Machine Learning Based Core Data Information Management System in Oil and Gas Industry

With the continuous improvement of the accuracy of core analysis equipment, the digital core data has become increasingly abundant, and a large amount of core data information in oil and gas industry has been accumulated within the company. Thus, in order to reduce the cost of core data acquisition and improve the ability of core data sharing and intelligent analysis, this paper discussed how to build a core data information management system based on machine learning methods with information technologies in oil and gas industry. The information system architecture consists of hardware resource layer, data resource layer, data analysis layer and application layer. The hardware resource layer mainly provides the hardware and software resources for the proposed system, the data resource layer is designed for integration and management of core data information, the data analysis layer is installed with the commonly-used machine learning algorithms, and the application layer mainly completes the 2D/3D display of various data. The core functions of the system include three parts, which are data management, data classification and prediction, and data visualization and display. Through the application of the system, the problems of core analysis and data sharing are solved to a certain extent in oil and gas industry.