Seismic Monitoring of Cold Heavy Oil Production
Bibliographic record
Abstract
Summary Cold production of heavy oil sands accounts for significant oil production in Canada. In order to enhance heavy oil cold production, seismic monitoring of the reservoir can be used to determine production footprints and allow for optimum infill drilling. The cold heavy oil production with sand (CHOPS) was pioneered in Canada, by mid 1990s, CHOPS became the primary heavy oil production method in Canada. To date CHOPS has achieved wide utilization in Canada and Venezuela, and there is successful use of the technology in China as well. CHOPS is a non-thermal process in which heavy oil and sand are simultaneously extracted and produced by using powerful progressive cavity pumps. The simultaneous extraction of oil and sand generates high porosity channels termed wormholes. It is believed that the wormholes play an important role in heavy oil production due to their permeability effects in the heavy oil reservoirs. The development of wormholes causes the reservoir pressure to fall below the bubble point, and the dissolved-gas comes out of solution to form foamy oil. The formation of foamy oil then causes a partially gas saturated reservoir. In CHOPS, development of wormholes increases porosity in the reservoir. This could change the stress and rigidity of sand matrix in the reservoir, and the changes could result in velocity variations of the reservoir rocks. Based on laboratory experiments, Han et al. (1986) concluded that the measured Vp and Vs decreased dramatically with an increased porosity, and generally the effects of porosity on Vs is larger than on Vp. Formation of foamy oil results in a higher gas saturation in the reservoir, and this could also affect seismic velocity. Toksoz et al. (1976) demonstrated that in partial gas saturation rocks, a small amount of gas can lower the Vp significantly, Domenico (1976, 1977) further concluded that a small amount of gas in sediments diminishes Vp significantly, whereas Vs is insensitive to the presence of gas. Based on the laboratory experiments, Lee (2004) found that the amount of gas and the mode of gas saturation in the pore space dramatically affects the Vp, but not the Vs.
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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 | 0.001 |
| 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 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".