Attenuation analysis of heavy oil sands based on laboratory measurements
Bibliographic record
Abstract
ABSTRACT Analyzing elastic and attenuation characteristics of heavy oil sand is critical for understanding and interpreting sonic and seismic data for their use in exploration and reservoir monitoring. The attenuation characteristic of oil sands is inherently complicated because of its loose frame, large porosity, and highly temperature-dependent viscosity of heavy oil. During thermal production, the attenuation of heavy oil sands undergoes significant changes due to the effects of pressure, temperature, and gas. Therefore, we have performed laboratory measurements of heavy oil sands under different physical conditions. By applying spectral-ratio method on the recorded wave signals, we are able to investigate the attenuation of the oil sands under different pressure and temperature conditions. For the measured sample, the 1/Qp decreases from 0.083 to 0.043 for a differential pressure increasing from 1.38 to 9.65 MPa. A peak of 1/Qs occurs at the middle temperature (approximately 60°C) for the wet sample, whereas the weakest 1/Qs occurs at the low temperature. Comparisons between the as-is (partially saturated) and wet (fully saturated) samples suggest that attenuation (1/Q) of the oil sands can be significantly affected by the presence of gas at a high temperature (greater than 60°C). In the end, the Havriliak-Negami model is used to capture the temperature-dependent attenuation characteristics of fully saturated oil sands. Although the measurements are conducted at ultrasonic frequency, the presented results indicate some implications for field-reservoir monitoring and also offer insights into applying attenuation attribute to characterize heavy oil reservoir during thermal production.
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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 | 0.001 |
| 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) | 0.001 | 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 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".