Assisted business intelligence on performance of complex assets with taxonomy of real time systems

A system for analyzing a performance of an asset in a petroleum service environment, comprising:

• an interface configured to receive a signal from an unknown source of a petroleum service environment, wherein the signal is transmitted by a transmitter using a communication protocol;
• and
• at least one processor connected to the interface to perform operations that include:
• automatically determining characteristics of the signal from one or more values of the signal, wherein the characteristics include a sampling rate and a value range of the signal, and
• automatically deducing a source of the signal using the characteristics of the signal, wherein the automatically deducing includes determining a range-based category of the signal using the sampling rate and the value range of the signal, normalizing the one or more values of the signal, extracting a feature of the signal by applying a transformation to the normalized values of the signal, correlating the extracted features with known sensors of petroleum service environments, reinforcing the correlating by comparing identified signals from a particular sensor of the petroleum service environment with the correlated known sensors, and identifying the particular sensor as the source of the received signal.

A system for automatically deducing a source of signals in a petroleum service environment, comprising:

• one or more processors to perform operations that include:
• receiving a data stream generated from an unknown source of a petroleum service environment, wherein the data stream is transmitted by a transmitter;
• obtaining one or more values of the signal by observing the signal,
• automatically determining a sampling rate and a value range of the signal from the one or more values,
• classify the signal within one or more categories according to at least the sampling rate and the value range,
• normalizing the one or more values of the signal,
• extracting a feature of the signal by applying a transformation to the normalized one or more values of the signal,
• correlating the extracted feature with known sources using a trained machine learning model trained using historic sensor signals of petroleum service environments to determine correlations between sensors of the petroleum service environments and signals based on features of the signals,
• identifying possible sources of the signal from the known sources using previously identified sensor signals,
• selecting one or more generic taxonomic types of the possible sources using the categories,
• automatically deducing a source of the signal from the possible sources of the signal by observing the signal over at least one contextual event involving the one or more generic taxonomic types of the possible sources, and
• controlling one or more assets of the petroleum service environment associated with the source according to an analysis based on the one or more values and the one or more generic taxonomic types.