Evaluation of a Field-Wide Post-Steam In-Situ Combustion Performance in a Heavy Oil Reservoir in China
Bibliographic record
Abstract
Abstract We evaluated the performance of a field-wide post-steam in-situ combustion (ISC) project conducted in a complex heavy oil reservoir in China using laboratory one-dimensional combustion experiments, reservoir simulation outputs, and data collected from the field application. The commercial ISC project showed vastly different production performances in different regions of the field and two types of representative well groups were identified. Type I group has a low oil viscosity (<8000 mPa.s) and a high steam-flooded recovery factor (>30%); after ISC treatment, these producers show a high initial water cut, while some experience channeling issues and hence produce a large quantity of flue gas. Type II group has a high oil viscosity (>20000 mPa.s) and a low cyclic steam stimulation (CSS) recovery factor (15-20%); these producers have a high air injection pressure exceeding the fracture pressure. Corresponding remedial methods were designed and applied to these two well groups. Presently, the evaluation methods described in this paper are being applied in the field, and initial results have been acquired.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".