Distributed control system using asynchronous services in a wellbore

    公开(公告)号:US11352874B2

    公开(公告)日:2022-06-07

    申请号:US16473134

    申请日:2018-12-07

    Abstract: Certain aspects and features relate to a system that efficiently determines optimal actuator set points to satisfy an objective in controlling equipment such as systems for drilling, production, completion or other operations associated with oil or gas production from a wellbore. A platform can receive data and also make use of and communicate with multiple algorithms asynchronously and efficiently to project automatic optimum set points for controllable parameters. Services can provide data over a real-time messaging bus and the data can be captured by an orchestrator that aggregates all data and calls a solver orchestrator to determine optimized parameters for a current state in time to send to control systems or display in a dashboard.

    Automated optimization of real-time data frequency for modeling drilling operations

    公开(公告)号:US11492892B2

    公开(公告)日:2022-11-08

    申请号:US16652336

    申请日:2019-05-16

    Abstract: Systems and methods can automatically and dynamically determine an optimum frequency for data being input into a drilling optimization tool in order to provide predictive modeling for well drilling operations. The methods and systems selectively input sets of data having different frequencies into the drilling optimization tool to build different predictive models at different frequencies. An optimization algorithm such as Bayesian optimization is then applied to the models to identify in real time an optimum frequency for the data sets being input into the drilling optimization tool based on current operational and environmental parameters.

    EVENT PREDICTION USING STATE-SPACE MAPPING DURING DRILLING OPERATIONS

    公开(公告)号:US20220003108A1

    公开(公告)日:2022-01-06

    申请号:US17256164

    申请日:2020-02-03

    Abstract: System and methods for event prediction during drilling operations are provided. Regression data associated with coefficients of a predictive model are retrieved for a downhole event during a drilling operation along a planned path of a wellbore. The regression data includes a record of changes in historical coefficient values associated with prior occurrences of the event. As the wellbore is drilled over different stages of the operation, a value of an operating variable is estimated based on values of the coefficients and real-time data acquired during each stage. A percentage change in coefficient values adjusted between successive stages of the operation is tracked. An occurrence of the downhole event is estimated, based on a correlation between the percentage change tracked for at least one coefficient and a corresponding change in the historical coefficient values. The path of the wellbore is adjusted, based on the estimated occurrence of the event.

    SELF-ADAPTING DIGITAL TWINS
    5.
    发明申请

    公开(公告)号:US20210404328A1

    公开(公告)日:2021-12-30

    申请号:US16764240

    申请日:2019-05-15

    Abstract: A system and method can be used for implementing self-adapting digital twins. The system may include operations for estimate a state matrix characterizing behavior of a hydrocarbon recovery process implemented by a hydrocarbon recovery tool. Observed values of one or more sensors for at least one process parameter may be obtained from sensors deployed throughout the drilling environment. These sensors may be physical sensors acquiring information about physical changes within the drilling environment; and processes monitoring output of system functions and/or other processes. A data assimilation tool may be applied to the estimated state matrix and the observed values to produce an updated state matrix. The updated state matrix may be used as the previous state matrix in a subsequent time step, thus implementing a self-adapting digital twin model.

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