Viscoelasticity of Ells River bitumen sand and 4D monitoring of thermal enhanced oil recovery processes
Bibliographic record
Abstract
ABSTRACT Samples of Ells River bitumen sand from Alberta, Canada were measured at low frequencies (0.2–205 Hz) to determine the temperature and frequency dependence of velocities and attenuations. The samples were first measured “as received” where the pore space is mostly filled with bitumen but also contains small amounts of air and water. With residual air in the pores, at 5°C, there is strong dispersion in the P-wave modulus and a peak in attenuation at seismic frequencies. The frequency-dependent moduli and attenuations shift by three orders of magnitude in frequency as temperature is increased from 5°C to 48°C, consistent with the bitumen viscosity. Samples were then saturated so any empty pore space is filled with water. After saturation, at 1 Hz, increasing temperature from 5°C to 49°C causes a 30% reduction in the saturated P-wave modulus, a 34% reduction in the saturated bulk modulus, and a 6% reduction in the shear modulus. This behavior can only be explained by the temperature-dependent bulk modulus of bitumen. The results enable predictions regarding the P-velocities that can be expected during seismic monitoring of thermal enhanced oil recovery processes. Velocities for cold bitumen sand are near 2200 m/s at reservoir pressure and temperature. Following steam injection, velocities should be very low (near 1050 m/s) in heated zones more than 50°C with a free gas phase, which could be steam or gas. There will be a progressive reduction in velocities, i.e., −11% at 25°C and −17% at 49°C, in areas of formation heating, but without steam or gas in the pores. Albeit smaller than the effect of steam, the effect of formation heating alone is large enough to be easily detected by today’s 4D surveys. With local rock physics calibration, it should be possible to map the areal extent of formation heating using 4D seismic data.
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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".