Reconstruction of sparsely sampled seismic data is critical for maintaining the quality of
seismic images when significant numbers of shots and receivers are missing. We present a …

介绍了CSI (Compressive Seismic Imaging) 技术. 该技术是基于压缩感知理论所开发出的一
整套地震资料采集和处理综合技术, 主要包括非规则最优化采样设计, 地震信号的稀疏化处理 …

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 …

Seismic surveys are subject to many different design criteria, but often the parameters are
established based on an outdated view of how data can be acquired and how it will be …

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

We illustrate the advantages of deblending a simultaneous source acquisition with a
multiple stages source separation with prior approach using higher dimensional transform …

We present a new sampling scheme for seismic network observations and seismic
exploration data acquisition based on compressive sensing theory. According to this theory …

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 acquisition and reconstruction of seismic data are fundamental to seismic exploration.
The balancing data quality and acquisition cost is essential. To address this challenge, we …

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