WELLINSIGHT leverages AI for well log analysis and interpretation in four domains:
• AI-BHI: Resistivity and conductivity borehole image analysis utilizing supervised Machine Learning and Computer Vision.
• AI-Geostress - Analysis of in-situ and paleo stresses using borehole image interpretations.
• AI-1DMEM - Automates wellbore stability modeling using ML.
• AI-Payzones - Provides reservoir heterogeneity insights, secondary porosity, permeability estimation, and perforation interval selection.
• AI-BHI: An automated AI engine that interprets borehole images with at least the same level of accuracy as an experienced geologist.
• AI-1DMEM: Models subsurface rock properties at the well level, providing interpretation of data from well logs.
• AI-GeoStress: Identifies and analyzes the fractures within borehole images to provide insights regarding the number of fracture sets present in a rock formation and how the subsurface regime is set to change over time.
• AI-Payzones: A data-driven workflow web application designed to rapidly identify the best perforation zones. Using subsurface interpretations, an output of analysis generated using AI-BHI is a primary input for AI-Payzones.
Highly responsive, able to segment borehole images into different geological or drilling-related features.
Helps identify the safe mud window in an automated way, aiding avoidance of serious drilling-related issues.
Identifies and analyzes fractures within borehole images to provide insights, allowing more efficient fracking.
Able to quickly generate information on high-potential reservoirs to perforate, using borehole images.
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