Oil sands reservoir monitoring using 4D seismic data
Bibliographic record
Abstract
Time-lapse three-dimensional (3D) seismic monitoring study was conducted in the JACOS Hangingstone steam assisted gravity drainage (SAGD) operation area, Alberta, Canada. The objective of the study was to delineate steam-affected areas using differences between two 3D seismic data acquired at different production stages for efficient reservoir management.The time-lapse surveys were acquired in February, 2002 and in March, 2006. As repeatability is important for the time-lapse seismic surveys, the two 3D seismic surveys were recorded with nearly identical field acquisition parameters and the data sets of both surveys were processed with identical processing flows.P-wave and S-wave velocities of oil sands core plugs from the field were also measured under various pressure and temperature conditions to understand the relationship between seismic velocities and reservoir conditions. The laboratory measurement results were combined and a rock physics model was proposed to predict velocity changes of the oil sands under reservoir conditions expected during SAGD operations.The two seismic volumes show significant differences in seismic character within the reservoir and time delays below the reservoir around the active SAGD well pairs. Synthetic seismic data based on the rock physics model were analyzed to evaluate seismic response changes of the time-lapse 3D seismic survey. From our analysis, the differences of the seismic responses between the two 3D seismic volumes can be quantitatively explained by P-wave velocity decrease of the oil sands layers due to the steam-injection. In addition, our result suggests that a larger area would be influenced by pressure than by temperature.In conclusion, the time-lapse 3D seismic monitoring along with the rock physics model is useful for qualitative and quantitative estimate of the rock property changes of the interwell reservoir sands in the field.
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How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".