Virtual life meter for fracking equipment

A method comprising:

• receiving, from each fracking device of one or more fracking devices, historical characteristics corresponding to usage of a corresponding fracking device;
• defining a feature set for each fracking device of the one or more fracking devices using the historical characteristics, the feature set including a device type and a portion of the historical characteristics of the corresponding fracking device;
• generating a trained machine-learning model using the feature set corresponding to each fracking device of the one or more fracking devices;
• receiving, from each fracking device of the one or more fracking devices, operational characteristics;
• generating, using the trained machine-learning model and the operational characteristics, a service object for each fracking device of the one or more fracking devices, wherein the service object indicates an expected operational life of the fracking device and an amount of time remaining until a failure is expected to occur;
• receiving, from a remote computing device, a request for a portion of operational characteristics associated with a particular fracking device of the one or more fracking devices;
• and
• transmitting, to the remote computing device, a representation of the service object corresponding to the particular fracking device in response to receiving the request, the representation of the service object for use to determine an interval of time over which to initiate or cease a wellbore operation.

A non-transitory computer-readable medium including instructions that are executable by one or more processors to cause the one or more processors to preform operations including:

• receiving, from each fracking device of one or more fracking devices, historical characteristics corresponding to usage of a corresponding fracking device;
• defining a feature set for each fracking device of the one or more fracking devices using the historical characteristics, the feature set including a device type and a portion of the historical characteristics of the corresponding fracking device;
• generating a trained machine-learning model using the feature set corresponding to each fracking device of the one or more fracking devices;
• receiving, from each fracking device of the one or more fracking devices, operational characteristics;
• generating, using the trained machine-learning model and the operational characteristics, a service object for each fracking device of the one or more fracking devices, wherein the service object indicates an expected operational life of the fracking device and an amount of time remaining until a failure is expected to occur;
• receiving, from a remote computing device, a request for a portion of operational characteristics associated with a particular fracking device of the one or more fracking devices;
• and
• transmitting, to the remote computing device, a representation of the service object corresponding to the particular fracking device in response to receiving the request, the representation of the service object for use to determine an interval of time over which to initiate or cease a wellbore operation.