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<p>Seismic exploration has been widely used in the oil and gas industry thanks to its high imaging resolution. However, as exploration targets become more and more complex, the density of sources and receivers is required to be higher and higher, resulting in a significant increase in costs. Instead of conventional uniform sampling constrained by the Nyquist/Shannon theorem, compressive sensing theory breaks aliasing by random sampling, which leads to a sparse seismic acquisition design without losing data fidelity. An application study in Liaohe oilfield has been conducted in 2020. The compressive sensing acquisition not only avoids surface obstacles effectively, but also reduces the number of geophones by 25%. The imaging quality of reconstructed seismic data was also improved compared to conventional acquisition. These results suggest that CS acquisition may reduce cost while increasing imaging quality.</p>

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Compressive sensing based seismic data acquisition a case study in northeast China

  • 期刊论文

  • 发表日期：

    2026年5月21日

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  • Jian-guo Chen,
  • Guo-xu Shu,
  • Sheng-qiang Mu,
  • Yi-yuan Wang,
  • Shou-dong Huo

摘要

Seismic exploration has been widely used in the oil and gas industry thanks to its high imaging resolution. However, as exploration targets become more and more complex, the density of sources and receivers is required to be higher and higher, resulting in a significant increase in costs. Instead of conventional uniform sampling constrained by the Nyquist/Shannon theorem, compressive sensing theory breaks aliasing by random sampling, which leads to a sparse seismic acquisition design without losing data fidelity. An application study in Liaohe oilfield has been conducted in 2020. The compressive sensing acquisition not only avoids surface obstacles effectively, but also reduces the number of geophones by 25%. The imaging quality of reconstructed seismic data was also improved compared to conventional acquisition. These results suggest that CS acquisition may reduce cost while increasing imaging quality.