Samarang is a 35-year-old offshore oilfield in Malaysia, operated by Petronas. By 2003, with the declining production trends anddwindling reserves, the field abandonment was on the horizon. SamarangRedevelopment Project was kicked-off in 2012 with a vision to implementIntegrated Operations (IO) as an Asset Management Decision Support tool byimplementing a real time production, reservoir and process surveillance system. For the IO implementation, various intelligent asset decisionprocesses referred as workflow were identified and in various reservoir, production, and operations domains suchas Flow Assurance, Well Performance, Artificial Lift, Production and facilityPlanning and EOR Optimization. These workflow groups are linked to provide an integrated asset decision support system whichwill improve decision quality and operational efficiency. workflowm will deliver value with enhanced asset management by focusing on decisions toimprove reservoir drainage, production, and operations. In the initial phase, well performance workflow group, by acquiring data from the SCADA system andprocessing the real-time analysis workflows, enables the asset team to movefrom a reactive to a pro-active asset management system. ‘Well Status andUptime Calculation’ and ‘Well Rate Estimation’ workflow enable engineers to know in real-time the performance andstatus of wells to reduce the production deferment. The ‘Well Test Validation’ workflow will provide online validation, enhanced test quality andimproved confidence in back-allocation and reservoir modeling leading to betterField Management. ‘GasLift Surveillanceand Optimization’ workflow monitorslift performance, performs diagnostics and optimizes gaslift distribution. UsingReal Time data and integrated software, this solution will enable efficientdecisions with a shorter turnaround timeThus workflows equipthe asset team with cutting edge technology and collaborationenvironment for operational decision making. The IO implementation will help to extend the fieldlife and increase recoverable reserves while facilitating an effectivereservoir management strategy.

Samarang field, operated by PETRONAS Carigali Sdn Bhd (PCSB) is located offshore Sabah, Malaysia with first oil in 1975. The field is undergoing a major redevelopment project with Integrated Operations (IO) being part of initiatives that covers re-instrumentation, telemetry and telecommunication infrastructure installation, Collaborative Working Environment construction and Workflows implementation. Samarang Integrated Operations was designed as an Asset Management Decision Support solution to improve the quality and efficiency of decision processes through implementation of a real time production, reservoir and process surveillance system.Understanding and analyzing the asset performance is not an easy and well-defined process in the current state of operations in Samarang. Lack of proper instrumentation to measure the actual production parameters, delay in data transfers from field operations to office, manual data processing, delay in model updates and a long decision cycle have made it difficult to assess the accurate status, diagnose issues and optimize the production. In order to overcome these challenges and to improve field awareness, 5 workflows were designed and deployed in order to achieve an early milestone of providing real time well performance monitoring, surveillance and optimization. These workflows are:

Increased demand in production and recovery, advancements in technologies and the desire to collaborate expertise across multiple assets are changing the work process at many oil and gas companies. Integrated Operations (IO) program describes the process, performance improvement and transformation of Petronas Carigali (PCSB) production operations. The program aims to help PCSB to address growth, organization and environmental challenges by integrating new transformational technologies with streamlined work processes and enables the followings: Enables a more effective working environment  Work processes are streamlined and automated  Quality information is available and accessible across the organization  Collaborative expertise of multiple locations, teams and domains across distance  Intelligent alarms and alerts for continuous asset awareness  Increase hydrocarbon production and recovery Samarang was the first field selected for end-to-end asset management IO project. Its implementation deliver objective and focus at the whole of the asset operation optimization through providing increasing levels of monitoring and surveillance, diagnosis, optimization and operations transformation in a way that fits PCSB's current IO state as well as future expansion plans.

The goal for mature fields, is to efficiently close the gap between its existing production and its maximum available capacity. For the mature field offshore Borneo, with timeworn infrastructure, old technology and manual data processing, the big challenge was understanding and analyzing the asset performance. With multiple operational locations, dispersed teams and domain experts working in silos, not all the reservoir-production-facility system interactions were considered for strategic decisions. Amount of time spent in the model updates has not only resulted in limited time for engineering analysis, but also resulted in longer decision cycle time. The lack of model readiness in time to respond has led to reactive decisions rather than proactive asset management. The core challenge was – how to leverage investment in real-time operational data to continuously update discipline-specific models facilitating accurate predictions of key events, possible system upsets, and support engineers to proactively manage their production systems to optimize current production while improving overall recovery. This triggered adoption of an Integrated Asset Modeling (IAM) methodology for end-to-end asset optimization. This was achieved by creating an IAM framework that includes the 8 reservoir simulation models, coupled with a common production network model of around 80 strings integrated with a complex process-facilities model. This new business process is supported by an underlying system that keeps model live/up-to-date with the current reservoir and production changes creating Integrated "Live Asset Model" (LAM) for the asset optimization. IAM approach has resulted in accurate metering, debottlenecking and boosting production operational efficiency. End-to-end surveillance of the system and full understanding of hydrocarbon pathway was the key for successful implementation of IAM for the asset optimization. The technique was not only implemented for the short term planning to improve the production using well intervention & optimization techniques, but also for improving reserves by injection of liquids/gases into the reservoir or Enhanced Oil Recovery (EOR) techniques. This case study illuminates the effective use of an IAM approach in the complex mature asset for improved asset production forecasting. Some of the key benefits and early value gains are – Realized the promised reserves expected by the EOR program by optimizing the reserves and production.Delivered integrated solution with a holistic view of the asset, by breaking down the barrier between different disciplines.Accurate estimation of production potential, with a rigorous scientific approach, by integrating reservoir, network, and process models without losing any of the details of the individual models. Promoted collaborative decision making by bringing people, process and technology together via collaborative work environment (CWE)Assessing how the existing surface pipeline network and facilities impact on the overall asset performance.Enhanced development planning by simulating various optimization scenarios and validating the impact of additional/infill wells and quantifying its production gains. The IAM model results emphasize the criticality of such an approach in making decisions for declaring reserves and production profiles throughout field life. It is the first field to implement Integrated "Live Asset Model" concept by automating the relevant time model updates. Leveraging CWE to bring experts across multiple locations, teams and domains for improved quality decisions.

No abstract