Multivariate regression model from water level and production rate time series for the geothermal reservoir Waiwera (New Zealand)
- Water management tools are necessary to guarantee the preservation of natural resources while ensuring optimum utilization. Linear regression models are a simple and quick solution for creating prognostic capabilities. Multivariate models show higher precision than univariate models. In the case of Waiwera, implementation of individual production rates is more accurate than applying just the total production rate. A maximum of approximately 1,075 m3/day can be pumped to ensure a water level of at least 0.5 m a.s.l. in the monitoring well. The model should be renewed annually to implement new data and current water level trends to keep the quality.
Author details: | Michael KühnORCiDGND, Tim Schöne |
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DOI: | https://doi.org/10.1016/j.egypro.2017.08.196 |
ISSN: | 1876-6102 |
Title of parent work (English): | Energy procedia |
Publisher: | Elsevier |
Place of publishing: | Amsterdam |
Publication type: | Other |
Language: | English |
Date of first publication: | 2017/09/14 |
Publication year: | 2017 |
Release date: | 2022/09/08 |
Tag: | coefficient of determination; data based model; geothermal reservoir; multivariate regression; scenario analysis; water management |
Volume: | 125 |
Number of pages: | 9 |
First page: | 571 |
Last Page: | 579 |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften |
DDC classification: | 5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften |
Peer review: | Referiert |
Institution name at the time of the publication: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Erd- und Umweltwissenschaften |
License (German): | CC-BY-NC-ND - Namensnennung, nicht kommerziell, keine Bearbeitungen 4.0 International |