Reservoir monitoring of steam‐assisted gravity drainage using borehole measurements
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Bibliographic record
Abstract
ABSTRACT This paper presents the results from a research project focusing on permanent cross‐well geophysical methods for reservoir monitoring during steam‐assisted gravity drainage. A feasibility study indicated detectable differences in seismic and electrical reservoir properties based on expected changes in temperature and fluid saturation during the production of extra heavy oil. As a result of this, a permanent cross‐well system was installed at the Leismer Demonstration Area, located in the Athabasca Oil Sands region in Alberta, Canada. Baseline data sets, including cross‐well seismic, three‐dimensional vertical seismic profiling and cross‐well electrical resistivity tomography, have been acquired. Comparisons between conventional surface seismic and downhole seismic data show an increase in resolution and frequency content as expected. Steam‐assisted gravity drainage‐induced time‐lapse effects are clearly visible in the 3D vertical seismic profiling and electrical resistivity tomography data sets, even after a few months of oil production. In general, the 3D vertical seismic profiling images show a higher resolution than the surface seismic data, in particular when dealing with vertical positioning of the time‐lapse events. The electrical resistivity tomography baseline shows clear separation between zones of high and low electrical resistivity, and during 23 months of electrical resistivity tomography measurements the maximum reduction of resistivity is 85%. Time‐lapse observations from acoustic and electrical borehole data correspond well, and are also supported by temperature measurements in the two observation wells. Emerging technologies, updated models, improved flexibility, and reduced costs will allow future reservoir monitoring with surface and borehole data in combination, or even with borehole data exclusively.
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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 | 0.001 | 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