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Bibliographic record
Abstract
Abstract Earlier, we reported results of numerical simulation that, for the low permeability reservoirs of Cold Lake and Peace River, show the Fast-SAGD process to obtain a better performance, lower steam requirement and higher productivity than does the SAGD process. Now, we report results of experiments using a scaled physical model, which represents a bituminous reservoir near Cold Lake being operated at high temperature and pressure. Also, we used an automated process control system. The results of the experiments showed that, for the Fast-SAGD process, the overall cumulative oil production is larger and the end-point CSOR higher than for the SAGD process. We concluded tentatively that for the Fast-SAGD experiment, the boiler did not produce sufficient volume of high quality steam. Results of numerical simulation of these experiments confirmed this conclusion; best history matches showed the steam quality to have been 30% during the SAGD and then 15% after starting the CSS. Moreover, the best history match of the Fast-SAGD experiment showed that the steam chamber was lost and subsequently recovered during the experiment. These preliminary high temperature and pressure experiments have provided important insights into operation of the SAGD and Fast-SAGD processes and suggest a mechanism of the steam chamber's collapse and recovery. Introduction Fast-SAGD, a modification of the steam-assisted gravity drainage (SAGD) process, uses offset wells operated with cyclic steam stimulation (CSS) beside the SAGD well pair in order to accelerate the steam chamber growth sideways (1). Previous numerical studies(2) (3) of a typical Cold Lake-type reservoir have shown that the Fast-SAGD process enhances thermal efficiency, resulting in better production performance as compared to the conventional SAGD process. A numerical study (4) for Fast- SAGD application in the Alberta oil sands areas showed the Fast-SAGD process to have higher net present values (NPV) for the low permeability type reservoirs of Cold Lake and Peace River because of lower steam requirements and higher productivity. In this study, high temperature and high pressure scaled physical model experiments were conducted to investigate the Fast-SAGD process using an automated process control system. From numerical simulations showing the Fast-SAGD process to result in enhanced performance compared to the SAGD process in Cold-Lake-type reservoirs (4),, a suitable permeability of 1.25 Darcy was chosen for the prototype. High pressure and high temperature scaled physical model experiments Conducting high temperature and high pressure model experiments is very difficult as many variables, such as steam quality, injection rate and pressure need to be controlled all at once and in real time. An initial study (5) showed that an automated process control system is capable of controlling and optimizing steam injection processes such as the steam-assisted gravity drainage process. Two-dimensional scaled model A two-dimensional scaled model cannot represent a field reservoir prototype because there are no perfect scaling methods. For example, the heat loss aspect is different. In the field, only over- and under-burden heat losses are considered, whereas in a laboratory, heat losses are not only to the over- and under-burden but also to the sides of the scaled model.
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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 | 0.000 |
| 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) | 0.000 | 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