WellInsight

WellInsight leverages AI for modern well log analysis and interpretation, targeting four domains:

AI-BHI - Resistivity and conductivity borehole image analysis (Logging While Drilling and Wireline), utilizing supervised machine learning in conjunction with computer vision. AI-Geostress - Analysis of in-situ and paleo stresses using borehole image interpretation results. AI-1D-MEM - Automates wellbore stability modeling using ML with auto-correlation and linear equation optimizations. AI-Payzone - Provides reservoir heterogeneity insights, secondary porosity, and permeability estimation, and perforation interval selection.

AI-BHI Module Features:

• Upload of .dlis, .lis, .las (2.0, 3.0), .csv well data.
• Display of various types of data: point data, continuous lines, blocky curves, image array data.
• Export of .png, .pdf, .las.
• Borehole image enhancement: pad-based images gap-filling, image calibration, normalization, and cleaning.
• Image interpretation sensitivity analysis (high and low confidence features mapping with user control).
• Automatic borehole image interpretation for vertical, deviated, and horizontal wells: structural (conductive and resistive bedding planes, elongated bedding planes in horizontal wells, conductive and resistive continuous natural fractures, faults), sedimentary features (wags, stylolites, compaction and solution seams, borrows), and mechanical features (breakouts and drilling-induced fractures for vertical wells).
• Interpreted features intensity estimation.
• True and apparent dip conversion, and vice versa.

AI-Geostress Module Features:

• Stress orientation estimation and visualization with different stereonets.
• Automatic stress evaluation and display.
• Stress ratio identification.
• Stress regime identification and visualization.
• Fracture and fault clustering and analysis.

AI-1DMEM Module Features:

• Well trajectory estimation.
• Missing elastic properties modeling using empirical equations.
• Overburden stress estimation with auto-calibration, using Machine Learning.
• Pore pressure estimation with auto-calibration, using Machine Learning.
• Elastic moduli estimation with auto-calibration, using Machine Learning.
• Rock strength estimation with auto-calibration, using Machine Learning.
• Minimum and maximum horizontal stresses estimation with auto-calibration, using Machine Learning.
• Fracture gradient estimation with auto-calibration, using Machine Learning.
• Wellbore stability modes - safe mud window estimation.

AI-Payzone Module Features:

• Porosity estimation using only borehole image data.
• Permeability estimation using only borehole image data with finite element Darcy flow modeling.
• Porosity and permeability partitioning into primary and secondary components.
• Autonomous perforation interval selection.