Crosscoherence-based interferometry for the retrieval of first arrivals and subsequent tomographic imaging of differential weathering

Exhumation of crust exposes rocks to weathering agents that weaken the rocks’ mechanical strength. Weakened rocks will have lower seismic velocity than intact rocks and can therefore be mapped using seismic methods. However, if the rocks are heavily weathered, they will attenuate controlled-source seismic waves to such a degree that the recorded wavefield would become dominated by ambient noise and/or surface waves. Therefore, we have examined the structure of differential weathering by first-break traveltime tomography over a seismic profile extending approximately 3.5 km and acquired at a mining site in Zambia using explosive sources and a source based on the swept-impact seismic technique (SIST). Seismic interferometry has been tested for the retrieval of supervirtual first arrivals masked by uncorrelated noise. However, use of crosscorrelation in the retrieval process makes the method vulnerable to changes in the source signal (explosives and SIST). Thus, we have developed a crosscoherence-based seismic-interferometry method to tackle this shortcoming. We investigate the method’s efficiency in retrieving first arrivals and, simultaneously, correctly handling variations in the source signal. Our results illustrate the superiority of the crosscoherence- over crosscorrelation-based method for retrieval of the first arrivals, especially in alleviating spurious ringyness and in terms of the signal-to-noise ratio. These benefits are observable in the greater penetration depth and the improved resolution of the tomography sections. The tomographic images indicate isolated bodies of higher velocities, which may be interpreted as fresh rocks embedded into a heavily weathered regolith, providing a conspicuous example of differential weathering. Our study advances the potential of seismic methods for providing better images of the near surface (the critical zone).

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Reversed Multi-offset VSP Traveltime Tomography Employing Direct-push Technology for Near-surface Seismic Velocity Imaging

10.3997/2214-4609-pdb.241.paasche_paper1 ◽

2009 ◽

Author(s):

H. Paasche ◽

U. Werban ◽

P. Dietrich

Keyword(s):

Seismic Velocity ◽

Near Surface ◽

Traveltime Tomography ◽

Direct Push ◽

Velocity Imaging ◽

Push Technology

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Seismic velocity recovery following the 2015 Mw 7.8 Gorkha earthquake, Nepal: Towards a coupled vision of damage and hydrological-induced velocity variations

10.5194/egusphere-egu21-12714 ◽

2021 ◽

Author(s):

Luc Illien ◽

Christoph Sens-Schönfelder ◽

Christoff Andermann ◽

Odin Marc ◽

Kristen Cook ◽

...

Keyword(s):

Seismic Waves ◽

Seismic Velocity ◽

Monsoon Season ◽

Seismic Interferometry ◽

Linear Superposition ◽

Gorkha Earthquake ◽

Ground Shaking ◽

Velocity Variations ◽

Velocity Changes ◽

Induced Velocity

Following the passage of seismic waves, most geomaterials experience non-linear mesoscopic elasticity (NLME). This is described by a drop in elastic moduli that precedes a subsequent recovery of physical properties over a relaxation timescale. Thanks to the development of seismic interferometry techniques that allows for the continuous monitoring of relative seismic velocity changes &#948;v in the subsurface, observations of NLME (&#948;vNLME) in the field are now numerous. In parallel, a growing community uses seismic interferometry to monitor velocity changes induced by seasonal hydrological variations (&#948;vhydro). Monitoring of these variations are often independently done and a linear superposition of both effects is mostly assumed when decomposing the observed &#948;v signal (&#948;v =&#160; &#948;vNLME + &#948;vhydro). However, transient hydrological behaviour following co-seismic ground shaking has been widely reported in boreholes measurements and streamflow, which suggests that&#160; &#948;vhydro may be impacted by the transient variation of material properties caused by NLME. In this presentation, we attempt to characterize the relative seismic velocity variations &#948;v retrieved from a small dense seismic array in Nepal that was deployed in the aftermath of the &#160;2015 Mw 7.8 Gorkha earthquake and that is prone to highly variable hydrological conditions. We first investigated the effect of aftershocks in computing &#948;v at a 10-minute resolution centered around significant ground shaking events. After correcting &#948;v for NLME caused by the Gorkha earthquake and its subsequent aftershocks, we test whether the corresponding residuals are in agreement with the background hydrological behaviour which we inferred from a calibrated hydrological model. This is not the case and we find that transient hydrological properties improve the data description in the early phase after the mainshock. We report three distinct relaxation time scales that are relevant for the recovery of seismic velocity at our field site:&#160; 1. A long time scale activated by the main shock of the Gorkha earthquake (~1 year) 2. A relatively short timescale (1-3 days) that occurs after moderate aftershocks. 3. An intermediate timescale (4-6 months) during the 2015 monsoon season that corresponds to the recovery of the hydrological system. This timescale could correspond to an enhanced permeability caused by Gorkha ground shaking. Our study demonstrates the capability of seismic interferometry to monitor transient hydrological properties after earthquakes at a spatial scale that is not available with classical hydrological measurements. This investigation demands calibrated hydrological models and a framework in which the different forcing of &#948;v are coupled.

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Seismo-Acoustic Shockwave Isolation for Low-Yield Local Explosions

10.5194/egusphere-egu2020-9799 ◽

2020 ◽

Author(s):

Joshua Dickey ◽

Michael Pasyanos ◽

Richard Martin ◽

Raúl Peña

Keyword(s):

Ground Motion ◽

Acoustic Waves ◽

Seismic Waves ◽

Acoustic Analysis ◽

Seismic Velocity ◽

Forensic Analysis ◽

Great Success ◽

Near Surface ◽

The Earth ◽

Leave One Out

Seismic and acoustic recordings have long been used for the forensic analysis of various natural and anthropogenic events, especially in the realm of nuclear treaty monitoring. More recently, multi-phenomenological analysis has been applied to these signals with great success, providing unique constraints for studying a broad range of source events, including man-made noise, earthquakes and explosions. In particular, the fusion of seismic and infrasonic data has proven valuable for the analysis of explosive yield, significantly improving on the yield estimates obtained from either seismic or acoustic analysis alone.Unfortunately, the seismo-acoustic analysis of local explosions is complicated by the fact that the two phenomena are potentially co-dependent. Large seismic waves displace the earth like a piston, potentially inducing acoustic waves into the atmosphere as they pass. Similarly, large acoustic waves can couple into the earth, inducing ground motion along their path. This co-dependence can be problematic, particularly when the passing acoustic shockwave couples into the earth coincident with a seismic phase arrival, thereby corrupting the signal.To address this problem, we present a method for isolating the shockwave response of a seismic sensor, such that any underlying seismic phase arrivals can be recovered. This is accomplished by employing the adaptive noise cancellation model, where a co-located infrasound sensor is used as a reference measurement for the shockwave. In this model, the adaptive filter learns the transform between the relative atmospheric pressure (as recorded by the infrasound sensor), and the resulting ground motion (as recorded by the seismometer). In this way, the filtered infrasound recording approximates the seismic shockwave response, and can be subtracted from the seismograph to recover the phase arrivals.The experimental data comes from a set of three low-yield near-surface chemical explosions conducted by LLNL as part of a field experiment, known as FE2. The explosions were recorded at eight stations, located at varying distances from the source (between 64m and 2km), with each station consisting of a co-located three-component seismic velocity transducer and differential infrasound sensor. The adaptive technique is demonstrated for recovering seismic arrivals in both the vertical and horizontal channels across all eight stations, and evaluated using leave-one-out cross-validation across the three explosions.

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Denoising ambient seismic field correlation functions with convolutional autoencoders

Geophysical Journal International ◽

10.1093/gji/ggz509 ◽

2019 ◽

Vol 220 (3) ◽

pp. 1521-1535

Author(s):

Loïc Viens ◽

Chris Van Houtte

Keyword(s):

Real Time ◽

Correlation Functions ◽

Cross Correlation ◽

Seismic Velocity ◽

Temporal Evolution ◽

Seismic Interferometry ◽

Filter Method ◽

Near Surface ◽

Single Station ◽

Field Correlation

SUMMARY Seismic interferometry is an established method for monitoring the temporal evolution of the Earth’s physical properties. We introduce a new technique to improve the precision and temporal resolution of seismic monitoring studies based on deep learning. Our method uses a convolutional denoising autoencoder, called ConvDeNoise, to denoise ambient seismic field correlation functions. The technique can be applied to traditional two-station cross-correlation functions but this study focuses on single-station cross-correlation (SC) functions. SC functions are computed by cross correlating the different components of a single seismic station and can be used to monitor the temporal evolution of the Earth’s near surface. We train and apply our algorithm to SC functions computed with a time resolution of 20 min at seismic stations in the Tokyo metropolitan area, Japan. We show that the relative seismic velocity change [dv/v(t)] computed from SC functions denoised with ConvDeNoise has less variability than that calculated from raw SC functions. Compared to other denoising methods such as the SVD-based Wiener Filter method developed by Moreau et al., the dv/v results obtained after using our algorithm have similar precision. The advantage of our technique is that once the algorithm is trained, it can be apply to denoise near-real-time SC functions. The near-real-time aspect of our denoising algorithm may be useful for operational hazard forecasting models, for example when applying seismic interferometry at an active volcano.

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Acquisition/Processing

The Leading Edge ◽

10.1190/tle40060460.1 ◽

2021 ◽

Vol 40 (6) ◽

pp. 460-463

Author(s):

Lionel J. Woog ◽

Anthony Vassiliou ◽

Rodney Stromberg

Keyword(s):

Model Building ◽

Seismic Velocity ◽

Signal To Noise Ratio ◽

Velocity Model ◽

High Signal ◽

Processing Unit ◽

High Quality ◽

Near Surface ◽

Velocity Model Building ◽

Static Corrections

In seismic data processing, static corrections for near-surface velocities are derived from first-break picking. The quality of the static corrections is paramount to developing an accurate shallow velocity model, a model that in turn greatly impacts the subsequent seismic processing steps. Because even small errors in first-break picking can greatly impact the seismic velocity model building, it is necessary to pick high-quality traveltimes. Whereas various artificial intelligence-based methods have been proposed to automate the process for data with medium to high signal-to-noise ratio (S/N), these methods are not applicable to low-S/N data, which still require intensive labor from skilled operators. We successfully replace 160 hours of skilled human work with 10 hours of processing by a single NVIDIA Quadro P6000 graphical processing unit by reducing the number of human picks from the usual 5%–10% to 0.19% of available gathers. High-quality inferred picks are generated by convolutional neural network-based machine learning trained from the human picks.

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Near-surface characterization using traveltime and full-waveform inversion with vertical and horizontal component seismic data

Interpretation ◽

10.1190/int-2018-0132.1 ◽

2019 ◽

Vol 7 (1) ◽

pp. T141-T154 ◽

Cited By ~ 4

Author(s):

Md. Iftekhar Alam

Keyword(s):

Surface Characterization ◽

Seismic Waves ◽

Seismic Velocity ◽

Waveform Inversion ◽

Horizontal Component ◽

Full Waveform Inversion ◽

Near Surface ◽

Velocity Modeling ◽

Full Waveform ◽

Attenuation Models

Seismic imaging of the shallow subsurface (approximately 5 m) can be very challenging when reflections are absent and the data are dominated by ground roll. I analyzed the transmission coda to produce fine-scale, interpretable vertical and horizontal component seismic velocity ([Formula: see text] and [Formula: see text]) models using full-waveform inversion (FWI). Application of FWI is tested through imaging two buried targets. The first target is a pair of well-documented utility pipes with known diameters (0.8 m) and burial depths (approximately 1.5 m). The second target is a poorly documented former location of the pipe(s), which is now a backfilled void. Data are acquired along a 23 m 2D profile using a static array with single-component vertical and horizontal geophones. Our results indicate considerable velocity updates in the [Formula: see text] and [Formula: see text] models across the pipes and backfill. The pipes appear as negative velocity updates in the final inverted [Formula: see text] and [Formula: see text] models, whereas the backfilled area represents negative and positive velocity updates in the [Formula: see text] and [Formula: see text] models, respectively. Variations of the polarities in the inverted models ([Formula: see text] and [Formula: see text]) across the backfill can be indicative of the medium, which respond differently to the vertical and horizontal component seismic waves. The attenuation models show a general decreasing trend with increasing depth. Therefore, simultaneous applications of vertical ([Formula: see text]) and horizontal ([Formula: see text]) component seismic velocity modeling can be an effective tool to understand the subsurface medium in near-surface characterization.

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Seismic velocity estimation using time-reversal focusing

Geophysics ◽

10.1190/geo2017-0569.1 ◽

2018 ◽

Vol 83 (4) ◽

pp. U43-U50 ◽

Cited By ~ 5

Author(s):

Ariel Lellouch ◽

Evgeny Landa

Keyword(s):

Wave Equation ◽

Time Reversal ◽

Seismic Velocity ◽

Signal To Noise Ratio ◽

Onset Time ◽

Velocity Model ◽

Source Location ◽

Velocity Estimation ◽

Adequate Model ◽

Traveltime Tomography

Seismic velocity estimation is a challenging task, especially when no initial model is present. In most cases, a traveltime tomography approach is used as a significant part of the workflow. However, it requires noise-sensitive, time-consuming picking and uses a ray approximation of the wave equation. Time reversal (TR) is a fundamental physical concept, based on the wave equation’s invariance under TR operation. If the recorded wavefield is reversed and back-propagated into the medium, it will focus at its original source location regardless of the complexity of the medium. We use this property for seismic velocity analysis, formulated as an inversion problem with focusing at the known source location and onset time as the objective function. It is globally solved using competitive particle swarm optimization and an adequate model parameterization. This approach has the advantages of using the wave equation, being picking-free, handling low signal-to-noise ratio and requiring neither information on the source wavelet nor an initial velocity model. Although the method is discussed in the framework of direct source-receiver path acquisition, the foundations for its use with conventional reflection data are laid. We have determined the method’s usefulness and limitations using synthetic and field crosshole acquisition examples. In both cases, inversion results are compared with a standard traveltime tomography approach and illustrate the advantages of using TR focusing.

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Near-surface seismic traveltime tomography using a direct-push source and surface-planted geophones

Geophysics ◽

10.1190/1.3131612 ◽

2009 ◽

Vol 74 (4) ◽

pp. G17-G25 ◽

Cited By ~ 12

Author(s):

Hendrik Paasche ◽

Ulrike Werban ◽

Peter Dietrich

Keyword(s):

Velocity Distribution ◽

Seismic Velocity ◽

Velocity Model ◽

Unconsolidated Sediments ◽

Alluvial Deposits ◽

Near Surface ◽

Traveltime Tomography ◽

Direct Push ◽

Refraction Seismic ◽

Push Technology

Information about seismic velocity distribution in heterogeneous near-surface sedimentary deposits is essential for a variety of environmental and engineering geophysical applications. We have evaluated the suitability of the minimally invasive direct-push technology for near-surface seismic traveltime tomography. Geophones placed at the surface and a seismic source installed temporarily in the subsurface by direct-push technology quickly acquire reversed multioffset vertical seismic profiles (VSPs). The first-arrival traveltimes of these data were used to reconstruct the 2D seismic velocity distribution tomographically. After testing this approach on synthetic data, we applied it to field data collected over alluvial deposits in a former river floodplain. The resulting velocity model contains information about high- and low-velocity anomalies and offers a significantly deeper penetration depth than conventional refraction tomography using surface-planted sources and receivers at the investigated site. A combination of refraction seismic and direct-push data increases resolution capabilities in the unsaturated zone and enables reliable reconstruction of velocity variations in near-surface unconsolidated sediments. The final velocity model structurally matches the results of cone-penetration tests and natural gamma-radiation data acquired along the profile. The suitability of multiple rapidly acquired reverse VSP surveys for 2D tomographic velocity imaging of near-surface unconsolidated sediments was explored.

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Physics-Based Relationship for Pore Pressure and Vertical Stress Monitoring Using Seismic Velocity Variations

Remote Sensing ◽

10.3390/rs13142684 ◽

2021 ◽

Vol 13 (14) ◽

pp. 2684

Author(s):

Eldert Fokker ◽

Elmer Ruigrok ◽

Rhys Hawkins ◽

Jeannot Trampert

Keyword(s):

Pore Pressure ◽

Seismic Velocity ◽

Pressure Head ◽

Groundwater Table ◽

Surface Velocity ◽

Seismic Velocities ◽

Stress Monitoring ◽

Near Surface ◽

Velocity Variations ◽

Velocity Changes

Previous studies examining the relationship between the groundwater table and seismic velocities have been guided by empirical relationships only. Here, we develop a physics-based model relating fluctuations in groundwater table and pore pressure with seismic velocity variations through changes in effective stress. This model justifies the use of seismic velocity variations for monitoring of the pore pressure. Using a subset of the Groningen seismic network, near-surface velocity changes are estimated over a four-year period, using passive image interferometry. The same velocity changes are predicted by applying the newly derived theory to pressure-head recordings. It is demonstrated that the theory provides a close match of the observed seismic velocity changes.

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Crustal Structure across Central Scandinavian Peninsula along Silver Road refraction profile

10.5194/egusphere-egu21-15666 ◽

2021 ◽

Author(s):

Metin Kahraman ◽

Hans Thybo ◽

Irina Artemieva ◽

Alexey Shulgin ◽

Alireza Malehmir ◽

...

Keyword(s):

Atlantic Ocean ◽

North Atlantic ◽

Baltic Shield ◽

Velocity Structure ◽

Seismic Velocity ◽

Seismic Profile ◽

High Mountain ◽

Mountain Range ◽

Air Gun ◽

The Baltic

The Baltic Shield is located in the northern part of Europe, which formed by amalgamation of a series of terranes and microcontinents during the Archean to the Paleoproterozoic, followed by significant modification in Neoproterozoic to Paleozoic time. The Baltic Shield includes an up-to 2500 m high mountain range, the Scandes , along the western North Atlantic coast, despite being a stable craton located far from any active plate boundary.We study a crustal scale seismic profile experiment in northern Scandinavia between 63oN and 71oN. Our Silverroad seismic profile extends perpendicular to the coastline around Lofoten and extends ~300km in a northwest direction across the shelf into the Atlantic Ocean and ~300km in a southeastern direction across the Baltic Shield. The seismic data were acquired with 5 explosive sources and 270 receivers onshore; 16 ocean bottom seismometers and air gun shooting from the vessel Hakon Mosby were used to collect both offshore and onshore.We present the results from raytracing modelling of the seismic velocity structure along the profile. The outputs of this experiment will help to solve high onshore topography and anomalous and heterogeneous bathymetry of the continental lithosphere around the North Atlantic Ocean. The results show crustal thinning from the shield onto the continental shelf and further into the oceanic part. Of particular interest is the velocity below the high topography of the Scandes, which will be discussed in relation to isostatic equilibrium along the profile.

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