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Leveraged on the abundant weight data comprised of more than 200 offshore platforms, a smart digitalized analytical tool called i-WEIGHT, an integrated weight control tool consisting of three (3) main modules: centralized multi-discipline weight database module for all offshore platforms, seamlessly linked with Insights dashboard module in providing actionable insights, and weight predictive module supported by Machine Learning (ML) model was developed. This paper discussed the Minimum Viable Product (MVP) Phase 1 development outcome, using a close-loop weight control ecosystem for continuous update of validated weight data in Module 1, and eventually improve & enhance capability of both the EDA and Predictive module. Using a supervised machine learning algorithms, the identified target variables were observed to provide weight prediction between 16% to 38% of Mean Absolute Percentage Error (MAPE), using Extreme Gradient Boosting Regressor (XGBR) algorithm. Top 10 important features were identified for each target variable, which provide insights to the operators on critical data required for topside with identified missing equipment weight data for future i-WEIGHT improvement. Based on more than 200 integrated platform topside data gathered for this study, consolidated insights from the data enabled operators to identify the threat of current data quality and thus bringing forward a promising opportunity to enhance platform weight data management system. Having a centralized and automated platform weights data, this tool has the potential answers for United Nations’ Sustainability Development Goals, in particular Goal 9.4, where the study represents a small but crucial step to upgrade from an existing conventional process into a digitally driven operation, introducing a sustainable ecosystem in offshore structure weight management, thus fostering sustainable growth within the industry.

Mini Remotely Operated Vehicle (mini-ROV) technology has been utilized to perform underwater inspection with optimized Risk-based Underwater Inspection (RBUI) scope for offshore platforms which conventionally utilize divers and ROV supported by Dynamic Positioning II Diving Support Vessel (DPII DSV). This offshore technology was introduced by launching mini-ROV from platform deck to perform General Visual Inspection (GVI), Cathodic Potential (CP) Survey, Flooded Member Detection (FMD) & Ultrasonic Thickness (UT) measurement with customized mini-ROV integration with other tooling. The small size ROV is light and easy to handle by technician onboard platform deck. It is also capable to enter congested areas as it is easily maneuvered, which help to capture close visual of the findings. During emergency, the mini-ROV can be mobilized instantly at site to support any GVI related scope. PETRONAS has successfully deployed this technology at four platforms in one of the operating regions from 2017 to 2021 with cost saving of 30%–50% compared to conventional method. The successful implementation in PETRONAS can become benchmark and reference for other Oil & Gas operators as an alternative to conduct optimized RBUI scope which can contribute to lower Operating Expenditure (OPEX).

This paper describes the SPM Integrity Management approach using risk based strategies for Single Point Mooring (SPM) throughout its asset life cycle, to ensure that there is a structural integrity management processes are implemented and SPM asset fitness for purpose is always maintained. SPM is one of the most important assets for any oil and gas upstream business, as its primary function is for product export and offloading operations. PETRONAS UPSTREAM currently operate seven (7) Single Point Mooring (SPM) assets for its Malaysia Upstream/ Downstream. To manage the integrity of the SPMs, an Integrity Management system has been developed and includes newer assets and those that are approaching or exceeding design lives. To optimize and focus limited resources toward critical activities, a SPM risk-based strategy and methodology for the SPM assets has been developed. The risk based inspection approach is aligned with the Structural Integrity Management (SIM) processes of DATA, EVALUATION, STRATEGY PROGRAM of the API RP2SIM code of practice. A qualitative risk based integrity management has been developed and for its implementation, inspection and maintenance activities shall target high expenditure items. SPM design, characteristic, assessment, and inspection data have been compiled and utilized in the risk based approach development. With this risk-based approach, PETRONAS can optimize and significantly reduce its inspection and maintenance activities whilst keeping operational risk levels within acceptable limits. The risk-based approach provides that added advantage to look at inspections and maintenance activities critically and make informed decisions on resourcing and aligning inspection & maintenance campaigns for the future. Inspection and maintenance measures also include an anomaly management, RBI, data management and inspections scopes of work which are being digitized and maintained within the Company's Structural Integrity Compliance System (SICS).

The objective of this paper is to demonstrate the best practices of Topside Structural Integrity Management for an aging fleet of more than 200 platforms with about 60% of which has exceeded the design life. PETRONAS as the operator, has established a Topside Structural Integrity Management (SIM) strategy to demonstrate fitness of the offshore topside structures through a hybrid philosophy of time-based inspection with risk-based maintenance, which is in compliance to API RP2SIM (2014) inspection requirements. This paper shares the data management, methodology, challenges and value creation of this strategy. The SIM process adopted in this work is in compliance with industry standards API RP2SIM, focusing on Data-Evaluation-Strategy-Program processes. The operator HSE Risk Matrix is adopted in risk ranking of the topside structures. The main elements considered in developing the risk ranking of the topside structures are the design and assessment compliance, inspection compliance and maintenance compliance. Effective methodology to register asset and inspection data capture was developed to expedite the readiness of Topside SIM for a large aging fleet. The Topside SIM is being codified in the operator web-based tool, Structural Integrity Compliance System (SICS). Identifying major hazards for topside structures were primarily achieved via data trending post implementation of Topside SIM. It was then concluded that metal loss as the major threat. Further study on effect of metal loss provides a strong basis to move from time-based maintenance towards risk-based maintenance. Risk ranking of the assets allow the operator to prioritize resources while managing the risk within ALARP level. Current technologies such as drone and mobile inspection tools are deployed to expedite inspection findings and reporting processes. The data from the mobile inspection tool is directly fed into the web based SICS to allow reclassification of asset risk and anomalies management.