Sensitivity maps for time-reverse imaging: an accuracy study for the Los Humeros Geothermal Field (Mexico)

Finger, Claudia; Saenger, Erik H.

doi:10.1093/gji/ggaa160

Cited by 4 publications

(7 citation statements)

References 24 publications

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“…A workflow is developed in this study for locating and characterizing seismic events in the presence of these challenges. This workflow is presented in Figure 4 and incorporates the localization of events as proposed by Finger and Saenger (2020) and the characterization of earthquakes using stress recordings at the determined source locations. A crucial step is the distinction between artificial convergence locations and source locations.…”

Section: Characterizing Sources In a Synthetic Realistic Scenariomentioning

confidence: 99%

“…In the illumination compensated volume, the remaining background noise is eliminated by muting amplitudes below a threshold calculated from the mean amplitudes in each coordinate direction as described in detail in Finger and Saenger (2020). The post-processed image volumes for I e can be seen in Figure 8a using the same velocity model in the forward and time-reversed simulation, adding no noise to the displacement traces and using the 27 stations.…”

Section: Post-processing Of Tri Image Volumesmentioning

confidence: 99%

“…The clusters of high amplitudes are identified using an iterative search for the maximum amplitude and subsequently muting the area around it. A detailed description of this approach can be found in Finger and Saenger (2020). The result is a list of convergence points for each tested imaging conditions.…”

Section: Post-processing Of Tri Image Volumesmentioning

confidence: 99%

“…In this study, the time-dependent moment tensor is derived using TRI based on numerical simulations. After determining the source location with TRI following Finger and Saenger (2020), the components of the stress tensor are recorded at the determined source location. It is shown that the time-dependent stress tensor at a single grid point represents the time-dependent moment tensor of the source initially implemented at this grid point.…”

Section: Introductionmentioning

confidence: 99%

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Determination of the time-dependent moment tensor using time reverse imaging

Finger

Saenger²

2021

GEOPHYSICS

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An approach is presented to determine the time-dependent moment tensor and the origin time in addition to commonly derived locations of seismic events using time-reverse imaging (TRI). It is crucial to locate and characterize the occurring micro-seismicity without making a priori assumptions about the sources to fully understand the subsurface processes inducing seismicity. Low signal-to-noise ratios often force standard methods to make assumptions about sources or only characterize selected larger-magnitude events. In TRI, micro-earthquakes are located by back propagating the full recorded time-reversed wavefield through a velocity model until it ideally convergences on the source location. Therefore, it is less affected by low signal-to-noise ratios and potentially locates and characterizes most of the events. After distinguishing artificial convergence locations from source locations, the quality of the source location and the moment tensors are derived by recording the stress at the determined source locations during the back propagation of the time-reversed wavefield. A robust workflow is derived using synthetic test cases in a realistic scenario with velocity models that only approximate the true velocity model and/or noisy displacement traces. The influence of a rudimentary velocity model on the source-location accuracy and characterisation is significant. The proposed workflow handles these less-than optimal station distributions and velocity models. Finally, the derived workflow is successfully applied to field data recorded at the geothermal field of Los Humeros, Mexico. Although only a one-dimensional velocity model is currently available, source locations and (time-dependent) moment tensors could be determined for selected events.

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Section: Characterizing Sources In a Synthetic Realistic Scenariomentioning

confidence: 99%

Section: Post-processing Of Tri Image Volumesmentioning

confidence: 99%

Section: Post-processing Of Tri Image Volumesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Determination of the time-dependent moment tensor using time reverse imaging

Finger

Saenger²

2021

GEOPHYSICS

Self Cite

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“…Rather, it is a process that begins before the actual segmentation and ends with assigning physical mineral properties to the corresponding segmented phases, which properties may have to be adjusted due to the prevailing microstructure. The incorporation of geologically based information for geophysical interpretations is already well established in areas of image processing, such as seismic reflection image interpretation, large-scale velocity modeling, or time reverse imaging interpretations (e.g., Ritzmann et al, 2007;Finger and Saenger, 2020). In DRP, a comparable geological interpretation of gray-scale images is not well established, yet.…”

Section: Introductionmentioning

confidence: 99%

Digital Rock Physics: A Geological Driven Workflow for the Segmentation of Anisotropic Ruhr Sandstone

et al. 2021

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Over the last 3 decades, Digital Rock Physics (DRP) has become a complementary part of the characterization of reservoir rocks due to the non-destructive testing character of this technique. The use of high-resolution X-ray Computed Tomography (XRCT) has become widely accepted to create a digital twin of the material under investigation. Compared to other imaging techniques, XRCT technology allows a location-dependent resolution of the individual material particles in volume. However, there are still challenges in assigning physical properties to a particular voxel within the digital twin, due to standard histogram analysis or sub-resolution features in the rock. For this reason, high-resolution image-based data from XRCT, transmitted-light microscope, Scanning Electron Microscope (SEM) as well as geological input properties like geological diagenesis, mineralogical composition, sample’s microfabrics, and estimated sample’s porosity are combined to obtain an optimal spatial segmented image of the studied Ruhr sandstone. Based on a homogeneity test, which corresponds to the evaluation of the gray-scale image histogram, the preferred scan sample sizes in terms of permeability, thermal, and effective elastic rock properties are determined. In addition, these numerically derived property predictions are compared with laboratory measurements to obtain possible upper limits for sample size, segmentation accuracy, and a geometrically calibrated digital twin of the Ruhr sandstone. The comparison corresponding gray-scale image histograms as a function of sample sizes with the corresponding advanced numerical simulations provides a unique workflow for reservoir characterization of the Ruhr sandstone.

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P- and S-wave energy current density vectors dot product imaging condition of source time-reversal imaging

Zhang

et al. 2023

Geophysical Journal International

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Summary Source time-reversal imaging (TRI) based on decoupled elastic wave equation can utilize vector P- and S-wave time differences and achieve high-precision source location in complex geological models. The imaging condition is critical for TRI. However, because of the orthogonally polarized properties of P- and S-wave, traditional vector dot product imaging condition directly applied to TRI will decrease the effective imaging values. In contrast, the energy current density vectors of P- and S-wave represent the propagation directions of the wavefields and are almost parallel. Their dot product can result in the maximum imaging energy. Based on this principle, we propose a P- and S-wave energy current density vectors dot product imaging condition (PSEDPIC), which uses the propagation direction information of P- and S-wave at the source point to suppress imaging artefacts generated by waves with inconsistent propagation directions. Numerical tests reveal that PSEDPIC can (1) reduce the image artefacts, (2) improve the imaging spatial resolution and (3) allow a shallower imaging region. In addition, if the numerical simulation algorithm used in TRI can reconstruct the seismic wavefield accurately in the presence of surface topography, the impact of an observation system with elevation differences on imaging can be eliminated automatically. For this reason, we use the curvilinear grid finite difference method to directly reconstruct the wavefield in TRI to solve the problem of data elevation correction. The test results of 3D synthetic and field data for microseismic monitoring demonstrate the effectiveness of the proposed method.

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Sensitivity maps for time-reverse imaging: an accuracy study for the Los Humeros Geothermal Field (Mexico)

Cited by 4 publications

References 24 publications

Determination of the time-dependent moment tensor using time reverse imaging

Determination of the time-dependent moment tensor using time reverse imaging

Digital Rock Physics: A Geological Driven Workflow for the Segmentation of Anisotropic Ruhr Sandstone

P- and S-wave energy current density vectors dot product imaging condition of source time-reversal imaging

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