Multivariate Statistical Analysis and S-A Multifractal Modeling of Lithogeochemical Data for Mineral Exploration: A Case Study from the Buerhantu Area, Hadamengou Gold Orefield, Inner Mongolia, China

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Publicado en:Geosciences vol. 15, no. 12 (2025), p. 473-508
Autor principal: Fan Songhao
Otros Autores: Wang, Da, Yang, Biao, Ma Huchao, Su Rilige, Chen, Lei, Su Panyun, Hou Xiuhong, Lv Hanqin, Xia Zhiwei
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024 7 |a 10.3390/geosciences15120473  |2 doi 
035 |a 3286299830 
045 2 |b d20251201  |b d20251231 
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100 1 |a Fan Songhao  |u Hohhot General Survey of Natural Resources Center, China Geological Survey, Hohhot 010010, China; fansonghao@mail.cgs.gov.cn (S.F.); surili@mail.cgs.gov.cn (R.S.); chenlei01@mail.cgs.gov.cn (L.C.); supanyun@mail.cgs.gov.cn (P.S.); houxiuhong@mail.cgs.gov.cn (X.H.); lvhanqin@mail.cgs.gov.cn (H.L.); wwenjie@mail.cgs.gov.cn (Z.X.) 
245 1 |a Multivariate Statistical Analysis and S-A Multifractal Modeling of Lithogeochemical Data for Mineral Exploration: A Case Study from the Buerhantu Area, Hadamengou Gold Orefield, Inner Mongolia, China 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a The Hadamengou gold deposit, located on the northern margin of the North China Craton, represents one of the region‘s most significant gold mineralization clusters. However, exploration in its deeper and peripheral sectors is constrained by ecological protection policies and the structural complexity of the ore-forming systems. Multivariate analysis combined with multi-model integration provides an effective mathematical approach for interpretating geochemical datasets and guiding mineral exploration, yet, its application in the Hadamengou region has not been systematically investigated. To address this research gap, this study developed a pilot framework in the key Buerhantu area, on the periphery of the Hadamengou metallogenic cluster, applying and adapting a multivariate-multimodel methodology for mineral prediction. The goal is to improve exploration targeting, particularly for concealed and deep-seated mineralization, while addressing the methodological challenges of mathematical modeling in complex geological conditions. Using 1:10,000-scale lithogeochemical data, we implemented a three-step workflow. First, isometric log-ratio (ILR) and centered log-ratio (CLR) transformations were compared to optimize data preprocessing, with a reference column (YD) added to overcome ILR constraints. Second, principal component analysis (PCA) identified a metallogenic element association (Sb-As-Sn-Au-Ag-Cu-Pb-Mo-W-Bi) consistent with district-scale mineralization patterns. Third, S-A multifractal modeling of factor scores (F1–F4) effectively separated noise, background, and anomalies, producing refined geochemical maps. Compared with conventional inverse distance weighting (IDW), the S-A model enhanced anomaly delineation and exploration targeting. Five anomalous zones (AP01–AP05) were identified. Drilling at AP01 confirmed the presence of deep gold mineralization, and the remaining anomalies are recommended for surface verification. This study demonstrates the utility of S-A multifractal modeling for geochemical anomaly detection and its effectiveness in defining exploration targets and improving exploration efficiency in underexplored areas of the Hadamengou district. 
651 4 |a China 
651 4 |a Mongolia 
653 |a Mineral exploration 
653 |a Principal components analysis 
653 |a Copper 
653 |a Multivariate analysis 
653 |a Geochemistry 
653 |a Gold 
653 |a Background noise 
653 |a Quartz 
653 |a Effectiveness 
653 |a Multivariate statistical analysis 
653 |a Anomalies 
653 |a Statistical methods 
653 |a Mineralization 
653 |a Mineral deposits 
653 |a Silver 
653 |a Accuracy 
653 |a Fault lines 
653 |a Modelling 
653 |a Antimony 
653 |a Data processing 
653 |a Statistical analysis 
653 |a Isometric 
653 |a Drilling 
653 |a Cratons 
653 |a Complexity 
653 |a Mathematical models 
653 |a Lithogeochemistry 
653 |a Minerals 
653 |a Tin 
653 |a Metallogenesis 
700 1 |a Wang, Da  |u School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China; 3101220009@email.cugb.edu.cn 
700 1 |a Yang, Biao  |u Hohhot General Survey of Natural Resources Center, China Geological Survey, Hohhot 010010, China; fansonghao@mail.cgs.gov.cn (S.F.); surili@mail.cgs.gov.cn (R.S.); chenlei01@mail.cgs.gov.cn (L.C.); supanyun@mail.cgs.gov.cn (P.S.); houxiuhong@mail.cgs.gov.cn (X.H.); lvhanqin@mail.cgs.gov.cn (H.L.); wwenjie@mail.cgs.gov.cn (Z.X.) 
700 1 |a Ma Huchao  |u School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China; 3101220009@email.cugb.edu.cn 
700 1 |a Su Rilige  |u Hohhot General Survey of Natural Resources Center, China Geological Survey, Hohhot 010010, China; fansonghao@mail.cgs.gov.cn (S.F.); surili@mail.cgs.gov.cn (R.S.); chenlei01@mail.cgs.gov.cn (L.C.); supanyun@mail.cgs.gov.cn (P.S.); houxiuhong@mail.cgs.gov.cn (X.H.); lvhanqin@mail.cgs.gov.cn (H.L.); wwenjie@mail.cgs.gov.cn (Z.X.) 
700 1 |a Chen, Lei  |u Hohhot General Survey of Natural Resources Center, China Geological Survey, Hohhot 010010, China; fansonghao@mail.cgs.gov.cn (S.F.); surili@mail.cgs.gov.cn (R.S.); chenlei01@mail.cgs.gov.cn (L.C.); supanyun@mail.cgs.gov.cn (P.S.); houxiuhong@mail.cgs.gov.cn (X.H.); lvhanqin@mail.cgs.gov.cn (H.L.); wwenjie@mail.cgs.gov.cn (Z.X.) 
700 1 |a Su Panyun  |u Hohhot General Survey of Natural Resources Center, China Geological Survey, Hohhot 010010, China; fansonghao@mail.cgs.gov.cn (S.F.); surili@mail.cgs.gov.cn (R.S.); chenlei01@mail.cgs.gov.cn (L.C.); supanyun@mail.cgs.gov.cn (P.S.); houxiuhong@mail.cgs.gov.cn (X.H.); lvhanqin@mail.cgs.gov.cn (H.L.); wwenjie@mail.cgs.gov.cn (Z.X.) 
700 1 |a Hou Xiuhong  |u Hohhot General Survey of Natural Resources Center, China Geological Survey, Hohhot 010010, China; fansonghao@mail.cgs.gov.cn (S.F.); surili@mail.cgs.gov.cn (R.S.); chenlei01@mail.cgs.gov.cn (L.C.); supanyun@mail.cgs.gov.cn (P.S.); houxiuhong@mail.cgs.gov.cn (X.H.); lvhanqin@mail.cgs.gov.cn (H.L.); wwenjie@mail.cgs.gov.cn (Z.X.) 
700 1 |a Lv Hanqin  |u Hohhot General Survey of Natural Resources Center, China Geological Survey, Hohhot 010010, China; fansonghao@mail.cgs.gov.cn (S.F.); surili@mail.cgs.gov.cn (R.S.); chenlei01@mail.cgs.gov.cn (L.C.); supanyun@mail.cgs.gov.cn (P.S.); houxiuhong@mail.cgs.gov.cn (X.H.); lvhanqin@mail.cgs.gov.cn (H.L.); wwenjie@mail.cgs.gov.cn (Z.X.) 
700 1 |a Xia Zhiwei  |u Hohhot General Survey of Natural Resources Center, China Geological Survey, Hohhot 010010, China; fansonghao@mail.cgs.gov.cn (S.F.); surili@mail.cgs.gov.cn (R.S.); chenlei01@mail.cgs.gov.cn (L.C.); supanyun@mail.cgs.gov.cn (P.S.); houxiuhong@mail.cgs.gov.cn (X.H.); lvhanqin@mail.cgs.gov.cn (H.L.); wwenjie@mail.cgs.gov.cn (Z.X.) 
773 0 |t Geosciences  |g vol. 15, no. 12 (2025), p. 473-508 
786 0 |d ProQuest  |t Publicly Available Content Database 
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