Improving reservoir thickness prediction using seismic attributes and attributes fusion

被引:3
|
作者
Liu, Haojie [1 ]
Lei, Xinhua [1 ]
Mao, Chuanlong [2 ]
Li, Songnan [3 ]
机构
[1] China Univ Geosci, Sch Informat Engn, Beijing, Peoples R China
[2] DianQianGui Oil Co, Sinopec Grp, Res Inst Explorat & Dev, Kunming, Yunnan, Peoples R China
[3] QingHai Oil Co, CNPC, Res Inst Explorat & Dev, Dunhuang, Gansu, Peoples R China
关键词
ACOUSTIC-IMPEDANCE; TRACE ANALYSIS; INVERSION; ATTENUATION; GRADIENT; WAVE;
D O I
10.2478/s11600-013-0174-5
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Usage of any single attribute would introduce unacceptable uncertainty due to limited reservoir thickness and distribution, and strong lateral variations in lithological traps. In this paper, a wide range of prestack and post-stack seismic attributes is utilized to identify a range of properties of turbidity channel sandstone reservoir in Block L118 of J Oilfield, China. In order to better characterize the turbidity channel and lower the uncertainty, we applied multi-attribute fusion to weight a variety of seismic attributes in terms of their relevance to the identification of turbidity channel reservoir. Turbidity channel boundary is clearly present in the new attribute and the reservoir thickness prediction is improved. Additionally, fluid potential of reservoir was predicted using this fused attribute with a high value anomaly indicating high fluid potential. The multi-attribute fusion is a valid approach for the fine prediction of lithologic reservoirs, reducing the risks typically associated with exploration.
引用
收藏
页码:544 / 563
页数:20
相关论文
共 50 条
  • [21] Ultra-Thin Bed Reservoir Interpretation Using Seismic Attributes
    Mohammed Farfour
    Wang Jung Yoon
    Arabian Journal for Science and Engineering, 2014, 39 : 379 - 386
  • [22] Estimation of reservoir porosity using probabilistic neural network and seismic attributes
    HOU Qiang
    ZHU Jianwei
    LIN Bo
    GlobalGeology, 2016, 19 (01) : 6 - 12
  • [23] Seismic image segmentation by fuzzy fusion of attributes
    Valet, L
    Mauris, G
    Bolon, P
    Keskes, N
    IMTC/2000: PROCEEDINGS OF THE 17TH IEEE INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE: SMART CONNECTIVITY: INTEGRATING MEASUREMENT AND CONTROL, 2000, : 360 - 364
  • [24] Multiattribute rotation scheme: A tool for reservoir property prediction from seismic inversion attributes
    Alvarez, Pedro
    Bolivar, Francisco
    Di Luca, Mario
    Salinas, Trino
    Interpretation-A Journal of Subsurface Characterization, 2015, 3 (04): : SAE9 - SAE18
  • [25] Seismic image segmentation by fuzzy fusion of attributes
    Valet, L
    Mauris, G
    Bolon, P
    Keskes, N
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2001, 50 (04) : 1014 - 1018
  • [26] Seismic attributes in 3D reservoir models
    不详
    JOURNAL OF PETROLEUM TECHNOLOGY, 1997, 49 (01): : 51 - 51
  • [27] Inclusion of seismic attributes in reservoir ensemble coverage analysis
    Lie E.O.
    Bhakta T.
    Sandø I.
    Leading Edge, 2022, 41 (12): : 848 - 856
  • [28] Characterization of a Volcanic Gas Reservoir Using Seismic Dispersion and Fluid Mobility Attributes
    Guo, Zhiqi
    Li, Yuedong
    Liu, Cai
    Zhang, Da
    Li, Anbang
    LITHOSPHERE, 2022, 2021 (SpecialIssue 3)
  • [29] Characterization of a Volcanic Gas Reservoir Using Seismic Dispersion and Fluid Mobility Attributes
    Guo, Zhiqi
    Li, Yuedong
    Liu, Cai
    Zhang, Da
    Li, Anbang
    LITHOSPHERE, 2021, 2021
  • [30] Reservoir characterization using microseismic facies analysis integrated with surface seismic attributes
    Rafiq, Aamir
    Eaton, David W.
    McDougall, Adrienne
    Pedersen, Per Kent
    INTERPRETATION-A JOURNAL OF SUBSURFACE CHARACTERIZATION, 2016, 4 (02): : T167 - T181