Maximizing Production with Real-Time Integrity Operating Windows
Authors: Honjo Shintaro , Matsumoto Shunsaku , Sano Takeshi 
Published: August 2021

A conceptual design of digital Intelligent Production Integrity Operating Windows (IP-IOW) system, which is an unique and transformational solution to the oil and gas offshore industry focusing on maximizing production while optimizing equipment operation, was developed through a Nippon Foundation (NF) - DeepStar® partnership project. This connects the fluids system with the equipment system using IP-IOW architecture and specifications of a digital platform.

The developed digital IP-IOW architecture contains five major evaluation modules, which are Component risk analysis (CRA), Failure Mode and Effect Analysis (FMEA), Failure Evaluation (FE), Maintenance Evaluation (ME), and Reliability Availability, and Maintainability Analysis (RAMA) focusing on critical components, including subsea choke, flowline and riser, topside choke, topside equipment, and crude export line. Each module has a function of monitoring, risk evaluation or analysis of each component based on various existing databases and/or industrial standards.

Component risk analysis (CRA) module is designed as a key module to evaluate individual risk of each component based on the evaluation results of the other modules and to provide IP-IOW dashboards through operation and maintenance analysis methods. CRA module analyzes operation and maintenance based on the likelihood of failure (probability of failure) as a function of operation and maintenance conditions and impact of the damage. Calculated safety operating windows (SOWs) and reliability operating windows (ROWs) would be indicated on the IP-IOW dashboard.

In this project, detailed gap analysis was also conducted to gain an understanding of what relevant industry standards and practices have been published and how these publications have gaps with respect to IP-IOW. A completed search was made of technical indices and reference sources to identify codes and standards that may or can be used for developing Integrity Operating Windows (IOWs) for topside fixed equipment. Current API, DNV, and EI applicable recommended practices (RP) cover damaging effect, in-service inspection, risk ranking, repair items prioritization, and alteration of fixed equipment systems. However, the RPs do not cover how to integrate industry best practices into a real-time digital operating environment that is integral to the next generation O&M system. A critical recommendation is to connect the systems digitally allowing for data analytics using the Digital Twin of the asset.

Several case studies on module development were conducted to demonstrate an example of the module development process and the workflow of module. RAM analysis on one of selected offshore production facilities identified top 30 high risk components from around 1200 components. A pilot physical model was also developed to enable the embodiment of a new industry recommended practice for offshore large scale of FPSO asset. This conceptual pilot has used the topside choke sand erosion connecting the fluid characterization (multi-phase flow) with the selected equipment to develop the correlation addressing major technical challenges of fixed equipment while maximizing production. An example of validation results of erosion module showed good agreement between actual inspection results and CFD calculation results.

Overall, IP-IOW is designed based on rigorous CFD and field data to predict critical section of system and/or equipment likelihood of failure (LOF), such as Erosion with solids, flow induced vibration (FIV), acoustic induced vibration (AIV), vortex induced vibration (VIV), and corrosion in offshore environment.

Mitsubishi Heavy Industries (MHI) has been sponsored by Nippon Foundation (NF) and DeepStar (DS) Joint Ocean Innovation R&D Program to perform a research study (Phase 1) of project titled "19143 Fixed Equipment Integrity Operating Windows based on Facility Operating Conditions" started from May 2019.