Numerical Simulation of Dielectric Heating in a Heavy Oil Reservoir Using a Shaped Dipole Antenna
Bibliographic record
Abstract
Abstract The numerical evaluation of dielectric heating in a heavy oil containing sand is presented using a shaped dipole antenna under static (no oil production) and dynamic (with oil production) conditions. The electromagnetic simulator AxREMS™ was coupled to the commercial reservoir simulator STARS™ to model RF heating using three different shaped antenna designs (Straight dipole, Concave, and Convex design). The static simulations showed that the Concave design offers more uniform radiation pattern and temperature profile than the Straight and Convex counterparts. A conceptual model with seven sands (over- and under-burden and five oil-containing sands) was utilized for the dynamic simulation of downhole RF dielectric heating. The results indicated that all the RF heating cases had accelerated oil production than that found for the Base Case (cold production). Modeling shows that peak production is increased if RF heating is initiated before the start of production. However, all cases studied converged to approximately equal cumulative incremental oil above the Base Case, after about 700 days after the initiation of RF heating.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".