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物探与化探  2021, Vol. 45 Issue (5): 1239-1247    DOI: 10.11720/wtyht.2021.1335
  方法研究·信息处理·仪器研制 本期目录 | 过刊浏览 | 高级检索 |
致密砂岩储层脆性测井评价方法研究及应用——以鄂尔多斯盆地渭北油田为例
朱颜(), 韩向义(), 岳欣欣, 杨春峰, 常文鑫, 邢丽娟, 廖晶
中国石油化工股份有限公司 河南油田分公司勘探开发研究院,河南 郑州 450018
Research and application of brittleness logging evaluation method to tight sandstone reservoirs:Exemplified by Weibei oilfield in Ordos Basin
ZHU Yan(), HAN Xiang-Yi(), YUE Xin-Xin, YANG Chun-Feng, CHANG Wen-Xin, XING Li-Juan, LIAO Jing
Exploration and Development Research Institute of Henan Oilfield Company,Sinopec,Zhengzhou 450018,China
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摘要 

致密砂岩储层具有非均质性强、物性差、勘探开发难度大等特点,为了寻找渭北油田致密砂岩储层的高脆性段进行储层的压裂改造,针对现有横波测井资料匮乏以及当前脆性预测方法在渭北油田致密砂岩储层是否适用等问题,提出了基于ANN(artificial neural network)模型的横波预测方法,预测值与实测值高度吻合,进而通过弹性参数法计算出研究区每口井的脆性指数。为了校正该方法预测脆性指数的准确性,通过对研究区较少井的X射线衍射全岩分析研究,明确了石英和碳酸盐类矿物为研究区延长组的主要脆性矿物,利用“(石英+碳酸盐)含量/矿物总量”计算岩石脆性指数去校正弹性参数法预测的脆性指数,这种矿物组分法和弹性参数法相互制约而又相互依存的方法,不但提高了预测精度,而且弥补了阵列声波测井和全岩分析资料不足的问题。利用该方法对渭北油田WB2井区延长组致密砂岩储层进行了测井脆性评价,为WB52和WB49井高脆性有利压裂目的层段识别及增产方案设计提供了依据。所提出的方法和流程具有较强的应用价值和推广价值。

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朱颜
韩向义
岳欣欣
杨春峰
常文鑫
邢丽娟
廖晶
关键词 脆性指数致密砂岩压裂改造横波预测弹性参数人工神经网络矿物脆性指数甜点    
Abstract

Tight sandstone reservoirs have the characteristics of strong heterogeneity,poor physical properties,and difficulty in exploration and development.In order to find the high-brittleness section of tight sandstone reservoirs in the Weibei oilfield and fracture this kind of reservoirs,this paper proposes a method based on ANN (artificial neural network) model for shear wave prediction under the condition of lacking suitable brittleness prediction methods for tight sandstone reservoirs in the Weibei oilfield at present.The predicted value is highly consistent with the measured value,and the brittleness index of each well in the study area is calculated by the elastic parameter method further.For the purpose of improving the accuracy of the brittleness index predicted by this method,X-ray diffraction full-rock analysis of fewer wells in the study area is utilized,and it is concluded that quartz and carbonate rocks are the main brittle minerals of the Yanchang formation in the study area."(quartz+carbonate) content/ total minerals " are adopted to calculate the rock brittleness index and then improve the brittleness index predicted by the elastic parameter method.This technique which takes advantage of the balance between the mineral composition method and the elastic parameter method not only improves the prediction accuracy but also makes up for the lack of array acoustic logging and whole rock analysis data.This method was used to predict the brittleness of tight sandstone reservoirs in the WB2 well area of the Yanchang formation in the Weibei oilfield, and high-brittleness sections of WB52 and WB49 were further chosen to be fractured.It is shown that the production stimulation effect was obvious after fracturing,which is of great significance for guiding hydraulic fracturing.The method and process proposed in this paper have strong application and promotion value.

Key wordsbrittleness index    tight sandstone    fracturing transformation    shear wave prediction    elastic parameters    artificial neural network    mineral fragility index    dessert
收稿日期: 2020-09-29      修回日期: 2021-06-17      出版日期: 2021-10-20
ZTFLH:  P631.4  
基金资助:中国石油化工股份有限公司重点科技攻关项目“鄂南致密油地球物理预测技术应用研究”(PE19008-5)
通讯作者: 韩向义
作者简介: 朱颜(1983-),男,高级工程师,主要从事油气勘探综合研究工作。Email: zhu007yan@163.com
引用本文:   
朱颜, 韩向义, 岳欣欣, 杨春峰, 常文鑫, 邢丽娟, 廖晶. 致密砂岩储层脆性测井评价方法研究及应用——以鄂尔多斯盆地渭北油田为例[J]. 物探与化探, 2021, 45(5): 1239-1247.
ZHU Yan, HAN Xiang-Yi, YUE Xin-Xin, YANG Chun-Feng, CHANG Wen-Xin, XING Li-Juan, LIAO Jing. Research and application of brittleness logging evaluation method to tight sandstone reservoirs:Exemplified by Weibei oilfield in Ordos Basin. Geophysical and Geochemical Exploration, 2021, 45(5): 1239-1247.
链接本文:  
https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2021.1335      或      https://www.wutanyuhuatan.com/CN/Y2021/V45/I5/1239
Fig.1  人工神经网络结构
Fig.2  ANN横波速度预测方法流程
Fig.3  研究区测井曲线与横波时差交会
Fig.4  不同井横波速度预测值与实测真实值对比
Fig.5  WB48井目的层段横波速度结果分析
深度/m 层位 黏土类
矿物/%
石英/% 长石(钾
长石+钠长
石)/%
碳酸盐类矿物
(方解石+
白云石)/%
498.02
499.65
501.01
502.42
503.35
522.91
524.86
526.16
528.08
530.38
533.66
538.8
807.28
809.05
810.5
811.66
812.74
813.7
815.45
817.17
827.28
828.73
830.76
831.9
833.44
C3
C3
C3
C3
C3
C3
C3
C3
C3
C3
C3
C3
C6
C6
C6
C6
C6
C6
C6
C6
C7
C7
C7
C7
C7
11
9
6
9
10
12
12
11
8
8
7
9
16
17
13
15
10
10
17
14
15
22
13
13
17
49
52
33
46
55
52
47
49
44
50
44
40
47
43
49
44
40
48
44
49
44
37
44
26
40
30
30
42
41
30
29
30
33
40
32
44
48
26
30
32
32
28
31
29
26
32
28
34
36
32
10
9
19
4
5
7
11
7
8
10
5
3
11
10
6
9
22
11
10
11
9
13
9
25
11
Table 1  WB48井延长组全岩矿物X衍射数据
Fig.6  石英、长石、碳酸盐岩类矿物和黏土类矿物与杨氏模量、泊松比交会分析
a—石英与杨氏模量、泊松比交会分析;b—长石与杨氏模量、泊松比交会分析;c—碳酸盐岩类矿物与杨氏模量、泊松比交会分析;d—黏土类矿物与杨氏模量、泊松比交会分析
Fig.7  杨氏模量、泊松比交会图版
Fig.8  渭北地区致密油井脆性指数预测
Fig.9  渭北地区致密油井脆性预测结果
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