Power of Machine Learning in Dynamic QRA using PyRISK™
We are celebrating our ongoing successful business case with PetroGulf Misr of performing Dynamic QRA for their offshore topside facilities to understand the baseline risk and additional risk with intention to make recommendations if required to reduce the risk to its tolerable limits.
One of the requirements under this project is to perform a Quantitative Risk Assessment to identify the risk. It has been highlighted to PetroGulf Misr team that the limitations of static QRA usually provide an overview of the risk at fixed reference point in time. Such studies involve hundreds, sometimes thousands of scenarios covering operating conditions, manning level and maintenance activities. The cost can be substantial, and a study may need repeating every few years.
Alternatively Optimize Global Solutions and Kageera have offered the utilization of the Dynamic QRA for this challenging project to empower the the decision making for the HSE managers and executives. Optimize Global Solutions’ product in cooperation with Kageera for PyRISK™ unlocks the opportunities of machine learning in the risk management. It supports customers already using PyRISK™ to perform Dynamic QRA to get even more value from the data at no additional cost.
Data Preparation
Given the critical importance of having the right & clean data, Optimize Global Solutions and Kageera prudently apply a holistic approach in executing their oil and gas project differently and remarkably from other competitors where the inception and culmination of the processes are within their expertise and base knowledge. The following processes are applied chronologically to ensure the compliance of the data for further machine learning activities.
1-Problem Definition and Framing out.
2-Functional Block Assessment.
3-Frequency Calculations.
4-Consequence Modeling for governing Cases.
5-Sensitivity Analysis using VB-based PyRISK™
Problem Frame-out
Geisum North Field platform comprises four (4) decks, namely
1-Upper Deck.
2-Main Deck.
3-Machinery Deck.
4-Lower Deck
Red blocks denotes the hazardous operation where the facilities handle hydrocarbon.
Functional Block Assessment
The objective of the function blocks is to identify the global scenarios where the static and dynamic inventories for each key unit operation. Each functional block should include the operating temperature and pressure plus the fluid compositions for further consequence modeling using Phast DNV GL
From P&IDs, pipe size, approximate length, number of flanges, manual valves, instrument connections, etc. are counted to eventually calculate the frequency of failure.
Frequency Calculations
The frequency of leak event is quite important to deeply understand the likelihood of each scenario and the frequency of occurrence of each hazard. Following the latest codes and standards in oil and gas industry, and utilizing of experience in the programming, the VBA-based application of CCE™is empowered to calculate an accurate results of frequencies for various leak sizes scenarios e.g. small leak, medium leak and large leak.
Consequence Modeling
Quantifying the hazard intensity threshold / Severity of each potential hazard is essential for our machine learning solutions.
Data Generation & Dynamic QRA
This step is a combination of science and art where the produced data should ensure proper distribution with intention to avoid over-fitting and under-fittings.
VBA-based application of PyRISK™ (in-house tool programmed by Optimize and kageera) empowered with thremo-dynamic data from Phast and has the ability of running various sensitivity cases . This cutting-edge tool was quite imperative to massively decrease the analysis time of nearly 65% compared to the conventional ways of working.
Front-end Machine Learning Application
Starting from Data Exploratory through out algorithms testing and culminating with the most accurate predictive model selection is one of the outstanding strength of Kageera which enables our smart solutions to take place in the industry with full recognition from our clients.
