Velocity model estimation by means of Full Waveform Inversion of transmitted waves: An example from a seismic profile in the geothermal areas of Southern Tuscany, Italy

Tognarelli, Andrea; Stucchi, E.; Mazzotti, Alfredo

doi:10.1016/j.geothermics.2020.101894

Cited by 6 publications

(5 citation statements)

References 41 publications

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“…Long-offset acquisition is beneficial not only for the low wavenumbers of the model but also for the deep portion of the model. Transmitted-wave full-waveform inversion can be used to estimate the velocity model of geothermal areas [6]. The estimated velocity model has a low resolution because only the transmitted waves are included in the inversion.…”

Section: Discussionmentioning

confidence: 99%

“…Synthetic results show that the supercritical water zone can be well-imaged by combining the FWI method, active seismic sources and appropriate natural earthquakes, as well as a distributed acoustic sensor (DAS) seismic array in the borehole and surface seismic array [5]. Tognarelli et al (2020) [6] presented a case study of velocity model estimation in geothermal areas with full-waveform inversion of transmitted waves (direct waves, refracted waves and diving waves). The combination of global and local optimization methods allowed for the estimation of velocity to be independent of the a priori interpretation of the subsurface.…”

Section: Introductionmentioning

confidence: 99%

“…The combination of global and local optimization methods allowed for the estimation of velocity to be independent of the a priori interpretation of the subsurface. The input data do not contain reflected waves, so the inverted velocity model does not contain too many high wavenumber portions and it can be used as complementary information to the standard seismic reflection image [6]. For full-waveform inversion in geothermal reservoir exploration, the input data, including reflections that contain high frequencies, can lead to a high-resolution model and even directly delineate the geothermal reservoir on the recovered model.…”

Section: Introductionmentioning

confidence: 99%

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Multiscale Full-Waveform Inversion with Land Seismic Field Data: A Case Study from the Jizhong Depression, Middle Eastern China

et al. 2022

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The Jizhong depression contains several geothermal reservoirs that are characterized by localized low-velocity anomalies. In this article, full-waveform inversion (FWI) is used to characterize these anomalies and determine their extent. This is a challenging problem because the reservoirs are quite small and the available data have usable frequencies only down to 5 Hz. An accurate-enough starting model is carefully built by using an iterative travel time tomography method combined with a cycle-skipping assessment method to begin the inversion at 5 Hz. A multiscale Laplace–Fourier-domain FWI with a layer-stripping approach is implemented on the starting model by gradually increasing the maximum offset. The result of overlapping the recovered velocity model on the migrated seismic profile shows a good correlation between the two results. The recovered model is assessed by ray tracing, synthetic seismogram modeling, checkerboard testing and comparisons with nearby borehole data. These tests indicate that low-velocity anomalies down to a size of 0.3 km × 0.3 km at a maximum depth of 2 km can be recovered. Combined with the well log data, the resulting velocity model allows us to delineate two potential geothermal resources, one of which was previously unknown.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multiscale Full-Waveform Inversion with Land Seismic Field Data: A Case Study from the Jizhong Depression, Middle Eastern China

et al. 2022

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“…The inversion is driven by the GA, a global optimization technique that mimics biological evolution (Holland, 1975;Goldberg, 1989), which has been shown to be effective in reducing the risk to be trapped in local minima of the error function (Sen & Stoffa, 2013;Aleardi et al, 2019;Pierini et al, 2019;Tognarelli et al, 2020). In GA, each individual of the FIGURE 6 The full-waveform inversion (FWI) workflow population corresponds to a model and by means of selection, recombination and mutation procedures the whole population evolves generation after generation towards models producing a better fit with the observed data.…”

Section: Global Inversionmentioning

confidence: 99%

Application of a global–local full‐waveform inversion of Rayleigh wave to estimate the near‐surface shear wave velocity model

Lamuraglia

Stucchi

Aleardi

2022

Near Surface Geophysics

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We present a global–local full‐waveform inversion (FWI) of surface waves to estimate a high‐resolution shear wave velocity model of the near‐surface at the site of Grenoble (France). The seismic data we use have been acquired in the framework of the InterPACIFIC project. A first attempt is made by employing the multichannel analysis of surface waves (MASW) to invert the fundamental modes of Rayleigh waves. This inversion is solved through a global optimization driven by the neighbourhood algorithm. However, the limiting 1D assumption, together with the severely ill‐posedness of the MASW inversion motivate us to exploit all the information content of the recorded Rayleigh waves (i.e., travel‐times and amplitudes) by implementing a global–local FWI approach. We first perform a global FWI in which a genetic algorithm (GA) is used to minimize the L2 norm difference between observed and simulated seismic waveforms up to 30 Hz. This inversion employs a two‐grid scheme in which the subsurface is described by a fine grid input to the forward modelling, whereas the unknowns are defined on a coarse grid. A bilinear interpolation brings the coarse‐grid model into the fine grid. To accelerate the convergence, two strategies are considered; offset marching and frequency marching. Then, the long‐wavelength velocity profile provided by the GA inversion is used as the starting point for a local FWI for further refinement of the predicted model. In this case, we employ a frequency‐marching strategy up to a maximum frequency of 60 Hz. Both the global and local approaches use a finite difference code for the forward computation. Despite the limited a priori information infused into the inversion framework, the presented global–local FWI scheme provides reliable results as demonstrated by the good match between recorded and predicted seismograms and by the agreement of the estimated velocity with both nearby borehole data and stratigraphic information on the study site. Our global–local strategy also achieves better data fitting and improved matching with the available borehole data with respect to the velocity profile estimated when the local FWI is started from the MASW predictions.

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“…The full waveform inversion (FWI) approach is an efficient tool for migration imaging, and can be used to obtain a high resolution of underground structure by continuing to fit the calculated values and field data. At present, FWI has been applied to the inversion of ground radar wave [19] [20], transmitted waves [21] SH waves, Love waves [22], and so on. However, an FWI method for deep electromagnetic migration imaging has yet to appear.…”

mentioning

confidence: 99%

Full Waveform Inversion of Transient Electromagnetic Data in the Time Domain

Xue

Cheng

Gelius

et al. 2022

IEEE Trans. Geosci. Remote Sensing

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Quasi-seismic imaging is a popular form of electromagnetic imaging technology. In most cases, it is considered that it will yield more obvious layered characteristics if the electromagnetic response is transformed into the virtual wave domain. However, the time profile of virtual wave cannot effectively show the underground electromagnetic structure before migration. In this paper, we make an improvement to process the virtual wave, by applying the full waveform inversion method, with the steps detailed as follows: (1) we use the truncated singular value decomposition method to transform the transient electromagnetic response to the virtual wave field. (2) Using the FDTD method, we calculate the virtual wave field according to the resistivity model, then use the shearlet transform to remove the direct wave. (3) We use a least square equation between the virtual wave and transformed virtual wave to express the problem of full waveform inversion. Next, we apply one of steepest descent methods-the Marquardt approach-to obtain the optimal underground conductivity information. Finally, we use the synthetic and field data to show the accuracy and rationality of the method proposed in this paper. Index Terms-quasi-seismic, virtual wave field, full waveform inversion, transient electromagnetic field I. INTRODUCTIONHE transient electromagnetic method (TEM) has been widely applied in resource, environment and engineering detection [1][2][3]. It involves setting the loop or finite long wire source in the ground to excite an initial electromagnetic field. Then, during the interval of primary pulse, the coil or ground electrode is used to collect field data and reveal the underground resistance structure distribution [4].

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Velocity model estimation by means of Full Waveform Inversion of transmitted waves: An example from a seismic profile in the geothermal areas of Southern Tuscany, Italy

Cited by 6 publications

References 41 publications

Multiscale Full-Waveform Inversion with Land Seismic Field Data: A Case Study from the Jizhong Depression, Middle Eastern China

Multiscale Full-Waveform Inversion with Land Seismic Field Data: A Case Study from the Jizhong Depression, Middle Eastern China

Application of a global–local full‐waveform inversion of Rayleigh wave to estimate the near‐surface shear wave velocity model

Full Waveform Inversion of Transient Electromagnetic Data in the Time Domain

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