A Data-Driven Model for Subsea Umbilical Integrity Monitoring Using Hydraulic Line Behavior and Flow Deviation Analytics

• Author(s): Malvern Iheanyichukwu Odum ; Iduate Digitemie Jason ; Dazok Donald Jambol
• Paper ID: 1709569
• Page: 259-269
• Published Date: 12-09-2020
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 4 Issue 2 August-2020

Abstract

Subsea umbilicals are vital for delivering hydraulic power, chemical injection, and control signals to subsea production systems. Their continuous and reliable operation is critical to offshore oil and gas infrastructure. However, current inspection-based integrity strategies are reactive, resource-intensive, and often fail to detect progressive failures such as internal leakage, flow restrictions, or fatigue damage. This paper presents a novel data-driven model for real-time integrity monitoring of subsea umbilicals, utilizing hydraulic line behavior and flow deviation analytics. The model employs high-resolution pressure and flow sensor data collected via a distributed acquisition architecture and processed through advanced feature engineering techniques to capture critical indicators such as pressure gradients, flow variability, and behavioral deviations. Core analytical components include statistical thresholding and machine learning-based anomaly detection, enabling the identification of abnormal flow patterns linked to specific failure modes. The model introduces hydraulic behavior signatures, distinct pressure-flow interaction profiles, as diagnostic tools to classify degradation types. Importantly, the framework supports continuous learning and real-time updating, ensuring adaptability to changing operational conditions and reducing false positives. By providing early warnings of integrity threats, this approach enhances operational safety, minimizes downtime, and supports predictive maintenance. The study advances the field of offshore asset management by integrating real-time analytics with intelligent system diagnostics for subsea infrastructure.

Keywords

Subsea Umbilical Monitoring, Flow Deviation Analytics, Hydraulic Behavior Signatures, Data-Driven Integrity Assessment, Real-Time Anomaly Detection

Citations

IRE Journals:
Malvern Iheanyichukwu Odum , Iduate Digitemie Jason , Dazok Donald Jambol "A Data-Driven Model for Subsea Umbilical Integrity Monitoring Using Hydraulic Line Behavior and Flow Deviation Analytics" Iconic Research And Engineering Journals Volume 4 Issue 2 2020 Page 259-269

IEEE:
Malvern Iheanyichukwu Odum , Iduate Digitemie Jason , Dazok Donald Jambol "A Data-Driven Model for Subsea Umbilical Integrity Monitoring Using Hydraulic Line Behavior and Flow Deviation Analytics" Iconic Research And Engineering Journals, 4(2)