提出了基于压缩感知的非规则观测系统优化设计和地震数据重建方法. 基于贪心序贯策略,
利用逐个选取采样点位置的方法来降低感知矩阵的最大互相关值, 从而完成非规则观测系统的 …

Blended acquisition along with efficient detector and source geometries allows for a cost-
effective operation. The outcome of subsequent deblending and data reconstruction is of …

Physical and budget constraints often result in inadequate sampling for accurate subsurface
imaging. Preprocessing approaches, such as missing trace interpolation, are typically …

Seismic acquisition is a trade-off between image quality and cost. While there is an
increasing need for higher quality images due to the more complex geologic settings of …

Compressive Sensing (CS) opens up new perspectives for seismic acquisition design and
data reconstruction. The quality of CS reconstructed data depends on three elements …

Seismic data acquisition is essential for discovering new hydrocarbon targets, where a high-
resolution regular-spaced acquisition is critical to obtain high-quality seismic images …

The compressive sensing (CS) framework offers a cost-effective alternative to dense alias-
free sampling. Designing seismic layouts based on the CS technique imposes the use of …

In this paper, we propose a novel approach for compressive sensing seismic acquisition:
Two-stage sampling. A random sampling scheme is used for the first stage and then large …

The application of blended acquisition has drawn considerable attention owing to its ability
to improve the operational efficiency as well as the data quality and health, safety and …

A method is described to design sparse acquisition grids that minimize mutual coherence
between Fourier components of the measured signals. The designs are bases on difference …