Seismic characterization of heavy oil reservoir during thermal production: A case study
Bibliographic record
Abstract
ABSTRACT Heavy oil reservoirs are important alternative energy resources to conventional oil and gas reservoirs. However, due to the high viscosity, most production methods of heavy oil reservoirs involve thermal production. Heavy oil reservoirs’ properties change dramatically during thermal production because the viscosity drops drastically with increasing temperature. Moreover, the velocity and density also decrease after steam injection, leading to a longer traveltime of seismic velocities and low impedance of the steam chamber zone. These changes of properties can act as indicators of the steam chamber and can be detected through the time-lapse inversion method. We first establish the rock-physics relationship between oil sands’ impedance and temperature on the basis of our previous laboratory work. Then, we perform the forward modeling of the heavy oil reservoir with the steam chamber to demonstrate the influence of steam injection on seismic profiles. Then, we develop a modified-Cauchy prior-distribution-based time-lapse inversion method and perform a 2D model test. The inversion method is then applied on the real field data, and the results are analyzed. By combining the inverted impedance and rock-physics relation between impedance and temperature, the temperature distribution map is obtained, which can work as an indicator of steam chamber. Finally, an empirical relation between impedance and velocity is established, and velocity is derived from the impedance.
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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 | 0.000 | 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 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".