Let and denote respectively the functionswhere λ≥1, The author discusses the similarity transformation of the regularizing functionals of these functions and the similar property of their Fourier transformation.
Geophysical inversion under different stabilizers has different descriptions of the target body boundary,especially in complex geological structures.In this paper,we present an extremum boundary inversion algorithm ba...Geophysical inversion under different stabilizers has different descriptions of the target body boundary,especially in complex geological structures.In this paper,we present an extremum boundary inversion algorithm based on different stabilizers for electrical interface recognition.Firstly,we use the smoothest and minimum-support stabilizing functional to study the applicability of adaptive regularization inversion algorithm.Then,an electrical interface recognition method based on different stabilizers is developed by introducing extremum boundary inversion algorithm.The testing shows that the adaptive regularization inversion method does work for different stabilizers and has a low dependence on the initial models.The ratio of the smooth and focusing upper and lower boundaries obtained using the extremum boundary inversion algorithm can clearly demarcate electrical interfaces.We apply the inversion algorithm to the magnetotelluric(MT)data collected from a preselected area of a high-level-waste clay-rock repository site in the Tamusu area.We recognized regional structures with smooth inversion and the local details with focusing inversion and determined the thickness of the target layer combined with the geological and drilling information,which meets the requirement for the site of the high-level waste clay-rock repository.展开更多
文摘Let and denote respectively the functionswhere λ≥1, The author discusses the similarity transformation of the regularizing functionals of these functions and the similar property of their Fourier transformation.
基金supported by the National Natural Science Foundation of China(Nos.41604104,41674077 and 41404057)PRC High-level Radioactive Waste Geological Disposal Project([2014] No.1578)+2 种基金Open Fund of State Key Laboratory of Marine Geology(Tongji University)(MGK1704)Jiangxi Province Youth Science Fund(No.20171BAB213031)Scientific Research Starting Foundation for Doctors of East China University of Technology(DHBK201403)
文摘Geophysical inversion under different stabilizers has different descriptions of the target body boundary,especially in complex geological structures.In this paper,we present an extremum boundary inversion algorithm based on different stabilizers for electrical interface recognition.Firstly,we use the smoothest and minimum-support stabilizing functional to study the applicability of adaptive regularization inversion algorithm.Then,an electrical interface recognition method based on different stabilizers is developed by introducing extremum boundary inversion algorithm.The testing shows that the adaptive regularization inversion method does work for different stabilizers and has a low dependence on the initial models.The ratio of the smooth and focusing upper and lower boundaries obtained using the extremum boundary inversion algorithm can clearly demarcate electrical interfaces.We apply the inversion algorithm to the magnetotelluric(MT)data collected from a preselected area of a high-level-waste clay-rock repository site in the Tamusu area.We recognized regional structures with smooth inversion and the local details with focusing inversion and determined the thickness of the target layer combined with the geological and drilling information,which meets the requirement for the site of the high-level waste clay-rock repository.
