Book Chapter10.1007/978-3-030-26050-7_6-1
Computational Geoscience
Xi-An Li
- 01 Jan 2022
- pp 1-22
2
TL;DR: In this paper , a systematic approach to the evaluation of geochemical data involves the use of multivariate methods that identify processes, represented by element associations that reflect mineralogy, which can be used to enhance the signal/noise ratio in the data.
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Abstract: A systematic approach to the evaluation of geochemical data involves the use of multivariate methods that identify processes. These processes are represented by element associations that reflect mineralogy. Processes may be linear or nonlinear, depending on the type of process. Different metrics can reflect different processes. Metrics with coordinates derived from principal component analysis, independent component analysis, and t-distributed stochastic embedding, to name a few, reflect different processes. The dominant components of these metrics can be used to enhance the signal/noise ratio in the data. An integral part of process discovery is the geospatial coherence of multivariate signatures. Models can be constructed by tagging the dominant components with attributes such as geology or mineral deposit information. These models can be tested using a range of multivariate classification/validation/prediction procedures from which probability-based measures of likelihood can be determined and displayed geospatially. The application of these techniques requires acknowledgment of the limitations inherent in the data.
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References
Independent component analysis, a new concept?
TL;DR: An efficient algorithm is proposed, which allows the computation of the ICA of a data matrix within a polynomial time and may actually be seen as an extension of the principal component analysis (PCA).
9K
Multivariable geostatistics in S: the gstat package $
TL;DR: The gstat S package is introduced, an extension package for the S environments (R, S-Plus) that provides multivariable geostatistical modelling, prediction and simulation, as well as several visualisation functions.
3K
Isometric Logratio Transformations for Compositional Data Analysis
TL;DR: An important result is the decomposition of the simplex, as a vector space, into orthogonal subspaces associated with nonoverlapping subcompositions, which gives the key to join compositions with different parts into a single composition by using a balancing element.
1.8K
The separation of geochemical anomalies from background by fractal methods
TL;DR: In this paper, a log-log plots for element concentration-area and perimeter-area relations were employed to separate geochemically anomalous areas from background, where the values used for perimeters and areas are the lengths and enclosed areas of geochemical isopleths obtained by interpolation.
897
Integrated Spatial and Spectrum Method for Geochemical Anomaly Separation
TL;DR: In this paper, a new approach for separating geochemical anomalies from background has been developed on the basis of integration of spatial and spectrum analysis, where a map generated from geochemical data can be transformed into a frequency domain in which a spatial concentration-area fractal method can be applied to distinguish the patterns based on the power-spectrum distribution.
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