Determination of Source Parameters of Simple-shaped Geologic Subsurface Structures from Self-potential Anomalies Using Enhanced Local Wavenumber Method
Main Article Content
Abstract
Abstract: Simple geometry model structures can be useful in quantitative evaluation of self-potential data. In this paper, we solve local wavenumber equation to estimate the horizontal position, the depth and the type of the causative source geometry by using a linear least-squares approximation. The advantages of the algorithm in determining the horizontal position and depth measure are its independence to shape factor of the sources and also its simple computations. The algorithm is built in Matlab environment. The validity of the algorithm is illustrated on variable noise-free and random noise included synthetic data from two-dimensional (2-D) models where the achieved parametric quantities coincide well with the actual ones. The algorithm is also utilized to real self-potential data from Ergani Copper district, Turkey. The results from the actual data application are in good agreement with the published literature for the study area. The source code of the algorithm is available from the authors on request.
Keywords: Local wavenumber, Self-potential, a linear least-squares approximation, Ergani copper field.
Keywords:
Local wavenumber, Self-potential, a linear least-squares approximation, Ergani copper field
References
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[39] R. Di Maio, e. Piegari, P. Rani, Source depth estimation of self-potential anomalies by spectral methods, Journal of Applied Geophysics, 136 (2017), 315–325.
[40] L.T. Pham, E. Oksum, T.D. Do, M. Le-Huy, New method for edges detection of magnetic sources using logistic function, Geofizicheskiy Zhurnal, 40(2018), 127-135.
[41] L.T. Pham, E. Oksum, T.D. Do, Edge enhancement of potential field data using the logistic function and the total horizontal gradient, Acta Geodaetica et Geophysica, 54(2019), pp. 143-155.
[42] E.M. Abdelrahman, T.M. El-Araby, A.A. Ammar, H.I. Hassanein, A Least-squares approach to shape determination from residual Self-potential anomalies, Pure and Applied Geophysics, 150(1997), 121–128.
[2] E. Pekşen, T. Yas, A.Y. Kayman, C. Özkan C, Application of particle swarm optimization on self-potential data, Journal of Applied Geophysics, 75(2011), 305–318.
[3] R.F. Corwin, D.B. Hoover, The self-potential method in geothermal exploration, Geophysics, 44 (1979), 226–245.
[4] H.M. El-Araby, A new method for complete quantitative interpretation of self-potential anomalies, Journal of Applied Geophysics, 55 (2004), 211–224, 2004.
[5] G. Göktürkler, C. Balkaya, Inversion of self-potential anomalies caused by simple-geometry bodies using global optimization algorithms, Journal of Geophysics and Engineering, 9(2012), 498–507.
[6] B.B. Bhattacharya, N. Roy, A note on the use of a nomogram for self-potential anomalies, Geophysical Prospecting, 29 (1981), 102–104.
[7] B.V.S. Murty, P. Haricharan, Nomogram for the complete interpretation of spontaneous polarization profiles and sheet like and cylindrical two-dimensional sources, Geophysics, 50 (1985), 1127–1135.
[8] B.S.R. Rao, I.V.R. Murthy, S.J. Reddy, Interpretation of self-potential anomalies of some geometric bodies, Pure and Applied Geophysics, 78(1970), 66–77.
[9] A.D. Rao, H.V. Ram Babu, Quantitative interpretation of self-potential anomalies due to two-dimensional sheet like bodies, Geophysics, 48(1983), 1659–1664.
[10] B.N.P Agarwal, Quantitative interpretation of self-potential anomalies, Extended Abstract of the 54th SEG Annual Meeting and Exposition, Atlanta, (1984) 154–157.
[11] N. Sundarajan, Y. Srinivas, A modified Hilbert transform and its application to self-potential interpretation, Journal of Applied Geophysics, 36(1996), 137–143.
[12] N. Sundarajan, R.P Srinivasa, V. Sunitha, An analytical method to interpret self-potential anomalies caused by 2-D inclined sheet, Geophysics, 63(1998), 1151–1155.
[13] E.M. Abdelrahman, H.M. El-Araby, T.M. El-Araby, K.S. Essa, A new approach to depth determination from magnetic anomalies, Geophysics, 67(2002), 1524–1531.
[14] E.M. Abdelrahman, E.R. Abo-Ezz, T.M. El-Araby, K.S. Essa KS, A simple method for depth determination from self-potential anomalies due to two superimposed structures, Exploration Geophysics, (2015), doi:10.1071/eg15012.
[15] D. Patella, Introduction to ground surface self-potential tomography, Geophysical Prospecting, 45(1997), 653–681.
[16] D. Patella, Self-potential global tomography including topographic effects, Geophysical Prospecting, 45(1997), 843–863.
[17] A. Revil, L. Ehouarne, E. Thyreault, Tomography of self-potential anomalies of electrochemical nature, Geophysical Research Letters, 28(2001), 4363–4366.
[18] T. Iuliano, P. Mauriello, D. Patella, Looking inside Mount Vesuvius by potential fields integrated probability tomographies, Journal of Volcanology and Geothermal Research, 113(2002), 363–378.
[19] A. Jardani, A. Revil, A. Boleve, A. Crespy, J.P. Dupont, W. Barrash, Tomography of the Darcy velocity from self-potential measurements, Geophysical Research Letters, 34(2007), L24403.
[20] B.J. Minsley, J. Sogade, F.D. Morgan, Three-dimensional source inversion of self-potential data, Journal of Geophysical Research, 112(2007), B02202, doi:10.1029/2006JB004262.
[21] K. Essa, S. Mehanee, P.D. Smith, A new inversion algorithm for estimating the best fitting parameters of some geometrically simple body to measured self-potential anomalies, Exploration Geophysics, 39(2008), 155.
[22] J. Castermant, C.A. Mendonça, A. Revil, F. Trolard, G. Bourrié, N. Linde, Redox potential distribution inferred from self-potential measurements during the corrosion of a burden metallic body, Geophysical Prospecting, 56(2008), 269–282.
[23] C.A. Mendonça, Forward and inverse self-potential modeling in mineral exploration, Geophysics, 73(2008), F33–F43.
[24] A. Soueid-Ahmed, A. Jardani, A. Revil, J.P. Dupont, SP2DINV: A 2D forward and inverse code for streaming potential problems, Computers & Geosciences, 59(2013), 9–16.
[25] J. Stoll, J. Bigalke, E.W. Grabner, Electrochemical modelling of self-potential anomalies, Surveys in Geophysics, 16(1995), 107–120.
[26] S.S. Vasconcelos, C.A. Mendonça, N. Silva, Self-potential signals from pumping tests in laboratory experiments, Geophysics, 79(2014), EN125–EN133, 2014.
[27] J.H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, University of Michigan Press, 1975.
[28] S. Kirkpatrick, C.D. Gelatt, M.P. Vecchi, Optimization by Simulated Annealing, Science, 220(1983), 671–680.
[29] J. Kennedy, R.C. Eberhart, Particle swarm optimization”. Proceedings of the IEEE International Conference on Neural Networks, (1995), 1942–1948.
[30] J.L. Fernandez-Martinez, E. Garcia-Gonzalo, J.P. Fernandez-Alvarez, H.A. Kuzma, C.O. Menendez Perez, PSO: a powerful algorithm to solve geophysical inverse problems: application to a 1D-DC resistivity case, Journal of Applied Geophysics, 71(2010), 13–25.
[31] J.L. Fernandez-Martinez, E. Garcia-Gonzalo, V. Naudet, Particle swarm optimization applied to solving and appraising the streaming-potential inverse problem, Geophysics, 75(2010), WA3–WA15.
[32] E. Momeni, D.J. Armaghani, M. Hajihassani, M.F.M. Amin, Prediction of uniaxial compressive strength of rock samples using hybrid particle swarm optimization-based artificial neural networks, Measurement, 60(2015), 50–63.
[33] A.Salem, D. Ravat, R. Smith, K. Ushijima. Interpretation of magnetic data using an enhanced local wave number (ELW) method, Geophysics, 70(2005), L7–12.
[34] S. Srivastava, B.N.P. Agarwal, Interpretation of self-potential anomalies by Enhanced Local Wave number technique, Journal of Applied Geophysics, 68(2009), 259–268, 2009.
[35] J.B. Thurston, R.S. Smith, Automatic conversion of magnetic data to depth, dip, and susceptibility contrast using the SPI(TM) method, Geophysics, 62(1997), 807–813.
[36] R.J. Blakely, Potential Theory in Gravity and Magnetic Applications. Cambridge, Cambridge University Press, 1995
[37] S.J. Miller, The method of least squares, Mathematics Department Brown University, (2006), 1–7.
[38] V. Srivardhan, S.K. Pal, J. Vaish, S. Kumar, A.K. Bharti, P. Priyam, Particle swarm optimization inversion of self-potential data for depth estimation of coal fires over East Basuria colliery, Jharia coalfield, India, Environ Earth Sci 75(2016), 688.
[39] R. Di Maio, e. Piegari, P. Rani, Source depth estimation of self-potential anomalies by spectral methods, Journal of Applied Geophysics, 136 (2017), 315–325.
[40] L.T. Pham, E. Oksum, T.D. Do, M. Le-Huy, New method for edges detection of magnetic sources using logistic function, Geofizicheskiy Zhurnal, 40(2018), 127-135.
[41] L.T. Pham, E. Oksum, T.D. Do, Edge enhancement of potential field data using the logistic function and the total horizontal gradient, Acta Geodaetica et Geophysica, 54(2019), pp. 143-155.
[42] E.M. Abdelrahman, T.M. El-Araby, A.A. Ammar, H.I. Hassanein, A Least-squares approach to shape determination from residual Self-potential anomalies, Pure and Applied Geophysics, 150(1997), 121–128.