Multiple-point geostatistical (MPS) simulation methods have attracted an enormous amount of attention in earth and environmental sciences due to their ability to enhance extraction and synthesis of heterogeneous patterns. To characterize the subtle features of heterogeneous structures and phenomena, large-scale and high-resolution simulations are often required. Accordingly, the size of simulation grids has increased dramatically. Since MPS is a sequential process for each grid unit along a simulation path, it results in severe computational consumption. In this work, a new hybrid parallel framework is proposed for the case of MPS simulation on large areas with enormous amount of grid cells. Both inter-node-level and intra-node-level parallel strategies are combined in this framework. To maintain the quality of the realizations, we implement a conflict control method adapting to the Monte-Carlo process. Also, an optimization method for the simulation information is embedded to reduce the inter-node communication overhead. A series of synthetic tests were used to verify the availability and performance of the proposed hybrid parallel framework. The results corroborate that the proposed framework can efficiently achieve the high-resolution reproduction and characterization of complex structures and phenomena in earth sciences.

多点地质统计 (MPS) 模拟方法由于能够增强异构模式的提取和合成能力，在地球和环境科学领域引起了极大的关注。为了表征异质结构和现象的细微特征，通常需要大规模和高分辨率的模拟。因此，模拟网格的大小急剧增加。由于 MPS 是沿模拟路径的每个网格单元的顺序过程，因此会导致严重的计算消耗。在这项工作中，针对具有大量网格单元的大面积 MPS 模拟的情况，提出了一种新的混合并行框架。该框架结合了节点间级和节点内级并行策略。为了保持实现的质量，我们实现了一种适应蒙特卡洛过程的冲突控制方法。此外，还嵌入了模拟信息的优化方法，以减少节点间通信开销。一系列综合测试用于验证所提出的混合并行框架的可用性和性能。结果证实，所提出的框架可以有效地实现地球科学中复杂结构和现象的高分辨率再现和表征。