Abstract: A method comprises selecting at least one wellbore variable of a wellbore operation and for each of two or more machine learning models, training each respective machine learning model with a respective set of training data values of the at least one wellbore variable detected in a respective different time interval. The method comprises for each of the two or more machine learning models, processing, for each of the at least one wellbore variable, a set of data samples of the respective at least one wellbore variable using each of the two or more trained machine learning models to output a respective model output response for each data sample of a set of data samples.

Abstract: Some implementations include a method for controlling a computer system configured to detect scaling and/or plugging of an electric submersible pump (ESP) deployed in a wellbore. The method may include determining, based on a measurement of pressure in the wellbore, a required total dynamic head (RTDH) for the ESP while the ESP is operating in the wellbore. The method also may include determining, based on information from one or more sensors in the ESP, a produced total dynamic head (PTDH) for the ESP while the ESP is operating in the wellbore. The method also may include detecting scaling status or plugging status of the ESP based on the RTDH and the PTDH.

Abstract: A method of testing an electrical submersible pump (ESP) component may include placing an ESP component in a transport assembly at a first location for transport to a second location. The ESP component may be tested or maintained while the ESP component remains in the transport assembly, before being deployed at a wellsite. The ESP components can be prepared in the transport assembly to be lifted (including placement of lifting clamps) to run in hole. In various embodiment, the transport assembly may comprise the ESP component and a transport basket configured for stacking multiple transport assemblies.

Abstract: A method of testing an electrical submersible pump (ESP) component may include placing an ESP component in a transport assembly at a first location for transport to a second location. The ESP component may be tested or maintained while the ESP component remains in the transport assembly, before being deployed at a wellsite. The ESP components can be prepared in the transport assembly to be lifted (including placement of lifting clamps) to run in hole. In various embodiment, the transport assembly may comprise the ESP component and a transport basket configured for stacking multiple transport assemblies.

Abstract: Aspects of the subject technology relate to systems, methods, and computer-readable media for identifying a wellbore pressure based on a predicted pump intake loss. A pump intake pressure after an intake for a submersible pump deployed downhole in a wellbore is identified. An intake loss prediction model for identifying a virtual intake loss associated with the intake for the submersible pump as a function of one or more intake loss parameters is accessed. The virtual intake loss is identified by applying the intake loss prediction model based on intake loss prediction input of the one or more intake loss parameters. A pump intake pressure before the intake for the submersible pump is determined based on the virtual intake loss and the identified pump intake pressure after the intake.

Abstract: A method of testing an electrical submersible pump (ESP) component may include placing an ESP component in a transport assembly at a first location for transport to a second location. The ESP component may be tested or maintained while the ESP component remains in the transport assembly, before being deployed at a wellsite. The ESP components can be prepared in the transport assembly to be lifted (including placement of lifting clamps) to run in hole. In various embodiment, the transport assembly may comprise the ESP component and a transport basket configured for stacking multiple transport assemblies.