1887

Abstract

Summary

The main challenge of unconventional reservoirs is to find out their high production zones (so-called “sweet spots”). For “sweet spots” mapping, there is information from wells, which are drilled only in a few points of a reservoir, and from seismic survey covering the entire reservoir area. During upscaling the well data for the whole reservoir, there is a problem how having a limited amount of information from a finite number of points (wells), turn it into an infinite number of polygon points (a reservoir). In this work, the new adaptive modeling approach for seeking “sweet spots” is proposed. The main difference of the adaptive approach from the deterministic one is that it does not connect the well and seismic data by rigid functions. The adaptive approach gives real forecasting of future performance not its calculation, because it is based on artificial intelligence in a form of fuzzy logic algorithms, which are able to form relatively free correlation between the well and seismic data. This work demonstrates the capabilities of the adaptive approach for a real unconventional reservoir in a carbonate formation with heavy oil to predict the location of the reservoir “sweet spots” for new drilling.

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/content/papers/10.3997/2214-4609.201800196
2018-04-09
2024-04-26
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References

  1. ЭшбиУ.Р.
    Введение в кибернетику. - М.: Иностранная литература, 1959. - 432 с.:
    [Google Scholar]
  2. СтальгороваЕ., БабадаглиТ.
    Использование неклассических алгоритмов при моделировании смешиваемого вытеснения в трещиноватой поровой среде. // SPE 135903. –2010;
    [Google Scholar]
  3. КолмогоровА.Н.
    О представлении непрерывных функций нескольких переменных суперпозициями непрерывных функций меньшего числа переменных // Докл. АН СССР, том 108, с. 2, 1956;
    [Google Scholar]
  4. ПфанцагльИ.
    Теория измерений. - М. Мир1976. - 248 с.
    [Google Scholar]
  5. УрсеговС.О., ПчелаК.В. и ЧерепановВ.Н.
    Характеристика естественной трещиноватости и моделирование пермо-карбоновой залежи Усинского нефтяного месторождения // Тезисы докладов 4 Международной геолого-геофизической конференции и выставке EAGE «Санкт-Петербург – 2010. К новым открытиям через интеграцию геонаук», Санкт-Петербург, Россия, 5 - 8 апреля 2010 г.
    [Google Scholar]
  6. Ashby, W.R.
    Introduction to Cybernetics. - M.: Inostrannay literatura, 1959. - 432 p.;
    [Google Scholar]
  7. Stalgorova, E., Babadagli, T.
    Modeling Miscible Injection In Fractured Porous Media Using Non-Classical Simulation Approaches. // SPE 135903. – 2010;
    [Google Scholar]
  8. Kolmogorov, A.N.
    Foundations of the Theory of Probability. - New York: Chelsea, 1950. – 80 p.;
    [Google Scholar]
  9. PfantsaglI.
    Theory of measurment. - М.: Mir, 1976. - 248 p.
    [Google Scholar]
  10. UrsegovS.O., PchelaK.V. and CherepanovV.N.
    Natural Fracture Characterization and Modeling of the Permian-Carboniferous Reservoir of the Usinsk Field // Abstracts of the 4th International Conference & Exhibition EAGE: New Discoveries through Integration of Geosciences, St. Petersburg, Russia, April 5 – 8, 2010.
    [Google Scholar]
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