US 12,000,976 B2
Systems and methods for training a well model to predict material loss for a pipe string within a borehole
Sebastian Kroczka, Cracow (PL); Welton Danniel Souza, Dan Haag (NL); and Chafaa Badis, Lons (FR)
Assigned to Landmark Graphics Corporation, Houston, TX (US)
Filed by Landmark Graphics Corporation, Houston, TX (US)
Filed on Aug. 28, 2020, as Appl. No. 17/006,110.
Claims priority of provisional application 62/923,729, filed on Oct. 21, 2019.
Prior Publication US 2021/0116599 A1, Apr. 22, 2021
Int. Cl. G01V 20/00 (2024.01); E21B 47/085 (2012.01); G01V 1/40 (2006.01); G06F 30/27 (2020.01); G06F 113/08 (2020.01); G06F 113/14 (2020.01); G06N 20/00 (2019.01)
CPC G01V 20/00 (2024.01) [E21B 47/085 (2020.05); G01V 1/40 (2013.01); G06F 30/27 (2020.01); G06N 20/00 (2019.01); E21B 2200/20 (2020.05); G06F 2113/08 (2020.01); G06F 2113/14 (2020.01)] 20 Claims
OG exemplary drawing
 
1. A method for training a well model to predict material loss for a pipe string having a wall thickness and located within a borehole, the method comprising:
measuring the wall thickness of a first pipe string at locations axially along the first pipe string with a logging tool at a first time;
measuring the wall thickness of the first pipe string at the locations with the logging tool at a second time;
training a first well model based on a machine learning (“ML”) algorithm to predict a predicted amount of material loss in the future for the first pipe string at a selected location using the wall thickness measurements at the first and second times and well operating condition information related to the first pipe string;
determining an amount of actual material loss for the first pipe string at the locations based on the wall thickness measurements;
receiving input from a user relating to user-defined color-coded categories based on the amount of actual material loss for the pipe string;
categorizing the locations into the user-defined color-coded categories at the respective locations; and
generating a graphical user interface showing a visual representation of the amount of actual material loss for the first pipe string using the user-defined color-coded categories on a display.