Adaptive Prediction of Enhanced Oil Recovery by N2 huff-n-puff in Fractured-Cavity Reservoir Using an FNN-FDS Hybrid Model
Abstract
:1. Introduction
2. Research Background
3. Adaptive FNN-FDS Hybrid Model
3.1. Adaptive Neuro-Fuzzy Inference System
3.2. Fractional Order Differential Simulation Model
3.3. Calculation of Enhanced Oil Recovery Ratio
3.4. Calculation Procedures of FNN-FDS Hybrid Model
4. Results and Discussion
4.1. Raw Data
4.2. Model Appraisal
4.3. Adaptive Prediction and Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Well No. | Annual Output (m3) | Cumulative Gas Storage (104 m3) | Cumulative Water Storage (m3) | Permeability (mD) | Well Depth (m) |
---|---|---|---|---|---|
LG01 | 6231 | 186 | 7361 | 11000 | 6800 |
LG02 | 2281 | 150 | 526 | 5000 | 6200 |
LG03 | 4062 | 100 | 2995 | 8000 | 6500 |
LG04 | 5033 | 120 | 2763 | 9500 | 6600 |
LG05 | 2556 | 200 | 1474 | 5500 | 6200 |
LG06 | 2437 | 80 | 740 | 5300 | 6200 |
LG07 | 6450 | 600 | 800 | 11000 | 6800 |
LG08 | 2086 | 1000 | 658 | 4800 | 6100 |
LG09 | 3929 | 200 | 800 | 7700 | 6400 |
LG10 | 2817 | 168 | 46 | 6000 | 6200 |
LG11 | 6530 | 600 | 800 | 12000 | 6800 |
LG12 | 3427 | 400 | 720 | 7000 | 6400 |
LG13 | 7340 | 100 | 4067 | 13000 | 7000 |
LG14 | 2218 | 100 | 636 | 5000 | 6200 |
LG15 | 2215 | 600 | 918 | 5000 | 6200 |
LG16 | 4725 | 150 | 3905 | 8500 | 6500 |
LG17 | 1986 | 260 | 3578 | 4500 | 6100 |
LG18 | 1045 | 200 | 2403 | 3100 | 6000 |
LG19 | 2935 | 180 | 942 | 6100 | 6300 |
LG20 | 1447 | 180 | 1907 | 3700 | 6000 |
LG21 | 3138 | 200 | 605 | 6500 | 6300 |
LG22 | 4825 | 100 | 3968 | 9000 | 6600 |
Well No. | Annual Production (m3) | Well No. | Annual Production (m3) |
---|---|---|---|
LG01 | 5121 | LG12 | 2637 |
LG02 | 2031 | LG13 | 6824 |
LG03 | 3526 | LG14 | 1865 |
LG04 | 4542 | LG15 | 1754 |
LG05 | 2019 | LG16 | 3951 |
LG06 | 2028 | LG17 | 1468 |
LG07 | 5965 | LG18 | 896 |
LG08 | 1506 | LG19 | 2087 |
LG09 | 3017 | LG20 | 1065 |
LG10 | 2027 | LG21 | 2614 |
LG11 | 5684 | LG22 | 3687 |
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Wang, Q.; Jiang, H.; Han, J.; Wang, D.; Li, J. Adaptive Prediction of Enhanced Oil Recovery by N2 huff-n-puff in Fractured-Cavity Reservoir Using an FNN-FDS Hybrid Model. Appl. Sci. 2021, 11, 8871. https://doi.org/10.3390/app11198871
Wang Q, Jiang H, Han J, Wang D, Li J. Adaptive Prediction of Enhanced Oil Recovery by N2 huff-n-puff in Fractured-Cavity Reservoir Using an FNN-FDS Hybrid Model. Applied Sciences. 2021; 11(19):8871. https://doi.org/10.3390/app11198871
Chicago/Turabian StyleWang, Qi, Hanqiao Jiang, Jianfa Han, Daigang Wang, and Junjian Li. 2021. "Adaptive Prediction of Enhanced Oil Recovery by N2 huff-n-puff in Fractured-Cavity Reservoir Using an FNN-FDS Hybrid Model" Applied Sciences 11, no. 19: 8871. https://doi.org/10.3390/app11198871
APA StyleWang, Q., Jiang, H., Han, J., Wang, D., & Li, J. (2021). Adaptive Prediction of Enhanced Oil Recovery by N2 huff-n-puff in Fractured-Cavity Reservoir Using an FNN-FDS Hybrid Model. Applied Sciences, 11(19), 8871. https://doi.org/10.3390/app11198871