@article{fdi:010064166,
  title = {{G}ravity inversion and uncertainty assessment of basement relief via {P}article {S}warm {O}ptimization},
  author = {{P}allero, {J}. {L}. {G}. and {F}ernandez-{M}artinez, {J}. {L}. and {B}onvalot, {S}ylvain and {F}udym, {O}.},
  editor = {},
  language = {{ENG}},
  abstract = {{G}ravity inversion is a classical tool in applied geophysics that corresponds, both, to a linear (density unknown) or nonlinear (geometry unknown) inverse problem depending on the model parameters. {I}nversion of basement relief of sedimentary basins is an important application among the nonlinear techniques. {A} common way to approach this problem consists in discretizing the basin using polygons (or other geometries), and iteratively solving the nonlinear inverse problem by local optimization. {N}evertheless, this kind of approach is highly dependent of the prior information that is used and lacks from a correct solution appraisal (nonlinear uncertainty analysis). {I}n this paper, we present the application of a full family {P}article {S}warm {O}ptimizers ({PSO}) to the 20 gravity inversion and model appraisal (uncertainty assessment) of basement relief in sedimentary basins. {T}he application of these algorithms to synthetic and real cases (a gravimetric profile from {A}tacama {D}esert in north {C}hile) shows that it is possible to perform a fast inversion and uncertainty assessment of the gravimetric model using a sampling while optimizing procedure. {B}esides, the parameters of these exploratory {PSO} optimizers are automatically tuned and selected based on stability criteria. {W}e also show that the result is robust to the presence of noise in data. {T}he fact that these algorithms do not require large computational resources makes them very attractive to solve this kind of gravity inversion problems.},
  keywords = {{N}onlinear gravity inversion ; {P}article {S}warm {O}ptimization ; {U}ncertainty assessment ; {S}edimentary basin},
  booktitle = {},
  journal = {{J}ournal of {A}pplied {G}eophysics},
  volume = {116},
  numero = {},
  pages = {180--191},
  ISSN = {0926-9851},
  year = {2015},
  DOI = {10.1016/j.jappgeo.2015.03.008},
  URL = {https://www.documentation.ird.fr/hor/fdi:010064166},
}