Abstract

In 2019, The United States Department of Energy created four new regional carbon storage partnerships following the success of the previous regional partnership program established in 2003. The new partnerships are designed to accelerate development of commercial storage projects in the United States. The Carbon Utilization and Storage Partnership of the Western United States (CUSP) was formed as an outgrowth of three of the former partnerships: The Southwest Regional Partnership on Carbon Sequestration; the WestCArb partnership; and the Big Sky Partnership (see map). The CUSP primary objective is to catalog, analyze and rank CCUS options for parts or all of 13 states that make up the contiguous western USA. The multi-state CUSP team and project coordinates the capabilities, experience, data collection methods and advanced modelling tools developed and refined through several decades of efforts via many previous NETL-sponsored projects. The CUSP team seeks to accelerate CCUS technology development and deployment in the Western U.S., with a Partnership that consists of 13 universities, seven geological surveys, three research institutes and three national laboratories. Goals of the CUSP project include assembly of existing CCUS data into a uniform database, and increased data collection and analysis of new data not yet present in EDX, NATCARB or other databases. Additionally, the CUSP seeks improvement of modeling tools used for risk prediction and economic scenario analysis, and identification of major technical challenges and development of CCUS deployment readiness indices. One primary deliverable of the CUSP project maps, interactive software and data products that delineate not only regions and specific targets that have the best prospects for commercially-viable CCUS, but also highlight technical challenges and their effects on CCUS development. Other products include analysis tools and large data sets tailored for machine learning efforts via the new DOE initiative on machine learning. These goals are being accomplished by updating existing data (for example, CO2 storage data collected during the creation of the National Carbon Atlas, EPA CO2 source data, and pipeline and infrastructure data), augmenting and refining that data where gaps are identified, and feeding the data into various analytical and optimization models to create a series of readiness indices for the Western Region of the United States. In addition to reducing geological characterization uncertainty, particularly for stacked storage reservoirs (saline+EOR), the project is incorporating a variety of soft data into models that will help identify the best prospects for commercially-viable CCUS and help quantify potential economic impact. This effort provides targeted regions with the most promising combination of geology, geography and infrastructure and industrial sectors for short term, mid-term, and long-term CCUS projects, and identifies improvements necessary for maximizing success and assess scenarios that can swiftly and cost-effectively graduate potential projects to short-term status. Via SimCCS and additional desktop-based software tools, dynamic readiness mapping are developed and verified, modified as needed, and distributed. Use of these tools are supported by educational workshops and online training materials. Finally, the CUSP Partnership is participating in a variety of technology transfer programs to help facilitate regional efforts to guide and develop policies and permitting mechanisms to further CCUS in this region. The benefits of the CUSP project include improving the quality and interoperability of existing data, incorporation of more extensive, and detailed, technical as well as soft data into very large data sets for Machine Learning efforts, and using local and regional expertise to continue and improve technology transfer and stimulate stakeholder interest and knowledge of CCUS. Progress to date for major objectives will be presented, including preliminary heat maps of CCS/CCUS potential in the western United States.

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