Analysis of IOR Pilots in Bakken Formation by Using Numerical Simulation
Bibliographic record
Abstract
Abstract Bakken is the most productive formation among unconventional plays in North America. This formation has 7.4 billion barrels of recoverable oil. However, the primary oil recovery is still low as 5-10%. Miscible natural gas and carbon dioxide (CO2) might be the most two potential strategies to improve oil recovery in such complex play. In this study, some of the IOR pilots which have been conducted in Montana, North Dakota, and South Saskatchewan have been presented. The performance results of these pilots in US-Bakken versus Canadian-Bakken have been compared. Moreover, the reasons beyond the successful IOR pilots in Canadian-Bakken versus US-Bakken have been discussed. Then, numerical simulation models have been constructed to mimic the results of these pilots. Two different compositional models have been built for two different formation-oils. Furthermore, two different models, single porosity model and dual permeability model have been created to match the performance of some pilot-tests. Implementation of molecular diffusion mechanism has been conducted in both of single porosity and dual permeability model. Finally, continuous miscible gases injection versus huff-n-puff protocols have been compared and investigated. The results showed that the performance of natural gases generally over-performed the CO2 injection technique's in Bakken formation. Although the diffusion flow is dominant, the diffusivity of the injected CO2 into formation oil is slow due to its large molecules as compared with the small pore throats of these porous media. Accordingly, miscible CO2-EOR might be not beneficial in huff-n-puff as compared to continuous flooding process. However, success of natural gases does not have that strong functionality of molar diffusivity. Therefore, their performance was much better than CO2 performance in the field scale of these tight formations. Furthermore, the numerical simulation of this study concluded that the spacing between the production wells and injection wells should be minimized, for the continuous flooding process of miscible-gases EOR, to enhance their performance. Although the permeability of Canadian-Bakken has permeability of 1-2 order higher than the permeability of US-Bakken, the spacing between injectors and producers in Canadian Bakken is interestingly much shorter than that for US-Bakken, which might be the reason beyond the EOR success in Canadian Bakken. Finally, the activation process for the highly intensive natural fractures might be the key to enhance the diffusivity of CO2-EOR. Otherwise, natural gases are highly recommended to be the most potential EOR in these types of reservoirs. This study explains how diffusion mechanism of miscible gases affects their performance to improve oil recovery in these plays since they are more complex and very different from conventional formations. Also, it suggests that CO2 flooding process would be a good practice to overcome the limitations of CO2-diffusion rate in these reservoirs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".