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天然气地球科学 ›› 2020, Vol. 31 ›› Issue (2): 307–316.doi: 10.11764/j.issn.1672-1926.2019.11.012

• 天然气勘探 • 上一篇    下一篇

基于自然伽马和电阻率曲线的高温高压气层孔隙度计算方法

谭伟(),何胜林,张海荣,丁磊,梁玉楠   

  1. 中海石油（中国 ）有限公司湛江分公司，广东 湛江 524057
  • 收稿日期:2019-07-16 修回日期:2019-11-29 出版日期:2020-02-10 发布日期:2019-12-03
  • 作者简介:谭伟（1987-），男，湖北利川人，工程师，硕士，主要从事地球物理测井储层评价研究.E-mail: tan06023@126.com.
  • 基金资助:
    国家“十三五”科技重大专项子课题“南海西部海域低渗油藏勘探开发关键技术”(2016ZX05024-006)

Porosity calculation method of high temperature and high pressure gas reservoir based on natural gamma ray and resistivity curve

Wei TAN(),Sheng-lin HE,Hai-rong ZHANG,Lei DING,Yu-nan LIANG   

  1. Zhanjiang Branch of CNOOC Ltd. , Zhanjiang 524057, China
  • Received:2019-07-16 Revised:2019-11-29 Online:2020-02-10 Published:2019-12-03
  • Supported by:
    China National Science & Technology Major Project during the 13th five year plan(016ZX05024-006)

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摘要：

海上高温高压气田开发井受测井作业难度大和环境评估要求高的限制，测井项目通常只有自然伽马和电阻率曲线，储层定量评价中以孔隙度为核心的相关参数难以获取，严重制约了开发配产及后期储量核算等工作。以研究区含泥质砂岩储层导电模型——印度尼西亚方程为理论基础，分析了储层孔隙度与电阻率、含水饱和度和泥质含量的关系，揭示了常规基于数理统计思想的孔隙度计算方法存在的不足。在此基础上结合油气成藏毛管压力理论，通过严格的过程推导分岩性建立了储层孔隙度与电阻率、泥质含量和气柱高度的函数关系式。数值模拟研究表明：研究区电阻率的高低最能反映气层孔隙度的大小，泥质含量次之，烃柱高度影响较小；且在其他2个因素不变的前提下，电阻率、泥质含量均与孔隙度呈正相关，而烃柱高度与其呈反相关。最后利用数值求解手段确定了更加符合气藏特征的孔隙度数值解，形成一种基于自然伽马和电阻率曲线的孔隙度计算方法。与常规3种数理统计方法对比，孔隙度计算效果明显改善;与最优化算法相比，相对误差在±8%以内，证实了方法的可靠性。

关键词: 孔隙度, 自然伽马, 电阻率, 数值模拟, 开发井

Abstract:

The development wells of offshore oilfields are limited by the difficulty of logging operation and the high requirement of environmental assessment. Logging projects usually only have natural gamma ray and resistivity curves. It is difficult to obtain the related parameters with porosity as the core in reservoir quantitative evaluation, which seriously restricts the production allocation and later reserves accounting of oilfield development. Based on the conductivity model of argillaceous sandstone reservoirs in the study area, Indonesia equation, the relationship between reservoir porosity and resistivity, water saturation and argillaceous content is analyzed, and the shortcomings of conventional porosity calculation method based on mathematical statistics are revealed. On this basis, combined with the capillary pressure theory of hydrocarbon reservoir formation, two kinds of lithology’s functional relationship of reservoir porosity with resistivity, shale content and oil column height is established through rigorous process deduction. Secondly, numerical simulation shows that: (1) Resistivity can best reflect the size of reservoir porosity, followed by shale content, and oil column height has little influence; (2) Resistivity and shale content are positively correlated with porosity while oil column height is negatively correlated with other two factors unchanged. Finally, combined with reservoir conditions in the study area, the numerical solution is correct. The numerical solution of porosity which is more in line with reservoir characteristics is determined. A method for calculating porosity based on natural gamma ray and resistivity curves is developed. Compared with the conventional three methods of mathematical statistics, the effect of porosity calculation is obviously improved. Compared with the neutron-density intersection method, the relative error is less than 8%, which proves the reliability of the method.

Key words: Porosity, Natural gamma ray, Resistivity, Digital simulation, Development wells

中图分类号: 

  • TE122.2

图1

F气田储层自然伽马、电阻率分别与岩心孔隙度关系"

图2

F气田储层孔隙度与自然伽马和电阻率（取自然对数）的二元拟合关系"

表1

研究区2种主要岩性的关于式(5)的参数统计"

岩性系数D系数E系数n
细砂岩0.286 41.190 11.59
粉砂岩0.311 61.136 31.56

图3

F气田54块样品的地层条件下储层毛管压力曲线特征"

图4

F气田储层毛管压力曲线的Sw与J函数的关系"

表2

研究区2种主要岩性的关于式(12)的参数统计"

岩性系数D系数E系数F
细砂岩0.286 41.190 1-0.607 4
粉砂岩0.311 61.136 3-0.595 9

图5

不同电阻率条件下函数F(φe)与自变量孔隙度的关系"

图7

不同气柱高度条件下函数F(φe)与自变量孔隙度的关系"

图6

不同泥质含量条件下函数F(φe)与自变量孔隙度的关系"

图8

南海F气田X井孔隙度计算效果"

表1

F气田X井孔隙度计算误差统计"

层

号

深度/m

录井

岩性

岩心分析

孔隙度/%

测井计算孔隙度/%相对误差/%
12345σ1σ2σ3σ4
13 075.4~3 077.2粉砂岩14.910.913.411.211.914.3-23.8-6.3-21.7-16.8
23 079.1~3 080.4粉砂岩18.616.114.514.015.417.6-8.5-17.6-20.5-12.5
43 081.7~3 088.0粉砂岩17.217.117.717.917.617.3-1.22.33.51.7
53 088.0~3 098.4细砂岩19.1

18.4

15.8

15.6

19.4

18.3

16.7

15.6

17.8

18.8

18.3

18.519.418.818.6-1.1-0.54.31.1
73 100.5~3 102.4细砂岩17.314.213.914.116.4-3.7-13.4-15.2-14.0
83 105.1~3 129.5细砂岩17.817.216.116.917.2-9.30.0-6.4-1.7
93 129.5~3 134.6细砂岩—17.818.318.318.17.2-1.71.11.1
103 146.4~3 148.4细砂岩—16.116.516.817.45.2-7.5-5.2-3.4
123 149.5~3 154.7细砂岩16.715.115.116.216.13.7-6.2-6.20.6
143 158.3~3 160.0细砂岩—14.013.315.016.1-3.1-13.0-17.4-6.8
163 162.2~3 173.1细砂岩16.114.014.516.116.48.5-14.6-11.6-1.8
173 173.1~3 177.3细砂岩—9.111.815.616.911.2-46.2-30.2-7.7
183 177.3~3 188.4细砂岩17.58.09.616.116.98.3-52.7-43.2-4.7
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