Open Access
Issue
E3S Web of Conf.
Volume 536, 2024
2024 6th International Conference on Environmental Prevention and Pollution Control Technologies (EPPCT 2024)
Article Number 03017
Number of page(s) 4
Section Gas Emission Control and Solid Waste Treatment
DOI https://doi.org/10.1051/e3sconf/202453603017
Published online 10 June 2024
  1. Afshari, S., Pishvaie, M.R. (2014) Well placement optimization using a particle swarm optimization algorithm, a novel approach. Petroleum science and technology, 32: 170-179. [CrossRef] [Google Scholar]
  2. Borda, E.S., Govindan, R., Elahi, N. (2020) The Development of a Dynamic CO2 Injection Strategy for the Depleted Forties and Nelson Oilfields Using Regression-based Multi-objective Programming. Energy Procedia, 114: 3335-3342. [Google Scholar]
  3. Zheng, F., Jahandideh, A., Jha, B. (2021) Geologic CO2 storage optimization under geomechanical risk using coupled-physics models. International Journal of Greenhouse Gas Control, 110: 103-115. [CrossRef] [Google Scholar]
  4. Rigby, S.P., Alsayah, A. (2023) Storage Sites for Carbon Dioxide in the North Sea and Their Particular Characteristics. Energies, 17: 211-228. [CrossRef] [Google Scholar]
  5. Zweigel, P., Arts, R., Lothe, A.E.(2004) Reservoir geology of the Utsira Formation at the first industrial-scale underground CO2 storage site (Sleipner area, North Sea). Geological Society, London, Special Publications, 233: 165-180. [CrossRef] [Google Scholar]
  6. Deng, W., Shang, S. (2021) An improved differential evolution algorithm and its application in optimization problem. Soft Computing, 25: 5277-5298. [CrossRef] [Google Scholar]
  7. Zeng, Z., Zhang, M., Chen, T. (2021) A new selection operator for differential evolution algorithm. Knowledge-Based Systems, 226: 107-120. [Google Scholar]
  8. Ahmad, M.F., Lim, W.H. (2022) Differential evolution: A recent review based on state-of-the-art works. Alexandria Engineering Journal, 61: 3831-3872. [CrossRef] [Google Scholar]
  9. Nilsen, H.M., Lie, K.A., Andersen, O. (2015) Analysis of CO2 trapping capacities and long-term migration for geological formations in the Norwegian North Sea using MRST-co2lab. Computers & geosciences, 79: 15-26. [CrossRef] [Google Scholar]
  10. Andersen, O. (2017)Simplified models for numerical simulation of geological CO2 storage. the University of Bergen, [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.