Natural Resources Research

, Volume 28, Issue 1, pp 199–212 | Cite as

Assessment of Geochemical Anomaly Uncertainty Through Geostatistical Simulation and Singularity Analysis

  • Yue LiuEmail author
  • Qiuming Cheng
  • Emmanuel John M. Carranza
  • Kefa Zhou
Original Paper


Geochemical anomalies are commonly separated into different geochemical anomaly levels based on one or more thresholds. However, this practice may cause some important geochemical anomaly information to be lost and subsequently draw wrong decisions for mineral exploration. In addition, previous studies indicate that sparse geochemical sampling always entails uncertainty resulting from conventional geochemical interpolation methods because of smoothing effect. Uncertainty can propagate through the various steps of geochemical data analysis that may lead to significant impact on the final results (e.g., anomaly interpretation and mineral exploration). For geochemical anomaly identification, quantifying the probability of unsampled locations and characterizing the spatial uncertainty of geochemical anomaly based on (not) exceeding a key threshold is very important for practical demands such as exploration risk assessment. Considering the limitations of deterministic modeling method and geochemical anomaly assessment, this study proposes a new method of geochemical anomaly uncertainty assessment by combining geostatistical simulation and singularity analysis. A case study for Au anomaly uncertainty assessment is presented in the west Tianshan region (China) so as to verify the feasibility and effectiveness of the proposed method. The sequential Gaussian simulation was adopted to generate a set of equiprobable realizations that were subsequently employed to produce a series of corresponding singularity index realizations by means of singularity analysis. Critical thresholds of E-type singularity index (α) were determined by the method of singularity-quantile plot analysis, which were used to simulate the spatial uncertainty of Au anomaly in the study area. The results show that the risk probability of Au anomaly characterized by (not) exceedance of a critical threshold can be considered as an important reference for exploration decision-making and risk management.


Sequential Gaussian simulation Singularity analysis Geochemical anomaly separation Uncertainty assessment West Tianshan region 



We greatly appreciate the valuable comments of Associate Editor Dr. Renguang Zuo and two anonymous reviewers, which helped us improve the paper. This work was funded jointly by the project of CAS “Light of West China” program (No. 2015-XBQN-B-23), the project of China Postdoctoral Science Foundation (Nos. 2016M590992, 2018T111123), and the National Natural Science Foundation of China (Nos. 41702356, U1503291, 41430320).


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Copyright information

© International Association for Mathematical Geosciences 2018

Authors and Affiliations

  • Yue Liu
    • 1
    • 2
    • 3
    Email author
  • Qiuming Cheng
    • 4
  • Emmanuel John M. Carranza
    • 5
    • 6
  • Kefa Zhou
    • 1
    • 2
    • 3
  1. 1.State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and GeographyChinese Academy of SciencesÜrümqiChina
  2. 2.Xinjiang Research Centre for Mineral Resources, Xinjiang Institute of Ecology and GeographyChinese Academy of SciencesÜrümqiChina
  3. 3.Xinjiang Key Laboratory of Mineral Resources and Digital GeologyÜrümqiChina
  4. 4.State Key Laboratory of Geological Processes and Mineral ResourcesChina University of GeosciencesBeijingChina
  5. 5.Geological Sciences, School of Agriculture, Engineering and SciencesUniversity of KwaZulu-NatalDurbanSouth Africa
  6. 6.Economic Geology Research Centre (EGRU)James Cook UniversityTownsvilleAustralia

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