# US 2025/0093544 A1 · Machine learning and physics fusion modeling on run duration > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2025/0093544 A1 - Document ID: US20250093544A1 - Status: Published application - Kind: A1 - Application number: 18/467,051 - Filed: 2023-09-14 - Published: 2025-03-20 - Earliest claimed: 2023-09-14 - Assignees: Schlumberger Technology Corporation - Applicants: Schlumberger Technology Corporation - Inventors: Wei Li; Wenrui Li; Yang Zhang; Lihui Meng; Pan Xi; Dawei Xu; Daniel Gemmell - Web page: https://patentgrep.com/patent/US20250093544A1 ## CPC - E21B 47/00: Survey of boreholes or wells (monitoring pressure or flow of drilling fluid E21B21/08) - G01V 1/50: Analysing data - G01V 1/46: Data acquisition - 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 - G01V 2210/74: Visualisation of seismic data - E21B: EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS - G01V: GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS (means for indicating the location of accidentally buried, e.g. snow-buried, persons A63B29/02) ## Abstract Embodiments presented provide for modeling of wireline runs for hydrocarbon recovery operations. In embodiments, a run duration of wireline activities is split into a winch duration and a pass duration, wherein the pass duration is calculated using a machine learning model. ## Claims ### Claim 1 A method for estimating a run duration time of a wireline activity, comprising: gathering data related to a wellbore; gathering data related to a wellbore conveyance; separating the run duration into a winch duration time and a logging duration time, wherein the winch duration time is calculated according to an algorithm; feeding the data related to the wellbore and wireline tools to be used for scanning a section of the wellbore into a model; calculating the logging duration time according to the model; and calculating the run duration time of the wireline activity based upon the winch duration time and the logging duration time. ### Claim 2 (depends on 1) The method according to claim 1, wherein the gathering the data related to the wellbore includes at least one of a wellbore length, a wellbore diameter, a wellbore shoe length and a length of wireline wellbore to be analyzed by the wireline activity. ### Claim 3 (depends on 1) The method according to claim 1, wherein the wellbore conveyance is a wireline truck. ### Claim 4 (depends on 1) The method according to claim 1, wherein the gathering of the data to the wellbore conveyance includes a maximum speed of travel. ### Claim 5 (depends on 1) The method according to claim 1, wherein the algorithm includes a maximum speed per section of the wellbore for drawing and a distance of wellbore that the maximum speed per section of wellbore is drawn. ### Claim 6 (depends on 1) The method according to claim 1, wherein the algorithm separates a wellbore length into separate sections. ### Claim 7 (depends on 6) The method according to claim 6, wherein the separate sections include at least a shoe section, a casing section and an open wellbore section. ### Claim 8 (depends on 1) The method according to claim 1, wherein the calculating the run duration time of the wireline activity based upon the winch duration time and the logging duration time is accomplished through addition. ### Claim 9 (depends on 1) The method according to claim 1, wherein the feeding the data related to the wellbore includes entering geological properties encountered by the wellbore. ### Claim 10 (depends on 1) The method according to claim 1, wherein the calculating the logging duration time according to the model involves at least two uses of wireline downhole tools. ### Claim 11 (depends on 1) The method according to claim 1, wherein the model uses artificial intelligence. ### Claim 12 (depends on 11) The method according to claim 11, wherein the model has at least two nodal layers. ### Claim 13 (depends on 11) The method according to claim 11, wherein the model uses data of prior wireline activities to calculate the logging duration. ### Claim 14 (depends on 1) The method according to claim 1, further comprising: storing the calculated run duration time in a non-volatile memory. ### Claim 15 (depends on 1) The method according to claim 1, further comprising displaying the calculated run duration time on a monitor. ### Claim 16 An article of manufacture that is configured to store instructions readable by a computer, the instructions including a method for estimating a run duration time of a wireline activity, comprising: gathering data related to a wellbore; gathering data related to a wellbore conveyance; separating the run duration into a winch duration time and a logging duration time, wherein the winch duration time is calculated according to an algorithm; feeding the data related to the wellbore and wireline tools to be used for scanning a section of the wellbore into a model; calculating the logging duration time according to the model; and calculating the run duration time of the wireline activity based upon the winch duration time and the logging duration time. ### Claim 17 (depends on 16) The article of manufacture according to claim 16, wherein the article of manufacture is one of a compact disk, a universal serial bus storage device and a solid state drive. ### Claim 18 (depends on 16) The article of manufacture according to claim 16, wherein the method stored on the article of manufacture wherein the algorithm separates a wellbore length into separate sections. ### Claim 19 (depends on 18) The article of manufacture according to claim 18, wherein the separate sections include at least a shoe section, a casing section and an open wellbore section. ### Claim 20 (depends on 16) The article of manufacture according to claim 16, wherein the model uses artificial intelligence.