基于煤岩脆性指数的煤体结构测井定量判识

doi:10.3969/j.issn.1673-8926.2017.02.017

岩性油气藏 ›› 2017, Vol. 29 ›› Issue (2): 139–144.doi: 10.3969/j.issn.1673-8926.2017.02.017

基于煤岩脆性指数的煤体结构测井定量判识

艾林^1,2, 周明顺³, 张杰⁴, 梁霄^1,2, 钱博文^1,2, 刘迪仁^1,2

1. 油气资源与勘探技术教育部重点实验室(长江大学), 武汉 430100;
2. 长江大学非常规油气湖北省协同创新中心, 武汉 430100;
3. 中国石油华北油田分公司勘探开发研究院, 河北任丘 062552;
4. 中国石油华北油田分公司地球物理勘探研究院, 河北任丘 062552

收稿日期:2016-08-29 修回日期:2016-10-19 出版日期:2017-03-21 发布日期:2017-03-21
通讯作者: 刘迪仁(1965-),男,博士,教授,主要从事测井正反演及复杂储层测井评价等方面的教学和科研工作。Email:liudr666@163.com。
作者简介:艾林(1990-),男,长江大学在读硕士研究生,研究方向为测井方法原理和煤层气测井评价。地址:(430100)湖北省武汉市蔡甸区大学路111号长江大学武汉校区。Email:1393737530@qq.com
基金资助:
国家自然科学基金项目“地层条件下富有机质页岩电磁响应机理与应用基础研究”（编号：U1562109）资助

Quantitative identification of coal structure based on coal rock brittleness index by logging data

AI Lin^1,2, ZHOU Mingshun³, ZHANG Jie⁴, LIANG Xiao^1,2, QIAN Bowen^1,2, LIU Diren^1,2

1. Key Laboratory of Exploration Technologies for Oil and Gas Resources, Ministry of Education, Yangtze University, Wuhan 430100, China;
2. Hubei Cooperative Innovation Center of Unconventional Oil and Gas, Yangtze University, Wuhan 430100, China;
3. Research Institute of Exploration and Development, PetroChina Huabei Oilfield Company, Renqiu 062552, Hebei, China;
4. Research Institute of Geophysical Exploration, PetroChina Huabei Oilfield Company, Renqiu 062552, Hebei, China

Received:2016-08-29 Revised:2016-10-19 Online:2017-03-21 Published:2017-03-21

摘要/Abstract

摘要： 准确判识煤体结构是煤层气勘探开发研究的一个关键问题，不同煤体结构类型的煤层，因孔隙大小、裂隙网络和破碎程度不同，对煤层气富集和运移的影响也不相同。根据煤体的破碎程度，将沁水盆地F 区块3# 煤层煤体结构类型划分为原生结构、过渡结构和碎裂结构，并分析了不同煤体结构的测井响应特征。统计表明：随着煤体破碎程度增加，测井曲线上通常表现为密度与电阻率均降低、井径扩大、声波时差增大。在测井资料定性划分煤体结构的基础上，提出利用阵列声波测井资料计算煤岩脆性指数来定量判识煤体结构。通过实际应用认为，用煤岩脆性指数定量判识煤体结构是可行的，判识结果与实际钻井取心资料符合率较高，能够提高煤体结构研究的精度。

Abstract: An accurate identification of coal structure is one of key issues in coalbed methane(CBM)exploration and development. Different coal structure have different influences on the migration and enrichment of coalbed methane. According to the coal broken degree,the coal structure of No.3 coal bed was divided into primary structure, transition structure and cataclastic structure in F block of Qinshui Basin,and the characteristics of their logging response were analyzed. The results show that the logging curve is usually characterized with lower density and resistivity,and higher borehole diameter and acoustic time as the coal broken degree increases. Based on the qualitative identifying of coal structure by logging data,array acoustic logging data was used to calculate the coal rock brittleness index(BI)quantitatively. The application results show that it is feasible to identify coal structure quantitatively by the coal rock brittleness index,the identification result is consistent with the actual drilling coring data,and it can greatly reduce the error of the qualitative identification.

中图分类号:

P631

艾林, 周明顺, 张杰, 梁霄, 钱博文, 刘迪仁. 基于煤岩脆性指数的煤体结构测井定量判识[J]. 岩性油气藏, 2017, 29(2): 139–144.

AI Lin, ZHOU Mingshun, ZHANG Jie, LIANG Xiao, QIAN Bowen, LIU Diren. Quantitative identification of coal structure based on coal rock brittleness index by logging data[J]. Lithologic Reservoirs, 2017, 29(2): 139–144.

参考文献

[1] 范俊佳,琚宜文,柳少波,等. 不同煤储层条件下煤岩微孔结构及其对煤层气开发的启示. 煤炭学报,2013,38(3):441-447 ． FAN J J,JU Y W,LIU S B,et al. Micropore structure of coals under different reservoir conditions and its implication for coalbed methane development. Journal of China Coal Society, 2013,38(3):441-447 ．
[2] 降文萍,张群,姜在炳,等. 构造煤孔隙结构对煤层气产气特征的影响. 天然气地球科学,2016,27(1):173-179 ． JIANG W P,ZHANG Q,JIANG Z B,et al. Effect on CBM drainage characteristics of pore structure of tectonic coal. Natural Gas Geoscience,2016,27(1):173-179 ．
[3] LI J Q,LIU D M,YAO Y B,et al. Evaluation of the reservoir permeability of anthracite coals by geophysical logging data. International Journal of Coal Geology,2011,87(2):121-127 ．
[4] 康园园,邵先杰,石磊,等. 煤层气开发目标区精选体系与方法研究. 岩性油气藏,2011,23(1):62-66 ． KANGYY,SHAO X J,SHI L,et al. Study on system and method of ranking coalbed methane development perspectives. Lithologic Reservoirs,2011,23(1):62-66 ．
[5] 胡奇,王生维,张晨,等. 沁南地区煤体结构对煤层气开发的影响. 煤炭科学技术,2014,42(8):65-68 ． HU Q,WANG S W,ZHANG C,et al. Coal structure affected to coalbed methane development in Qinnan region. Coal Science and Technology,2014,42(8):65-68 ．
[6] DASHTIAN H,JAFARI G R,SAHIMI M,et al. Scaling,multifractality, and long-range correlations in well log data of largescale porous media. Physica A:Statistical Mechanics and its Applications,2011,390:2096-2111．
[7] 姚军朋,司马立强,张玉贵. 构造煤地球物理测井定量判识研究. 煤炭学报,2011,36(增刊1):94-98 ． YAO J P,SIMA L Q,ZHANG Y G. Quantitative identification of deformed coals by geophysical logging. Journal of China Coal Society,2011,36(Suppl 1):94-98 ．
[8] 陈跃,汤达祯,许浩,等. 基于测井信息的韩城地区煤体结构的分布规律. 煤炭学报,2013,38(8):1435-1442 ． CHEN Y,TANG D Z,XU H,et al. The distribution of coal structure in Hancheng based on well logging data. Journal of China Coal Society,2013,38(8):1435-1442．
[9] 张坤鹏,姜波,李明,等. 新景煤矿3 号煤层煤体结构测井曲线判识及其分布规律. 煤田地质与勘探,2016,44(1):123-127 ． ZHANG K P,JIANG B,LI M,et al. Identification and distribution of structure of seam No.3 in Xinjing Mine on the basis of well logs. Coal Geology & Exploration,2016,44(1):123-127 ．
[10] 孟召平,刘珊珊,王保玉,等. 晋城矿区煤体结构及其测井响应特征研究. 煤炭科学技术,2015,43(2):58-63 ． MENG Z P,LIU S S,WANG B Y,et al. Study on feature of coal body structure and logging response in Jincheng mining area. Coal Science & Technology,2015,43(2):58-63 ．
[11] CHEN Q,YAO H F,CHANG S L,et al. Coalbody structure classification method based on dual-lateral and RXO crossplot analysis. Journal of Coal Science and Engineering,2013,19 (4):522-529 ．
[12] 李伟,要慧芳,刘鸿福,等. 基于显微CT 的不同煤体结构煤三维孔隙精细表征. 煤炭学报,2014,39(6):1127-1132 ． LI W,YAO H F,LIU H F,et al. Advanced characterization of three-dimensional pores in coals with different coal-body structure by micro-CT. Journal of China Coal Society,2014,39(6): 1127-1132 ．
[13] 闫霞,李小军,赵辉,等. 煤层气井井间干扰研究及应用. 岩性油气藏,2015,27(2):126-132 ． YAN X,LI X J,ZHAO H,et al. Research on well interference of coalbed methane wells and its application. Lithologic Reservoirs, 2015,27(2):126-132 ．
[14] 刘之的,王剑,杨秀春,等. 密度测井扩径影响校正方法在煤层气储层中的适用性分析. 地球物理学进展,2014,29(5): 2219-2223 ． LIU Z D,WANG J,YANG X C,et al. Analyzing on applicability of expanding influence correction method of density logging in the coalbed methane reservoir. Progress in Geophysics, 2014,29(5):2219-2223 ．
[15] 许启鲁,黄文辉,杨延绘,等. 构造煤的测井曲线判识——以柿庄北区块为例. 科学技术与工程,2016,16(3):11-16 ． XU Q L,HUANG W H,YANG Y H,et al. Analysis of identifying deformed coal by logging curve in Shizhuang north block, Qinshui Basin,China. Science Technology and Engineering, 2016,16(3):11-16 ．
[16] 赵毅,毛志强,孙伟,等. 煤层气储层非常规测井资料评价方法研究. 测井技术,2011,35(5):441-446 ． ZHAO Y,MAO Z Q,SUN W,et al. Evaluation method for unconventional log data of CBM reservoir. Well Logging Technology, 2011,35(5):441-446 ．
[17] 刘鹏,乔文孝,车小花,等. 多极子阵列声波测井技术在煤层气储层评价中的应用. 测井技术,2014,38(3):292-296 ． LIU P,QIAO W X,CHE X H,et al. Application of multipole acoustic logging to the evaluation of coalbed methane reservoirs. Well Logging Technology,2014,38(3):292-296 ．
[18] 王赟,许小凯,张玉贵. 六种不同变质程度煤的纵横波速度特征及其与密度的关系. 地球物理学报,2012,55(11):3754-3761 ． WANG Y,XU X K,ZHANG Y G. Characteristics of P-wave and S-wave velocities and their relationships with density of six metamorphic kinds of coals. Chinese Journal of Geophysics, 2012,55(11):3754-3761 ．
[19] 冯昕鹏,李金付,聂建委,等. 横波速度拟合技术在苏里格气田的应用. 岩性油气藏,2012,24(6):106-109 ． FENG X P,LI J F,NIE J W,et al. Application of shear wave velocity fitting technology in Sulige Gas Field. Lithologic Res ervoirs,2012,24(6):106-109 ．
[20] 王成龙,夏宏泉,杨双定. 基于岩石脆性系数的压裂缝高度与宽度预测方法研究. 测井技术,2013,37(6):676-680 ． WANG C L,XIA H Q,YANG S D. On fracture height and width prediction method based rock brittleness coefficient. Well Logging Technology,2013,37(6):676-680 ．
[21] 李华阳,周灿灿,李长喜,等. 致密砂岩脆性指数测井评价方法——以鄂尔多斯盆地陇东地区长7 段致密砂岩储集层为例. 新疆石油地质,2014,35(5):593-597. LI H Y,ZHOU C C,LI C X,et al. Logging evaluation and application of brittleness index in tight sandstone reservoir—A case study of Chang-7 tight sandstone reservoir in Longdong area of Ordos Basin. Xinjiang Petroleum Geology,2014,35(5): 593-597.
[22] JARVIE D M,HILL R J,RUBLE T E,et al. Uncoventional shale-gas systems:the Mississippian Barnett shale on Northcentral Texas as one model for thermogenic shale-gas assessment. APPG Bulletin,2007,91(4):475-499 ．
[23] RICKMAN R,MULLEN M,PETRE E,et al. A practical use of shale petrophysics for stimulation design optimization:all shale plays are not clones of the Barnett shale. SPE 115258,2008: 1-11 ．
[24] GRIESER B,BRAY J. Identification of production potential in unconventional reservoirs. SPE 106623,2007:1-6 ．

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

基于煤岩脆性指数的煤体结构测井定量判识

Quantitative identification of coal structure based on coal rock brittleness index by logging data

PDF (PC)

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 10

[1]	赵岩, 毛宁波, 陈旭. 基于时频域信噪比的自适应增益限反Q滤波方法[J]. 岩性油气藏, 2021, 33(4): 85-92.
[2]	孟会杰, 苏勤, 曾华会, 徐兴荣, 刘桓, 张小美. 基于独立分量分析的地震信号盲源分离及应用[J]. 岩性油气藏, 2021, 33(4): 93-100.
[3]	马乔雨, 张欣, 张春雷, 周恒, 武中原. 基于一维卷积神经网络的横波速度预测[J]. 岩性油气藏, 2021, 33(4): 111-120.
[4]	谷志猛, 明君, 刘传奇, 王腾. 基于多元线性回归的地层平均速度分析及应用——以渤海A油田为例[J]. 岩性油气藏, 2021, 33(4): 121-127.
[5]	孙夕平, 张昕, 李璇, 韩永科, 王春明, 魏军, 胡英, 徐光成, 张明, 戴晓峰. 基于叠前深度偏移的基岩潜山风化淋滤带储层预测[J]. 岩性油气藏, 2021, 33(1): 220-228.
[6]	姚军, 乐幸福, 陈娟, 苏旺, 张永峰. 基于拟三维多属性反演的优质烃源岩分布预测[J]. 岩性油气藏, 2021, 33(1): 248-257.
[7]	张艳, 高世臣, 孟婉莹, 成育红, 蒋思思. 致密砂岩储层AVO正演模拟过程中的不确定性分析[J]. 岩性油气藏, 2020, 32(6): 120-128.
[8]	张鹏, 杨巧云, 范宜仁, 张云, 张海涛. 基于Xu-White模型的致密砂岩储层含气性评价[J]. 岩性油气藏, 2020, 32(6): 138-145.
[9]	刘博, 徐刚, 纪拥军, 魏路路, 梁雪莉, 何金玉. 页岩油水平井体积压裂及微地震监测技术实践[J]. 岩性油气藏, 2020, 32(6): 172-180.
[10]	王建君, 李井亮, 李林, 马光春, 杜悦, 姜逸明, 刘晓, 于银华. 基于叠后地震数据的裂缝预测与建模——以太阳—大寨地区浅层页岩气储层为例[J]. 岩性油气藏, 2020, 32(5): 122-132.
[11]	刘梦丽, 徐兴荣, 王小卫, 胡书华, 刘金涛. 预条件弹性介质最小二乘逆时偏移[J]. 岩性油气藏, 2020, 32(5): 133-142.
[12]	戴晓峰, 谢占安, 杜本强, 张明, 唐廷科, 李军, 牟川. 高石梯—磨溪地区灯影组多次波控制因素及预测方法[J]. 岩性油气藏, 2020, 32(4): 89-97.
[13]	何健, 武刚, 聂文亮, 刘松鸣, 黄伟. 基于近似支持向量机的裂缝分类方法[J]. 岩性油气藏, 2020, 32(2): 115-121.
[14]	宋宣毅, 刘月田, 马晶, 王俊强, 孔祥明, 任兴南. 基于灰狼算法优化的支持向量机产能预测[J]. 岩性油气藏, 2020, 32(2): 134-140.
[15]	刁瑞. 地震数据提高分辨率处理监控评价技术[J]. 岩性油气藏, 2020, 32(1): 94-101.