Extrapolation of flow units away from wells with 3D pre-stack seismic amplitude data:: Field example

被引:0
|
作者
Contreras, Arturo
Torres-Verdin, Carlos
Chesters, William
Kvien, Knut
Fasnacht, Tim
机构
[1] Univ Texas, Dept Geol Sci, Austin, TX 78712 USA
[2] Univ Texas, Dept Petr & Geosyst Engn, Austin, TX 78712 USA
[3] Fugro Jason Netherlands BV, Rotterdam, Netherlands
[4] Anadarko Petr Corp, The Woodlands, TX 77380 USA
来源
PETROPHYSICS | 2006年 / 47卷 / 03期
关键词
reservoir connectivity; seismic petrophysics; elastic properties; turbidites; Marco Polo Field;
D O I
暂无
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
We estimate the spatial continuity and lateral extent of lithologic and flow units penetrated by wells, using pre-stack seismic amplitude data and well logs. The approach is based on a stochastic global inversion algorithm that concomitantly honors well logs and multiple partial-angle stacks of seismic amplitude data. Inversion results consist of 3D spatial distributions of elastic properties, litho-types, and petrophysical properties between wells. These distributions have a vertical resolution that is intermediate relative to those of well logs and 3D seismic amplitude data. An example of application is shown with high-quality 3D seismic amplitude data acquired over the Marco Polo Field in the deepwater Gulf of Mexico. Reservoir units in this field consist of stacked turbidite sands. Petrophysical logs, elastic-petrophysical correlations, and four partial-angle stacks of pre-stack seismic amplitude data are input to the stochastic inversion algorithm to estimate 3D distributions of lithotype, porosity, permeability, and fluid saturation. When cross-validated at blind-well locations, the estimated spatial distributions of porosity, permeability, and water saturation of individual sand units agree well with the same properties derived from well logs. Sensitivity analyses indicate that inversion results are slightly conditioned by the choice of variogram model and range, as well as by the assumed global lithology proportions. The uncertainty of the extrapolated lithotypes and petrophysical properties increases with distance away from wells. In addition, we find that the uncertainty of the extrapolation increases when flow units are thinner than the vertical resolution of seismic amplitude data. However, in all of the examples considered in this paper, the joint stochastic inversion of wells and pre-stack seismic data yields more accurate extrapolations of lithologic and flow units than pre-stack seismic data alone.
引用
收藏
页码:223 / 238
页数:16
相关论文
共 50 条
  • [41] On the value of 3D seismic amplitude data to reduce uncertainty in the forecast of reservoir production
    Varela, OJ
    Torres-Verdín, C
    Lake, LW
    JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, 2006, 50 (3-4) : 269 - 284
  • [42] Amplitude preserved seismic data reconstruction by fast 3D parabolic Radon transform
    Wang Liang-Liang
    Mao Wei-Jian
    Tang Huan-Huan
    Zhao Bo
    CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION, 2017, 60 (07): : 2801 - 2812
  • [43] Automatic gas chimney detection from 3D seismic reflection data using a single amplitude attribute
    Bargees, Amen
    Harishidayat, Dicky
    Iqbal, Naveed
    Al-Shuhail, Abdullatif A.
    MARINE AND PETROLEUM GEOLOGY, 2023, 152
  • [44] Accelerating POCS interpolation of 3D irregular seismic data with Graphics Processing Units
    Wang, Shu-Qin
    Gao, Xing
    Yao, Zhen-Xing
    COMPUTERS & GEOSCIENCES, 2010, 36 (10) : 1292 - 1300
  • [45] Seismic imaging of the complex geological structures in the southwestern edge of the Western limb, Bushveld Complex through focusing pre-stack depth migration of legacy 2D seismic data
    Sihoyiya, Mpofana
    Hlousek, Felix
    Manzi, Musa S. D.
    Rapetsoa, Moyagabo K.
    Buske, Stefan
    Khoza, David
    GEOPHYSICAL PROSPECTING, 2024, 72 (07) : 2504 - 2519
  • [46] Scanning Electron Microscopy: Extrapolation of 3D Data from SEM Micrographs
    Kareiva, Simonas
    Selskis, Algirdas
    Ivanauskas, Feliksas
    Sakirzanovas, Simas
    Kareiva, Aivaras
    MATERIALS SCIENCE-MEDZIAGOTYRA, 2015, 21 (04): : 640 - 646
  • [47] Reservoir properties estimation from 3D seismic data in the Alose field using artificial intelligence
    Ogbamikhumi, A.
    Ebeniro, J. O.
    JOURNAL OF PETROLEUM EXPLORATION AND PRODUCTION TECHNOLOGY, 2021, 11 (03) : 1275 - 1287
  • [48] Prediction of Gamma Ray data from pre-stack seismic reflection partial angle stacks using Continuous Wavelet Transform and convolutional neural network approach
    Shahsenov, Izat
    Malikov, Ruslan
    Cook, Peter
    Grant, Sara
    Ismayilov, Nariman
    Abbasov, Kamran
    JOURNAL OF APPLIED GEOPHYSICS, 2022, 197
  • [49] Geometry of extensional faults developed at slow-spreading centres from pre-stack depth migration of seismic reflection data in the Central Atlantic (Canary Basin)
    Reston, TJ
    Ranero, CR
    Ruoff, O
    Perez-Gussinye, M
    Dañobeitia, JJ
    GEOPHYSICAL JOURNAL INTERNATIONAL, 2004, 159 (02) : 591 - 606
  • [50] Integrating geologic and engineering data into 3-D reservoir models: An example from norman wells field, NWT, Canada
    Yose, LA
    GEOLOGICAL DISPOSAL: BUILDING CONFIDENCE USING MULTIPLE LINES OF EVIDENCE, 2003, : 103 - 108