معکوس‌سازی خطی دو‌بعدی داده‌های الکترومغناطیس زمینی حوزه فرکانس با چشمه مصنوعی در محدوده عدد القاء کوچک

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار، دانشکده مهندسی معدن و متالورژی، دانشگاه یزد، یزد، ایران

2 دانش‌آموخته دکتری، گروه فیزیک زمین، مؤسسه ژئوفیزیک، دانشگاه تهران، تهران، ایران

چکیده

به‌منظور بازسازی مقاطع رسانایی الکتریکی زیرسطحی با استفاده از داده­های ژئوالکترومغناطیس حوزه فرکانس تحت شرایط عدد القاء کوچک، یک الگوریتم مدل­سازی معکوس تکراری در دو بعد از طریق رویکرد معادلات انتگرال خطی در محیط برنامه­نویسی MATLAB توسعه داده شده است. الگوریتم معکوس­سازی حاضر بر اساس یک مدل‌سازی پیشرو خطی دو‌بعدی بنا نهاده شده است که برای حل این مسئله پیشرو از راه‌حل عددی به‎جای شیوه تحلیلی استفاده می­شود. از قابلیت­های این الگوریتم خطی، محاسبه کرنل تنها در یک مرحله و استفاده از آن در تمام تکرارها می­باشد که باعث افزایش سرعت محاسبات می­شود. ورودی این فرایند معکوس­سازی، مقادیر رسانایی الکتریکی ظاهری می­باشند. برای بهینه­سازی تابع هدف از شیوه کمترین‌مربعات وزن داده‌شده با حضور منظم­سازی و همچنین اعمال قید، از طریق تابع وزن‌دهی عمقی، استفاده شده است که از شدت عدم‌یکتایی و ناپایداری آن کاسته شود. در این تحقیق، مقدار اولیه پارمتر منظم‌سازی با استفاده از بیشنه مقدار ماتریس عملگر پیشرو حاصل و سپس بهینه می‌شود. الگوریتم مذکور قادر به معکوس­سازی در دو حالت منفرد و توأمان آرایه­های هم­صفحه افقی و هم­صفحه قائم می­باشد. صحت این الگوریتم با استفاده از داده­های حاصل از دو مدل مصنوعی، مدل اول شامل یک آنومالی در دو حالت افقی یا قائم و مدل دوم شامل چهار آنومالی با ابعاد و موقعیت­های مختلف، و همچنین داده­های مربوط به یک دایک ضخیم در آفریقای جنوبی ارزیابی می­شود. داده­ها از طریق شرایط دستگاه­های EM31، EM34 و EM38 شبیه­سازی یا برداشت شده­اند. نتایج معکوس­سازی­ها کارآیی روش را در حد مطلوب نشان می­دهند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

2D Linear inversion of ground-based controlled-source electromagnetic data under a low induction number condition

نویسندگان [English]

  • Hosseinali Ghari 1
  • Ramin Varfinezhad 2
1 Assistant Professor, Faculty of Mining and Metallurgical Engineering, Yazd University, Yazd, Iran
2 Ph.D. Graduated, Department of Earth Physics, Institute of Geophysics, University of Tehran, Tehran, Iran
چکیده [English]

Low-induction-number frequency-domain geoelectromagnetic (LIN-GeoFEM) instruments are ground conductivity meters that use a small coil transmitter (Tx) and one coil receiver (Rx). This coil–coil system is designed to propagate alternating electromagnetic fields through the earth at small Tx–Rx separations and low frequency and receive the EM field coupling in the shallow subsurface to provide direct measures of the apparent electrical conductivity. This measured property is a complicated average of spatially distributed localized electrical conductivities in the subsurface. Instruments capable of operating as LIN FEM instruments include the EM38, EM31, and EM34 (Geonics Ltd., Mississauga, ON), the DUALEM instruments series (DUALEM, Inc., Milton, ON), the GEM instrument series (Geophex Ltd., Raleigh, NC) and CMD series (GF Instruments, s.r.o.). The Tx and Rx coils can be oriented relative to each other and the earth's surface. Orientations considered in this study are horizontal coplanar (HCP) (both coils lie flat on the ground) and vertical coplanar (VCP) (coils are upright and coplanar). The range of LIN FEM instruments applications for environmental and hydrologic characterization and monitoring is large and increasing.
The LIN-GeoFEM applications are industrially feasible as long as there is a reasonably fast algorithm that is accurate enough to invert the survey data. Furthermore, forward modeling plays a key role in the inversion procedure. The linear integral equation (IE) method is a powerful tool in EM forward modeling for geophysical applications, especially for simple background conductivity structures. The main advantage of the IE method in comparison with the finite difference (FD) and finite element (FE) methods is its fast and accurate simulation of the response for models with compact 2-D or 3-D bodies in a layered background. The main limitation of the IE method is that the background conductivity model must have a simple structure to allow for an efficient Green’s function calculation. Fortunately, the most widely used background models in LIN-GeoFEM explorations are those formed by horizontally homogeneous layers. A main issue is that the EM field integral equation is nonlinear. However, an approximate linear equation is obtained for the electromagnetic induction at low induction numbers using the Born approximation. A 2D forward modeling code for LIN-GeoFEM is developed based on the integral equation (IE) method. Here, a linear relation between model parameters and apparent conductivity values is proposed. The 2D problem is obtained from 3D using numerical integration along the y-axis (strike direction) from minus infinity to infinity. So, the linear approximation is applied to the 2D inversion of LIN measurements. We use a damped minimum length solution using depth weighting to solve this problem iteratively. Thus, we obtain a better estimate of conductivity in a few iterations. Using this 2D linear inversion or imaging technique, we can produce reasonably good results of inverting jointly and individually VCP and HCP for low and moderate conductivity contrasts.
To validate the algorithm, we consider two 2D synthetic scenarios and field data acquired on a thick conductive dyke in the Bloemfontein Nature Reserve region in South Africa. The first synthetic scenario consists of one 3 W.m conductive horizontal or vertical prism immersed in a 100 W.m resistive host. In this example, the recovered models from the inversion of the HCP (VMD) and VCP (HMD) data show good results for the vertical and horizontal prism, respectively. The second scenario simulates four 20 W.m conductive vertical and horizontal prisms in a 100 W.m resistive background. The recovered conductivity from the inversion of the VCP data has the weakest results, especially in the case of vertical prisms. In the conductivity section from the inversion of HCP data, the existence of the four anomalous bodies is evident. However, the image obtained from the joint inversion of HCP and VCP data has generated useful information about the true model in all recovered models. The result of jointly inverting VCP and HCP field data confirms the presence of the dyke as a zone of low conductivities.

کلیدواژه‌ها [English]

  • Low-induction-number frequency-domain geoelectromagnetic
  • forward modeling
  • linear integral equations
  • joint inversion
  • depth weighting
Aster, R. C., Borchers, B. and Thurber, C. H., 2018, Parameter estimation and inverse problems, Elsevier.
Brosten, T. R., Day-Lewis, F. D., Schultz, G. M., Curtis, G. P. and Lane Jr, J. W., 2011, Inversion of multi-frequency electromagnetic induction data for 3D characterization of hydraulic conductivity., J. Appl. Geophys., 73, 323-335.
Beamish, D., 2011, Low induction number, ground conductivity meters: A correction procedure in the absence of magnetic effects, J. Appl. Geophys., 75, 244-253.
Callegary, J. B., Ferré, T. P. and Groom, R. W., 2007, Vertical spatial sensitivity and exploration depth of low-induction-number electromagnetic-induction instruments, Vadose Zone J., 6, 158-167.
Cavalcante Fraga, L. H., Schamper, C., Noel, C., Guerin, R. and Rejiba, F., 2019, Geometrical characterization of urban fill by integrating the multi‐receiver electromagnetic induction method and electrical resistivity tomography: A case study in Poitiers, France, Eur. J. Soil Sci., 70, 1012-1024.
Cella, F. and Fedi, M., 2012, Inversion of potential field data using the structural index as weighting function rate decay, Geophys. Prospect., 60, 313-336.
Dentith, M. and Mudge, S. T., 2014, Geophysics for the mineral exploration geoscientist, Cambridge University Press.
Deidda, G. P., Himi, M., Barone, I., Cassiani, G. and Casas Ponsati, A., 2022, Frequency-Domain Electromagnetic Mapping of an Abandoned Waste Disposal Site: A Case in Sardinia (Italy), Remote Sensing, 14, 878.
De Kock, M. O., Beukes, N. J., Götz, A. E., Cole, D., Robey, K., Birch, A., Withers, A. and Van Niekerk, H.S., 2016, Open file progress report on exploration of the Southern Karoo Basin through CIMERAKARIN borehole KZF-1 in the Tankwa Karoo, Witzenberg (Ceres) district. DST-NRF Centre of Excellence for Integrated Mineral and Energy Resources Analysis (CIMERA), University of Johannesburg, South Africa.
Elwaseif, M., Robinson, J., Day-Lewis, F. D., Ntarlagiannis, D., Slater, L. D., Lane, J. W., Minsley, B. J. and Schultz, G., 2017, A matlab-based frequency-domain electromagnetic inversion code (FEMIC) with graphical user interface, Comput. and Geosci., 99. 61-71.
Gómez-Treviño, E., Esparza, F. J. and Méndez-Delgado, S., 2002, New theoretical and practical aspects of electromagnetic soundings at low induction numbers, Geophysics, 67, 1441-1451.
Gómez-Treviño, E., 1987, Nonlinear integral equations for electromagnetic inverse problems, Geophysics, 52, 1297-1302.
Gómez-Puentes, F. J., Pérez-Flores, M. A., Reyes-López, J. A., Lopez, D. L., Herrera-Barrientos, F., García-Cueto, R. O., Romero-Hernández, S., Solís-Domínguez, F. A. and Martín-Loeches Garrido, M., 2016, Geochemical modeling and low-frequency geoelectrical methods to evaluate the impact of an open dump in arid and deltaic environments, Environ. Earth Sci., 75, 1-14.
Li, Y. and Oldenburg, D. W., 1996, 3-D inversion of magnetic data, Geophysics, 61, 394-408.
Makhokha, D. and Fourie, F., 2016, A systematic approach to the interpretation of conductivity anomalies across intrusive dolerite dykes and sills in the Karoo Supergroup, MSc thesis, University of the Free State, Bloemfontein.
Matias, M. S., Da Silva, M. M., Ferreira, P. and Ramalho, E., 1994, A geophysical and hydrogeological study of aquifers contamination by a landfill, J. Appl. Geophys., 32, 155–162.
McNeill, J. D., 1980, Electromagnetic Terrain Conductivity Measurement at Low Induction Numbers, Geonics Ltd., Technical Note TN-6.
M´endez-Delgado, S., G´ omez-Trevi ˜no, E. and P´erez-Flores, M. A., 1999, Forward modelling of direct current and low-frequency electromagnetic fields using integral equations, Geophys. J. Int., 137, 336-352.
Menke, W., 2012, Geophysical data analysis: discrete inverse theory. MATLAB edition, Academic press.
Minsley, B. J., 2011, A trans-dimensional Bayesian Markov chain Monte Carlo algorithm for model assessment using frequency-domain electromagnetic data, Geophys. J. Int., 187, 252-272.
Santos, F. A. M., 2004, 1-D laterally constrained inversion of EM34 profiling data, J. Appl. Geophys., 56, 123–134.
Monteiro Santos, F.A., Triantafilis, J., Taylor, R.S., Holladay, S. and Bruzgulis, K.E., 2010, Inversion of conductivity profiles from EM using full solution and a 1-D laterally constrained algorithm, J. Environ. Eng. Geophys., 15, 163-174.
Nyquist, J. E. and Blair, M.S., 1991, A geophysical tracking and data logging system: Description and case history, Geophysics, 56, 1114-1121.
Oh, S., Noh, K., Seol, S.J., Byun, J. and Yi, M.J., 2016, Interpretation of controlled-source electromagnetic data from iron ores under rough topography. J. Appl. Geophys., 124, 106-116.
Orozco, A. F., Ciampi, P., Katona, T., Censini, M., Papini, M.P., Deidda, G.P. and Cassiani, G., 2021, Delineation of hydrocarbon contaminants with multi-frequency complex conductivity imaging, Sci. Total Environ., 768, 144997.
Pérez-Flores, M. A., Méndez-Delgado, S. and Gómez-Treviño, E., 2001, Imaging low-frequency and dc electromagnetic fields using a simple linear approximation, Geophysic, 66, 1067-1081.
Pérez-Flores, M. A., Antonio-Carpio, R.G., Gómez-Treviño, E., Ferguson, I. and Méndez-Delgado, S., 2012, Imaging of 3D electromagnetic data at low-induction numbers, Geophysic, 77, WB47-WB57.
Perez-Flores, M. A., Ochoa-Tinajero, L. E. and Villela y Mendoza, A., 2019, Three-dimensional inverse modeling of EM-LIN data for the exploration of coastal sinkholes in Quintana Roo, Mexico, Nat. Hazards Earth Syst. Sci., 19, 1779-1787.
Parnow, S., Oskooi, B. and Florio, G., 2021, Improved linear inversion of low induction number electromagnetic data, Geophys. J. Int., 224, 1505-1522.
Sasaki, Y., 2001, Full 3-D inversion of electromagnetic data on PC, J. Appl. Geophys., 46, 45-54.
Sasaki, Y., Kim, J.H. and Cho, S.J., 2010, Multidimensional inversion of loop-loop frequency-domain EM data for resistivity and magnetic susceptibility, Geophysics, 75, F213-F223.
Selepeng, A. T., Sakanaka, S. Y. and Nishitani, T., 2017, 3D numerical modelling of negative apparent conductivity anomalies in loop-loop electromagnetic measurements: a case study at a dacite intrusion in Sugisawa, Akita Prefecture, Japan, Explor. Geophys., 48, 177-191.
Spies, B. R. and Frischknecht, F.C., 1991, Electromagnetic sounding. Electromagnetic methods in applied geophysics, 2(Part A), 285-426.
Sudduth, K. A., Drummond, S.T. and Kitchen, N.R., 2001, Accuracy issues in electromagnetic induction sensing of soil electrical conductivity for precision agriculture, Comput. Electron. Agric., 31, 239-264.
Tikhonov, A. N. and Arsenin, V. Y., 1977, Solutions of ill-posed problems, New York 1, 487.
Wait, J.R., 1955, Mutual electromagnetic coupling of loops over a homogenous ground, Geophysics, 20, 630–637.
Ward, S.H. and Hohmann, G.W., 1988, Electromagnetic theory for geophysical applications. Electromagnetic Methods in Applied Geophysics Society of Exploration Geophysicists, Tulsa, Oklahoma. 131–311.
Zhdanov, M. S., 2002, Geophysical inverse and regularization problems. 1sted.: Elsevier Science B. V.
Zhdanov, M.S., 2009, Geophysical electromagnetic theory and methods. Elsevier.