Utilization of CO2 for Improving the Performance of Waterflooding in Heavy Oil Recovery
Bibliographic record
Abstract
Abstract Due to the favorable effects of CO2, such as oil viscosity reduction, oil swelling, and surface tension reduction, CO2 injection has been established as an effective technique in enhanced oil recovery for light to medium oils. However the utilization of CO2 for improving the recovery of heavy oil reserves, such as those of Western Canada, has not been given enough attention due to immiscible nature of the mixture of CO2 and these heavy oil resources. Many heavy oil reservoirs in Western Canada have been under waterflooding where oil is produced at very high water-oilratios. Due to the high solubility of CO2 in both water and oil, it might be possible to improve the overall oil recovery from these waterflooding operations by adding small volumes of CO2 to the injected water. This paper presents the results obtained in an experimental study, consisting of six core-flooding experiments, to investigate the effects of CO2 utilization on improving the performance of waterflooding in heavy oil recovery. Here, the following injection strategies are tested; (1) injection of carbonated water and (2) injection of 11% and 27% of pore volume CO2 followed by a soak period and resuming water injection. Experiments are carried out at temperatures of 30 and 35 °C, and water injection rates between 1 and 50 feet per day, to recover heavy oils with viscosities of 1500 to 2000 cP. Carbonated water used in these experiments is prepared by dissolving CO2 in 1% wt. NaCl brine over 48 hours. The results indicate that, in general, the recovery of heavy oil by waterflooding is significantly improved when a combination of water and CO2 is used. Utilization of CO2 resulted in incremental recoveries in the range of 15 to 27% OOIP. It was also found that intermittent injection of water and CO2 results in greater recovery improvements compared to carbonated water injection. Furthermore, increased CO2 volume led to higher oil recovery. Also, it was found that greater recoveries were obtained at higher rates of water injection. Introduction Amongst the largest resources of the world's oil are the heavy oil and bitumen deposits of western Canada (Saskatchewan and Alberta). These heavy oil deposits total more than 5200 million m3. Waterflooding as a secondary method of recovery has been employed in some Canadian heavy oil reservoirs for many years. This is despite the poor performance and low recoveries of heavy oil waterfloods due to unfavorable mobility ratio as reported in numerous studies. The main reason for the widespread application of waterflooding in heavy oil reservoirs has been its relatively low cost and the ease of operations. An additional value of waterflooding is that, if more expensive EOR options are being considered for a given field, waterflooding is a low-risk option that can be used to recover some additional oil while more advanced lab and pilot studies are being designed1. In conventional oil waterfloods the occurrence of high wateroil- ratios is an indication that the end of the process is near, but this is not true in the case of heavy oil waterfloods.
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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".