InterfaceGrid: Gridding representation of 3D geological models for complex geological structures

Lujia NIU, Chengyue SHI, Zhangang WANG, Yongzhang ZHOU

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Earth Science Frontiers ›› 2024, Vol. 31 ›› Issue (4) : 129-138. DOI: 10.13745/j.esf.sf.2024.5.7

InterfaceGrid: Gridding representation of 3D geological models for complex geological structures

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Abstract

3D structural geological models are a digital representation of geological structures and geological body (object) boundaries in geological space. With the increasing demands for raster and vector integration and spatial query and analysis of geological data, the construction of integrated spatial data model for unified expression of geological structures has become one of the basic problems of 3D geological information science. To address the problem of expressing complex geological structures by regular grids, PillarGrid, Stack-Based Representation of Terrains (SBRT), etc., this study proposes the InterfaceGrid data model to fully consider that the distribution of geological structures/attributes underground exhibit strong non-uniformity, discontinuity, spatially multi-scaled, and show longitudinal stratification and multi-attribute field coupling. By design, this InterfaceGrid data model can uniformly describe 3D geological structures and realize the vector raster integration expression of complex geological structures. In this paper, the formal expression framework of InterfaceGrid is constructed based on GeoAtom theory; the construction process of the InterfaceGrid model is described; and the data update and spatial query algorithms are designed based on the InterfaceGrid model. The volume visualization and online browsing of geological grid are realized using GPU ray casting and adaptive sampling strategy. Compared with SBRT, InterfaceGrid can more truly describe the geological boundaries and improve the accuracy of 3D structural geological models. The application of InterfaceGrid in the 3D grid construction of the global lithosphere verifies the applicability of InterfaceGrid in the organization and management of large-scale geological data. Compared with PillarGrid, the data volume is reduced by about 1/3 in InterfaceGrid, making it more suitable for the data-intensive geoscience network applications.

Key words

3D structural geological model / InterfaceGrid / visualization / fault modeling / spatial query

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Lujia NIU , Chengyue SHI , Zhangang WANG , et al. InterfaceGrid: Gridding representation of 3D geological models for complex geological structures. Earth Science Frontiers. 2024, 31(4): 129-138 https://doi.org/10.13745/j.esf.sf.2024.5.7

References

[1]
毛先成, 张显洋, 刘占坤, 等. 胶西北金矿集区地球化学多重分形模型与异常识别[J]. 物探化探计算技术, 2022, 44(2): 213-223.
[2]
袁峰, 张明明, 李晓晖, 等. 成矿预测: 从二维到三维[J]. 岩石学报, 2019, 35(12): 3863-3874.
[3]
周永章, 左仁广, 刘刚, 等. 数学地球科学跨越发展的十年: 大数据、 人工智能算法正在改变地质学[J]. 矿物岩石地球化学通报, 2021, 40(3): 556-573, 777.
[4]
潘懋, 方裕, 屈红刚. 三维地质建模若干基本问题探讨[J]. 地理与地理信息科学, 2007, 23(3): 1-5.
[5]
MALLET J L. Geomodelling[M]. New York: Oxford University Press, 2002.
[6]
WANG Z G, QU H G, WU Z X, et al. Formal representation of 3D structural geological models[J]. Computers and Geosciences, 2016, 90(PA): 10-23.
[7]
曾佐勋, 樊光明. 构造地质学[M]. 3版. 武汉: 中国地质大学出版社, 2008.
[8]
唐骥, 蒋潇, 姜雪莲, 等. 矿体三维可视化建模技术在成矿模式分析中的应用[J]. 地质科技通报, 2023, 42(5): 273-284.
[9]
ZHOU C Y, DU Z C, OUYANG J W, et al. A 3D geological model and cutting algorithm based on a vertically projected triangulated network[J]. Computers and Geosciences, 2020, 143: 104562.
[10]
CAUMON G, COLLON-DROUAILLET P, LE CARLIER DE VESLUD C, et al. Surface-based 3D modeling of geological structures[J]. Mathematical Geosciences, 2009, 41(8): 927-945.
[11]
PEYROT J L, DUVAL L, PAYAN F, et al. HexaShrink, an exact scalable framework for hexahedral meshes with attributes and discontinuities: multiresolution rendering and storage of geoscience models[J]. Computational Geosciences, 2019, 23(4): 723-743.
[12]
JACKSON M D, HAMPSON G J, SAUNDERS J H, et al. Surface-based reservoir modelling for flow simulation[J]. Geological Society, London, Special Publications, 2014, 387(1): 271-292.
[13]
BENES B, FORSBACH R. Layered data representation for visual simulation of terrain erosion[C]// Proceedings spring conference on computer graphics. Budmerice, Slovakia: IEEE, 2001: 80-86.
[14]
HOULDING S W. 3D geoscience modeling: computer techniques for geological characterization[M]. Berlin, Heidelberg: Springer Science and Business Media, 2012.
[15]
李青元, 张丽云, 魏占营, 等. 三维地质建模软件发展现状及问题探讨[J]. 地质学刊, 2013, 37(4): 554-561.
[16]
LI F Y, GAO C L, LIU Y Q, et al. Integrated multi-scale reservoir data representation and indexing for reservoir data management and characterization[J]. Computers and Geosciences, 2020, 138: 104433.
[17]
HILL K M, SWIFT J N, HOWARD C, et al. 3D visualization of subsurface objects from La Brea tar pits, Los Angeles, CA[J]. Digital Applications in Archaeology and Cultural Heritage, 2021, 20: e00167.
[18]
蔡思敏, 任伟中, 冯亮, 等. 基于GTP-TEN的复杂地质体三维混合建模[J]. 岩石力学与工程学报, 2023, 42(2): 441-449.
[19]
SUN J X, LENZ D, YU H F, et al. MFA-DVR: direct volume rendering of mfa models[J]. Journal of Visualization, 2024, 27(1): 109-126.
[20]
QIN R F, FENG B, XU Z N, et al. Web-based 3D visualization framework for time-varying and large-volume oceanic forecasting data using open-source technologies[J]. Environmental Modelling and Software, 2021, 135: 104908.
[21]
YOUNG G, KRISHNAMURTHY A. GPU-accelerated generation and rendering of multi-level voxel representations of solid models[J]. Computers and Graphics, 2018, 75: 11-24.
[22]
熊祖强, 贺怀建, 夏艳华. 工程地质三维建模及分析系统设计研究[J]. 岩石力学与工程学报, 2007, 26(增刊2): 4176-4182.
[23]
陈良, 高成敏. 快速离散化双线性插值算法[J]. 计算机工程与设计, 2007, 28(15): 3787-3790.
[24]
GRACIANO A, RUEDA A J, FEITO F R. A formal framework for the representation of stack-based terrains[J]. International Journal of Geographical Information Science, 2018, 32(10): 1999-2022.
[25]
PASYANOS M E, MASTERS T G, LASKE G, et al. LITHO1.0: an updated crust and lithospheric model of the Earth[J]. Journal of Geophysical Research: Solid Earth, 2014, 119(3): 2153-2173.
[26]
GRACIANO A, RUEDA A J, FEITO F R. Real-time visualization of 3D terrains and subsurface geological structures[J]. Advances in Engineering Software, 2018, 115: 314-326.
[27]
孙黎明, 刘禹杉, 张睿卓, 等. 基于几何细分的三维地质模型自适应精细化构建方法[J]. 岩土工程学报, 2023, 45(增刊1): 244-248.
[28]
牛露佳, 王双威, 曾义文, 等. 基于规则网格的复杂断层网络处理与建模[J]. 地质论评, 2023, 69(5): 1980-1990.
[29]
YU J Q, WU L X, ZI G J, et al. SDOG-based multi-scale 3D modeling and visualization on global lithosphere[J]. Science China: Earth Sciences, 2012, 55(6): 1012-1020.
[30]
ZHONG S J, MCNAMARA A, TAN E, et al. A benchmark study on mantle convection in a 3-D spherical shell using CitcomS[J]. Geochemistry, Geophysics, Geosystems, 2008, 9(10): 1-32.
[31]
陈建平, 李靖, 谢帅, 等. 中国地质大数据研究现状[J]. 地质学刊, 2017, 41(3): 353-366.

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