Generation of Turbidite Probability Scenarios Using Geostatistical Methods

被引:2
|
作者
Sarruf, Eduardo [1 ]
Caseri, Angelica N. [1 ]
Barreto, Abelardo [1 ]
Pesco, Sinesio [1 ]
机构
[1] Pontificia Univ Catolica Rio de Janeiro, Math Dept, BR-22451900 Rio De Janeiro, Brazil
关键词
Computational modeling; Oils; Uncertainty; Reservoirs; Brain modeling; Minerals; Context modeling; Cross-validation; kriging; sequential Gaussian simulation (SGS); turbidite lobes; variogram; UNCERTAINTY; PREDICTION;
D O I
10.1109/LGRS.2020.3012479
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
Turbidite deposits are known to be potential oil reservoirs. The techniques used to detect these deposits are usually indirect measurement methods, normally, using sound waves emission. From several studies, it is known that these data have uncertainties. With the development of new technologies and the relevance of the oil exploration area, this theme has been gaining importance. However, this issue remains a major challenge for the scientific community. This work aims to develop a method based on geostatistics to generate possible scenarios (ensembles) that allow to quantify the uncertainties of the data used to identify turbidite deposits. For this, a set of coordinates extracted from the F3 field was used as study area. The results obtained showed that the methodology proposed in this study is appropriate to quantify the uncertainties in the detection of turbidite deposits.
引用
收藏
页码:2025 / 2029
页数:5
相关论文
共 50 条
  • [31] Probability Estimation of Rockburst Using Bayesian Network Methods
    Yuan, Jilai
    Lin, Jianru
    Ke, Zengyong
    2011 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION AND INDUSTRIAL APPLICATION (ICIA2011), VOL I, 2011, : 90 - 93
  • [32] Probability Estimation of Rockburst Using Bayesian Network Methods
    Yuan, Jilai
    Lin, Jianru
    Ke, Zengyong
    2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL VI, 2010, : 92 - 95
  • [33] Spatio-temporal variations of groundwater quality index using geostatistical methods and GIS
    Frsat Abdullah Ababakr
    Kaywan Othman Ahmed
    Ata Amini
    Mehdi Karami Moghadam
    Hüseyin Gökçekuş
    Applied Water Science, 2023, 13
  • [34] Spatio-temporal variations of groundwater quality index using geostatistical methods and GIS
    Ababakr, Frsat Abdullah
    Ahmed, Kaywan Othman
    Amini, Ata
    Karami Moghadam, Mehdi
    Goekcekus, Hueseyin
    APPLIED WATER SCIENCE, 2023, 13 (10)
  • [35] Investigating the geomechanical properties and permeability of the rocks of the Kurit dam site using geostatistical methods
    Ghasvareh M.A.
    Shahabi M.A.
    Shahid M.R.
    Panjeh M.G.
    Soils and Rocks, 2024, 47 (01):
  • [36] Estimation of nested spatial patterns and seasonal variation in the longitudinal distribution of Sicyopterus japonicus in the Datuan Stream, Taiwan by using geostatistical methods
    Yu-Pin Lin
    Cheng-Long Wang
    Chi-Ru Chang
    Hsiao-Hsuan Yu
    Environmental Monitoring and Assessment, 2011, 178 : 1 - 18
  • [37] Estimation of nested spatial patterns and seasonal variation in the longitudinal distribution of Sicyopterus japonicus in the Datuan Stream, Taiwan by using geostatistical methods
    Lin, Yu-Pin
    Wang, Cheng-Long
    Chang, Chi-Ru
    Yu, Hsiao-Hsuan
    ENVIRONMENTAL MONITORING AND ASSESSMENT, 2011, 178 (1-4) : 1 - 18
  • [38] A review of geostatistical simulation models applied to satellite remote sensing: Methods and applications
    Zakeri, Fatemeh
    Mariethoz, Gregoire
    REMOTE SENSING OF ENVIRONMENT, 2021, 259
  • [39] Assessment of geostatistical methods for spatiotemporal analysis of drought patterns in East Texas, USA
    Subedi, Mukti Ram
    Xi, Weimin
    Edgar, Christopher B.
    Rideout-Hanzak, Sandra
    Hedquist, Brent C.
    SPATIAL INFORMATION RESEARCH, 2019, 27 (01) : 11 - 21