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Method for building models in non-stationary manner on basis of anisotropy

A technology of anisotropy and modeling methods, applied in character and pattern recognition, image data processing, instruments, etc., can solve problems such as non-stationary training images, difficult multi-point geological statistical modeling, and large differences in partitions

Inactive Publication Date: 2016-12-14
YANGTZE UNIVERSITY
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Problems solved by technology

This method solves the problem that "non-stationary training images are difficult to directly perform multi-point geostatistical modeling". The proposed method can automatically partition the non-stationary area. The partition is relatively stable, and the difference between the partitions is large. , each area is simulated separately

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  • Method for building models in non-stationary manner on basis of anisotropy
  • Method for building models in non-stationary manner on basis of anisotropy
  • Method for building models in non-stationary manner on basis of anisotropy

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Embodiment Construction

[0050] In order to better explain the present invention, the main content of the present invention is further clarified below in conjunction with specific examples, but the content of the present invention is not limited to the following examples.

[0051] In order to understand the present invention well, relevant terms are explained below:

[0052]1. Grid unit (C-Cell): a rectangular cubic unit with a specified length (ISize), width (JSize), and height (KSize) along the X, Y, and Z directions. The grid unit stores specific numerical representations its properties.

[0053] 2. Grid (G-Grid): A three-dimensional structure composed of many grid units C. The dimensions in the X direction, Y direction and Z direction are I×J×K, and the essence is a three-dimensional matrix. The meaning of G(i, j, k) is the grid unit whose index in the X direction is equal to i, the index in the Y direction is equal to j, and the index in the Z direction is equal to k.

[0054] 3. Training image...

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Abstract

The invention discloses a method for building models in a non-stationary manner on the basis of anisotropy. The method has the advantages that local anisotropy of training images is quantitatively represented by rose diagrams of range combinations of different directional variation functions, the method is combined with classic multi-dimensional scale analysis and K-means cluster analysis, accordingly, the non-stationary training images can be automatically segmented, various sub-regions are independent from one another, the insides of segments are simulated by the aid of the traditional stationery multi-point model building algorithms, and the models can be ultimately built in the non-stationary manner; multi-point geologic statistic model building can be effectively carried out by the aid of the non-stationary training images as compared with SIMPAT algorithms.

Description

technical field [0001] The invention relates to the technical field of reservoir geological modeling, in particular to ASNSIM (Non-stationary Simulation based on Segmentation using Anisotropy), an anisotropy-based non-stationary modeling method. Background technique [0002] The theoretical basis of geostatistics is the assumption of stationarity, that is, the mean and variance of regionalized variables satisfy spatial stationarity and have nothing to do with location. The training images based on the stationarity assumption should be stable, i.e. the spatial variability is independent of the spatial position. However, in the actual nature, due to changes in structure, water advance / retreat, and provenance, the sedimentary system develops in a non-stationary direction. Typical types of non-stationary sedimentary facies include alluvial fans and braided river delta depositional systems. [0003] Multi-point geostatistics is a popular geostatistical modeling method in current...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06K9/62G06T7/00
CPCG06F30/20G06F18/22G06F18/214
Inventor 喻思羽李少华段太忠王鸣川
Owner YANGTZE UNIVERSITY
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