The use of Ann for the prediction of the modified relative permeability functions in stratified reservoirs
- 作者: Potashev K.1
-
隶属关系:
- Kazan (Volga Region) Federal University, N.I. Lobachevsky Institute of Mathematics and Mechanics
- 期: 卷 38, 编号 5 (2017)
- 页面: 843-848
- 栏目: Article
- URL: https://journals.rcsi.science/1995-0802/article/view/199868
- DOI: https://doi.org/10.1134/S1995080217050286
- ID: 199868
如何引用文章
详细
The paper presents a method of instantaneous construction of relative permeability pseudo functions in analytical form upscaled to a coarser computational grid using a system of artificial neural networks. The coefficients of these functions can be forecasted by the neural network. The learning dataset is based on a preliminary series of calculations at the reference values of the system parameters the exponents of the initial functions, the liquid phases viscosity ratio, the statistical parameters of distribution laws of the reservoir’s properties. The latter may be obtained according to the primary well logging data with no need for building a detailed geological model.
作者简介
K. Potashev
Kazan (Volga Region) Federal University, N.I. Lobachevsky Institute of Mathematics and Mechanics
编辑信件的主要联系方式.
Email: kpotashev@mail.ru
俄罗斯联邦, Kazan, 420008