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Infinite possibilities

The delivery of AI to seismic interpretation workflows

AI presents a huge opportunity to improve seismic interpretation especially if used to complement traditional techniques. It has the power to improve the quality, speed and understanding of subsurface data, which is why we’ve designed an integrated intelligence platform with the boost of AI to assist the seismic interpretation workflow.

Work with us to experience the integrated workflow and understand the future of seismic interpretation through our latest offering.

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Our Modules

Building off our core Interpret module our patented and uniquely powerful tools enable you to accurately interpret exactly what you see using a data-driven but interpreter guided approach.

Interpret-1

INTERPRET (Core Offering)

Adaptive interpretation delivers more accurate interpretation in less time. Incorporating the building blocks of machine learning.

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condition

Condition: Produce industry leading data and image quality, sharper and clearer images: Improve signal to noise ratio for optimal structural interpretation and attribute analysis.

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reveal

Reveal: Intuitive colour blending of Seismic Attributes unlocks greater insights into the geology. Simple and easy to use allowing the geoscientist to focus on the subsurface rather than the process.

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Collaborative AI

Collaborative AI: Readily incorporated into existing or new workflows at any level, see how our cutting-edge AI technology is enabling a revolution in subsurface understanding.  

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classify

Classify: Using machine learning, identify different seismic classes and relate them to your geological classes. Directly transfer the learning and models to your favourite geocellular modelling package.

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validate-5

Validate: Is your geological model appropriate? Efficiently validate your interpretation and model. Correlate synthetic seismic volumes generated from your geological interpretations with the original seismic data.

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IPS2-1

Infill Drilling

Purpose

Characterise channel systems in complex clastic reservoirs for secondary recovery purposes and infill drilling.

  • Workflow Frequency Decomposition & High Definition Frequency Decomposition.
  • RGB colour blending.

Outcome

  • Better characterisation of channel systems.
  • Identification of potential unswept areas.
  • Defined accurate locations for infill drilling and for enhanced secondary recovery.

Infill Drilling

Reservoir Characterisation

Drilling Hazard Identification

Model Validation

The Geoteric Approach

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Interpreter-led design and process

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Dynamic data classification

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Data-driven decision making

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Greater certainty

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Real-time training

Decode, De-risk, Deliver

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