[1]张冲.基于海上砂砾岩低渗透率成因分析及测井评价[J].测井技术,2019,43(05):524-530.[doi:10.16489/j.issn.1004-1338.2019.05.016]
 ZHANG Chong.Log Evaluation of Offshore Low-permeability Conglomerate Based on permeability Genesis Analysis[J].WELL LOGGING TECHNOLOGY,2019,43(05):524-530.[doi:10.16489/j.issn.1004-1338.2019.05.016]
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基于海上砂砾岩低渗透率成因分析及测井评价()
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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:
524-530
栏目:
解释评价
出版日期:
2019-10-20

文章信息/Info

Title:
Log Evaluation of Offshore Low-permeability Conglomerate Based on permeability Genesis Analysis
文章编号:
1004-1338(2019)05-0524-07
作者:
张冲
(中海石油(中国)有限公司湛江分公司,广东湛江524057)
Author(s):
ZHANG Chong
(Zhanjiang Branch, CNOOC, Zhanjiang, Guangdong 524057, China)
关键词:
测井评价低渗砂砾岩储层渗透率储层品质指数孔隙结构流沙港组三段
Keywords:
log evaluation low-permeability conglomerate reservoir permeability reservoir quality index pore structure Liu 3 member
分类号:
P631.84
DOI:
10.16489/j.issn.1004-1338.2019.05.016
摘要:
南海北部湾盆地乌石凹陷东区流沙港组三段以砂砾岩为主,岩石矿物类型多变、孔隙结构复杂、测井响应差异大,采用传统的地质统计回归方法很难准确求取储层渗透率。对流沙港组三段砂砾岩储层低渗透率成因分析的基础上,利用Bayes岩性判别原理建立岩相判别方程,对单井岩相进行数字划分,确定单井纵向上岩相类型,从而为储层渗透率的精细解释奠定基础。建立储层品质指数分级下的储层孔渗关系,认为储层品质指数可以作为储层孔隙度、渗透率与孔隙结构特征参数相互转换验证求取的中间桥梁。应用多矿物模型精确确定储层孔隙度,引入和建立储层孔隙结构参数与常规测井之间的定量关系,在岩相划分、孔隙结构特征分析和储层品质指数引入等地质研究基础上,采用非线性BP神经网络求取储层品质指数,进而反算砂砾岩储层渗透率。该方法提高了现有测井信息的利用率,解释结果与岩心和生产情况吻合度高,能够满足油藏描述和储量计算对参数精度的要求,可为南海西部相似低渗砂砾岩体的储层渗透率预测提供技术支撑。
Abstract:
The Liu 3 Member of the Liushagang formation is mainly composed of conglomerate in the eastern Wushi sag, the Beibu Gulf basin in the South China Sea. It is characterized by different minerals, complex pore structures and changing logging response, so that it is difficult to accurately calculate the reservoir permeability by using traditional geostatistical regression methods. In this study, first the genesis of the low permeability of the Liu 3 conglomerate reservoir is analyzed, based on which a lithofacies discrimination equation is built by the Bayes lithofacies principle. Using it, vertical lithofacies in single wells are determined by digital division. It lays a foundation for fine interpretation of reservoir permeability. Second, the relationship between reservoir porosity and permeability is established under the guide of classified reservoir quality index. It is considered that reservoir quality index can be used as a bridge among reservoir porosity, permeability and pore structure in their conversion and verification. Finally, after using a multi-mineral model to calculate the reservoir porosity, and establishing the relationship between pore structures and logging curves, the reservoir quality index is calculated and then the permeability is inverted, using a nonlinear BP neural network. This method improves the utilized rate of available logging data. The interpretation results are highly consistent with core and production data. It can meet the requirements of parameter accuracy for reservoir description and reserve calculation, and can provide technical support to the permeability prediction of similar conglomerate reservoirs in the west of the South China Sea.

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备注/Memo

备注/Memo:
第一作者:张冲,男,1988年生,工程师,从事开发地质工作。E-mail:zchlsqw@163.com (修改回稿日期: 2019-05-23本文编辑余迎)
更新日期/Last Update: 2019-10-20