Drillstring sticking management framework

Abstract

A method includes receiving information during a drilling operation for a drillstring disposed in a bore in a formation; estimating uncertainty associated with the information; analyzing at least a portion of the information using a physics-based model to generate a result; computing, via a Bayesian network, a risk probability of the drilling string sticking in the bore in the formation based at least in part on the result and the estimated uncertainty; and, based at least in part on the risk probability, issuing a signal.

What is claimed is: 
     
         1 . A method comprising:
 receiving information during a drilling operation for a drillstring disposed in a bore in a formation;   estimating uncertainty associated with the information;   analyzing at least a portion of the information using a physics-based model to generate a result;   computing, via a Bayesian network, a risk probability of the drilling string sticking in the bore in the formation based at least in part on the result and the estimated uncertainty; and   based at least in part on the risk probability, issuing a signal.   
     
     
         2 . The method of  claim 1  wherein the signal comprises a control signal that controls drilling equipment of the drilling operation. 
     
     
         3 . The method of  claim 1  wherein the signal comprises an alert. 
     
     
         4 . The method of  claim 1  comprising, responsive to comparing the risk probability to a threshold, identifying a primary contributing factor to the risk probability. 
     
     
         5 . The method of  claim 4  wherein the identifying comprises progressing backwards through the Bayesian network to identify an input to the Bayesian network. 
     
     
         6 . The method of  claim 1  wherein the Bayesian network comprises a risk of differential sticking component and a risk of pack-off sticking component. 
     
     
         7 . The method of  claim 6  wherein the Bayesian network comprises a potential for differential sticking component. 
     
     
         8 . The method of  claim 7  comprising determining potential for differential sticking via the differential sticking component prior to performing the drilling operation. 
     
     
         9 . The method of  claim 1  wherein the computing occurs during the drilling operation. 
     
     
         10 . The method of  claim 1  wherein the physics-based model comprises a torque and drag model. 
     
     
         11 . The method of  claim 1  wherein the physics-based model comprises a hydraulics model. 
     
     
         12 . The method of  claim 1  wherein the physics-based model comprises a geomechanics model. 
     
     
         13 . The method of  claim 1  wherein the information comprises drilling fluid information. 
     
     
         14 . The method of  claim 1  wherein the computing comprises determining at least one cause of the risk probability. 
     
     
         15 . The method of  claim 1  wherein the computing comprises determining at least one action to mitigate the risk probability. 
     
     
         16 . The method of  claim 15  wherein the at least one action comprises an action that aims to prevent cuttings from packing off around the drillstring. 
     
     
         17 . The method of  claim 16  wherein the action comprises at least one of increasing rotation rate and increasing circulation rate to clean the bore. 
     
     
         18 . The method of  claim 17  wherein the action comprises associated parameters that decrease likelihood of creating a hole or washout. 
     
     
         19 . A system comprising:
 a processor;   memory accessible by the processor;   processor-executable instructions stored in the memory and executable to instruct the system to:
 receive information during a drilling operation for a drillstring disposed in a bore in a formation; 
 estimate uncertainty associated with the information; 
 analyze at least a portion of the information using a physics-based model to generate a result; 
 compute, via a Bayesian network, a risk probability of the drilling string sticking in the bore in the formation based at least in part on the result and the estimated uncertainty; and 
 based at least in part on the risk probability, issue a signal. 
   
     
     
         20 . One or more computer-readable storage media comprising processor-executable instructions to instruct a computing system to:
 receive information during a drilling operation for a drillstring disposed in a bore in a formation;   estimate uncertainty associated with the information;   analyze at least a portion of the information using a physics-based model to generate a result;   compute, via a Bayesian network, a risk probability of the drilling string sticking in the bore in the formation based at least in part on the result and the estimated uncertainty; and   based at least in part on the risk probability, issue a signal.