Application of sensitivity analysis in DC resistivity monitoring of SAGD steam chambers
Bibliographic record
Abstract
Steam Assisted Gravity Drainage (SAGD) is a proven technology to extract heavy oil from the Athabasca oil sands in Alberta, Canada. Research and pilot programs have shown the growth in steam chambers can be detected and monitored using electrical methods, indicating a decrease in electrical resistivity due to steaming process. We analyze surveys currently in practice using the sensitivity of the data to model perturbations. We show that certain surveys have greater sensitivity to important regions of the reservoir, and that inversions of data collected using these surveys provide better recovery of the chambers. The sensitivity analysis provides a computationally fast and inexpensive approximation of what a full inversion can recover, making it ideal in survey design studies. Our aim is to use analysis of the sensitivity matrix to design improved surveys as well as extend the surveys to multi-frequency electromagnetic methods. Presentation Date: Wednesday, October 19, 2016 Start Time: 1:55:00 PM Location: 174 Presentation Type: ORAL
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".