Seismic rock physics of steam injection in bituminous‐oil reservoirs
Bibliographic record
Abstract
This case study explores rock physical properties of heavy oil reservoirs subject to the Steam Assisted Gravity Drainage (SAGD) thermal enhanced recovery process. Previously published measurements (e.g. Wang et. al, 1990, and Eastwood, 1993) of the temperature dependant properties of heavy oil saturated sands are extended by fluid substitutional modeling and wireline data in order to assess the effects of pore fluid composition, pressure and temperature changes on the seismic velocities of unconsolidated sands. Rock physics modeling is applied to the shallow McMurray reservoir within the bituminous Athabasca oil sands deposit in order to construct a petrophysical velocity model of the SAGD process. Although the injected steam pressure and temperature controls the fluid bulk moduli within the pore space, the stress dependant elastic frame modulus is the most poorly known yet most important factor governing the changes of seismic properties during this recovery operation. The results of the fluid substitution are used to construct a 2-D synthetic seismic section in order to establish seismic attributes for analysis and interpretation of the physical SAGD process. The findings of this modeling promote a more complete description of 11 high resolution time-lapse 2-D seismic profiles collected over a shallow oil sands reservoir undergoing SAGD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".