Speaker’s name: Musab Ibrahim
Organization: Innervate Engineering
Job title: Founder and CEO
Biography:
Musab Ibrahim is a Chartered Engineer and founder of Innervate Engineering, a UK deep-tech company developing predictive corrosion intelligence and non-intrusive sensing technologies for critical energy infrastructure. With more than 18 years of experience in pipeline integrity and corrosion engineering across the North Sea, West Africa and Southeast Asia, he has worked extensively on the assessment and management of complex pipeline systems.
Presentation title: Bridging the gap between inspections: A predictive methodology for internal corrosion management
Presentation abstract/summary:
A persistent challenge in internal corrosion management is understanding how pipeline condition evolves between inspection or assessment campaigns. This is particularly significant for assets where conventional in-line inspection is difficult or unavailable, leaving integrity teams reliant on historical data, operating records and periodic point-in-time assessments.
This presentation introduces a methodology for connecting these individual assessments into an evolving view of pipeline condition through three steps: predict, contextualise and verify.
First, Corrosion prediction using physics-informed models constrained by established engineering relationships for multiphase flow, corrosion mechanisms and structural integrity assessment, including recognised approaches such as Beggs-Brill, NORSOK M-506 and ASME B31G. Rather than producing a single deterministic result, uncertainty is retained explicitly so that the limits of what can be inferred from the available data remain visible.
Second, the prediction is contextualised using the pipeline's actual operating history. Pressure, temperature, flow conditions, and other available process data are used to reconstruct how the corrosion environment has changed since the previous inspection or assessment. This allows integrity teams to evaluate predicted condition in the context of what the asset has actually experienced rather than relying solely on static design assumptions or periodic snapshots.
Third, predictions are verified against available actual condition. This may include subsequent ILI data, direct inspection, corrosion monitoring measurements, or targeted non-intrusive condition measurements. Differences between predicted and observed condition are used to recalibrate the assessment, refine uncertainty, and improve subsequent predictions.
The methodology is not intended to replace inspection or established corrosion assessment practices. Instead, it connects them across time, helping integrity teams identify changing corrosion risk earlier, understand uncertainty, and better target subsequent monitoring, inspection and intervention.