准噶尔盆地玛湖凹陷百口泉组多因素流体识别技术及应用

准噶尔盆地玛湖凹陷百口泉组多因素流体识别技术及应用

张浩^1,2 甘仁忠¹ 王国斌¹ 曹志峰² 赵彦青² 吴保中²

1 中国石油新疆油田公司；2 中国石油集团西部钻探工程有限公司

发布日期:2015-05-20
作者简介:张浩（1983-），男，山西侯马人，2005 年毕业于中国石油大学（华东），工程师，主要从事录井、测井项目管理及研究工作。地址：新疆克拉玛依市友谊路98 号三号楼新疆油田公司勘探公司，邮政编码：834000。E-mail:zhanghao8@petrochina.com.cn
基金资助:
中国石油新疆油田公司油气勘探科技专项^“多因素流体识别技术及提高油气解释符合率方法研究^”（XJKT-76）

Multi-factor Fluid Identification Technology and Its Application in Baikouquan Formation of MahuDepressioin in Junggar Basin

Zhang Hao^1,2,Gan Renzhong¹,Wang Guobi¹,Cao Zhifeng²,Zhao Yanqing²,Wu Baozhong²

1 PetroChina Xinjiang Oilfield Company; 2 CNPC Western Drilling Engineering Co Ltd

Published:2015-05-20

摘要/Abstract

摘要： 利用聚类分析和交会图技术，将准噶尔盆地玛湖凹陷百口泉组低孔低渗砂砾岩储层分为4 类，同时综合分析录井、测井和试油资料，探索多学科联合的复杂储层多因素流体识别方法。建立了基于核磁测井物性参数的储层质量分类图版；创建了气测含油因子、测井含油因子计算模型；构建了玛湖凹陷流体识别方法，使录井、测井解释符合率分别提高30.6% 和28.1%。通过储层改造效果分析，建立了基于测井杨氏模量判别标准，将玛湖凹陷储层划分为易压裂与不易压裂两类；通过对最优裂缝动态缝长、加砂因子等参数分析，建立了储层改造达到最优效果压裂预测模型，玛湖凹陷压裂见效率提高了32.7%。

Abstract: Based on the cluster analysis and cross plot technique, the low-porosity and low-permeability sandstone reservoir of Baikouquan Formation in Mahu Depression of Junggar Basin is divided into four categories. Meanwhile, comprehensive well log, logging and oil testing data are used to develop the multidisciplinary identification method for multi-factor fluid in the complicated reservoir. The reservoir quality classification plot is established on the basis of the physical properties acquired by NMR logging while the calculation model of gas-logging oil-bearing factor and wireline logging oil-bearing factor is created. In addition, with the fluid identification method for Mahu Depression developed, the coincidence rate of mud logging and wireliine logging is improved by 30.6 percent and 28.1 percent. Through the analysis of reservoir renovation results, the distinguishing criteria are established on the basis of the Young^’s modulus from logging, dividing the reservoir in this area into ^“easy to fracture^” and ^“difficult to fracture.^” Based on analysis of the relevant parameters, such as dynamic fractural length and sanding factor, the fracturing prediction model for maximum results of reservoir renovation is established, which improves the fracturing results of Mahu Depression by 32.7 percent.

张浩,甘仁忠,王国斌,曹志峰,赵彦青,吴保中. 准噶尔盆地玛湖凹陷百口泉组多因素流体识别技术及应用[J]. .

Zhang Hao,Gan Renzhong,Wang Guobi,Cao Zhifeng,Zhao Yanqing and Wu Baozhong. Multi-factor Fluid Identification Technology and Its Application in Baikouquan Formation of MahuDepressioin in Junggar Basin[J]. .