Uncertainty assessment of nonstationary data

地质统计学使用统计技术来评估地质存款的资源或储量。 最近，这些技术已成为越来越受欢迎的了解稀疏采样的矿床，石油储层，二氧化碳封存地点，污染区和许多其他空间分布的现象，地质沉积的不确定性。 这项工作涉及开发技术，以更好地模拟表现出复杂的非平稳地质特征的矿床。 最近的研究探讨了建模方法，考虑非平稳特征的背景下，采矿或石油研究，典型的功能包括渠道，静脉，曲线地层，背斜，辊前存款等建议的工作是扩大这些非平稳技术，包括环境数据，特别是时空数据。 有三个方面的研究计划（1）推广非平稳空间建模技术，包括非平稳时空数据的情况下，（2）开发技术和工具，以推断非平稳技术所需的复杂的输入统计数据和（3）条件对象为基础的模型，硬和软数据，以产生条件非平稳模型。

Geostatistics uses statistical techniques to assess the resources or reserves for a geological deposit. Lately, these techniques have become increasingly popular for understanding the uncertainty in sparsely sampled mineral deposits, petroleum reservoirs, CO2 sequestration sites, contaminated areas and many other spatially distributed phenomenon that follow geological deposits. This work relates to the development of techniques to better model deposits that exhibit complex nonstationary geological features. Recent research has explored modeling methodologies that consider nonstationary features in the context of mining or petroleum studies; typical features include channels, veins, curvilinear strata, anticlines, roll front deposits, etc. The proposed work is to expand these nonstationary techniques to include environmental data, specifically spatial-temporal data. There are three aspects of research planned (1) generalize nonstationary spatial modeling techniques to include cases of nonstationary spatial-temporal data and (2) develop techniques and tools to infer the complex input statistics required for nonstationary techniques and (3) condition object based models to hard and soft data to generate conditioned nonstationary models.