# US 11,898,410 B2 · Method and system for predicting locations of stuck pipe events > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,898,410 B2 - Document ID: US11898410B2 - Status: Granted - Kind: B2 - Application number: 17/469,478 - Filed: 2021-09-08 - Published: 2023-03-09 - Granted: 2024-02-13 - Earliest claimed: 2021-09-08 - Assignees: Saudi Arabian Oil Company - Applicants: Saudi Arabian Oil Company - Inventors: Islam Ali Al-Baiyat - Web page: https://patentgrep.com/patent/US11898410B2 ## CPC - E21B 31/03: Freeing by flushing - E21B 44/00: Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions - E21B 21/08: Controlling or monitoring pressure or flow of drilling fluid, e.g. automatic filling of boreholes, automatic control of bottom pressure (valve arrangements therefor E21B21/10) - E21B 31/00: Fishing for or freeing objects in boreholes or wells - E21B 47/09: Locating or determining the position of objects in boreholes or wells {, e.g. the position of an extending arm}; Identifying the free or blocked portions of pipes - E21B 2200/20: Computer models or simulations, e.g. for reservoirs under production, drill bits - 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 ## Abstract A method may include determining a stuck pipe event in a well operation for a well. The method may further include obtaining well data regarding the well operation and stuck pipe data regarding the stuck pipe event. The method may further include determining, using the well data and the stuck pipe data, a diagnostic action for the stuck pipe event. The method may further include transmitting a command to a stuck pipe adapter to perform the diagnostic action. The stuck pipe adapter may be a substitute adapter for a drill string or a work string in the well. The method may further include obtaining diagnostic data regarding the stuck pipe event in response to the stuck pipe adapter performing the diagnostic action. The method may further include determining a predicted location in the well of the stuck pipe event based on the diagnostic data and a machine-learning algorithm. ## Claims ### Claim 1 A method, comprising: determining, by a computer processor, a stuck pipe event in a well operation for a well; obtaining, by the computer processor, well data regarding the well operation and stuck pipe data regarding the stuck pipe event; determining, by the computer processor and using the well data and the stuck pipe data, a diagnostic action for the stuck pipe event; transmitting, by the computer processor, a command to a stuck pipe adapter to perform the diagnostic action, wherein the stuck pipe adapter is a substitute adapter for a drill string or a work string in the well; obtaining, by the computer processor, diagnostic data regarding the stuck pipe event in response to the stuck pipe adapter performing the diagnostic action; and determining, by the computer processor, a predicted location in the well of the stuck pipe event based on the diagnostic data and a machine-learning algorithm. ### Claim 2 (depends on 1) The method of claim 1, further comprising: determining, by the computer processor, a first remediation procedure for the stuck pipe event based on the predicted location. ### Claim 3 (depends on 2) The method of claim 2, wherein the first remediation procedure is selected from a group consisting of: rotating the drill string; adjusting a weight of a drilling fluid circulating within the well; circulating fresh water within the well; sending an opener into the well to drill a predetermined wall section around a predetermined pipe section; and performing a sidetracking operation around the predetermined location of the stuck pipe event. ### Claim 4 (depends on 2) The method of claim 2, further comprising: obtaining, by the computer processor, second diagnostic data using the stuck pipe adapter in response to the first remediation operation; determining, by the computer processor and using the second diagnostic data, whether the first remediation operation freed one or more pipe sections in the stuck pipe event; and determining, based on the second diagnostic data and in response to the first remediation operation failing to free the one or more pipe sections, a second remediation operation. ### Claim 5 (depends on 2) The method of claim 2, further comprising: performing, by the stuck pipe adapter, the diagnostic action; and performing, by a control system, the first remediation procedure. ### Claim 6 (depends on 1) The method of claim 1, further comprising: obtaining a pipe stretch model, wherein the pipe stretch model is an artificial neural network that is trained using second well data, second stuck pipe data, second diagnostic data for a plurality of well operations at a plurality of wells, wherein the machine-learning algorithm is a supervised learning algorithm, and wherein the prediction location of the stuck pipe event is a depth value that is output by the pipe stretch model. ### Claim 7 (depends on 1) The method of claim 1, wherein the stuck pipe adapter comprises a processor, a communication interface, and a diagnostic assembly, and wherein the diagnostic assembly generates a predetermined amount of tension on one or more pipe sections in response to the stuck pipe adapter obtaining one or more commands from a stuck pipe manager. ### Claim 8 (depends on 1) The method of claim 1, wherein the stuck pipe event is selected from a group consisting of: a predetermined pipe cannot be removed from a wellbore without exceeding a predetermined hook load for a drilling rig; a drill string becomes embedded in a mud cake; an inability to rotate a drill string; a stationary cuttings bed forms on a side of the well; and a keyseating section forms on a side of the well. ### Claim 9 An apparatus, comprising: a computer processor; a communication interface; a plurality of sensors; a diagnostic assembly coupled to the plurality of sensors and the computer processor, wherein the diagnostic assembly is configured to apply a predetermined amount of tension in a drill string or a work string, wherein the diagnostic assembly comprises an electric motor and a lead screw, and wherein the command is transmitted by a stuck pipe manager; and a memory coupled to the computer processor, wherein the memory comprises functionality for: obtaining, over a network connection, a command to perform a diagnostic action to the drill string or the work string, generating, using the plurality of sensors and the diagnostic assembly, diagnostic data based on performing the diagnostic action, and transmitting, over the network connection, the diagnostic data. ### Claim 10 (depends on 9) The apparatus of claim 9, further comprising: a pipe connector configured to couple to a pipe section in the drill string or the work string. ### Claim 11 (depends on 9) The apparatus of claim 9, further comprising: a connector configured to couple to a substitute adapter in the drill string or the work string, wherein the substitute adapter is configured to couple to a pipe section in the drill string or work string. ### Claim 12 (depends on 9) The apparatus of claim 9, wherein the network connection is a wireless connection, and wherein the command is transmitted by a stuck pipe manager. ### Claim 13 A system, comprising: a drilling rig; a drill string coupled to the drilling rig, the drill string comprising a plurality of pipe sections; a stuck pipe adapter coupled to the drill string, the stuck pipe adapter comprises a first computer processor and a communication interface, wherein the stuck pipe adapter is configured to produce a predetermined amount of tension in at least one pipe section among the plurality of pipe sections; and a stuck pipe manager coupled to the stuck pipe adapter, the stuck pipe manager comprising a second computer processor, wherein the stuck pipe manager comprises functionality for: obtaining well data regarding a drilling operation and stuck pipe data regarding a stuck pipe event associated with the drill string; determining, using the well data and the stuck pipe data, a diagnostic action for the stuck pipe event; transmitting a command to the stuck pipe adapter that causes the stuck pipe adapter to perform the diagnostic action; obtaining diagnostic data regarding the stuck pipe event in response to the stuck pipe adapter performing the diagnostic action; and determining a predicted location in the well of the stuck pipe event based on the diagnostic data and a machine-learning algorithm. ### Claim 14 (depends on 13) The system of claim 13, further comprising: a control system coupled to the stuck pipe manager, the control system being configured to manage one or more drilling fluid properties regarding a drilling fluid circulating in the well, wherein the stuck pipe manager further comprises functionality for: determining a remediation action for the stuck pipe event based on the predicted location, and transmitting a command to the control system to perform the remediation procedure, and wherein the remediation procedure is an adjustment of a weight of a drilling fluid circulating within the well. ### Claim 15 (depends on 13) The system of claim 13, further comprising: a control system coupled to the stuck pipe manager, the control system being configured to manage a drilling operation in the well, wherein the stuck pipe manager further comprises functionality for: determining a remediation action for the stuck pipe event based on the predicted location, and transmitting a command to the control system to perform the remediation procedure, and wherein the remediation procedure is a rotation of the drill string. ### Claim 16 (depends on 13) The system of claim 13, wherein the stuck pipe manager further comprises functionality for: obtaining a pipe stretch model, wherein the pipe stretch model is an artificial neural network that is trained using second well data, second stuck pipe data, second diagnostic data for a plurality of well operations at a plurality of wells, wherein the machine-learning algorithm is a supervised learning algorithm, and wherein the prediction location of the stuck pipe event is a depth value that is output by the pipe stretch model. ### Claim 17 (depends on 13) The system of claim 13, further comprising: a user device coupled to the stuck pipe manager, wherein the user device presents, using a graphical user interface, a recommendation for a plurality of remediation procedures in response to the diagnostic action, wherein the user device obtains, in response to a user input within the graphical user interface, a user selection of a remediation procedure among the plurality of remediation procedures, and wherein the stuck pipe manager is configured to transmit a command that triggers the remediation procedure in response to the user selection. ### Claim 18 (depends on 13) The system of claim 13, wherein the stuck pipe adapter comprises a processor, a communication interface, and a diagnostic assembly, and wherein the diagnostic assembly generates a predetermined amount of tension on one or more pipe sections in response to the stuck pipe adapter obtaining one or more commands from a stuck pipe manager. ### Claim 19 (depends on 13) The system of claim 13, wherein the stuck pipe event is selected from a group consisting of: a predetermined pipe cannot be removed from a wellbore without exceeding a predetermined hook load for a drilling rig; a drill string becomes embedded in a mud cake; an inability to rotate a drill string; a stationary cuttings bed forms on a side of the well; and a keyseating section forms on a side of the well.