岩性油气藏 ›› 2019, Vol. 31 ›› Issue (6): 95–101.doi: 10.12108/yxyqc.20190610

• 勘探技术 • 上一篇    下一篇

一套针对高泥质疏松砂岩薄储层的识别技术——以珠江口盆地X油田为例

罗泽, 谢明英, 涂志勇, 卫喜辉, 陈一鸣   

  1. 中海石油(中国)有限公司深圳分公司 研究院, 广东 深圳 518000
  • 收稿日期:2019-05-20 修回日期:2019-08-20 出版日期:2019-11-21 发布日期:2019-09-28
  • 作者简介:罗泽(1985-),男,硕士,工程师,主要从事地震地质综合解释及储层预测等研究工作。地址:(518000)广东省深圳市南山区后海滨路(深圳湾段)3168号中海油大厦。Email:luoze@cnooc.com.cn。
  • 基金资助:
    中海石油（中国）有限公司综合科研项目"恩平18区疏松砂岩稠油油藏有效开发技术"（编号：YXKY-2019-SZ-01）资助

A set of recognition techniques for thin reservoirs with unconsolidated high-argillaceous sandstone: a case study from X oilfield in Pearl River Mouth Basin

LUO Ze, XIE Mingying, TU Zhiyong, WEI Xihui, CHEN Yiming   

  1. Research Institute, Shenzhen Branch of CNOOC Ltd., Shenzhen 518000, Guangdong, China
  • Received:2019-05-20 Revised:2019-08-20 Online:2019-11-21 Published:2019-09-28

PDF (PC)

314

摘要： 针对珠江口盆地X油田韩江组高泥质疏松砂岩段扩径严重引起测井曲线质量差、波阻抗属性叠置严重、储层薄且非均质性强等难题，形成的薄储层精细表征技术概括为"三步法"：①遗传化神经网络技术重构能得到反映真实地层特征的弹性曲线，进而解决在疏松砂岩井段因扩径严重导致测井曲线失真的问题；②针对高泥质疏松砂岩薄储层识别难的问题，新构建DVT敏感特征参数来区分砂岩与泥岩；③利用波形指示高分辨率反演方法预测高泥质疏松薄砂岩储层的空间展布。实际应用表明：该技术在X油田注水收效、调整井优化实施和开发调整方案井网设计等方面取得了较好的应用效果，解决了该油田3~5 m薄层精确描述的难题，形成了一套完整的针对高泥质疏松砂岩薄储层预测的技术流程。该技术对同类油藏表征和油田高效开发具有参考意义。

关键词: 高泥质疏松砂岩, 神经网络, 波形指示反演, 薄储层预测, 韩江组, 珠江口盆地

Abstract: Aiming at the problems of poor quality of logging curves,serious overlapping of wave impedance attributes,thin reservoir and strong heterogeneity caused by serious expansion of unconsolidated high-argillaceous sandstone of Hanjiang Formation in X oilfield,Pearl River Mouth Basin,a fine characterization technology for thin reservoir was formed,which is summarized as "three-step method".(1)The elastic curve reflecting real formation characteristics can be obtained by reconstructing logging curves with genetic neural network technology,and then the problem of poor quality of logging curves caused by the serious expansion of unconsolidated sandstone can be solved.(2)A new sensitive characteristic parameter DVT for the identification of thin reservoirs with unconsolidated high-argillaceous sandstone was constructed to distinguish sandstone from mudstone.(3)High resolution inversion method with waveform indication was used to predict the spatial distribution of thin reservoirs with unconsolidated high-argillaceous sandstone. Practical application shows that this technology achieved good application results in water injection efficiency,optimization implementation of adjustment wells and well pattern design of development adjustment scheme in X oilfield. A complete set of technical process has been formed for the prediction of thin reservoir with unconsolidated high-argillaceous sandstone,which solves the difficulty of accurate description of 3-5 m thin reservoir in the oilfield. This technology has reference significance for the characterization of similar reservoirs and the efficient development of oilfields.

Key words: unconsolidated high-argillaceous sandstone, neural network, waveform indication inversion, thin reservoir prediction, Hanjiang Formation, Pearl River Mouth Basin

中图分类号: 

  • TE122.2
[1] 陈长民,施和生,许仕策,等.珠江口盆地(东部)第三系油气藏形成条件.北京:科学出版社,2003. CHEN C M,SHI H S,XU S C,et al. Formation conditions of Tertiary oil and gas reservoirs in the Pearl River Mouth Basin (Eastern Part). Beijing:Science Press,2003.
[2] 李文红,李英蕾,雷霄,等.南海西部油田高泥质疏松砂岩储层数字岩心渗流特征.中国海上油气,2015,27(4):86-92. LI W H,LI Y L,LEI X,et al. Digital core percolation characteristics of loose sandstone reservoir with high mud content in western South China Sea. China Offshore Oil and Gas,2015,27(4):86-92.
[3] 韩长城,林承焰,任丽华,等.地震波形指示反演在东营凹陷王家岗地区沙四上亚段滩坝砂的应用. 中国石油大学学报(自然科学版),2017,41(2):60-69. HAN C C,LIN C Y,REN L H,et al. Application of seismic waveform inversion in Es 4 sbeach-bar sandstone in Wangjiagang area,Dongying Depression. Journal of China University of Petroleum(Edition of Natural Sciences),2017,41(2):60-69.
[4] 李雪英,李东庆,白诗缘.薄层研究方法综述.地球物理学进展,2017,29(5):2197-2203. LI X Y,LI D Q,BAI S Y. Review of thin layer studies. Progress in Geophysics,2017,29(5):2197-2203.
[5] 杨占龙,肖冬生,周隶华,等.高分辨率层序格架下的陆相湖盆精细沉积体系研究:以吐哈盆地西缘侏罗系-古近系为例. 岩性油气藏,2017,29(5):1-10. YANG Z L,XIAO D S,ZHOU L H,et al. Depositional system of lacustrine basins within high-resolution sequence framework:a case of Jurassic to Paleogene in western Turpan-Kumul Basin. Lithologic Reservoirs,2017,29(5):1-10.
[6] 石战战,王元君,唐湘蓉,等.一种基于时频域波形分类的储层预测方法.岩性油气藏,2018,30(4):98-104. SHI Z Z,WANG Y J,TANG X R,et al. Reservoir prediction based on seismic waveform classification in time-frequency domain. Lithologic Reservoirs,2018,30(4):98-104.
[7] 杨希濮,杨小丽,刘钧,等.一体化储层精细分类方法在非均质储层定量表征中的应用.岩性油气藏,2017,29(1):124-129. YANG X P,YANG X L,LIU J,et al. Application of integrated reservoir classification method to the quantitative characterization of heterogeneity reservoir. Lithologic Reservoirs,2017,29(1):124-129.
[8] 孙思敏,彭仕宓.地质统计学反演方法及其在薄层砂体预测中的应用.西安石油大学学报(自然科学版),2007,22(1):41-48. SUN S M,PENG S M. Geostatistical inversion method and its application in the prediction of thin reservoirs. Journal of Xi'an Shiyou University(Natural Science Edition),2007,22(1):41-48.
[9] 盛述超,毕建军,李维,等.关于地震波形指示反演(SMI)方法的研究.内蒙古石油化工,2015,21(17):147-151. SHENG S C,BI J J,LI W,et al. Research on the method of seismic waveform indication simulation inversion(SMI). Inner Mongolia Petrochemical Industry,2015,21(17):147-151.
[10] 潘光超,周家雄,韩光明,等.中深层"甜点"储层地震预测方法探讨:以珠江口盆地西部文昌A凹陷为例. 岩性油气藏, 2016,28(1):94-100. PAN G C,ZHOU J X,HAN G M,et al. Seismic prediction method of "sweet" reservoir in middle-deep zone:a case study from Wenchang A sag,western Pearl River Mouth Basin. Lithologic Reservoirs,2016,28(1):94-100.
[11] 冉令.一种基于地震波形指示的反演方法研究. 中国石油大学胜利学院学报,2016,30(3):3-5. RAN L. A research on inversion method based on seismic waveform instruction. Journal of Shengli College China University of Petroleum,2016,30(3):3-5.
[12] HAAS A,DUBRULE O. Geostatistical inversion:a sequential method for stochastic reservoir modeling constrained by seismic data. First Break,1994,13(12):561-569.
[13] DUBRULE O,THIBAUT M,LAMY P,et al. Geostatistical reservoir characterization constrained by 3D seismic data. Petroleum Science,1998,43(4):121-128.
[14] ROTHMAN D H. Geostatistical inversion of 3 D seismic data for thin-sand delineation. Geophysics,1998,51(2):332-346.
[15] 杜伟维,金兆军,邸永香.地震波形指示反演及特征参数模拟在薄储层预测中的应用. 工程地球物理学报,2017,14(1):56-61. DU W W,JIN Z J,DI Y X. The application of seismic waveform indicator inversion and characteristic parameter simulation to thin reservoir prediction. Chinese Journal of Engineering Geophysics,2017,14(1):56-61.
[16] 张亚斌,瞿亦斌,陈忠云.神经网络技术在测井曲线重构中的应用.石油天然气学报,2011,33(3):89-94. ZHANG Y B,QU Y B,CHEN Z Y. Application of neural network technology in reconstructing logging curves. Journal of Oil and Gas Technology,2011,33(3):89-94.
[17] 刘化清,苏明军,倪长宽,等.薄砂体预测的地震沉积学研究方法.岩性油气藏,2018,30(2):1-11. LIU H Q,SU M J,NI C K,et al. Thin bed prediction from interbeded background:Revised seismic sedimentological method. Lithologic Reservoirs,2018,30(2):1-11.
[18] 杨志力,周路,彭文利,等.BP神经网络技术在声波测井曲线重构中的运用. 西南石油大学学报(自然科学版),2008,30(1):63-66. YANG Z L,ZHOU L,PENG W L,et al. Application of BP neural-network technology in sonic log data rebuilding. Journal of Southwest Petroleum University(Science & Technology Edition), 2008,30(1):63-66.
[19] 张永军,程超,梁涛,等.基于BP神经网络的测井曲线构建. 西部探矿工程,2006,18(2):82-85. ZHANG Y J,CHENG C,LIANG T,et al. Logging curve construction based on BP neural network. West-China Exploration Engineering,2006,18(2):82-85.
[20] 杨涛,乐友喜,吴勇.波形指示反演在储层预测中的应用.地球物理学进展,2018,33(2):769-776. YANG T,YUE Y X,WU Y. Application of the waveform inversion in reservoir prediction. Progress in Geophysics,2018,33(2):769-776.
[21] 梁杰,陈维涛,罗明,等.地震波形指示反演在珠江口盆地A油田薄层预测中的应用.物探化探计算技术,2019,41(3):1-7. LIANG J,CHEN W T,LUO M,et al. Application of seismic motion inversion in thin layer prediction of A oilfield in Pearl River Mouth Basin. Geophysical and Geochemical Exploration Computing Technology,2019,41(3):1-7.
[22] 王贤,唐建华,毕建军,等.地震波形指示反演在石南地区薄储层预测中的应用.新疆石油天然气,2017,13(3):1-5. WANG X,TANG J H,BI J J,et al. Application of seismic waveform inversion in Shinan area. Xinjiang Oil and Gas,2017,13(3):1-5.
[23] 李金磊,陈祖庆,王良军,等.相控技术在低勘探区生屑滩相储层预测中的应用.岩性油气藏,2017,29(3):110-117. LI J L,CHEN Z Q,WANG L J,et al. Application of facies-controlled technique to bioclastic shoal reservoir prediction in less well zones. Lithologic Reservoirs,2017,29(3):110-117.
[24] 彭真明,张启衡,龚奇,等.波阻抗反演中的全局寻优策略.物探化探计算技术,2003,25(2):151-156. PENG Z M,ZHANG Q H,GONG Q,et al. A global optimization strategy for impedance inversion. Geophysical and Geochemical Exploration Computing Technology,2003,25(2):151-156.
[25] 乔中林,杜立筠.约束稀疏脉冲波阻抗正反演参数研究.海洋地质前沿,2016,32(8):52-57. QIAO Z L,DU L J. Research on impedance forward and inversion parameters of constrained spares spike method. Marine Geology Frontier,2016,32(8):52-57.
[1] 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.
[2] 赵军, 韩东, 何胜林, 汤翟, 张涛. 基于水气比计算的低对比度储层流体性质识别[J]. 岩性油气藏, 2021, 33(4): 128-136.
[3] 武中原, 张欣, 张春雷, 王海英. 基于LSTM循环神经网络的岩性识别方法[J]. 岩性油气藏, 2021, 33(3): 120-128.
[4] 向巧维, 李小平, 丁琳, 杜家元. 珠江口盆地珠一坳陷古近系高自然伽马砂岩形成机制及油气地质意义[J]. 岩性油气藏, 2021, 33(2): 93-103.
[5] 曹思佳, 孙增玖, 党虎强, 曹帅, 刘冬民, 胡少华. 致密油薄砂体储层预测技术及应用实效——以松辽盆地敖南区块下白垩统泉头组为例[J]. 岩性油气藏, 2021, 33(1): 239-247.
[6] 罗泽, 谢明英, 梁杰, 涂志勇, 侯凯. 地震伪井速度点宏观校正方法与应用——以珠江口盆地M气田为例[J]. 岩性油气藏, 2020, 32(3): 115-121.
[7] 杜旭林, 戴宗, 辛晶, 李海龙, 曹仁义, 罗东红. 强底水稠油油藏水平井三维水驱物理模拟实验[J]. 岩性油气藏, 2020, 32(2): 141-148.
[8] 蒋德鑫, 姜正龙, 张贺, 杨舒越. 烃源岩总有机碳含量测井预测模型探讨——以陆丰凹陷文昌组为例[J]. 岩性油气藏, 2019, 31(6): 109-117.
[9] 刘跃杰, 刘书强, 马强, 姚宗森, 佘家朝. BP神经网络法在三塘湖盆地芦草沟组页岩岩相识别中的应用[J]. 岩性油气藏, 2019, 31(4): 101-111.
[10] 杜贵超, 苏龙, 陈国俊, 张功成, 丁超, 曹青, 鲁岳鑫. 番禺低隆起珠海组砂岩碳酸盐胶结特征及其对储层物性的影响[J]. 岩性油气藏, 2019, 31(3): 10-19.
[11] 李亚哲, 王力宝, 郭华军, 单祥, 邹志文, 窦洋. 基于地震波形指示反演的砂砾岩储层预测——以中拐-玛南地区上乌尔禾组为例[J]. 岩性油气藏, 2019, 31(2): 134-142.
[12] 李文静, 王英民, 何敏, 陈维涛, 徐少华, 卓海腾. 珠江口盆地中中新世陆架边缘三角洲的类型及控制因素[J]. 岩性油气藏, 2018, 30(2): 58-66.
[13] 陈锋，朱筱敏，葛家旺，黎明，吴陈冰洁. 珠江口盆地陆丰南地区文昌组层序地层及沉积体系研究[J]. 岩性油气藏, 2016, 28(4): 67-77，94.
[14] 马勇新,雷 霄,张乔良，孟令强. 低渗透油藏有效渗透率计算新模型—— — 以珠江口盆地海相低渗透砂岩为例[J]. 岩性油气藏, 2016, 28(1): 117-122.
[15] 潘光超，周家雄，韩光明，朱沛苑，刘 峰. 中深层“甜点”储层地震预测方法探讨—— 以珠江口盆地西部文昌 A 凹陷为例[J]. 岩性油气藏, 2016, 28(1): 94-100.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] 庞雄奇, 陈冬霞, 张　俊. 隐蔽油气藏的概念与分类及其在实际应用中需要注意的问题[J]. 岩性油气藏, 2007, 19(1): 1 -8 .
[2] 雷卞军，张吉，王彩丽，王晓蓉，李世临，刘斌. 高分辨率层序地层对微相和储层的控制作者用——以靖边气田统5井区马五段上部为例[J]. 岩性油气藏, 2008, 20(1): 1 -7 .
[3] 杨杰，卫平生，李相博. 石油地震地质学的基本概念、内容和研究方法[J]. 岩性油气藏, 2010, 22(1): 1 -6 .
[4] 王延奇，胡明毅，刘富艳，王辉，胡治华. 鄂西利川见天坝长兴组海绵礁岩石类型及礁体演化阶段[J]. 岩性油气藏, 2008, 20(3): 44 -48 .
[5] 代黎明, 李建平, 周心怀, 崔忠国, 程建春. 渤海海域新近系浅水三角洲沉积体系分析[J]. 岩性油气藏, 2007, 19(4): 75 -81 .
[6] 段友祥, 曹婧, 孙歧峰. 自适应倾角导向技术在断层识别中的应用[J]. 岩性油气藏, 2017, 29(4): 101 -107 .
[7] 黄龙，田景春，肖玲，王峰. 鄂尔多斯盆地富县地区长6砂岩储层特征及评价[J]. 岩性油气藏, 2008, 20(1): 83 -88 .
[8] 杨仕维，李建明. 震积岩特征综述及地质意义[J]. 岩性油气藏, 2008, 20(1): 89 -94 .
[9] 李传亮，涂兴万. 储层岩石的2种应力敏感机制——应力敏感有利于驱油[J]. 岩性油气藏, 2008, 20(1): 111 -113 .
[10] 李君, 黄志龙, 李佳, 柳波. 松辽盆地东南隆起区长期隆升背景下的油气成藏模式[J]. 岩性油气藏, 2007, 19(1): 57 -61 .

陇ICP备17006252号
版权所有© 2018 中国石油集团西北地质研究所有限公司《岩性油气藏》编辑部

地址：甘肃省兰州市城关区雁儿湾路535号(陇ICP备17006252号)    电话：0931-8686158;8686058;8686288    邮箱：yxyqc@petrochina.com.cn

甘公网安备 62010202002827号

本系统由北京玛格泰克科技发展有限公司设计开发