Your partner for spatial data science
What We Do
Geostatistical Resource Modelling Solutions
Our resource modelling expertise helps our costumers manage their resources by improving knowledge of their assets.
- Evaluation of mineral resources and reserves in complex geological environments.
- Stochastic models for subsurface characterization, uncertainty and risk evaluation.
- Optimize the dynamic of fluid flow in gas storage.
- Risk characterization for CO2 and H2 geological storage.
Spatial Data Science and Artificial Intelligence
We are able to deploy state of the art solutions for spatial problems in diverse areas, with a focus on mining, energy, and the environment.
- Machine Learning tools for optimized sampling of resources.
- Real time monitoring of subsurface geomechanical conditions.
- Smart Mining - Real time monitoring and updating of mineral resources and reserves.
- Mine planning, reserves reconciliation, decision assistance.
State of the Art Integrated Geophysical Methods
We have a large experience in the development, implementation and application of geophysical seismic inversion techniques.
- Geostatistical Seismic Inversion for subsurface properties characterization, uncertainty and risk evaluation.
- Seismic-driven inversion for geomechanics modelling.
- Seismic Inversion to characterize the risk of CO2 and H2 geological storage.
- Multiphysics inversion to characterize fluid dynamics and risks of CO2 and H2 geological storage.
Our Projects
Seismic-driven geomechanical modelling
The aim of this ongoing project is risk evaluation during the drilling and productions activities in deep subsurface environments, either for oil and gas production or CO2 and Hydrogen storage. We developed for this project a software solution for Geomechanical Seismic Inversion, in partnership with UFRGS, in Brazil, and an oil industry company. This software accomplishes two main tasks:
- Creation of a subsurface geomechanical model based on geostatistical seismic inversion of elastic properties.
- Creation of a Pore Pressure Model based on machine learning techniques and geostatistical simulations.
Risk analysis in early stages of exploration of oil and gas reservoirs
In this project we develop a multidisciplinary Risk Analysis system for the initial phases of exploration of mineral resources, integrating expert knowledge with geological and geophysical historical data. Mind2Earth develops the fundamental software for the two phases of this project.
- Identification of the most relevant geological features for a given lead/prospect. Generation of adequate 3D models geological scenarios with stochastic simulation methods.
- Using machine learning methods (GAN – Generative Adversarial Networks) and spatial data analysis techniques, characterize, test and rank, the most consistent of the models created and the most likely to succeed, obtaining uncertainty estimates.
Mining Digitalization and Real Time Mining
We are developing a set of tools integrated in the modern mining industry strategy of mining digitalization. We developed two main platforms integrating the concept of Real Time Mining, in the interface with heterogeneous mineral orebody characterization: Uncertainty of Mineral Resources and Real Time Mining : Fast Updating of Resources; and Integrating Uncertainty and Risk in Dynamic Reserves.
In our Uncertainty of Mineral Resources project, we develop software allowing Uncertainty of Mineral Resources evaluation in a mineral orebody. The software simulates the main metals content in order to provide not only the most probable value at any spatial location of a block model but also the uncertainty associated with those estimated values. Our software is based on Direct Sequential Simulation algorithms.
Software
Geostatistical Seismic Inversion Toolkit
Our state of the art inversion solutions are built with speed and flexibility in mind. Compare several inversion methods, integrate previous models, assess uncertainty, all that is easier with our software. Ask us about cloud support!
Mining reserves update
Built to deal with massive data sets, our software integrates uncertainty into your mineral reserves estimates in a seamless workflow. Our state of the art model coupling algorithms permit the model uncertainty to be assessed at any arbitrary shape within the mineral reserves model.
Geostatistical mineral resources evaluation and uncertainty assessment
Mind2Earth, in cooperation with the mine of Somincor (Lundin), developed a software for Geostatistical Resources Evaluation and Uncertainty Assessment, based on a stochastic simulation methodology: Direct Sequential Simulation. The resources are evaluated per oretype for different metal grades and the uncertainty is reported for each block.
CONNECT WITH US
Rua do Campo da Bola, 24, 2705-597 São João das Lampas, Sintra, Portugal
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