
Preliminary study of HVSR forward modeling: parameters properties and non-uniqueness of subsurface models
Author(s) -
Ahmad Zaenudin,
Rustadi,
Iswan,
Ida Bagus Suananda Yogi
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1816/1/012063
Subject(s) - inversion (geology) , uniqueness , attenuation , amplitude , position (finance) , transfer function , function (biology) , mathematics , mathematical analysis , geology , physics , optics , seismology , electrical engineering , engineering , finance , economics , tectonics , evolutionary biology , biology
The application of horizontal to a vertical spectral ratio (HVSR) in Indonesia is often analyzed using theoretical equations that only focus on Vs. or the two rock layers’ thickness. On the other hand, there are already HVSR modeling programs that involve other parameters such as V P , density, Q P , and Qs for multiple layers. Armed with existing modeling, the effect of each parameter and test the possible non-uniqueness of HVSR modeling is found. In the end, the right inversion method to get satisfactory results is found. Modeling is done by calculating the wave amplification of the transfer function, the phenomenon of attenuation, and dispersion. A synthetic model will be made from the modeling scheme, which is approached with various possible parameters using a random test of 2 models for each test. From the existing parameters, it is found that only the parameters Vs, thickness, and Qs affect the position f 0 . Meanwhile, the parameters V P , density, and Q P only affect the amplitude of the curve. The parameters V P , Vs, density, and thickness have a consistent relationship between parameters, but not for Q P and Qs. From the various tests carried out, it was found that many combinations can produce similar responses, both parameter combinations, and combinations of parameters with a different number of layers. Inversion modeling is needed to produce a precise subsurface model that can reduce the non-uniqueness results, such as optimization with a global approach, a statistical approach, or a hybrid inversion method.