GRAVITY ANOMALY SEPARATION USING A COMBINATION OF GAUSSIAN AND BIDIMENSIONAL EMPIRICAL MODE DECOMPOSITION (BEMD) METHODS
The separation of regional and residual components in the analysis of geological features through gravity methods is a widely employed technique by geoscientists worldwide. Although gravity anomaly separation methods have been continuously improving, no single method can be considered an absolute...
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id-itb.:775342023-09-08T13:50:30ZGRAVITY ANOMALY SEPARATION USING A COMBINATION OF GAUSSIAN AND BIDIMENSIONAL EMPIRICAL MODE DECOMPOSITION (BEMD) METHODS Sahrul Indonesia Theses gravity, regional anomaly, residual anomaly, Gaussian, BEMD, noise INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/77534 The separation of regional and residual components in the analysis of geological features through gravity methods is a widely employed technique by geoscientists worldwide. Although gravity anomaly separation methods have been continuously improving, no single method can be considered an absolute solution for obtaining the most accurate information about geological features. Therefore, there is always scope for refinement and further enhancement. The obstacle experienced by interpreters in interpreting geophysical data, especially gravity methods, is noise contamination in gravity data caused by geological features or errors in data acquisition. Therefore, in this research conducted various methods to separate gravity anomalies, such as the Gaussian filter, Bidimensional Empirical Mode Decomposition (BEMD), and a combination of Gaussian and BEMD techniques. The findings show that the integration of the Gaussian and BEMD methods proved to be more efficient in characterizing the near-surface gravity anomaly features in synthetic gravity data models containing noise, this conclusion is supported by the observed patterns and relatively lower Root Mean Square Error (RMSE) values, one example in the prismatic synthetic model I has an RMSE value of 0.1672, lower by 0.0237 and 0.4311 compared to the results of the Gaussian and BEMD methods respectively at 10% noise percentage noise, as well as with higher noise percentages of 20% and 30%. The next step is the application of the methods to the CBA data of the Kadidia region, which is a geothermal potential area in Central Sulawesi, Indonesia. The results obtained indicate that the integration of the Gaussian and BEMD methods is better at depicting the structure with the NW-SE trend and other structures with the NE-SW trend. Additionally, the obtained results also align with the position of the hot water manifestations situated at the boundary of low anomaly contrast and high anomaly contrast. As a result, this research offers enhanced opportunities for interpreting gravity anomalies more effectively. The procedure adopted in this study was developed utilizing the MATLAB programming language. text |
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The separation of regional and residual components in the analysis of geological
features through gravity methods is a widely employed technique by geoscientists
worldwide. Although gravity anomaly separation methods have been continuously
improving, no single method can be considered an absolute solution for obtaining
the most accurate information about geological features. Therefore, there is always
scope for refinement and further enhancement. The obstacle experienced by
interpreters in interpreting geophysical data, especially gravity methods, is noise
contamination in gravity data caused by geological features or errors in data
acquisition. Therefore, in this research conducted various methods to separate
gravity anomalies, such as the Gaussian filter, Bidimensional Empirical Mode
Decomposition (BEMD), and a combination of Gaussian and BEMD techniques.
The findings show that the integration of the Gaussian and BEMD methods proved
to be more efficient in characterizing the near-surface gravity anomaly features in
synthetic gravity data models containing noise, this conclusion is supported by the
observed patterns and relatively lower Root Mean Square Error (RMSE) values,
one example in the prismatic synthetic model I has an RMSE value of 0.1672, lower
by 0.0237 and 0.4311 compared to the results of the Gaussian and BEMD methods
respectively at 10% noise percentage noise, as well as with higher noise
percentages of 20% and 30%. The next step is the application of the methods to the
CBA data of the Kadidia region, which is a geothermal potential area in Central
Sulawesi, Indonesia. The results obtained indicate that the integration of the
Gaussian and BEMD methods is better at depicting the structure with the NW-SE
trend and other structures with the NE-SW trend. Additionally, the obtained results
also align with the position of the hot water manifestations situated at the boundary
of low anomaly contrast and high anomaly contrast. As a result, this research offers
enhanced opportunities for interpreting gravity anomalies more effectively. The
procedure adopted in this study was developed utilizing the MATLAB programming
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Sahrul GRAVITY ANOMALY SEPARATION USING A COMBINATION OF GAUSSIAN AND BIDIMENSIONAL EMPIRICAL MODE DECOMPOSITION (BEMD) METHODS |
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title |
GRAVITY ANOMALY SEPARATION USING A COMBINATION OF GAUSSIAN AND BIDIMENSIONAL EMPIRICAL MODE DECOMPOSITION (BEMD) METHODS |
title_short |
GRAVITY ANOMALY SEPARATION USING A COMBINATION OF GAUSSIAN AND BIDIMENSIONAL EMPIRICAL MODE DECOMPOSITION (BEMD) METHODS |
title_full |
GRAVITY ANOMALY SEPARATION USING A COMBINATION OF GAUSSIAN AND BIDIMENSIONAL EMPIRICAL MODE DECOMPOSITION (BEMD) METHODS |
title_fullStr |
GRAVITY ANOMALY SEPARATION USING A COMBINATION OF GAUSSIAN AND BIDIMENSIONAL EMPIRICAL MODE DECOMPOSITION (BEMD) METHODS |
title_full_unstemmed |
GRAVITY ANOMALY SEPARATION USING A COMBINATION OF GAUSSIAN AND BIDIMENSIONAL EMPIRICAL MODE DECOMPOSITION (BEMD) METHODS |
title_sort |
gravity anomaly separation using a combination of gaussian and bidimensional empirical mode decomposition (bemd) methods |
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https://digilib.itb.ac.id/gdl/view/77534 |
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