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  • Determination of Source Parameters of Simple-shaped Geologic Subsurface Structures from Self-potential Anomalies Using Enhanced Local Wavenumber Method.pdf.jpg
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  • Determination of Source Parameters of Simple-shaped Geologic Subsurface Structures from Self-potential Anomalies Using Enhanced Local Wavenumber Method

    • Authors: Pham, Thanh Luan; Vu, Duc Minh; Oksum, Erdinc (2019)

  • Simple geometry model structures can be useful in quantitative evaluation of selfpotential data. In this paper, we solve local wavenumber equation to estimate the horizontal position, the depth and the type of the causative source geometry by using a linear least-squares approximation. The advantages of the algorithm in determining the horizontal position and depth measure are its independency to shape factor of the sources and also its simple computations. The algorithm is built in Matlab environment. The validity of the algorithm is illustrated on variable noise-free and random noise included synthetic data from two-dimensional (2-D) models where the achieved parametric quantities ...

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Browsing by Subject A linear least-squares approximation

Jump to: 0-9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
or enter first few letters:  
Showing results 1 to 1 of 1
  • Determination of Source Parameters of Simple-shaped Geologic Subsurface Structures from Self-potential Anomalies Using Enhanced Local Wavenumber Method.pdf.jpg
  • Article

  • Determination of Source Parameters of Simple-shaped Geologic Subsurface Structures from Self-potential Anomalies Using Enhanced Local Wavenumber Method

    • Authors: Pham, Thanh Luan; Vu, Duc Minh; Oksum, Erdinc (2019)

  • Simple geometry model structures can be useful in quantitative evaluation of selfpotential data. In this paper, we solve local wavenumber equation to estimate the horizontal position, the depth and the type of the causative source geometry by using a linear least-squares approximation. The advantages of the algorithm in determining the horizontal position and depth measure are its independency to shape factor of the sources and also its simple computations. The algorithm is built in Matlab environment. The validity of the algorithm is illustrated on variable noise-free and random noise included synthetic data from two-dimensional (2-D) models where the achieved parametric quantities ...