Digital Oil Field
The paper presents the design and successful field deployment of the first closed-loop hydraulic fracturing program.
The authors write that by replacing outdated, labor-intensive processes with an integrated, cloud-based platform, companies can streamline planning, improve accuracy, and foster better coordination across teams and vendors.
This paper presents the first global application of autonomous drilling in deepwater and the journey to reach optimal drilling parameters, integrating proprietary tools from the project’s business partners.
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Despite the recent market conditions during the last year, our industry continued to demonstrate further advances in the monitoring and surveillance field and to attest to the added value provided. -
In the past decade, fiber-optic -based sensing has opened up opportunities for in-well reservoir surveillance in the oil and gas industry. In this paper, the authors present a recent example of single-phase-flow profiling with distributed acoustic sensing.
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Since 2007, an operator in Nigeria has registered a significant increase of oil-spill events caused by sabotage and oil-theft activities. The technology presented here allows detecting and locating leaks taking place at a distance from the sensor of up to 35 km.
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For thin-oil-rim reservoirs, well placement, well type, well path, and the completion methods must be evaluated with close integration of key reservoir and production-engineering considerations.
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Many business and digital corporations claim that between 100 billion and 200 billion devices could be connected by 2020.
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Permanent downhole gauges (PDGs) provide vast amounts of pressure-transient and rate data which may be interpreted with improved pressure-transient-analysis (PTA) approaches to gain more knowledge about reservoir dynamics.
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This paper proposes a framework based on proxies and rejection sampling (filtering) to perform multiple history-matching runs with a manageable number of reservoir simulations.
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This paper describes the development of “digital-rocks” technology, in which high-resolution 3D image data are used in conjunction with advanced modeling and simulation methods to measure petrophysical rock properties.
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A new intelligent model that successfully learns from high-dimensional data and effectively identifies high-production areas and optimum lateral-re-entry candidates is presented.
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For thin-oil-rim reservoirs, well placement, type and path, and well-completion methods, should be evaluated with close integration of key reservoir- and production-engineering considerations.
