SimPEG.potential_fields.gravity.Simulation3DDifferential#
- class SimPEG.potential_fields.gravity.Simulation3DDifferential(mesh, rho=1.0, rhoMap=None, **kwargs)[source]#
- Bases: - BasePDESimulation- Finite volume simulation class for gravity. - Notes - From Blakely (1996), the scalar potential \(\phi\) outside the source region is obtained by solving a Poisson’s equation: \[\nabla^2 \phi = 4 \pi \gamma \rho\]- where \(\gamma\) is the gravitational constant and \(\rho\) defines the distribution of density within the source region. - Applying the finite volumn method, we can solve the Poisson’s equation on a 3D voxel grid according to: \[\big [ \mathbf{D M_f D^T} \big ] \mathbf{u} = - \mathbf{M_c \, \rho}\]- Attributes - Cell center inner product matrix. - Edge inner product matrix. - Edge inner product inverse matrix. - Face inner product matrix. - Face inner product inverse matrix. - Node inner product matrix. - Node inner product inverse matrix. - A list of solver objects to clean when the model is updated - SimPEG - Counterobject to store iterations and run-times.- A list of properties stored on this object to delete when the model is updated - Mesh for the simulation. - The inversion model. - True if a model is necessary - Specific density (g/cc) physical property model. - Derivative of Specific density (g/cc) wrt the model. - Mapping of the inversion model to Specific density (g/cc). - Path to directory where sensitivity file is stored. - Numerical solver used in the forward simulation. - Solver-specific parameters. - The survey for the simulation. - Verbose progress printout. - MccI - Vol - Methods - Jtvec(m, v[, f])- Compute the Jacobian transpose times a vector for the model provided. - Jtvec_approx(m, v[, f])- Approximation of the Jacobian transpose times a vector for the model provided. - Jvec(m, v[, f])- Compute the Jacobian times a vector for the model provided. - Jvec_approx(m, v[, f])- Approximation of the Jacobian times a vector for the model provided. - dpred([m, f])- Predicted data for the model provided. - fields([m])- Compute fields - getA()- GetA creates and returns the A matrix for the Gravity nodal problem - getRHS()- Return right-hand side for the linear system - make_synthetic_data(m[, relative_error, ...])- Make synthetic data for the model and Gaussian noise provided. - residual(m, dobs[, f])- The data residual.