A new integrated 3D modeling method based on multisource heterogeneous geological data and its application

IF 5.1 3区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
China Geology Pub Date : 2026-04-01 Epub Date: 2026-05-22 DOI:10.31035/cg2024063
Zhao-yang Ma , Sen Zhang , Jie Li , Ya-kai Qiao , Hua-feng Sun , Fateh Bouchaala
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引用次数: 0

Abstract

With continuous advancement in geological studies, three-dimensional (3D) geological modeling technology based on big data and artificial intelligence (AI) has become a prominent focus in the interdisciplinary field of earth and information sciences. Through the analysis and comparison of existing 3D modeling methods, this study introduces a high-precision 3D geological modeling approach. The new method leverages advanced computing technologies, including multisource heterogeneous data processing, integrated model databases, seamless splicing of local models, and cluster analysis. Furthermore, it enables unified 3D visualization of subsurface and surface conditions, providing new insights into disaster prevention, mitigation, and intelligent mineral exploration. To validate its practicality, this study conducts 3D geological modeling of the X area within the Sichuan Basin, China. The data sources include remote sensing images, geological maps, geophysical data, borehole data, and X-ray fluorescence (XRF) spectroscopy data. Preliminary exploration in the X area has successfully identified new mineralization belts, verifying the feasibility and effectiveness of the new 3D geological modeling method that integrates big data processing and intelligent techniques.
基于多源非均质地质数据的三维综合建模新方法及其应用
随着地质研究的不断深入,基于大数据和人工智能的三维地质建模技术已成为地球与信息科学交叉领域的突出热点。通过对现有三维建模方法的分析和比较,提出了一种高精度三维地质建模方法。新方法利用了先进的计算技术,包括多源异构数据处理、集成模型数据库、局部模型无缝拼接和聚类分析。此外,它还可以实现地下和地表条件的统一3D可视化,为防灾、减灾和智能矿产勘探提供新的见解。为了验证其实用性,本研究对四川盆地X地区进行了三维地质建模。数据来源包括遥感图像、地质图、地球物理数据、钻孔数据和x射线荧光(XRF)光谱数据。X地区初步勘查成功发现新的成矿带,验证了大数据处理与智能技术相结合的三维地质建模新方法的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
China Geology
China Geology GEOLOGY-
CiteScore
7.80
自引率
11.10%
发文量
275
审稿时长
16 weeks
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