Method and system for locating a downhole tool in steel-cased holes

Abstract

A method for locating a downhole tool in a wellbore involves obtaining, by the downhole tool, a pressure measurement in the wellbore, generating a first depth estimate based on the pressure measurement, and anticipating a passing of the downhole tool by a collar, based on the first depth estimate and a known depth of the collar. The method further involves, based on the anticipating of the passing of the downhole tool by the collar, performing, by the downhole tool, a collar detection, and based on the collar detection resulting in a detection of the collar: generating an updated depth estimate, and reporting the updated depth estimate.

What is claimed: 
     
         1 . A method for locating a downhole tool in a wellbore, the method comprising:
 obtaining, by the downhole tool, a pressure measurement in the wellbore;   generating a first depth estimate based on the pressure measurement;   anticipating a passing of the downhole tool by a collar, based on the first depth estimate and a known depth of the collar;   based on the anticipating of the passing of the downhole tool by the collar, performing, by the downhole tool, a collar detection; and   based on the collar detection resulting in a detection of the collar:
 generating an updated depth estimate, and 
 reporting the updated depth estimate. 
   
     
     
         2 . The method of  claim 1 , wherein the first depth estimate is generated using a Kalman filter. 
     
     
         3 . The method of  claim 2 , wherein the Kalman filter is parameterized using a first hypothesis based on surface parameters. 
     
     
         4 . The method of  claim 3 , wherein the surface parameters comprise a 0-ft depth and a 0-ft/s speed. 
     
     
         5 . The method of  claim 3 , wherein generating the updated depth estimate comprises:
 determining a discrepancy between the first depth estimate and the known depth;   generating a second hypothesis that corrects for the discrepancy; and   generating a second depth estimate using the Kalman filter parameterized based on the second hypothesis.   
     
     
         6 . The method of  claim 5 , wherein generating the updated depth estimate comprises:
 continue making depth estimates using the Kalman filter parameterized based on the first hypothesis;   continue making depth estimates using the Kalman filter parameterized based on the second hypothesis; and   determining, a first weight for the first hypothesis and the second weight for the second hypothesis, the first and second weights reflecting an accuracy of the depth estimates made using the Kalman filter parameterized based on the first hypothesis and the second hypothesis, respectively.   
     
     
         7 . The method of  claim 6 , wherein the first weight and the second weight are assigned based on Bayesian probability. 
     
     
         8 . The method of  claim 6 ,
 wherein the first hypothesis and the second hypothesis are members of a plurality of hypotheses, and   wherein generating the updated depth estimate further comprises:   based on determining that a cardinality of the plurality of hypotheses exceeds a specified limit, eliminating a hypothesis with a lowest accuracy from the plurality of hypotheses, based on the weight associated with the hypothesis.   
     
     
         9 . The method of  claim 6 ,
 wherein the first hypothesis and the second hypothesis are members of a plurality of hypotheses, and   wherein reporting the updated depth estimate comprises reporting a depth estimate associated with a hypothesis with a highest accuracy of the plurality of hypotheses, based on the weight associated with the hypothesis.   
     
     
         10 . The method of  claim 1 , wherein the anticipating of the passing of the downhole tool comprises applying a depth tolerance window to the depth estimate in which the collar is expected. 
     
     
         11 . The method of  claim 1 , wherein the collar detection is performed using a magnetometer. 
     
     
         12 . The method of  claim 1 , wherein generating the depth estimate is further based on an acceleration measurement. 
     
     
         13 . The method of  claim 1 , wherein the downhole tool is configured to obtain measurements of one or more properties along the wellbore, and wherein the updated depth estimate is used to label the measurements. 
     
     
         14 . An untethered device comprising:
 a tool comprising a pressure sensor and a processor,   wherein the processor:
 obtains a pressure measurement from the pressure sensor, 
 generates a first depth estimate based on the pressure measurement, 
 anticipates a passing of the untethered device by a collar, based on the first depth estimate and a known depth of the collar; 
 based on the anticipating of the passing of the downhole tool by the collar, performs a collar detection; and 
 based on the collar detection resulting in a detection of the collar:
 generates an updated depth estimate, and 
 reports the updated depth estimate. 
 
   
     
     
         15 . The untethered device of  claim 14 , wherein the tool further comprises a magnetometer, and wherein the collar detection is performed using the magnetometer. 
     
     
         16 . The untethered device of  claim 14 , further comprising a ballast weight releasably attached to the tool. 
     
     
         17 . The untethered device of  claim 14 ,
 wherein the tool further comprises at least one sensor for obtaining a measurement of a property along a wellbore, and   wherein the processor further labels the measurement of the property using the updated depth estimate.   
     
     
         18 . The untethered device of  claim 14 , wherein the first depth estimate is generated using a Kalman filter. 
     
     
         19 . The untethered device of  claim 18 , wherein the Kalman filter is parameterized using a first hypothesis based on surface parameters. 
     
     
         20 . The untethered device of  claim 19 , wherein generating the updated depth estimate comprises:
 determining a discrepancy between the first depth estimate and the known depth;   generating a second hypothesis that corrects for the discrepancy; and   generating a second depth estimate using the Kalman filter parameterized based on the second hypothesis.