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Hidden Geothermal Signatures of the Southwest New Mexico

Velimir V. VESSELINOV, Bulbul AHMMED, Maruti K. MUDUNURU, Satish KARRA, Richard MIDDLETON

Key words
new mexico, geothermal, big data, nmfk, hidden geothermal signals
Conference
World Geothermal Congress
Year
2020
Session
Big Data and Data Analytics
Language
English
Paper number
32011

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Abstract

In Play Fairway Analysis (PFA)s Phase-I Project funding by the U.S. Department of Energy’s Geothermal Technologies Office, we identified four potential regions for exploration of new geothermal resources in the southwest NM (SWNM). These regions include Colorado Plateau, Volcanic Field, Rio Grande Rift, and Basin and Range Province. They are known to have moderate- and high-temperature geothermal resources (e.g., more than 60oC) in operation. Moreover, based on the outcomes of the PFA Phase-I, these regions are also known to have hidden geothermal systems. The objective of this study is to find the signatures of the hidden geothermal systems and future data collection locations to efficiently explore and develop geothermal resources in the SWNM region. To achieve this, we combine datasets from these four distinct regions. A dataset is generated to perform advanced data analysis to find hidden geothermal signatures. An unsupervised machine learning technique called non-negative matrix factorization with customized k-means clustering (NMFk) is applied to this data matrix. NMFk is a robust technique for finding hidden patterns / signatures in data that are not visible in open eyes or other exploratory data analytics. Hidden signals of NMFk analysis reveal hidden geothermal resources and indicate key parameters to characterize the geothermal system in SWNM. Also, spatial clusters by NMFk provide potential geothermal resources and future data collection plans to explore more geothermal resources in SWNM.

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