Patent ID: 11860326
Assignee: INSTITUTE OF GEOLOGY AND GEOPHYSICS, CHINESE ACADEMY OF SCIENCES
Field: Measurement (Instruments)
Classification: CPC G | IPC G

Claim 7:
8. The fault characterization method for precise navigation of deep oil and gas based on image fusion described in claim 1 is characterized in that the image fusion carried out through the hierarchical wavelet transform method is specifically:
divide the gradient amplitude attribute fault confidence region and the dip angle attribute data volume defining the fault position into a high-frequency image and a low-frequency image through preset frequency boundary values;
based on the high-frequency image, define a local Log Gabor energy LGf(x, y) of a window at an any point in the high-frequency image (x, y) as:, LG
    f
   
   (
   
    x
    ,
    y
   
   )
  
  =
  
   
    1
    
     M
     ×
     N
    
   
   ⁢
   
    
     
      ∑
      
       m
       =
       1
      
     
     M
    
    
     
      
       ∑
       
        n
        =
        1
       
      
      N
     
     
      
       T
       f
      
      (
      
       
        x
        +
        m
        -
        
         
          M
          +
          1
         
         2
        
       
       ,
       
        y
        +
        n
        -
        
         
          N
          +
          1
         
         2
        
       
      
      )
     
    
   
  
 

wherein, M×N represents a size of a local neighborhood window and Tf represents a Log Gabor energy value of a current image f at (x, y)
high-frequency fusion rules are:, LG
    Hi
    A
   
   (
   
    x
    ,
    y
   
   )
  
  =
  
   
    1
    
     M
     ×
     N
    
   
   ⁢
   
    
     
      ∑
      
       m
       =
       1
      
     
     M
    
    
     
      
       ∑
       
        n
        =
        1
       
      
      N
     
     
      
       T
       H
       A
      
      (
      
       
        x
        +
        m
        -
        
         
          M
          +
          1
         
         2
        
       
       ,
       
        y
        +
        n
        -
        
         
          N
          +
          1
         
         2
        
       
      
      )
     
    
   
  
 

 
  
   
    LG
    Hi
    B
   
   (
   
    x
    ,
    y
   
   )
  
  =
  
   
    1
    
     M
     ×
     N
    
   
   ⁢
   
    
     
      ∑
      
       m
       =
       1
      
     
     M
    
    
     
      
       ∑
       
        n
        =
        1
       
      
      N
     
     
      
       T
       H
       B
      
      (
      
       
        x
        +
        m
        -
        
         
          M
          +
          1
         
         2
        
       
       ,
       
        y
        +
        n
        -
        
         
          N
          +
          1
         
         2
        
       
      
      )
     
    
   
  
 

wherein,, T
   H
   A
  
  (
  
   
    x
    +
    m
    -
    
     
      M
      +
      1
     
     2
    
   
   ,
   
    y
    +
    n
    -
    
     
      N
      +
      1
     
     2
    
   
  
  ), is the Log-Gabor energy value of the gradient amplitude attribute at, (
   
    
     x
     +
     m
     -
     
      
       M
       +
       1
      
      2
     
    
    ,
    
     y
     +
     n
     -
     
      
       N
       +
       1
      
      2
     
    
   
   )
  
  ,, LGHiA(x, y) denotes an evaluated Log-Gabor energy value of the high-frequency image of the gradient amplitude attribute fault confidence region in the local neighborhood M×N,, T
   H
   B
  
  (
  
   
    x
    +
    m
    -
    
     
      M
      +
      1
     
     2
    
   
   ,
   
    y
    +
    n
    -
    
     
      N
      +
      1
     
     2
    
   
  
  ), is the Log-Gabor energy value of a dip angle attribute at, (
   
    
     x
     +
     m
     -
     
      
       M
       +
       1
      
      2
     
    
    ,
    
     y
     +
     n
     -
     
      
       N
       +
       1
      
      2
     
    
   
   )
  
  ,
  
   
    (
    
     
      
       x
       +
       m
      
      =
      
       
        M
        +
        1
       
       2
      
     
     ,
     
      y
      +
      n
      -
      
       
        N
        +
        1
       
       2
      
     
    
    )
   
   ., denotes the evaluated Log-Gabor energy value of the high-frequency image of the dip angle attribute data volume in the local neighborhood-window M×N;
a high-frequency component of a fused image is FHi, and a fusion coefficient is a coefficient with a larger local Log Gabor energy:, F
    H
   
   (
   
    x
    ,
    y
   
   )
  
  =
  
   {
   
    
     
      
       
        
         A
         
          H
          ⁢
          i
         
        
        (
        
         x
         ,
         y
        
        )
       
       ,
       
        
         
          LG
          Hi
          A
         
         (
         
          x
          ,
          y
         
         )
        
        ≥
        
         
          LG
          Hi
          B
         
         (
         
          x
          ,
          y
         
         )
        
       
      
     
    
    
     
      
       
        
         LG
         
          H
          ⁢
          i
         
         B
        
        (
        
         x
         ,
         y
        
        )
       
       ,
       
        
         
          LG
          Hi
          A
         
         ⁢
         
          (
          
           x
           ,
           y
          
          )
         
        
        <
        
         
          LG
          Hi
          B
         
         (
         
          x
          ,
          y
         
         )
        
       
      
     
    
   
  
 

wherein, AHi is a value of the gradient amplitude attribute at (x, y), FH(x, y) denotes the Log-Gabor energy value of the high-frequency component of the fused image at(x, y);
based on the low-frequency image, compare a pixel points of the low-frequency image in the confidence region of the gradient amplitude attribute fault with the pixel points of the low-frequency image in the dip attribute data volume one by one to obtain a weight map W1, W2:, W
      1
     
     =
     
      {
      
       
        
         
          1
          ,
         
        
        
         
          
           A
           1
          
          >
          
           A
           2
          
         
        
       
       
        
         
          0
          ,
         
        
        
         else
        
       
      
     
    
   
  
  
   
    
     
      W
      2
     
     =
     
      {
      
       
        
         
          1
          ,
         
        
        
         
          
           A
           2
          
          >
          
           A
           1
          
         
        
       
       
        
         
          0
          ,
         
        
        
         else
        
       
      
     
    
   
  
 

Wherein, A1 is a pixel point value of a low frequency image of the gradient amplitude attribute fault confidence region. A2 is the pixel point value of the low frequency image of the dip angle attribute data volume,
a weighted fusion is performed on the weight map to obtain a processed low-frequency image A:, A
  =
  
   
    
     
      W
      1
     
     ×
     
      A
      1
     
    
    +
    
     
      W
      2
     
     ×
     
      A
      2
     
    
   
   
    
     W
     1
    
    +
    
     W
     2
    
   
  
 

combine the Log Gabor energy values of the high-frequency components of the fused image at (x, y) with the processed low-frequency image A to obtain the superimposed fault attribute map.