Title
Implicit structural inversion of gravity data using linear programming, a validation study
Author
van Zon, A.T.
Roy Chowdhury, K.
TNO Defensie en Veiligheid
Publication year
2010
Abstract
In this study, a regional scale gravity data set has been inverted to infer the structure (topography) of the top of the basement underlying sub-horizontal strata. We apply our method to this real data set for further proof of concept, validation and benchmarking against results from an earlier forward modelling done elsewhere.Our aim is to carry out implicit structural inversion, i.e., to obtain a geologically reasonable model, without specifically solving for structure. The 2.5D volume of interest is parametrized with homogeneous horizontal prisms and a two-lithology medium is assumed. A possible regional linear trend and a general floating reference are also inverted for. Using a gridded parametrization, linear programming is used to minimize the L1-norm of the data misfit, relative to a floating reference.Given a known density contrast between the lithologies, an inversion using linear programming has the intrinsic advantage that a relatively sharp image of the sub-surface is retrieved instead of a smooth one. The model recovered is almost bi-modal and its general features seem to be robust with respect to several parametrization scenarios investigated. The floating reference and a linear trend in the data were also retrieved simultaneously. The inversion results, indicating two depressions in the basement, are robust and agree with those obtained earlier based upon detailed 2D forward modelling using many narrow, near-vertical prisms. © 2010 European Association of Geoscientists & Engineers.
Subject
Physics
Gravity
Inversion
Linear programming
Data sets
Forward modelling
Gravity
Gravity data
Gravity inversions
Inversion results
Parametrizations
Proof of concept
Regional scale
Sub-surfaces
Validation study
Volume of interest
Buildings
Linear programming
Lithology
Optimization
Prisms
Two dimensional
Linearization
benchmarking
data set
forward modeling
gravity survey
linear programing
lithology
model validation
parameterization
structural geology
topography
two-dimensional modeling
To reference this document use:
http://resolver.tudelft.nl/uuid:1bcbb8b0-e5ad-4f2c-aad2-e8bf08a3e587
DOI
https://doi.org/10.1111/j.1365-2478.2009.00858.x
TNO identifier
364400
Source
Geophysical Prospecting, 58 (4), 697-710
Document type
article