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International Journal of Frontiers in Engineering Technology, 2021, 3(10); doi: 10.25236/IJFET.2021.031001.

Improved Adaptive Butterfly Subdivision Algorithm and Its Application in 3D Geological Modeling


Jiajing Li, Zhe Liu, Wei Wang

Corresponding Author:
Jiajing Li

School of Petroleum Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, Guangdong, China


It is of great significance in the fields of 3D modeling, geological engineering and oil and gas storage. This paper mainly studies the improved adaptive butterfly subdivision algorithm and its application in 3D geological modeling. After the geological body section is created, the surface model can be constructed by connecting the sampling points on the contour line of adjacent sections with triangular patches according to the improved adaptive butterfly subdivision algorithm, and then the construction of the geological body model is realized by connecting the strata blocks with the same attributes on the adjacent sections. In this paper, the contour algorithm is used to generate the volume element surface. In this paper, the regular grid interpolation data is generated by butterfly subdivision algorithm using borehole data with multi-layer geological information. After all the simplexes in a 3D geological modeling area are generated, the complex body or complex to which the simple body belongs and the complex body to which the complex body belongs can be assigned. So far, the geological body simulation of 3D modeling area has been completed. Experimental data show that the total execution time of the algorithm is less than 20s. The results show that the improved butterfly subdivision algorithm can improve the accuracy and accuracy of the model.


Improved Butterfly Algorithm, 3d Geological Modeling, Adaptive Subdivision, Data Model

Cite This Paper

Jiajing Li, Zhe Liu, Wei Wang. Improved Adaptive Butterfly Subdivision Algorithm and Its Application in 3D Geological Modeling. International Journal of Frontiers in Engineering Technology (2021), Vol. 3, Issue 10: 1-13. https://doi.org/10.25236/IJFET.2021.031001.


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