Systems and methods for predicting wellbore stimulation performance of acid jetting through pre-perforated liners

Abstract

The present disclosure relates to systems and methods for predicting wellbore stimulation performance of acid jetting through pre-perforated liners. In particular, the methods presented herein include collecting data relating to a wellbore stimulation operation performed subsurface in a wellbore, and utilizing a physics-based model to predict an effect of jetting on efficiency of a reactive fluid during the wellbore stimulation operation based at least in part on the collected data. In addition, experimental and field treatment data, real-time telemetry, production logs, flow quantification logs or distributed sensing (e.g., temperature, acoustic, strain, and so forth) results may be used to calibrate tuning parameters of the physics-based model, which may be adjusted based on data analytics and machine learning methods.

1 . A method, comprising:
 solving a flow problem associated with one or more perforations created during a wellbore stimulation operation performed subsurface in a wellbore;   calculating a first amount of wormhole propagation around the wellbore and away from the one or more perforations created during the wellbore stimulation operation based at least in part on the solved flow problem;   calculating a second amount of wormhole propagation around the wellbore and near the one or more perforations created during the wellbore stimulation operation based at least in part on the solved flow problem; and   updating near-wellbore permeability away from the one or more perforations created during the wellbore stimulation operation and near the one or more perforations created during the wellbore stimulation operation associated with the first and second amounts of wormhole propagation.   
     
     
         2 . The method of  claim 1 , comprising solving the flow problem utilizing a physics-based model to predict an effect of jetting on efficiency of a reactive fluid during the wellbore stimulation operation based at least in part on data collected during the wellbore stimulation operation. 
     
     
         3 . The method of  claim 2 , comprising calibrating tuning parameters of the physics-based model utilizing experimental and field treatment data, real-time telemetry, production logs, flow quantification logs or distributed sensing results. 
     
     
         4 . The method of  claim 3 , comprising adjusting the tuning parameters of the physics-based model based on data analytics and machine learning methods. 
     
     
         5 . The method of  claim 1 , wherein solving the flow problem comprises determining one or more pressures in a limited entry liner (LEL) used to perform the wellbore stimulation operation, one or more pressures in an annulus formed between the wellbore and the LEL, and one or more pressures in a formation through which the wellbore extends. 
     
     
         6 . The method of  claim 1 , wherein solving the flow problem comprises determining an impingement pressure directly adjacent the one or more perforations created during the wellbore stimulation operation. 
     
     
         7 . The method of  claim 1 , wherein solving the flow problem comprises determining one or more flow velocities in a limited entry liner (LEL) used to perform the wellbore stimulation operation, one or more flow velocities in an annulus formed between the wellbore and the LEL, and one or more flow velocities across the one or more perforations created during the wellbore stimulation operation. 
     
     
         8 . The method of  claim 1 , wherein solving the flow problem comprises determining one or more flow rates into a formation through which the wellbore extends and away from jets that form the one or more perforations created during the wellbore stimulation operation, and one or more flow rates into the formation through which the wellbore extends and near the jets that form the one or more perforations created during the wellbore stimulation operation. 
     
     
         9 . The method of  claim 1 , comprising calculating the first amount of wormhole propagation around the wellbore and away from the one or more perforations created during the wellbore stimulation operation based at least in part on a pressure in an annulus formed between the wellbore and a limited entry liner used to perform the wellbore stimulation operation that is determined as part of the solved flow problem. 
     
     
         10 . The method of  claim 1 , comprising calculating the second amount of wormhole propagation around the wellbore and near the one or more perforations created during the wellbore stimulation operation based at least in part on an impingement pressure directly adjacent the one or more perforations created during the wellbore stimulation operation that is determined as part of the solved flow problem. 
     
     
         11 . The method of  claim 1 , wherein the recited method steps are performed iteratively over time as a plurality of iterative loops. 
     
     
         12 . The method of  claim 11 , comprising adjusting one or more operational parameters of the wellbore stimulation operation during each iterative loop of the plurality of iterative loops. 
     
     
         13 . The method of  claim 1 , wherein the recited method steps are performed in substantially real-time during performance of the wellbore stimulation operation. 
     
     
         14 . A method, comprising:
 collecting data relating to a wellbore stimulation operation performed subsurface in a wellbore; and   utilizing a physics-based model to predict an effect of jetting on efficiency of a reactive fluid during the wellbore stimulation operation based at least in part on the collected data.   
     
     
         15 . The method of  claim 14 , comprising utilizing experimental and field treatment data to calibrate tuning parameters of the physics-based model. 
     
     
         16 . The method of  claim 15 , comprising adjusting the tuning parameters of the physics-based model based on data analytics and machine learning methods. 
     
     
         17 . The method of  claim 14 , comprising utilizing real-time telemetry, production logs, flow quantification logs or distributed sensing results to calibrate tuning parameters of the physics-based model. 
     
     
         18 . The method of  claim 17 , comprising adjusting the tuning parameters of the physics-based model based on data analytics and machine learning methods. 
     
     
         19 . The method of  claim 14 , comprising using jetting acids during the wellbore stimulation operation to create deep tunnels in geothermal wells to improve steam/heat recovery from geothermal reservoirs. 
     
     
         20 . A method, comprising:
 solving a flow problem associated with one or more perforations created during a wellbore stimulation operation performed subsurface in a wellbore utilizing a physics-based model to predict an effect of jetting on efficiency of a reactive fluid during the wellbore stimulation operation based at least in part on data collected during the wellbore stimulation operation;   calculating a first amount of wormhole propagation around the wellbore and away from the one or more perforations created during the wellbore stimulation operation based at least in part on a pressure in an annulus formed between the wellbore and a limited entry liner used to perform the wellbore stimulation operation that is determined as part of the solved flow problem;   calculating a second amount of wormhole propagation around the wellbore and near the one or more perforations created during the wellbore stimulation operation based at least in part on an impingement pressure directly adjacent the one or more perforations created during the wellbore stimulation operation that is determined as part of the solved flow problem; and   updating near-wellbore permeability away from the one or more perforations created during the wellbore stimulation operation and near the one or more perforations created during the wellbore stimulation operation associated with the first and second amounts of wormhole propagation.