In-situ combustion: influence of injection parameters using CMG stars
Bibliographic record
Abstract
In-situ combustion (ISC) is one of the oldest methods of thermal oil recovery, the method of ISC incurs much more complex, challenging, and volatile physical and chemical processes compare to other method. With current advancement in technology, interest in ISC process is increasing, it offers unparalleled economic benefits when compared to other enhance oil recovery (EOR) methods, particularly,in terms of high oil recovery and applicability to a broad range of reservoirs. In this research work, a new 1-D tube model was developed serves as the base case for other analysis to generate good predictability for the optimum sustainable development of the reservoir performance. The dimensions and initial conditions provided by Belgrave et al. (1990) and Yang et al., (2009) was used to develop the base case. A similar model is also developed by Liu (2011) using Belgrave’s data and both models are used for comparison of results in this research. Numerical simulator CMG STARS established by the computer modelling group in Calgary was used to study the influence of some parameters. The parameters studied included: Injection rate of air/gas, oxygen mole fraction injected, temperature propagation and pore volume Injected. Athabasca Bitumen is used as the heavy oil. The practical concern, benefits, and limitation of each developed scenarios are examined in detail. This research works present recommendations related to the novel and mature in-situ combustion plan in which development of the simulation model is on-going.
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 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 | 0.001 |
| 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".