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Upgrade Your Signal Processing AI

Synthetic geophysical data for machine learning exploitation 

Our solutions provide a realistic and diverse set of simulated data, enabling the development of signal processing models that succeed in complex real-world scenarios. Click here to explore our technology.

Our Approach

Coupling thermodynamic 

electromagnetic and mechanical influences at the molecular-level 

First we build a subatomic system with realistic geology, then we simulate it's evolution under environmental influences

Governing

Equations

External

Forces

Boundary  Conditions

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Customized

Survey

Design

Subatomic

Model

Noise & Sensor Effects

SynSignal's

Data

Subsurface Insight

Machine Learning Model

Can utilize new patterns within the interactions of physical fields

Optimized for real world application​

Can be trained to reproduce molecular-level subsurface information

Discover how our unique approach to data generation works to expand the subsurface knowledge accessible through model-based processing. Let us help you optimize your model's performance.

What We Provide

Data founded on state-of-the-art physics and mineral models

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Physical Simulation

Novel computational physics workflows fine-tuned for the massive size of geologic molecular structures and adapted to the thermodynamic complexities of environmentally-open subsurface systems. 

Compact Data

Efficient reduced representations of the computed physical state. Minimized final dataset reflecting surveying constraints (the locations and equipment-determined times of measurement). 

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Geology Models

Randomly generated synthetic rocks with pores, fractures, and molecular detailing rspect mineral crystallization. Large scale rock mass alteration by a range of structural features, including faults and joints.

Key Features

Explore our comprehensive features including modern machine learning approaches for geophysical data processing

Unlock the full potential of your geophysical measurments with our advanced features. Let us help you achieve superior performance.

Why Use SynSignal

Avoid Unreasonable Assumptions

Forces can be unknown, correlated, co-existing, and low frequency. Multiples and masking from strong reflectors can be present in the data. Gain insight from records of real world situations where typical geophysical interpretation fails.

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