Machine learning based automatic marker separation

A system for automatically separating geological markers associated with well log data, the system comprising:

• a computer processor;
• and
• memory storing instructions that are executable by the computer processor to:
• receive well log data captured by one or more sensors disposed within a wellbore of a well at a resource site,
• generate a marker time series window for the well log data, the marker time series window being applied to select one or more data samples within the well log data to generate a first windowed dataset of the well log data,
• mask one or more data elements of the first windowed dataset of the well log data to generate a masked windowed dataset, such that the one or more data elements of the first windowed dataset comprise data elements in a first dimension,
• configure a transformer model using the masked windowed dataset of the well log data,
• execute a minimization operation on encoder output data to generate minimized data in a second dimension in response to generating the encoder output data based on applying a second windowed dataset to the data encoder of the transformer model, and
• automatically execute a clustering operation on the minimized data, the clustering operation including aggregating together, one or more geological markers comprised in the plurality of geological markers.

A computer program comprising instructions, that when executed by a computer processor of a computing device, causes the computing device to:

• receive well log data captured by one or more sensors disposed within a wellbore of a well at a resource site;
• generate a marker time series window for the well log data, the marker time series window being applied to select one or more data samples within the well log data to generate a first windowed dataset of the well log data;
• mask one or more data elements of the first windowed dataset of the well log data to generate a masked windowed dataset, such that the one or more data elements of the first windowed dataset comprise data elements in a first dimension;
• configure a transformer model using the masked windowed dataset of the well log data;
• execute a minimization operation on the encoder output data to generate minimized data in a second dimension in response to generating encoder output data based on applying a second windowed dataset to the data encoder of the transformer model;
• and
• automatically execute a clustering operation on the minimized data, the clustering operation including aggregating together, one or more geological markers comprised in the plurality of geological markers.