Well completion operations intelligent advisory based on dimension embedding
Abstract:
Systems and methods include a method for providing plots for challenges, successes, and failures in well completions. A challenges-successes-failures database is created from historical data collected from past well completions. The database identifies: 1) challenges encountered during well completions, 2) corresponding successes and failures, and 3) job parameters used during well completions. A dimension embedding algorithm is selected to represent the data. Hyper-parameter tuning is performed on the algorithm. The dimension embedding model is generated and added to a system pipeline for a new well completion job. Nonlinear dimension embedding algorithms are run against data points in the cleaned and processed data using the challenges-successes-failures database and new job parameters entered in a user interface. Scatter plots of two-dimensional (2D) points are generated and labeled with each point's job parameters.
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