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- Volume 19, Issue 1, 2021
Near Surface Geophysics - Volume 19, Issue 1, 2021
Volume 19, Issue 1, 2021
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A geostatistical Markov chain Monte Carlo inversion algorithm for electrical resistivity tomography
Authors Mattia Aleardi, Alessandro Vinciguerra and Azadeh HojatABSTRACTElectrical resistivity tomography is an ill‐posed and nonlinear inverse problem commonly solved through deterministic gradient‐based methods. These methods guarantee a fast convergence towards the final solution, but the local linearization of the inverse operator impedes accurate uncertainty assessments. On the contrary, numerical Markov chain Monte Carlo algorithms allow for accurate uncertainty appraisals, but appropriate Markov chain Monte Carlo recipes are needed to reduce the computational effort and make these approaches suitable to be applied to field data. A key aspect of any probabilistic inversion is the definition of an appropriate prior distribution of the model parameters that can also incorporate spatial constraints to mitigate the ill conditioning of the inverse problem. Usually, Gaussian priors oversimplify the actual distribution of the model parameters that often exhibit multimodality due to the presence of multiple litho‐fluid facies. In this work, we develop a novel probabilistic Markov chain Monte Carlo approach for inversion of electrical resistivity tomography data. This approach jointly estimates resistivity values, litho‐fluid facies, along with the associated uncertainties from the measured apparent resistivity pseudosection. In our approach, the unknown parameters include the facies model as well as the continuous resistivity values. At each spatial location, the distribution of the resistivity value is assumed to be multimodal and non‐parametric with as many modes as the number of facies. An advanced Markov chain Monte Carlo algorithm (the differential evolution Markov chain) is used to efficiently sample the posterior density in a high‐dimensional parameter space. A Gaussian variogram model and a first‐order Markov chain respectively account for the lateral continuity of the continuous and discrete model properties, thereby reducing the null‐space of solutions. The direct sequential simulation geostatistical method allows the generation of sampled models that honour both the assumed marginal prior and spatial constraints. During the Markov chain Monte Carlo walk, we iteratively sample the facies, by moving from one mode to another, and the resistivity values, by sampling within the same mode. The proposed method is first validated by inverting the data calculated from synthetic models. Then, it is applied to field data and benchmarked against a standard local inversion algorithm. Our experiments prove that the proposed Markov chain Monte Carlo inversion retrieves reliable estimations and accurate uncertainty quantifications with a reasonable computational effort.
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Determination of the resistivity distribution along underground pipes in urban contexts using galvanic and capacitive methods
Authors Simon Rejkjær, Cécile Finco, Cyril Schamper, Fayçal Rejiba, Alain Tabbagh, Jesper König and Torleif DahlinABSTRACTRenovation of water and central heating pipelines is a very costly and time‐consuming process; therefore, a way to prioritize the limited resources between different parts of the systems is very important. The risk for corrosion damage can be assessed from the resistivity of the ground, because the processes facilitating the metal oxidation also affect the resistivity. However, galvanic resistivity mapping is time consuming and work‐intensive in paved areas. To determine the resistivity in the vicinity of pipes two different resistivity methods were applied: electrical resistivity tomography using galvanic coupling, and the logistically easier and rapid electrostatic measurements using capacitive coupling. The two methods were tested in a series of experiments undertaken in the province of Scania in southern Sweden with the aim to acquire a better knowledge about the electrical resistivity of the soil surrounding the heating and water distribution pipes, in order to better assess the corrosivity of the environment. From the experiments it is shown that the electrical resistivity tomography and electrostatic methods mostly give comparable results for the shallow investigated depths in focus here, where differences might be caused by different sensitivities and noise characteristics. In the case of both methods, it is shown, with the help of modelling of the different expected ground models including the pipes, that the pipes only influence the data in cases of pipes of very large diameters or those buried at a very shallow depth, even without any protective surface coating. The missing influence of the pipes on the data makes the methods very applicable for knowing the resistivity of the soil surrounding the pipes and thus evaluation of corrosion risk.
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Cross‐borehole geoelectrical time‐lapse monitoring of in situ chemical oxidation and permeability estimation through induced polarization
ABSTRACTWorldwide, soil contamination due to industrial activities is a major issue. One method for remediation of contaminated sites is in situ chemical oxidation, where an oxidizing agent is injected into the contaminated soil. Normally, monitoring wells are established in the remediation area for tracking the oxidizing agent. However, wells only provide point information of the injectant spread. This issue can be addressed using cross‐borehole resistivity and induced polarization tomography, by mapping the electrical properties in the entire remediation volume and by deriving, through petrophysical relations, the hydraulic properties of the medium. Here we present a proof‐of‐concept study, performed over one year as part of a larger remediation project, where resistivity and time‐domain induced polarization data were acquired among 10 boreholes, before and after two rounds of injection of oxidizing agents. The time‐lapse resistivity models, obtained through a focusing inversion scheme that favours compact time‐lapse changes, clearly show the oxidizing agent spread as highly conductive anomalies and confirmed by water conductivity measurements in boreholes. The time‐lapse inversions also show spatial variability in the injectant spread, with some areas not reached. The induced polarization data quality decreased significantly just after the injection rounds, because of the decrease in resistivity and induced polarization signal level, so that induced polarization time‐lapse inversions were not feasible. However, the induced polarization data were used for background characterization and to estimate permeability. In particular, there is a good match between the imaged low‐permeability zones and the areas in which the injectant did not spread, identified by the time‐lapse resistivity inversions. Furthermore, geological samples confirm the presence of fine‐grained sediments in the estimated low‐permeability zones. While time‐lapse resistivity tomography may be used for documenting the injectant spread, induced polarization permeability estimates prior to injection can be used to better tailor the remediation in terms of dimension and location of injection filters.
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Transient electromagnetic inversion based on particle swarm optimization and differential evolution algorithm
Authors Ruiyou Li, Nian Yu, Ruiheng Li, Qiong Zhuang and Huaiqing ZhangABSTRACTFor transient electromagnetic inversion, a gradient‐based algorithm is strongly dependent on the quality of the initial model, while any non‐gradient‐based algorithm often falls too easily into local optima. This paper proposes a joint differential‐evolution–particle‐swarm‐optimization inversion algorithm, which provides a better global optimization. A dual‐population evolution strategy and information exchange mechanism is presented. For verification, this is followed by adoption of a layered inversion model in the transient electromagnetic inversion with a central loop. The results show that the differential‐evolution–particle‐swarm‐optimization joint algorithm can reduce the probability of a premature phenomenon (i.e. falling into local optima) and improve the inversion accuracy, efficiency and stability, with a fast convergence occuring in the early stages. Furthermore, the proposed algorithm has a higher degree of fitting (prediction ability) for data inversion and is feasible for transient electromagnetic inversion.
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Estimation of earthquake local site effects using microtremor observations for the Garhwal–Kumaun Himalaya, India
Authors Ramesh Pudi, Priyom Roy, Tapas R. Martha and K. Vinod KumarABSTRACTThe Garhwal–Kumaun region of the Himalaya encompassing the state of Uttarakhand, India, has experienced several earthquakes in the past. Damage due to earthquakes is controlled by local site conditions, primarily resonance frequency and wave amplification from the ground. We present local site parameters with their site geology for 37 sites using ambient noise data. Horizontal to vertical spectral ratio technique is used to estimate the spectral ratio curves. Based on the type of curve, sites are classified into four classes, viz. clear peak, broad peak, double and multi‐peak, and flat H/V curve. Sites seen with clear or broad peaks are located on either soil or weathered rocks, thus indicating large impedance contrast and sharp discontinuity with large velocity contrast. Multiple peaks are observed in either soil or boulder bed and reveal large impedance contrast, probably representing shallow and thick strata. Sites with flat curves are found on weathered/phyllite/granite gneiss/granite schist rock types within highly dissected hilly areas. Fourteen sites have a peak frequency >6 Hz with a dominance of broad and clear peaks in the Lesser and Higher Himalayan regions. On the contrary, foothills and part of Siwalik sites exhibited a peak frequency between 1.14 and 4.94 Hz. The results demonstrate that sites with thick soil cover and boulder bed areas, that is, Doon valley and foothills, show low‐frequency peaks and hard rock or shallow bedrock sites, that is, Lesser and Higher Himalaya exhibit a higher frequency range. The estimated H/V amplitude and peak frequency values have shown a good correlation with site geology and geomorphology.
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Detection of urban underground cavities using seismic scattered waves: a case study along the Xuzhou Metro Line 1 in China
Authors Jun Zhang, Shengdong Liu, Cai Yang, Xue Liu and Bo WangABSTRACTDuring metro construction, unidentified cavities pose a serious threat to the integrity of the tunnels and public safety. An efficient and accurate cavity‐detection method is needed, given the limited space and time constraints of urban construction. Equivalent offset migration is a high‐accuracy, seismic scattered‐wave imaging method that is effective in wavefield extraction, has the ability to derive the wavefield outside the range of the source–receiver points and can use imaging data for areas with poor signal‐to‐noise ratios. In this study, we consider a stratified subsurface structure and the geological conditions of a city and construct a typical urban cavity geological model to study the characteristics of cavity‐scattered waves. In numerical studies, equivalent offset migration is superior to Kirchhoff post‐stack migration in the case of seismic scattered‐wave imaging. A fast‐moving detection device for urban construction conditions is designed to meet the data‐acquisition requirements on the basis of the scattered‐wave characteristics and equivalent offset migration method. Efficient acquisition and accurate detection are confirmed, with the detected depth deviating by less than 1 m compared to the depth obtained from borehole checks along the Xuzhou Metro Line 1 in China. The results show that cavity detection using seismic scattered waves can meet urban engineering requirements. Further study on the design of a high‐performance detection device, reception and extraction of weakly scattered waves, and scattered‐wave recognition and interpretation techniques for different targets will be helpful in solving cavity‐detection problems in urban engineering.
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A numerical dispersion‐suppressed method for shallow seismic migration
Authors Yanli Liu, Zhenchun Li, Jiao Wang, Miaomiao Sun and Qiang LiuABSTRACTReverse time migration can accurately image underground earth structures. However, for shallow seismic exploration, the seismic wave velocity is often lower than the velocity in the middle‐deep layers, which causes numerical dispersion for finite‐difference schemes and leads to poor seismic imaging quality. Suppressing numerical dispersion by grid encryption or increasing the finite‐difference order seriously reduces computational efficiency, which is not the optimal solution. To improve the imaging quality without sacrificing computational efficiency, a regularization factor is added to the acoustic wave equation to correct the phase velocity of high wave‐number components. An appropriate regularization factor can eliminate numerical dispersion that results from large grid interval schemes and can reduce the size of computational grids and improve computational efficiency. For simulations in the frequency domain, reducing the grid size also means reducing computer memory requirements. Numerical experiments indicate that the regularization factor should match the degree of numerical dispersion. Larger regularization factors can suppress serious numerical dispersion. However, excessively large regularization factors may destroy the effective wave field. Different numerical models verify the effectiveness of the improved acoustic equation for suppressing numerical dispersion and maintaining amplitudes and provide a novel means to improve the shallow seismic image quality.
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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)