Improve the Reliability of 3d Geological Model for Terrigenous Sandstone Reservoir, F Block, Dh Field, Nam Con Son Basin by Using Gaussian Random Function Simulation (GRFS) and Hydraulic Flow Units (HFU) Integrated Artificial Neural Network (ANN)

Authors

  • Dr. Ngoc Thai Ba

Keywords:

contaminants, ecosystems, Snow Pollution, Ecological Impacts, Environmental Policies., soil degradation, landslides, land use, soil profile evolution., 3D Geological Model, Terrigenous Sandstone Reservoir, Gaussian Random Function Simulation (GRFS), Hydraulic Flow Units (HFU), Artificial Neural Network (ANN).

References

Improve the Reliability of 3d Geological Model for Terrigenous Sandstone Reservoir, F Block, Dh Field, Nam Con Son Basin by Using Gaussian Random Function Simulation (GRFS) and Hydraulic Flow Units (HFU) Integrated Artificial Neural Network (ANN)

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Published

2024-01-09

Issue

Vol. 23 No. 20 (2023): LJRS Volume 23 Issue 20

Section

Articles

License

Copyright (c) 2023 Authors and Global Journals Private Limited

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Improve the Reliability of 3d Geological Model for Terrigenous Sandstone Reservoir, F Block, Dh Field, Nam Con Son Basin by Using Gaussian Random Function Simulation (GRFS) and Hydraulic Flow Units (HFU) Integrated Artificial Neural Network (ANN). (2024). London Journal of Research In Science: Natural and Formal, 23(20), 37-45. https://journalspress.uk/index.php/LJRS/article/view/504