Perspectives

From the Lab

Technical perspectives on physics-AI hybrid modeling, industrial software development, and the realities of building operational tools for Oil & Gas.

Equipment HealthPredictive MaintenancePhysics-AI

Physics-Informed Equipment Health Monitoring: Catching Degradation Before Failure

Vibration thresholds and statistical outlier alarms catch failures after they've already started. Physics-informed health monitoring catches the drift that causes them.

July 20, 20265 min read

Equipment Health MonitoringPredictive MaintenancePhysics-AI

Physics-Based Equipment Health Monitoring: Catching Degradation Before It Looks Like a Failure

Threshold alarms fire after performance has already degraded. Physics-based residuals catch the deviation while the equipment still looks healthy on paper.

July 13, 20265 min read

Physics-AIMachine LearningModeling

Why Physics-AI Hybrid Models Outperform Pure Machine Learning in Oil & Gas

Pure machine learning models can capture patterns in historical data, but they fall apart outside the training envelope. Physics-AI hybrids don't—and here's why that matters for industrial operations.

May 20, 20263 min read

Flow NetworksMultiphase FlowState Estimation

Multiphase Flow Monitoring with Sparse Instrumentation: A Physics-Based Approach

Most gathering networks operate with 30–50% of measurement points either missing, failed, or unreliable. Here's how physics-based state estimation restores full operational visibility.

April 8, 20263 min read

Engineering ToolsSoftware DevelopmentIndustrial AI

Decision-First Development: Why Most Industrial Software Initiatives Fail and How to Fix It

The failure mode of industrial software projects is almost always the same: a platform is selected before the decision is defined. Here's a better approach.

March 15, 20264 min read