Advances in acquisition and processing of near-surface seismic tomographic data for geotechnical...

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special topicfirst break volume 31, August 2013

Near Surface Geoscience

1 Helmholtz Centre for Environmental Research - UFZ, Department of Monitoring and Exploration Technologies, Permoserstr. 15, 04318 Leipzig, Germany.

2 University of Potsdam, Institute of Earth and Environmental Sciences, Karl-Liebknecht-Str. 24, 14476 Potsdam, Germany.3 Geotomographie GmbH, Am Tonnenberg 18, 56567 Neuwied, Germany.* Corresponding author, Email: [email protected]

Advances in acquisition and processing of near-surface seismic tomographic data for geotechnical site assessment

Hendrik Paasche,1* Michael Rumpf,2 Jörg Hausmann,1 Thomas Fechner,3 Ulrike Werban,1 Jens Tronicke2 and Peter Dietrich1 highlight recent projects where technology advances are improving the use of near-surface seismic tomography to support geotechnical site assessment.

A growing population and particularly people’s increas-ing demand for mobility requires substantial effort in improving infrastructure, i.e. there is an increas-ing need for new traffic and transportation systems

above and below. Planning new routes or reconstructing and extending old ones needs communication and interaction between initiators, planners, consultants and constructors. Throughout this process geophysicists and geotechnical engineers have an important role. For new construction or reconstruction, a detailed characterisation of the ground is essential. In this context, the prediction of ground deforma-tion in the sense of geotechnical risk analysis is of particular importance.

Nowadays, geotechnical site characterisation typically relies on local tests such as cone penetration tests (CPT) and load-bearing tests as well as laboratory tests of sampled mate-rial to assess the relevant soil properties (e.g. Lunne et al., 1997; Fahay, 1998; Atkinson, 2000). However, owing to the assumption of lateral homogeneity of subsurface conditions inherent in most interpretation methods solely relying on log-ging, coring and inspection of sampled materials, significant uncertainties and errors may hamper a spatially continuous and quantitative assessment of construction ground quality.

An alternative for spatially continuous characterisation of the subsurface is the use of near-surface geophysical methods. Owing to physical factors, seismic methods are particularly suitable for investigating construction grounds and their mechanical properties (e.g. Robertson et al., 1995; Dietrich and Leven, 2006). However, geophysical techniques provide information about physical material properties, such as propagation velocities of P- and S- waves. Although these parameters are somehow related to relevant geotechnical parameters (e.g. small strain soil stiffness), the exact relations are often unknown and can be non-linear or even non-unique. Furthermore, geophysical data usually

requires processing to achieve 2D or 3D physical parameter models, i.e. by using tomographic reconstruction techniques (e.g., Lehmann 2007). In most cases, such model generation procedures are ill-posed due to limited number and accuracy of available observations. Considering multiple geophysical data sets and models allows for reducing non-uniqueness in geophysical model generation and in linking the geophysical parameters to geotechnical properties, respectively. Thus, in geotechnical site characterisation the best results can be expected from the combination of high-resolution 2D or 3D P- and S-wave seismic methods with local and sparse geo-technical tests and laboratory investigation of soil samples.

In this work we highlight recent achievements striving to improve the potential of near-surface seismic tomogra-phy to support geotechnical site assessment. We begin by reviewing recent developments in acquisition technology and experimental set-up for improved information return of near-surface seismic surveying. We will present some innova-tive approaches in the fields of data processing and model generation. Finally, we will discuss recent advances towards linking multiple geophysical tomograms to sparse logging information, avoiding the explicit formulation of a determin-istic transfer function quantifying inter-data relationships.

Experimental set-up and acquisition technologyTypical near-surface seismic experimental set-ups with tar-get depths relevant for geotechnical applications are largely inspired by those heavily used for resources exploration. Spread lengths as well as source and receiver spacing are adjusted in scale. For example, inter-geophone distances of 2 m or less are common to near-surface refraction tomography surveys allowing for the use of towed land streamers in some applications (e.g., Van der Veen et al., 2001). For near-surface refraction seismic surveys, seismic energy is usually generated at the Earth’s surface or within the upper 50 to 100 cm of the

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of a few metres. Recently, a lot of effort has been directed towards the development of sources allowing the generation of broad-band seismic energy with a frequency content of 200 Hz and more. For example, this led to the availability of mobile mini-vibrators for P- and S-wave generation as described by Krawczyk et al. (2013). However, the high mobility of such sources goes along with relatively limited system weight. Realisation of efficient coupling can be chal-lenging when operating such vibrator sources with sweep frequencies up to 400 Hz on unconsolidated or wet soils. For P-wave refraction seismic surveys, particularly, this can be a problem. In such experiments, the required source-receiver offsets can easily exceed several hundred metres to enable penetration depths below the transition from unsaturated to saturated sediments with typical P-wave velocities of less than 500 m/s and more than 1500 m/s, respectively.

Alternatively, 2D or even 3D velocity images based on first onset travel time tomography could be obtained by multi-offset (MO) reversed vertical seismic profiling (RVSP) tomography (Figure 2a). Here, a seismic source is operated at various depths below the ground water level. This allows for velocity imaging to depths below the ground water level while avoiding the large source receiver offsets of classical P-wave refraction seismic experiments. However, to ensure good tomographic coverage of the model area, we require dense lateral spacing between the shot points. This can easily be realised using direct push technology (Dietrich and Leven, 2006; Paasche et al., 2009). For efficiency, the direct push crawler vehicle can also be used to tow a land streamer (Figure 2a). Paasche et al. (2009) used direct push technology to hammer a steel rod temporarily down to a depth of more than 15 m below ground surface. At the bottom end, a Geoprobe SP16 groundwater sampler was mounted with an outside diameter of 4 cm (Figure 2b). After driving the sampler to the desired depth, the sampler had to be opened by retention of the outer rod while keeping the inner filtered part down using an inserted extension rod, which must be regarded as a cumbersome procedure. Once the groundwa-ter sampler was opened and the extension rod removed, a slim sparker source with a diameter of 13 mm generating P-wave energy up to a frequency of more than 1 kHz was inserted and fired in the range of the open sampler. By recording seismic energy at the surface and using multiple direct push injection points with lateral distances of 10 m, a 2D velocity model had been generated. Advantageously and opposite to conventional refraction tomography, also low-velocity regions can be imaged by MO RVSP tomography.

Recently, we extended the MO RVSP method by devel-oping a mobile crosshole seismic tomographic approach (Figure 3). In doing so, a steel rod is temporarily installed using sonic drill technology. The bottom section of the steel rod was screened and sealed afterwards by synthetic resin or silicone to avoid fine sediments being washed into the rod. Within the steel rod a commercial seismic source can be

ground. A significant amount of the excited energy usually goes into source-related noise, such as surface or guided waves.

In recent years multichannel analysis of surface wave energy (MASW) recorded in a shot gather became popular and is nowadays the standard approach for near-surface 1D S-wave velocity imaging (e.g. Socco and Strobbia 2004). Analysis of adjacent shot records allows for pseudo-2D or 3D imaging of near-surface S-wave velocity variations. Accompanying MASW by seismic refraction tomography relying on first cycle onsets picked in the recorded shot gathers results in complementary P- and S-wave velocity images suitable for further linkage to geotechnical parameters of interest, such as shear strengths, stiffness or Poisson’s ratio (e.g., Schön 1998). However, the fundamental assumption of MASW is that the subsurface is horizontally layered along the geophone spread considered when calculating phase velocities. When measuring over highly heterogeneous near-surface deposits this may not always be the case and no reliable pseudo-2D S-wave velocity models can be generated by MASW (Hausmann et al., 2012; Figure 1).

The signals generated by traditional near-surface seismic sources, such as weight drop, sledge hammer or pipe gun are characterised by a broad frequency range between approxi-mately 10 Hz and 120 Hz. The resultant wave lengths, even in unconsolidated sediments, are often not sufficient for high-resolution imaging of near-surface sediments exhibiting significant parameter and material variations on the scale

Figure 1 (a) shot gather acquired over fluvial sediments in the floodplain of the Mulde River, Germany. Note the disturbed pattern of surface waves (A) caused by lateral inhomogeneity in the upper areas of the subsurface. The disturbed region corresponds to the edge of a former river channel. Seismic energy is reflected at this lateral boundary (B and C). (b) Pseudo-2D S-wave velocity models obtained by lateral constrained 1D MASW imaging in the region of lateral inhomogeneity (Hausmann et al. 2012). Note the difference of both models when changing source – receiver direction.




placed, i.e. we operated the Borehole Impacter Source (BIS) generating broadband P- and S-wave seismic energy with upper frequency limits of up to 1000 Hz. Propagating P- and S-waves are recorded at the Earth’s surface using three-component geophones. Additionally, we temporarily install a second screened steel rod using direct push technology 10–20 m laterally apart from the source. A three component borehole geophone is operated in this steel rod recording P- and S-wave energy at the depth according to the screened region. The procedure is repeated with varying source and borehole geophone depths to ensure good tomographic coverage of the area of interest. However, operation with only one receiver tool is time consuming and thus was the motiva-tion to develop a modular multi-station borehole acquisition system. This allows for efficient and simultaneous crosshole-type P- and S-wave tomography (Figure 4). Combining this advantage in acquisition technology with newly developed experimental set-ups, such as the mobile tomography rely-ing on direct push technology, is expected to enable highly flexible and economic near-surface seismic P- and S-wave tomography with outstanding resolution. This could form the basis for routine use of high-resolution seismic imaging for near-surface geotechnical and engineering applications.

Processing and model generationThe fundamental processing step in seismic tomography is the identification of first-cycle onsets of direct and refracted waves. Picking ten or a hundred thousand first breaks manu-ally is a tedious and costly task. Various semi or fully auto-mated picking routines have been developed over the years (e.g. McCormack et al., 1993; Boschetti et al., 1996). They have been routinely and successfully applied to identify first-cycle onsets of direct or refracted P-waves in refraction and crosshole tomographic data.

Figure 2 (a) Conceptual sketch of multi-offset (MO) reversed vertical seis-mic profiling (RVSP) tomography. For efficient acquisition, the direct push machine can be used as a towing vehicle for a land streamer (photograph). (b) Sketch illustrating the operation of a slim sparker source in a groundwater sampler temporarily installed by direct push technology (Paasche et al. 2009). The steps of installing the sampler still sheathed, opening the sampler by insertion of an extension rod, insertion of the sparker source, lowering to the open sampler and firing are labelled (a)-(d), respectively.

Figure 3 Photograph of experimental set-up over-lain by conceptual sketch for direct push based mobile seismic tomography. The MO RVSP tomog-raphy is now combined with crosshole tomogra-phy by operating source and borehole geophones in sonic drill and direct push rods, respectively. The rods are sliced and sealed with synthetic resin or silicone to avoid tedious opening of samplers (see Figure 2b). This setup is used for combined P- and S-wave tomography using three-component receivers and a commercial borehole source gener-ating compression and shear wave energy.




Once all first arrivals belonging to a survey have been picked, they are globally inspected by producing a number of different plots, i.e. visualizing the identified travel times over shot-receiver offset (e.g. Harris et al., 1995). Suspicious picks may be eliminated or checked by revisiting the recorded shots.

Based on P- or S-wave travel time data sets correspond-ing tomographic velocity models can be generated. In most cases, the available data sets will be individually inverted using regularised inversion algorithms (e.g. Aster et al. 2005). Here, a carefully selected starting model is stepwise perturbed to optimize the misfit between observed travel times and model responses concurrent with additional assumptions made a priori about the model character, e.g. smoothness. Such approaches are generally deterministic and result in a single model. An objective exploration of the model search space is usually not possible.

Recently, a number of different techniques have been developed to link the model generation procedures of individual fully or partially co-located P- and S-wave seismic tomographic data sets. The most powerful approaches strive to define structural links between the P- and S-wave velocity models to be found, i.e. by fuzzy cluster analysis or cross gradients (Paasche et al., 2012; Gallardo, 2007; Figure 5). Such joint or co-operative inversion approaches gener-ally reduce the ambiguity inherent to the individual model generation processes and are even sufficiently flexible to bring in additional non-seismic tomographic data. However, since they rely on deterministic approaches depending on a suitable initial model to be provided by the user, they do not allow for quantitative appraisal of model uncertainty beyond the simple analysis of model resolution matrices illustrating relative uncertainties and mutual dependencies between the individual model parameters.

Computational hardware advances make it feasible to employ inversion techniques searching the model space globally for near-surface 2D seismic tomography. For many near-surface seismic tomography applications, such problems can now be solved on modern desktop computers and do not require access to high-performance computing anymore. Recently developed global optimisation algo-rithms, such as particle swarm optimisation (PSO; Kennedy and Eberhardt, 1995) or cuckoo search (Yang and Deb, 2010), combine efficient model space exploration capability with fast conversion rates and high robustness to algorith-mic settings compared to more traditional algorithms, such as simulated annealing (e.g. Sen and Stoffa 1995). Adaption of these techniques to joint inversion of P- and S-wave tomographic travel time data sets is straightforward (Paasche and Tronicke 2013; Figure 6). As displayed, a global joint inversion of P- and S-wave travel times acquired by a mobile tomography experiment (Figure 3) has been done using PSO. The final ensemble of plausible models

Identification of S-wave first-cycle onsets is usually more challenging. Opposite to P-waves, direct or refracted S-waves usually do not make up the first signal onset on a recorded trace. When exciting horizontally polarised S-wave energy two shots recorded with opposite source excitation direction can be used to identify S-wave onsets (Figure 4c). Alternatively, reversing trace polarity of one shot and stacking it with the other will significantly reduce recorded energy arriving prior to the first S-wave. Theoretically, one could expect that now traditional picking algorithms may perform well and enable the reliable and largely auto-mated identification of S-wave first arrival times. However, owing to limited accuracy in shot orientation, uncontrolled energy emission into the ground when using seismic impulse sources and inaccurate adjustment of the receiving three-component geophones relative to the source orientation, S-wave first cycle onsets are often difficult to identify, even if shots with different excitation direction are available. Techniques striving to overcome orientation-dependent amplitude differences between opposite shots have been developed (e.g., Michaels, 2001). Nevertheless, in many cases manual picking of S-wave first-cycle onsets is required to ensure accurate and reliable travel time assessment. This hampers the routine use of S-wave tomography building on first arrival travel times.

Figure 4 (a) Sketch of a newly developed modular multi-station borehole acquisition system for operation in near-surface boreholes. (b) Photograph of a single three-component module. (c) Two recorded shots of a Borehole Impacter Source (BIS) generating horizontally polarised shear waves and com-pressional waves. The two shots (red and black traces, respectively) differ by opposite excitation direction for the shear waves (See the opposite polariza-tion of S-wave first onsets).




More recent approaches building on statistical tech-niques avoiding the explicit assumption of a deterministic transfer function are considered more powerful when it comes to appraisal of non-uniqueness in parameter estima-tion. Flexible techniques integrating several geophysical models for prediction of 2D or 3D geotechnical parameter distributions are regarded as more robust with regard to some model artefacts likely to present due to inherent ambi-guity of the geophysical model generation processes (Dietrich and Tronicke, 2009). Additionally, some approaches easily cope with non-linear and non-unique parameter relations (e.g., Linder et al., 2010). However, when building on deterministically derived geophysical models for geotechnical site characterisation, objective and quantitative risk analysis on the basis of the derived geotechnical information is not possible, since ambiguity inherent to the geophysical model generation cannot be adequately taken into account.

In contrast, geophysical ensemble solutions achieved by globally searching the geophysical model space may offer the potential to propagate or link geophysical model generation uncertainty quantitatively to geotechnical parameter informa-

comprises several hundred P- and S-wave velocity models. This ensemble of models can be used to quantify the relative frequency of model parameter conditions, i.e. in the sense of predicting the likelihood of a certain velocity at a distinct model area (Tronicke et al., 2012). However, visualization and interpretation of such ensemble solutions comprising several hundreds or thousands of plausible models is still challenging.

Linking seismic and geotechnical informationThe final step required when using seismic exploration techniques for geotechnical site assessment concerns the transformation or integration of geophysical information into or with geotechnical data and information, respectively. Traditionally, deterministic transfer functions have been used to transform individual geophysical models achieved by deterministic model generation procedures into relevant geotechnical parameters (e.g., Schön, 1998). Unfortunately, this does not allow for assessing uncertainty propagation from geophysical model generation via model transforma-tion using deterministic transfer functions.

Figure 5 Result of a zonal cooperative inversion (ZCI) of P- and S-wave crosshole tomographic travel time data sets. The zonal model reflects the common structure of both underlying velocity models as described by fuzzy c-means cluster analysis (Paasche et al. 2008).

Figure 6 Joint inversion results of P- and S-wave tomographic travel time data sets acquired using the mobile tomography set-up shown in Figure 3. The models in (a) and (b) are two equivalent solutions out of a larger ensemble of equally acceptable solutions achieved by joint global inversion using particle swarm optimisation. Note, depth is referenced to a point outside the survey area.




of model generation uncertainty. Development of technolo-gies for propagating this uncertainty into the prediction of geotechnical parameters on the basis of the geophysical information is still a challenge, but essential for objective geotechnical site characterization and risk analysis.

AcknowledgementThis work has been supported by the German Federal Ministry of Education and Research (BMBF) under grants 03G0745 (MuSaWa) and 03G0636 (COMEXTECH). We would like to thank Steffen Popp-Hofmann, Karin Marschall, Andreas Schoßland, Helko Kotas, Marco Pohle, Simon Kögler, Hannes Steinel, Manuel Kreck (Helmholtz Centre for Environmental Research – UFZ, Leipzig) and Marcel Delock (University of Potsdam) for their support during the field campaigns.

ReferencesAster, R. C., Borchers, B. and Thurber, C. H. [2005] Parameter Estimation

and Inverse Problems. Academic Press.

Atkinson, J. H. [2000] Non-linear soil stiffness in routine design.

Géotechnique, 50, 487–508.

Boschetti, F., Dentith, M. D. and List, R. D. [1996] A fractal-based

algorithm for detecting first arrivals on seismic traces. Geophysics,

61, 1095–1102.

Dietrich, P. and Leven, C. [2006] Direct push-technologies. In: Kirsch, R.

(Ed.) Groundwater Geophysics. Springer, 321–340.

Dietrich, P. and Tronicke, J. [2009] Integrated analysis and interpretation

of cross-hole P- and S-wave tomograms: A case study. Near Surface

Geophysics, 7, 101–109.

Fahay, M. [1998] Deformation and in situ stress measurements:

Geotechnical site characterization. Proceedings of the 1st International

Conference on Site Characterization, Vol. 1, 49–68. Balkema.

Gallardo, L. [2007] Multiple cross-gradient joint inversion for geo-

spectral imaging. Geophysical Research Letters, 34, L19301, doi:

10.1029/2007GL030409.

Harris, J. M., Nolen-Hoeksema, R. C., Langan, R. T., Van Schaack, M.,

Lazaratos, S. K. and Rector, J. W. [1995] High-resolution crosswell

imaging of a west Texas carbonate reservoir: part 1 – project sum-

mary and interpretation. Geophysics, 60, 667–681.

Hausmann, J., Steinel, H., Werban, U. and Dietrich, P. [2012]

Characterisation of a meander structure using MASW and direct

push techniques. EAGE Near Surface Geoscience 2012, Extended

Abstracts.

Kennedy, J. and Eberhardt, R. C. [1995] Particle swarm optimization.

Proceedings of the IEEE International Joint Conference on Neural

Networks. 1942–1948.

Krawczyk, C. M., Polom, U. and Beilecke, T. [2013] Shear-wave reflection

seismics as a valuable tool for near-surface urban applications. The

Leading Edge, 32, 256–263.

Lehmann, B. [2007] Seismic Traveltime Tomography for Engineering and

Exploration Applications. European Association of Geoscientists

and Engineers.

tion. Resultant 2D or 3D geotechnical models, accompanied by quantitative uncertainty information, i.e. in the form of probability density information illustrating the likely range of geotechnical conditions at every model location, may allow for a reliable geotechnical risk assessment. However, to our knowledge, no such technique is known in combination with geophysical model ensembles achieved by global model space exploration. Some techniques developed for integration of multiple deterministic geophysical models and linkage of those to sparse geotechnical information may bear substan-tial potential for adaptation to model ensemble solutions (Figure 7) while preserving a proper handling of commonality between geophysical and geotechnical parameters.

ConclusionsNear-surface P- and S-wave tomography has the poten-tial to enhance geotechnical site characterization. Highly mobile P- and S-wave tomographic acquisition technologies solely using direct push technology instead of boreholes allow for efficient acquisition of high-resolution seismic tomographic data sets at irregular direct push injection locations. The potential of such mobile high-resolution tomography for efficient 2D or even 3D high-resolution P- and S-wave velocity imaging clearly goes beyond those of MASW and refraction seismic tomography. In addition to near-surface applications, such acquisition set-up is expected to offer highly accurate near-surface low velocity corrections when considered in addition to deep-looking reflection seismic surveys.

Formulation of joint inversion approaches suitable to link the model generation process of P- and S-wave tomo-graphic data in combination with efficient optimisation algorithms allowing for global exploration of the model search space are applicable to many near-surface tomo-graphic data sets without the need for high-performance computing. Resultant ensembles of equally plausible P- and S-wave velocity models allow for quantitative assessment

Figure 7 Postulation of a potential processing flow potentially capable of link-ing model ensemble solutions obtained by global optimisation quantitatively to sparse geotechnical information, e.g. obtained from direct push logs.




Paasche, H. and Tronicke, J. [2013] Global joint inversion of tomo-

graphic data – appraisal of model reconstruction ambiguity. EAGE

Near Surface Geoscience 2013, Extended Abstract.

Robertson, P. K., Sasitharan, S., Cunning, J. C. and Segs, D. C. [1995]

Shear-wave velocity to evaluate in-situ state of Ottawa sand.

Journal of Geotechnical Engineering, 121, 262–273.

Socco, V. and Strobbia, C. [2004] Surface-wave method for near-

surface characterization: A tutorial. Near Surface Geophysics, 2,

165–185.

Tronicke, J., Paasche, H. and Böniger, U. [2012] Crosshole Traveltime

tomography using particel swarm optimization. Geophysics, 77,

R19–R32.

Yang, X. S. and Deb, S. [2010] Engineering optimization by cuckoo

search. International Journal of Mathematical Modelling and

Numerical Optimisation, 1, 330–343.

Schön, J. [1998] Physical Properties of Rocks: Fundamentals and

Principles of Petrophysics. Pergamon.

Sen, M. K. and Stoffa, P. L. [1995] Global Optimization Methods in

Geophysical Inversion. Elsevier.

van der Veen, M., Spitzer, R., Green, A. G. and Wild, P. [2001] Design

and application of a towed land-streamer system for cost-effective

2-D and pseudo 3-D shallow seismic data acquisition. Geophysics,

66, 482–500.

Linder, S., Paasche, H., Tronicke, J., Niederleithinger, E. and Vienken,

T. [2010] Zonal cooperative inversion of crosshole P-wave,

S-wave, and georadar traveltime data sets. Journal of Applied

Geophysics, 72, 254–262.

Lunne, T., Robertson, P. K. and Powell, J. J. M. [1997] Cone penetra-

tion testing in geotechnical practice. Taylor and Francis.

McCormack, M. D., Zaucha, D. E. and Dushek, D. W. [1993] First-

break refraction event picking and seismic data trace editing using

neural networks. Geophysics, 58, 67–78.

Michaels, P. [2001] Use of principal component analysis to determine

down-hole tool orientation and enhance SH-waves. Journal of

Environmental and Engineering Geophysics, 6, 175–183.

Paasche, H., Werban, U. and Dietrich, P. [2009] Near-surface seismic

traveltime tomography using a direct-push source and surface-

planted receivers. Geophysics, 74, G17–G25.

Paasche, H., Tronicke, J. and Dietrich, P. [2008] Cooperative inver-

sion based on fuzzy c-means cluster analysis – application to

field data. 21st Symposium on the Application of Geophysics to

Environmental and Engineering Problems (SAGEEP), Extended

Abstracts, 94–99.

Paasche, H., Tronicke, J. and Dietrich, P. [2012] Zonal cooperative

inversion of partially co-located data sets constrained by structur-

ally a priori information. Near Surface Geophysics, 10, 103–116.

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