Semiautomated quantification of the influence of data richness on confidence in the geologic interpretation of aeromagnetic maps

    Research output: Contribution to journalArticle

    8 Citations (Scopus)

    Abstract

    Geologic interpretations of aeromagnetic maps are highly subjective but are rarely accompanied by a quantitative confidence assessment, which is a key limitation on the usefulness of the results. Here, we outline a method with which the relative level of data richness can be assessed quantitatively, leading to an improved understanding of spatial variations in interpretational confidence. Simple rules were used to quantify the likely influence of several major sources of uncertainty. These were: (1) the level of geologic constraint, using the local abundance of outcropping rock and the quality of geologic mapping; (2) the interpretability of the aeromagnetic data, considering the strength of edge-like features and the degree of directionality of these features, a proxy for structural complexity; (3) data collection and processing errors, including gridding errors, derived from the statistical error returned during kriging, and the influence of anisotropic line data collection on the detection of gradients. From these individual sources of uncertainty, an overall data richness map was generated through a weighted summation of these grids. Weightings were assigned so as to best match the result to the interpreter's perception of interpretational confidence. This method produced a map of data richness, which reflects the opportunity that the data provided to the interpreter to make a correct interpretation. An example from central Australia indicated that the data influences were preserved over a moderate range of weighting factors, and that strong bias was required to override these. In addition to providing a confidence assessment, this method also provides a way to test the potential benefits of additional data collection. © 2013 Society of Exploration Geophysicists.
    Original languageEnglish
    Pages (from-to)J1-J13
    JournalGeophysics
    Volume78
    Issue number2
    DOIs
    Publication statusPublished - 2013

    Fingerprint

    confidence
    kriging
    Rocks
    grids
    rocks
    Processing
    gradients
    aeromagnetic survey
    spatial variation
    Uncertainty
    rock
    method

    Cite this

    @article{86fe8b7edf2549d6b2832ea1dcc75611,
    title = "Semiautomated quantification of the influence of data richness on confidence in the geologic interpretation of aeromagnetic maps",
    abstract = "Geologic interpretations of aeromagnetic maps are highly subjective but are rarely accompanied by a quantitative confidence assessment, which is a key limitation on the usefulness of the results. Here, we outline a method with which the relative level of data richness can be assessed quantitatively, leading to an improved understanding of spatial variations in interpretational confidence. Simple rules were used to quantify the likely influence of several major sources of uncertainty. These were: (1) the level of geologic constraint, using the local abundance of outcropping rock and the quality of geologic mapping; (2) the interpretability of the aeromagnetic data, considering the strength of edge-like features and the degree of directionality of these features, a proxy for structural complexity; (3) data collection and processing errors, including gridding errors, derived from the statistical error returned during kriging, and the influence of anisotropic line data collection on the detection of gradients. From these individual sources of uncertainty, an overall data richness map was generated through a weighted summation of these grids. Weightings were assigned so as to best match the result to the interpreter's perception of interpretational confidence. This method produced a map of data richness, which reflects the opportunity that the data provided to the interpreter to make a correct interpretation. An example from central Australia indicated that the data influences were preserved over a moderate range of weighting factors, and that strong bias was required to override these. In addition to providing a confidence assessment, this method also provides a way to test the potential benefits of additional data collection. {\circledC} 2013 Society of Exploration Geophysicists.",
    author = "Alan Aitken and Eun-Jung Holden and Mike Dentith",
    year = "2013",
    doi = "10.1190/GEO2012-0033.1",
    language = "English",
    volume = "78",
    pages = "J1--J13",
    journal = "Geophysics",
    issn = "0016-8033",
    publisher = "SOC EXPLORATION GEOPHYSICISTS",
    number = "2",

    }

    TY - JOUR

    T1 - Semiautomated quantification of the influence of data richness on confidence in the geologic interpretation of aeromagnetic maps

    AU - Aitken, Alan

    AU - Holden, Eun-Jung

    AU - Dentith, Mike

    PY - 2013

    Y1 - 2013

    N2 - Geologic interpretations of aeromagnetic maps are highly subjective but are rarely accompanied by a quantitative confidence assessment, which is a key limitation on the usefulness of the results. Here, we outline a method with which the relative level of data richness can be assessed quantitatively, leading to an improved understanding of spatial variations in interpretational confidence. Simple rules were used to quantify the likely influence of several major sources of uncertainty. These were: (1) the level of geologic constraint, using the local abundance of outcropping rock and the quality of geologic mapping; (2) the interpretability of the aeromagnetic data, considering the strength of edge-like features and the degree of directionality of these features, a proxy for structural complexity; (3) data collection and processing errors, including gridding errors, derived from the statistical error returned during kriging, and the influence of anisotropic line data collection on the detection of gradients. From these individual sources of uncertainty, an overall data richness map was generated through a weighted summation of these grids. Weightings were assigned so as to best match the result to the interpreter's perception of interpretational confidence. This method produced a map of data richness, which reflects the opportunity that the data provided to the interpreter to make a correct interpretation. An example from central Australia indicated that the data influences were preserved over a moderate range of weighting factors, and that strong bias was required to override these. In addition to providing a confidence assessment, this method also provides a way to test the potential benefits of additional data collection. © 2013 Society of Exploration Geophysicists.

    AB - Geologic interpretations of aeromagnetic maps are highly subjective but are rarely accompanied by a quantitative confidence assessment, which is a key limitation on the usefulness of the results. Here, we outline a method with which the relative level of data richness can be assessed quantitatively, leading to an improved understanding of spatial variations in interpretational confidence. Simple rules were used to quantify the likely influence of several major sources of uncertainty. These were: (1) the level of geologic constraint, using the local abundance of outcropping rock and the quality of geologic mapping; (2) the interpretability of the aeromagnetic data, considering the strength of edge-like features and the degree of directionality of these features, a proxy for structural complexity; (3) data collection and processing errors, including gridding errors, derived from the statistical error returned during kriging, and the influence of anisotropic line data collection on the detection of gradients. From these individual sources of uncertainty, an overall data richness map was generated through a weighted summation of these grids. Weightings were assigned so as to best match the result to the interpreter's perception of interpretational confidence. This method produced a map of data richness, which reflects the opportunity that the data provided to the interpreter to make a correct interpretation. An example from central Australia indicated that the data influences were preserved over a moderate range of weighting factors, and that strong bias was required to override these. In addition to providing a confidence assessment, this method also provides a way to test the potential benefits of additional data collection. © 2013 Society of Exploration Geophysicists.

    U2 - 10.1190/GEO2012-0033.1

    DO - 10.1190/GEO2012-0033.1

    M3 - Article

    VL - 78

    SP - J1-J13

    JO - Geophysics

    JF - Geophysics

    SN - 0016-8033

    IS - 2

    ER -