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物探与化探  2019, Vol. 43 Issue (4): 815-821    DOI: 10.11720/wtyht.2019.0012
     方法研究·信息处理·仪器研制 本期目录 | 过刊浏览 | 高级检索 |
地层水矿化度对补偿中子测井影响的自动校正方法研究
李鹏举1,2, 李勇勇1, 徐茂河3, 付勇路1, 田甜1
1. 东北石油大学 地球科学学院,黑龙江 大庆 163318
2. 东北石油大学 非常规油气成藏与开发省部共建国家重点实验室培育基地,黑龙江 大庆 163318
3. 中国石油大庆油田分公司第五采油厂,黑龙江 大庆 163513
A study of automatic correction method for the influence of formation water salinity on compensating neutron logging
Peng-Ju LI1,2, Yong-Yong LI1, Mao-He XU3, Yong-Lu FU1, Tian TIAN1
1. Earth Science Institute,Northeast Petroleum University,Daqing 163318,China
2. Accumulation and Development of Unconventional Oil and Gas,State Key Laboratory Cultivation Base Jointly-constructed by Heilongjiang Province and the Ministry of Science and Technology,Northeast Petroleum University,Daqing 163318,China
3. No.5 Production Plant of Daqing Oilfield Company,PetroChina,Daqing 163513,China
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摘要 

在以往补偿中子测井的蒙特卡罗模拟研究中,地层水矿化度多设置为0,但实际上地层水矿化度变化会对补偿中子测井造成影响。对此文中利用蒙特卡罗方法模拟研究了地层水矿化度对补偿中子测井的影响并提出其校正方法。先后模拟计算了不同孔隙度条件下,矿化度与计数率、计数比的关系以及矿化度对计数比与孔隙度的关系和孔隙度灵敏度的影响。结果表明,在相同孔隙度条件下,探测器计数率随矿化度增加而降低,远探测器计数率降低速率大于近探测器;近远计数比随矿化度增加呈二次函数线性增加;基于大量模拟数据,建立了适用于不同地层水矿化度条件下孔隙度与矿化度的双变量函数关系式,消除了地层水矿化度对补偿中子测井的影响。此外,孔隙度灵敏度在中、低孔隙度地层受矿化度影响明显。文中建立的孔隙度与矿化度的双变量函数关系式,完成了地层水矿化度效应的自动校正,简化了与地层水矿化度效应相关的后续校正工作,避免了复杂的仪器重新刻度,为准确评价储层孔隙度提供了理论依据。

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李鹏举
李勇勇
徐茂河
付勇路
田甜
关键词 地层水矿化度补偿中子测井计数比蒙特卡罗模拟双变量函数    
Abstract

In the previous Monte Carlo numerical simulation of compensated neutron logging, formation water salinity was mostly set at 0, but in fact, the alteration of formation water salinity would affect compensated neutron logging. In this paper, Monte Carlo method was used to simulate the influence of formation water salinity on compensated neutron logging, and its correction method was proposed. The relationship between salinity and counting rate, salinity and counting ratio, and the effect of salinity on the relationship between counting ratio and porosity and porosity sensitivity under different porosity conditions were simulated successively. According to the calculated results, under the same porosity condition, the counting rate decreases with the increase of salinity, and the counting rate of far detector decreases faster than that of near detector; the near-far counting ratio increases linearly with the increase of salinity as a quadratic function; based on a large number of simulation data, a bivariate function relationship between porosity and salinity is established for different formation water salinity conditions, which eliminates the influence of formation water salinity on compensated neutron logging. In addition, the sensitivity of porosity is obviously affected by salinity in medium and low porosity formations. The bivariate function relation between porosity and salinity established in this paper has completed the automatic correction of salinity effect, simplified the subsequent correction work related to formation water salinity effect, avoided complex instrument re-calibration, and provided a theoretical basis for accurate evaluation of reservoir porosity.

Key wordsformation water salinity    compensated neutron logging    count ratio    Monte Carlo simulation    bivariate function
收稿日期: 2019-01-07      出版日期: 2019-08-15
:  P631  
基金资助:国家科技重大专项课题“海上油田化学驱油技术”子课题“海上油田化学驱综合调整技术研究”(2016ZX05025-003-005);国家自然科学基金项目“骨架导电低阻油层人造岩样实验及导电规律与导电模型研究”(41274110);“致密砂岩储层纳微米孔隙有效下限研究”(41572132)
作者简介: 李鹏举(1970-),男,教授,博士,主要从事地球物理资料处理解释教学和研究工作。Email: 13936900420@126.com
引用本文:   
李鹏举, 李勇勇, 徐茂河, 付勇路, 田甜. 地层水矿化度对补偿中子测井影响的自动校正方法研究[J]. 物探与化探, 2019, 43(4): 815-821.
Peng-Ju LI, Yong-Yong LI, Mao-He XU, Yong-Lu FU, Tian TIAN. A study of automatic correction method for the influence of formation water salinity on compensating neutron logging. Geophysical and Geochemical Exploration, 2019, 43(4): 815-821.
链接本文:  
https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2019.0012      或      https://www.wutanyuhuatan.com/CN/Y2019/V43/I4/815
Fig.1  补偿中子测井蒙特卡罗数值模拟计算模型
Fig.2  241Am-Be中子源能谱分布
Fig.3  计数率与孔隙度的关系曲线
a—近探测器;b—远探测器
Fig.4  地层水矿化度与计数比的关系
Fig.5  近远探测器计数率比值与孔隙度关系
K
103 mg/L
R
?=5%
R
?=10%
R
?=15%
R
?=20%
R
?=25%
R
?=30%
R
?=35%
R
?=40%
2 5.5358 7.3936 9.2141 11.6282 14.1128 17.0609 18.9479 21.6945
4 5.5444 7.4277 9.2462 11.6992 14.2696 17.1051 19.0131 21.9471
6 5.5572 7.4825 9.3373 11.7815 14.3485 17.2619 19.0914 22.1562
8 5.5731 7.5638 9.3841 11.9180 14.3956 17.4312 19.2609 22.3781
10 5.5901 7.5894 9.4568 12.0523 14.5766 17.6433 19.4910 22.3431
20 5.6567 7.7037 9.7060 12.5078 14.9819 18.0859 20.3406 22.7827
40 5.8027 8.0302 10.1818 13.3278 15.9587 19.0758 21.2311 23.7184
60 5.8788 8.2548 10.6310 14.0790 16.5734 19.9398 22.2737 24.8705
80 5.9763 8.5090 10.9372 14.5618 17.0692 20.9989 23.0968 25.8535
100 6.0386 8.7159 11.3617 14.8231 17.7682 21.5449 23.8259 26.0628
120 6.2177 8.9431 11.8504 15.3939 18.1720 21.3842 24.1710 26.2046
140 6.3345 9.1501 12.1744 15.8193 18.4743 22.1051 23.8934 26.5727
160 6.4960 9.3850 12.5665 16.2511 18.8303 22.3568 24.3982 26.9084
180 6.6368 9.5602 12.7814 16.7247 19.1785 21.9225 24.2472 26.7856
200 6.7386 9.8133 12.9987 16.7941 19.3919 22.4329 24.9869 27.5232
Table 1  不同矿化度、孔隙度地层的近远探测器计数率比值
Fig.6  视孔隙度与真孔隙度对比
a—式(1)计算的视孔隙度与真孔隙度;b—式(2)计算的视孔隙度与真孔隙度
Fig.7  式(2)的孔隙度与灵敏度及相对灵敏度的关系
a—灵敏度;b—相对灵敏度
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