[1]黄秋静,孙建孟,王海青.元素录井确定矿物含量多种方法对比研究[J].测井技术,2019,43(05):445-451.[doi:10.16489/j.issn.1004-1338.2019.05.001]
 HUANG Qiujing,SUN Jianmeng,WANG Haiqing.Comparison of Element-logging-based Methods for Determining Mineral Contents[J].WELL LOGGING TECHNOLOGY,2019,43(05):445-451.[doi:10.16489/j.issn.1004-1338.2019.05.001]
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元素录井确定矿物含量多种方法对比研究()
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《测井技术》[ISSN:1004-1338/CN:61-1223/TE]

卷:
第43卷
期数:
2019年05期
页码:
445-451
栏目:
综述
出版日期:
2019-10-20

文章信息/Info

Title:
Comparison of Element-logging-based Methods for Determining Mineral Contents
文章编号:
1004-1338(2019)05-0445-07
作者:
黄秋静1孙建孟1王海青2
(1.中国石油大学(华东)地球科学与技术学院,山东青岛266580; 2.山东立鼎石油科技有限公司,山东东营257000)
Author(s):
HUANG Qiujing1SUN Jianmeng1WANG Haiqing2
(1. China University of Petroleum (East China), Qingdao, Shandong 266580, China; 2. Shandong Leading Petro-Tech CO. LTD., Dongying, Shandong 257000, China)
关键词:
元素荧光录井元素含量矿物含量转换系数线性规划方法对比岩性划分
Keywords:
element fluorescence logging elemental concentration mineral content conversion coefficient linear programming method comparison lithology classification
分类号:
P631.84
DOI:
10.16489/j.issn.1004-1338.2019.05.001
文献标志码:
A
摘要:
通过5种方法实现矿物含量反演对比研究。氧化物闭合模型法基于矿物的氧化物与碳酸盐含量百分数之和为100%建模求解;非负最小二乘法、截断奇异值法和线性规划法以Herron模型为基础,通过对区块岩性特征分析,建立元素与岩性矿物组分转换关系,基于矩阵求解方法,建立元素含量反演矿物含量模型;神经网络法通过构建神经网络结构求解。在矿物含量反演基础上,利用斯伦贝谢公司岩性图版进行处理,实现碎屑岩岩性定名。以长庆油田×井为例,通过5种反演方法进行矿物含量计算和岩性定名,将计算结果与全岩分析结果对比表明,线性规划方法处理结果最佳,神经网络法次之;各方法随地层深度变化趋势与全岩分析结果基本一致;编写了自动处理软件,使碎屑岩岩性识别正确率达到89%,取得了良好的应用效果。
Abstract:
Five inversion methods were compared for calculating mineral contents. The oxide closure model method assumes that the total content of oxide and carbonate minerals is 100%. The non negative least square method, the singular value truncating method and the linear programming method are based on the Herron model. Through the analysis of regional lithology, the transformation relationship between elements and lithologic mineral components is established, and then a mineral content inversion model is established based on the matrix solution method. The neural network method calculates mineral content by constructing a neural network structure. On the basis of mineral content inversion, Schlumberger lithologic charts are used to describe specific lithology of clastic rock. Taking well × in Changqing oilfield as a case, the five inversion methods were used to calculate the mineral content and name the lithology. The results from the five methods were compared with whole rock analysis results. It is found that the linear programming method is the most effective, followed by the neural network method. All the results are basically consistent with the whole rock analysis results on the trend changing with depth. An automatic processing software has been developed. And its correct rate of lithology identification of clastic rock reaches 89%, indicating good application effect.

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相似文献/References:

[1]黄隆基,仇维勇.地球化学测井[J].测井技术,1991,15(01):42.
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[2]章海宁,张金功,岳爱忠,等.利用地层元素识别沉积岩岩性和矿物含量计算方法[J].测井技术,2016,40(06):683.[doi:10.16489/j.issn.1004-1338.2016.06.005]
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备注/Memo

备注/Memo:
第一作者:黄秋静,1994年生,硕士研究生,从事测井解释与方法等方面应用研究。E-mail:qjhuang810@qq.com(修改回稿日期: 2019-07-26本文编辑余迎)
更新日期/Last Update: 2019-10-20