Well Data Labs, Inc.

Carly T Wolfbrandt

Jessica G Iriarte Lopez

Samid Ameer Hoda

Alberto J Ramirez Ramirez

Mary S Van Domelen

One or more aspects of the present disclosure are directed to cloud based applications that automatically and quickly identify start and end times of fracturing stages in real-time as well as one or more additional performance characteristics of the fracturing process. In one aspect, a method for real-time analysis of well data includes receiving treating data for a well in real-time, the treating data including one or more of a treating pressure channel and a slurry rate channel; preprocessing the treating data; identifying one or more stages of one or more fracturing processes in association with which the treating data is received; identifying, automatically and in real-time, a start time and an end time for each of the one or more stages; and generating a visual output of the start time and the end time of each of the one or more stages.

Real-time analysis of in-field collected well fracturing data

A method of mapping unknown well data channels involves generating, with a processor, summary statistics for unknown sequences of well data values where the well data values pertain to respective particular types of data and where each type belongs to a category of well data. The system processes the respective summary statistics with a trained super model to classify the respective sequences of well data values into categories of well data. The system then processes the summary statistics for a given sequence using a trained sub-model of the category to which the sequence belongs in order to further classify the sequence as to its particular type within the category thereby mapping originally unknown sequences of well data values to the correct category and type of well data.

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Denver, CO, United States of America

Carly T Wolfbrandt