SimPEG.potential_fields.gravity.Point#

class SimPEG.potential_fields.gravity.Point(locations, components='gz', **kwargs)[source]#

Bases: BaseRx

Point receiver class for gravity simulations

The Point receiver defines the locations and the components of the gravity field that are simulated at each location. The length of the resulting data vector is n_loc X n_comp, and is organized by location then component.

Important

Density model is assumed to be in g/cc.

Important

Acceleration components (“gx”, “gy”, “gz”) are returned in mgal (\(10^{-5} m/s^2\)).

Important

Gradient components (“gxx”, “gyy”, “gzz”, “gxy”, “gxz”, “gyz”) are returned in Eotvos (\(10^{-9} s^{-2}\)).

Parameters:
locations: (n_loc, 3) numpy.ndarray

Receiver locations

components: str or list of str

Data component(s) measured at each receiver location. Use a str for a single component or a list of str if multiple components are simulated at each location. Component choices are:

  • “gx” –> x-component of the gravity field

  • “gy” –> y-component of the gravity field

  • “gz” –> z-component of the gravity field (DEFAULT)

  • “gxx” –> x-derivative of the x-component

  • “gxy” –> y-derivative of the x-component (and visa versa)

  • “gxz” –> z-derivative of the x-component (and visa versa)

  • “gyy” –> y-derivative of the y-component

  • “gyz” –> z-derivative of the y-component (and visa versa)

  • “gzz” –> z-derivative of the z-component

  • “guv” –> UV component

Attributes

nD

Number of data

Galleries and Tutorials using SimPEG.potential_fields.gravity.Point#

PF: Gravity: Tiled Inversion Linear

PF: Gravity: Tiled Inversion Linear

Forward Simulation of Gravity Anomaly Data on a Tensor Mesh

Forward Simulation of Gravity Anomaly Data on a Tensor Mesh

Forward Simulation of Gradiometry Data on a Tree Mesh

Forward Simulation of Gradiometry Data on a Tree Mesh

Least-Squares Inversion of Gravity Anomaly Data

Least-Squares Inversion of Gravity Anomaly Data

Sparse Norm Inversion of Gravity Anomaly Data

Sparse Norm Inversion of Gravity Anomaly Data

Cross-gradient Joint Inversion of Gravity and Magnetic Anomaly Data

Cross-gradient Joint Inversion of Gravity and Magnetic Anomaly Data