Development of a Correlation Between Performance of CO2 Flooding and the Past Performance of Waterflooding in Weyburn Oil Field
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Bibliographic record
Abstract
Summary Weyburn oil field, located in southeast Saskatchewan, has been the site of one of the largest carbon dioxide (CO2) flooding projects in the world since September 2000. In this paper, data of the past performance of waterflooding in the Weyburn field was used to develop empirical correlations to predict the performance of CO2 flooding. Two different correlations were developed based on CO2-injection schemes in Wey-burn. The first correlation is based on a water-alternating-gas (WAG) process through vertical wells, and the second correlation is based on the cases in which CO2 is injected through horizontal wells and water is injected separately through vertical wells. The first step was to collect and analyze production data from 1958 to 2004. Oil-production rates for both waterflooding and CO2 flooding periods, water-injection rates, and CO2-injection rates were used in developing the correlations. The empirical model for injecting CO2 and water through vertical wells was verified using the Kinder Morgan CO2 flood-scoping model (this is not a trademark product) and actual field production data. The comparative analysis showed 12% error between our simple correlation and the Kinder Morgan model. For injecting CO2 in horizontal wells, the correlation could not be verified against the Kinder Morgan model, but the correlation followed the actual oil production in the field very closely. This new model can be used effectively as a screening tool for predicting the performance of CO2 flooding in various locations in the Weyburn reservoir based on the data obtained from past waterflooding performance and the rate of CO2 injection. Therefore, it can contribute significant savings in time and expense to the operating oil company. Also, this approach can be used for other potential CO2-flooding processes in reservoirs with histories and properties similar to those of the Weyburn field.
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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 it