Nothing Special   »   [go: up one dir, main page]

skip to main content
article

Design of Intelligent Control Systems for Layered Water Injections in Oilfields

Published: 16 April 2024 Publication History

Abstract

With rapid socio-economic growth and increased energy demand, exploration and exploitation of oil and gas resources have become crucial. Long-term exploitation leads to problems such as pressure drop and production reduction in oil fields, and water injection technology has become a common method to improve these problems. The traditional direct water injection for oil extraction has problems such as high injection cost and low oil recovery efficiency. Therefore, an intelligent control system for different oilfield reservoirs is needed. This study focuses on the layered water injection intelligent system based on advanced sensor technology, digital signal processing and intelligent algorithms. The article reviews the advantages of layered water injection system and the current research status, designs an intelligent control structure including hardware circuits and modular software processes, and adopts adaptive particle swarm optimization algorithm as the core of intelligent control.

References

[1]
BarretoC. E.GasparA. T.SchiozerD. J. (2016, June). Impact of the use of intelligent wells on the evaluation of oilfield development and production strategy [Paper presentation]. SPE Trinidad and Tobago Section Energy Resources Conference, Port of Spain, Trinidad and Tobago. 10.2118/180861-MS
[2]
Cheng, H., Yang, D., Lu, C., Qin, Q., & Cadasse, D. (2022). [Retracted] Intelligent oil production stratified water injection technology. Wireless Communications and Mobile Computing, 2022(3954446), 1–7.
[3]
DuG. (2019, November). Research and application of cable controlled layered water injection technology in Daqing oilfield. In Proceedings of the IOP Conference Series: Earth and Environmental Science. IOP Publishing Ltd. 10.1088/1755-1315/384/1/012068
[4]
Gaixing, H., Zhenning, J., Guangzhi, D., Jierui, F., Guanglun, W., Xiaoxuan, J., & Erzhen, W. (2022). Design and application of real-time monitoring system in digital layered water injection. Drilling & Production Technology, 45(4), 114–118.
[5]
HegdalT.HarunaS.SvebergK. (2020, May). Fully integrated subsea sulfate removal and low salinity plant for IOR and EOR [Paper presentation]. Offshore Technology Conference, Houston, Texas. 10.4043/30832-MS
[6]
Lei, J., Du, J., Lei, X., Tian, S., Ni, F., & Cheng, H. (2023). Oily wastewater treatment and reuse technology in low permeability oilfield. Petroleum Science and Technology, 1–15.
[7]
Su, Y., Han, M.-Z., Zhang, B.-M., Zhao, F., & Jiang, Y. (2021). Study on and application of intelligent regulation and distribution technology for separate water injection wells. In Proceedings of the International Petroleum and Petrochemical Technology Conference 2020. IPPTC 2020, (pp. 716–726). Springer Singapore. 10.1007/978-981-16-1123-0_65
[8]
TongG.JingW.ShanG.YangS.JinxiuW.JingZ. (2020, November). Design of automatic layered water injection system based on Internet of Things. In Proceedings of the 2020 IEEE 8th International Conference on Computer Science and Network Technology (ICCSNT), (pp. 194–197). IEEE. 10.1109/ICCSNT50940.2020.9304995
[9]
WangB. (2022, September). Design and implementation of information management system for layered testing of water injection wells. In Proceedings of SPIE 12346, 2nd International Conference on Information Technology and Intelligent Control (CITIC 2022), 123460V, (pp. 202–205). SPIE. 10.1117/12.2653435
[10]
Wang, T., Li, P.-W., & Lin, J.-E. (2022, November). Study on intelligent pulsating stratified water injection technology and its application scheme. In Proceedings of the International Field Exploration and Development Conference. IFEDC 2022, (pp. 3523–3536). Springer Nature Singapore. 10.1007/978-981-99-1964-2_304
[11]
WangZ.YangL.LiuY.YuJ. (2019, March). Research of macroscopic control system applied in separate layer water injection in intelligent oilfield. In Proceedings of the 2019 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA), (pp. 1–4). IEEE. 10.1109/ICAICA.2019.8873508
[12]
Xing, S., Song, N., & Wen, X. (2023, August). Oilfield water injection surface monitoring system. In Proceedings of the Third International Conference on Image Processing and Intelligent Control (IPIC 2023). Society of Photo-Optical Instrumentation Engineers (SPIE). 10.1117/12.3000768
[13]
Yang, L., Yu, J., Ju, M., Luo, B., Wang, Z., & Hu, G. (2018, July). Intelligent monitoring and controlling technology of water injection in ultra-low permeability reservoir of Ordos Basin. In Z. Qu & J. Lin (Eds.), Proceedings of the international field exploration and development conference 2017. Springer series in geomechanics and geoengineering (pp. 1353–1362). Springer Singapore. 10.1007/978-981-10-7560-5_125
[14]
Yue, Y.-L., Wen, H.-Y., Zuo, X., Sheng, M., & Sun, F.-C. (2021). Output fusion of MPC and PID and its application in intelligent layered water injection of oilfield. Preprint. arXiv:2112.07129 [eess.SY]. https://doi.org//arXiv.2112.0712910.48550
[15]
ZhaoX.ZhouS.XuG.XiangY.LiQ.ZhaoM.XiaM.ZhuK. (2020, January). Optimization and simplification technology of maturing oilfields gathering and transportation system and water injection system [Paper presentation]. International Petroleum Technology Conference, Dhahran, Kingdom of Saudi Arabia. 10.2523/IPTC-19998-Abstract

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image International Journal of Distributed Systems and Technologies
International Journal of Distributed Systems and Technologies  Volume 15, Issue 1
Nov 2024
163 pages

Publisher

IGI Global

United States

Publication History

Published: 16 April 2024

Author Tags

  1. Control System
  2. Design
  3. Layered Water Injection
  4. Intelligent
  5. Oil Recovery Engineering

Qualifiers

  • Article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 0
    Total Downloads
  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 14 Dec 2024

Other Metrics

Citations

View Options

View options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media