JL
J. Liu
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1
Seismic incoherent noise and waves scattered from objects in the crossline directions can cause 2D elastic full-waveform inversion (FWI) to produce artifacts in the resulting 2D models. We develop a complete workflow that can determine subsurface S-wave velocity (VS) models inverted from 2D near-surface seismic data more stably. We make use of a combination of supervirtual interferometry and a matched filter to accurately retrieve dominant surface waves from the field data, whereas the incoherent noise and 3D scattering events are significantly suppressed. The subsurface structures obtained from inverting the retrieved data can be interpreted together with the sections resulting from FWI of the original data to mitigate the potential misinterpretation of artifacts. Our results demonstrate that it is possible to invert 2D near-surface seismic data even when the data quality is lowered by the presence of strong noise and 3D scattered events caused by objects located in the crossline direction.
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Seismic incoherent noise and waves scattered from objects in the crossline directions can cause 2D elastic full-waveform inversion (FWI) to produce artifacts in the resulting 2D models. We develop a complete workflow that can determine subsurface S-wave velocity (VS) models inverted from 2D near-surface seismic data more stably. We make use of a combination of supervirtual interferometry and a matched filter to accurately retrieve dominant surface waves from the field data, whereas the incoherent noise and 3D scattering events are significantly suppressed. The subsurface structures obtained from inverting the retrieved data can be interpreted together with the sections resulting from FWI of the original data to mitigate the potential misinterpretation of artifacts. Our results demonstrate that it is possible to invert 2D near-surface seismic data even when the data quality is lowered by the presence of strong noise and 3D scattered events caused by objects located in the crossline direction.
At different places in the world, the local climate conditions have helped the preservation of archaeological sites to a very high degree. This has helped us understand better our history. This situation, however, is quickly changing due to the climate change we are now facing. The condition at an increasing number of ancient sites around the world is now deteriorating due to the warming climate. Obtaining high-resolution images of the subsurface of the archaeological sites without excavation can help us make better strategies for conserving these sites. Such possibilities are provided by the application of geophysical exploration methods. Among all available geophysical approaches, high-resolution reflection seismic using transverse (S-) waves is one of the few options that can provide detailed information regarding the subsurface structure beneath archaeological sites for depths up to several meters. However, most unexcavated sites are covered by soil. Near-surface seismic data acquired in such soil-covered sites are dominated by source-generated, dispersive surface waves, and sometimes surface waves caused by other anthropogenic sources, e.g., traffic and human activities in the vicinity of the seismic line. Both of these strong events can camouflage the very shallow reflections. The conventional techniques for suppression of surface waves, e.g., muting or spatial filtering, are ineffective or even detrimental to the target reflections, especially at near offsets. This is especially challenging in surveys where the available source-receiver offset range is often quite limited, and the velocity and frequency content of the surface waves largely overlap with those of the target S-wave reflections. In chapter 2, we aim to develop a data-driven way to suppress surface-wave noise and thus reveal the very shallow reflections. We make use of seismic interferometry (SI) to retrieve both source-coherent and source-incoherent surface-wave parts of the data. The retrieved surface waves are then adaptively subtracted (AS) from the recorded data, thereby exposing the hidden reflections. We apply our schemes to both synthetic and field seismic data. We show that artifacts caused by stacking surface-wave noise are greatly reduced and that reflectors, especially at very shallow depth, can be much better imaged and interpreted. The dominance of surface waves also make it impossible to identify weak diffraction signals, which is the seismic response of buried objects of small size. The diffraction events can be used to detect and locate the distribution of shallow objects. Revealing the hidden diffraction signals from under the dominant surface waves and using them for locating objects constitute another goal of this thesis. In chapters 3 and 4, we introduce an interferometric workflow for imaging subsurface objects using masked diffractions. This workflow includes three main steps. We first reveal masked diffractions by suppression of the dominant surface waves through a combination of SI and nonstationary AS. The revealed weak diffraction signal is then enhanced by cross coherence-based super virtual interferometry (SVI). Finally, we produce a diffraction image by a multipath summation approach, which can be used to interpret the locations of subsurface diffractors. We apply our method to field data acquired at an archaeological site using two different active sources. Two shallow anomalies were detected in our sections, whose locations agree well with burial burnt stones. These burnt stones have also been detected in an independent magnetic survey and in corings. The limitation of our workflow is that it can only be applied with desired resolution to S-wave data when seismic sources and receivers polarized in the cross-line direction.
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At different places in the world, the local climate conditions have helped the preservation of archaeological sites to a very high degree. This has helped us understand better our history. This situation, however, is quickly changing due to the climate change we are now facing. The condition at an increasing number of ancient sites around the world is now deteriorating due to the warming climate. Obtaining high-resolution images of the subsurface of the archaeological sites without excavation can help us make better strategies for conserving these sites. Such possibilities are provided by the application of geophysical exploration methods. Among all available geophysical approaches, high-resolution reflection seismic using transverse (S-) waves is one of the few options that can provide detailed information regarding the subsurface structure beneath archaeological sites for depths up to several meters. However, most unexcavated sites are covered by soil. Near-surface seismic data acquired in such soil-covered sites are dominated by source-generated, dispersive surface waves, and sometimes surface waves caused by other anthropogenic sources, e.g., traffic and human activities in the vicinity of the seismic line. Both of these strong events can camouflage the very shallow reflections. The conventional techniques for suppression of surface waves, e.g., muting or spatial filtering, are ineffective or even detrimental to the target reflections, especially at near offsets. This is especially challenging in surveys where the available source-receiver offset range is often quite limited, and the velocity and frequency content of the surface waves largely overlap with those of the target S-wave reflections. In chapter 2, we aim to develop a data-driven way to suppress surface-wave noise and thus reveal the very shallow reflections. We make use of seismic interferometry (SI) to retrieve both source-coherent and source-incoherent surface-wave parts of the data. The retrieved surface waves are then adaptively subtracted (AS) from the recorded data, thereby exposing the hidden reflections. We apply our schemes to both synthetic and field seismic data. We show that artifacts caused by stacking surface-wave noise are greatly reduced and that reflectors, especially at very shallow depth, can be much better imaged and interpreted. The dominance of surface waves also make it impossible to identify weak diffraction signals, which is the seismic response of buried objects of small size. The diffraction events can be used to detect and locate the distribution of shallow objects. Revealing the hidden diffraction signals from under the dominant surface waves and using them for locating objects constitute another goal of this thesis. In chapters 3 and 4, we introduce an interferometric workflow for imaging subsurface objects using masked diffractions. This workflow includes three main steps. We first reveal masked diffractions by suppression of the dominant surface waves through a combination of SI and nonstationary AS. The revealed weak diffraction signal is then enhanced by cross coherence-based super virtual interferometry (SVI). Finally, we produce a diffraction image by a multipath summation approach, which can be used to interpret the locations of subsurface diffractors. We apply our method to field data acquired at an archaeological site using two different active sources. Two shallow anomalies were detected in our sections, whose locations agree well with burial burnt stones. These burnt stones have also been detected in an independent magnetic survey and in corings. The limitation of our workflow is that it can only be applied with desired resolution to S-wave data when seismic sources and receivers polarized in the cross-line direction.
Traditional least-squares full-waveform inversion (FWI) suffers from severe local minima problems in case of the presence of strongly dispersive surface waves. Additionally, recorded wavefields are often characterized by amplitude errors due to varying source coupling and incorrect 3D-to-2D geometrical-spreading correction. Thus, least-squares FWI is considered less than suitable for near-surface applications. In this paper, we introduce an amplitude-unbiased coherency measure as a misfit function that can be incorporated into FWI. Such coherency was earlier used in phase-weighted stacking (PWS) to enhance weak but coherent signals. The benefit of this amplitude-unbiased misfit function is that it can extract information uniformly for all seismic signals (surface waves, reflections, and scattered waves). Using the adjoint-state method, we show how to calculate the gradient of this new misfit function. We validate the robustness of the new approach using checkerboard tests and synthetic data contaminated by random noise. We then apply the new FWI approach to a field dataset acquired at an archaeological site located in Ostia, Italy. The goal of this survey was to map the unexcavated archaeological remains with high-resolution. We identify a known tumulus in the FWI results. The instantaneous-phase coherency FWI results also establish that the shallow subsurface under the survey lines is quite heterogeneous. The instantaneous-phase coherency FWI of near-surface data can be a promising tool to image shallow small-scale objects buried under shallow soil covers, as found at archaeological sites.
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Traditional least-squares full-waveform inversion (FWI) suffers from severe local minima problems in case of the presence of strongly dispersive surface waves. Additionally, recorded wavefields are often characterized by amplitude errors due to varying source coupling and incorrect 3D-to-2D geometrical-spreading correction. Thus, least-squares FWI is considered less than suitable for near-surface applications. In this paper, we introduce an amplitude-unbiased coherency measure as a misfit function that can be incorporated into FWI. Such coherency was earlier used in phase-weighted stacking (PWS) to enhance weak but coherent signals. The benefit of this amplitude-unbiased misfit function is that it can extract information uniformly for all seismic signals (surface waves, reflections, and scattered waves). Using the adjoint-state method, we show how to calculate the gradient of this new misfit function. We validate the robustness of the new approach using checkerboard tests and synthetic data contaminated by random noise. We then apply the new FWI approach to a field dataset acquired at an archaeological site located in Ostia, Italy. The goal of this survey was to map the unexcavated archaeological remains with high-resolution. We identify a known tumulus in the FWI results. The instantaneous-phase coherency FWI results also establish that the shallow subsurface under the survey lines is quite heterogeneous. The instantaneous-phase coherency FWI of near-surface data can be a promising tool to image shallow small-scale objects buried under shallow soil covers, as found at archaeological sites.
Detecting small-size objects is a primary challenge at archaeological sites due to the high degree of heterogeneity present in the near surface. Although high-resolution reflection seismic imaging often delivers the target resolution of the subsurface in different near-surface settings, the standard processing for obtaining an image of the subsurface is not suitable to map local diffractors. This happens because shallow seismic-reflection data are often dominated by strong surface waves that might cover weaker diffractions and because traditional common-midpoint moveout corrections are only optimal for reflection events. We propose an approach for imaging subsurface objects using masked diffractions. These masked diffractions are first revealed by a combination of seismic interferometry and nonstationary adaptive subtraction, and then further enhanced through crosscoherence-based supervirtual interferometry. A diffraction image is then computed by a spatial summation of the revealed diffractions. We use the phase-weighted stack to enhance the coherent summation of weak diffraction signals. Using synthetic data, we show that our scheme is robust in locating diffractors from data dominated by strong Love waves. We test our method on field data acquired at an archaeological site. The resulting distribution of shallow diffractors agrees with the location of anomalous objects identified in the VS model obtained by elastic SH/Love full-waveform inversion using the same field data. The anomalous objects correspond to the position of a suspected burial, also detected in an independent magnetic survey and corings.
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Detecting small-size objects is a primary challenge at archaeological sites due to the high degree of heterogeneity present in the near surface. Although high-resolution reflection seismic imaging often delivers the target resolution of the subsurface in different near-surface settings, the standard processing for obtaining an image of the subsurface is not suitable to map local diffractors. This happens because shallow seismic-reflection data are often dominated by strong surface waves that might cover weaker diffractions and because traditional common-midpoint moveout corrections are only optimal for reflection events. We propose an approach for imaging subsurface objects using masked diffractions. These masked diffractions are first revealed by a combination of seismic interferometry and nonstationary adaptive subtraction, and then further enhanced through crosscoherence-based supervirtual interferometry. A diffraction image is then computed by a spatial summation of the revealed diffractions. We use the phase-weighted stack to enhance the coherent summation of weak diffraction signals. Using synthetic data, we show that our scheme is robust in locating diffractors from data dominated by strong Love waves. We test our method on field data acquired at an archaeological site. The resulting distribution of shallow diffractors agrees with the location of anomalous objects identified in the VS model obtained by elastic SH/Love full-waveform inversion using the same field data. The anomalous objects correspond to the position of a suspected burial, also detected in an independent magnetic survey and corings.
Book chapter
(2020)
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Ranajit Ghose , Jianhuan Liu, Deyan Draganov, Dominique Ngan-Tillard, Martijn Warnaar, Joeri Brackenhoff, Jens van den Berg, Hanna Stoger
The southern boundary of Region IV of ancient Ostia coincides with the southern limit of the excavated area of the ancient city. The perceived expanse of the city is influenced by the extent of the excavation. It is not known if the unexcavated part lying south of Region IV also contains structures of antiquity which might have important historical significance. We have carried out high-resolution, shallow seismic reflection surveys along two profiles, using shear (transverse) waves. The goal of these pilot surveys was to see if any indication of ultra-shallow scatterers, indicating potential location of shallow-buried structures, can be found in the shear wave data. The results show very distinct back-scattered shear-wave arrivals from a mysterious tumulus, whose location along Line A was known. It has been possible to interpret with reasonable confidence the location of several conspicuous, shallow scatterers in the two seismic profiles. Use of shear waves and a high-frequency, electromagnetic shear-wave vibrator was crucial to achieve seismic a resolution of nearly 25 cm. The amplitude of the scattered energy is helpful to locate the relatively strong scatterers. Our results suggest that the unexcavated areas located south of Region IV most likely contain buried underground structures. 3-D shear-wave seismic reflections together with new seismic-imaging approaches will be promising to illuminate the unknown shallow subsurface of this important archeological site in a noninvasive manner.
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The southern boundary of Region IV of ancient Ostia coincides with the southern limit of the excavated area of the ancient city. The perceived expanse of the city is influenced by the extent of the excavation. It is not known if the unexcavated part lying south of Region IV also contains structures of antiquity which might have important historical significance. We have carried out high-resolution, shallow seismic reflection surveys along two profiles, using shear (transverse) waves. The goal of these pilot surveys was to see if any indication of ultra-shallow scatterers, indicating potential location of shallow-buried structures, can be found in the shear wave data. The results show very distinct back-scattered shear-wave arrivals from a mysterious tumulus, whose location along Line A was known. It has been possible to interpret with reasonable confidence the location of several conspicuous, shallow scatterers in the two seismic profiles. Use of shear waves and a high-frequency, electromagnetic shear-wave vibrator was crucial to achieve seismic a resolution of nearly 25 cm. The amplitude of the scattered energy is helpful to locate the relatively strong scatterers. Our results suggest that the unexcavated areas located south of Region IV most likely contain buried underground structures. 3-D shear-wave seismic reflections together with new seismic-imaging approaches will be promising to illuminate the unknown shallow subsurface of this important archeological site in a noninvasive manner.
The detection of shallow buried ancient structures or objects of cultural heritage is a primary challenge for seismic surveys at archaeological sites. The knowledge of the distribution of shallow objects can assist archaeologists’ study of the past without making excavations. Excavations lead to surface exposure of the buried objects and potential damages and preservation issues. The seismic response arising from localized archaeological targets is encoded in diffractions, which can be used to locate the objects. However, the energy of a diffracted wave is usually weak and masked behind the strong presence of other coherent signals or coherent noise in the data (e.g., surface waves, specular reflections). This makes it difficult to detect and interpret reliably. In the past decades, researchers have attempted to detect various near-surface features using diffracted waves. Landa and Keydar (1998) developed a method for identifying local targets in the shallow subsurface using diffracted waves. They constructed a so-called diffraction-point-section (D-section) by concentrating diffracted waves from diffractor points. The anomalies in this D-section can be interpreted as potential scattering objects. Shtivelman and Keydar (2005) proposed a multipath summation approach to image near-surface objects by stacking diffracted energy along all possible diffraction curves defined by all veloc-ity values within a specific range. Subsequently, Shtivelman et al. (2009) improved the resolution of this multipath summation approach by introducing image-dependent weights. The above-mentioned methods have been tested earlier on field data dominated by surface waves; no identification of diffracted waves could be found. To improve the reliability of diffraction imaging, in this paper we first apply a method that consists of seismic interferometry (SI) and adaptive subtrac-tion for the suppression of high-amplitude surface-wave noise (Konstantaki et al., 2015; Liu et al., 2018). We then present an approach based on an extension of the spatial summation of weak diffractions as proposed by Shtivelman and Keydar (2005). We utilize instantaneous-phase coherency (Schimmel and Paulssen, 1997) to enhance the optimal summation of weak but coherent diffractions. In the following, we first describe the practical steps for the implementation of each of the above methods. We then demonstrate the feasibility of our approach in locating scatterers on numerically modelled data with a low signal-to-noise ratio (S/N). Finally, we test our method on field seismic data acquired at an archaeological site.
...
The detection of shallow buried ancient structures or objects of cultural heritage is a primary challenge for seismic surveys at archaeological sites. The knowledge of the distribution of shallow objects can assist archaeologists’ study of the past without making excavations. Excavations lead to surface exposure of the buried objects and potential damages and preservation issues. The seismic response arising from localized archaeological targets is encoded in diffractions, which can be used to locate the objects. However, the energy of a diffracted wave is usually weak and masked behind the strong presence of other coherent signals or coherent noise in the data (e.g., surface waves, specular reflections). This makes it difficult to detect and interpret reliably. In the past decades, researchers have attempted to detect various near-surface features using diffracted waves. Landa and Keydar (1998) developed a method for identifying local targets in the shallow subsurface using diffracted waves. They constructed a so-called diffraction-point-section (D-section) by concentrating diffracted waves from diffractor points. The anomalies in this D-section can be interpreted as potential scattering objects. Shtivelman and Keydar (2005) proposed a multipath summation approach to image near-surface objects by stacking diffracted energy along all possible diffraction curves defined by all veloc-ity values within a specific range. Subsequently, Shtivelman et al. (2009) improved the resolution of this multipath summation approach by introducing image-dependent weights. The above-mentioned methods have been tested earlier on field data dominated by surface waves; no identification of diffracted waves could be found. To improve the reliability of diffraction imaging, in this paper we first apply a method that consists of seismic interferometry (SI) and adaptive subtrac-tion for the suppression of high-amplitude surface-wave noise (Konstantaki et al., 2015; Liu et al., 2018). We then present an approach based on an extension of the spatial summation of weak diffractions as proposed by Shtivelman and Keydar (2005). We utilize instantaneous-phase coherency (Schimmel and Paulssen, 1997) to enhance the optimal summation of weak but coherent diffractions. In the following, we first describe the practical steps for the implementation of each of the above methods. We then demonstrate the feasibility of our approach in locating scatterers on numerically modelled data with a low signal-to-noise ratio (S/N). Finally, we test our method on field seismic data acquired at an archaeological site.
We develop a new approach to locate very shallow subsurface objects using seismic diffractions of low signal-tonoise ratio. In our approach we use the diffraction arrivals recorded from the subsurface objects. To image the objects, we apply spatial instantaneous-phase-coherency summation along diffraction hyperbolae. We demonstrate the performance of our method using synthetic and field data.
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We develop a new approach to locate very shallow subsurface objects using seismic diffractions of low signal-tonoise ratio. In our approach we use the diffraction arrivals recorded from the subsurface objects. To image the objects, we apply spatial instantaneous-phase-coherency summation along diffraction hyperbolae. We demonstrate the performance of our method using synthetic and field data.
High-resolution reflection seismics is a powerful tool that can provide the required resolution for subsurface imaging and monitoring in urban settings. Shallow seismic reflection data acquired in soil-covered sites are often contaminated by source-coherent surface waves and other linear moveout noises (LMON) that might be caused by, e.g., anthropogenic sources or harmonic distortion in vibroseis data. In the case of shear-wave seismic reflection data, such noises are particularly problematic as they overlap the useful shallow reflections. We have developed new schemes for suppressing such surface-wave noise and LMON while still preserving shallow reflections, which are of great interest to high-resolution near-surface imaging. We do this by making use of two techniques. First, we make use of seismic interferometry to retrieve predominantly source-coherent surface waves and LMON. We then adaptively subtract these dominant source-coherent surface waves and LMON from the seismic data in a separate step. We illustrate our proposed method using synthetic and field data. We compare results from our method with results from frequency–wave-number (f-k) filtering. Using synthetic data, we show that our schemes are robust in separating shallow reflections from source-coherent surface waves and LMON even when they share very similar velocity and frequency contents, whereas f-k filtering might cause undesirable artefacts. Using a field shear-wave reflection dataset characterised by overwhelming LMON, we show that the reflectors at a very shallow depth can be imaged because of significant suppression of the LMON due to the application of the scheme that we have developed.
...
High-resolution reflection seismics is a powerful tool that can provide the required resolution for subsurface imaging and monitoring in urban settings. Shallow seismic reflection data acquired in soil-covered sites are often contaminated by source-coherent surface waves and other linear moveout noises (LMON) that might be caused by, e.g., anthropogenic sources or harmonic distortion in vibroseis data. In the case of shear-wave seismic reflection data, such noises are particularly problematic as they overlap the useful shallow reflections. We have developed new schemes for suppressing such surface-wave noise and LMON while still preserving shallow reflections, which are of great interest to high-resolution near-surface imaging. We do this by making use of two techniques. First, we make use of seismic interferometry to retrieve predominantly source-coherent surface waves and LMON. We then adaptively subtract these dominant source-coherent surface waves and LMON from the seismic data in a separate step. We illustrate our proposed method using synthetic and field data. We compare results from our method with results from frequency–wave-number (f-k) filtering. Using synthetic data, we show that our schemes are robust in separating shallow reflections from source-coherent surface waves and LMON even when they share very similar velocity and frequency contents, whereas f-k filtering might cause undesirable artefacts. Using a field shear-wave reflection dataset characterised by overwhelming LMON, we show that the reflectors at a very shallow depth can be imaged because of significant suppression of the LMON due to the application of the scheme that we have developed.
The Green's function between two receivers can be retrieved using seismic interferometry (SI) by cross-correlation, as if one of the receivers were a virtual seismic source. When the wavefields experience intrinsic losses during propagation, non-physical arrivals (ghosts) would appear in the retrieved result. These ghosts are a result of internal reflections inside the different layers lying between the subsurface sources and the receivers. Recent studies have introduced a stable method to monitor the layer-specific changes in quality factor (Q) using the ghosts retrieved by SI applied to a horizontal-well data. However, drilling a horizontal well is much more complicated and expensive than drilling a conventional vertical well. Because of this, we show here how the Q-estimation method introduced for the horizontal well can be adapted to monitor layer-specific changes of Q using a vertical well. In order to improve the accuracy of the Q-estimation, we propose a grid-searching method to detect the optimal effective Q. We illustrate our method using numerically modelling data from a horizontal and a vertical well.
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The Green's function between two receivers can be retrieved using seismic interferometry (SI) by cross-correlation, as if one of the receivers were a virtual seismic source. When the wavefields experience intrinsic losses during propagation, non-physical arrivals (ghosts) would appear in the retrieved result. These ghosts are a result of internal reflections inside the different layers lying between the subsurface sources and the receivers. Recent studies have introduced a stable method to monitor the layer-specific changes in quality factor (Q) using the ghosts retrieved by SI applied to a horizontal-well data. However, drilling a horizontal well is much more complicated and expensive than drilling a conventional vertical well. Because of this, we show here how the Q-estimation method introduced for the horizontal well can be adapted to monitor layer-specific changes of Q using a vertical well. In order to improve the accuracy of the Q-estimation, we propose a grid-searching method to detect the optimal effective Q. We illustrate our method using numerically modelling data from a horizontal and a vertical well.
High-resolution reflection seismics can be very helpful in subsurface imaging and monitoring in urban environments and in archaeological sites. An obstacle that hinders the success of high-resolution reflection seismic imaging of the very shallow targets is the presence of source-generated surface waves at soil-covered sites and surface waves generated by other anthrogenic sources, e.g., traffic and construction activities in the vicinity of the seismic line. Both of these can hide the very shallow reflection events. We have developed new schemes involving seismic interferometry (SI) to retrieve both source-coherent (and/or source-incoherent) surface waves part of data. The retrieved surface waves are then adaptively subtracted from the raw data, thereby exposing hidden reflections. We illustrate results on both synthetic and field seismic data. We show that artefacts caused by stacking the surface-wave noise are greatly reduced, and that reflectors, especially at very shallow depth, can be much better imaged and interpreted.
...
High-resolution reflection seismics can be very helpful in subsurface imaging and monitoring in urban environments and in archaeological sites. An obstacle that hinders the success of high-resolution reflection seismic imaging of the very shallow targets is the presence of source-generated surface waves at soil-covered sites and surface waves generated by other anthrogenic sources, e.g., traffic and construction activities in the vicinity of the seismic line. Both of these can hide the very shallow reflection events. We have developed new schemes involving seismic interferometry (SI) to retrieve both source-coherent (and/or source-incoherent) surface waves part of data. The retrieved surface waves are then adaptively subtracted from the raw data, thereby exposing hidden reflections. We illustrate results on both synthetic and field seismic data. We show that artefacts caused by stacking the surface-wave noise are greatly reduced, and that reflectors, especially at very shallow depth, can be much better imaged and interpreted.
It is challenging to image the very shallow structures in a heterogeneous dyke using traditional geophysical methods. With the aim to reveal these structures, a low-budget seismic S-wave reflection survey was carried out over a dyke with a fixed-receivers array. We applied seismic interferometry to this dataset in order to retrieve
surface waves and then adaptively subtracted these surface waves from the original recordings. Combined interpretation of the stacked images obtained from the original data and that from the data after adaptive subtraction reveals more complete shallow structures inside the dyke.
...
It is challenging to image the very shallow structures in a heterogeneous dyke using traditional geophysical methods. With the aim to reveal these structures, a low-budget seismic S-wave reflection survey was carried out over a dyke with a fixed-receivers array. We applied seismic interferometry to this dataset in order to retrieve
surface waves and then adaptively subtracted these surface waves from the original recordings. Combined interpretation of the stacked images obtained from the original data and that from the data after adaptive subtraction reveals more complete shallow structures inside the dyke.