موسسه ژئوفیزیک دانشگاه تهرانفیزیک زمین و فضا2538-371X46420210120A Combination of Monte-Carlo and Damped Least Square Inversion Method for Determining Radon Source in Geothermal CaseA Combination of Monte-Carlo and Damped Least Square Inversion Method for Determining Radon Source in Geothermal Case1031167644110.22059/jesphys.2020.291763.1007174FANandiHaerudinAssociate Professor, Department of Geophysical Engineering, Faculty of Engineering, University of Lampung, Bandar Lampung, IndonesiaIda Bagus SuanandaYogiAssistant Professor, Department of Geophysical Engineering, Faculty of Engineering, University of Lampung, Bandar Lampung, Indonesia0000-0002-3080-7695Journal Article20191116Radon 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.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.https://jesphys.ut.ac.ir/article_76441_e166c34d684c13d2fc1a583898959b5f.pdf