Data & Analytics
Autonomous drilling through managed pressure drilling (MPD) at the Atlantis field has given the operator confidence to scale the method.
The cloud platform provider said the initiative is designed to help energy companies manage and analyze large-scale operational data.
Major increases in hydrocarbon production require both incremental and revolutionary technologies, industry leaders said during the SPE Hydraulic Fracturing Technology Conference.
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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. -
Visualization technology has played a key role in reducing operational expenditure (OPEX) and improving collaboration, thus maximizing uptime across the industry throughout the asset life cycle.
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A recently released report predicted that IoT networks will not take up as much of the overall market share as previously anticipated.
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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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AUVs have evolved from an emerging technology with niche uses to a viable solution and an established part of operations in various marine sectors. Douglas-Westwood’s AUV Market Forecast considers the prospective demand for AUVs in the commercial, military and research sectors over the next 5 years.
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Big ideas for digital intelligence in Oil and Gas are being discussed at ATCE.
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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.
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The difficulty in applying traditional reservoir-simulation and -modeling techniques for unconventional-reservoir forecasting is often related to the systematic time variations in production-decline rates. This paper proposes a nonparametric statistical approach to resolve this difficulty.
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Managing an unconventional asset requires the proper analysis of large amounts of data. How can unconventional asset operators utilize data processing technologies commonly used in other industries?
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The oil and gas industry is facing an invasion of data analytics startups who saw a wide-open gap in the market a few years ago when talk of big data first began.
