In a complex offshore gas network covering both green and mature fields' production to LNG plants, end-to-end integration is essential in building a portfolio that can maintain output. Often in the course of identifying conceptual development opportunities by individual field, this aspect isoverlooked in the broader context of regional optimization. To provide assurance of production sustainability to meet commercial agreement, it is imperative to formulate a development plan that integrates subsurface and surface elements to accurately quantify the remaining reserves and thus the value of the asset. As such, this paper will focus on the methodology of formulating this optimized development plan to incorporate subsurface and surface network modeling and demonstrate the importance of this system for excellent asset management and future development. A series of reservoir evaluations has been performed on a simple one-dimensional model and three-dimensional model depicting the gas reservoir performance. The analysis is further enhanced by using subsurface and surface production network modeling. The key advantages of this workflow compared to the conventional field development plan (FDP) approach is that the field capacity is derived based on pressure interface and existing production constraints to capture any backpressure effects for anyinfill drilling or upgrading projects. In this field example, the integrated network model has resulted in a simpler yet more reliable technical proposal where synergistic opportunities and the associated potential production challenges can be identified.Higher level goals on production attainment and cost avoidance can be achieved through circumventing the potential production hiccups for new development. A detailed analysis workflow using real time data will be discussed as part of technical assurance.The key benefits include full field optimization and opportunities identification,and generation ofa representative business case in a timely manner to meet the demands of managing a dynamic gas system.

PETRONAS Baronia field is a mature oil field with over 45 years of production history, located offshore Sarawak, Malaysia. It consists of several vertically stacked clastic sandstone reservoirs, namely two major reservoirs: S and V2 reservoirs. Both reservoirs have been on production since 1970's with the production strategy evolving over the years to maximize recovery. Natural depletion, infill drilling, water and gas injection, and recently Immiscible Water-Alternating-Gas (IWAG) IOR/EOR strategies have been implemented. All these elements combined with the subsurface uncertainties pose challenges to history match and to conduct probabilistic forecast studies on the dynamic models. Conventionally, the development scenarios for subsurface investigation are limited due to finite computing resources. As PETRONAS is shifting its portfolios to develop more complex and challenging fields, the need for transformation in development concept evaluation is evident. This is key for proper risk and uncertainties quantification. The notable challenges are a) limited number of development scenarios being investigated, evaluated, and compared; b) limited software licenses and infrastructure availability; c) lack of data and decisions traceability. These limitations are addressed by the PETRONAS LiveFDP digital transformation initiative commenced in 2019, through deployment of digital cloud technologies and solutions with scalable High- Performance Computing (HPC) environment. The cloud-based native and Petrotechnical applications enable remote work, ensure full data traceability and auditability, enable multi-realization ensemble analysis, and streamline the automated integration from the reservoir engineering ensemble workflow to economic analysis. Unlimited cloud computing power and licenses facilitate a broader spectrum of reservoir simulation cases to be investigated in a fast-tracked manner. The cloud HPC infrastructure has shortened the history matching cycle from 3 months to 1.5 months. The team has also observed over 5 times speed enhancement on simulation run performance using cloud computing compared to virtual machine and on-premise infrastructure. Utilizing the cloud solutions and ensemble probabilistic approach, the team has achieved over 90% of history match quality through 300 realizations per ensemble running concurrently and completed within 2 hours. The optimized IWAG injection resulted in 2% (~1MMStb) higher oil reserves with 37% less gas injection and 40% shorter injection cycles. This has improved gas sales and prioritization in the field while also monetizing the oil reserves. The ensemble analyses are then visualized using cloud-based data analytics system whereby key realizations and uncertainty parameters are further reviewed and highlighted across various disciplines collaboratively at real time.