Gravity gradiometry inversion can provide important knowledge about a salt body and can assist in subsalt imaging. However, such inversions are faced with difficulties associated with the lack of response from the nil zone in which the salt density is nearly identical to that of the background sediments and weak signals from the deeper portion of the salt. It is well understood that such difficulties could be alleviated by incorporating prior information, such as the top of salt from seismic imaging and petrophysical data, into the inversions. How to effectively incorporate such prior information is still a challenge, and what level of increased knowledge such constrained inversions can provide remains to be understood. We have investigated and compared the additional knowledge provided by incorporating different forms of prior information, such as a top-of-salt surface and an expected density contrast model. These different types of information are incorporated through different strategies of constrained inversion, including an inversion with bound constraints on the density contrast, inversion after a reduction-to-binary process, and discrete-valued inversion. We apply these strategies first to synthetic gravity gradiometry data calculated from the SEG/EAGE salt body and evaluate the improvements to the recovered salt provided from successive imposition of increased prior information. We further apply the strategies to a set of marine gravity gradiometry data collected in the Gulf of Mexico and examine the additional knowledge gained from the imaging of the salt in the region. We find that much more valuable knowledge about the salt can be obtained with the right prior information imposed through an effective strategy, and we determine that such gravity gradiometry data contain information about the salt body at depths much greater than previously recognized.

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通过盐体约束反演了解重力梯度数据中的信息含量

重力梯度反演可以提供关于盐体的重要知识，并有助于盐下成像。然而，这种反演面临着与缺乏来自无盐带的响应相关的困难，在无盐带中盐密度几乎与背景沉积物的盐密度相同，并且来自盐的较深部分的信号较弱。众所周知，通过将先验信息（例如来自地震成像和岩石物理数据的盐顶）纳入反演，可以减轻此类困难。如何有效地结合这些先验信息仍然是一个挑战，这种约束反演可以提供何种程度的增加知识仍有待理解。我们已经调查并比较了通过结合不同形式的先验信息提供的额外知识，例如盐顶表面和预期的密度对比模型。这些不同类型的信息通过不同的约束反演策略合并，包括对密度对比度有边界约束的反演、归约到二进制过程后的反演和离散值反演。我们首先将这些策略应用于从 SEG/EAGE 盐体计算的合成重力梯度数据，并评估通过连续施加增加的先验信息提供的回收盐的改进。我们进一步将这些策略应用于在墨西哥湾收集的一组海洋重力梯度数据，并检查从该地区盐的成像中获得的额外知识。