Fluidsdata Presented AI Driven MPFM Workflow Innovations at SPE Workshop

Fluidsdata recently presented at the SPE Workshop held in San Antonio in May 7-8, 2026. The presentation, delivered by Afzal Memon, was titled "Democratizing Fluids Characterization Data with Artificial Intelligence for Accurate MPFM Performance."

The talk focused on two important industry challenges impacting multiphase flow meter (MPFM) performance and engineering workflows:

• Democratization and operationalization of fluids characterization and phase behavior data across engineering teams and workflows with Agentic AI
• Physics backed AI predictions for missing, sparse, outdated or NEW fluid data using existing operator PVT databases

The presentation highlighted how disconnected reports, spreadsheets, and siloed repositories often limit access to fit for purpose fluid data required for accurate MPFM configuration and surveillance workflows. Fluidsdata presented practical approaches with Agentic AI to standardize, QA/QC, centralize, and operationalize fluids characterization data to improve accessibility and engineering efficiency.

Fluidsdata also showcased its physics backed and domain driven AI modeling approach for generating representative phase behavior data from existing operator datasets while preserving data ownership and privacy. The workflow utilizes thermodynamically similar fluids and local interpolation modeling to improve MPFM robustness, reduce sampling and laboratory costs, and accelerate engineering decision making.

The workshop provided an excellent opportunity to engage with industry experts, operators, and clients on the growing role of AI in engineering workflows. Many participants appreciated the practical and domain focused AI perspective shared during the presentation.

Fluidsdata continues to advance its vision of combining domain expertise, physics, and AI to transform fluids characterization data into an intelligent operational asset for the energy industry.