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Joint Geophysical Data Analysis for Geothermal Energy Exploration Antony Munika Wamalwa University of Texas at El Paso, [email protected]

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Joint Geophysical Data Analysis for Geothermal Energy Exploration Antony Munika Wamalwa University of Texas at El Paso, Amwamalwa@Gmail.Com University of Texas at El Paso DigitalCommons@UTEP Open Access Theses & Dissertations 2011-01-01 Joint Geophysical Data Analysis For Geothermal Energy Exploration Antony Munika Wamalwa University of Texas at El Paso, [email protected] Follow this and additional works at: https://digitalcommons.utep.edu/open_etd Part of the Geophysics and Seismology Commons, and the Oil, Gas, and Energy Commons Recommended Citation Wamalwa, Antony Munika, "Joint Geophysical Data Analysis For Geothermal Energy Exploration" (2011). Open Access Theses & Dissertations. 2414. https://digitalcommons.utep.edu/open_etd/2414 This is brought to you for free and open access by DigitalCommons@UTEP. It has been accepted for inclusion in Open Access Theses & Dissertations by an authorized administrator of DigitalCommons@UTEP. For more information, please contact [email protected]. JOINT GEOPHYSICAL DATA ANALYSIS FOR GEOTHERMAL ENERGY EXPLORATION ANTONY MUNIKA WAMALWA Department of Geological Sciences APPROVED: ___________________________ Laura Serpa, Ph.D., Chair ___________________________ Elizabeth Anthony, Ph.D. ___________________________ Diane Doser, Ph.D. ___________________________ Aaron Velasco, Ph.D. ___________________________ Kevin Mickus, Ph.D. _________________________ Benjamin C. Flores, Ph.D. Acting Dean of the Graduate School Copyright © Antony Munika Wamalwa 2011 JOINT GEOPHYSICAL DATA ANALYSIS FOR GEOTHERMAL ENERGY EXPLORATION by ANTONY MUNIKA WAMALWA, M.S., B.S. DISSERTATION Presented to the Faculty of the Graduate School of The University of Texas at El Paso in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY Department of Geological Sciences THE UNIVERSITY OF TEXAS AT EL PASO December 2011 Acknowledgements Many people helped in making this study a success. Although I may not mention all of them here dues to limited space, I would like to extend my gratitude to Dr. Laura Serpa for the opportunity she gave me to study geophysics and some fruitful discussion we had over the period. I would also like to thank Dr. Kevin Mickus for his insightful discussions and data processing and interpretation, Dr. Diane Doser, Dr. Elizabeth Anthony, Dr. Aaron Velasco, Dr. Terry Pavlis, and Dr. Peter Omenda for the helpful reviews. I would also like to thank Andrew Sabin and Wei-Chuang Huang of the United Stated geothermal Program at Coso, California for availing the MT data for Coso geothermal field study. Much thanks to Dr. Silas Simiyu and the Geothermal Development Company (GDC) for giving the data collected over the geothermal fields in Kenya. Thanks to Charles Muturia of DGC and Karen Christopherson of Chinook Geoconsulting, Inc. for the helpful discussions on data collection and processing. I would like to thank Kenny, Sarahi, and Christian Gross for the support they awarded me during my entire stay in El Paso. It behooves me to recognize and be thankful for the contribution of Mellisa Jimenez for kindness and support whenever in want and how she played a role of a dear sister that made me feel at home while in El Paso. To friends and colleagues at the geology department who form a long list, I thank you all. I greatly appreciate the patience and support of my dear parents Jared and Mary Wamalwa who also gave me the chance to get education. I would like to appreciate the patience and encouragement from Jamillah Wanyonyi and George Munika and all my family members. This work was supported by NSF grants EAR 0749382 awarded to Dr. Laura Serpa, and a UTEP Student Research Grant Awarded to Antony Wamalwa. This Dissertation was submitted to the Supervising Committee on the 16 th of November 2011 iv Abstract Geophysical data modelling often yields non-unique results and hence the interpretation of the resulting models in terms of underlying geological units and structures is not a straightforward problem. However, if multiple datasets are available for a region of study, an integrated interpretation of models for each of the geophysical data may results to a more realistic geological description. This study not only demonstrates the strength of resistivity analysis for geothermal fields but also the gains from interpreting resistivity data together with other geophysical data such as gravity and seismic data. Various geothermal fields have been examined in this study which includes Silali and Menengai geothermal fields in Kenya and Coso geothermal field in California, USA. v Table of Contents Acknowledgements ................................................................................................................... iv Abstract ...................................................................................................................................... v Table of Contents ...................................................................................................................... vi SECTION 1 ................................................................................................................................ 1 Resistivity Investigation of the Geothermal Potential at the Silali Volcano, Northern Kenya Rift, Using Electromagnetic Data. .............................................................................. 1 1.1 Abstract ........................................................................................................................... 1 1.2 Introduction ..................................................................................................................... 2 1.3 Previous studies .............................................................................................................. 4 1.2.1 The Silali volcano .................................................................................................. 5 1.3 Magnetotelluric (MT) and Transient Electromagnetic (TEM) field survey .............. 8 1.3.1 Data acquisition and processing .......................................................................... 9 1.3.2 MT distortion analysis ........................................................................................ 10 1.4 Data interpretation ........................................................................................................ 11 1.4.1 2D modeling of MT data..................................................................................... 14 1.5 Conclusions ................................................................................................................... 20 1.6 Acknowledgements ...................................................................................................... 23 1.7 References ..................................................................................................................... 24 SECTION 2 .............................................................................................................................. 27 Joint Geophysical Analysis of the Coso Geothermal Field, south-eastern California ..... 27 2.1 Abstract ......................................................................................................................... 27 2.2 Introduction ................................................................................................................... 28 2.3 Coso Geothermal Field ................................................................................................ 29 2.4 Previous geophysical studies ....................................................................................... 32 2.4.1 Seismic .................................................................................................................. 32 vi 2.4.2 Gravity ................................................................................................................... 33 2.4.3 Resistivity ............................................................................................................. 35 2.5 Magnetotelluric method and data analysis ................................................................. 36 2.6 Gravity data analysis .................................................................................................... 42 2.7 Conclusions ................................................................................................................... 48 2.8 Acknowledgements ...................................................................................................... 50 2.9 References ..................................................................................................................... 51 SECTION 3 .............................................................................................................................. 55 Geophysical Characterization of the Menengai Volcano, Central Kenya Rift from the Analysis of Magnetotelluric and Gravity Data ................................................................... 55 3.1 Abstract ......................................................................................................................... 55 3.2 Introduction ................................................................................................................... 56 3.3 Previous geophysical studies in the Kenya Rift ......................................................... 57 3.3.1 Menengai Volcano ............................................................................................... 60 3.4 Geophysical data analysis ............................................................................................ 61 3.4.1 Gravity ..................................................................................................................
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