Solution-Gas Drive in Heavy Oil: Field Prediction and Sensitivity Studies with Low Gas Phase Relative Permeability
Bibliographic record
Abstract
Abstract The favourable behaviour of heavy oil reservoirs under solution-gas drive has intrigued the oil industry for long. Many mechanistic models have been proposed to explain this behaviour. It is believed that the flow in heavy oil reservoir is quite complex and cannot be represented by one theory alone. This paper investigates one of the theories that attribute this behaviour of heavy oil reservoirs to low gas mobility. Simulation is carried out on a commercial black oil simulator to match the production data of heavy oil fields in Lindbergh and Frog Lake. Further, sensitivity studies are carried out to investigate the effect of various parameters in gas relative permeability model, on oil recovery in a radial geometry. The effect of sand production, which is an integral part of heavy oil production in Western Canada, is also investigated. A new parameter is used in the simulator to model the increase in permeability due to sand production. Finally, the results obtained from simulation in radial geometry are compared with that obtained in linear geometry. The results indicate that the field performance can be predicted by assigning low gas phase relative permeability values and incorporating improved permeability due to sand production. Neither of them by itself can model the field performance. It is concluded that the sand production increases the effective permeability of the reservoir in the far away field too. The low gas mobility is successful in explaining high pressure gradients and pressure maintenance mechanism observed in the field, and may be attributed as one of the reasons leading to favourable behaviour of heavy oil reservoirs. Introduction PanCanadian is the major operator in the Lindbergh and Frog Lake heavy oil fields in northeastern Alberta1. The fields have shown recovery, much in excess of what can be predicted by application of conventional flow equations in radial geometry. The oil production in these fields is accompanied by sand production. The mechanism of heavy oil production with sand production has been termed as "Cold Production". The production wells in Lindbergh and Frog Lake fields, under primary production, had produced about 9300 m3 of oil and about 230 m3 of sand in 1000 days. High pressure gradients were also observed in the field. Several tests were done in the field1 to test the mechanism responsible for the favourable behaviour of these reservoirs. Metwally and Solanki1 attempted to explain the mechanism and presented a simulation model to match the field production behaviour. With the above field performance in mind, and trying to match the field data, Metwally and Solanki1 postulated that the porosity and hence the permeability of the reservoir is increased due to sand production. Additionally, they incorporated a pressure maintenance mechanism to match the field data. They, however, were unable to present a physical explanation for this mechanism in absence of an aquifer. LITERATURE REVIEW Due to anomalously high primary recoveries (under Solution-gas drive process), a lot of interest has been generated in the production of heavy oil via "Cold Production" process1, 10–13.
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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".