Promising Progress in Field Application of Reservoir Electrical Heating Methods
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Electrical Heating of heavy oil reservoirs has been successfully applied in near wellbore regions. Well stimulations through downhole resistive, dielectric, or induction electric heating systems when applied in suitable reservoirs can triple flow rates for a small additional operating cost. In such cases high-energy conversion ratios such as 10-15 bbls. Of oil for every bbl of oil consumed at the power plant can be achieved. Applications of electric heating can particularly be beneficial in situations where steam cannot be used due to either depth, formation incompatibility, low incipient injectivity, excessive heat losses or existence of thief zones. Additionally, for reservoirs already having a high temperature in the 60-80 degree C and higher range, only a small amount of electric heating-stimulation is enough to increase oil production by an order of magnitude. Some Orinoco reservoirs of Venezuela fall into this category. Heavy oil reservoirs, overlain by heat sensitive permafrost, may also find electrical heating a viable thermal stimulation technique. Electrical heating process has also been adapted to apply in preheat phase of other complimentary processes like VAPEX. The process also has been investigated for hot water flood in deep reservoirs. This paper proposes to use downhole electric systems for stimulating for both vertical and horizontal wells in such reservoirs. Using CMG's thermal simulator-STARS (ref. 7), results of several worldwide investigations are included. A summary of field applications is also presented. In addition, incremental oil recovery vs. energy consumption is tabulated.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it