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
  • [41] ESTIMATED PROBABILITY OF SURVIVAL USING NONPARAMETRIC METHODS
    MUNOZ, JA
    VALDES, MJN
    BUSTABAD, A
    GUERRA, A
    KIDNEY INTERNATIONAL, 1993, 44 (06) : 1490 - 1491
  • [42] GEOSTATISTICAL CONCEPTS AND STOCHASTIC METHODS IN HYDROGEOLOGY
    FREEZE, RA
    GELHAR, LW
    MADDOCK, T
    GEOLOGY, 1978, 6 (05) : 297 - 298
  • [43] Geostatistical Methods for Polluted Sites Characterization
    Soares, Amilcar
    GEOENV VII - GEOSTATISTICS FOR ENVIRONMENTAL APPLICATIONS, 2010, 16 : 187 - 198
  • [44] GEOSTATISTICAL METHODS APPLIED TO GEOMETALLURGICAL MODELING
    Vieira, M.
    Mendonca, A.
    Costa, J. F. C. L.
    HOLOS, 2015, 31 (07) : 65 - 71
  • [45] GEOSTATISTICAL METHODS TO PREDICT COLLAPSING SOILS
    ALI, MM
    NOWATZKI, EA
    MYERS, DE
    PROCEEDINGS OF THE TWELFTH INTERNATIONAL CONFERENCE ON SOIL MECHANICS AND FOUNDATION ENGINEERING, VOL 1: TECHNICAL PAPERS, 1989, : 567 - 570
  • [46] Assessment of the spread of chestnut ink disease using remote sensing and geostatistical methods
    L. Martins
    J. Castro
    W. Macedo
    C. Marques
    C. Abreu
    European Journal of Plant Pathology, 2007, 119 : 159 - 164
  • [47] Assessment of the spread of chestnut ink disease using remote sensing and geostatistical methods
    Martins, L.
    Castro, J.
    Macedo, W.
    Marques, C.
    Abreu, C.
    EUROPEAN JOURNAL OF PLANT PATHOLOGY, 2007, 119 (02) : 159 - 164
  • [48] Obtaining soil and land quality indicators using research chains and geostatistical methods
    Hoosbeek, MR
    Bouma, J
    NUTRIENT CYCLING IN AGROECOSYSTEMS, 1998, 50 (1-3) : 35 - 50
  • [49] COMPARISON OF GEOSTATISTICAL METHODS FOR ESTIMATING TRANSMISSIVITY USING DATA ON TRANSMISSIVITY AND SPECIFIC CAPACITY
    AHMED, S
    DEMARSILY, G
    WATER RESOURCES RESEARCH, 1987, 23 (09) : 1717 - 1737
  • [50] Characterization of Helicoverpa armigera spatial distribution in pigeonpea crop using geostatistical methods
    Seethalam, Malathi
    Bapatla, Kiran Gandhi
    Kumar, Murari
    Nisa, Shabistana
    Chandra, Puran
    Mathyam, Prabhakar
    Sengottaiyan, Vennila
    PEST MANAGEMENT SCIENCE, 2021, 77 (11) : 4942 - 4950