As oil and gas extraction becomes more advanced, deep-water exploration becomes increasingly focused on imaging near or under complex salt geology, which necessitates detailed velocity models with strong contrast interfaces. These interfaces can be elegantly tracked using the level sets of an implicit surface. One can invert for the velocity model that best fits the recorded data in a full-waveform inversion (FWI) style objective function by reparameterizing the model in terms of an implicit surface representation of the salt interface. With this parameterization of the FWI objective function, we find the Hessian and solve a conjugate gradient system for the Newton step at every nonlinear iteration. We sparsify the representation of the implicit surface using radial basis functions, which can hasten convergence of the inner inversion by reducing the number of model parameters. We have developed a guided inversion approach that embeds information about the certainty of different salt boundary regions by the initialization of the implicit surface slope at the salt interface. This can help guide the inversion away from perceived local minima. The results of testing this inversion workflow on a 3D Gulf of Mexico data set show that it can be a useful tool for refining salt models because the initial and final seismic images show clearer and more consistent features below the updated salt area.

中文翻译：

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使用具有水平集的形状优化进行的3D盐体重构应用

随着石油和天然气开采的日益先进，深水勘探越来越集中于复杂盐地质附近或之下的成像，这需要具有强对比度界面的详细速度模型。可以使用隐式表面的级别集精确地跟踪这些界面。通过根据盐分界面的隐含表面表示重新对模型进行参数化，可以将最适合记录的数据的速度模型进行反演。通过对FWI目标函数的这种参数化，我们找到了Hessian并在每次非线性迭代中为Newton步骤求解了共轭梯度系统。我们使用径向基函数稀疏隐式曲面的表示，通过减少模型参数的数量可以加速内部反演的收敛。我们已经开发了一种引导反演方法，该方法通过初始化盐分界面处的隐式表面坡度来嵌入有关不同盐分边界区域确定性的信息。这可以帮助引导反演远离感知的局部最小值。在3D墨西哥湾数据集上测试此反演工作流的结果表明，它可以用作精炼盐模型的有用工具，因为初始和最终地震图像在更新的盐分区域下方显示出更清晰，更一致的特征。这可以帮助引导反演远离感知的局部最小值。在3D墨西哥湾数据集上测试此反演工作流的结果表明，它可以用作精炼盐模型的有用工具，因为初始和最终地震图像在更新的盐分区域下方显示出更清晰，更一致的特征。这可以帮助引导反演远离感知的局部最小值。在3D墨西哥湾数据集上测试此反演工作流的结果表明，它可以用作精炼盐模型的有用工具，因为初始和最终地震图像在更新的盐分区域下方显示出更清晰，更一致的特征。