Diffracted wavefields with superior illumination encode key geologic information about small‐scale geologic discontinuities or inhomogeneities in the subsurface and thus possess great potential for high‐resolution imaging. However, the weak diffracted wavefield is easily masked by the dominant reflected data. Diffraction separation from specular reflected data still plays an important role and plays a major role in diffraction imaging implementation. To solve this problem, a new diffraction‐separation method is proposed that uses variational mode decomposition to suppress reflected data and separate diffracted wavefields in the common‐offset or poststack domains. The variational mode decomposition algorithm targets reflected wavefield by decomposing seismic data into an ensemble of band‐limited intrinsic mode functions representing linear and strong reflected data. This method is based on the principle of energy sparsity and can utilize the kinematic and dynamic differences between reflected and diffracted wavefields to effectively predict linear reflected data. Synthetic and field data examples using complex body geometries demonstrate the effectiveness and performance of the proposed method in enhancing diffracted wavefield and attenuating reflected data as well as increasing the signal‐to‐noise ratio, which helps to clearly image small‐scale subwavelength geologic structures.

中文翻译：

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变分分解的衍射分离

具有出色照明的衍射波场可编码有关地下小规模地质不连续性或不均匀性的关键地质信息，因此具有高分辨率成像的巨大潜力。但是，弱的衍射波场很容易被主要的反射数据掩盖。从镜面反射数据中进行衍射分离仍然起着重要作用，并且在衍射成像实现中起着重要作用。为了解决这个问题，提出了一种新的衍射分离方法，该方法使用变分模式分解来抑制反射数据并分离出公共偏移域或叠后域中的衍射波场。变分模式分解算法通过将地震数据分解为代表线性和强反射数据的带限固有模式函数的集合，从而以反射波场为目标。该方法基于能量稀疏原理，可以利用反射波场和衍射波场之间的运动学和动态差异来有效地预测线性反射数据。使用复杂几何体的合成和现场数据示例证明了该方法在增强衍射波场和衰减反射数据以及增加信噪比方面的有效性和性能，这有助于清晰地成像小规模的亚波长地质结构。该方法基于能量稀疏原理，可以利用反射波场和衍射波场之间的运动学和动态差异来有效地预测线性反射数据。使用复杂几何体的合成和现场数据示例证明了该方法在增强衍射波场和衰减反射数据以及增加信噪比方面的有效性和性能，这有助于清晰地成像小规模的亚波长地质结构。该方法基于能量稀疏原理，可以利用反射波场和衍射波场之间的运动学和动态差异来有效地预测线性反射数据。使用复杂几何体的合成和现场数据示例证明了该方法在增强衍射波场和衰减反射数据以及增加信噪比方面的有效性和性能，这有助于清晰地成像小规模的亚波长地质结构。