Consideration of Geomechanics for In-situ Bitumen Recovery in Xinjiang, China
Bibliographic record
Abstract
Abstract This paper describes a geomechanical work program carried out in Karamay heavy oil field, Xinjiang Province, China. Three mini-frac tests were conducted to measure the in-situ minimum stresses in the reservoir sands, shale interbed and caprock shales. Geomechanical triaxial tests under room- and high-temperature were completed to investigate the geomechanical properties of the reservoir sands. These works were motivated by repeating the success experienced in Alberta oilsands reservoirs which proactively use geomechanics to enhance the in-situ thermal recovery. One particular technology, i.e. using geomechanical dilation mechanism for early SAGD start-up was successfully demonstrated on one SAGD well pair in the Karamay reservoir. The results from the mini-frac tests and laboratory tests are presented and compared with the oilsands reservoirs in Alberta, Canada. Differences were discovered. Petrophysical and mineralogical measurements were made and geological origins are sought to explain the difference. Furthermore, relevant results from the dilation start-up demonstration are also shared to the end of this paper. Such success has proven again that geomechanics is equally important in the optimization of in-situ thermal stimulation of the heavy oil reservoirs in Karamay heavy oil field.
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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 | 0.000 | 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 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".