2.5 Airborne Electromagnetic Inversion
MOKSHA-EM provides unparalleled imaging capabilities allowing detection of challenging features and formations.
MOKSHA-EM delivers improved resolving power vs CDI and 1D inversions, while being faster than 3D inversion.
MOKSHA-EM differentiates signal and IP effects using our Joint IP Inversion algorithm, ensuring accuracy to real world phenomena.
Intrepid Geophysics provides a 2.5D Inversion service for airborne electromagnetic survey data using our proprietary MOKSHA-EM inversion software. MOKSHA-EM’s core algorithm assumes 2D geology and a 3D source, combining the resolution of a 3D inversion with the speed of a 1D inversion. This enables entire surveys to be inverted rather than a select few flight lines, enhancing coverage and ensuring no flight data is wasted.
A joint IP inversion option is now available, enabling imaging of geological features below previously difficult to process areas such as those covered with induced polarization effects.
Any time or frequency domain system can be supported provided we have documented system configuration. Systems already supported include:
Inversion Applications
Case Studies
This case study of a SPECTREM survey in the Bryah Basin (WA) demonstrates the ability of MOKSHA-EM to indicate geological trends, at depth, for conductors with complex geometries.
Inversion of Excite survey data located in the Abra East project area (WA), demonstrating MOKSHA-EM's joint inversion capabilities.
Publications
Comparing 1D and 2.5D AEM inversions in 3D geological mappingThe advantages of 2.5D airborne electromagnetic inversion in 3D geological mapping applications compared to CDI transforms or simple 1D inversions.
2.5D inversion of airborne electromagnetic data2.5D electromagnetic (EM) modelling computes the response of a 3D source from an arbitrary 2D geoelectrical model.
Improved Structural Mapping and Conductive Targeting Delivered by a new 2.5D AEM Inversion SolverDemonstration of the improvements made in the 2.5D AEM solver, including MPI parallelisation and optimisation of the sensitivity matrix.