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SubsurfaceAI 2024 Module List

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SubsurfaceAI 2024 comprises 21 modules, all integrated within a unified database and visualization environment. Each of the 7 software packages includes relevant modules designed to enhance subsurface exploration and production.

Module 1: Multi-Scale Database

The foundation of SubsurfaceAI, supporting multi-scale subsurface data from core plugs, seismic, and production.

Module 2: Integrated Visualization Environment

Comprehensive visualization for subsurface data interpretation, integration, and modeling

Module 3: Well Log Data Analysis and Prediction

Interactive well log calculation and data analysis with machine learning predictions.

Module 4: AI for Core Photo Interpretation and Prediction

AI-assisted lithofacies classification and petrophysical property prediction from core photos.

Module 5: Geologic Correlation of Well Logs

Interactive correlation of stratigraphic boundaries and facies from well logs.

Module 6: Formation Property Modeling & Prediction

Predict well formation properties using machine learning and geostatistical workflows.

Module 7: Near Wellbore Heterogeneity Modeling and Upscaling

Model lamina-scale heterogeneity to reconcile differences between core plugs, well logs, and static reservoir models.

Module 8: 2-D & 3-D Seismic Interpretation

Complete workflow solutions from well tie to domain conversion for both 2-D and 3-D seismic interpretation.

Module 9: Volume Interpretation and Advanced Visualization

3-D volume interpretation of seismic data with advanced visualization techniques.

Module 10: AI for Seismic Interpretation

AI-assisted workflows for 2-D and 3-D seismic interpretation.

Module 11: Seismic Attribute Calculation and Interpretive Processing

Interactive calculation and enhancement of over 100 seismic attributes.

Module 12: Seismic Attribute Analysis

Qualitative and quantitative analysis tools for seismic attributes in reservoir characterization.

Module 13: Data Analysis

Estimate probabilities, cross-correlations, and variograms for multiple properties on horizons, intervals, strata-grids, cores, well logs, and reservoir models.

Module 14: Rock Physics Modeling and Facies Classification

Build rock physics templates based on elastic models for quantitative pre-stack inversion and facies classification.

Module 15: Machine Learning for Subsurface Data Integration

Integrate subsurface data from cores, well logs, seismic attributes, completions, and production into maps or 3-D models for informed decision-making.

Module 16: Geostatistics for subsurface Data Integration

Robust geostatistical toolbox for integrating spatial data in the subsurface, including variogram modeling, collocated kriging, and conditional co-simulation.

Module 17: Production Prediction and Sweet Spot Mapping

Data-driven forecasting of well production and sweet spot mapping through machine learning workflows.

Module 18: Microseismic Data Analytics & Integration

3-D and 4-D visualization and prediction with AI and machine learning to optimize hydraulic fracturing and thermal production.

Module 19: Static Reservoir Modeling

Workflows for building static reservoir models during seismic interpretation.

Module 20: Rule-Based Modeling of Stratigraphic Architectures

Convert conceptual geologic models into digital models and reservoir properties to optimize performance forecasting.

Module 21: Synthetic AI Labels for Model Training

Enhance interpretations with rule-based geologic models and synthetic seismic volumes for more accurate AI model training.

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subsurfaceAI Module List

SubsurfaceAI 2024 Module List

SubsurfaceAI 2024 comprises 21 modules, all integrated within a unified database and visualization environment. Each of the 7 software packages includes relevant modules designed to enhance subsurface exploration and production.

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