res3dinv 3.19.2
2D and 3D inversion software for processing induced polarization data. It uses the fast least squares method to invert the data, greatly reducing the time required for inversion while ensuring the quality of the inversion results, making it suitable for Wenner（ α、β、γ）、 Dipole Dipole, (AB MN Rolling), Monopole Dipole (A-MN Rolling, MN-B Rolling, A-MN Rectangle), Dipole (A-M Rolling), Schlumberger（ α Various devices such as 2-arrangement and quadrupole sounding rolling can process ground measurement data, as well as underwater measurement data and cross hole measurement data. It is currently a highly recognized IP data inversion software internationally.
Res2Dinv Induced Polarization Inversion Software-1.jpg
Functional characteristics
Quickly perform 2D resistivity and IP inversion using the least squares method
● Support for Winner（ α、β、γ）、 Dipoles, Schlumberger, Tripoles, Middle Ladders, and Unconventional Devices
● Support surface, water, inter well, and delay data inversion
2D support for up to 16000 electrodes and 100000 data points of line
● Support processing of device data with unequal electrode spacing
● Support batch processing of multiple survey lines
Can convert 2D data into 3D data
● Support data input for instruments such as Zonge, GDD, ABEM, IRIS, OYO, etc
RES3DINV parameter
● Support for Winner（ α、β、γ）、 Dipoles, Schlumberger, Tripoles, Middle Ladders, and Unconventional Devices
● Support surface, water, inter well, and delay data inversion
It can process three-dimensional data collected by electrode devices arranged in rectangular grids and at any position, and can process data collected using electrode arrangements in different directions and spacing.
Invert IP data using the complex resistivity method.
Supports a dataset of up to 200000 electrodes and 700000 data points.
Supports parallel processing, supports 64 core multi-core CPUs, and also supports multi CPU PCs.
Output results in commonly used Voxler and Paraview formats.
Featured function display
Comparison between Smooth Inversion Method and Robust Inversion Method
Figure 1-a shows a composite model with a fault block (resistivity of 50 ohm. m) at the bottom left and a small rectangular block (1 ohm. m) at the bottom right. The surrounding medium resistivity is 10 ohm. m, and a test dataset was generated using the Wenner device to generate a simulated cross-sectional view of the apparent resistivity; Figure 1-b shows the conventional smooth constrained least squares method for inversion of quasi cross-sectional images, with the boundaries shown as gradient boundaries; Figure 1-1c shows the pseudo cross-section of the Robust inversion method. In contrast, the model boundary obtained by the Robust model inversion method is clearer.
Product:res3dinv 3.19.2
Lanaguage:english
Platform:Win7/WIN10
Size:1CD