oil reservoirs that would have remained untapped due to low reservoir pressure could be produced at lower energy consumption per oil recovered if a low pressure ES-SAGD process at low concentration of the diluents is employed in the recovery of the oil. Introduction Certain Athabasca reservoirs have low pressures because they have been depleted due to production of overlying gas. Other reservoirs are naturally occurring low pressure shallow bitumen reservoirs. The application of Expanding Solvent-SAGD (ES-SAGD)(1–2) to these low pressure reservoirs has been a major area of attention at the Alberta Research Council (ARC) in recent years. As a result of this, experiments were initiated to extend the ES-SAGD application to low pressure Athabasca reservoirs. The goal is to develop a low pressure ES-SAGD process with better performance than, or comparable performance to, that of the high pressure SAGD process and extend the ES-SAGD process application to gas-over-bitumen reservoirs and naturally occurring low pressure reservoirs. In this paper, four low pressure experiments and one high pressure experiment conducted in a 2D experimental facility at the Alberta Research Council are presented and analyzed in order to evaluate the performance of ES-SAGD at low pressure.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".