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RECONSTRUCTING 3-D GEOLOGY USING GEOPHYSICAL MODELLING AND INVERSIONS ON UNSTRUCTURED MESHES
(Consulting Services And Software For Mineral, Metal, Hydrocarbon, Groundwater, Geotechnical, And Environmental Explorations)

NEWS

February 2024

Geotexera is proud to offer geophysical forward modelling and inversion services to Kraken Robotics in their upcoming project aimed at detecting sub-seabed buried oil pipelines in the Gulf of Mexico.

What clients say...

Alexander Prikhodko

(VP and Chief geophysicist, Expert Geophysics Limited)

Geotexera's services, algorithms/software, interpretation approach, and principles are one of the best on the market and in some ways unrivaled. Generated by Geotexera, inversion results are free of artifacts, close to geology, and clearly distinguish the host environment from structures and discrete targets.
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GEOPHYSICAL MODELLING AND UNSTRUCTURED MESH

Complex Data Require Accurate Modelling
 
At Geotexera, we specialize in 3D geophysical modelling and inversions, leveraging our proprietary software. Our software employs new and advanced techniques and features such as unstructured meshes. Unlike the conventional structured meshes, this cutting-edge technique allows us to quickly and accurately add borehole information, geological contacts, high-resolution topography, and surfaces (generated by Leapfrog, GOCAD, and more...) to increase the reliability of model results.
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GEOPHYSICAL INVERSION

Today, in mineral, oil&gas, water, geotechnical and environmental explorations, new problems and challenges need new and modern solutions. We use advanced geophysical inversion methods (independent, joint, and constrained) to image and reconstruct geologic structures from geophysical data. We model and interpret many types of geophysical data, including magnetic, gravity, gravity gradiometry, magnetotelluric, and seismic.
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FORWARD MODELLING

Forward modelling is an interpretation method in which we generate synthetic geophysical data based on known or experimental physical properties and geometries. This can define the size, position, and contribution of geological structures in geophysical data.

Geophysical Machine Learning

MACHINE LEARNING

Machine learning methods can produce or improve geological maps and predict subsurface resources in geophysical data. We use both unsupervised and supervised machine learning methods on geophysical, geological, geochemical, radiometric, and remote sensing datasets.

A Brief Review of tools and methods

(We use all of them to provide you with the most reliable results ...) 

MESHES

Unstructured meshes (triangular for 2-D and tetrahedral for 3-D

Rectilinear meshes (the old conventional one)

We prefer and recommend (new) unstructured meshes not only because of their higher accuracy but also it is time to move on to real models!

-To learn more about methods (from papers), click on underlined words.

ABOUT US

Our expert geophysicists provide accurate and highly detailed interpretations of the subsurface by applying advanced 3D modelling and inversion methods to geophysical data. We collaborate closely with academia to keep our tools and techniques at the cutting edge of what’s possible in modern geoscience. Geotexera has pioneered unstructured 3D geophysical models and offers the most comprehensive geophysical inversion software currently on the market. We have a proven track record of successfully executing numerous worldwide projects and significantly improving geology models.

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