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DETECTION OF SUBSURFACE VOIDS IN STRATIFIED MEDIA USING SEISMIC WAVE METHODS
ABSTRACT
The primary objective of this study is to investigate the effect of sub-surface anomalies such as voids in the stratified soil media on surface wave propagation. A data processing protocol was developed for processing seismic wave data for void detection by studying the signal simultaneously in the time and frequency domain using continuous wavelet transformation (CWT). The effect of voids in the soil media was examined by qualitatively comparing the signal properties acquired from the controlled laboratory experiments on the soil media, both with and without voids. For the controlled experimental study, a wooden box of dimensions 4.5m x 1.67m x 1.37m (15′x5′6′′x4′6′′), was constructed and filled with sand and gravel in two layers. A void of known dimension was excavated in the soil mass in the box at a known location. Micro seismic waves were produced using a 7.25kg (16-lb) sledge hammer and a rubber mallet. The vertical response of the soil mass surface was recorded using the SignalCalc®620
Dynamic Signal Analyzer and was processed using the MATLAB® 7.0 wavelet toolbox. Time-frequency plots of the seismic wave signals obtained from the unvoided soil mass experiment indicate that damped, uniform undulations are due to the surface wave dispersive behavior. Also, data obtained from the voided soil mass experiment indicate that the void anomalies cause low strength ripples in the time-frequency plots, usually in the low frequency region of the time-frequency plots. This observation has been used to study the properties of voids.
In addition to the experimental study, a numerical study was also conducted. The wave propagation phenomenon was simulated for voided and stratified regions using the finite difference method in the Wave2000pro software. Thus, a refraction test was performed in the soil box to determine the shear wave velocity profile. The receiver data was processed with the same protocol that was used for analyzing the experimental test data conducted in the soil box with void. The time-frequency maps constructed using the experimental data confirm the numerical results.
Finally, the time-frequency maps using different types of wavelets for the same set of experimental data were compared. From this analysis it was concluded that the wavelets that correlates with the properties of the original signal produce time-frequency plots with all the signal features distinctively so that all the signal properties can be separately studied. Thus, wavelet analysis of the seismic wave signals obtain from the micro-seismic tests can effectively investigate the sub surface void anomalies.
TABLE OF CONTENTS
LIST OF FIGURES ……………………………………………………………………………………………. ix
LIST OF TABLES……………………………………………………………………………………………… xii
ACKNOWLEDGEMENTS…………………………………………………………………………………xiii
CHAPTER 1 INTRODUCTION…………………………………………………………………………..1
1.1 Background …………………………………………………………………………………………………….1
1.2 Problem Statement …………………………………………………………………………………………..4
1.3 Objectives ………………………………………………………………………………………………………5
1.4 Scope of Research ……………………………………………………………………………………………5
1.5 Organization of Report …………………………………………………………………………………….6
CHAPTER 2 LITERATURE REVIEW ……………………………………………………………….7
2.1 Introduction …………………………………………………………………………………………………….7
2.2 Elastic Wave Propagation in Homogenous, Isotropic Half-space …………………………..7
2.3 Seismic Wave Methods …………………………………………………………………………………. 10
2.3.1 Seismic Refraction Survey …………………………………………………………………… 11
2.3.2 Seismic Reflection Survey…………………………………………………………………….. 13
2.3.3 Surface Wave Methods…………………………………………………………………………. 15
2.4 Applicability of Seismic Methods in Void and Sinhole Detection ………………………. 16
2.5 Analysis of Seismic Test Data ……………………………………………………………………….. 19
2.5.1 Time-history Analysis ………………………………………………………………………….. 19
2.5.2 Wavelet Analysis ………………………………………………………………………………… 22
2.5.2.1 Continous Wavelet Transformation (CWT) …………………………………. 22
2.5.2.2 Wavelet Families ………………………………………………………………………. 31
2.5.2.2.1 Daubechies Wavelets …………………………………………………… 32
2.5.2.2.2 Symlet Wavelet Family ……………………………………………….. 33
2.5.2.2.3 Meyer Wavelet …………………………………………………………… 33
2.4.2.2.4 Mexican Hat Wavelet …………………………………………………… 34
2.4.2.2.5 Gaussian Wavelet Family …………………………………………….. 35
2.6 Numerical Simulation of Wave-propagation in Elastic Media ……………………………. 36
2.7 Summary……………………………………………………………………………………………………… 40 CHAPTER 3 TESTING PROGRAM………………………………………………………………… 41
3.1 Introduction………………………………………………………………………………………………….. 41
3.2 Data Acquisition System ……………………………………………………………………………….. 41
3.2.1 Signal Analyzer …………………………………………………………………………………… 42
3.2.2 Geophones …………………………………………………………………………………………. 43
3.2.3 Energy Source……………………………………………………………………………………… 44
3.2.4 Data Acquisition Software…………………………………………………………………….. 45
3.3 Laboratory Test Setup……………………………………………………………………………………. 46
3.4 In–situ Soil Properties Tests: Refraction Test on Soil Box………………………………….. 50
3.5 Summary……………………………………………………………………………………………………… 52
CHAPTER 4 NUMERICAL SIMULATION……………………………………………………… 53
4.1 Introduction………………………………………………………………………………………………….. 53
4.2 Parameters for FDTD Simulation of Wave Propagation Phenomenon ………………… 53
4.2.1 Image Size ………………………………………………………………………………………….. 54
4.2.2 Material Properties……………………………………………………………………………….. 54
4.2.3 Boundary Condition……………………………………………………………………………… 55
4.2.4 Source Confiurgation……………………………………………………………………………. 55
4.2.5 Receiver Confiugration…………………………………………………………………………. 56
4.2.6 Time Step Scale…………………………………………………………………………………… 56
4.2.7 Maximum Frequency……………………………………………………………………………. 56
4.3 Numerical Simulation of Wave Propagation in Layered Media…………………………… 57
4.4 Summary……………………………………………………………………………………………………… 59
CHAPTER 5 RESULTS AND DISCUSSION…………………………………………………….. 60
5.1 Introduction………………………………………………………………………………………………….. 60
5.2 Data Processing…………………………………………………………………………………………….. 60
5.2.1 Data Processing Software……………………………………………………………………… 61
5.2.1.1 MATLAB® 7.0 Programming Platform and Wavelet Toolbox………… 61
5.2.1.2 Seisimager®2D………………………………………………………………………….. 61
5.2.2 Data Processing Protocol………………………………………………………………………. 62
5.3 Data Processing Results…………………………………………………………………………………. 64
5.3.1 In-situ Refraction Survey for In-site Shear Wave Velocity Profile……………… 64
5.3.2 Wavelet Analysis of the Experimental Data…………………………………………….. 65
5.3.2.1 Analysis Using Different Wavelet Families………………………………….. 65
5.3.2.2 Wavelet Analysis of Soil Box Test Data………………………………………. 68
5.3.3 Wavelet Analysis of the Numerical Simulation Data………………………………… 75
5.4 Summary……………………………………………………………………………………………………… 78
CHAPTER 6 SUMMARY AND CONCLUSIONS……………………………………………… 80
6.1 Summary……………………………………………………………………………………………………… 80
6.2 Conclusions………………………………………………………………………………………………….. 81
6.3 Recommendations for Future Research……………………………………………………………. 83
REFERENCES…………………………………………………………………………………………………. 84
APPENDIX A…………………………………………………………………………………………………… 88
APPENDIX B …………………………………………………………………………………………………… 89
Chapter 1
Introduction
1.1 Background
Detection of obstacles, voids, cavities, subsurface rock profiles, or underground utilities is required for the planning, design, and remediation of existing sub-structures (foundations, tunnels or basements). These sub-surface features affect the soil properties such as shear strength, shear modulus, in-situ density and bed rock profile in their vicinity. The design and planning process of any sub-structure are primarily dependent on these sub-surface soil properties. Detection of these sub surface features has received much consideration due to rapid formation of sinkholes and damage to infrastructure (Alexander and Book 1984; Canace and Dalton 1984; Stewart 1987). Most of the currently used, traditional methods of determining the soil properties are laboratory based tests and require transportation of the soil samples from the site. The collection and transportation of soil samples results in a disturbed sample and thus may not represent the soil conditions in-situ (Powrie 2004). The other drawback of laboratory testing is that the procedure requires a fixed time for transporting samples and conducting tests. To overcome the drawbacks of the laboratory testing, a large variety of in-situ tests were developed. These tests include the vane shear test, cone penetration method, sand cone replacement method, bore-hole shear test, rock pressure meter test, dilatometer test, KoStep blade test, and rock shear test (Roy 2007). These in-situ tests are very quick and can provide results in real time. However, they may require sophisticated instruments and substantial manpower. Another drawback of in-situ tests is that the depth of exploration of these tests is limited to near the surface, and the spatial resolution of the variation of the soil properties is poor. To overcome the resolution problem, non-destructive, in-situ tests were developed. These methods include multi-channel analysis of surface waves (MASW), spectral analysis of surface waves (SASW), seismic refraction survey, seismic reflection survey, electrical imaging, ground penetrating radar, subsurface penetrating radar, and microgravity survey (Belesky and Hardy, 1986). Most of these exploration methods are based on the generation-collection methods. In these methods radio or acoustic waves, or electric current is generated in the ground and the surface vertical response or electric current is measured with the help of geophones or electrodes. Then, the data is processed and deductions are made about the sub-surface soil properties based on the data analysis. These methods vary widely in feasibility, cost to benefit ratio, applicability, and effectiveness.
Dobecki and Upchurch (2006) compared the effectiveness of various geophysical methods in detecting sinkholes and other ground subsidence and concluded that seismic wave based sub-surface exploration techniques are very successful in determining the elastic moduli of the soil layers surrounding these ground features. Seismic wave based exploration techniques utilize different types of data processing tools to extract the medium property information about the medium. Seismic methods include the travel time estimation or spectral analysis of the elastic waves (surface waves, compression waves and shear waves) generated in a medium due to an impact on the ground surface (Richart,
Woods, and Hall 1970). Travel time based methods include the refraction and reflection method and spectral analysis methods include spectral analysis of surface waves (SASW) and multichannel analysis of surface waves (MASW).
Most of the current commercially available software for the seismic wave data processing, such as Seisimager®2D and Surfseis®, identify the surface wave component with a built-in algorithm and estimate the quality of the signal based on the power and arrival time of the surface wave component. In some cases, the software algorithm for surface wave identification fails due to ripples in the signal generated from the reflection of waves from voids and other anomalies (Park, and Heljeson 2006). Thus, there is a need for an efficient and accurate procedure for the surface wave identification during signal processing.
Signal processing techniques have improved exponentially due to advancements in the available computational resources. Signals can now be analyzed more effectively and quickly using different methods simultaneously (Yilmaz 1987; Tokimatsu 1997; Ganji, Gucunski, Nazarian 1998). These methods include Fourier analysis, time domain analysis, time-series analysis, wavelet analysis and fractal analysis. Recently, wavelet transformation has gained popularity due to its wide range of applicability (Shokouhi and Gucunski 2003). Traditional spectrum analysis only provides the frequency content of the signal but contains no information on the location of the signal where these frequencies are occurring. However, wavelet transforms can be used to study the time localization of the signal (the variation of the frequency content of the signal with time) (Walker 1999). Kaiser (1994) defined the wavelet transformation as, “…the convolution between a function known as wavelet and the original signal.” The convolution result is used to form time-frequency maps to give a representation of the signal in both the time and frequency domain.
1.2 Problem Statement
The conventional seismic wave test approach that are generally used to estimate the soil properties at the site of interest lacks the information of spectrum variation in the time domain due to the presence of cavities and layers of soil. The spectrum variation information of the reflected waves from any cavities or anomalies is lost when a Fourier transform is performed on seismic test data. Travel time based methods that are generally used in the case of reflection and refraction of seismic waves do not supply information about change in frequency content. Time-frequency maps can be used to study the change in frequency content over time and thus can be used for cavity detection in the region with distributed soil properties.
This research demonstrates a new scheme for the detection of voids by analyzing the surface wave component of a signal travelling through voided stratified soil media by improving on the currently available signal processing methods used in the seismic wave tomography. The focus is on the analysis of data obtained from the seismic wave tests using different families of wavelets and development of a scheme for detecting voids in the soil media. In this study the wave propagation was considered as elastic because these seismic tests the strains produced by the impact are small and the media particles are not permanently deformed.
1.3 Objectives
The primary objectives of this research are as follows:
- Develop a method to identify the surface wave component from the signal generated by the seismic wave test using wavelet transform in the voided soil media.
- Propose the most efficient and effective mother wavelet for seismic wave test applications by investigating the effect of different types of wavelets on the analysis.
- Develop a wavelet based protocol for processing of seismic wave data for void detection.
1.4 Scope of Research
This research focuses on the development of a protocol for processing seismic wave data for void detection using wavelet transformation. Other methods of void detection, uncertainties associated with the measurement of data, participation of higher Raleigh wave modes, data scatter and systematic error (Marosi 2004; Tuomi 1999) are not examined in this study. Also the effect of porosity and saturation level of the soil was not considered. The primary method used to investigate wave propagation in stratified voided media consists of micro-seismic tests conducted under laboratory conditions. The data is analyzed using wavelets from different classes, or families, to investigate the effect of wavelet selection on wavelet analysis and the generation of time-frequency plots. The effect of voids is studied simultaneously in the time domain as well as the frequency domain using time-frequency plots generated from wavelet analysis of the signals. A numerical model is developed using finite difference methods and focuses on simulation of wave propagation in stratified voided soil media. The numerical model is then used to study the wave propagation in the voided soil media. Results from the numerical simulation and the laboratory tests are utilized to develop a protocol for the void detection in the stratified soil media.
1.5 Organization of Report
Chapter two presents a literature review of the relevant studies on the fundamentals of wave propagation phenomenon in elastic media and seismic wave test methods. The wavelet transformation is also briefly discussed. The finite difference simulation of wave propagation phenomenon in stratified soil media is reviewed.
Chapter three presents details of the testing program. It includes a description of the data acquisition system and laboratory test setups. Chapter three also reviews soil property tests conducted to provide input data for the finite difference simulation model.
Chapter four investigates the aspects of numerical modeling of wave propagation in stratified soil media and an overview of the parameters associated with finite difference time domain (FDTD) simulation of wave propagation in elastic media, and also the numerical model used for the simulation of the soil box test.
Chapter five presents details of the analytical program related to laboratory testing and an overview of the data processing methods used for analyzing laboratory tests and numerical simulation test data. Also included are the results from all laboratory tests. Chapter five also presents a detailed discussion of numerical simulation results and comparison with experimental results. Chapter six provides a summary and conclusions from the research and recommendations for future research.
DETECTION OF SUBSURFACE VOIDS IN STRATIFIED MEDIA USING SEISMIC WAVE METHODS
