石油勘探与开发 >

2021 , Vol. 48 >Issue 4: 768 - 776

DOI: https://doi.org/10.11698/PED.2021.04.09

油气勘探

胜利埕岛极浅海油田薄储集层地震描述及流体识别

  • 束宁凯 ,
  • 苏朝光 ,
  • 石晓光 ,
  • 李治平 ,
  • 张学芳 ,
  • 陈先红 ,
  • 朱剑兵 ,
  • 宋亮
展开
  • 1.中国地质大学（北京）,北京100083;
    2.非常规天然气能源地质评价与开发工程北京市重点实验室,北京100083;
    3.中国石油大学胜利学院,山东东营257061;
    4.中国石化胜利油田分公司物探研究院,山东东营257022
束宁凯（1993-）,女,江苏丹阳人,中国地质大学（北京）能源学院在读博士研究生,主要从事油田开发地质及提高采收率研究。地址：北京市海淀区学院路29号,中国地质大学（北京）能源学院,邮政编码：100083。E-mail: 522345876@qq.com

收稿日期: 2020-10-14

  修回日期: 2021-05-20

  网络出版日期: 2021-07-23

基金资助

国家科技重大专项“胜利油田特高含水期提高采收率技术（二期）”(2016ZX050006); 中国石化科技攻关项目“薄互层地球物理特征分析及处理与解释技术研究”（P15156）; 中国石化科技攻关项目“碎屑岩储层地震相模式及自动识别关键技术”（P15159）

收起

Seismic description and fluid identification of thin reservoirs in Shengli Chengdao extra-shallow sea oil field

  • SHU Ningkai ,
  • SU Chaoguang ,
  • SHI Xiaoguang ,
  • LI Zhiping ,
  • ZHANG Xuefang ,
  • CHEN Xianhong ,
  • ZHU Jianbing ,
  • SONG Liang
Expand
  • 1. China University of Geosciences (Beijing), Beijing 100083, China;
    2. Beijing Key Laboratory of Unconventional Natural Gas Geology Evaluation and Development Engineering, China University of Geosciences (Beijing), Beijing 100083, China;
    3. Shengli College, China University of Petroleum, Dongying 257061, China;
    4. Geophysical Research Institute, Shengli Oilfield Company, Sinopec, Dongying 257022, China

Received date: 2020-10-14

  Revised date: 2021-05-20

  Online published: 2021-07-23

Fold

摘要

胜利埕岛极浅海油田新近系馆陶组上段曲流河沉积相变化快,加之受极浅海地表及海水鸣震等不利因素的影响,导致常规处理的海陆双检地震资料信噪比和分辨率低,难以满足该区10 m以下薄储集层地震描述及含油流体识别的需求。应用海陆双检叠前高分辨率二级提频处理技术有效提高地震资料的信噪比和分辨率,地震主频从30 Hz提高到50 Hz,砂体厚度分辨率从10 m提升至6 m;在地震精细层控的基础上,划分出河漫滩型、天然堤型、边滩型3种地震相模式,以此建立相层双控智能识别技术,储集层厚度预测误差小于1.5 m,提高了曲流河薄储集层砂体描述的准确性;综合泊松比、流体因子、拉梅参数与密度的乘积等多个叠前弹性参数,建立叠前多参数流体概率半定量含油性地震识别,流体识别吻合率达到90%以上,为胜利埕岛极浅海油田薄储集层的勘探开发提供物探技术支撑,有望为国内类似油田的勘探开发提供借鉴。 图11 表2 参26

关键词： 济阳坳陷; 埕岛油田; 极浅海; 新近系; 海陆双检; 叠前高分辨率二级提频处理; 相层双控智能识别; 叠前地震流体识别

本文引用格式

束宁凯 , 苏朝光 , 石晓光 , 李治平 , 张学芳 , 陈先红 , 朱剑兵 , 宋亮 . 胜利埕岛极浅海油田薄储集层地震描述及流体识别[J]. 石油勘探与开发, 2021 , 48(4) : 768 -776 . DOI: 10.11698/PED.2021.04.09

Abstract

The meandering channel deposit of the upper member of Neogene Guantao Formation in Shengli Chengdao extra-shallow sea oil field is characterized by rapid change in sedimentary facies. In addition, affected by surface tides and sea water reverberation, the double sensor seismic data processed by conventional methods has low signal-to-noise ratio and low resolution, and thus cannot meet the needs of seismic description and oil-bearing fluid identification of thin reservoirs less than 10 meters thick in this area. The secondary high resolution frequency bandwidth expanding processing technology was used to improve the signal-to-noise ratio and resolution of the seismic data, as a result, the dominant frequency of the seismic data was enhanced from 30 Hz to 50 Hz, and the sand body thickness resolution was enhanced from 10 m to 6 m. On the basis of fine layer control by seismic data, three types of seismic facies models, floodplain, natural levee and point bar, were defined, and the intelligent facies-layer control recognition technology was worked out, which had a prediction error of reservoir thickness of less than 1.5 m. Clearly, the description accuracy of meandering channel sand bodies has been improved. The probability semi-quantitative oiliness identification method of fluid by prestack multi-parameters has been worked out by integrating Poisson's ratio, fluid factor, product of Lame parameter and density, and other pre-stack elastic parameters, and the method has a coincidence rate of fluid identification of more than 90%, providing solid technical support for the exploration and development of thin reservoirs in Shengli Chengdao extra-shallow sea oil field.

Key words： Jiyang Depression; Chengdao oilfield; extra-shallow sea; Neogene; double-sensor data; pre-stack high resolution frequency bandwidth expanding processing; intelligent facies-layer controlled recognition technology; prestack seismic fluid identification

参考文献

[1] 李阳. 埕岛油田馆陶组油藏高产开发技术[J]. 油气采收率技术, 1998, 5(2): 36-40.
LI Yang. High production development technology of Guantao Formation Reservoir in Chengdao Oilfield[J]. Petroleum Geology and Recovery Efficiency, 1998, 5(2): 36-40.
[2] 邓宏文, 李小孟. 高分辨率层序地层对比在河流相中的应用[J]. 石油天然气地质, 1997, 18(2): 90-95.
DENG Hongwen, LI Xiaomeng. Application of high-resolution sequence stratigraphic correlation to fluvial facies[J]. Oil & Gas Geology, 1997, 18(2): 90-95.
[3] 岳大力, 李伟, 王军, 等. 基于分频融合地震属性的曲流带预测与点坝识别: 以渤海湾盆地埕岛油田馆陶组为例[J]. 古地理学报, 2018, 20(6): 941-950.
YUE Dali, LI Wei, WANG Jun, et al. Prediction of meandering belt and point-bar recognition based on spectral-decomposed and fused seismic attributes: A case study of the Guantao Formation, Chengdao Oilfield, Bohai Bay Basin[J]. Journal of Palaeogeography, 2018, 20(6): 941-950.
[4] 陈广军, 张善文, 李建明, 等. 小波分析技术在薄砂岩储集层描述中的应用: 以埕岛地区馆上段为例[J]. 石油物探, 2002, 41(1): 95-99.
CHEN Guangjun, ZHANG Shanwen, LI Jianming, et al. Application of wavelet analysis to the characterization of thin sandstone reservoirs: An example from the upper member of Guantao Formation in Chengdao Area[J]. Geophysical Prospecting for Petroleum, 2002, 41(1): 95-99.
[5] 张学芳, 董月昌, 慎国强, 等. 曲线重构技术在测井约束反演中的应用[J]. 石油勘探与开发, 2005, 32(3): 70-72.
ZHANG Xuefang, DONG Yuechang, SHEN Guoqiang, et al. Application of log rebuilding technique in constrain inversion[J]. Petroleum Exploration and Development, 2005, 32(3): 70-72.
[6] 陈浩林, 张保庆, 倪成洲, 等. 水深对OBC地震资料的影响分析与对策[J]. 石油地球物理勘探, 2010, 45(S1): 18-24.
CHEN Haolin, ZHANG Baoqing, NI Chengzhou, et al. The analysis and strategy of influence of water depth to OBC seismic data[J]. Oil Geophysical Prospecting, 2010, 45(S1): 18-24.
[7] 韩立强, 常稳. 海底电缆初至波二次定位技术的应用[J]. 石油物探, 2003, 42(4): 501-504.
HAN Liqiang, CHANG Wen. Application of first break second positioning technique in OBC[J]. Geophysical Prospecting For Petroleum, 2003, 42(4): 501-504.
[8] 全海燕, 韩立强. 海底电缆双检接收技术压制水柱混响[J]. 石油地球物理勘探, 2005, 40(1): 7-12.
QUAN Haiyan, HAN Liqiang. Using OBC dual-receiver to suppress reverberation of water column[J]. Oil Geophysical Prospecting, 2005, 40(1): 7-12.
[9] 王振华, 夏庆龙, 田立新, 等. 消除海底电缆双检地震资料中的鸣震干扰[J]. 石油地球物理勘探, 2008, 43(6): 626-635.
WANG Zhenhua, XIA Qinglong, TIAN Lixin, et al. Elimination of singing interference in OBC dual-geophone seismic data[J]. Oil Geophysical Prospecting, 2008, 43(6): 626-635.
[10] 秦宁. 海底电缆双检资料陆检微分合并技术[J]. 地球物理学进展, 2018, 33(3): 1369-1273.
QIN Ning. Merging method using the derivative of geophone data in OBC dual-sensor seismic processing[J]. Progress in Geophysics, 2018, 33(3): 1369-1273.
[11] 张明振. 基于地震叠前大角度道集的调谐压制提高分辨率方法[J]. 科学技术与工程, 2017, 17(11): 169-174.
ZHANG Mingzhen. The method of resolution improvement through tuning suppression based on large angle pre-stack seismic data[J]. Science Technology and Engineering, 2017, 17(11): 169-174.
[12] 国景星. 冲积-河流相层序地层模式: 以济阳凹陷新近系为例[J]. 新疆地质, 2003, 21(4): 393-397.
GUO Jingxing. The mode of sequence stratum of alluvial-fluvial facies: Taking the upper Tertiary of Jiyang Depression for example[J]. Xinjiang Geology, 2003, 21(4): 393-397.
[13] 郑和荣, 林会喜, 王永诗. 埕岛油田勘探实践与认识[J]. 石油勘探与开发, 2000, 27(6): 1-8.
ZHENG Herong, LIN Huixi, WANG Yongshi. Exploration practice and understanding of Chengdao Oilfield[J]. Petroleum Exploration and Development, 2000, 27(6): 1-8.
[14] 陈清华, 曾明, 章凤奇, 等. 河流相储层单一河道的识别及其对油田开发的意义[J]. 油气地质与采收率, 2004, 11(3): 13-15.
CHEN Qinghua, ZENG Ming, ZHANG Fengqi, et al. Practice and knowledge of exploration on Chengdao oil field[J]. Petroleum Geology and Recovery Efficiency, 2004, 11(3): 13-15.
[15] 杨帆, 林琛, 周绮凤, 等. 基于随机森林的潜在K近邻算法及其在基因表达数据分类中的应用[J]. 系统工程理论与实践, 2012, 32(4): 815-825.
YANG Fan, LIN Chen, ZHOU Qifeng, et al. Random forest based potential K nearest neighbor classifier and its application in gene expression data[J]. System Engineering Theory and Practice, 2012, 32(4): 815-825.
[16] BREIMAN L. Random forests[J]. Machine Learning, 2001, 45(1): 5-32.
[17] LINARI M, SANTIAGO M, PASTORE C, et al. Seismic facies analysis based on 3D multiattribute volume classification, La Palma Field, Maracaibo, Venezuela[J]. Leading Edge, 2003, 22(1): 32-36.
[18] 李国发, 岳英, 熊金良, 等. 基于三维模型的薄互层振幅属性实验研究[J]. 石油地球物理勘探, 2011, 46(1): 115-120.
LI Guofa, YUE Ying, XIONG Jinliang, et al. Experimental study on seismic amplitude attribute of thin interbed based on 3D model[J]. Oil Geophysical Prospecting, 2011, 46(1): 115-120.
[19] 吴琼, 周维民, 李运田. 数据挖掘分类算法优化非平衡采样样本的研究与应用[J]. 工业控制计算机, 2014, 27(2): 63-78.
WU Qiong, ZHOU Weimin, LI Yuntian. Research and application of data mining classification algorithm to optimize unbalanced samples[J]. Industrial Control Computer, 2014, 27(2): 63-78.
[20] URSENBACH C. P-S converted-wave AVO[R]. Houston: The 73rd Annual International Society of Exploration Geophysics Meeting, 2003.
[21] 梁兵, 杨建礼, 张春峰, 等. 叠前弹性参数反演在黄珏油田的应用[J]. 石油勘探与开发, 2007, 34(2): 202-206.
LIANG Bing, YANG Jianli, ZHANG Chunfeng, et al. Application of pre-stack elastic parameter inversion in Huangjue Oilfield[J]. Petroleum Exploration and Development, 2007, 34(2): 202-206.
[22] HAMPSON D, RUSSELL B. Simultaneous inversion of pre-stack seismic data[R]. Tulsa, Oklahoma, USA: The 75th Annual International Society of Exploration Geophysics Meeting, 2005.
[23] 陈建江, 印兴耀. 基于贝叶斯理论的AVO三参数波形反演[J]. 地球物理学报, 2007, 50(4): 1251-1260.
CHEN Jianjiang, YIN Xingyao. Three-parameter AVO waveform inversion based on Bayesian theorem[J]. Chinese Journal of Geophysics, 2007, 50(4): 1251-1260.
[24] 慎国强, 李海涛, 王玉梅, 等. 密度及泊松比参数叠前地震反演技术应用研究[J]. 石油天然气学报, 2011, 33(3): 67-71.
SHEN Guoqiang, LI Haitao, WANG Yumei, et al. Application of density and poisson-ratio parameters form prestack seismic inversion[J]. Journal of Oil and Gas Technology, 2011, 33(3): 67-71.
[25] GRANA D, DVORKIN J. The link between seismic inversion, rock physics, and geostatistical simulations in seismic reservoir characterization studies[J]. Leading Edge, 2011, 30(1): 54-61.
[26] BOSCH M, MUKERJI T, MAVKO G. Seismic inversion combining statistical rock physics and geo-statistics: A review[J]. Geophysics, 2010, 75(5): 165-176.
Options
文章导航

/

〈 〉

版权所有：《石油勘探与开发》编辑部；《石油勘探与开发（英文）》编辑部
地址：北京市海淀区学院路20号，中国石油勘探开发研究院数据中心605室　

京ICP备15044687号    技术支持：北京玛格泰克科技发展有限公司