Comparative Analysis and Joint Inversion of MT and ZTEM Data
Exploration Geophysics(2018)
Abstract
Ground Magnetotelluric (MT) data acquired today are typically broadband, covering 0.001 to u003e1000 Hz with inter-site spacing typically at 500 to 1000 m. Airborne Z-axis tipper data (ZTEM) are sampled at higher spatial density but usually band-limited to frequencies u003e30Hz. We analyze a pair of overlapping 3D surveys to examine lateral and vertical spatial sensitivity. The MT data include a 2D line and a 3D survey. The line data also has magnetic tipper data that allows for a direct comparison with ZTEM; in the overlapping frequency range the agreement between the two magnetic data sets is good, with ZTEM showing higher lateral smoothness. CGG’s RLM-3D non-linear conjugate gradient MT-CSEM inversion engine was extended to accurately model the ZTEM data, using measured sensor altimetry data and detailed 3D topography. Both single domain and joint inversions of the ZTEM and MT data were carried out. A suite of inversions were run to test the influence of starting resistivity and regularization parameters on output models, equally for MT, ZTEM, and joint MT+ZTEM inversions to allow for direct comparison. ZTEM single domain inversion results depend strongly on the starting resistivity value, confirming that the method maps relative variations rather than absolute resistivity values, as expected for magnetics-only measurements. Shallower lateral structure shows qualitative agreement with the MT, but at depth resistivity from ZTEM inversion is driven by model regularization only. Joint inversion improved the relatively shallow section, calibrating the ZTEM resistivities and adding continuity between the MT sites. Below around 1000m depth, the 3D resistivity model is controlled by the MT data alone. Our overall conclusion is that today’s 3D broadband MT only benefits from joint MT-ZTEM acquisition and inversion workflows in the case of sparse MT station spacing.
MoreTranslated text
Key words
Magnetotelluric Imaging
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined