The upstream oil and gas industry requires a diverse set of political, personnel, mechanical, and technological capabilities as it possesses innumerable and voluminous data from seismic, drilling, completion, and production. In this competitive field, technical data mining and analysis are key to the creation of intelligent oilfields. However, there are major challenges associated with the generation and consumption of data in intelligent oil and gas fields, including the acquisition, storage, classification, transformation, visualization, and analysis of data.
A service company’s technical data mining application platform that has built-in analytical tools should aid field engineers in the retrieval of relevant data, as well as the analysis of data for their own requirements. Such an application, when combined with live notification capabilities, can help improve the operational productivity and lessen time lost during a job failure or any other events contributing to nonproductive time (NPT). It also would help standardize the measurement of key performance indicators across different areas or regions. Continuous surveillance and monitoring of wells, which are the basis for intelligent oilfields, help improve productivity and reduce operating costs.
This paper discusses one service company’s state-of-the-art application for big data archiving algorithms and practices that are distinctive for improving data mining in intelligent oilfields. This application acts as an enabler for extracting relevant information to improve predictive models, making more reliable decisions, and, ultimately, sustaining existing business and creating new business opportunities.
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