The Effectiveness of Shallow Surface Geophysical Methods in Shear Wave Velocity Derivation

Transcription

1 Journal of Civil Engineering and Architecture 12 (2018) doi: / / D DAVID PUBLISHING The Effectiveness of Shallow Surface Geophysical Methods in Shear Wave Velocity Derivation Dewan Mohammad Enamul Haque 1 and A. S. M. Woobaidullah 2 1. Department of Disaster Science and Management, Faculty of Earth and Environmental Sciences, University of Dhaka, Dhaka-1000, Bangladesh 2. Department of Geology, Faculty of Earth and Environmental Sciences, University of Dhaka, Dhaka-1000, Bangladesh Abstract: Shear wave velocity Vs is measured by the surface geophysical survey like MASW (multi-channel surface wave analysis) or RWM (refraction wave method) and by the subsurface method like PS logging. PS logging and RWM are direct methods to derive shear wave velocity and MASW retrieves shear wave through the inversion of the surface wave. In this work, the effectiveness of surface methods (MASW and RWM) is compared with PS logging in determining shear wave velocity. For this purpose, shear wave velocity results Vs30 of 12 PS logging and MASW surveys conducted in Mymensingh Municipality in Bangladesh have been utilized. Additionally, the shear wave velocity results of three PS logging have been compared with the refraction profiles of RWM survey conducted in Rooppur nuclear power plant site in Bangladesh. The relative discrepancy between RWM and PS logging is found less (ranges from to 0.93) compared to MASW and PS logging (+/-0.88 to 33.92). The correlation coefficient of Vs30 derived from RWM and PS logging is observed much better (0.60) compared to MASW and PS logging (0.40). The result is good considering the lateral lithologic variability and inherent differences among techniques. It is evident from the comparison that the RWM can be used as a cost-effective alternative to traditional borehole PS logging method for Vs30 determination and thus the number of down-hole logging tests might be significantly reduced. Key words: Shear wave velocity, surface wave velocity, shallow seismic survey, inversion. 1. Introduction Engineering seismology develops new methods for estimating in-situ S-wave velocity with good accuracy using both active (e.g. seismic refraction, seismic reflection, surface wave method, P-S logging etc.) and passive source (seismic noise) methods [1]. Shear wave (S-wave) velocity Vs is one of the key parameters for evaluating the dynamic properties of soil [2, 3]. The shear wave can be derived from the PS logging or RWM (refraction wave method) or through the inversion of surface wave e.g. MASW (multi-channel analysis of surface wave) [2]. MASW is found to be efficient for retrieving the dispersive properties of surface wave [4]. Ambient seismic noise mainly consists of the surface wave Corresponding author: Dewan Mohammad Enamul Haque, M.Sc., assistant professor. dewan.dsm@du.ac.bd. which can be converted to shear wave through the inversion of dispersion curve of surface wave [5]. The waveform passing through an anisotropic medium shows different velocity at a different frequency. This dispersion phenomenon is used for surface wave analysis. Currently, two broad families of methods [6] are widely used to retrieve the dispersion curve from surface wave recordings: the frequency-wave number method (f-k hereafter) and spatial auto-correlation method (SPAC hereafter). The f-k method has two more sub-methods: BFM (beam forming method) and MLM (maximum likelihood method) [7]. The main difference between BFM and MLM is the fact that BFM is determined only by sensor location and MLM depends on the quality of the data [8]. Although the resolving power of MLM is more than BFM, the MLM is more sensitive to measurement errors [8]. The ESAC (extended spatial autocorrelation) method which is an

2 574 The Effectiveness of Shallow Surface Geophysical Methods in Shear Wave Velocity Derivation extended version of SPAC, appears to be more suitable than an f-k method for providing reliable dispersion curves over a lower frequency range i.e. larger depth of investigation which is up to two times the array dimension [9]. Aki [10] has shown the derivation of the shear wave from ambient noise utilizing the SPAC (statistical technique of spatial autocorrelation) which was subsequently upgraded by Ohori et al. [7] and Okada [11] through the ESAC. In multi- or omnidirectional-wave field, SPAC method is more efficient in yielding wave scalar velocity than BFM [9]. Inversion is often used to better constrain the sub-surface structure from the indirect geophysical measurement at the surface. The dispersion curve of fundamental and higher mode of a surface wave depends on non-linearity of the structure, soil density and P-wave velocity structure [5]. Shear wave velocity can be derived by LIN (linearized inversion) [12] of dispersion curve when a-priory information of subsurface structure is assumed, otherwise non-linear inversions are usually applied e.g. simplex downhill method [13] or genetic algorithm [14]. LIN method which is based on least square solution approach has the advantage of finding optimal inversion solution starting from a suitable initial guess model [15]. There are, however, some other inversion algorithms which perform dispersion and inversion simultaneously based on both linearized and non-linearized inversion. Monte Carlo [16], genetic algorithm and simulated annealing perform both conversion of dispersion curve and inversion of shear wave velocity together [6]. Even, [17] have performed joint inversion scheme of phase velocity dispersion and H/V (horizontal/vertical) ratio [18] curves from seismic noise recordings using a genetic algorithm considering the higher mode. Picozzi and Albarello [15] have used GA to provide the LIN with an initial model through the joint inversion of H/V ratio and Raleigh wave dispersion to increase the likelihood of convergence towards the best fitting model. However, ambient noise based methods cannot resolve the problem posed by the inherent trade-off between velocity and soil thickness in the inversion scheme, especially in the case of H/V ratio [5]. From the above discussion, it is clear that the MASW method is computationally more intensive compared to PS logging. But PS logging requires borehole which is in contrast cost-intensive. We have introduced another direct method of S-wave velocity derivation referred hereafter as RWM (refraction wave method). A shear wave is acquired in opposite polarity from horizontal geophones in RWM. We have made an attempt to evaluate the cost-effectiveness of surface geophysical methods through the comparison of the shear wave velocity results derived from MASW (active), PS logging and RWM. 2. Methods of Shear Wave Velocity Determination The current research work is conducted for the comparison of shear wave velocity derived from surface geophysical methods like MASW and RWM and PS Logging. To help reach the goal, shear wave velocity results of 12 PS logging and MASW surveys conducted in Mymensingh Municipality area have been utilized. Mymensingh is the first municipality of Bangladesh for which seismic risk is taken into consideration while formulating the land use plan. Moreover, the shear wave velocity results of three PS logging and refraction wave method conducted along five profiles close to the boreholes of PS logging in Rooppur nuclear power plant site in Bangladesh are also being utilized. 2.1 PS Logging The PS logging conducted in the present study is based on Conventional Interval method [19]. This test aims to measure the travel time of elastic wave from the ground surface to some arbitrary depths beneath the ground (Fig. 1). The inverse of the slope of the travel time curve at a particular depth indicates the shear wave velocity to that depth (Fig. 2). As the waves travel through all materials between impulse source

3 The Effectiveness of Shallow Surface Geophysical Methods in Shear Wave Velocity Derivation 575 and geophone at the bore hole, the PS tests allow detecting the layers that might remain hidden in refraction seismic methods [3, 20]. In this study, the seismic wave was generated by striking a wooden plank by a 7 kg sledgehammer. The plank was placed on the ground surface at around 1 m distance in the horizontal direction from the top of the borehole. The plank was hit separately on both ends to generate shear wave energy in opposite directions (Fig. 3) and is polarized in the direction parallel to the plank. t tc = D R Fig. 1 Calculation scheme of traveling distance. V d ΔD = Δ t c Fig. 2 Interpretation of PS Log data by interval method where D is the depth interval showing similar slope and t c is the corrected travel time difference of D.

4 576 The Effectiveness of Shallow Surface Geophysical Methods in Shear Wave Velocity Derivation Fig. 3 The arrival of S waves with opposite polarity. After calculating the shear wave velocity for each one-meter depth increment the average shear wave velocity is calculated by using the following equation. T 30 = (H i /V i ) Vs30 = 30/T 30 where, H i Thickness of the i th layer and 30 = Hi; V i = S wave velocity of the i th layer; Vs30 is the average shear wave velocity of upper 30 m. 2.2 MASW The basis of the surface wave method is the dispersive characteristicc of Rayleigh waves when propagating in a layered medium. The variation of phase velocity with frequency or wavelength is called dispersion [21]. Shorter the wavelength or higher the frequency the lower the velocity will be. The Rayleigh wave phase velocity primarily depends on the material properties i. e. shear-wavee velocity, p-wave velocity or Poisson s ratio, mass density and soil thickness [22]. Brown et al. [21] show that Raleigh wave phase velocity at a wavelength of 36 m, V R 36 is highly correlated with upper 30 m shear wave velocity, Vs30; Vs30 = 1.076V R 36 with r 2 = Surface wave testing consists of collecting surface-wave phase data in the field, generating the dispersion curve, and then using iterative forward or inverse modeling techniques to back-calculate the corresponding Vs profile and from the Vs profile, Vs30 can be calculated [2]. The analysis can be conducted by active source measurement or seismic noise recordings [23]. Active method is applied to the higher frequency component of the data, and passive method is applied to lower frequency data [24]. In this research, 4.5 Hz geophones are used as receivers, and a sledgehammer is used for source generation Cross-correlation of the CMP (common mid point) gather is made by a lot of shot cross-correlation of any two receivers. The phase velocity is derived at CMP location by transforming the cross-correlation of CMP micro-tremor measurement, the vertical component of the ambient noise was recorded for 10 minutes. For active MASW, first, the cross correlations for every pair of calculated. Then, cross-correlations with same receiverr spacing are averaged in the time domain. This time domain component is converted into frequency domain through Fourierr transform. Finally, a phase velocity image is calculated from cross-correlation by a phase shift and stack [ 4, 24]. The passive MASW data weree divided into several time coherences are estimated for every pair of receivers in each ambient compared with Bessel function and phase velocity is derived through the error analysis of this comparison [7]. for surface wave acquisition. gathers and gather. In the passive receivers in each shot location are blocks. Then, complex noise block. Finally, coherence is The derived dispersion curve in both cases is utilized to obtain shear wave velocity through the non-linear least square solution inversion approach [22]. The inversion process tries to adjust the assumed layer model as much as possible through several iterations in order to make the calculated spectrum looks similar to the dispersion curve obtained from the field test. Once the algorithm can match the calculated dataa with the measured one, the assumed model willl be considered as the true profile (Figs. 4 and 5).

5 The Effectiveness of Shallow Surface Geophysical Methods in Shear Wave Velocity Derivation 577 Fig. 4 showing the principles of MASW [23]. Fig. 5 Derivation of 1-D shear wave velocity structure from the dispersion curve. 2.3 RWM Similar to down-hole Vs30, RWM provides shear wave velocity directly. Seismic refraction methods rely on the fundamental assumption that shear wave velocities increase with depth, so the arrival time of refracted energy on the surface at the geophone array can be utilized to estimate the velocity-depth function [25]. Using the polarity reversing capability, it is possible to stack signals from the two orientations of a polarized source. Geophones are connected via a multi-core cable to a portable 12 channel seismic recorder. S-wave travel time is calculated from the first cross of generated opposite phase shear waves by striking the wooden plank from opposite faces. The first arrival time of S-waves is plotted against geophone position (distance) and the time-distance plots are made for each shot point of the profile. The slope of the fitting curve represents the S-wave velocity. For the verification of the functionality of geophones, the geophones were stacked and recording is made (Fig. 6). The recording in the field is made without any use of a filter (Fig. 7) and then using different frequency filters (15-64 Hz and Hz band pass filters), appropriate filter is selected for the recording (Figs. 8 and 9). Reversed refraction profiling keeping source at -22 m, 0 m, 22 m, 44 m, 66 m, 86 m, and 110 m is used for refracted S-wave recording along five profiles.

6 578 The Effectiveness of Shallow Surface Geophysical Methods in Shear Wave Velocity Derivation Geophones are placed from 0 to 88 m (Fig. 10) and the source is kept at -22 m, 0 m, 22 m, 44 m, 66 m, 88 m and 110 m. Refracted S-wave seismic survey is carried out following reversed refraction profiling along five profiles. For each profile, a number of shot points with different offset are used (Fig. 10). S-wave travel time is calculated from the first cross of generated opposite phase shear waves by striking the wooden plank from opposite faces. The first arrival time of S waves are plotted against geophone position (distance) and the time-distance plots are made for each shot point of the profile (Fig. 11). By plotting the travel time versus distance, the velocity of each layer is obtained from the slope of the fitting curve using the data points that have a similar trend. The inverse of the slope of the fitting curve represents the S-wave velocity (Fig. 11). Fig. 6 Verification of the functionality of horizontal geophone for S-wave recording.

7 The Effectiveness of Shallow Surface Geophysical Methods in Shear Wave Velocity Derivation 579 Fig. 7 S wave seismogram without any filter use. Fig. 8 S wave seismogram with a Hz band pass frequency filter use.

8 580 The Effectiveness of Shallow Surface Geophysical Methods in Shear Wave Velocity Derivation Fig. 9 S wave seismogramm with a Hz band pass frequency filter use. Fig. 10 Reversed refraction profiling schemes along profiles V-IX for S waves. 3. Comparison of Vs30 Obtained from PS Logging, MASW, and RWM Twelve down-hole logging and MASW surveys have been carried out in Mymensingh Town area. The shear wave velocity Vs30 derived from PS loggingg and MASW are compared and shown in Table 1. PS logging is executed along four boreholes (BH Nos. 5, 20, 503 and 504) and RWM survey is also carried out along profiles V to VIII close to the boreholes in Rooppur area. RWM obtained S-wave velocities for each shot of different profiles are given in Table 2. S-wave velocity determined from RWM for each profile at different shots shows a small variation in the distribution of velocity. The variation of velocity in the first layer along profile V is in the range of 181 to 1911 m/s and for the second layer, it varies from 204 to 215 m/s. Profile VI and VII show first layer velocity on average about 175 m/s ( m/s) and 180 m/s ( m/s) and second layer average velocity about 210 m/s ( m/s) and 210 m/s ( m/s) respectively. Relatively higher S-wave velocity is

9 The Effectiveness of Shallow Surface Geophysical Methods in Shear Wave Velocity Derivation 581 obtained along profile VIII and IX and the average velocities for the first layer are 185 m/s and 180 m/s and second layer 221 m/s respectively. Shear wave velocity Vs30 determined from PS logging and RWM presented in Table 3 shows a good agreement of Vs30 retrieved from RWM and PS logging conducted in Rooppur site. Apart from error percentage or relative discrepancy calculation, methods have been compared by investigating the correlation of MASW and RWM derived Vs30 results with Vs30 acquired from down-hole logging (Table 4). Fig. 11 Time-distance graph showing velocities for S wave along profile VIII.

10 582 The Effectiveness of Shallow Surface Geophysical Methods in Shear Wave Velocity Derivation Table 1 Comparison of shear wave velocity (Vs30) determined from PS logging and MASW. BH number PS logging Vs30 (m/s) Active MASW Vs30 (m/s) Relative discrepancy (+/-) Table 2 S wave velocity determined from refraction wave method (RWM) for profiles V-IX. Profile No. Shot point (m) V1 (m/s) V2 (m/s) V VI VII VIII IX Table 3 Comparison of Vs30 determined from PS logging and RWM survey. Borehole number Value of V, m/s from PS Logging Value of V, m/s from RWM Relative discrepancy (+/-)

11 The Effectiveness of Shallow Surface Geophysical Methods in Shear Wave Velocity Derivation 583 Table 4 Comparison of correlation coefficient PS-MASW and PS-RWM. Methods comparison PS logging Correlation coefficient MASW active PS-MASW 0.39 RWM PS-RWM Discussion Shear wave velocity Vs30 estimation has appreciable engineering interest as it gives information about the rigidity of the subsoil. The basic assumption of engineering seismology is that the soil having uniform Vs30 will respond to an earthquake ground motion in a similar way [26]. In this study, three different techniques of Vs30 determination have been presented. PS logging and RWM are direct methods to obtain shear wave velocity and MASW retrieve shear wave through the inversion of the surface wave. Although MASW is computationally intensive-different algorithm do exist for MASW analysis that makes it as a viable alternative for PS logging considering the cost effectiveness. However, more often, MASW and PS logging do not exhibit identical results. In this study the same scenario has also been observed. Moreover, few MASW tests have noisy data which have further enhanced the error percentage. Interestingly, refraction wave method results are more correlated with PS logging results compared to MASW active. This study shows the correlation coefficient of Vs30 derived from RWM and PS logging is much better (0.60) than MASW and PS logging (0.39). In addition the relative discrepancy percentage between RWM and PS logging is quite low (ranges from to 0.93). The result is good considering lateral lithologic variability, limited observation number and inherent differences between surface geophysical and PS logging techniques. Rational application of RWM survey and calibration of RWM results with PS logging results will help reduce the number of boreholes for PS logging. Thus, RWM might be used as a cost effective alternative to traditional PS logging method. In this study, only active MASW technique results are taken into consideration while making comparison with PS logging as the passive method cannot provide phase velocity of several tens of Hz [24]. In connection, the passive MASW in the study area exhibits comparatively even lower correlation with PS logging than its active counterpart. 5. Conclusions Knowledge of shear wave velocity variation laterally and vertically is crucial to estimate earthquake ground motion response in thick soils. PS logging is the best technique to determine shear wave velocity Vs30 but it requires bore-hole which make the work slow and costly. The surface geophysical techniques RWM and MASW discussed in this study provide a cost-effective means of acquiring accurate and realistic shear wave velocity information for thick soil sites. RWM is a very cost-effective alternative to traditional PS logging method and might be considered as one of the most supportive methods for PS logging. Acknowledgments The data used in this work are collected by the authors as part of the team working for conducting the project in Mymensingh Municipality area and in Rooppur NPP site and are grateful to the authorities of the respective Consulting Companies.

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