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Subsurface Trend Analysis 2D Tool
OwnerNational Energy Technology Laboratory (NETL) - view all
Update frequencyunknown
Last updatedabout 1 year ago
Format
Overview

STA Tool – a virtual research assistant designed to: • Organize and visualize disparate big data and knowledge resources • Simplify geologic domain formation • Provide and execute multi-dimensional statistical analyses and validation • Utilize ML to characterize property trends and predictions The Subsurface Trend Analysis (STA) Tool utilizes the STA method as a framework for integrating machine learning and artificial intelligence to accelerate subsurface analyses. The Subsurface Trend Analysis method (Rose et al., 2020) is a validated methodology that improves prediction of subsurface properties, even in areas with little to no data. This download includes the 2D version of the STA Tool. A 3D version is forthcoming. This work was conducted under the Advanced Offshore Research Portfolio, FWP Number 1022409 at National Energy Technology Laboratory, U.S. Dept. of Energy. For more information: https://edx.netl.doe.gov/offshore/portfolio-items/geohazards-subsurface-uncertainty-modeling/ Rose, K., Bauer, J.R., and Mark-Moser, M., “A Systematic, Science-Driven Approach for Predicting Subsurface Properties,” Interpretation, 8:1 (2020), 167–181, https://doi.org/10.1190/INT-2019-0019.1.

AIMLGeostatistical AnalysisReservoir PropertiesSubsurface Characterizationsoftwaresubsurface trend analysis
Additional Information
KeyValue
citationMacKenzie Mark-Moser, Patrick Wingo, Dakota Zaengle, Scott Pantaleone, Chukwuemeka Okoli, jacob shay, Kelly Rose, Anuj Suhag, Brendan Hoover, Thomas Martin, Subsurface Trend Analysis 2D Tool, 10/20/2022, https://edx.netl.doe.gov/dataset/subsurface-trend-analysis-2d-tool
geospatialno
netl_productyes
poc_emailjimmy.thornton@netl.doe.gov
point_of_contactJimmy Thornton
program_or_projectAdvanced Offshore Research
project_number1022409
publication_date2022-09-29
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