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Computation of the gravity gradient tensor due ...

Leonardo Uieda
October 15, 2010

Computation of the gravity gradient tensor due to topographic masses using tesseroids

Leonardo Uieda

October 15, 2010
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  1. Computation of the gravity gradient tensor due to topographic masses

    using tesseroids Leonardo Uieda 1 Naomi Ussami 2 Carla F Braitenberg 3 1. Observatorio Nacional, Rio de Janeiro, Brazil 2. Universidade de São Paulo, São Paulo, Brazil 3. University of Trieste, Trieste, Italy. August 9, 2010
  2. Outline The Gravity Gradient Tensor (GGT) What is a tesseroid

    Why use tesseroids Numerical issues Modeling topography with tesseroids Topographic effect in the Paraná Basin region Further applications Concluding remarks
  3. Gravity Gradient Tensor Hessian matrix of gravitational potential GGT =

      gxx gxy gxz gyx gyy gyz gzx gzy gzz   =           ∂2V ∂x2 ∂2V ∂x∂y ∂2V ∂x∂z ∂2V ∂y∂x ∂2V ∂y2 ∂2V ∂y∂z ∂2V ∂z∂x ∂2V ∂z∂y ∂2V ∂z2          
  4. Gravity Gradient Tensor Hessian matrix of gravitational potential GGT =

      gxx gxy gxz gyx gyy gyz gzx gzy gzz   =           ∂2V ∂x2 ∂2V ∂x∂y ∂2V ∂x∂z ∂2V ∂y∂x ∂2V ∂y2 ∂2V ∂y∂z ∂2V ∂z∂x ∂2V ∂z∂y ∂2V ∂z2           Volume integrals
  5. Gravity Gradient Tensor Hessian matrix of gravitational potential GGT =

      gxx gxy gxz gyx gyy gyz gzx gzy gzz   =           ∂2V ∂x2 ∂2V ∂x∂y ∂2V ∂x∂z ∂2V ∂y∂x ∂2V ∂y2 ∂2V ∂y∂z ∂2V ∂z∂x ∂2V ∂z∂y ∂2V ∂z2           Volume integrals gij(x, y, z) = ˆ Ω Kernel(x, y, z, x , y , z ) dΩ
  6. What is a tesseroid? Delimited by: 2 meridians 2 parallels

    2 concentric spheres Z X Y r φ λ 1 r
  7. What is a tesseroid? Delimited by: 2 meridians 2 parallels

    2 concentric spheres Z X Y r φ λ 2 r
  8. Why use tesseroids? Good for small regions (Rule of thumb:

    < 2500 km) Observation Point Flat Earth + Rectangular Prisms
  9. Why use tesseroids? Good for small regions (Rule of thumb:

    < 2500 km) and close observation point Observation Point Flat Earth + Rectangular Prisms
  10. Why use tesseroids? Good for small regions (Rule of thumb:

    < 2500 km) and close observation point Not very accurate for larger regions Observation Point Flat Earth + Rectangular Prisms
  11. Why use tesseroids? Usually accurate enough (if mass of prisms

    = mass of tesseroids) Observation Point Spherical Earth + Rectangular Prisms
  12. Why use tesseroids? Usually accurate enough (if mass of prisms

    = mass of tesseroids) Involves many coordinate changes Observation Point Spherical Earth + Rectangular Prisms
  13. Why use tesseroids? Usually accurate enough (if mass of prisms

    = mass of tesseroids) Involves many coordinate changes Computationally slow Observation Point Spherical Earth + Rectangular Prisms
  14. Why use tesseroids? As accurate as Spherical Earth + rectangular

    prisms Observation Point Spherical Earth + Tesseroids
  15. Why use tesseroids? As accurate as Spherical Earth + rectangular

    prisms But faster Observation Point Spherical Earth + Tesseroids
  16. Why use tesseroids? As accurate as Spherical Earth + rectangular

    prisms But faster As shown in Wild-Pfeiffer (2008) Observation Point Spherical Earth + Tesseroids
  17. Why use tesseroids? As accurate as Spherical Earth + rectangular

    prisms But faster As shown in Wild-Pfeiffer (2008) Some numerical problems Observation Point Spherical Earth + Tesseroids
  18. Numerical issues Gravity Gradient Tensor (GGT) volume integrals solved: Analytically

    in the radial direction Numerically over the surface of the sphere
  19. Numerical issues Gravity Gradient Tensor (GGT) volume integrals solved: Analytically

    in the radial direction Numerically over the surface of the sphere Using the Gauss-Legendre Quadrature (GLQ)
  20. Numerical issues General rule: Distance to computation point > Distance

    between nodes Increase number of nodes Divide the tesseroid in smaller parts
  21. Modeling topography with tesseroids Computer program: Tesseroids Python programming language

    Open Source (GNU GPL License) Project hosted on Google Code
  22. Modeling topography with tesseroids Computer program: Tesseroids Python programming language

    Open Source (GNU GPL License) Project hosted on Google Code http://code.google.com/p/tesseroids
  23. Modeling topography with tesseroids Computer program: Tesseroids Python programming language

    Open Source (GNU GPL License) Project hosted on Google Code http://code.google.com/p/tesseroids Under development:
  24. Modeling topography with tesseroids Computer program: Tesseroids Python programming language

    Open Source (GNU GPL License) Project hosted on Google Code http://code.google.com/p/tesseroids Under development: Optimizations using C coded modules
  25. Modeling topography with tesseroids To model topography: Digital Elevation Model

    (DEM) ⇒ Tesseroid model 1 Grid Point = 1 Tesseroid
  26. Modeling topography with tesseroids To model topography: Digital Elevation Model

    (DEM) ⇒ Tesseroid model 1 Grid Point = 1 Tesseroid Top centered on grid point
  27. Modeling topography with tesseroids To model topography: Digital Elevation Model

    (DEM) ⇒ Tesseroid model 1 Grid Point = 1 Tesseroid Top centered on grid point Bottom at reference surface
  28. Topographic effect in the Paraná Basin region Digital Elevation Model

    (DEM) Grid: ETOPO1 10’ x 10’ Grid ~ 23,000 Tesseroids
  29. Topographic effect in the Paraná Basin region Digital Elevation Model

    (DEM) Grid: ETOPO1 10’ x 10’ Grid ~ 23,000 Tesseroids Density = 2.67 g × cm−3
  30. Topographic effect in the Paraná Basin region Digital Elevation Model

    (DEM) Grid: ETOPO1 10’ x 10’ Grid ~ 23,000 Tesseroids Density = 2.67 g × cm−3 Computation height = 250 km
  31. Topographic effect in the Paraná Basin region Topographic effect in

    the region has the same order of magnitude as a 2◦ × 2◦ × 10 km tesseroid (100 Eötvös)
  32. Topographic effect in the Paraná Basin region Topographic effect in

    the region has the same order of magnitude as a 2◦ × 2◦ × 10 km tesseroid (100 Eötvös) Need to take topography into account when modeling (even at 250 km altitudes)
  33. Further applications Satellite gravity data = global coverage + Tesseroid

    modeling: Regional/global inversion for density (Mantle)
  34. Further applications Satellite gravity data = global coverage + Tesseroid

    modeling: Regional/global inversion for density (Mantle) Regional/global inversion for relief of an interface (Moho)
  35. Further applications Satellite gravity data = global coverage + Tesseroid

    modeling: Regional/global inversion for density (Mantle) Regional/global inversion for relief of an interface (Moho) Joint inversion with seismic tomography
  36. Concluding remarks Developed a computational tool for large-scale gravity modeling

    with tesseroids Better use tesseroids than rectangular prisms for large regions
  37. Concluding remarks Developed a computational tool for large-scale gravity modeling

    with tesseroids Better use tesseroids than rectangular prisms for large regions Take topographic effect into consideration when modeling density anomalies within the Earth
  38. Concluding remarks Developed a computational tool for large-scale gravity modeling

    with tesseroids Better use tesseroids than rectangular prisms for large regions Take topographic effect into consideration when modeling density anomalies within the Earth Possible application: tesseroids in regional/global gravity inversion
  39. References WILD-PFEIFFER, F. A comparison of different mass elements for

    use in gravity gradiometry. Journal of Geodesy, v. 82 (10), p. 637 - 653, 2008.