Search

Earth’s oxygenation history can be reconstructed using machine learning and mafic igneous geochemical data. Agreement with independent proxy predictions for surface conditions implies that interior processes are critical in atmospheric oxygenation.

Weights of evidence (WofE) and logistic regression (LR) are two loglinear methods for mineral potential mapping. Both models are limited by their respective basic assumptions in application. Ideally, WofE indicator patterns have the property of conditional independence (CI) with respect to the point pattern of mineral deposits to be predicted; in LR, there supposedly are no interactions between the point pattern and two or more of the indicator patterns. If the CI assumption is satisfied, estimated LR coefficients become approximately equal to WofE contrasts and the two methods produce similar results; additionally, bias then is avoided in that the sum of all estimated posterior probabilities becomes approximately equal to the number of observed discrete events. WofE allows construction of input layers that have missing data as a separate category in addition to known presence-absence type input, while logistic regression as such is not capable of handling missing data. As an improved WofE model based on LR, modified weights of evidence (MWofE) inherit the advantages of both LR and WofE, i.e., eliminates bias due to lack of CI and can handle missing data as well. Pixel or unit area input for MWofE consists of positive and negative weights for presence and absence of a pattern plus zeros for missing data. MWofE first is illustrated by application to simple examples. Next, it is applied to a study area with 20 known gold occurrences in southwestern Nova Scotia in relation to four input layers based on geological and lake geochemical data. Assuming that geochemical data were missing for the northern part of the study area, MWofE, like WofE but unlike LR, provides posterior probabilities for the entire area.

Abstract  This paper is concerned with the lognormal, and its logbinomial approximation, in connection with a three-parameter version of the model of de Wijs. The three parameters are: overall average element concentration value (ξ), dispersion index (d), and apparent number of subdivisions of the environment (N). Multifractal theory produces new methods for estimating the parameters of this model. In practical applications, the frequency distribution of element concentration values for small rock samples is related to self-similar spatial variability patterns of the element in large regions or segments of the Earth's crust. The approach is illustrated by application to spatial variability of gold and arsenic in glacial till samples from southern Saskatchewan. It is shown that for these two elements the model of de Wijs is satisfied on a regional scale but degree of dispersion decreases rapidly toward the local, sample-size scale. Thus the apparent number of subdivisions (N) is considerably less than would be expected if degree of dispersion were to extend from regional to local scale. A random-cut variant of the model of de Wijs produces an empirical frequency distribution of relative element concentration values that can be related to random dispersion index [ABSTRACT FROM AUTHOR]

Geochemical anomaly identification in areas with overburden is a challenging task because primary geochemical anomaly signals from buried mineralization could be masked by cover layers, and could also be overprinted by various pseudo-geochemical anomalies formed by mobile elements. In this study, porphyry Cu-Mo deposits in the Gobi desert, a covered geographical landscape of Eastern Tianshan, China, are taken as an example to illustrate delineation of significant geochemical anomalies in covered area. Firstly, element behavior was analyzed by means of accumulation coefficient (AC) analysis for investigating possible mobility of elements to assist in determining a set of suitable indicator elements including Cu, Mo, Pb and Zn for porphyry Cu-Mo mineralization. Next, the singularity mapping technique was employed to recognize weak geochemical anomaly signals of the indicator elements. Finally, single element geochemical anomalies were normalized and combined to derive a comprehensive geochemical anomaly, and Student's t-statistic was used to quantitatively estimate the spatial relationship between the integrated geochemical anomaly and known porphyry Cu-Mo deposits for classifying and grading the anomaly in order to delineate potential porphyry Cu-Mo prospects for future exploration in the study area. It is concluded that: (1) AC analysis is an easy and efficient method to characterize enrichment or depletion of elements in different geological units for determining probable mobility of elements; (2) there exists a strong genetic relationship of geochemical composition between bedrock and Gobi desert cover in the Eastern Tianshan region; (3) it is important to analyze element behavior for identifying principal geochemical anomalies in overburden as found in the Gobi desert; (4) singularity mapping is a proper method to delineate weak geochemical anomalies in overburden; and (5) there is probably a high potential to discover buried porphyry Cu-Mo deposits beneath identified anomalies with or without associated known porphyry Cu-Mo deposits. [ABSTRACT FROM AUTHOR]