A multi-lithology diffusive stratigraphic model is considered, which simulates at large scales in space and time the infill
of sedimentary basins governed by the interaction between tectonics displacements, eustatic variations, sediment supply, and
sediment transport laws. The model accounts for the mass conservation of each sediment lithology resulting in a mixed parabolic,
hyperbolic system of partial differential equations (PDEs) for the lithology concentrations and the sediment thickness. It
also takes into account a limit on the rock alteration velocity modeled as a unilaterality constraint. To obtain a robust,
fast, and accurate simulation, fully and semi-implicit finite volume discre tization schemes are derived for which the existence
of stable solutions is proved. Then, the set of nonlinear equations is solved using a Newton algorithm adapted to the unilaterality
constraint, and preconditioning strategies are defined for the solution of the linear system at each Newton iteration. They
are based on an algebraic approximate decoupling of the sediment thickness and the concentration variables as well as on a
proper preconditioning of each variable. These algorithms are studied and compared in terms of robustness, scalability, and
efficiency on two real basin test cases. 相似文献
为了提高AVO(amplitude versus offset)反演结果的精度和横向连续性,本文提出了一种新的AVO反演约束方法,该方法结合贝叶斯原理和卡尔曼滤波算法实现了对反演参数纵向和横向的同时约束.文章首先结合反演参数的纵向贝叶斯先验概率约束和反演参数的横向连续性假设建立了与卡尔曼滤波算法对应的AVO反演系统的数学模型,然后将该数学模型代入卡尔曼滤波算法框架,利用卡尔曼滤波算法实现了双向约束AVO反演.二维模型测试和实际数据测试结果表明,相对于单纯的纵向贝叶斯先验概率约束,双向约束能更准确地刻画参数的横向变化,得到更准确、横向连续性更好的反演结果.