{"title":"利用Matlab对半无限平板重力数据进行反演","authors":"A. Adhi, S. Sismanto, A. Setiawan","doi":"10.15294/jpfi.v15i2.21937","DOIUrl":null,"url":null,"abstract":"Semi-infinite slab modeling has been made through inverse data gravity using Matlab. Inversion of gravity data is done by first determining the simulation data. Forward modeling uses simulation data to produce an initial guess inversion model expressed with parameters n0 (1), n0 (2), n0 (3) and n0 (4). The forward modeling is performed on the next initial guess that the value of the misfit is as small as possible through an iteration using the Jacobian matrix. Accuracy of inversion results is determined by the initial guess and the number of iterations. The results obtained show that inversion modeling is more valid in the inversion modeling process compared to advanced modeling, because the value of the parameters sought is generated from mathematical observations of the observation data. Guesses greatly affect the results of inversions obtained. Initial guesses are given in the form of parameters n0 (1), n0 (2), n0 (3) and n0 (4). The initial guess for the parameters n0 (1), and n0 (2) that are made far deviant does not affect inversion. The initial guess for the parameters n0 (3), and n0 (4) that are made deviating far influences the inversion caused by a very small RCON value so that the result is NAN","PeriodicalId":42020,"journal":{"name":"Jurnal Pendidikan Fisika Indonesia-Indonesian Journal of Physics Education","volume":" ","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2019-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Invers Modeling Gravity Data for Semi-Infinite Slab Using Matlab\",\"authors\":\"A. Adhi, S. Sismanto, A. Setiawan\",\"doi\":\"10.15294/jpfi.v15i2.21937\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Semi-infinite slab modeling has been made through inverse data gravity using Matlab. Inversion of gravity data is done by first determining the simulation data. Forward modeling uses simulation data to produce an initial guess inversion model expressed with parameters n0 (1), n0 (2), n0 (3) and n0 (4). The forward modeling is performed on the next initial guess that the value of the misfit is as small as possible through an iteration using the Jacobian matrix. Accuracy of inversion results is determined by the initial guess and the number of iterations. The results obtained show that inversion modeling is more valid in the inversion modeling process compared to advanced modeling, because the value of the parameters sought is generated from mathematical observations of the observation data. Guesses greatly affect the results of inversions obtained. Initial guesses are given in the form of parameters n0 (1), n0 (2), n0 (3) and n0 (4). The initial guess for the parameters n0 (1), and n0 (2) that are made far deviant does not affect inversion. The initial guess for the parameters n0 (3), and n0 (4) that are made deviating far influences the inversion caused by a very small RCON value so that the result is NAN\",\"PeriodicalId\":42020,\"journal\":{\"name\":\"Jurnal Pendidikan Fisika Indonesia-Indonesian Journal of Physics Education\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2019-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Pendidikan Fisika Indonesia-Indonesian Journal of Physics Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15294/jpfi.v15i2.21937\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"EDUCATION, SCIENTIFIC DISCIPLINES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Pendidikan Fisika Indonesia-Indonesian Journal of Physics Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15294/jpfi.v15i2.21937","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
Invers Modeling Gravity Data for Semi-Infinite Slab Using Matlab
Semi-infinite slab modeling has been made through inverse data gravity using Matlab. Inversion of gravity data is done by first determining the simulation data. Forward modeling uses simulation data to produce an initial guess inversion model expressed with parameters n0 (1), n0 (2), n0 (3) and n0 (4). The forward modeling is performed on the next initial guess that the value of the misfit is as small as possible through an iteration using the Jacobian matrix. Accuracy of inversion results is determined by the initial guess and the number of iterations. The results obtained show that inversion modeling is more valid in the inversion modeling process compared to advanced modeling, because the value of the parameters sought is generated from mathematical observations of the observation data. Guesses greatly affect the results of inversions obtained. Initial guesses are given in the form of parameters n0 (1), n0 (2), n0 (3) and n0 (4). The initial guess for the parameters n0 (1), and n0 (2) that are made far deviant does not affect inversion. The initial guess for the parameters n0 (3), and n0 (4) that are made deviating far influences the inversion caused by a very small RCON value so that the result is NAN