Work

Adaptive internal multiples suppression in vertical seismic profiling imaging

Year: 2026
Type: article
Abstract: Vertical seismic profiling (VSP) imaging offers superior resolution of subsurface structures compared to traditional surface seismic methods, but its accuracy is often degraded by internal multiple reflections within complex well logging environments. To address internal multiple contamination in VSP data, we develop an adaptive internal multiple suppression strategy within a two-way wave-equation-based wavefield depth extrapolation framework, incorporating wavefield decomposition and wavefield reciprocity to construct a more effective imaging workflow tailored to the characteristics of VSP data. Numerical tests on synthetic datasets—including a horizontal layer model, multilayer model with curved structure, and SEG/EAGE (Society of Exploration Geophysicists / European Association of Geoscientists and Engineers) salt dome model—demonstrate its effectiveness, compared to conventional one-way phase-shift plus interpolation imaging. The proposed approach markedly reduces internal multiple-induced artifacts, enhances reflector continuity, and improves target clarity, especially beneath laterally varying salt bodies. Although the proposed method shows a slight decline in internal multiple attenuation under smoothed velocity models, it nonetheless outperforms conventional methods by attenuating these multiples and mitigating their influence on the imaging results. Moreover, imaging of a modeled VSP dataset using real well-logging velocity function further demonstrates the advantage of our proposed method in dealing with internal multiples suppression, compared to conventional migration methods. Overall, our proposed strategy provides a high-fidelity VSP imaging solution with internal multiples suppression for complex reservoirs, advancing subsurface characterization in deep resource exploration.
Language: English
Subfield: Geophysics
Open Access status: gold
Estimated APC paid: $1,550
OpenAlex ID: W7118173107
FWCI: 3.869
Cites: 29
Cited by: 1
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