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A Combination of Monte-Carlo and Damped Least Square Inversion Method for Determining Radon Source in Geothermal Case | ||
| فیزیک زمین و فضا | ||
| مقاله 9، دوره 46، شماره 4، بهمن 1399، صفحه 103-116 اصل مقاله (1.1 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jesphys.2020.291763.1007174 | ||
| نویسندگان | ||
| Nandi Haerudin* 1؛ Ida Bagus Suananda Yogi2 | ||
| 1Associate Professor, Department of Geophysical Engineering, Faculty of Engineering, University of Lampung, Bandar Lampung, Indonesia | ||
| 2Assistant Professor, Department of Geophysical Engineering, Faculty of Engineering, University of Lampung, Bandar Lampung, Indonesia | ||
| چکیده | ||
| Radon measurement on the surface can represent the subsurface condition. The measured Radon in geothermal field is caused by the source, which is usually a geothermal reservoir. This study did the inversion process for determining the depth and value of Radon Source. Another fact, non-uniqueness of the solution can produce a result with different model parameter combinations. Hence, it can confuse the interpreter to determine the correct model. Based on this case, we proposed an inversion scheme that can minimize the non-uniqueness effect in the Radon data inversion. The scheme is started by Monte-Carlo inversion and finished by damped least-square. Monte-Carlo inversion, as one of the global optimizations, produce an appropriate starting model for the damped least squares. The damped least square method will finish the scheme fast. In order to be sure with the result, the whole scheme is repeated 19 times. The relative RMS error for the synthetic data is 0.07% to 0.32% to a depth difference of 7% from the synthetic model. With this synthetic data inversion test, the inversion scheme was applied to the real data from the Rajabasa Geothermal field. With this scheme, the section AA’ gives an error of 0.51% to 0.88% with a depth of 712 m and section BB’ gives an error of 5.79% to 5.27% with a depth of 728 m. This result is coherent with the magnetotelluric data in this area. | ||
| کلیدواژه‌ها | ||
| Damped Least Square؛ Geothermal؛ Monte Carlo؛ Radon؛ Reservoir | ||
| عنوان مقاله [English] | ||
| A Combination of Monte-Carlo and Damped Least Square Inversion Method for Determining Radon Source in Geothermal Case | ||
| نویسندگان [English] | ||
| Nandi Haerudin1؛ Ida Bagus Suananda Yogi2 | ||
| 1Associate Professor, Department of Geophysical Engineering, Faculty of Engineering, University of Lampung, Bandar Lampung, Indonesia | ||
| 2Assistant Professor, Department of Geophysical Engineering, Faculty of Engineering, University of Lampung, Bandar Lampung, Indonesia | ||
| چکیده [English] | ||
| Radon measurement on the surface can represent the subsurface condition. The measured Radon in geothermal field is caused by the source, which is usually a geothermal reservoir. This study did the inversion process for determining the depth and value of Radon Source. Another fact, non-uniqueness of the solution can produce a result with different model parameter combinations. Hence, it can confuse the interpreter to determine the correct model. Based on this case, we proposed an inversion scheme that can minimize the non-uniqueness effect in the Radon data inversion. The scheme is started by Monte-Carlo inversion and finished by damped least-square. Monte-Carlo inversion, as one of the global optimizations, produce an appropriate starting model for the damped least squares. The damped least square method will finish the scheme fast. In order to be sure with the result, the whole scheme is repeated 19 times. The relative RMS error for the synthetic data is 0.07% to 0.32% to a depth difference of 7% from the synthetic model. With this synthetic data inversion test, the inversion scheme was applied to the real data from the Rajabasa Geothermal field. With this scheme, the section AA’ gives an error of 0.51% to 0.88% with a depth of 712 m and section BB’ gives an error of 5.79% to 5.27% with a depth of 728 m. This result is coherent with the magnetotelluric data in this area. | ||
| کلیدواژه‌ها [English] | ||
| Damped Least Square, Geothermal, Monte Carlo, Radon, Reservoir | ||
| مراجع | ||
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Abdoh, A. and Pilkington, M., 1989, Radon Emanation Studies of the Ile Bizard Fault, Montreal, Geoexploration, 25, 341–354. Arnason, K. and Hersir, G. P., 1988, One Dimensional Inversion Schlumberger Resistivity Soundings, Computer Program, Description and User’s Guide,The United Nations University, Geothermal Training, Report 8, 59. Balcázar, M., Martínez, A. L., Huerta, M., Ruíz, J. F. and Peña, P. 2010, Use of Environmental Radioactive Isotopes in Geothermal Prospecting, 17th Pacific Basin Nuclear Conference. Bhattacharya, B. B. and Sen, M. K., 2003, Use of VFSA for Resolution, Sensitivity and Uncertainty Analysis in 1D DC Resistivity and IP Inversion, Geophys. Prosp., 51, 393–408. Chunduru, R. K., Sen, M. K. and Stoffa, P. L. 1997, Hybrid Optimization Methods for Geophysical Inversion, Geophysics, 62, 1196–1207. Dimwani, W., Pramono, B. Hadi, J. and Alamsyah, O. 2011, Determining Geothermal Concession Area of The Gunung Rajabasa Geothermal Field Based on Magnetotelluric Data, The 11 Th Annual Indonesian Geothermal Association Meeting & Conference, 2011. Ekinci, Y. L. and Demirci, A., 2008, A Damped Least-Squares Inversion Program for the Interpretation of Schlumberger Sounding Curves, Journal of Applied Sciences, 8, 4070–4078. Fleischer, R. L., Hart, H. R. and Mogro-Campero, A., 1980, Radon emanation over an ore body, Search for long-distance transport of radon, Nuclear Instruments and Methods, 173, 169–181. Haerudin, N., Wahyudi, and Suryanto, W., 2013, Radon and thoron analysis of soil gas survey case study of Rajabasa geothermal field, AIP Conference Proceedings, 1554, 218–221. Haerudin, N., Karyanto, and Kuntoro, Y., 2016, Radon and thoron mapping to delineate the local-fault in the way Ratai geothermal field lampung Indonesia, ARPN Journal of Engineering and Applied Sciences, 11, 4804–4809. Iakovleva, V. S. and Ryzhakova, N. K., 2003, A method for estimating the convective radon transport velocity in soils, Radiation Measurements, 36, 389–391. Iskandar, D., Iida, T., Yamazawa, H., Moriizumi, J., Koarashi, J., Yamasoto, K., Yamasaki, K., Shimo, M., Tsujimoto, T., Ishikawa, S., Fukuda, M. and Kojima, H. 2005, The transport mechanisms of 222 Rn in soil at Tateishi as an anomaly spot in Japan, Applied Radiation and Isotopes, 63, 401–408. Jupp, D. L. B. and Vozoff, K. 1975, Stable Iterative Methods for the Inversion of Geophysical Data, Geophysical Journal of the Royal Astronomical Society, 42, 1975. Krister, K. and Lennart, M., 1982, Evidence for nondiffusive transport of 222Rn in the ground and a new physical model for the transport, Geophysics, 47, 1444–1452. Liu, J., Wang, Z. and Wang, X., 2008, The numerical simulation and inversion fitting of radon concentration distribution in homogeneous overburden above active fault zones, Applied Geophysics, 5, 238–244. Maiti, S., Erram, V. C., Gupta, G. and Tiwari, R. K., 2012, ANN based inversion of DC resistivity data for groundwater exploration in hard rock terrain of western Maharashtra (India), Journal of Hydrology, 464–465, 294–308. Mogro-Campero, A. and Fleischer, R. L., 1977, Subterrestrial fluid convection, A hypothesis for long-distance migration of radon within the earth, Earth and Planetary Science Letters, 34, 321–325. Rubinstein, R. Y., 1991, Simulation and the Monte Carlo Method, John Wiley and Sons. Schroeder, G. L., Kraner, H. W. and Evans, R. D., 1965, Diffusion of Radon in Several Naturally Occurring Soil Types, Journal of Geophysical Research, 70, 471–474. Sen, M. K. and Stoffa, P. L., 2013, Global Optimization Methods in Geophysical Inversion, second., Cambridge University Press. Soonawala, N. M. and Telford, W. M., 2002, Movement of radon in overburden, Geophysics, 45, 1297–1315. Tanner, A. B., 1980, Radon Migration in the Ground, A Supplementary Review, in Natural radiation environment III, proceedings of a symposium held at Houston, Texas, April 23-28, 1978, Volume 1 (DOE Symposium Series 51), U.S. Department of Energy, 5–56. Yogi, I. B. S. and Widodo, 2017, Time domain electromagnetic 1D inversion using genetic algorithm and particle swarm optimization, AIP Conference Proceedings, 1861, 030014-1-030014–14. Yogi, I. B. S., and Wido, 2017, Implementation of Hybrid Optimization for Time Domain Electromagnetic 1D Inversion, AIP Conference Proceedings, 1861, 030035-1-030035–4. Zhdanov, M. S., 2002, Geophysical Inverse Theory and Regularization Problems, First., Elsevier Science. | ||
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