Advanced Analytics

Convolutional Neural Networks on Field Programmable Gate Arrays

Advanced Analytics, Digital Transformation /

KeyLogic data scientists and embedded system software engineers are rewriting convolutional neural network (CNN) algorithms to operate smoothly and efficiently on field programmable-gate arrays (FPGAs). More than standard CPUs and even graphical processing units (GPUs), FPGAs have the capacity to massively accelerate deep learning algorithms on very low power, restricted weight, edge devices for computer […]

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Published paper in Journal of Natural Gas Science and Engineering on evaluation of production drivers in the Marcellus Shale using machine learning approaches

Advanced Analytics, Publication, Systems Research and Analysis / ,

Artificial intelligence and machine learning (ML) are being applied to many oil and gas (O&G) applications and seen as novel techniques that may facilitate efficiency gains in exploration and production operations. Significant improvements in that regard are likely to occur when ML can be applied to evaluate O&G challenges with inherent synergies that may have

Published paper in Journal of Natural Gas Science and Engineering on evaluation of production drivers in the Marcellus Shale using machine learning approaches Read More »

News release by DOE’s Loan Program office featuring report compiled by KeyLogic and partners on evaluating the potential environmental impacts and compliance best practices for carbon capture and storage

Advanced Analytics, Mission Management, Publication, Systems Research and Analysis / ,

The Loan Programs Office (LPO) takes its role in protecting taxpayer interests very seriously, including evaluating the potential impacts of projects in accordance with the National Environmental Policy Act (NEPA).  Given the growth of interest in the carbon capture utilization & sequestration (CCUS) sector, LPO’s Environmental Compliance Division prepared a report as a reference for

News release by DOE’s Loan Program office featuring report compiled by KeyLogic and partners on evaluating the potential environmental impacts and compliance best practices for carbon capture and storage Read More »

“Featured paper” published in Energies Special Issue on Alternative Energy Policy

Advanced Analytics, Publication, Systems Research and Analysis / , ,

This paper evaluates how changes in economic market and policy conditions, including the establishment of a per-unit tax on unabated emissions of carbon dioxide (CO2) set equal to estimates of the social cost of carbon (SCC), influence the economics of carbon capture and storage (CCS) for two hypothetical power generation facilities located in the United

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Using Common Boundaries to Assess Methane Emissions: A Life Cycle Evaluation of Natural Gas and Coal Power Systems

Advanced Analytics, Mission Management, Publication, Systems Research and Analysis / , , ,

There is consensus on the importance of upstream methane (CH4) emissions to the life cycle greenhouse gas (GHG) footprint of natural gas systems, but inconsistencies among recent studies explain why some researchers calculate a CH4 emission rate of less than 1% whereas others calculate a CH4 emission rate as high as 10%. These inconsistencies arise from differences

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Designing an Integrated Energy Modeling Platform

Advanced Analytics, Systems Research and Analysis / ,

OnLocation Inc (a KeyLogic company) successfully designed an Integrated Energy Modeling Platform for a global petroleum and gas company.   The integrated energy modeling platform will bring 12 (twelve!) disparate models together and act as a comprehensive simulation tool to run scenarios and identify risks and opportunities. Corporate planners will be able to study energy supply, demand,

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Analysis of Regional Approaches to Reducing CO2 Emissions

Advanced Analytics, Mission Management, Systems Research and Analysis / ,

Client Challenge: How to build an understanding of the potential impact on the power supply system if states used a mix of regional CO2 policies, some emission rate-based and others mass-based, to meet the requirements of the EPA’s proposed Clean Power Plan. Solution: We designed a set of model scenarios using an enhanced version of NEMS created by

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