Entropy-Based Weighting in One-Dimensional Multiple Errors Analysis of Geological Contacts to Model Geological Structure
Entropy-Based Weighting in One-Dimensional Multiple Errors Analysis of Geological Contacts to Model Geological Structure
复制标题
地质接触一维多重误差分析中基于熵的加权来模拟地质结构
DOI：
10.1007/s11004-018-9750-1
复制
发表时间：
2018-06
影响因子：
2.6
通讯作者：
Keith Clarke
中科院分区：
文献类型：
--
作者：
Weisheng Hou;Chanjie Cui;Liang Yang;Qiaochu Yang;Keith Clarke
在地质建模的每一步中，误差都会对测量和工作流程产生影响，因此会对精确的三维地质建模提出挑战。在经典误差理论的背景下，目前，只考虑空间位置误差，承认时间，属性和本体误差以及许多其他误差是完整误差预算的一部分。现有的方法通常假设单一的误差分布（高斯）存在于所有类型的空间数据。然而，在不同种类的原始数据（诸如钻孔日志、用户定义的地质剖面和地质图）之间并且甚至在不同种类的原始数据内，可能存在不同类型的位置误差分布。大多数统计方法对影响其解释力的误差分布进行先验假设。因此，分析多源数据和混合数据中的地质建模误差仍然是地质建模中的一个巨大挑战。在这项研究中，提出了一种新的方法来分析一维多个错误的原始数据用于模型地质结构。该分析是基于空间误差分布与不同地质属性之间的关系。通过假定地质地下空间的接触点由地下空间两侧的地质属性决定，将地质接触点的空间误差转化为三维空间各点处所有相关地质属性的具体概率，即“地质属性概率”。将正态分布和连续均匀分布转换为地质属性概率，转换后可直接对不同的空间误差分布求和。在交叉点上，多个原始数据的误差遵循不同的分布，基于熵的权重被赋予每种类型的数据，以计算最终的概率。空间上各点的权值由相关地质属性的概率决定。在解释地质接触的最佳估计的测试应用中，实验结果表明：（1）对于线段，地质属性概率的带状形状与现有误差模型的带状形状相匹配;以及（2）地质属性概率直接显示误差分布，并且是描述输入数据之间的多个误差分布的有效方式。
In each step of geological modeling, errors have an impact on measurements and workflow processes and, so, have consequences that challenge accurate three-dimensional geological modeling. In the context of classical error theory, for now, only spatial positional error is considered, acknowledging that temporal, attribute, and ontological errors—and many others—are part of the complete error budget. Existing methods usually assumed that a single error distribution (Gaussian) exists across all kinds of spatial data. Yet, across, and even within, different kinds of raw data (such as borehole logs, user-defined geological sections, and geological maps), different types of positional error distributions may exist. Most statistical methods make a priori assumptions about error distributions that impact their explanatory power. Consequently, analyzing errors in multi-source and conflated data for geological modeling remains a grand challenge in geological modeling. In this study, a novel approach is presented regarding the analysis of one-dimensional multiple errors in the raw data used for model geological structures. The analysis is based on the relationship between spatial error distributions and different geological attributes. By assuming that the contact points of a geological subsurface are decided by the geological attributes related to both sides of the subsurface, this assumption means that the spatial error of geological contacts can be transferred into specific probabilities of all the related geological attributes at each three-dimensional point, which is termed the “geological attribute probability”. Both a normal distribution and a continuous uniform distribution were transferred into geological attribute probabilities, allowing different kinds of spatial error distributions to be summed directly after the transformation. On cross-points with multiple raw data with errors that follow different kinds of distributions, an entropy-based weight was given to each type of data to calculate the final probabilities. The weighting value at each point in space is decided by the related geological attribute probabilities. In a test application that accounted for the best estimates of geological contacts, the experimental results showed the following: (1) for line segments, the band shape of geological attribute probabilities matched that of existing error models; and (2) the geological attribute probabilities directly show the error distribution and are an effective way of describing multiple error distributions among the input data.
登录
查看更多内容
影响因子：
2.9
作者：
M. Lindsay;L. Aillères;M. Jessell;E. Kemp;P. Betts
通讯作者：
M. Lindsay;L. Aillères;M. Jessell;E. Kemp;P. Betts
多源数据复杂故障的 3D 建模方法
影响因子：
4.4
作者：
Qiang WU;Hua XU;Xukai ZOU;Hongzhuan LEI
通讯作者：
Hongzhuan LEI
影响因子：
2.6
作者：
G. Caumon;P. Collon-Drouaillet;C. L. C. D. Veslud-C.-L.-C.-D.-Veslud-3212821;S. Viseur;J. Sausse
通讯作者：
G. Caumon;P. Collon-Drouaillet;C. L. C. D. Veslud-C.-L.-C.-D.-Veslud-3212821;S. Viseur;J. Sausse
DOI：
10.1016/0198-9715(93)90040-c
发表时间：
1993-03
期刊：
Computers, Environment and Urban Systems
影响因子：
--
作者：
W. Caspary;Robert Scheuring
通讯作者：
W. Caspary;Robert Scheuring
影响因子：
1.9
作者：
R. Reyment;J. C. Davis
通讯作者：
R. Reyment;J. C. Davis