Saudi Arabian Oil Company

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Abdullah Mohammed Alabdullatif

Dalal Abadi Alharbi

Yaqeen A Mahdi

Sarafudheen M Veettil Tharayi

Abdullah Yousef Bukhamsin

Nadim Sohail

Yaqeen Abdullah Al Mahdi

A method for intelligent maintenance services using machine learning involves obtaining maintenance tickets associated with an industrial operation. The maintenance tickets include unstructured text. The method further involves, for each of the maintenance tickets, performing, by one or more computer processors, a natural language processing of the unstructured text to extract features, and generating, by the computer processor, a topic model for the maintenance tickets, based on the features. The topic model represents each of the maintenance tickets by a collection of topics. The method also involves applying the topic model to obtain maintenance insights for the industrial operation.

Method and system for intelligent maintenance services using machine learning

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.

Well completion operations intelligent advisory based on dimension embedding

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Dhahran, Saudi Arabia

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