Controlling Microwave Penetration and Absorption in Heavy Oil Reservoirs
Bibliographic record
Abstract
Abstract Microwave heating has great potential to recover heavy oil reservoirs, because it significantly reduces the heating time and consequently the cost of heavy oil extraction. Moreover, heavy crude oils contain high amounts of polar molecules (asphaltenes) and polar functional groups, making them great microwaving candidates. This study investigates the microwave effectiveness for a specific heavy oil reservoir focused on its polar components. Furthermore, the impact of asphaltene precipitants and dispersants on microwave efficiency was investigated. A crude oil sample from Canada was subjected to microwave experiments for 30 seconds. Dielectric properties of the crude oil before and after exposure to microwave were mostly measured by using a vector network analyzer to quantify the overall polarity changes in the bulk crude. The impact of asphaltene precipitants (nC5 and nC7) and a dispersant (toluene) on microwave efficiency was also investigated. The crude oil sample was blended with nC5, nC7, or toluene at three varying doses (10%, 20%, or 50%) to investigate the impact of solvent dose on microwave efficiency. Microwave absorption and penetration depth were calculated to quantify the effectiveness of microwave heating. It has been observed through dielectric property measurements that microwave energy was absorbed by mainly the asphaltenes. Dielectric constant and loss tangent values of the blends prepared with asphaltene precipitants (nC5 and nC7) and toluene were measured before and after exposure to microwave to quantify the microwave absorption in different blends. Although precipitant mixtures had higher dielectric constants, the dispersant mixtures had much higher microwave absorption due to higher loss tangents. This finding was further supported by penetration depth measurements, in which dispersant mixtures had lower values, which led to higher microwave absorption of the crude oil mixtures. Microwave heating as a thermal enhanced oil recovery method is promising, however, complicated due to the uncontrollable nature of microwave penetration and absorption. This study reveals that while injection of an asphaltene precipitant to the desired reservoir locations can enhance the microwave penetration, injection of asphaltene dispersants will increase the microwave absorption. Cyclic injection of asphaltenes dispersants and precipitants may achieve the creation of effective heating spots within the reservoir by using only one microwave source.
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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 | 0.000 |
| 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 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".