Methods and systems for borehole texture analysis

Abstract

A method may include segmenting a borehole image of a first well into a first plurality of zones based on pixel data, segmenting the borehole image of the first well into a second plurality of zones based on covariance data, merging the first plurality of zones and the second plurality of zones to generate an updated borehole image, clustering one or more sets of features of the updated borehole image into one or more clusters based on a classification algorithm, and generating a borehole texture model representative of expected properties of an additional borehole based on the one or more clusters.

1 . A method, comprising:
 segmenting a borehole image of a first well into a first plurality of zones based on pixel data;   segmenting the borehole image of the first well into a second plurality of zones based on covariance data;   merging the first plurality of zones and the second plurality of zones to generate an updated borehole image;   clustering one or more sets of features of the updated borehole image into one or more clusters based on a classification algorithm; and   generating a borehole texture model representative of expected properties of an additional borehole based on the one or more clusters.   
     
     
         2 . The method of  claim 1 , wherein the borehole image is segmented based on kernel density estimation (KDE), a variogram, or both. 
     
     
         3 . The method of  claim 1 , wherein the variogram corresponds to a measurement of a covariance of a pair of data points associated with the borehole image. 
     
     
         4 . The method of  claim 1 , wherein the updated borehole image comprises one or more boundaries between zone segments identified based on the first plurality of zones and the second plurality of zones. 
     
     
         5 . The method of  claim 1 , wherein clustering the one or more sets of features comprises an agglomerative clustering method. 
     
     
         6 . The method of  claim 1 , comprising:
 receiving an additional borehole image associated with a second well; and   applying the borehole texture model to classify one or more textures of the second well.   
     
     
         7 . The method of  claim 6 , comprising:
 determining one or more commands for drilling the second well based on the one or more textures; and   sending the one or more commands to a drilling system configured to adjust operations of a drill in response to receiving the one or more commands.   
     
     
         8 . A system, comprising:
 a controller having a processor, a memory, and instructions stored on the memory and executable by the processor to:
 segment a borehole image of a first well into a first plurality of zones based on pixel data; 
 segment the borehole image of the first well into a second plurality of zones based on covariance data; 
 merge the first plurality of zones and the second plurality of zones to generate an updated borehole image; 
 cluster one or more sets of features of the updated borehole image into one or more clusters based on a classification algorithm; and 
 generate a borehole texture model representative of expected properties of an additional borehole based on the one or more clusters. 
   
     
     
         9 . The system of  claim 8 , wherein the processor is configured to segment the borehole image based on kernel density estimation (KDE), a variogram, or both. 
     
     
         10 . The system of  claim 8 , wherein the variogram corresponds to a measurement of a covariance of a pair of data points associated with the borehole image. 
     
     
         11 . The system of  claim 8 , wherein the updated borehole image comprises one or more boundaries between zone segments identified based on the first plurality of zones and the second plurality of zones. 
     
     
         12 . The system of  claim 8 , wherein the processor is configured to cluster the one or more sets of features using an agglomerative clustering method. 
     
     
         13 . The system of  claim 8 , wherein the processor is further configured to:
 receive an additional borehole image associated with a second well; and   apply the borehole texture model to classify one or more textures of the second well.   
     
     
         14 . The system of  claim 13 , wherein the processor is further configured to:
 determine one or more commands for drilling the second well based on the one or more textures; and   send the one or more commands to a drilling system configured to adjust operations of a drill in response to receiving the one or more commands.   
     
     
         15 . A non-transitory computer readable medium comprising instructions that, when executed by a processor, causes the processor to perform operations comprising:
 segmenting a borehole image of a first well into a first plurality of zones based on pixel data;   segmenting the borehole image of the first well into a second plurality of zones based on covariance data;   merging the first plurality of zones and the second plurality of zones to generate an updated borehole image;   clustering one or more sets of features of the updated borehole image into one or more clusters based on a classification algorithm; and   generating a borehole texture model representative of expected properties of an additional borehole based on the one or more clusters.   
     
     
         16 . The computer readable medium of  claim 15 , wherein the borehole image is segmented based on kernel density estimation (KDE), a variogram, or both. 
     
     
         17 . The computer readable medium of  claim 15 , wherein the variogram corresponds to a measurement of a covariance of a pair of data points associated with the borehole image. 
     
     
         18 . The computer readable medium of  claim 15 , wherein the updated borehole image comprises one or more boundaries between zone segments identified based on the first plurality of zones and the second plurality of zones. 
     
     
         19 . The computer readable medium of  claim 15 , wherein the instructions that cause the processor to cluster the one or more sets of features comprises additional instructions to employ an agglomerative clustering method. 
     
     
         20 . The computer readable medium of  claim 15 , comprising:
 receiving an additional borehole image associated with a second well; and   applying the borehole texture model to classify one or more textures of the second well.