Using AI to allow insightful and objective decisions to be made regarding geological uncertainties.
Introduction
ROCKINSIGHT incorporates Computer Vision; developed in conjunction with a supervised Machine Learning technique for thin section image analysis to automatically detect and classify geological features.
The tool provides detailed characterization of micron-scale framework grains, matrix permeability, rock textures, facies, reservoir-scale depositional environments, and more. Its UI allows the creation of reservoir and rock parameters, and interpretation of geological data.
Features
ROCKINSIGHT provides high-precision, consistent, and reproducible results in seconds, visualizing every subsurface grain and pore in detail to produce 3D geological modeling resources.
Permits subsurface data integration and accelerated Value of Information, speeding up the decision-making time-cycle.
ROCKINSIGHT provides the combined offer:
• Fully commercial product • Fully automated thin section interpretation • Multi-scale and multidisciplinary reservoir insights from single image
Fast results
Seconds instead of days, weeks, or even months.
Reliable results
AI algorithms extract knowledge from different sources and reach a final, objective decision.
High precision
Estimated permeability and predicted mercury injection capillary pressure (MICP).
Benefits
- 01Cost reductionThrough speeding up of decision-making, and accuracy of petrographic and other thin section analysis.
- 02Capacity retentionExpert knowledge preservation and technical staff shortage mitigation.
- 03ConsistencyConsistent, non-biased analysis, which is independent of subjective human interpretation.
- 04Improved integrationImprovement of subsurface data integration and Value of Information.
Brochure
Please download the brochure by clicking below.
Talk to us about ROCKINSIGHT.
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