1,721,011 research outputs found
3D wavefront attribute determination and conflicting dip processing
No full textThe knowledge of 3D wavefront attributes allows many important applications, such as stacking, 5D interpolation, 3D diffraction separation and imaging, and 3D wavefront tomography, just to name a few. For the determination of wavefront attributes, we use the common-reflection-surface (CRS) operator. We adopt a simultaneous search for the determination of wavefront attributes and combine it with conflicting dip processing. For the simultaneous search, we compare three heuristic global optimization algorithms such as particle swarm optimization (PSO), genetic algorithm (GA), and differential evolution (DE). For conflicting dip processing, a dip angle decomposition method for the probed sample is introduced and the simultaneous search is independently performed in specified dip ranges to individually obtain attributes and semblance for each range. Results for the laterally heterogeneous 3D SEG C3WA data indicate that DE has superior performance to determine the 3D wavefront attributes when compared with PSO, GA, and the conventional pragmatic approach because a higher semblance and an improved set of wavefront attributes are achieved. A comparison of the data-driven wavefront attributes obtained from the DE with the model-driven wavefront attributes computed by kinematic and dynamic ray tracing reveals the validity of the data-driven wavefront attributes. Combining the simultaneous search with conflicting dip processing for the 3D CRS stack further improved reflected energy and diffraction details when compared with results without simultaneous search and/or conflicting dip processing
Reliability of data-driven wavefront attributes in laterally heterogeneous media
No full text3D wavefront attributes play a major role in many processing steps, such as prestack data enhancement, diffraction separation, and wavefront tomography. For the determination of the 3D wavefront attributes, various stacking operators can be used by adopting semblance optimization. These operators are derived for laterally homogeneous media. In praxis, however, they are applied in real geologic environments with even strong lateral velocity variations such as salt structures. This leads to the question of the quality of the 3D wavefront attributes using these operators when determined in the presence of strong lateral velocity changes. We compared the 3D wavefront attributes determined by 3D common-reflection-surface (CRS) operator (called data-driven wavefront attributes) with the 3D wavefront attributes computed by 3D kinematic and dynamic ray tracing (called model-driven wavefront attributes). For the determination of the 3D CRS wavefront attributes, we have developed a global optimization scheme based on differential evolution. Reflection seismic data of the laterally heterogeneous 3D SEG C3WA salt model are considered, and the model-driven wavefront attributes are computed for a smoothed version of the 3D SEG salt model. The comparison reveals that the wavefront attributes for the normal-incidence-point ray indicate a very good match not only in areas of mild lateral velocity variation but even in regions with strong lateral velocity variations. Approximately 80%–90% of the total picks indicate the good match with a relative error of less than 10% when a semblance threshold of 0.1 is considered in the automatic picking process. This confirms the validity of the determined wavefront attributes even in the presence of strong lateral velocity changes. Using a higher semblance threshold in the automatic picking leads to fewer picks but with an even better match between model- and data-driven wavefront attributes
5-D interpolation with wave-front attributes
No full textMost 5-D interpolation and regularization techniques reconstruct the missing data in the frequency domain by using mathematical transforms. An alternative type of interpolation methods uses wave-front attributes, that is, quantities with a specific physical meaning like the angle of emergence and wave-front curvatures. In these attributes structural information of subsurface features like dip and strike of a reflector are included. These wave-front attributes work on 5-D data space (e.g. common-midpoint coordinates in x and y, offset, azimuth and time), leading to a 5-D interpolation technique. Since the process is based on stacking next to the interpolation a pre-stack data enhancement is achieved, improving the signal-to-noise ratio (S/N) of interpolated and recorded traces. The wave-front attributes are determined in a data-driven fashion, for example, with the Common Reflection Surface (CRS method). As one of the wave-front-attribute-based interpolation techniques, the 3-D partial CRS method was proposed to enhance the quality of 3-D pre-stack data with low S/N. In the past work on 3-D partial stacks, two potential problems were still unsolved. For high-quality wave-front attributes, we suggest a global optimization strategy instead of the so far used pragmatic search approach. In previous works, the interpolation of 3-D data was performed along a specific azimuth which is acceptable for narrow azimuth acquisition but does not exploit the potential of wide-, rich- or full-azimuth acquisitions. The conventional 3-D partial CRS method is improved in this work and we call it as a wave-front-attribute-based 5-D interpolation (5-D WABI) as the two problems mentioned above are addressed. Data examples demonstrate the improved performance by the 5-D WABI method when compared with the conventional 3-D partial CRS approach. A comparison of the rank-reduction-based 5-D seismic interpolation technique with the proposed 5-DWABI method is given. The comparison reveals that there are significant advantages for steep dipping events using the 5-D WABI method when compared to the rank-reduction-based 5-D interpolation technique. Diffraction tails substantially benefit from this improved performance of the partial CRS stacking approach while the CPU time is comparable to the CPU time consumed by the rank-reduction-based method
On‐the‐fly full Hessian Kernel calculations based upon seismic‐wave simulations
No full textFull waveform inversion or adjoint tomography has routinely been performed to image the internal structure of the Earth at high resolution. This is typically done using the Fréchet kernels and the approximate Hessian or the approximate inverse Hessian because of the high‐computational cost of computing and storing the full Hessian. Alternatively, the full Hessian kernels can be used to improve inversion resolutions and convergence rates, as well as possibly to mitigate interparameter trade‐offs. The storage requirements of the full Hessian kernel calculations can be reduced by compression methods, but often at a price of accuracy depending on the compression factor. Here, we present open‐source codes to compute both Fréchet and full Hessian kernels on the fly in the computer random access memory (RAM) through simultaneously solving four wave equations, which we call Quad Spectral‐Element Method (QuadSEM). By recomputing two forward fields at the same time that two adjoint fields are calculated during the adjoint simulation, QuadSEM constructs the full Hessian kernels using the exact forward and adjoint fields. In addition, we also implement an alternative approach based on the classical wavefield storage method (WSM), which stores forward wavefields every kth (k≥1) timestep during the forward simulation and reads required fields back into memory during the adjoint simulation for kernel construction. Both Fréchet and full Hessian kernels can be computed simultaneously through the QuadSEM or the WSM code, only doubling the computational cost compared with the computation of Fréchet kernels alone. Compared with WSM, QuadSEM can reduce the disk space and input/output cost by three orders of magnitude in the presented examples that use 15,000 timesteps. Numerical examples are presented to demonstrate the functionality of the methods, and the computer codes are provided with this contribution
Waveform-based microseismic location using stochastic optimization algorithms: a parameter tuning workflow
No full textA fast and accurate source location estimation is the foundation for passive seismic processing and interpretation. Waveform-based location methods become more and more popular for analysis of both natural and induced seismicity. We utilize stochastic optimization algorithms to speed up microseismic location. Two waveform-based location methods (i.e. diffraction stacking and cross correlation stacking) are adopted to test the performance of three algorithms (i.e. particle swarm optimization, differential evolution, and neighbourhood algorithm). In order to enhance the algorithmic performance, we propose a parameter tuning workflow which consists of two types of repeated tests. One type is multiple independent tests for a single event and the other involves tests of multiple events. The success rate, speedup, location uncertainty and bias are investigated to assess the algorithmic performances. We apply the workflow to a field dataset of mining induced seismicity and obtain preferential algorithm(s) with optimized ranges of control parameters. Synthetic tests are also conducted to demonstrated the feasibility of the proposed parameter tuning workflow. Given the two imaging operators, differential evolution is demonstrated to be the preferential one accounting for both algorithmic robustness and efficiency. Meanwhile, the workflow also examines the characteristics of different imaging operators. Cross correlation stacking proves to be simpler and more robust than its counterpart. Though the workflow is developed for microseismic location, it can also be adapted for other seismic inversion problems (e.g., source mechanism inversion) and ensure the algorithmic robustness and efficiency
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Overcoming challenges in time reversal for passive seismic source localization
No full textPassive seismic source localization plays a crucial role in understanding geodynamics, monitoring geological activities, forecasting geological hazards, and managing geological fracturing processes. This doctoral thesis presents three consecutive approaches to enhance the robustness and accuracy of time-reversal source localization. The proposed methods address challenges such as source imaging artifacts, low-resolution source images, sparse and small-aperture seismic data acquisitions, and unknown seismic velocity models.
In the first approach, the focus is on refining time-reversal imaging. Conventional time-reversal source imaging methods like autocorrelation imaging or grouped crosscorrelation imaging often suffer from source imaging artifacts due to the use of low-quality seismic data or less constrained velocity models. These artifacts typically degrade the quality of the image and can lead to subsequent misinterpretation, resulting in false source location estimation. To overcome this, the Gaussian-weighted crosscorrelation imaging condition is proposed. Each time step in this method includes dividing the back-propagated wavefield, weighting seismic amplitudes using Gaussian functions, and using a zero-lag crosscorrelation. This process effectively minimizes source imaging artifacts, resulting in high-resolution, low-noise source images. Numerical examples of complex models and field examples illustrate the method’s performance, demonstrating its effectiveness in identifying sources, even within clusters and under conditions of noisy and sparse-sampled data.
The second approach addresses another challenge posed by sparse and small-aperture seismic data acquisition in time-reversal imaging techniques. Such acquisitions often lead to false wave focusing due to insufficient wave illumination. To address the issues, the maximum-amplitude path method is introduced for source localization using maximum-amplitude paths. The paths are constructed from back-projected wavefields using receiver patches selected from the acquisition. They include the maximum amplitudes of the back-projected wavefronts for each considered time step. The proposed method exploits the continuity of the maximum amplitudes of the back-projected wavefields. The point of closest proximity (or crossing point) of the paths is the source location and the corresponding time is the source time. The maximum-amplitude path method successfully overcomes the acquisition problems and provides accurate source location and source excitation time even in challenging scenarios.
In the final approach, a data-driven hybrid workflow is presented to address the challenge of the lack of velocity model in time-reversal localization methods including the proposed first and second time reversal localization approaches. The proposed workflow can simultaneously invert the source location, excitation times, and velocity model using wavefront attributes of passive seismic data. By combining wavefront tomography and time-reversal methods, the workflow eliminates the need for detailed prior information, making it particularly applicable in practical scenarios. The proposed workflow comprises the following steps. First, a set of user-defined vertical gradient velocity models is designed. Time reversal is then used to estimate the source excitation times for each model. After that, these source times and gradient models are used in wavefront tomography. The second step uses an optimization procedure to refine the velocity model and the source excitation time. Each iteration of the optimization involves a sequential application of time reversal and wavefront tomography. In the final step, the source location is refined using the optimal velocity model and the Gaussian-weighted crosscorrelation imaging condition. The proposed workflow overcomes the limitations of time reversal in the absence of a velocity model, providing good velocity models and fairly accurate source locations and excitation times
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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