Potential Evaluation on the Artificial Geothermal Energy of Post Steamed Heavy Oil Reservoirs
Bibliographic record
Abstract
Abstract Steam injection process is usually the primary extraction method for heavy oil reservoirs. But, in recent decades, with the steam injection operation continues, most of the steamed heavy oil reservoirs have achieved a depleted status (residual oil zone). Meanwhile, for most post steamed heavy oil reservoirs, the average formation temperature can reach above 150℃. It indicates that they can be considered as a potential artificial geothermal energy source. In this work, those post steamed heavy oil reservoirs are proposed as a source of artificial geothermal energy, and the extraction potential is evaluated. A heavy oil reservoir simulation model is firstly constructed based on a geological model which involves a five-spot well pattern of steam flooding operation in Shengli oilfield, Sinopec. This model can be used to represent a depleted status of a steamed heavy oil reservoir. Subsequently, based on this five-spot well pattern of steam flooding, a geothermal heat extraction model is developed. In order to accurately evaluate the extraction potential of this artificial geothermal energy, the wellbore heat loss is also considered by using a discretized wellbore model. Thus, two different extraction methods of water injection and CO2 injection are simulated. Then, based on the simulation model, the factors that control the heat extraction rate in high temperature depleted heavy oil reservoirs are also discussed. Results show that a post steamed heavy oil reservoir can be a potential source of geothermal energy. By using the existing steam flooding well pattern, the initial investment is reduced, thus, a high-efficient development can be achieved. From the simulation results, it is found that the method of geothermal energy extraction in high temperature depleted heavy oil reservoir (165 ℃, 2 MPa) using CO2 can achieve a high-speed geothermal energy extraction process in the early stage (<1.5 years). In comparison, a method of water injection process performs better within a longer time period (>1.5 years). Simultaneously, it is found that the bottom-hole pressure, heat extraction time and CO2 injection rate can have the biggest impact on the heat extraction rate. Because of the high temperature condition, the post steamed heavy oil reservoirs can have a huge potential of heat mining. The technology of geothermal energy extraction can further enhance their development value and prolong the working life.
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 | 0.001 | 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".