Application of Big Data analysis systems for drilling operations optimization

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Dzhafarov, R. (2019). Application of Big Data analysis systems for drilling operations optimization. [Master's Thesis, Montanuniversitaet Leoben (000)].

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@mastersthesis{0b475eca97094b93bab22f4ff9cb6748,
title = "Application of Big Data analysis systems for drilling operations optimization",
abstract = "In the conditions of market uncertainty, unstable oil price and development of oil and gas field with complex geological structure, the tasks of optimization and costs reduction for well construction become especially relevant for oil and gas producing and drilling service companies. The current situation is forcing companies to reduce volumes of drilling and abandon a number of planned projects. The time spent for a well construction basically depends on drilling crews{\textquoteright} qualification and coordinated work of all service organizations involved in the process. The means of increasing the work speed are not only transition to the use of more sophisticated equipment, but also rational and efficient organization of all processes. The thesis focuses on costs reduction for a well drilled by Gazprom EP International, which could be achieved with mud logging data processing using the ProNova data analysis system. Key features, advantages and disadvantages of the technology are discussed and potential time savings are calculated.",
keywords = "automatization, Key Performance Indicators, crew performance efficiency, time & cost savings, Automatisierung, Leistungsindikatoren, wirksame Leistung, Zeit- und Kosteneinsparung",
author = "Renat Dzhafarov",
note = "no embargo",
year = "2019",
language = "English",
school = "Montanuniversitaet Leoben (000)",

}

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TY - THES

T1 - Application of Big Data analysis systems for drilling operations optimization

AU - Dzhafarov, Renat

N1 - no embargo

PY - 2019

Y1 - 2019

N2 - In the conditions of market uncertainty, unstable oil price and development of oil and gas field with complex geological structure, the tasks of optimization and costs reduction for well construction become especially relevant for oil and gas producing and drilling service companies. The current situation is forcing companies to reduce volumes of drilling and abandon a number of planned projects. The time spent for a well construction basically depends on drilling crews’ qualification and coordinated work of all service organizations involved in the process. The means of increasing the work speed are not only transition to the use of more sophisticated equipment, but also rational and efficient organization of all processes. The thesis focuses on costs reduction for a well drilled by Gazprom EP International, which could be achieved with mud logging data processing using the ProNova data analysis system. Key features, advantages and disadvantages of the technology are discussed and potential time savings are calculated.

AB - In the conditions of market uncertainty, unstable oil price and development of oil and gas field with complex geological structure, the tasks of optimization and costs reduction for well construction become especially relevant for oil and gas producing and drilling service companies. The current situation is forcing companies to reduce volumes of drilling and abandon a number of planned projects. The time spent for a well construction basically depends on drilling crews’ qualification and coordinated work of all service organizations involved in the process. The means of increasing the work speed are not only transition to the use of more sophisticated equipment, but also rational and efficient organization of all processes. The thesis focuses on costs reduction for a well drilled by Gazprom EP International, which could be achieved with mud logging data processing using the ProNova data analysis system. Key features, advantages and disadvantages of the technology are discussed and potential time savings are calculated.

KW - automatization

KW - Key Performance Indicators

KW - crew performance efficiency

KW - time & cost savings

KW - Automatisierung

KW - Leistungsindikatoren

KW - wirksame Leistung

KW - Zeit- und Kosteneinsparung

M3 - Master's Thesis

ER -