Assessment of Geochemical Anomaly Uncertainty Through Geostatistical Simulation and Singularity Analysis

Liu, Yue; Cheng, Qiuming; Carranza, Emmanuel John M.; Zhou, Kefa

doi:10.1007/s11053-018-9388-1

Cited by 34 publications

(8 citation statements)

References 58 publications

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“…(e) Uncertainty arising from the interpolation of geochemical data . Stochastic simulation could be used to quantify such type of uncertainty, and novel metrics summarizing the uncertain results, can be derived to enable more robust identification of geochemical signatures (e.g., Liu et al., 2019; Wang & Zuo, 2018). Importantly, we can also use other thematic data or non‐structural information, such as remote sensing imagery, geochemical data from a different medium, and geological texts, to constrain or validate the geochemical mapping results, and reduce their uncertainties indirectly (e.g., Kirkwood et al., 2016; Zuo, Wang, & Yin, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…In the context of geochemical mapping, the primary concerns are local uncertainty and spatial uncertainty (Goovaerts, 2001). Local uncertainty is usually visualized by heatmaps, which encode uncertainty magnitude through color variations (e.g., Liu et al., 2019; Sadeghi et al., 2015). Spatial uncertainty, which is high‐dimensional, can be visualized by the distance‐based method (Figure 8).…”

Section: Uncertainty Visualization and Assessmentmentioning

confidence: 99%

“…A data set consisting of 3336 stream sediment samples with a density of ∼1 sample per 4 km 2 was compiled for analysis in this study. We accounted for the local and spatial uncertainties from the grinding process of geochemical point data, which affect the mapping of geochemical signatures, as shown by Wang and Zuo (2018) and Liu et al (2019).…”

Section: Case Studymentioning

confidence: 99%

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Uncertainty Quantification in Geochemical Mapping: A Review and Recommendations

Wang,

Zuo

2024

Geochem Geophys Geosyst

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Geochemical mapping is a crucial tool that can provide valuable insights for a wide range of applications, including mineral resources prospecting, environmental impact assessment, geological process understanding, and climate change research. Despite its significance, geochemical mapping requires spatial modeling based on sparse, heterogeneous, and potentially inaccurate data sets. Moreover, the underlying geological processes are often imperfectly understood. Therefore, uncertainty quantification (UQ) is vital in geochemical mapping to ensure accurate and reliable results, ultimately facilitating well‐informed decision‐making. In this contribution, we distinguish two primary types of uncertainties: systemic and stochastic. We identify the key sources of uncertainties in geochemical mapping and review the techniques that have been employed or hold potential for uncertainty quantification, communication, visualization, and sensitivity analysis. This contribution also illustrates the general procedure of UQ in geochemical mapping by a case study of mapping geochemical anomalies associated with gold mineralization in northwestern Sichuan Province, China. We also explore potential strategies for mitigating the critical uncertainties, such as gathering more geochemical data, developing more effective models, enhancing our understanding of the geochemical dispersion process, or leveraging other thematic information or knowledge. Future research should prioritize addressing underexplored uncertainties and implementing more practical applications to validate the UQ procedure in geochemical mapping.

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Section: Discussionmentioning

confidence: 99%

Section: Uncertainty Visualization and Assessmentmentioning

confidence: 99%

Section: Case Studymentioning

confidence: 99%

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Uncertainty Quantification in Geochemical Mapping: A Review and Recommendations

Wang,

Zuo

2024

Geochem Geophys Geosyst

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“…In summary, it can be said that singularity method is better in separation of Pb-Zn anomalies than the C-A method and spectrum-arS-Aea method. The importance of the singularity method in separating weak anomalies has been highlighted in other [26], Wang and Zuo [27,28], Liu et al [29], and Ersoy and Yunsel [30].…”

Section: Coefficient Of Areal Associationmentioning

confidence: 97%

Application of Finite Difference Method in Multifractal Techniques to Identify Pb–Zn Anomalies: a Case Study from Khomein, Iran

Khavari

Ghadimi

Mojeddifar

2020

Mining, Metallurgy & Exploration

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Separation of geochemical anomalies from background is an important and essential issue in the exploration of mineral deposits. Statistical methods are used to separation of anomaly from background. Fractal/multifractal and singularity methods are very suitable for the separation of weak anomalies. For interpolation, various methods could be used such as most distance-weighting methods, kriging, spline interpolation, interpolating polynomials, and finite difference methods. This paper addressed application of multifractal techniques together with finite difference procedure to detect the anomalous regions. Fractal models such as concentration-area, spectrum-area, and singularity index model were selected to identify Pb-Zn anomalies. In this research, 170 samples from 33 boreholes were taken in the Haft-Savaran area and analyzed for determination of Pb-Zn anomaly. Singularity method was a suitable method for separating Pb and Zn anomalies. Also, the results showed that the geochemical anomaly has occurred along NE-SW trend and is consistent with the sulfide mineralization process and the faults of the region.

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“…These haloes extend like the pod around the deposit. The shape and extent of expansion of these haloes depend on several factors, such as the form and amount of mineral deposit, the content of mineral reservoir, and the kind of host rock [9][10][11][12][13][14][15][16][17][18] .…”

Section: Introductionmentioning

confidence: 99%

Comparison of U-spatial statistics method with Classical Statistics results in the determination of geochemical anomalies of Epithermal Gold in Khoshnameh area, Hashtjin, Iran

Seyedrahimi-Niaraq

2021

j. of geol. res.

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In this study, methods based on the distribution model (with and without personal opinion) were used for the separation of anomalous zones, which include two different methods of U-spatial statistics and mean plus values of standard deviation (). The primary purpose is to compare the results of these methods with each other. To increase the accuracy of comparison, regional geochemical data were used where occurrences and mineralization zones of epithermal gold have been introduced. The study area is part of the Hashtjin geological map, which is structurally part of the folded and thrust belt and part of the Alborz Tertiary magmatic complex. Samples were taken from secondary lithogeochemical environments. Au element data concerning epithermal gold reserves were used to investigate the efficacy of these two methods. In the U- spatial statistics method, and criteria were used to determine the threshold, and in the method, the element enrichment index of the region rock units was obtained with grouping these units. The anomalous areas were identified by, and criteria. Comparison of methods was made considering the position of discovered occurrences and the occurrences obtained from these methods, the flexibility of the methods in separating the anomalous zones, and the two-dimensional spatial correlation of the three elements As, Pb, and Ag with Au element. The ability of two methods to identify potential areas is acceptable. Among these methods, it seems the method with criteria has a high degree of flexibility in separating anomalous regions in the case of epithermal type gold deposits.

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Assessment of Geochemical Anomaly Uncertainty Through Geostatistical Simulation and Singularity Analysis

Cited by 34 publications

References 58 publications

Uncertainty Quantification in Geochemical Mapping: A Review and Recommendations

Uncertainty Quantification in Geochemical Mapping: A Review and Recommendations

Application of Finite Difference Method in Multifractal Techniques to Identify Pb–Zn Anomalies: a Case Study from Khomein, Iran

Comparison of U-spatial statistics method with Classical Statistics results in the determination of geochemical anomalies of Epithermal Gold in Khoshnameh area, Hashtjin, Iran

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