CO₂ Storage prospeCtive Resource Estimation Excel aNalysis (CO₂-SCREEN) User’s Manual: Python_V4.1

Technical Report · Fri Apr 08 00:00:00 EDT 2022

DOI:https://doi.org/10.2172/1862020· OSTI ID:1862020

Sanguinito, Sean ^[1]; Hanson, Angela Goodman ^[2]; Haeri, Foad ^[1]; Myshakin, Evgeniy ^[1]; Moore, Johnathan E. ^[1]; Crandall, Dustin ^[2]

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1. National Energy Technology Lab. (NETL), Pittsburgh, PA (United States); National Energy Technology Lab. (NETL), Pittsburgh, PA (United States). Site Support Contractor
2. National Energy Technology Lab. (NETL), Pittsburgh, PA (United States)

This user’s manual guides the use of the National Energy Technology Laboratory’s (NETL) CO₂ Storage prospeCtive Resource Estimation Excel aNalysis (CO₂-SCREEN) tool, which was developed to aid users in screening geologic formations for prospective CO₂ storage resources. This manual is specific to the CO₂-SCREEN 4.1 version which is based in Python. The 4.1 version of CO₂-SCREEN adds in newly updated storage efficiency factors for saline formations. CO₂-SCREEN applies U.S. Department of Energy (DOE) methods and equations for estimating prospective CO₂ storage resources for saline formations, shale formations, and residual oil zones (ROZ). CO₂-SCREEN was developed to be substantive and user-friendly and provide a consistent method for calculating prospective CO₂ storage resources. CO₂-SCREEN uses a Java- based graphical user interface (GUI) for data inputs and uses Python to calculate prospective CO₂ storage resources.

• Research Organization: National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)
• Sponsoring Organization: USDOE Office of Fossil Energy (FE)
• DOE Contract Number: 89243318CFE000003
• OSTI ID: 1862020
• Report Number(s): DOE/NETL-2022/3729
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
97 MATHEMATICS AND COMPUTING