Methods for optimizing production packer placement in hydrocarbon wells for uniform inflow profile

Abstract

A method to perform a completion operation of a wellbore is described. The method includes determining a wellbore trajectory of the wellbore penetrating a reservoir, generating a grid cell set of interest surrounding the wellbore, where the grid cell set of interest includes consecutive grid cells that are penetrated by the wellbore in the reservoir, generating, from the grid cell set of interest and using a clustering algorithm, grid cell clusters based on a grid cell position measure and a reservoir property of each grid cell, where each grid cell cluster corresponds to a flow compartment of the wellbore, and placing, during the completion operation and for each grid cell cluster, a packer at a starting position and an ending position of the corresponding flow compartment.

What is claimed: 
     
         1 . A method to perform a completion operation of a wellbore, comprising:
 determining a wellbore trajectory of the wellbore penetrating a reservoir;   generating a grid cell set of interest surrounding the wellbore, wherein the grid cell set of interest comprises a plurality of consecutive grid cells that are penetrated by the wellbore in the reservoir;   generating, from the grid cell set of interest and using a clustering algorithm, a plurality of grid cell clusters based on a grid cell position measure and a reservoir property of each grid cell, wherein each grid cell cluster corresponds to a flow compartment of the wellbore; and   placing, during the completion operation and for said each grid cell cluster, a packer at a starting position and an ending position of the corresponding flow compartment.   
     
     
         2 . The method of  claim 1 , wherein generating the plurality of grid cell clusters comprises:
 performing one or more of a geologic survey operation and a well logging operation to determine the wellbore trajectory and the reservoir property of each grid cell in the grid cell set of interest;   generating, based on the grid cell of interest, a multi-dimensional data set, wherein each data object in the multi-dimensional data set corresponds to one of the plurality of consecutive grid cells and comprises the grid cell position measure and the reservoir property of a corresponding grid cell; and   generating, by applying the clustering algorithm to the multi-dimensional data set, a plurality of data object clusters, wherein each data object cluster of the plurality of data object clusters corresponds to a grid cell cluster of the plurality of grid cell clusters.   
     
     
         3 . The method of  claim 2 ,
 wherein the clustering algorithm comprise a K-Means algorithm, and   wherein applying the clustering algorithm comprises:
 determining an aggregate silhouette coefficient value of the plurality of data object clusters; and 
 determining a target cluster count for the K-Means algorithm based at least on the aggregate silhouette coefficient value. 
   
     
     
         4 . The method of  claim 2 , further comprising:
 identifying, based on the plurality of grid cell clusters, a plurality of flow compartments of the wellbore.   
     
     
         5 . The method of  claim 4 , wherein identifying the plurality of flow compartments comprises:
 determining, for each grid cell cluster, a minimum value of the grid cell position measure and a maximum value of the grid cell position measure in a corresponding data object cluster; and   determining the starting position and the ending position of said corresponding flow compartment based on the minimum value and the maximum value of the grid cell position measure, respectively.   
     
     
         6 . The method of  claim 1 , further comprising:
 placing, during the completion operation and within at least one flow compartment, an inflow control device; and   facilitating production of the wellbore by the using the inflow control device to equalize reservoir inflow along the trajectory of the wellbore.   
     
     
         7 . The method of  claim 1 , wherein the grid cell position measure comprises a depth of the grid cell along the trajectory of the wellbore. 
     
     
         8 . A data analysis system to facilitate a completion operation of a wellbore, comprising:
 a computer processor; and   memory storing instructions, when executed by the computer processor comprising functionality for:
 determining a wellbore trajectory of the wellbore penetrating a reservoir; 
 generating a grid cell set of interest surrounding the wellbore, wherein the grid cell set of interest comprises a plurality of consecutive grid cells that are penetrated by the wellbore in the reservoir; 
 generating, from the grid cell set of interest and using a clustering algorithm, a plurality of grid cell clusters based on a grid cell position measure and a reservoir property of each grid cell, wherein each grid cell cluster corresponds to a flow compartment of the wellbore; and 
 determining, for said each grid cell cluster, a starting position and an ending position of the corresponding flow compartment, 
   wherein a packer is placed, during the completion operation and for said each grid cell cluster, at a starting position and an ending position of the corresponding flow compartment.   
     
     
         9 . The data analysis system of  claim 8 , wherein generating the plurality of grid cell clusters comprises:
 determining, based on results of one or more of a geologic survey operation and a well logging operation, the wellbore trajectory and the reservoir property of each grid cell in the grid cell set of interest;   generating, based on the grid cell of interest, a multi-dimensional data set, wherein each data object in the multi-dimensional data set corresponds to one of the plurality of consecutive grid cells and comprises the grid cell position measure and the reservoir property of a corresponding grid cell; and   generating, by applying the clustering algorithm to the multi-dimensional data set, a plurality of data object clusters, wherein each data object cluster of the plurality of data object clusters corresponds to a grid cell cluster of the plurality of grid cell clusters.   
     
     
         10 . The data analysis system of  claim 9 ,
 wherein the clustering algorithm comprise a K-Means algorithm, and   wherein applying the clustering algorithm comprises:
 determining an aggregate silhouette coefficient value of the plurality of data object clusters; and 
 determining a target cluster count for the K-Means algorithm based at least on the aggregate silhouette coefficient value. 
   
     
     
         11 . The data analysis system of  claim 9 , the instructions, when executed by the computer processor further comprising functionality for:
 identifying, based on the plurality of grid cell clusters, a plurality of flow compartments of the wellbore.   
     
     
         12 . The data analysis system of  claim 11 , wherein identifying the plurality of flow compartments comprises:
 determining, for each grid cell cluster, a minimum value of the grid cell position measure and a maximum value of the grid cell position measure in a corresponding data object cluster; and   determining the starting position and the ending position of said corresponding flow compartment based on the minimum value and the maximum value of the grid cell position measure, respectively.   
     
     
         13 . The data analysis system of  claim 8 ,
 wherein an inflow control device is placed within at least one flow compartment during the completion operation, and   wherein production of the wellbore is facilitated by the using the inflow control device to equalize reservoir inflow along the trajectory of the wellbore.   
     
     
         14 . The data analysis system of  claim 8 , wherein the grid cell position measure comprises a depth of the grid cell along the trajectory of the wellbore. 
     
     
         15 . A system comprising:
 a wellbore penetrating a reservoir; and   a data analysis system comprising a computer processor and memory storing instructions, when executed by the computer processor comprising functionality for:
 determining a wellbore trajectory of the wellbore penetrating a reservoir; 
 generating a grid cell set of interest surrounding the wellbore, wherein the grid cell set of interest comprises a plurality of consecutive grid cells that are penetrated by the wellbore in the reservoir; 
 generating, from the grid cell set of interest and using a clustering algorithm, a plurality of grid cell clusters based on a grid cell position measure and a reservoir property of each grid cell, wherein each grid cell cluster corresponds to a flow compartment of the wellbore; and 
 determining, for said each grid cell cluster, a starting position and an ending position of the corresponding flow compartment, 
   wherein a packer is placed, during a completion operation and for said each grid cell cluster, at a starting position and an ending position of the corresponding flow compartment.   
     
     
         16 . The system of  claim 15 , wherein generating the plurality of grid cell clusters comprises:
 determining, based on results of one or more of a geologic survey operation and a well logging operation, the wellbore trajectory and the reservoir property of each grid cell in the grid cell set of interest;   generating, based on the grid cell of interest, a multi-dimensional data set, wherein each data object in the multi-dimensional data set corresponds to one of the plurality of consecutive grid cells and comprises the grid cell position measure and the reservoir property of a corresponding grid cell; and   generating, by applying the clustering algorithm to the multi-dimensional data set, a plurality of data object clusters, wherein each data object cluster of the plurality of data object clusters corresponds to a grid cell cluster of the plurality of grid cell clusters.   
     
     
         17 . The system of  claim 16 ,
 wherein the clustering algorithm comprise a K-Means algorithm, and   wherein applying the clustering algorithm comprises:
 determining an aggregate silhouette coefficient value of the plurality of data object clusters; and 
 determining a target cluster count for the K-Means algorithm based at least on the aggregate silhouette coefficient value. 
   
     
     
         18 . The system of  claim 16 , the instructions, when executed by the computer processor further comprising functionality for:
 identifying, based on the plurality of grid cell clusters, a plurality of flow compartments of the wellbore.   
     
     
         19 . The system of  claim 18 , wherein identifying the plurality of flow compartments comprises:
 determining, for each grid cell cluster, a minimum value of the grid cell position measure and a maximum value of the grid cell position measure in a corresponding data object cluster; and   determining the starting position and the ending position of said corresponding flow compartment based on the minimum value and the maximum value of the grid cell position measure, respectively.   
     
     
         20 . The system of  claim 15 ,
 wherein an inflow control device is placed within at least one flow compartment during the completion operation, and   wherein production of the wellbore is facilitated by the using the inflow control device to equalize reservoir inflow along the trajectory of the wellbore.