Triumph of The Digital Twin Frontier: An Odyssey Unleashing Integrated Asset Modelling for Intelligent Well & Reservoir Management

Abstract Mubadala Energy commenced the Intelligent Well/Reservoir Management digital project initiative in mid-May 2023, spearheaded by the Subsurface team in collaboration with SLB Digital & Integration Team. The goal of the Intelligent Well/Reservoir Management digital project was to create a digital twin version of the offshore platform and to incorporate automated modelling features into the digital twin. Mubadala Energy operated field, "LFS" in Malaysia was selected as the candidate for involvement with this digital project. Mubadala Energy operates the "LFS" field in Central Luconia, off the coast of Sarawak, Malaysia. The "LFS" field is a gas condensate reservoir that started production in early 2022 and produces up to a daily gas production of 600 MMscf/d. The key technical aims for this digitalization project are to perform analytics to manage the subsurface uncertainties and to promote prudent reservoir management practices. The expectation of the business unit is to have a seamless integrated production modelling system from the reservoir to the export stream. Coupled with such initiatives, the project encompasses mainly building physics models for Subsurface, Production and Facilities, and integrating them into a common platform. These three key components of Subsurface, Production and Facilities domain each constitute their own dedicated calibrated model. The challenge is then to ensure that the integrated model platform is seamless, customizable and operationally functional. This paper presents the layout of the overall digitalization project for a new producing field and highlights the key architecture of an "intelligent" integration of asset modelling from both the operator and technology provider's perspectives, providing a holistic and balanced view to the reader. The business driver is to maximize operational efficiency and to create a safe operating environment using digitalization tools. This paper details the intelligent well and reservoir modelling steps, which consists of an Automated Objectives-Driven Workflow (AODW) and explains how these workflows are implemented in a real producing asset environment. From a broader overview perspective, the digitalization project involves integrating various tools into a common platform (i.e., Integrated Asset Modelling - IAM) and creating automated workflows to assist the asset team in well and reservoir management. The paper will also describe how the IAM model is further incorporated into the existing database system of a producing field that utilizes PI information, and subsequently how all these information is then migrated and displayed in a customized Asset Overview (AO) Dashboard. Using the IAM and AO tools, the authors will demonstrate how these tools are being employed for production forecasting and reservoir surveillance purposes. In addition, this paper outlines tangible operational benefits from having an integrated asset modelling tool and finally will highlight some key lessons learned. With the sharing of this information and experience, the authors hope to advance the knowledge bank of the petroleum engineering community. For the Subsurface modelling scope, an updated numerical reservoir model was constructed with the objective to mimic the behaviour of "LFS" field and to generate production forecasts for this field. This reservoir model was built with existing wells coupled with an infill well and was historically matched against actual field production data. The output from the reservoir model was then fed into the production network model. At this stage, a production network model was built to commingle all the reservoir and well production streams into a single stage production separator/sink. Subsequently, the production network model output was then fed into a surface engineering process simulator which, allows a classical surface process engineering material and energy balance simulation to be carried out. The integration of all the Subsurface, Production and Surface model was attained through an Integrated Asset Modelling tool (IAM). In this case, the IAM is utilized to map and integrate all the Subsurface, Production and Facility models which led to the creation of a powerful integrated asset management tool. Towards this end, real-time insights are achieved through the digital twin solution via an Asset Overview dashboard display, enabling stakeholders to access real-time information on asset performance through immediate data exchange, which marks Mubadala Energy's first-ever digital field deployment.