Asset Management
Winners of Alberta's Drilling Technology Challenge cover a range of technologies from robotics to enhance drilling rig safety to AI-enabled energy management, downhole sensing, well navigation, hybrid power systems, and geothermal energy.
The transaction broadens the company's North Sea footprint with long-life assets that boost production and reserves.
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Formerly titled E&P Notes, this monthly snapshot of global E&P activity highlights ongoing developments worldwide. -
This paper establishes that the use of a dual-gradient fluid column during the running of large casing in an extreme-reach deepwater well is an effective method to overcome drag and enable the casing to reach total depth.
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The authors write that by replacing outdated, labor-intensive processes with an integrated, cloud-based platform, companies can streamline planning, improve accuracy, and foster better coordination across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.
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The authors write that deployment of artificial-intelligence-based high-gas/oil ratio well-control technology enabled stabilization of well performance and maintenance of optimal production conditions.
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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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In this paper, a case study is described in which a software solution enabled prescriptive optimization of well delivery using a physics-informed machine-learning approach for predictive identification and characterization of well-construction risks.
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The paper describes the revalidation of a deepwater prospect that resulted in a no-drill decision.
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This paper describes the integration of iterative torque/drag/buckling and hydraulic simulations for multiple tapered string combinations, the results of which guided the selection of a string configuration that deemed planned well total depths feasible.
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The oilfield service company said its emissions reductions are thanks in part to the increased use of renewable energy and operation efficiencies.
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The companies also agreed to collaborate on new AI models to unlock further insights from S&P Global Energy’s upstream data.
