The combination of geophysical surface‐based imaging techniques, including seismic and electrical resistivity tomography (ERT), is now common practice to obtain a more accurate characterization of subsurface structures. Due to model non‐uniqueness and geological heterogeneity, conventional travel‐time tomography cannot solely reveal hidden layers (i.e., low‐velocity zones embedded between layers of higher velocities) in the subsurface. Hence, we present a joint inversion algorithm based on a normalized cross‐gradients function to detect hidden low‐velocity layers. The structural similarity between P‐wave velocity (V_p) and resistivity fields is enhanced by incorporating the normalized cross‐gradients constraint in the joint inversion algorithm. Improved structural similarity can mitigate the problem of the recovery of a hidden layer. We also take advantage of a priori information derived from borehole geological data to reduce the continuous range of possible solutions (i.e., exact‐data non‐uniqueness). In both joint and separate inversions, an auxiliary damping factor is used to ensure convergence, and also the smoothness constraints are applied to deal with instability stemming from error in the data. To verify the performance of the joint inversion procedure, the algorithm is tested on synthetic and real data examples with emphasis on hidden low‐velocity layer detection. Numerical experiments demonstrate that the joint inversion strategy can produce more reliable and better velocity models of the subsurface structures as compared with those obtained through individual inversions. We conclude that this simultaneous joint inversion of V_p and ERT integrates the best of both schemes and makes it possible to improve resolution, and, hence, reduces uncertainties in hidden low‐velocity layer problems.

中文翻译：

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利用P波传播时间和电阻率数据联合反演的隐层成像

如今，结合地面物理成像技术（包括地震层析成像和电阻率层析成像（ERT））已成为一种常见的做法，可以更准确地表征地下结构。由于模型的非唯一性和地质异质性，传统的行进时间层析成像不能仅揭示地下的隐含层（即，在较高速度层之间嵌入的低速度带）。因此，我们提出了一种基于归一化交叉梯度函数的联合反演算法，以检测隐藏的低速层。纵波速度（V _p），并通过在联合反演算法中纳入归一化的交叉梯度约束来增强电阻率场。改进的结构相似性可以减轻隐藏层恢复的问题。我们还利用先验优势来自钻孔地质数据的信息，以减少可能的解决方案的连续范围（即，精确数据的非唯一性）。在联合反演和单独反演中，都使用辅助阻尼因子来确保收敛，并且还将平滑度约束应用于处理由于数据错误而引起的不稳定性。为了验证联合反演程序的性能，对算法进行了合成和真实数据示例测试，重点是隐藏的低速层检测。数值实验表明，与通过单独反演获得的模型相比，联合反演策略可以生成更可靠，更好的地下结构速度模型。我们得出结论，V _p的这种同时联合反演 ERT结合了这两种方案的优点，并可以提高分辨率，从而减少了隐藏的低速层问题的不确定性。