Migration, velocity and amplitude analysis are the employed processing steps to find the desired subsurface information from seismic reflection data. The presence of free‐surface and internal multiples can mask the primary reflections for which many processing methods are built. The ability to separate primary from multiple reflections is desirable. Connecting Marchenko theory with classical one‐dimensional inversion methods allows to understand the process of multiple reflection elimination as a data‐filtering process. The filter is a fundamental wave field, defined as a pressure and particle velocity that satisfy the wave equation. The fundamental wave field does not depend on the presence or absence of free‐surface multiples in the data. The backbone of the filtering process is that the fundamental wave field is computed from the measured pressure and particle velocity without additional information. Two different multiples‐free datasets are obtained: either directly from the fundamental wave field or by applying the fundamental wave field to the data. In addition, the known schemes for Marchenko multiple elimination follow from the main equation. Numerical examples show that source and receiver ghosts, free‐surface and internal multiples can be removed simultaneously using a conjugate gradient scheme. The advantage of the main equation is that the source wavelet does not need to be known and no pre‐processing is required. The fact that the reflection coefficients can be obtained is an interesting feature that could lead to improved amplitude analysis and inversion than would be possible with other processing methods.

中文翻译：

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统一消除一维声学多重反射

迁移，速度和振幅分析是从地震反射数据中找到所需地下信息的处理步骤。自由表面和内部倍数的存在可以掩盖建立许多处理方法的主反射。期望将主反射与多次反射分离的能力。将Marchenko理论与经典的一维反演方法联系起来，可以将多次反射消除过程理解为数据过滤过程。滤波器是基波场，定义为满足波动方程的压力和粒子速度。基波场不取决于数据中自由表面倍数的存在与否。滤波过程的主干在于，基波场是从测得的压力和粒子速度计算出来的，而没有其他信息。获得两个不同的无倍数数据集：直接从基波场获得或通过将基波场应用于数据。另外，从主要方程式可知用于进行马尔琴科多项式消除的已知方案。数值示例表明，可以使用共轭梯度方案同时去除源和接收器的虚影，自由曲面和内部倍数。主方程的优点是不需要知道源小波，也不需要预处理。