A leading global geophysical technologies company that develops and provides advanced 3D imaging solutions relevant to oil & gas exploration and production, mineral, hydrological or geothermal exploration, environmental monitoring, and other potential applications. TechnoImaging processes all geophysical data types:  electromagnetic, gravity, magnetic, or seismic, and all types of surveys, whether airborne, land, or marine.

Lin, W., & Zhdanov, M. S. (2019). The Gramian Method of Joint Inversion of the Gravity Gradiometry and Seismic Data. Pure and Applied Geophysics, 1-14.

Zhdanov, M.S., Alfouzan, F.A., Cox, L., Alotaibi, A., Alyousif, M., Sunwall, D., Endo, M., 2018, Large-Scale 3D Modeling and Inversion of Multiphysics Airborne Geophysical Data: A Case Study from the Arabian Shield, Saudi Arabia: Minerals 8, 271.
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Zhdanov, M.S, Endo, M., Cox, L., Sunwall, D., 2018, Effective-Medium Inversion of Induced Polarization Data for Mineral Exploration and Mineral Discrimination: Case Study for the Copper Deposit in Mongolia: Minerals 8, 68.
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Masashi Endo, Leif Cox, David Sunwall, Michael S. Zhdanov, and Eiichi Asakawa, 2018, Geophysical exploration of submarine massive sulfide deposits based on integration of multimodal geophysical data: Near Surface GeoScience, Porto 2018.
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Michael S. Zhdanov and Wei Lin (2017). Adaptive multinary inversion of gravity and gravity gradiometry data. GEOPHYSICS, 82(6), G101-G114.
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Michael S. Zhdanov, Daeung Yoon, Johan Mattsson, Rapid Imaging of Towed Streamer EM Data Using the Optimal Synthetic Aperture Method: IEEE Geoscience and Remote Sensing Letters (Volume: 14, Issue: 2, Feb. 2017).
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l.M. Malovichkoa, N. Khokhlova, N. Yavicha, M. Zhdanov, 2017, Approximate solutions of acoustic 3D integral equation and their application to seismic modeling and full-waveform inversion: Journal of Computational Physics, 346, 1 October 2017, pp. 318-339.
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A.V. Gribenko and M.S. Zhdanov, 2017, 3-D Inversion of the MT EarthScope Data, Collected Over the East Central United States: Geophysical Research Letters 10.1002/2017GL075000.

Ĉuma, Cox & Zhdanov, 2017, Paradigm Change in Interpretation of AEM Data by Using a Large-Scale Parallel 3D Inversion and Moving Sensitivity Domain Approach: Best Papers from the EAGE Conference on Geophysics for Mineral Exploration and Mining, Barcelona 2016.

Martin Cuma and Michael S. Zhdanov, 2017, Continental-scale joint inversion of Alaska and Yukon gravity and magnetic data: First Break, 35, No 9, September 2017.
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Martin Čuma, Alexander Gribenko, Michael S. Zhdanov. 2017, Inversion of magnetotelluric data using integral equation approach with variable sensitivity domain: Application to EarthScope MT data: Physics of the Earth and Planetary Interiors, 270, September 2017, pp. 113-127.
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Hongzhu Cai; Michael S. Zhdanov, 2017, Joint Inversion of Gravity and Magnetotelluric Data for the Depth-to-Basement Estimation: IEEE Geoscience and Remote Sensing Letters ( Volume: 14, Issue: 8, Aug. 2017 )
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Glass Earth® Model
Glass Earth® is the toolset of proprietary imaging and analysis technologies developed by TechnoImaging® to render transparent the top kilometers of the strata of the Earth, precisely revealing the geological, hydrological and manmade formations beneath the surface.

EMVision® software package by TechnoImaging® was developed for processing, 3D inversion and 3D modeling of all kinds of geophysical data.  EMVision® makes it possible to transform into Earth models data sets of any size, including extremely large surveys, with the option of integration and joint inversion of different types of geophysical data.

  • 3D forward modeling based on the integral equation (IE) method with multiple inhomogeneous domains ensures high stability and accuracy of the results
  • The moving sensitivity domain approach provides unique capability of 3D inversion of the large-scale geophysical surveys to models with the fine-grid discretization
  • The joint 3D inversion with Gramian constraint delivers an integrated geophysical model based on multimodal geophysical data
  • 3D inversion with focusing regularization provides images of the geological targets with sharp and focused boundaries

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