Insulated Coiled Tubing as a Tool for a Thermal EOR Process Through Non-thermal Well
Bibliographic record
Abstract
Abstract A thermally insulated coiled tubing is permanently inserted in a horizontal heavy oil producer well and used to circulate hot oil (or water) in the well to heat by conduction the vicinity of the liner, where the drawdown is the most important. This process can be used in non-thermal wells and improves heavy oil field production with a limited quantity of energy. This paper presents the typical completion applied for this EOR process, the well integrity concerns due to high temperature and the calculated oil production increase that is confirmed by field application. The insulated coiled tubing is inserted into the horizontal well up to the well-toe. The production tubing is installed parallel to the insulated coiled tubing. The process is pumping hot oil at 230°C (or water) through the insulated coiled tubing. The heated oil is circulating from the well-toe back to the well-heel in the liner and heat the reservoir by conduction. This energy delivered to the reservoir will reduce the oil viscosity within a few meters from the liner and allow lower pressure drop. A transient thermal model has been developed to model this EOR process. The equations on which the model has been built are Darcy's law, the continuity of the flow and the energy balance. Some assumptions were taken to simplify the model such as constant reservoir properties over space and time. The model provides the temperature along the liner with max temperature at the toe and min temperature at the heel as well as the radial temperature in the reservoir. It models also the extra oil production allowed by the process. The temperature involved on the critical parts of the completion remain low and allow to apply this EOR on non-thermal wells. The field monitoring (temperature and net oil production) of the first pilots in Canada have confirmed the model results. The energy consumption requested is approx. 400kW, ten to twenty times lower than typical steam injection process. This process is not a competitor for steam injection but a good way to improve the production of heavy oil well with low CAPEX and low OPEX for specific fields where steam injection is not efficient like fields with thin reservoir. In this tough period for the oil industry, this technology can be applied on existing producer wells without drilling injector wells. The combination of this process with waterflooding is a win-win association. Waterflooding brings the driven mechanism to the reservoir and the thermal process allows better oil flow at the well.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".