基于页岩岩石物理分析技术的TOC和脆性预测

doi:10.13810/j.cnki.issn.1000-7210.2018.S2.031

摘要
图/表
参考文献
相关文章 (15)

全文: PDF (8825 KB) HTML []
输出: BibTeX | EndNote (RIS)

摘要页岩储层甜点评价需要综合利用岩心、测井、岩石物理、地震等各方面的资料，运用页岩岩石物理分析技术，结合叠前弹性参数地震反演结果，形成一套页岩气储层有机碳含量（TOC）预测和页岩气储层脆性预测的技术。为此，文中着重阐述了页岩储层岩石物理分析的三大方面：井曲线校正和反演预测技术、岩石物理扰动分析技术以及有利弹性参数交会分析技术。将该技术应用于中国南方海相页岩气储层甜点预测项目，结果表明该技术适用于该海相页岩气区块，对其他类似地区具有一定的借鉴意义。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	李远
	程飞
	雷栋
	夏存银
	胡超俊
	柯沛

关键词 ：页岩气, TOC, 岩石物理, 脆性, 测井分析

Abstract：The shale gas evaluation needs core,logging,rock physics,and seismic data for comprehensive analysis.Based on core,well logging,rock physics data and,combined with seismic prestack inversion results,an approach to predict the distribution of total organic carbon (TOC) and brittleness in shale gas reservoirs is developed.This paper mainly expounds three aspects of shale rock physical analysis:well curve correction and inversion prediction,rock physical disturbance analysis,and favorable elastic parameter crossplot analysis.These techniques have been applied to predict shale gas reservoirs in the shale gas exploration in South China Sea.The results show that the proposed approach is applicable to the marine facies shale gas exploration in the area,which provides a meaningful reference.

Key words： shale gas total organic carbon (TOC) rock physics brittleness logging data analysis

收稿日期: 2018-07-18

PACS:

P631

基金资助:本项研究受国家科技重大专项“走滑高原山地页岩气三维地震一体化勘探技术及应用”（2017ZX05063-001-001）和“非常规油气关键技术与集成”（2017ZX05018-004-004）联合资助。

通讯作者: 李远,河北省涿州市甲秀路39号科技楼A座东方地球物理公司新兴物探开发处,072750。Email:liyuan9@cnpc.com.cn E-mail: liyuan9@cnpc.com.cn

作者简介: 李远,工程师,1987年生;2011年毕业于中国石油大学(华东)地球物理学专业,获学士学位;2014年毕业于中国石油大学(华东)固体地球物理学专业,获硕士学位;现在东方地球物理公司新兴物探开发处开发地震研究所从事页岩气岩石物理分析与叠前地震反演。

引用本文:

李远, 程飞, 雷栋, 夏存银, 胡超俊, 柯沛. 基于页岩岩石物理分析技术的TOC和脆性预测[J]. 石油地球物理勘探, 2018, 53(s2): 204-210. LI Yuan, CHENG Fei, LEI Dong, XIA Cunyin, HU Chaojun, KE Pei. TOC and brittleness prediction based on shale rock physical analysis. Oil Geophysical Prospecting, 2018, 53(s2): 204-210.

链接本文:

http://www.ogp-cn.com/CN/10.13810/j.cnki.issn.1000-7210.2018.S2.031 或 http://www.ogp-cn.com/CN/Y2018/V53/Is2/204

[1]	Rickman R,Mike 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[C].SPE Annual Technical Conference and Exhibition,SPE,2008,46:2152-2168.
[2]	Roderick P,Marfurt K.Brittleness estimation from seismic measurements in unconventional reservoirs:Application to the Barnett Shale[C].SEG Technical Program Expanded Abstracts,2013,31:2258-2263.
[3]	Hart B,Sayers C,Jackson A,et al.Introduction to this special section:Shale[J].The Leading Edge,2011,30(3):272-340.
[4]	Ersoy A,Waller M D.Textural characterization of rocks[J].Engineeriong Geology,1995,39(3):123-136.
[5]	Jarvie D M,Hill R J,et al.Unconventional shale-gas Systems:the shale-gas assessment[J].AAPG Bulletin,2007,91(4):475-499.
[6]	李金磊,尹正武.四川盆地焦石坝地区页岩气储层地震定量预测方法[J].石油物探,2015,54(3):324-330.LI Jinlei,YIN Zhengwu.Seismic quantitative prediction method of shale gas reservoirs in the Jiaoshiba Area,Sichuan Basin[J].Geophysical Prospecting for Petroleum,2015,54(3):324-330.
[7]	王明飞,陈超,屈大鹏,等.涪陵页岩气田焦石坝区块五峰组-龙马溪组一段页岩气储层地球物理特征分析[J].石油物探,2015,54(5):613-620.WANG Mingfei,CHEN Chao,QU Dapeng,et al.The geophysical characteristics of shale gas reservoir from Wufeng member to Longmaxi member in Jiaoshiba block of Fulin shale gasfield[J].Geophysical Prospecting for Petroleum,2015,54(5):613-620.
[8]	刘勇,方伍宝,李振春,等.基于叠前地震的脆性预测方法及应用研究[J].石油物探,2016,55(3):425-432.LIU Yong,FANG Wubao,LI Zhenchun,et al.Brittleness prediction and application based on pre-stack seismic inversion[J].Geophysical Prospecting for Petroleum,2016,55(3):425-432.
[9]	董宁,许杰,孙赞东,等.泥页岩脆性地球物理预测技术[J].石油地球物理勘探,2013,48(1):69-74.DONG Ning,XU Jie,SUN Zandong,et al.Geophysical prediction of shale/clay brittleness[J].Oil Geophysical Prospecting,2013,48(1):69-74.
[10]	王鹏,纪友亮,潘仁芳,等.页岩脆性的综合评价[J].天然气工业,2013,33(12):48-53.WANG Peng,JI Youliang,PANG Renfang,et al.A comprehensive evaluation method of shale brittleness[J].Natural Gas Industry,2013,33(12):48-53.
[11]	周鹏,张益明,刘志斌,等.地震道集优化方法及应用[J].石油地球物理勘探,2016,51(2):232-237.ZHOU Peng,ZHANG Yiming,LIU Zhibin,et al.Seismic gather optimization[J].Oil Geophysical Prospecting,2016,51(2):232-237.
[12]	Yapping Z,Enur L,Alex M,et al.Understanding geophysical responses of shale-gas plays[J].The Leading Edge,2011,30(3):332-338.
[13]	张广智,郑静静,王玉梅,等.基于入射角的AVO近似及属性提取[J].石油地球物理勘探,2012,47(4):578-583.ZHANG Guangzhi,ZHENG Jingjing,WANG Yumei,et al.AVO approximation and attribute extraction based on the incident angle[J].Oil Geophysical Prospecting,2012,47(4):578-583.
[14]	刘伟,张宇生,万小平,等.四川盆地龙马溪组页岩气储层AVO预测可行性研究[J].石油地球物理勘探,2014,49(增刊1):5-10.LIU Wei,ZHANG Yusheng,WAN Xiaoping,et al.Feasibility study for shale gas reservoir prediction with AVO in Sichuan Basin[J].Oil Geophysical Prospecting,2014,49(S1):5-10.
[15]	Amie M,Lucifer D,Ronny H,et al.Evaluation of va-riables gas saturation on acoustic log data from the Haynesville Shale gas play[J].The Leading Edge,2011,30(3):300-311.
[16]	李建华,刘百红,张延庆,等.叠前AVO反演在储层含油气性预测中的应用[J].石油地球物理勘探,2016,51(6):1180-1186.LI Jianhua,LIU Baihong,ZHANG Yanqing,et al.Oil-bearing reservoir prediction with prestack AVO inversion[J].Oil Geophysical Prospecting,2016,51(6):1180-1186.
[17]	王建,石万忠,舒志国,等.富有机质页岩TOC含量的地球物理定量化预测[J].石油地球物理勘探,2016,51(3):596-604.WANG Jian,SHI Wanzhong,SHU Zhiguo,et al.TOC content quantitative prediction in organic-rich shale[J].Oil Geophysical Prospecting,2016,51(3):596-604.
[18]	Hartman R C,Lasswell P,Bhatta N.Recent advances in the analytical methods used for shale gas reservoir gas in place assessment[J].AAPG Bulletin,2008,92(1):302-312.
[19]	Tavella J,Moirano J,Carrero Z,et al.Integrated Characterization of unconventional Upper Jurassic reservoir in Northern Mexico[C].Extended Abstracts of 75th EAGE Conference & Exhibition,2013,10-13.
[20]	梁兴,王高成,徐政语,等.中国南方海相复杂山地页岩气储层甜点综合评价技术——以昭通国家级页岩气示范区为例[J].天然气工业,2016,36(1):33-42.LIANG Xing,WANG Gaocheng,XU Zhengyu,et al.Comprehensive evaluation technology for shale gas sweet spots in the complex marine mountains,South China:A case study from Zhaotong national shale gas demonstration zone[J].Natural Gas Industry,2016,36(1):33-42.