# US 2024/0200413 A1 · Real time shoulder point determination in threaded connection make-up > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2024/0200413 A1 - Document ID: US20240200413A1 - Status: Published application - Kind: A1 - Application number: 18/066,258 - Filed: 2022-12-14 - Published: 2024-06-20 - Earliest claimed: 2022-12-14 - Applicants: Weatherford Technology Holdings, LLC - Inventors: David GEISSLER; Benjamin SACHTLEBEN; Rainer RUEHMANN; Christina HEBEBRAND - Web page: https://patentgrep.com/patent/US20240200413A1 ## CPC - E21B 19/166: {Arrangements of torque limiters or torque indicators} - E21B 3/022: {Top drives} - E21B 17/042: Threaded - E21B 19/161: {using a wrench or a spinner adapted to engage a circular section of pipe (E21B19/168 takes precedence)} - E21B 19/165: {Control or monitoring arrangements therefor} - G05B 13/027: {using neural networks only} - E21B 2200/22: Fuzzy logic, artificial intelligence, neural networks or the like - E21B: EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS - G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G) ## Abstract A method of controlling make-up of a threaded connection can include training an artificial intelligence, inputting data to the artificial intelligence during the threaded connection make-up, the artificial intelligence thereby determining a shoulder point during the threaded connection make-up, and controlling application of torque to the threaded connection, based in part on the determined shoulder point. A system for controlled make-up of a threaded connection can include a torque application device configured to apply torque and rotation to the threaded connection, and a control system comprising a controller and an artificial intelligence. The controller may be configured to control operation of the torque application device, and the artificial intelligence may be adapted to determine a shoulder point of the threaded connection during the make-up of the threaded connection. ## Claims ### Claim 1 A method of controlling make-up of a threaded connection, the method comprising: training an artificial intelligence; inputting data to the artificial intelligence during the threaded connection make-up, the artificial intelligence thereby determining a shoulder point during the threaded connection make-up; and controlling application of torque to the threaded connection, based in part on the determined shoulder point. ### Claim 2 (depends on 1) The method of claim 1, in which the training is performed prior to the threaded connection make-up. ### Claim 3 (depends on 1) The method of claim 1, in which the training is performed at least in part during the threaded connection make-up. ### Claim 4 (depends on 1) The method of claim 1, in which the artificial intelligence comprises at least one of the group consisting of a neural network and a Kalman filter. ### Claim 5 (depends on 1) The method of claim 1, in which the determining further comprises determining, prior to the shoulder point, at least one parameter level that will be achieved at the shoulder point, the parameter comprising at least one of the group consisting of torque, turns and time. ### Claim 6 (depends on 1) The method of claim 1, in which the determining further comprises determining at least one parameter level achieved after the shoulder point, the parameter comprising at least one of the group consisting of torque, turns and time. ### Claim 7 (depends on 1) The method of claim 1, in which a control system comprises the artificial intelligence and a controller configured to control operation of a torque application device, in which the determined shoulder point is output from the artificial intelligence to the controller, and in which the controlling comprises the controller controlling the operation of the torque application device. ### Claim 8 (depends on 7) The method of claim 7, in which the artificial intelligence is incorporated in one of the group consisting of a real time operating portion of the control system and a non-real time operating portion of the control system. ### Claim 9 (depends on 1) The method of claim 1, in which the training comprises inputting to the artificial intelligence prior shoulder point determinations for make-up of prior threaded connections. ### Claim 10 (depends on 1) The method of claim 1, in which the training comprises: inputting data samples to the artificial intelligence; outputting estimated shoulder points from the artificial intelligence; comparing the estimated shoulder points to actual shoulder points for the data samples; and adjusting at least one parameter of the artificial intelligence to minimize a difference between the estimated shoulder points and the actual shoulder points. ### Claim 11 A system for controlled make-up of a threaded connection, the system comprising: a torque application device configured to apply torque and rotation to the threaded connection; and a control system comprising a controller and an artificial intelligence, the controller being configured to control operation of the torque application device, and the artificial intelligence being adapted to determine a shoulder point of the threaded connection during the make-up of the threaded connection. ### Claim 12 (depends on 11) The system of claim 11, further comprising a torque sensor, and in which the artificial intelligence is adapted to receive torque indications from the torque sensor during the make-up of the threaded connection. ### Claim 13 (depends on 12) The system of claim 12, in which the artificial intelligence is adapted to learn from the torque indications received during the make-up of the threaded connection. ### Claim 14 (depends on 11) The system of claim 11, further comprising a turns sensor, and in which the artificial intelligence is adapted to receive turns indications from the turns sensor during the make-up of the threaded connection. ### Claim 15 (depends on 14) The system of claim 14, in which the artificial intelligence is adapted to learn from the turns indications received during the make-up of the threaded connection. ### Claim 16 (depends on 11) The system of claim 11, in which the artificial intelligence is adapted to output estimated shoulder points in response to input of example data to the artificial intelligence prior to the make-up of the threaded connection. ### Claim 17 (depends on 11) The system of claim 11, in which the artificial intelligence comprises at least one of the group consisting of a neural network and a Kalman filter. ### Claim 18 (depends on 11) The system of claim 11, in which the torque application device comprises one of a rotary clamp and a top drive. ### Claim 19 (depends on 11) The system of claim 11, in which the artificial intelligence is adapted to determine, prior to the shoulder point, at least one parameter level that will be achieved at the shoulder point, the parameter comprising at least one of the group consisting of torque, turns and time. ### Claim 20 (depends on 11) The system of claim 11 in which the artificial intelligence is adapted to determine at least one parameter level achieved after the shoulder point, the parameter comprising at least one of the group consisting of torque, turns and time.