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Geostatistical Analysis of Geothermal Flow in Morocco

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Advanced Intelligent Systems for Sustainable Development (AI2SD’2020) (AI2SD 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1417))

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Abstract

The geostatistical analysis of the spatial relationships between geothermal events and geophysical and geological phenomena in the Northern and central provinces of Morocco, using the Multiple Linear Regression Method, made it possible to develop a numerical model for predicting geothermal flows. Thus, the computer calculation in the QGIS 12.04 geographical information system of digital data measurements: geological (Neogene and Quaternary volcanism, fracturing), geophysical (gravimetry, magnetism), seismic and geothermal manifestations, has led to the creation of a “Geothermal Flow Prediction” in Morocco.

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Acknowledgment

This study was supported by the Scientific Institute, Rabat, Morocco. The Geophysics data provided by Moroccan Ministry of Mines and Energy.

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Authors and Affiliations

  1. Faculty of Science, Mohammed V University of Rabat, Rabat, Morocco

    Lalla Amina Ouzzaouit

  2. Scientific Institute, Mohammed V University of Rabat, Rabat, Morocco

    Abdelmounim Qarbous

  3. Mohammadia School of Engineering, Mohammed V University, 10090, Rabat, Morocco

    Lahcen Bahi

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  1. Lalla Amina Ouzzaouit
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  2. Abdelmounim Qarbous
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  3. Lahcen Bahi
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Correspondence to Lalla Amina Ouzzaouit .

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  1. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  2. Aurel Vlaicu University of Arad, Arad, Romania

    Valentina E. Balas

  3. Sciences and Techniques of Tangier, Abdelmalek Essaâdi University, Tangier, Morocco

    Mostafa Ezziyyani

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Ouzzaouit, L.A., Qarbous, A., Bahi, L. (2022). Geostatistical Analysis of Geothermal Flow in Morocco. In: Kacprzyk, J., Balas, V.E., Ezziyyani, M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2020). AI2SD 2020. Advances in Intelligent Systems and Computing, vol 1417. Springer, Cham. https://doi.org/10.1007/978-3-030-90633-7_44

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