Data mining/analysis
This paper presents a robust workflow to identify optimization opportunities in gas lift wells through real-time data analysis and a surveillance-by-exception methodology.
This work presents the development of fast predictive models and optimization methodologies to evaluate the potential of carbon-dioxide EOR and storage operations quickly in mature oil fields.
This paper introduces a system that leverages sophisticated algorithms and user-friendly interfaces to tackle the challenge of developing complex, compartmentalized reservoirs effectively.
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Always recorded but almost never used, the water hammer signal could offer completions engineers another set of insightful data if petroleum engineers can crack its code. -
The potential of big data depends on the ability of companies to change the habits of its users.
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Figuring out the right price for an active oil and gas field is tricky business in the shale sector but one producer explains how it uses data analytics to get a clearer picture.
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Permian Basin producer Callon Petroleum is attributing its data-driven approach to a routine completions practice to improved proppant placement and higher oil production.
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The oil and gas industry has a lot to gain from the adoption of big data analytics as recently highlighted examples from major service company Halliburton demonstrate.
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Through data gathering, machine learning, and the use of a supercomputer, a non-profit organization in Texas is seeking to boost oil and gas production on land owned by the states’ two largest university systems.
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The oil and gas sector is an area primed for transformational development of its operations through new digital infrastructures, GE’s CEO said in an address to technological developers and company partners.
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In a recent GE/Accenture report, surveys show that 81% of senior executives believe that big data analytics is one of the top three corporate priorities for the oil and gas industry through 2018. A striking finding was the sense of urgency felt about implementing data analytics solutions.
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IoT has become a popular phrase in various industries. For upstream oil and gas operators, an IoT infrastructure may present an opportunity improve quality control on their projects, potentially reducing costs and increasing production.
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Optimization of maintenance costs is among operators’ main concerns in the search for operational efficiency, safety, and asset availability. The ability to predict critical failures emerges as a key factor, especially when reducing logistics costs is mandatory.
