[논문]다중목적함수 최적화에 기초한 광대역 유도분극 변수 예측 적용성 분석

김빛나래; 정주연; 민배현; 남명진

doi:10.7582/gge.2022.25.3.099

다중목적함수 최적화에 기초한 광대역 유도분극 변수 예측 적용성 분석
Applicability Analysis on Estimation of Spectral Induced Polarization Parameters Based on Multi-objective Optimization 원문보기

지구물리와 물리탐사 = Geophysics and geophysical exploration, v.25 no.3, 2022년, pp.99 - 108

김빛나래 (세종대학교 에너지자원공학과) , 정주연 (세종대학교 에너지자원공학과) , 민배현 (이화여자대학교 에너지자원공학과) , 남명진 (세종대학교 에너지자원공학과)

초록
AI-Helper

유도분극(induced polarization; IP) 탐사 중 광대역 혹은 빛띠(spectral) IP (SIP) 탐사법에서는 교류 전류를 송신원으로 하였을 때 나타나는 매질의 진동수에 따른 복소전기비저항의 크기와 위상을 측정하며, 진동수에 따라 값이 변화하는 복소전기비저항의 분산 혹은 이완 반응을 분석하게 된다. 이때 분산곡선은 등가회로 모델과 같은 이완 모델을 통해 설명할 수 있는데, 다중목적함수 최적화 기법을 적용하여 분산곡선에서 SIP 이완모델의 변수들을 예측해보았다. SIP 이완현상을 설명하기 위해 가장 많이 이용되는 Cole-Cole 모델 계열의 변수를 구하기 위해 크기 오차와 위상 오차를 최소화하는 두 가지 목적함수로 설정하고 다중목적함수를 최적화하기 위해 유전 알고리듬을 이용하였다. 다중목적함수 최적화 기법을 이용한 Cole-Cole 모델 변수 구하기는 수치 모델에 대해서는 잘 구해졌으나 기존에 보고된 SIP 실내실험 자료에 피팅할 경우, 주로 위상 크기가 작을 때(약 10 mrad 이하) 피팅이 맞지 않는 경우가 많았다. 이는 다중목적함수로 사용하는 크기와 위상의 자료 오차 사이에 스케일이 맞지 않아 발생하는 한계로 추정되며, 향후 복소전기비저항의 분산 곡선에서 SIP 변수를 예측하기 위해 이러한 한계를 극복할 수 있는 기계 학습 등 다양한 기법들에 대한 연구가 필요할 것으로 판단된다.

Abstract ▼ AI-Helper

Among induced polarization (IP) methods, spectral IP (SIP) uses alternating current as a transmission source to measure amplitudes and phase of complex electrical resistivity at each source frequency, which disperse with respect to source frequencies. The frequency dependence, which can be explained by a relaxation model such as Cole-Cole model or equivalent models, is analyzed to estimate SIP parameters from dispersion curves of complex resistivity employing multi-objective optimization (MOO). The estimation uses a generic algorithm to optimize two objective functions minimizing data misfits of amplitude and phase based on Cole-Cole model, which is most widely used to explain IP relaxation effects. The MOO-based estimation properly recovered Cole-Cole model parameters for synthetic examples but hardly fitted for the real laboratory measures ones, which have relatively smaller values of phases (less than about 10 mrad). Discrepancies between scales for data misfits of amplitude and phase, used as parameters of MOO method, and it is in necessity to employ other methods such as machine learning, which can deal with the discrepancies, to estimate SIP parameters from dispersion curves of complex resistivity.

주제어

표/그림 (9)

그림 Fig. 1. Schematic figure of multi-objective optimization (MOO).
그림 Fig. 2. MOO procedure for SIP data fitting.
그림 Fig. 3. Initial population and final pareto front as using (a) MSE, (b) RMSE, and (c) MAPE to evaluate multi objective function misfit.
그림 Fig. 4. Expected Cole-Cole model parameters from MOO with different objective functions (MSE, RMSE, MAPE of amplitude and phase).
그림 Fig. 5. (a) Amplitude and (b) phase depending on frequencies from expected multi Cole-Cole model using MOO method.
표 Table 1. Synthetic model parameters of multi Cole-Cole model referred from Dias (2000), average and standard deviation values from MOO
그림 Fig. 6. Fitting results for spectral amplitude and phase data from references ((a) Hubbard et al. (2014), (b) Hubbard et al. (2014), (c) Slater et al. (2006), and (d) Mao et al. (2016)) and MOO method.
표 Table 2. Estimated Cole-Cole model parameters from reference and MOO method
그림 Fig. 7. Cole-Cole model fitting results using MOO mean and pyGIMLi for experimental data from (a) Ustra et al. (2016), (b) Slater et al. (2007), and (c) Mansoor et al. (2007).

참고문헌 (42)

Abdel Aal, G. Z., Atekwana, E. A., Rossbach, S., and Werkema, D. D., 2010, Sensitivity of geoelectrical measurements to the presence of bacteria in porous media, J. Geophys. Res.: -Biogeosci., 115(G3). https://doi.org/10.1029/2009jg001279

상세보기
Binley, A., Slater, L. D., Fukes, M., and Cassiani, G., 2005, Relationship between spectral induced polarization and hydraulic properties of saturated and unsaturated sandstone. Water Resour. Res., 41(12). https://doi.org/10.1029/2005wr004202

상세보기
Bucker, M., and Hordt, A., 2013, Long and short narrow pore models for membrane polarization, Geophys., 78(6), E299-E314. https://doi.org/10.1190/geo2012-0548.1

상세보기
Cole, K. S., and Cole, R. H., 1941, Dispersion and absorption in dielectrics I. Alternating current characteristics, J. Chem. Phys., 9(4), 341-351. https://doi.org/10.1063/1.1750906

상세보기
Deb, K., Pratap, A., Agarwall, A., and Meyarivan, T. A., 2002, A fast and elitist multiobjective genetic algorithm. IEEE Trans. EVolut. Comput, 6(2), 182-197. https://doi.org/10.1109/4235.996017

상세보기
Dias, C. A., 2000, Developments in a model to describe low-frequency electrical polarization of rocks, Geophys., 65(2), 437-451. https://doi.org/10.1190/1.1444738

상세보기
Fonseca, C. M., and Fleming, P. J., 1995, An overview of evolutionary algorithms in multiobjective optimization, Evol. Comput., 3(1), 1-16. https://doi.org/10.1162/evco.1995.3.1.1

상세보기
Goldberg, D. E., 1989, Genetic Algorithms in Search, Optimization and Machine Learning, Addison Wesley. https://doi.org/10.5860/choice.27-0936
Gurin, G., Tarasov, A., Ilyin, Y., and Titov, K., 2013, Time domain spectral induced polarization of disseminated electronic conductors: Laboratory data analysis through the Debye decomposition approac, J. Appl. Geophys., 98, 44-53. https://doi.org/10.1016/j.jappgeo.2013.07.008

상세보기
Hubbard, C. G., West, L. J., Rodriguez-Blanco, J. D., and Shaw, S., 2014, Laboratory study of spectral induced polarization responses of magnetite-Fe 2+ redox reactions in porous media, Geophys., 79(1), D21-D30. https://doi.org/10.1190/geo2013-0079.1

상세보기
Jang, H., 2019, Layered-earth Resistivity Inversion of Small-loop Electromagnetic Survey Data using Particle Swarm Optimization, Geophys, Geophys. Explor., 22(4), 186-194. https://doi.org/10.7582/GGE.2019.22.4.186

원문보기 상세보기
Kemna, A., Binley, A., Cassiani, G., Niederleithinger, E., Revil, A., Slater, L., Williams, K. H., Orozco, A. F., Haegel F., Hordt, A., Kruschwitz, S., Leroux, V., Titov, K., and Zimmermann, E., 2012, An overview of the spectral induced polarization method for near-surface applications, Near Surf. Geophys., 10(6), 453-468. https://doi.org/10.3997/1873-0604.2012027

상세보기
Kemna, A., Binley, A., Ramirez, A., and Daily, W., 2000, Complex resistivity tomography for environmental applications, Chem. Eng. J., 77(1-2), 11-18. https://doi.org/10.1016/s1385-8947(99)00135-7

상세보기
Kim, B., Nam, M. J., Jang, H., Jang, H., Son, J. S., and Kim, H. J., 2017, The Principles and Practice of Induced Polarization Method. Geophys, Geophys. Explor., 20(2), 100-113 (in Korean with English abstract). https://doi.org/10.7582/GGE.2017.20.2.100

원문보기 상세보기
Lee, I., Shin, S. Y., Cho, Y. M., Yang, K. A., and Zhang B. T., 2008, Microarray Probe Design with Multiobjective Evolutionary Algorithm. J. KIISE: SA, 35(8), 501-511. (in Korean with English abstract). https://koreascience.kr/article/JAKO200827642579112.page
Lesmes, D. P., and Morgan, F. D., 2001, Dielectric spectroscopy of sedimentary rocks, J. Geophys. Res.- Solid Earth, 106(B7), 13329-13346. https://doi.org/10.1029/2000jb900402

상세보기
Mansoor, N., and Slater, L., 2007, On the relationship between iron concentration and induced polarization in marsh soils, Geophys., 72(1), A1-A5. https://doi.org/10.1190/1.2374853

상세보기
Mao, D., Revil, A., and Hinton, J., 2016, Induced polarization response of porous media with metallic particles-Part 4: Detection of metallic and nonmetallic targets in time-domain induced polarization tomography, Geophys., 81(4), D359-D375. https://doi.org/10.1190/geo2015-0480.1

상세보기
Min, B., Kang, J. M., Chung, S., Park, C., and Jang, I., 2014, Pareto-based multi-objective history matching with respect to individual production performance in a heterogeneous reservoir. J. Pet. Sci. Eng., 122, 551-566. https://doi.org/10.1016/j.petrol.2014.08.023

상세보기
Min, B., Sun, A. Y., Wheeler, M. F., and Jeong, H., 2018, Utilization of multiobjective optimization for pulse testing dataset from a CO 2 -EOR/sequestration field. J. Pet. Sci. Eng., 170, 244-266. https://doi.org/10.1016/j.petrol.2018.06.035

상세보기
Mitani, K., and Nakayama, H., 1997, A multiobjective diet planning support system using the satisficing trade-off method, J. Multi-Criteria Decision Analysis, 6(3), 131-139. https://doi.org/10.1002/(sici)1099-1360(199705)6:3%3C131::aid-mcda129%3E3.0.co;2-s
Nakayama, H., 1989, Sensitivity and trade-off analysis in multiobjective programming, In Methodology and Software for Interactive Decision Support, Springer, 86-93. https://doi.org/10.1007/978-3-662-22160-0_12
Nakayama, H., 1991, Interactive multi-objective programming and its applications, In Methodology, Implementation and Applications of Decision Support Systems, Springer, 175-197. https://doi.org/10.1007/978-3-7091-2606-6_7
Nakayama, H., 1995, Aspiration level approach to interactive multi-objective programming and its applications, In Advances in multicriteria analysis, Springer, 147-174. https://doi.org/10.1007/978-1-4757-2383-0_10
Nakayama, H., Nomura, J., Sawada, K., and Nakajima, R., 1986, An application of satisficing trade-off method to a blending problem of industrial materials, In Large-Scale Modelling and Interactive Decision Analysis, Springer, 303-313. https://doi.org/10.1007/978-3-662-02473-7_30
Nordsiek, S., and Weller, A., 2008, A new approach to fitting induced-polarization spectra, Geophysics, 73(6), F235-F245. https://doi.org/10.1190/1.2987412

상세보기
Pelton, W. H., Ward, S. H., Hallof, P. G., Sill, W. R., and Nelson, P. H., 1978, Mineral discrimination and removal of inductive coupling with multifrequency IP, Geophys., 43(3), 588-609. https://doi.org/10.1190/1.1440839

상세보기
Revil, A., and Florsch, N., 2010, Determination of permeability from spectral induced polarization in granular media, Geophys. J. Int., 181(3), 1480-1498. https://doi.org/10.1111/j.1365-246x.2010.04573.x

상세보기
Rucker, C., Gunther, T., and Wagner, F. M., 2017, pyGIMLi: An open-source library for modelling and inversion in Geophys., Computers and Geosciences, 109, 106-123. https://doi.org/10.1016/j.cageo.2017.07.011

상세보기
Scott, J. B. T., and Barker, R. D., 2003, Determining pore-throat size in Permo-Triassic sandstones from low-frequency electrical spectroscopy, Geophys. Res. Lett., 30(9). https://doi.org/10.1029/2003gl016951

상세보기
Shin, S. W., Park, S., and Shin, D. B., 2015. Development of a new equivalent circuit model for spectral induced polarization data analysis of ore samples, Environ. Earth. Sci., 74, 5711-5716. https://doi.org/10.1007/s12665-015-4588-z

상세보기
Slater, L. D., and Lesmes, D., 2002, IP interpretation in environmental investigations, Geophys., 67(1), 77-88. https://doi.org/10.1190/1.1451353

상세보기
Slater, L., Ntarlagiannis, D., and Wishart, D., 2006, On the relationship between induced polarization and surface area in metal-sand and clay-sand mixtures, Geophys., 71(2), A1-A5. https://doi.org/10.1190/1.2187707

상세보기
Slater, L., Ntarlagiannis, D., Personna, Y. R., and Hubbard, S., 2007, Pore-scale spectral induced polarization signatures associated with FeS biomineral transformations, Geophys. Res. Lett., 34(21). https://doi.org/10.1029/2007gl031840

상세보기
Tamaki, H., Kita, H., and Kobayashi, S., 1996, Multi-objective optimization by genetic algorithms: A review, In Proceedings of IEEE Int. Conference on Evol. Comput, 517-522. https://doi.org/10.1109/icec.1996.542653
Tarasov, A., Titov, K., 2013. On the use of the Cole-Cole equations in spectral induced: Polarization, Geophys. J. Int., 195(1), 352-356. https://doi.org/10.1093/gji/ggt251

상세보기
Uhlmann, D. R., and Hakim, R. M., 1971, Derivation of distribution functions from relaxation data, J. Physics and Chemistry of Solids, 32(11), 2652-2655. https://doi.org/10.1016/s0022-3697(71)80114-2

상세보기
Ustra, A., Mendonca, C. A., Ntarlagiannis, D., and Slater, L. D., 2016, Relaxation time distribution obtained from a Debye decomposition of spectral induced polarization data, Geophys., 81(2), E129-E138. https://doi.org/10.1190/geo2015-0095.1

상세보기
Vanhala, H., and Peltoniemi, M., 1992, Spectral IP studies of Finnish ore prospects, Geophys., 57(12), 1545-1555. https://doi.org/10.1190/1.1443222

상세보기
Weigand, M., and Kemna, A., 2016, Debye decomposition of time-lapse spectral induced polarisation data, Comput. Geosci., 86, 34-45. https://doi.org/10.1016/j.cageo.2015.09.021

상세보기
Zhdanov, M. S., Burtman, V., Endo, M., and Wilson, G. A., 2012, Laboratory-based GEMTIP analysis of spectral IP data for mineral discrimination, SEG Technical Program Expanded Abstracts, Society of Exploration Geophysicists, 1-5. https://doi.org/10.1190/segam2012-1268.1
Zisser, N., Kemna, A., and Nover, G., 2010, Dependence of spectral-induced polarization response of sandstone on temperature and its relevance to permeability estimation, J. Geophys. Res.: Solid Earth, 115(B9). https://doi.org/10.1029/2010jb007526

상세보기

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