• 应用地球物理学Ⅱ •

### 多参数层序地层的边缘最优智能划分算法及其应用

1. 1. 中国地质大学(武汉)环境学院, 武汉 430074;
2. 江苏省地质调查研究院, 南京 210018;
3. 国土资源部地裂缝地质灾害重点实验室, 南京 210018;
4. 中国地质大学(武汉)环境学院湿地演化与生态恢复湖北省重点实验室, 武汉 430074
• 收稿日期:2014-08-06 修回日期:2014-11-16 出版日期:2015-02-20 发布日期:2015-02-20
• 通讯作者: 梁杏, 女, 1958年生, 教授, 博士生导师, 主要从事地下水流系统理论与工程水文地质方向的教学与科研工作. (E-mail:xliang@cug.edu.cn) E-mail:xliang@cug.edu.cn
• 作者简介:朱常坤, 男, 1987年生, 地下水科学与工程专业硕士研究生, 主要从事三维地质建模及入渗补给科研工作. (E-mail:willing1104@163.com)
• 基金资助:

国家重点基础研究发展计划“973”项目(2010CB428802)和国家自然科学基金项目(41272258)联合资助.

### An edge detection optimum intelligent division method and its application for multi-parameter log data

ZHU Chang-kun1,2,3, LIANG Xing1,4

1. 1. School of Environmental Studies, China University of Geosciences (Wuhan), Wuhan, Hubei 430074, China;
2. Geological Survey of Jiangsu Province, Nanjing 210018, China;
3. Key laboratory of Earth Fissures Geological Disaster, Ministry of Land and Resources, Nanjing 210018, China;
4. Hubei Key Laboratory of Wetland Evolution & Ecological Restoration, School of Environment Studies, China University of Geosciences, Wuhan 430074, China
• Received:2014-08-06 Revised:2014-11-16 Online:2015-02-20 Published:2015-02-20

Abstract:

Sequence stratigraphy division is the important part of geological work, especially in the field of geologic modeling, inversion of sedimentary environment and mineral resources exploration. Well logs can be used for dividing a well (or a segment of it) into a group of sub-sections. In this paper, an edge detection optimum intelligent division method is designed for multi-parameter sequence stratigraphic division. The algorithm incorporates the Fisher optimal division and edge detection methods into Multi-Population Genetic Algorithm (MPGA). The optimization criterion involves the following steps. To begin with, Fisher Ratio and Lipschitz Exponent (LE), which respectively characterize the cycle and singularity of the measuring points, of the Logging parameters are utilized for optimization index constructing. Fisher ratio can be calculated by the sum of the deviation within and between layers, and LE can be calculated by Wavelet Transform Modulus Maxima (WTMM). Then logging measurement points are treated as genes and the group of ordered measurement points are regarded as chromosomes. In order to achieve different populations optimizing searching simultaneously, the parameters of crossover probability and mutation probability are controlled in a reasonable range. Meanwhile, immigrant operators are utilized for coevolving between various populations, which finally realize automatic dividing of sequence stratigraphy basing on multi-parameter logging data. This method mentioned before is applied on division of the Quaternary lithology in the Hebei Plain. It is shown that, the stratigraphic division results accord with the geologically fact. Moreover, the method proves faster and more efficient than the ordinary Fisher optimal division method in computation. It can be conclude that the edge detection optimum intelligent division method is highly applicable in Hebei Plain stratigraphic division of different sediment types, including piedmont area of diluvial alluvial plains, central area of alluvial lacustrine plain and eastern area of alluvial marine plain.