The goal for mature fields, is to efficiently close the gap between its existing production and its 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.