Seismic pre-stack AVA inversion using the Zoeppritz equation and its approximations as a forward engine yields Pand S-wave velocities and density. Due to the presence of seismic noise and other factors, the solution to seismic inversion is generally ill-posed and it is necessary to add constraints to regularize the algorithm. Moreover, since pre-stack inversion is a nonlinear problem, linearized optimization algorithms may fall into false local minima. The simulated annealing (SA) algorithm, on the other hand, is capable of finding the global optimal solution regardless of the initial model. However, when applied to multi-parameter pre-stack inversion, standard SA suffers from instability. Thus, a nonlinear pre-stack inversion method is proposed based on lithology constraints. Specifically, correlations among the elastic parameters are introduced to establish constraints based on a Bayesian framework, with special intention of mitigating the ill-posedness of the inversion problem as well as addressing the lithological characteristics of the formations. In particular, to improve the stability, a multivariate Gaussian distribution of elastic parameters is incorporated into the model updating the SA algorithm. We apply the algorithm to synthetic and field seismic data, indicating that the proposed method has a good resolution and stability performance.

中文翻译：

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基于岩性约束的地震叠前AVA反演方案

使用 Zoeppritz 方程及其近似值作为正向引擎的地震叠前 AVA 反演产生 Pand S 波速度和密度。由于地震噪声等因素的存在，地震反演的解一般是病态的，需要加入约束条件对算法进行正则化。此外，由于叠前反演是一个非线性问题，线性优化算法可能会陷入虚假的局部最小值。另一方面，模拟退火 (SA) 算法能够找到全局最优解，而不管初始模型如何。然而，当应用于多参数叠前反演时，标准 SA 存在不稳定性。因此，提出了一种基于岩性约束的非线性叠前反演方法。具体来说，引入弹性参数之间的相关性以建立基于贝叶斯框架的约束，特别是为了减轻反演问题的不适定性以及解决地层的岩性特征。特别是，为了提高稳定性，将弹性参数的多元高斯分布纳入更新 SA 算法的模型中。我们将该算法应用于合成和现场地震数据，表明所提出的方法具有良好的分辨率和稳定性性能。将弹性参数的多元高斯分布合并到更新 SA 算法的模型中。我们将该算法应用于合成和现场地震数据，表明所提出的方法具有良好的分辨率和稳定性性能。将弹性参数的多元高斯分布合并到更新 SA 算法的模型中。我们将该算法应用于合成和现场地震数据，表明所提出的方法具有良好的分辨率和稳定性性能。