Microtremor Data Research Articles

Characterizing Egyptian National Seismic Network station sites using genetic optimization for microtremor data inversion

Characterizing Egyptian National Seismic Network station sites using genetic optimization for microtremor data inversion

Are the Horizontal-to-Vertical Spectral Ratios of Earthquakes and Microtremors the Same?

ABSTRACT We consider the similarities and differences between earthquake and microtremor horizontal-to-vertical spectral ratios (eHVSR and mHVSR, respectively) using a dataset of 161 sites in southern California. Quantitative comparisons are made in terms of the eHVSR and mHVSR lognormal median curves, as well as the frequencies and amplitudes associated with the fundamental- and higher-mode resonances where present. The results show only 58% of the eHVSR–mHVSR pairs agree in terms of their median curve and only 25% of the eHVSR–mHVSR pairs agree in terms of shared resonances, which increases to 68% if flat HVSRs are considered equivalent. Furthermore, while the shared resonances match very well in terms of frequency (root mean square error, RMSE, <0.11 Hz), the amplitudes of those resonances do not agree (RMSE >1.6). These findings demonstrate that while eHVSR and mHVSR agree at some sites, they are not equivalent at all sites. To investigate if the agreement between eHVSR and mHVSR could be related to features of the microtremor data, earthquake recordings, and/or the site conditions, three machine learning (ML) models at varying levels of interpretability are presented. The ML models—which include multivariate logistic regression, gradient-boosted trees, and support vector machines—show only partial success at using site-specific data to predict whether eHVSR and mHVSR will likely agree in terms of their median curve (accuracy of 78%) and number of resonances (accuracy of 84%). Therefore, we conclude that while eHVSR and mHVSR can be quite similar in terms of resonant frequencies at some sites, they are not identical at all sites. Furthermore, preliminary evidence shows that the agreement of eHVSR and mHVSR can be predicted a priori given features of the microtremor measurements, earthquake recordings, and site conditions, although a larger dataset will be necessary for developing a robust predictive model.

Interpretation of Microtremor Data Through Analysis Horizontal to Vertical Spectral Ratio (HVSR) for Microzonation of Seismic Earthquake Hazards in Baubau City

Research has been carried out on seismic hazard microzonation in the city of Bau – bau using microtremor data. The aim of this research is to determine the seismic vulnerability index based on horizontal to vertical spectral ratio (HVSR) analysis and create a dominant frequency microzonation map (F0), dominant period map (T0), amplification factor map (A0), and seismic vulnerability index map (Kg) from microtremor data which can describe the level of vulnerability of an area to seismic hazards. Microtremor measurements were carried out using a portable three-component seismograph (TDS. 303), the data was analyzed with gepsy software via the HVSR method. The research results show that the distribution of dominant frequency values ​​(F0), ranges from 0.4795 Hz to 16.6383 Hz, dominant period values ​​(T0), ranges from 0.0601 seconds to 2.0854 seconds, amplification factor values ​​(A0), ranges from 1.2285 to 4.9043, and the seismic vulnerability index (Kg) value ranges from 0.1043 to 11.0276. The values ​​(F0), (T0), (A0), and (Kg) are interpreted by referring to literature data and surface geological maps of the research area. The results show that the study area has a small portion of sediment layers that are vulnerable to seismic hazards.

Pemodelan Bawah Permukaan Berdasarkan Nilai Kecepatan Gelombang Kompresi (vp) di Kawasan Rembesan Hidrokarbon Sangubanyu, Jawa Tengah

Sangubanyu is located in Central Java, Indonesia, besides having some hot springs it also has crude oil seepages that have been known since 1971, to understand the cause of these seepages subsurface structure analysis is needed by recording microtremor data at 63 points. The HVSR Method is used to process micrometer data to find subsurface conditions by wave velocity, Compressional wave velocity (vp) is part of this method. vp data could be used to interpret the layer types of subsurface conditions. The southern of the study area has about 112 to 1182 m/s of vp, and the northern has about 506 to 2944 m/s, the differential of these values could be interpreted as a fault with the southern relatively moving down from the northern, there is a little distance between this fault and the crude oil seepages, it is possible that the fracture that occurs by faults was creating secondary porosity in volcanic rock and becomes a migration route for the crude oil flows to the surface.

Hear Wave Velocity Analysis Based on Two Rock Layers Modeling Using Microtremor Data of Gresik and Surrounding Areas

The lithology on the surface in the current condition is often found to be not a fresh rocks, but all materials, be it alluvial, soil, backfill soil, or rocks with a very high degree of weathering. Therefore, this study was conducted to estimate the type of layer on the surface and its underlying layer based on the analysis of Vs (shear wave velocity) values in the surface lithological media and the underlying layer through the modeling of two rock layers. To complete this research, microtremor array data was collected by the Geological Survey Center in the Gresik area which was then processed using the SPAC (Spatial Autocorrelation) method. Based on the results of the study, the Gresik area has a surface Vs value that still shows soft soil values in the range of 65 - 170 m/s and its basement Vs already shows fresh rocks to older lithologies in the alluvial area in the range of 150 - 435 m/s, so it can be seen that some areas that should consist of a fairly hard lithology in the Gresik area have changed with a fairly high level of weathering.

Integration of Microtremor and PS-INSAR Analysis to Investigate the Susceptible Area in the Pronojiwo District (Indonesia) Following the 2021 East Java M6.1 Earthquake

The East Java M = 6.1 Earthquake struck on April 10, 2021, at the bottom of the Indian Ocean, about 96 km south of Kepanjen District, Malang Regency, Indonesia. The neighbouring Pronojiwo District in Lumajang Regency suffered significant damages and loss of lives. The earthquake aftermath underscored the necessity of examining susceptibility factors in the Pronojiwo area for future mitigation efforts. This research focuses on assessing earthquake vulnerability in Pronojiwo District using two methodologies: microtremor analysis and PS-InSAR. Microtremor data were directly collected, while PS-InSAR data were acquired from the Sentinel-1 satellite and processed using the ranging from 0.579 × 10 to 24.840 × 10 s /cm, in Pronojiwo District, with notably higher values found in areas with Semeru deposits, characterized by soft sediments. PS-InSAR analysis indicates concentrated negative shifts in residential zones, signaling structural damage. Regions with elevated vulnerability index values and negative PS points are considered more prone to earthquakes and subsequent building damages.

Comparison of the vs30 model and site class based on MASW, microtremor and N-SPT data in the Opak River Basin

Abstract The utilization of vs30 data offers numerous applications within the geotechnical field, with one of its primary applications being the determination of site class and the microzonation of site class. vs30 data can be acquired through various methods, including Multichannel Analysis of Surface Waves (MASW), microtremor measurements, and N-SPT data. This study seeks to compare vs30 data and site class criteria based on measurements obtained from MASW, microtremor, and N-SPT data in the Opak River Basin. For the vs30 data analysis, a total of 27 data points from MASW and microtremor measurements, along with 3 data points from N-SPT measurements, were employed. These measurements were conducted across various geological formations, encompassing the young volcanic deposits of Merapi Volcano, alluvial deposits, and the Nglanggran, Sentolo, Wonosari, and Semilir Formations. It is worth noting that all N-SPT data were specifically collected within the young volcanic deposits of the Merapi Volcano Formation. The results of this analysis revealed vs30 values ranging from 159 to 192 m/s for MASW measurements, 156 to 789 m/s for microtremor measurements, and 241 to 249 m/s for N-SPT measurements. In accordance with the SNI 1726-2019 site class criteria, the site classes determined based on vs30 values from MASW and microtremor data included rock (SB), very dense soil (SC), stiff soil (SD) and soft soil (SE), while the site class based on vs30 N-SPT data fell under the stiff soil (SD) criteria. The correlation between vs30 values obtained from MASW and microtremor measurements yielded a strong correlation coefficient (r) of 0.98, and the correlation between vs30 values from MASW and N-SPT measurements demonstrated a very strong correlation coefficient (r) of 0.99.

Use of spatial autocorrelation of microtremor using L- and triangle- arrays for estimations of S-wave velocity model and soil response at ITS Surabaya

Abstract Institut Teknologi Sepuluh Nopember (ITS) Surabaya is geologically vulnerable to earthquake hazards. Therefore, preparedness is necessary to address emergencies and risks caused by earthquake at ITS Surabaya. In this study, dispersion curve were obtained through the analysis of microtremor data using the Spatial Autocorrelation (SPAC) method. Microtremor data acquisition was performed at the PLN ITS Futsal Field using L- and triangle-arrays. We successfully got dispersion curves from both arrays. The shear wave velocity (Vs) profile and the best model of Vs profile for each array were obtained by inverting the dispersion curves. By using a two-layer model, the first layer produces identical velocities with a depth of 5.44 meters for an L-array and 5.02 meters for a triangle array. In the second layer, the resulting velocities for each array have quite a difference. The best model of Vs profile for both arrays were used to analyse 1D soil response with a linear approach in the frequency domain. Parameters including Peak Ground Acceleration (PGA), 5% damped Pseudo Spectral Acceleration (PSA), and Fourier Amplitude Ratio (FAR) were obtained from the linear approach analysis that could describe the ground’s response to seismic waves. Vs influences the soil response, the higher the difference in Vs values of a layer with the layer below it (half-space), the higher the increase in PGA, PSA, and FAR.

Analysis of subsidence zone of the village access road in Jatirunggo, Semarang Regency using microtremor data

The rehabilitation of the subsidence phenomenon in Jatikurung sub-village, Jatirunggo village, Pringapus Subdistrict, Semarang Regency, Central Java, has been carried out for a long time however, it has never been successful. Every time an embankment is made, it is only a matter of time before another subsidence occurs. This research aims to investigate the subsurface structure of the subsidence sites. It is proposed to be used as a reference for structural planning in the treatment of road subsidence. Subsurface information is very useful in addressing the subsidence problem more effectively and precisely. The method used was by recording microtremor data and analyzing shear wave velocity and Poisson ratio as parameters to determine the type of subsurface layer. The obtained results are in the form of clay layers to bedrock layers at a depth of 35m. The movement occurred because of the soft or loose soil below and at the edge of the road above the impermeable clay layer. In addition, to the north side of the collapse point is a fairly deep cliff, which is a burden on the bedrock. When it was raining, the soil filled with water and there was even a flow of water in the soil deposits (piping) resulting in the ground movement toward the lower part.

Fine Shear-Wave Velocity Structures of Subsurface beneath the Guangdong–Hong Kong–Macao Greater Bay Area with Dense Seismic Array and SPAC Method

Abstract We apply the spatial autocorrelation (SPAC) method to construct the 3D subsurface shear-wave velocity structure model using the short-period dense seismic array (containing 725 nodal geophones) located at the Guangdong–Hong Kong–Macao Greater Bay area (GBA). We first divided the dense array into numerous subarrays, with each subarray consisting of nine nodal geophones, and obtained 562 subarrays that can provide 1D VS profiles of the same quantity. Then, the SPAC method and genetic algorithm are utilized to extract the dispersion curve of the Rayleigh wave from the raw microtremor data and invert VS structure, respectively. Finally, a 3D VS structure model from the surface to 3.3 km depth is derived by combining all 1D VS structures. Relatively low-velocity anomalies above 700 m are considered unconsolidated shallow sediments as well as relatively high-velocity anomalies beneath 1100 m are attributed to consolidated granite bedrock. Meanwhile, low-velocity anomalies that are identified through the vertical VS profile at a depth of about 900–3000 m can be contributed to the fractured zone, and striped low-velocity anomalies in the horizontal VS maps reveal the location of the deeply buried faults in the study area. The results also mean that the SPAC method combined with the records of short-period dense seismic array can be effectively applied to image subsurface structures in high-populated urban area. The development of this noise-resistance and environment-friendly geophysical technique provides a reliable and effective way to explore the complicated subsurface geological structures, which is of great significance to urban engineering construction and earthquake disaster reduction work in densely populated urban agglomerations.

Land Use Sustainability: Assessment of the Dynamic Response of Typical Bedrock-Buried-Hill Earth Fissure Sites in the Su-Xi-Chang Area

Disaster prevention and the mitigation of earth fissures is a key issue in the sustainable development of urban land. Structures directly avoiding earth fissures are not conducive to the rational planning and efficient utilization of urban construction. The Su-Xi-Chang area, which consists of the cities of Suzhou, Wuxi, and Changzhou, surrounded by Taihu Lake, has developed bedrock buried-hill earth fissures that are rare in the rest of the country. Existing research results have identified the genesis mechanisms, distribution patterns, and developmental characteristics of this type of fissure. Not only does the slow-variable activity of earth fissures cause direct damage to surface and underground structures, but in addition, when an earthquake occurs, the presence of earth fissures may cause the seismic response of the site to be altered or even strengthened, leading to unknown damage or the possible destruction of structures near the fissures. However, no studies have been conducted to assess the dynamic effects of bedrock-buried-hill earth fissure sites. Therefore, in this research, based on six typical bedrock-buried-hill-type earth fissures in the Su-Xi-Chang area, and in order to accurately reveal the dynamic amplification effect law of the earth fissure sites, systematic spectral analyses and comparisons of the microtremor signals were carried out by using the linear analysis method (Direct Fourier Transform Analysis) and the nonlinear analysis method (Hilbert–Huang Transform). The results show that bedrock-buried-hill-type earth fissures have a significant amplification effect on the dynamic response of the site; the amplification effect of bedrock-buried-hill fissure sites follows the same attenuation pattern, and the furthest range of the dynamic response on the site is about 25 m, beyond which the original seismic fortification level can be maintained; the extreme value of the amplification factor of the two sides of this type of site, as derived from the Fourier and HHT methods, is about double, and the nearest earth fissure region should be considered to have a raised seismic fortification intensity of more than double the original. The Hilbert–Huang transform method has good applicability for processing microtremor data, and nonlinear signal analysis methods can be considered comprehensive for future microtremor signal processing.

Investigation of Sediment Layer Thickness Estimation at Bengkulu University Hospital Based on Microtremor Data

Bengkulu is the capital of Bengkulu Province and is located in the subduction zone between the Eurasian and Indo-Australian plates. Bengkulu is also close to the major faults of Sumatra, namely the Musi fault, the Ketahun fault, and the Manna fault. Therefore, regional planning and infrastructure development for earthquake mitigation is necessary. The purpose of this study is to estimate the thickness of the sedimentary layers in the construction zone of Bengkulu Hospital during the earthquake attenuation phase. This study is conducted by surface geological analysis using the HVSR method; data analysis using microtremor data. The microtremor data were analyzed using the HVSR method to obtain the amplification value (A0) and the dominant frequency (f0). HVSR analysis gave dominant frequency (f0) values from 5.1 to 5.8 Hz, amplification (A0) from 1.64 to 5.91 times, and dominant period (T0) from 1.49 to 2.81 seconds. The values of A0, f0, T0 are interpreted with reference to the literature and surface geology as a moderate risk of seismic vulnerability, characterized by moderate to weak sedimentation and moderate amplification values.

Investigation of the subsurface structure at the target site in Kumamoto, Japan, and the distributed data of the blind prediction exercise: report for the experiments for the 6th international symposium on effects of surface geology on seismic motion

This technical report explains details on the results of the investigation to build a subsurface structural model and a selection of earthquake data at the target site of the blind prediction exercise for “The 6th International Association of Seismology and Physics of the Earth’s Interior/International Association of Earthquake Engineering International Symposium on the Effect of Surface Geology on Seismic Motion (ESG6).” The selection process of the target site in the Kumamoto Plain, Japan, in ESG6 was explained with a historical review of the blind prediction tests in the previous ESG conferences. We have collected existing subsurface structural and earthquake data and conducted geophysical and geotechnical surveys in and around the target site to generate important velocity structure and the earthquake data used in the blind test. Microtremor data were obtained in triangular arrays ranging in side lengths from 1 to 962 m, and active surface wave data were derived along a 36-m line at the site. These data were provided for the prediction of a subsurface structural model in the first step of the blind prediction exercise. We also conducted a velocity logging in a borehole to a bottom depth of 39 m at the site and laboratory tests of soil samples from the borehole. We constructed a velocity profile of the shallow and deep sedimentary layers from a combination of the geophysical and geotechnical data at the site, and validated it by comparing the characteristics of the ground motion data from the moderate event. This “preferred velocity model” was provided as a standard model to the participants in the second and third steps of the blind prediction test to predict the earthquake ground motions of a moderate event and the mainshock of the 2016 Kumamoto earthquake.Graphical

SPECTRUM AND TIME-FREQUENCY ANALYSIS TO CHARACTERIZE MICROTREMOR DATA IN SEPAKU SUB-DISTRICT, EAST KALIMANTAN

Microtremor analysis has been done in the Sepaku Sub-District as a part of the New Capital City of Indonesia. This study aims to determine the characteristics of microtremors in the Sepaku Sub-District using Spectrum Analysis and Time-Frequency Analysis (TFA). Data in this study were taken using a seismometer on the 18 measurement points. The data were processed using default analysis from Geopsy software. Spectrum analysis and TFA used Fourier Transform to change time domain data into the frequency domain. Both analysis ways result in the characteristic microtremor data in the research area. The spectrum analysis data obtained shows two frequency ranges with maximum peaks: middle-frequency (5-8.8 Hz) and high-frequency (11.5-17.6 Hz). Afterward, the TFA shows similar results, where the characteristics of microtremor data are divided into two zones. The maximum peak occurs at the middle-frequency range of 5-10 Hz, and the high frequency ranges above 10 Hz

Pemodelan Peak Ground Accleration (PGA) dan Intensitas Gempabumi berdasarkan Pengukuran Mikrotremor pada Kawasan Longsor di Desa Kalongan, Ungaran Timur

The landslide in Kalongan Village affected an area of 5 hectares and has the potential to experience further landslides. Landslides can occur with triggers of external factors such as earthquakes. The Peak Ground Acceleration (PGA) parameter can represent the impacts that occur on the surface in the form of earthquake intensity (MMI). Kalongan Village is 25.5km from the epicenter of the Ambarawa earthquake on 27 May 2023. This study aims to modeling the PGA microzonation and the intensity of the Ambarawa earthquake in the avalanche zone in Kalongan Village. The PGA model is based on measurements of 72 microtremor data in the avalanche zone using the Kanai method. Parameters of the Ambarawa earthquake with a magnitude of 2.5 and a depth of 5 km. The results of PGA modeling in the avalanche zone varied between 1.0-7.1 gal or I-II MMI values. The results of the PGA modeling show that aftershocks can occur if the strength of the Ambarawa earthquake reaches M=4 or 7.1-50.8 gal. The strength of the earthquake is equivalent to the intensity of II-V MMI.

Hazard analysis of earthquake in Pleret, Bantul Regency, Yogyakarta Special Region based on microtremor data

Pleret, one of the sub-districts in Bantul Regency, Yogyakarta, is prone to earthquakes. This area is traversed by an active fault system known as the Opak fault, with a maximum magnitude of 6.6 Mw. The local geological conditions can be determined based on microtremor data from 43 measurement points. The purpose of this research is to understand the dynamic characteristics of the local geological conditions, including the dominant frequency (f0), shear wave velocity (Vs30), peak ground acceleration (PGA), and to map the earthquake impacts on the population and structures. Microtremor measurements were conducted for approximately 20 minutes, revealing a dominant frequency range of 0.61-10.85 Hz. The HVSR curve inversion revealed the Vs30 range 213 to 826 m/s distribution. Peak Ground Acceleration (PGA) values varied from 0.16 to 0.26 g. Using InaSAFE software, the estimated affected population reached 49,052 people, with over 23,176 structures affected. The results of this mapping are expected to be utilized as a step towards enhancing disaster preparedness.

Investigation of sediment thickness in the rammang-rammang maros karst area using microtremor method

The aims of this study were to analyze the value of dominant frequency and amplification, estimate the thickness of the sediment, and to evaluate the seismic vulnerability of the Rammang-Rammang Maros Karst Area. This work was carried out at the Rammang-Rammang Maros Karst Area, Salenrang and Bontolempangan Village, Bontoa District, Maros Regency, South Sulawesi. Microtremor data were analyzed using the Horizontal to Vertical Spectra Ratio (HVSR) method to obtain the H/V curve representing the dominant frequency and amplification values. The dominant frequency values were obtained in the range from 1.389 to 6.251 Hz. The amplification values were in the range from 0.455 to 3.944. The sediment thickness was obtained in the range from 18.521 to 88.029 m, and the seismic vulnerability was in the range from 0.040 to 5.761. High values of sediment thickness were obtained in riverbank areas, which indicated that the weathering that occurred was caused by weathering of limestone and sedimentation by rivers. Meanwhile, low sediment thickness values were obtained in karst hill areas, indicating that the weathering occurred due to the limestone dissolution process. Based on the seismic vulnerability and amplification, the Rammang-Rammang Maros Karst Area is in a relatively safe zone.

Micro-Zonation of hot spring manifestation site at Umbul Niti, South Lampung based on microtremor

In 2021, an intriguing event unfolded at Umbul Niti village when a resident’s well drilling endeavor unexpectedly yielded to a hot spring, thus transforming the site into a small local tourist attraction that captivates visitors and enhances local economies. However, it is crucial to prioritize the safety of visitors and infrastructure, considering the geological implications of hot springs are related to unstable weak zones that would be severely damaged when an earthquake strikes. Weak zones often exhibit heightened susceptibility to seismic events. Using Horizontal to Vertical Spectral Ratio (HVSR) analysis of micro-tremor data that was recorded for 40 minutes at 25 locations, the Amplification (A 0) and Natural Frequency (f 0) were obtained; then the Seismic Vulnerability Index (Kg ) were calculated. The study area has a dominant frequency of around 4.74 - 9.7 Hz indicating the dominance of hard Tertiary Type I soil from Lampung Formation (QTI). Kg value ranges from 0.08 - 3.57 interpreted as mostly low hazard level. However, in the NW - SE direction the value indicates a high Kg value which means a relatively high hazard level, passing through the hot spring location. Thus, the area at the NW-SE zone might require more specific treatment.

Delineation of Coal Identification Using Inversion Microtremor and Borehole at PT X

Coal is a natural resource composed of organic and inorganic materials. The potential of coal is one of the national and world resources. Microtremor method is a geophysical exploration method that utilises microseismic waves to identify the presence of hydrocarbons. Microtremor data processing is processed first using Geopsy software to obtain the H/V curve which will then be processed using Hv-Inv software to obtain the Vs value. Microtremor data is correlated with data from the borehole, the coal seam thickens to the southwest. Similarly, with the correlation results of other microtremor cross sections, the cross section shows that the coal seam is thickened and continuous to the west or southwest. This is further strengthened by the existence of boreholes as a correlation of coal Vs value data in the range of 613.37 m/s-887.70 m/s. Other constituent materials such as soil,claystone, sandstone, carboneseus. Based on the Vs value of the 1D model, it is known that the research area shows the distribution of coal at a depth of 53.5-76 metres. The coal layer in the study area is bituminous to sub-bituminous coal.

Research examining a spatial autocorrelation imaging method based on stationary characteristics of microtremors

The spatial autocorrelation method is an important method for extracting the velocity dispersion curve from microtremor data. However, site data typically cannot strictly meet spatial and temporal stationary feature, and this greatly affects the accuracy of the calculation results of this method. Therefore, based on the cosine similarity theory, this study deduces the applicability of the spatial autocorrelation method to unidirectional Rayleigh surface waves and again verifies the applicability of this method to spatially and temporally stationary Rayleigh waves. The numerical simulation results demonstrate that the velocity dispersion curve can be extracted from a one-way Rayleigh wave using the spatial autocorrelation method to obtain an accurate geological profile, whereas the superposition of finite groups of Rayleigh waves in different directions cannot yield an accurate geological profile. In this study, we quantitatively analyzed the impact of the spatial autocorrelation method on the extraction of the velocity dispersion curve when the signal could not meet the characteristics of temporal and spatial stationarity through numerical simulation. The results reveal that the velocity-dispersion curve can be accurately extracted only when the signal satisfies both spatial and temporal stationarity. When a signal is closer to the spatial and temporal stationary characteristics, this indicates that a more accurate velocity dispersion curve can be extracted. These results provide a reference for improving the calculation accuracy of spatial autocorrelation methods.