Double-weave 3D seismic acquisition — Part 1: Sampling and sparse Fourier reconstruction

Author:

Naghizadeh Mostafa1

Affiliation:

1. Formerly University of Alberta, Department of Physics, Edmonton, Alberta, Canada; presently Shell Canada Energy, Calgary, Alberta, Canada..

Abstract

A stochastic simulation technique analyzes the effectiveness of sparse Fourier reconstruction methods for multidimensional sampling functions. A regular 2D sampling pattern, called a weave pattern, is a suitable sampling scenario for sparse Fourier recovery. The simplicity of a weave sampling pattern provides a good alternative to replace random sampling patterns in compressive sensing applications. A double-weave 3D seismic acquisition design has been developed by using the weave sampling pattern for the shot and receiver distributions. Besides its homogeneous spatial coverage in the shot-receiver and offset-azimuth coordinates, double-weave 3D acquisition is a compatible survey design for alias-free 5D sparse Fourier interpolation in the shot and receiver domains. Zigzag and orthogonal double-weave acquisition layouts were proposed for land seismic surveys considering the economic and environmental parameters. The effectiveness of 5D interpolation for double-weave 3D acquisition were tested using synthetic planar 5D seismic events.

Publisher

Society of Exploration Geophysicists

Subject

Geochemistry and Petrology,Geophysics

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Designing alternative 3D seismic surveys for reduced environmental footprints using the seismic trace density parameter;Third International Meeting for Applied Geoscience & Energy Expanded Abstracts;2023-12-14

2. EcoSeis: A novel acquisition method for optimizing seismic resolution while minimizing environmental footprint;The Leading Edge;2023-01

3. Sparse thresholding for regularization, interpolation, and dealiasing;First International Meeting for Applied Geoscience & Energy Expanded Abstracts;2021-09-01

4. Directional interpolation of multicomponent data;Geophysical Prospecting;2017-02-01

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