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Source parameters estimation from gravity data using Bat algorithm with application to geothermal and volcanic activity studies
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DOI：10.1007/s13762-022-04263-z.png)
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Recently gravity data modeling plays an important role in the study of volcanic activity and geothermal investigation. Generally, gravity data modeling assumes the subsurface either homogenous or spatially variable densities within modeled source rocks and surrounding sediments. As a result, the subsurface geothermal and volcanic goals and targets are included and validated using simple-geometric sources in gravity data modeling. The Bat algorithm, which is considered one of the most recently, developed metaheuristic algorithms in geophysics applications, permits to discovery and delineation of the source's parameters. Here, we presented the contribution of the Bat algorithm technique in elucidating 2D gravity profiles for geothermal exploration and volcanic activity cases. The Bat algorithm is based on the echo-location behavior of bats to perform global optimization. The Bat optimization algorithm is applied to 2D gravity data to estimate the source's parameters such as depth, origin location, amplitude factor, and geometric shape of the causative buried body. The stability and efficiency of the introduced optimizing algorithm were checked to different synthetic cases, i.e., for model 1, which represents a horizontal cylinder model, and model 2 represents a multi-sources effect. Furthermore, the successful applications of the proposed algorithm for discovering the geothermal and volcanic activities in Japan and India were have presented. The obtained results are in good agreement with the available geological, geophysical, and borehole information.
Keyword:
Bat algorithm
Geothermal investigation
Gravity anomaly
Source depth
Volcanic activity
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3.4
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7.9K
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