Subsurface Analysis Archives - KeyLogic

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

Harry McKinney — Thu, 26 Aug 2021 04:37:29 +0000

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 otherwise not been evaluated concurrently. This study introduces an ensembled framework that couples a data-driven ML predictive model capable estimating a productivity indicator for unconventional O&G horizontal wells that correlates to estimated ultimate recovery (EUR) with a well design optimization approach that maximizes productivity.

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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

Harry McKinney — Thu, 26 Aug 2021 04:35:29 +0000

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 future applicants, to assist LPO in its review of CO2 injection and storage projects, and to inform the public. The report documents that the CO2 injection and storage process is broadly regarded as a safe endeavor if it is properly managed.

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

Harry McKinney — Thu, 26 Aug 2021 04:28:16 +0000

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 States. Changes in economic market and policy conditions are evaluated over a series of scenarios in which differences in the levelized cost of electricity (LCOE) provide estimates of the financial gap necessary to overcome for CCS to be considered the cost-minimizing choice for each power generation facility type considered.

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