Modeling Workflow
From data ingestion and model execution, to output generation and final deliverables.
Data Integration
Range-based data appropriate to the selected engagement are gathered
Probabilistic Modeling
Uncertainty distributions are generated for the integrated data
Physics-Based, Probabilistic Modeling
- Application-specific physics and coupled behaviors
- Uncertainty-aware inputs and distributions
- Scenario-based and auditable technical evaluation
Data Review, Analysis, & Key Deliverables
Review data, identify trends, generate insights, visualize findings, recommendations, and deliverables
Technical Credibility
Gaussian technology is grounded in a published body of work covering Gaussian pressure-transient solutions for porous media, well-rate solutions for wells under constant bottomhole pressure, transient flow, streamlines, potential functions, multi-fracture interference, coupled pressure superposition, history matching, and benchmarking against field data and independent simulation workflows.
This work shows that Gaussian methods can be used not only for forecasting, but also for understanding pressure depletion, well productivity, fracture interference, and flow behavior in a technically rigorous way.