Citas bibligráficas
Alama, A., (2022). Análisis y procesamiento de datos (Big Data) para la toma de decisiones utilizando la base de datos Perupetro (MDS) [Trabajo de suficiencia profesional, Universidad Nacional de Ingeniería]. http://hdl.handle.net/20.500.14076/22514
Alama, A., Análisis y procesamiento de datos (Big Data) para la toma de decisiones utilizando la base de datos Perupetro (MDS) [Trabajo de suficiencia profesional]. PE: Universidad Nacional de Ingeniería; 2022. http://hdl.handle.net/20.500.14076/22514
@misc{renati/712041,
title = "Análisis y procesamiento de datos (Big Data) para la toma de decisiones utilizando la base de datos Perupetro (MDS)",
author = "Alama Otaegui, Alonso Wilfredo",
publisher = "Universidad Nacional de Ingeniería",
year = "2022"
}
Today's operating companies are inundated with large and growing volumes of digital well data. Wells today not only generate electrical log data faster than ever, but the number of cores, surveys and petrophysical analysis is also increasing, while advanced downhole tools are capturing more sophisticated information, including real-time data, in many different formats. And that's just new drilling data, oil and gas companies can have thousands of historical wells and a large number of legacy data files scattered throughout the organization. Achieving efficient and timely well data management (Big Data) is fast becoming one of the most strategic challenges facing geoscientists, asset managers, E&P data managers, and IT personnel around the world. In this report I will develop or present the usefulness of the MDS database which is made up of the PETROBANK and RECALL applications for the storage of well information (electrical records, digital files, surveys, well seismic and reports) all this within of a total called Peru Petroleum Big Data which is managed within the state company Perupetro. Like any study, to be feasible, it must be technical, operational, and profitable, for which the study is based on the cost of applying the new technology, as well as the study on the use fulness of this database as an alternative to generate statistical tables, intelligent searches that help investment companies to obtain all the necessary information to make the decision to invest in an area of interest.
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