Presentation of Oil and Gas Spatio Temporal Big Data Visualization Techniques as Tools to Aid in Spatio Temporal Models

Marshal Wigwe, Marshall Watson

Research output: Contribution to conferencePaper

Abstract

Abstract Several oil and gas industry applications of artificial intelligence have been presented in the last decade. Machine learning techniques take center stage in most presentations. Prior to performing the actual modeling in data analytic project, the first three steps in the data analytic lifecycle involve planning, data preparation and model planning. Data visualization is an important aspect in the model planning phase as it aids in selecting variables that are important for modeling and in deciding the appropriate choice of ST model to use. Hence, it is important to invest time and resource to carry out this aspect of the project in order to delineate patterns in the dataset. Researches conducted in this area in the oil and gas industry have not maximized the power of visualizations, particularly when it comes to spatio-temporal data analysis. In this paper, we present applications of spatio-temporal exploratory data analysis for oil and gas datasets using ST-plots, applied o
Original languageEnglish
DOIs
StatePublished - Nov 6 2020

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