Introduction to the supplement on seismic modeling with applications to acquisition, processing, and interpretation

Robertsson, Johan O. A.; Bednar, Bee; Blanch, Joakim O.; Kostov, C.; Manen, Dirk‐Jan van

doi:10.1190/1.2755959

Cited by 24 publications

(9 citation statements)

References 5 publications

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“…Accurate simulation of seismic wave propagation in complex geologicl structures is of particular interest nowadays due to its applicability in various forward and inverse problems (e.g., Ursin, 2004;Robertsson et al, 2007;Virieux and Operto, 2009;Virieux et al, 2011). It is widely used for environmental and industrial applications for subsurface structure evaluation and in various aspects of seismic exploration, such as seismic data acquisition, data processing, interpretation, and as a core tool of seismic imaging and inversion methods.…”

Section: Introductionmentioning

confidence: 99%

Numerical modeling of 3D zero-offset laboratory data by a discretized Kirchhoff integral method

et al. 2014

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International audienceAccurate simulation of seismic wave propagation in complex geologic structures is of particular interest nowadays. However, difficulties arise for complex geologic structures with great and rapid structural changes, due, for instance, to the presence of shadow zones, head waves, diffractions and/or edge effects. Different methods have thus been developed and are typically tested on synthetic configurations against analytical solutions for simple canonical problems, reference methods, or via direct comparison with real data acquired in situ. Such approaches have limitations, especially if the propagation occurs in a complex environment with strong-contrast reflectors and surface irregularities because it can be difficult to determine the method that gives the best approximation of the "real" solution or to interpret the results obtained without an a priori knowledge of the geologic environment. An alternative approach for seismics consists in comparing the synthetic data with data obtained in laboratory experiments. In contrast to in situ experiments, high-quality data are collected under controlled conditions for a known configuration. In contrast with numerical experiments, laboratory data possess many of the characteristics of field data because real waves propagate through models with no numerical approximations. Our main purpose was to test the approach of using laboratory data as reference data for benchmarking 3D numerical methods and techniques using the setup that we have designed for this study. We performed laboratory-scaled measurements of zero-offset reflection of broadband pulses from a strong topographic environment immersed in a water tank. We compared these measurements with numerical data simulated by means of a discretized Kirchhoff integral method. The comparisons of synthetic and laboratory data indicated a good quantitative fit in terms of time arrivals and acceptable fit in amplitudes. Thus, the first step of the approach was successfully applied

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Section: Introductionmentioning

confidence: 99%

Numerical modeling of 3D zero-offset laboratory data by a discretized Kirchhoff integral method

et al. 2014

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“…Most studies applying wave-field modelling concentrate on deep reservoirs and crustal structures (Robertsson et al, 2007). A comprehensive approach is reported by Bellefleur et al (2012), which we use accordingly in this study.…”

Section: Introductionmentioning

confidence: 99%

Finite-difference modelling to evaluate seismic P-wave and shear-wave field data

2015

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Abstract. High-resolution reflection seismic methods are an established non-destructive tool for engineering tasks. In the near surface, shear-wave reflection seismic measurements usually offer a higher spatial resolution in the same effective signal frequency spectrum than P-wave data, but data quality varies more strongly.To discuss the causes of these differences, we investigated a P-wave and a SH-wave seismic reflection profile measured at the same location on the island of Föhr, Germany and applied seismic reflection processing to the field data as well as finite-difference modelling of the seismic wave field. The simulations calculated were adapted to the acquisition field geometry, comprising 2 m receiver distance (1 m for SH wave) and 4 m shot distance along the 1.5 km long P-wave and 800 m long SH-wave profiles. A Ricker wavelet and the use of absorbing frames were first-order model parameters. The petrophysical parameters to populate the structural models down to 400 m depth were taken from borehole data, VSP (vertical seismic profile) measurements and cross-plot relations.The simulation of the P-wave wave-field was based on interpretation of the P-wave depth section that included a priori information from boreholes and airborne electromagnetics. Velocities for 14 layers in the model were derived from the analysis of five nearby VSPs (v P = 1600-2300 m s −1 ). Synthetic shot data were compared with the field data and seismic sections were created. Major features like direct wave and reflections are imaged. We reproduce the mayor reflectors in the depth section of the field data, e.g. a prominent till layer and several deep reflectors. The SH-wave model was adapted accordingly but only led to minor correlation with the field data and produced a higher signal-to-noise ratio. Therefore, we suggest to consider for future simulations additional features like intrinsic damping, thin layering, or a near-surface weathering layer. These may lead to a better understanding of key parameters determining the data quality of near-surface shear-wave seismic measurements.

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“…Gjøystdal et al, 2007;Laurain et al, 2004;Robertsson et al, 2007). In complex geological settings seismic forward modeling can be used to test different acquisition parameters and subsurface models to achieve the optimum data collection strategy.…”

Section: Applications In Seismic Acquisitionmentioning

confidence: 99%

Seismic Modeling of Complex Geological Structures

Alaei¹

2012

Seismic Waves - Research and Analysis

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Introduction to the supplement on seismic modeling with applications to acquisition, processing, and interpretation

Cited by 24 publications

References 5 publications

Numerical modeling of 3D zero-offset laboratory data by a discretized Kirchhoff integral method

Numerical modeling of 3D zero-offset laboratory data by a discretized Kirchhoff integral method

Finite-difference modelling to evaluate seismic P-wave and shear-wave field data

Seismic Modeling of Complex Geological Structures

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