Remote reservoir monitoring in oil sands: From feasibility study to baseline datasets
Bibliographic record
Abstract
Summary A joint research project between Statoil and Schlumberger is focusing on permanent cross-well geophysical methods for reservoir monitoring during steam assisted gravity drainage (SAGD). In 2009, a feasibility study indicated detectable differences in seismic and electrical reservoir properties based on expected changes in temperature and fluid saturation during oil production. Based on these results, several geophysical reservoir monitoring methods were evaluated. These included cross-well seismic, vertical seismic profiling (VSP), and electrical resistivity tomography (ERT). The modeling study was followed by an installation of a permanent cross-well system at Statoil’s Leismer Demonstration Area (LDA) in Alberta, Canada, in 2010. After the system was successfully installed and tested, baseline datasets were acquired through an established data link, also allowing for remote monitoring throughout the calendar year. ERT datasets can now be acquired without personnel on site, while seismic acquisitions require a moving source on the surface or a cross-well seismic source and receiver array deployed on wireline. Comparisons of
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 0.001 |
| 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".