Overview

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AarhusInv is a high performance modeling and inversion code supporting a variety of geophysical data types, configurations, and source-receiver types. It provides efficient and high precision modelling and inversion of any airborne EM configuration and ground based TEM, GCM, ERT, MRS and TDIP configurations.

The high performance is obtained by an efficient code parallelization, iterative sparse matrix solvers and sparse matrix data stored for efficient memory handling. AarhusInv is therefore capable of handling vary large airborne EM surveys in a single spatial constraint model setup (SCI) and utilizing multi core CPU’s.​

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The AarhusInv inversion code is available through the Aarhus Workbench and SPIA program; it cannot be acquired as a standalone program.

 

Key features

• Layer, smooth, blocky and sharp model description

• Model description in a regular 3D grid with scatted data records

• Lateral and vertical constraining of any model parameter

• Prior constraints on any model parameters

• Joint or constraints inversion of different data types and methods

• Depth of investigation estimates (DOI)

• Cole-Cole and Maximum Phase Angle IP inversion

 

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EM Inversion

In general, AarhusInv uses a local 1D model description. The models are laterally and spatially constrained forming pseudo 2D and 3D model spaces. The inversion code is designed to handle data from very big airborne EM surveys and support multi CPU's. Besides the resistivity models, the inversion code also calculates a depth of investigation value (DOI) and a data residual for each resistivity model. The inversion setups are: 

 

• LCI-setup: The models are laterally constrained along the flight lines forming a 2D model space.

• SCI-setup: The models are laterally constrained along the flight lines and across the flight lines, resulting in a 3D model space.

• TEM IP: A full Cole-Cole or Maximum Phase Angle inversion is available to model IP effects in the TEM data.

 

The inversion is done iteratively and it supports:

 

• Smooth models: The resistivity model is discretized using several layers (~10-30) with fixed layer boundaries. The regularization penalizes vertical changes in resistivity using a L2 norm, resulting in a vertical smooth resistivity model.
   

• Blocky models: The resistivity model is discretized using several layers (~10-30) with fixed layer boundaries. The regularization penalizes vertical changes in resistivity using a L1 norm, resulting in a vertical smooth resistivity model.
   

• Sharp models: The resistivity model is discretized using several layers (~10-30) with fixed layer boundaries. The regularization penalizes the number of vertical resistivity
  transitions of a certain size, resulting in resistivity models with relatively sharp vertical resistivity transitions.
   

• Layered models: The resistivity model is characterized by a small number of layers (~4-6). Both layer thickness and resistivity are model parameters.
   

• Prior constraints on any model parameter. The prior constraints can be initialized from grids and directly from the GIS map or can be specified at borehole locations with decreasing strength moving away from the borehole locations.
   

• Depth of investigation (DOI) for each model. The DOI is derived from the Jacobian matrix and a standard and conservative DOI is estimated.

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1D/2D ERT/IP inversion

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For ERT data, a full 1D/2D Cole-Cole, Maximum Phase Angle, Constant Phase Angle or Integrated IP inversion is available.