Analysis of 3‐D seismic acquisition geometries by focal beams

Geophysical Prospecting

Verschuur

2015

Recent advances in survey design have led to conventional common-midpoint-based analysis being replaced by subsurface-based seismic acquisition analysis, with emphasis on advanced techniques of illumination analysis. Among them is the so-called focal beam method, which is a wave-equation-based seismic illumination analysis method. The objective of the focal beam method is to provide a quantitative insight into the combined influence of acquisition geometry, overburden structure, and migration operators on the resolution and angle-dependent amplitude fidelity of the image. The method distinguishes between illumination and sensing capability of a particular acquisition geometry by computing the focal source beam and the focal detector beam, respectively. Sensing is related to the detection properties of a detector configuration, whereas illumination is related to the emission properties of a source configuration. The focal source beam analyses the incident wavefield at a specific subsurface grid point from all available sources, whereas the focal detector beam analyses the sensing wavefield reaching at the detector locations from the same subsurface grid point. In the past, this method could only address illumination by primary reflections. In this paper, we will extend the concept of the focal beam method to incorporate the illumination due to the surface and internal multiples. This in fact complies with the trend of including multiples in the imaging process. Multiple reflections can illuminate a target location from other angles compared with primary reflections, resulting in a higher resolution and an improved illumination. We demonstrate how an acquisition-related footprint can be corrected using both the surface and the internal multiples.

Section: Methods Developement: Extension Of Focal Beamsmentioning

confidence: 99%

Extending illumination using all multiples: application to 3D acquisition geometry analysis

Kumar

Geophysical Prospecting

Verschuur

2015

“…Wðr s ; r f Þ describes forward wavefield propagation from sources r s to the focal point r f . Transforming the detector and source beams to the Radon domain, and extracting a horizontal section at τ ¼ 0, Volker (2002) derived the amplitude versus ray parameter (AVP) function as Figure 1. Schematic diagram of focal beams.…”

Section: Multifrequency Focal Beammentioning

confidence: 99%

“…However, in practice Bðz m ; z m Þ quantifies the imprint of the acquisition geometry on the reflectivity information (caused by the sparse sampling of the sources and detectors as given by Sðz 0 Þ end Dðz 0 Þ, respectively). According to Volker (2002), the continuous form of the spatial resolution function (equation 3) for a single temporal frequency component ω can be derived by considering the impact of a 3D target point r f ¼ ðx f ; y f ; z m Þ and a neighbor point r ¼ ðx; y; z m Þ surrounding r f (Figure 1 …”

Section: Multifrequency Focal Beammentioning

confidence: 99%

“…The focal beam analysis method Volker et al, 2001;Volker, 2002) originates from the migration of seismic reflection data using the common focus point concept (Berkhout, 1982;1997). Seismic migration is the process of extracting the reflectivity information from the recorded seismic data.…”

Section: Multifrequency Focal Beammentioning

confidence: 99%

“…Focal beam analysis Volker et al, 2001;Volker, 2002) is a method that relates prestack migration theory (Berkhout, 1987) directly to the assessment of seismic acquisition geometries. As opposed to spatial resolution analysis (Vermeer, 1999;Gibson and Tzimeas, 2002;Tzimeas, 2004;Xie et al, 2006) based on the theory of Beylkin (1985), which combines detector and source information, focal beams analyze the detector and source parts of an acquisition geometry separately.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fast multifrequency focal beam analysis for 3D seismic acquisition geometry

Wei

2012

GEOPHYSICS

A method for the efficient computation of multifrequency focal beams for 3D seismic acquisition geometry analysis has been developed. By computing them for all the frequency components of seismic data, single-frequency focal beams can be extended to multifrequency focal beams. However, this straightforward method involves considerable computer time and memory requirements, especially in complex media settings. Therefore, we propose a rapid 3D multifrequency focal beam method in which only a few single-frequency focal beam computations are followed by a number of smart interpolations. The 3D wavefield extrapolation in the focal beam analysis is conducted by the combined applications of a 3D degenerate Fourier migrator and a 3D Born-Kirchhoff interpolation operator, a process that reduces the computational cost for complex media. The multifrequency focal beam analysis is applied to a 3D model from an oil field of China, demonstrating how spatial sampling differences affect seismic imaging.

Automated Seismic Acquisition Geometry Design for Optimized Illumination at the Target: A Linearized Approach

Verschuur

IEEE Trans. Geosci. Remote Sensing

2022

In seismic exploration methods, imperfect spatial sampling at the surface causes a lack of illumination at the target in subsurface. The hampered image quality at the target area of interest causes uncertainties in reservoir monitoring and production, which can have a substantial economic impact. Especially in the case of a complex overburden, the impact of surface sampling on target illumination can be significant. Targetoriented acquisition analysis based on wavefield propagation and a known velocity model has been used to provide guidance for optimizing the acquisition parameters. Seismic acquisition design is usually a manual optimization process, with consideration of many aspects. In this study, we develop a methodology that automatically optimizes an irregular receiver geometry when the source geometry is fixed, or vice versa. The methodology includes objective functions defined by two criteria: optimizing the image resolution; and optimizing the angle-dependent illumination information. We use a two-step parameterization in order to make the problem more linear and, thereby, solve the acquisition design problem by using a gradient descent algorithm. With simple and complex velocity models, we demonstrate that the proposed method is effective, while the involved computational cost is acceptable. Interestingly, the optimization results in our examples show that the conventional uniform geometry already satisfies the resolution requirement, while optimizing for angle coverage can provide a large uplift and is strongly dependent on the velocity model.