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- Volume 18, Issue 5, 2020
Near Surface Geophysics - Volume 18, Issue 5, 2020
Volume 18, Issue 5, 2020
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Wind turbine induced seismic signals: the large‐scale SMARTIE1 experiment and a concept to define protection radii for recording stations
Authors Nikolaus Lerbs, Toni Zieger, Joachim Ritter and Michael KornABSTRACTWind turbines produce mechanical energy that can propagate to the ground and disturb sensitive measurements such as seismic recordings. The aim of the large‐scale experiment Seismic Monitoring And Research of wind Turbine Induced Emissions (SMARTIE1) at a single wind turbine in Pfinztal (SW Germany) is to understand how wind turbines emit seismic signals under different operating conditions and how these seismic signals propagate through the local subsurface. The main objectives of SMARTIE1 are the investigation of wind turbine induced seismic signals, the characteristics of their propagation behaviour, as well as the radiation pattern of a single wind turbine as defined using particle motions. Moreover, we quantify the emission of the wind turbine induced seismic signals with respect to the wind speed. The combination of the wind turbine's emission into the subsurface and the attenuation behaviour of the seismic signals (ground motion velocity) can be used to estimate protection radii around seismic stations to ensure the recording of seismic signals without noticeable influences of the wind turbines. In this study, we detect several discrete wind turbine induced frequency peaks ranging from 1 to 10 Hz. We identify a radiation pattern of the wind turbine, which could give further insights into the interaction between the movement of the wind turbine's nacelle and the generation of the wind turbine induced seismic signals. Using profile measurements with a maximum distance of almost 3 km each, we fit a power‐law decay for power spectral density proportional to . The attenuation factor, , ranges from 0.7 to 1.3 for lower frequencies between 1 and 4 Hz, and increases to = 2.3 for the higher frequency peak around 5.25 Hz. Finally, we present an example of estimation of a protection radius around the seismic station of the Collm Observatorium that is part of the German Regional Seismic Network. The example protection radius around Collm Observatorium regarding this single wind turbine is reached at a minimum distance of 3.7 km.
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Exploring a near‐surface subsidence over a rehabilitated underground mine through ambient seismic noise tomography in combination with other geophysical methods
ABSTRACTAn unexpected surface subsidence in Mexico City on 19 May 2015 prompted a detailed geophysical investigation of the three‐dimensional structure of a collapsed‐soil mine located in a section of the Chapultepec Park in the vicinity of an artificial lake. As revealed from past geological explorations, the subsoil at the site consists of volcano‐sedimentary materials that were quarried in the mid‐20th century; subsequently, during the construction of the park, most of those mines had been only partially rehabilitated, with a potential risk of land subsidence. Near‐surface imaging techniques based on ambient seismic noise as well as microgravimetry, electrical resistivity tomography, shallow seismic refraction methods were evaluated for their applicability to characterize the structure of the collapsed mine. Tomography images computed using ambient‐noise array data characterized the extent of the underground mine showing high‐velocity anomaly, while results from microgravimetry and electrical resistivity tomography analyses indicated the structure through weak contrasts in gravity and resistivity anomalies. Additionally, electrical resistivity tomography results also illustrated the saturated nature of the subsoil. While different methods exhibit different capabilities to constrain such a small spatial feature, the present study highlighted the scope of an integrated approach in confirming the existence of potential voids as well as to estimate soil‐subsidence hazard. In terms of operational convenience and rapid performance, the ambient noise tomography method proved to be a relatively efficient and economical reconnaissance tool for identifying 3D velocity contrasts in an urban environment.
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Numerical comparison of Rayleigh and Love full waveform inversion in characterizing soil spatial variability for near‐surface engineering applications
Authors Siavash Mahvelati and Joseph Thomas CoeABSTRACTThe use of surface wave testing for near‐surface engineering applications has increased in recent years. Typical surface wave analysis is based on the dispersion of surface waves in one‐dimensional layered models. One‐dimensional models are inappropriate for measurements at sites with appreciable lateral variability, a likely scenario in many engineering applications. Use of such models can subsequently undermine the reliability and accuracy of the surface wave results. Full waveform inversion (FWI) is a high‐resolution imaging technique that is proven to outperform the conventional dispersion‐based analysis of surface waves. Much of the near‐surface literature has focused on full waveform inversion of Rayleigh waves developed by the interaction of primary‐ and vertically polarized shear waves (P‐SV), and the capabilities of surface waves generated by horizontally polarized shear waves (Love waves) in mapping near‐surface spatial variabilities have not been fully explored. In this numerical study, full waveform inversion of Rayleigh and Love waves was performed on two different spatially correlated Gaussian random fields (mean VS of 200 and 500 m/s) to mimic the natural spatial variability of geologic materials. Each soil structure was produced at a low and high level of stiffness variability. Two sources with different frequency contents, 25 and 50 Hz, were used to evaluate the effects of source characteristics on the resolution of Rayleigh and Love waveform inversions. The inverted results from the high‐velocity domain demonstrated that Love waveform inversion using high‐frequency seismic sources outperforms Rayleigh full waveform inversion in detecting the shape and the velocities of horizontally deposited geologic materials. Results from the low‐velocity domain also confirmed that Love full waveform inversion was comparable or superior to Rayleigh full waveform inversion, though the performance difference was less significant. However, the 25‐Hz frequency inversions yielded superior results than the 50‐Hz frequency inversions for the low‐velocity domain because the dominant wavelength of the high‐frequency signals becomes so small that it offers an impractically small investigation depth.
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Transdimensional and Hamiltonian Monte Carlo inversions of Rayleigh‐wave dispersion curves: a comparison on synthetic datasets
Authors Mattia Aleardi, Alessandro Salusti and Silvio PieriniABSTRACTWe compare two Monte Carlo inversions that aim to solve some of the main problems of dispersion curve inversion: deriving reliable uncertainty appraisals, determining the optimal model parameterization and avoiding entrapment in local minima of the misfit function. The first method is a transdimensional Markov chain Monte Carlo that considers as unknowns the number of model parameters, that is the locations of layer boundaries together with the Vs and the Vp/Vs ratio of each layer. A reversible‐jump Markov chain Monte Carlo algorithm is used to sample the variable‐dimension model space, while the adoption of a parallel tempering strategy and of a delayed rejection updating scheme improves the efficiency of the probabilistic sampling. The second approach is a Hamiltonian Monte Carlo inversion that considers the Vs, the Vp/Vs ratio and the thickness of each layer as unknowns, whereas the best model parameterization (number of layer) is determined by applying standard statistical tools to the outcomes of different inversions running with different model dimensionalities. This work has a mainly didactic perspective and, for this reason, we focus on synthetic examples in which only the fundamental mode is inverted. We perform what we call semi‐analytical and seismic inversion tests on 1D subsurface models. In the first case, the dispersion curves are directly computed from the considered model making use of the Haskell–Thomson method, while in the second case they are extracted from synthetic shot gathers. To validate the inversion outcomes, we analyse the estimated posterior models and we also perform a sensitivity analysis in which we compute the model resolution matrices, posterior covariance matrices and correlation matrices from the ensembles of sampled models. Our tests demonstrate that major benefit of the transdimensional inversion is its capability of providing a parsimonious solution that automatically adjusts the model dimensionality. The downside of this approach is that many models must be sampled to guarantee accurate posterior uncertainty. Differently, less sampled models are required by the Hamiltonian Monte Carlo algorithm, but its limits are the computational effort related to the Jacobian computation, and the multiple inversion runs needed to determine the optimal model parameterization.
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Reprocessing of high‐resolution seismic data for imaging of shallow groundwater resources in glacial deposits, SE Sweden
Authors Ruixue Sun, Ayse Kaslilar and Christopher JuhlinABSTRACTReprocessing of high‐resolution seismic reflection data over groundwater‐bearing glacial deposits near Heby, southeastern Sweden, improved the images of near‐surface structure at this site. Post‐stack time migration and pre‐stack depth migration were tested and compared to determine the improvements on imaging an undulating bedrock surface. The pre‐stack depth migration image displays better continuity of the dipping structures within the glacial sediments and provides a more detailed topography of the bedrock reflector. First‐arrival picks were used to define an initial model for input into tomographic inversion. The tomography result then formed the basis for building the migration velocity model. The final pre‐stack depth migration image shows a strong reflection at around 35 m elevation (about 9 m below the surface) that can be correlated to a thin (0.2 m) hard silt layer. The upper 20 m of overburden is interpreted to consist of clay, and the seismic images show weaker sub‐horizontal reflections within this unit, except for the strong silt reflection, consistent with our modelling results. Below 20 m, sand/gravel sediments are present and overlay the bedrock. Forward modelling based on the pre‐stack depth migration image and subsequent processing shows that pre‐stack depth migration provides a higher resolution image compared with post‐stack time migration. Our study shows that pre‐stack depth migration is preferable to post‐stack time migration even for the shallow near‐surface seismic data acquired at Heby, and that integrating tomography, migration, modelling and geological information provides a better understanding of the structure which these groundwater resources are contained in.
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Analysis of measurement errors from electrical resistivity imaging investigation of First World War mining tunnels in La Boisselle, France
Authors Iris Audenrieth, Roland Martin, Pritam Yogeshwar and Dierk WilligABSTRACTTo derive reliable electrical resistivity subsurface models using error‐weighted inversion schemes, a meaningful and correct error model is required. An over‐estimated error leads to a lack of resolution and reduced target detectability. Furthermore, biased data are easily overlooked and can lead to artefacts and significant miss‐interpretation. We carried out an electrical resistivity tomography survey to detect mining tunnels of World War I in La Boisselle, France. French, British and German troops extensively used mining warfare, such as tunnel constructions, to undermine opponents. While the location and orientation of some British tunnels are known from archaeological excavations, the exact location of the German tunnels is currently unknown. Due to systematic measurement errors resulting from a malfunction in the system, the acquired electrical resistivity tomography data in La Boisselle were significantly biased. Therefore, a detailed systematic error analysis scheme was developed. Using a workflow of systematic error examination to identify biased data such as outliers or other bias, an unbiased dataset was retrieved. Subsequently, two‐dimensional electrical resistivity tomography inversions using different error models provided a qualitative estimate of how the data errors influence the tunnel detectability within an inversion scheme. The field data from La Boisselle demonstrates the importance of correctly estimating measurement errors, especially in view of the detection of small‐scale targets, such as tunnels.
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Computation of geophysical magnetic data for a buried 3‐D hexahedral prism using the Gauss–Legendre quadrature method
Authors Hassan Mohamed, Hideki Mizunaga and Hakim SaibiABSTRACTA new method is presented for the 3‐D forward modelling of the magnetic effects (induced magnetization) of a hexahedral (trilinear) prism using the Gauss–Legendre quadrature method. The 3‐D forward modelling provides an improved application to geological problems. The magnetic effect has been evaluated via the summation of the effects of the point dipole that fills the volume. The 3‐D volume is divided into smaller prisms using an appropriate number of nodes. The algorithm is tested on two synthetic examples, and the results are compared against calculated data from a common program developed at the University of British Columbia–Geophysical Inversion Facility, with both tests showing positive results. The results of testing the algorithm against two synthetic slab models are also given. Finally, the program is applied to a field data set from Aynak‐Logar Valley region in Afghanistan. Using this program, complex 3‐D model bodies may be constructed from hexahedral prisms to facilitate the calculation of their magnetic anomalies and magnetic susceptibility. Interpretation of the results shows that 3‐D constructed models are successful in recovering the shape and location of the true model.
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Volumes & issues
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Volume 22 (2024)
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Volume 21 (2023)
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Volume 20 (2022)
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Volume 19 (2021)
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Volume 18 (2020)
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Volume 17 (2019)
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Volume 16 (2018)
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Volume 15 (2017)
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Volume 14 (2015 - 2016)
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Volume 13 (2015)
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Volume 12 (2013 - 2014)
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Volume 11 (2013)
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Volume 10 (2012)
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Volume 9 (2011)
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Volume 8 (2010)
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Volume 7 (2009)
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Volume 6 (2008)
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Volume 5 (2007)
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Volume 4 (2006)
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Volume 3 (2005)
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Volume 2 (2004)
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Volume 1 (2003)