Analysis Of Surface Waves Method Research Articles

The linear swept sine method to determine the dispersion curve of structural pavement

Abstract Pavement evaluation must be performed in nondestructive ways. This includes using the multichannel analysis of surface waves method by recording waves detected by multiple sensors from one active source. However, heavy traffic produces noise and reduces the detection quality as the sensor moves further away from the measurement source. We need a pavement evaluation method that is immune to noise. The linear swept-sine method presented in this paper has a very high resistance to noise by using a wide frequency band vibration source to the ground received by a single accelerometer at a small distance. The noise resistance is obtained by applying a tracking filter at the receiver (accelerometer), which accepts the signal with the frequency swept linearly at the same rate as the transmitter. This tracking filter has a low-frequency component equal to the phase delay between the source and the receiver, even when the transmitted source is generated in the high-frequency range. The dispersion curve is calculated and inverted by using the surface wave inversion method to obtain the velocity model below the pavement by calculating the delay for each data segment.

Near-surface velocity inversion and modeling method based on surface waves in petroleum exploration: a case study from Qaidam Basin, China

Surface waves are widely used in the study of underground structures at various scales because of their dispersion characteristics in layered media. Whether in natural seismology or engineering seismology, surface wave analysis methods have matured and developed for their respective fields. However, in oil and gas exploration, many data processors still tend to consider surface waves as noise that needs to be removed. To make more people pay attention to the application of surface waves and widely utilize surface waves carrying the near surface information in oil and gas exploration, this paper takes the data processing of LH site in Qinghai, China as an example to apply surface wave analysis methods to oil and gas exploration. We first preprocess and perform dispersion imaging method on the seismic record in the LH site to obtain frequency-phase velocity spectrum with good resolution and signal-to-noise ratio. Then, utilizing clustering algorithms, it automatically identifies and picks dispersion curves. Finally, through a simultaneous inversion algorithm of velocity and thickness, it inverts the dispersion curves and obtain S-wave velocity profiles in the depth range of 0–200 m. The near surface is divided into four zones based on velocity ranges and depth ranges. Additionally, we apply the surface waves inversion results as constraints to first-arrival tomography and obtain objectively accurate P-wave velocity profiles and Poisson’s ratio profiles. The results indicate that by applying surface wave analysis methods, the near surface velocity information carried by surface waves can be extracted, providing near surface velocity models for static correction and migration. At the same time, compared with the surface wave application in engineering seismology, the scale of oil and gas exploration is larger, so that the data processing of surface waves is particularly important, otherwise it will affect the picking of the dispersion curve and inversion.

Assess the Effectiveness of Multichannel Analysis of Surface Waves Method in Mapping Ancient Structures in Ultrashallow Aquatic Environments: The Case of Agioi Theodoroi, Greece

ABSTRACTThe present geophysical research aims to evaluate the applicability of multichannel analysis of surface waves (MASW) on mapping ultrashallow underwater ancient masonry remnants. The work presents the analysis from a single seismic line using MASW and seismic refraction tomography (SRT) methods and its corresponding electrical resistivity tomography (ERT) section surveyed at the submerged prehistoric site of Agioi Theodoroi area located 10 km eastern of Heraklion, Crete, Greece. The 2D MASW velocity model exhibits significant correspondence with the resistivity structure extracted from the ERT data, showing lateral S‐wave velocity (Vs) variations at the positions where the high resistivity anomalies exist. The analysis of synthetic seismic data calculated from a respective model reproduced a comparable S‐wave velocity pseudo‐section with the real data. However, the investigated targets (submerged buried masonry) appear shallower and wider in MASW sections than in the real world and the corresponding synthetic models, due to insufficient vertical and horizontal resolution of this method. Surface waves travelling through the seafloor sediments (Scholte‐waves) demonstrate very low velocity values. This makes them suitable for the detection of shallow and relatively large (> 0.5 m) underwater manmade structures, providing the enhancement of MASW method resolution, by utilizing a high frequency (> 100 Hz) seismic source, recording short Scholte wavelengths (≤ 1 m) and using shorter (≤ 0.5 m) receiver spacing and array length. Consequently, the results of this work demonstrate the potential in employing conventional seismic techniques in the delineation of underwater antiquities and the revealing of the cultural dynamics in very shallow off‐shore archaeological sites.

Efficient and high‐resolution surface‐wave dispersive energy imaging using a proposed spatial smoothing propagation method

AbstractSurface‐wave information from seismic data can be used for near‐surface analysis, static computation and noise suppression. The multichannel analysis of surface waves method is a useful approach for obtaining the shear wave velocity of the near surface; however, rapidly generating an image of dispersive energy in the presence of coherent noise is a challenge. In this study, we propose the imaging of the dispersive energy of the Rayleigh wave using a spatial smoothing propagation method. In this method, forward and backward spatial smoothing algorithms were used to restore the rank of the covariance matrix in strong coherent noise. Subsequently, an image of the dispersive energy was rapidly generated by the propagation method using a linear operation equivalent to the eigenvalue decomposition. The proposed method was evaluated using both synthetic and field data. The results showed that the method was easy to use and has higher resolution representation, efficiency and noise robustness compared with conventional methods.

Investigation of an active landslide area with the Electrical Resistivity Tomography (ERT) and Surface-wave Analysis Methods in Hendek, Sakarya

Investigation of an active landslide area with the Electrical Resistivity Tomography (ERT) and Surface-wave Analysis Methods in Hendek, Sakarya

Modified Frequency-Bessel Transform Method for Dispersion Imaging of Surface Wave from Six-Component Ambient Noise Recordings

Surface wave analysis methods based on ambient noise have attracted considerable attention within the geophysical and civil engineering communities, particularly in light of the limitations associated with traditional seismic surveys in densely populated urban areas. Conventionally, translational seismic sensors have been employed for the observation of ambient noise. Nevertheless, recent advancements in rotational sensor technology have facilitated the direct measurement of ground motion induced by seismic waves in a rotational manner. Through the integration of these rotational sensors with traditional inertial seismometers, a novel six-component seismic sensor has been developed. This innovative sensor enables the local observation of six degrees of freedom pertaining to ground motion, encompassing three orthogonal components of translational motion and three orthogonal components of rotational motion. In order to demonstrate the seismological significance of rotational ground-motion data, we applied the modified frequency-Bessel transform method (MFJ) to six-component ambient noise recordings for surface wave analysis. To underscore the practical utility of the MFJ method, a real-world case study is presented, illustrating its effectiveness in quantifying Rayleigh and Love wave dispersion from six-component ambient noise recordings.

The soil characterization of the region between the Maltepe-Beykoz Fault and the Marmara Sea in İstanbul (Türkiye) with the integrated HVSR (Nakamura technique) and MASW method

Completing the earthquake recurrence period of the Marmara segment, one of the two seismic gaps of the northern Anatolian fault zone, necessitates earthquake hazard studies for Istanbul, considering the population density. This study focuses on determining the soil properties of the study area in the Maltepe district of Istanbul. The Maltepe, with its large population density, stands very close to this fault zone and is vulnerable to earthquake damage. The soil properties such as Vs30, dominant period (T0), and amplification ratio (A0) were determined with the MASW from surface wave analysis methods at 48 points and the HVSR approach of microtremor analysis methods at 26 points. These point-based properties were mapped in the GIS environment, and spatial distribution maps were prepared. In addition, seismic vulnerability (Kg) and effective shear strain (γe) calculations for different acceleration values were carried out to detect deformation-failure on the surface. It was understood from the maps and the 2D cross-sections produced to examine the lateral and vertical changes that the soil conditions in the study area developed under the control of the Maltepe Beykoz fault (MBF). Accordingly, the two sides of the MBF lineament were determined with different geophysical outputs by their different geological origins. Namely, the alluvial part in the coastal part was defined by low Vs30, high period, and Kg values; on the contrary, the more rigid parts located at high elevations were described by relatively high Vs30, low period, and Kg values. In addition, it was understood that the deltaic sediments spread loosely and undulated in the alluvium at the SE part of the MBF lineament. These results obtained in the study are significant for predicting disaster damages and taking precautions before disasters. In addition, the scientific data potential of the outcomes of this study will make future studies, which are carried out to determine other parameters to be used during the taking of the precautions, more accessible.

Direction of arrival estimation method for ground source based on optimally polarized Rayleigh waves.

This paper points out a critical issue in the study of estimating the azimuth of ground sources by using the polarization characteristics of Rayleigh waves: even if the signal quality is good, the degree of polarization of Rayleigh waves varies across different frequency bands, and the band with the strongest energy is not the one with the lowest azimuth error. A direction of arrival estimation method for ground sources based on optimally polarized Rayleigh waves using a single three-component geophone is presented in this paper. First, the reciprocal ellipse rate, flatness coefficient, and the angle between the semi-minor axes and the horizontal plane are selected as the polarization parameters of this method according to two quantitative principles. Then the frequency band range of the optimal polarization Rayleigh wave is determined by analyzing the sum of the weights of the three polarization parameters in different frequency bands. After filtering and combining with the existing surface wave analysis method, the actual data bearing estimation result with an average error of only 4.95 degrees and a standard deviation of only 1.82 degrees is obtained. It is also found that the signal-to-noise ratio approximates the exponential decay of the direction of arrival error obtained by this method.

Analysis of Subsurface Layers using the Multichannel Analysis of Surface Waves Method in Manimbahoi, Gowa Regency

This research is about the structure of the soil layer at the research site in Manimbahoi, Parigi District, Gowa Regency. This research is very important considering that the location has experienced a mega landslide which resulted in some residents being not found. This study aims to provide an overview of the shallow soil layer at the landslide disaster location. This study uses one of the geophysical methods, Multichannel Analysis of Surface Waves (MASW) method, with 4 lines at points at the landslide location. Based on the results of the study, the velocity of the Vs30 wave was obtained in each line. On the first line the velocity of Vs30 is 303.5 m/s. On the second line the velocity of Vs30 is 284.1 m/s. On the third line the velocity of Vs30 is 309.0 m/s. On the fourth line the velocity of Vs30 is 256.1 m/s. Based on the soil classification by looking at the Vs30 velocity, it can be determined that the type of soil at the research location is medium soil (sand). Medium soil is unconsolidated sediment, described as soil composed of minerals that are not compact

Investigation of site properties of the Çaldıran (Van, Eastern Turkey) settlement area using surface wave and microtremor methods

Çaldıran (Van, eastern side of Turkey) which is a seismically very active region has more than active faults around and the areas under active tectonic effect. The earthquakes and soil characteristics are the significant factors that increase the severity of the damages ratio. For this reason, the characteristics of the engineering structure should be defined accurately and reliably. The shear wave velocity (Vs) obtained from geophysical methods is one of the most important parameters that determine the behavior of the soil during an earthquake. In this study, active and passive source surface wave methods were applied at different measurement points in the study area in order to determine soil properties of the settlement area and its surroundings in Çaldıran district the city of Van. As part of this study, 80 boreholes, 95 multichannel analysis of surface wave (MASW) profiles, and 66 microtremor (HVSR) measurements were performed in the study area. The Vs velocity with depth dependent could be determined by using the dispersive behavior of Rayleigh waves in surface wave analysis methods. In order to analyze the engineering characteristic of the region and earthquake-soil-structure relations parameters such as the amplification factor, predominant period (t0), Vs velocity, average velocity up to 30 m Vs30, and seismic vulnerability index (Kg) maps have been prepared. In order to reveal the variety of the engineering properties of the area in horizontal and vertical directions, depth cross-sections in different directions were created. When the tectonic structure and regional geology were examined, it was determined that all profile results were compatible with the geological structure.

Affirmation of Elastic Modulus Derived from Spectral Analysis of Surface Waves Method using Artificial Neural Network

Pavement modulus is believed as one of the important features to characterize the pavement condition, specifically the pavement stiffness. The value of pavement modulus may be calculated using the existing Witczak mathematical dynamic pavement modulus prediction formulae. However, the equation developed by Witczak is heavily impacted by temperature while underestimating the impact of other mixing factors thus, only offering an adequate approximation for the circumstances for which they were designed. In this study, the Spectral Analysis of Surface Wave (SASW) test data was used to develop an Artificial Neural Network (ANN) that accurately backcalculates pavement profiles in real-time. The pavement modulus calculated from the equation was validated by using ANN developed in Matlab software to avoid any mistakes during calculation based on the equation. Three parameters, shear wave velocity, depth and thickness from SASW test data were used as inputs and elastic modulus calculated using Witczak pavement modulus equation was used as an output to train the models developed in ANN. Five segments of pavement are presented in this paper where almost compromise that the greater the depth, the lesser the shear wave velocity as well as pavement modulus. Nine neural network models were developed in this study. The network architecture of 4-80-4 is the most optimized network with the highest correlation coefficient of 0.9992, 0.9994, 1.0, 0.9996 for validation, testing, training and all respectively. The created ANN models’ final outputs were reasonable and relatively similar to the real output.

Extraction of surface-wave phase velocities from ambient noise in the presence of local noise sources based on matched-field processing

Passive surface wave methods have gained much attention from geophysics and civil engineering communities with the advantage of lower costs and deeper penetration depths compared to active seismic methods. The successful extraction of surface waves from ambient noise relies on the assumption of a homogeneous random distribution of noise sources. In urban environments, there are many strong noise sources located in localized areas (i.e., local sources) that violate the ideal noise distribution conditions, which causes errors in surface-wave dispersion extraction. To solve this problem, we propose a new passive surface wave analysis method in the presence of strong local noise sources (local-source passive surface wave analysis, LSPSW). We use the matched field processing (MFP) algorithm to capture noise source distributions and then extract reliable surface wave phase velocities. The MFP algorithm can accurately estimate the distribution of noise sources located either close to or far from the receiver array. Synthetic and field examples demonstrate the feasibility of using LSPSW to estimate phase velocities in complicated noise environments with a pseudo-linear array. Comparisons with other passive surface wave methods (seismic interferometry, the spatial autocorrelation method, pseudo-linear array analysis of passive surface waves based on beamforming) further illustrate the superiority of the MFP-based LSPSW method.

Uncertainty quantification of phase velocity surface waves multy-modal inversion using machine learning

The paper is devoted to uncertainty quantification of the inverse problem solution of the multichannel analysis of surface waves method - the inversion of the curves of the phase velocity via frequency dependence. The uncertainty estimation approach is based on the Monte Carlo sampling strategy and a multilayer fully connected artificial neural network to approximate nonlinear dependence of shear wave velocity and layers thickness via values of phase velocity surface waves. Frequency-dependent noise in the data and errors of the inverse operator are projected onto the inverse problem solution. The results of unimodal and multimodal inversion are compared on the example of synthetic data processing. The experimental results show that using of machine learning approaches makes it possible to quickly and accurately estimate the posterior probability density of the reconstructed velocity model parameters.

Forward modeling of Rayleigh surface waves for analytical characterization of dominant dispersion trends

AbstractForward modeling is of critical importance for inversion analysis of surface wave methods to obtain shear‐wave velocity (VS) profiles of soil sites. The dynamic stiffness matrix (DSM) method can provide forward modeling of Rayleigh surface waves to simulate complex wave propagation in layered soil sites. However, contamination from body waves and interference of multiple Rayleigh wave modes can reduce the accuracy of theoretical dispersion curves, especially at irregular soil sites with embedded low‐velocity or high‐velocity layers. An analytical method is developed herein to combine the techniques of the multichannel analysis of surface waves method with the DSM method to improve the accuracy of the theoretical dispersion analysis for soil sites. The proposed method implements multichannel analysis of the analytical displacement responses to capture dominant dispersion trends. Comparison of the results obtained with the new method against those from the transfer matrix method and the literature indicates that the new method can (1) effectively minimize the effects of contamination caused by body waves and interference from several Rayleigh wave modes, and (2) generate accurate dominant dispersion trends for soil sites with various stiffness profiles, especially for the high‐frequency dispersion characteristics of the profiles with embedded low‐velocity layers.

A New Approach to Predict Hydrogeological Parameters Using Shear Waves from the Multichannel Analysis of Surface Waves Method

For near-surface contaminant characterization, the accurate prediction of hydrogeological parameters in anisotropic and heterogeneous environments has been a challenge since the last decades. However, recent advances in near-surface geophysics have facilitated the use of geophysical data for hydrogeological characterization in the last few years. A pseudo 3-D high resolution P-wave shallow seismic reflection survey was performed at the P Reactor Area, Savannah River Site, South Carolina in order to delineate and predict migration pathways of a large contaminant plume including trichloroethylene. This contaminant plume originates from the northwest section of the reactor facility that is located within the Upper Atlantic Coastal Plain. The data were collected with 40 Hz geophones, an accelerated weight-drop as seismic source and 1 m receiver spacing with near- and far-offsets of 0.5 and 119.5 m, respectively. In such areas with near-surface contaminants, a detailed subsurface characterization of the vadose zone hydraulic parameters is very important. Indeed, an inexpensive method of deriving such parameters by the use of seismic reflection surveys is beneficial, and our approach uses the relationship between seismic velocity and hydrogeological parameters together with empirical observations relating porosity to permeability and hydraulic conductivity. Shear wave velocity ( Vs) profiles were estimated from surface wave dispersion analysis of the seismic reflection data and were subsequently used to derive hydraulic parameters such as porosity, permeability, and hydraulic conductivity. Additional geophysical data including core samples, vertical seismic profiling, surface electrical resistivity tomography, natural gamma and electrical resistivity logs allowed for a robust assessment of the validity and geological significance of the estimated Vs and hydrogeological models. The results demonstrate the usefulness of this approach for the upper 15 m of shallow unconsolidated sediments even though the survey design parameters were not optimal for surface wave analysis due to the higher than desired frequency geophones.

Automatic picking of multi-mode surface-wave dispersion curves based on machine learning clustering methods

The surface-wave analysis method is widely adopted to build near-surface shear-wave velocity structure. Automatic picking of surface-wave dispersion curves is a problem that needs to be solved, especially when dealing with a large amount of data. In this paper, we proposed an automatic picking method of multi-mode surface-wave dispersion curves based on unsupervised machine learning methods. Firstly, seismic data is transformed to two-dimensional dispersion image by dispersion imaging method. The discrete dispersion image points are separated into two clusters: dispersion energy and background noise by Gaussian mixture model clustering method. Then the dispersion energy points are projected into frequency-velocity domain, and are distinguished as different surface-wave modes by the density-based spatial clustering of applications with noise algorithm. Finally, multi-mode dispersion curves are obtained by searching for the local peaks in different mode areas of surface waves. Particle filter is used to smooth the picked dispersion curves to eliminate the influence of noise. The synthetic tests show that the automatically picked dispersion curves can match the theoretical dispersion curves well. We also applied the proposed method to the picking of dispersion curves of two field data. The automatically picked dispersion curves are applied to the subsequent inversion. In the second field data, the one-dimensional inversion results are interpolated to obtain the near-surface three-dimensional velocity model of the work area. The inversion results are in good agreement with borehole data, which further proves the accuracy and efficiency of the automatic picking method for multi-mode dispersion curves.

A Review of the High-Frequency Multi-Channel Analysis of Surface Wave Method for Proximal Soil Sensing

This paper reviews the development and applications of the high-frequency multi-channel analysis of surface waves method (HF-MASW) for proximal soil sensing. The HF-MASW method uses surface waves to noninvasively measure soil profile in terms of the shear (S) wave velocity as a function of depth. Recently, several practical techniques have been developed to enhance the HF-MASW method, including (1) the self-adaptive method using a variable sensor spacing configuration, (2) the phase-only signal processing, and (3) a nonlinear acoustic technique. Using this enhanced HF-MASW method, the S-wave velocity soil profiles from a few centimeters to a few meters were measured. Fundamentally, the S-wave velocity is related to soil mechanical and hydrological properties through the principle of effective stress. Therefore, the measured 2-dimeniaional S-wave velocity profile images can reflect the temporal and spatial variations of soils due to weather effects, geological anomalies, and anthropologic activities. In this paper, several HF-MASW applications were described, including (1) measuring soil profiles, (2) studying weather and seasonal effects, (3) capturing the instantaneous variations of soil profiles during rain events, (4) detecting and imaging fraigpan layers, and (5) studying and imaging farmland compaction. These studies demonstrated that the HF-MASW method can be used as an effective proximal soil sensing tool for agricultural and environmental applications.

Site Effect Potential in Fond Parisien, in the East of Port-au-Prince, Haiti

In the frame of a Belgo-Haitian cooperation project (PIC 2012–2016), a study of the local seismic hazard was performed in Fond Parisien, an area located on the foothills of the “Massif de la Selle”, along the easternmost portion of the Enriquillo Plantain Garden Fault (EPGF). The H/V Spectral Ratio (HVSR) technique was applied to study the resonance frequency of the target areas and the azimuth of the wave field. The amplification factors were estimated using Standard Spectral Ratios obtained from earthquakes recorded by a temporary seismic network. Using the Multichannel Analysis of Surface Waves method, the seismic properties of the shallow layers were investigated. Then, the results were compared to local Electrical Resistivity Tomography data. These results highlight, in the central part of Fond Parisien, an E-W zone of low velocities ranging from 200 m/s to 450 m/s and low resistivities between 1 Ωm and 150 Ωm, due both to tectonic folding of the rocks and to the presence of sediment filling in the eastern part. The latter is marked, in most of its sites, by resonances at one or more frequencies ranging from 0.7 Hz to 20 Hz. Infiltration and storage of brackish water in the underground layers also contribute to the low resistivity values. With the noise HVSR data, we also evidenced a significant influence of the EPGF on the main orientation of the seismic wavefield as in the vicinity of this fault, the azimuths are parallel to the orientation of the fault. Overall, the results also show greater potential for site effects in the block formed by the sedimentary basin and strong amplification of the seismic ground motion for the sites bordering the basin to the north and west. We interpret the amplification in the north and south-west as probably originating from topographic irregularities locally coupled with sediment deposits, while in the center of the western part, the site effects could be explained by the presence of folds and related weakened and softened rocks. By the integration of several geophysical methods, we could distinguish areas where it is possible to build more safely. These zones are located in the northern part and encompass Quisqueya Park and neighboring areas as well as the village “La Source” in the southern part. In the rest of Fond Parisien, i.e., in the more central and eastern parts, buildings should be erected with caution, taking into account the nearby presence of the EPGF and the influence of fine sediments on the amplification of the seismic motion.

Horizontally orthogonal distributed acoustic sensing array for earthquake- and ambient-noise-based multichannel analysis of surface waves

SUMMARY A 2-D orthogonal distributed acoustic sensing (DAS) array designed for seismic experiments was buried horizontally beneath the Kafadar Commons Geophysical Laboratory on the Colorado School of Mines campus at Golden, Colorado. The DAS system using straight fibre-optic cables is a cost-efficient technology that enables dense seismic array deployment for long-term seismic monitoring, favouring both earthquake-based and ambient-noise-based surface wave analysis for subsurface characterization. In our study, the horizontally orthogonal DAS array records ambient noise data for a period of about two months from November 2018 to January 2019. During this time, the array also detected seismic signals from an ML3.6 earthquake at Glenwood Springs, Colorado, which exhibit opposite signal polarities in the orthogonal DAS section recordings. We derive the transformation matrix for DAS strain measurements in horizontally orthogonal cables to retrieve both Rayleigh and Love wave dispersion information from the single-component DAS signals using the 2-D multichannel analysis of surface waves method. In addition, ambient noise interferometry is applied to long-term DAS noise recordings. Our theoretical derivation demonstrates that Rayleigh and Love wave Green's functions are coupled in the noise cross-correlation functions (NCFs) of DAS receiver pairs. Stacking NCFs over the horizontally orthogonal DAS array can constructively recover the radial Rayleigh wave component but destructively suppress the Love wave component. The multimodal Monte Carlo inversion of the earthquake-based Rayleigh wave and Love wave dispersion measurements and the noise-based Rayleigh wave measurement reveals a 1-D layered structure that agrees qualitatively with geological surveys of the site. Our study demonstrates that although straight fibre-optic cables lack broadside sensitivity, using appropriate DAS array configuration and seismic array methods can extend the seismic acquisition ability of DAS and enable its application to a broad range of scenarios.

Subsoil classification and geotechnical zonation for Guadalajara City, México: Vs30, soil fundamental periods, 3D structure and profiles

ABSTRACTGuadalajara, Jalisco, is the second largest city in Mexico with around 4.5 million inhabitants. A high seismic hazard exists in the city due to forces produced by the interaction between the Rivera, Cocos and North American plates and the smaller Jalisco Block. Guadalajara is one of the largest cities built over pumice soil deposits. Furthermore, the near‐surface phreatic level causes a high susceptibility to liquefaction. All these features can cause extreme earthquake site effects. Due to the fragile inner structure of pumice sands, traditional geotechnical tests are inappropriate to characterize the seismic response. Therefore, we propose the use of surface wave analysis methods (multichannel analysis of surface waves and refraction microtremor), which we applied in 33 sites to define the soil classification in terms of VS30 (the average shear wave velocity between the surface and 30 m depth), the bedrock depth and the fundamental period. From the soil classification, we construct a microzonation map consisting of four geotechnical zones, which we superimpose on the known construction systems within the city. The comparison between the construction period of the buildings and the fundamental frequencies of the soil indicates a high vulnerability to resonance in 1‐ to 4‐storied old buildings constructed of adobe and unreinforced masonry within zones II and III, followed by a medium vulnerability to seismic resonance in compact buildings of 1–4 stories within zone I and 1–12 stories within zones II and IV.