The Maari oil field, the first OMV operated offshore oil field development, has showcased OMV's impressive technical skills. Following the completion of a field re-development drilling campaign in August 2015, the well configuration currently consists of 10 producers and 1 water injector (with the option to convert a producer into a water injector in the future). Electric Submersible Pumps (ESPs) are installed on all 10 producing wells to provide lift of reservoir fluids to surface. A SCADA system and associated Production Historian Database (PHD) was included in order to capture the high frequency data for well & reservoir surveillance and daily production optimisation of the field. However, there were many challenges in utilising this live data stream from the offshore facility. In particular, it was vital to continuously and effectively monitor and optimise ESP performance in order to improve run life, reduce downtime and ultimately increase production. An integrated decision support system was therefore required for real-time data collection, production monitoring, ESP health check and KPI analysis for proactive decision making and limiting the number of manual processes involved. This paper describes how these challenges were overcome by creating an integrated workflow and aligning the existing system architecture in order to meet the business needs. The system is based on full workflow automation, and has been deployed for data acquisition, validation and analysis by optimising the components of integrated asset management. The system includes an integrated framework connected to various live data sources with different time increments, allowing data aggregation to a reliable intra-day hub. Automated job scheduling has also been built in with a decision support dashboard setup for production analysis and ESP performance monitoring. Based on historical trends, an optimum operating envelope was defined and automatic rules were configured for anomaly detection. The system has provided standardized data access throughout the asset team, streamlining their entire process and resulting in improved efficiency, which has optimised the engineers time for core operational activities. With a secure and automated workflow, and the ability for multiple users to work simultaneously, the system has minimised their downtime, thus improving overall productivity. Utilizing the live data feed for updating of simulation models has allowed quicker comparisons of numerical predictions with analytical forecasts, hence helping to streamline the overall reservoir management of the field. The system has not only assisted the team in meeting their production reporting deadlines, but has also alleviated bottlenecks in their decision-making processes helping to boost overall asset productivity.

Eni Australia is operating the Blacktip gas field offshore Australia and Kitan oil field offshore East Timor. The main challenge was to manage these green fields remotely, with lean resources and strict deadlines covering tasks like data capture and acquisition, data validation, application integration and field analysis efficiently. The implications of the decisions made during the development of a green field are imperative to the optimization of reservoir production. Therefore, an integrated production decision support system was required for performance monitoring of asset health and optimizing production to meet the targets. This paper describes how these challenges were overcome at Eni Australia by centralizing the operations of both fields into a standardized production platform, providing a seamless data transfer from offshore assets to the onshore technical office and establishing the foundation towards a digital oilfield. The platform framework automates the process of acquisition, transfer, conditioning, aggregation and storage of production and operations data into a secure centralized data repository with an auditable amendment history. The production platform provides improved operational and reservoir visibility, which forms the basis for all subsequent analysis and underpins the engineering justification to support operational decisions.The current solution framework provides a multifunctioning system that can be expanded for future assets and fields as they come online by leveraging the investment in the existing system. All the domain experts, from production operations to reservoir engineering, will have the required information at their fingertips for collaborative decision making. Thus, a centralized production platform provides engineers with an improved field visibility for remote field management, proactive decision making and help them to strategically develop fields by optimizing production. Introduction:

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The objective of this study was to determine the highest flowrate through a client's existing flowline without top-of-line condensation rates exceeding a critical value of 0.25 g/m2.s. Automation of the workflow allowed a large combination of operating conditions to be analysed within a shorter timeframe than a traditional flow assurance analysis process. A multiparameter case matrix was developed to analyse the full range of process and environmental variables. A proprietary multiphase flow assurance software in the cloud was used to develop a reference case model. Then a software script was developed to read in the reference case model's code and produce input files for 1,080 cases. All cases were run within 30 minutes in the cloud. Another software script then extracted key data from the 1,080 output files into a single Excel spreadsheet to enable data visualisation and identification of a simple and effective flow rate criterion to limit condensation rates. Automation of the workflow allowed all combinations of variables to be analysed within a shorter timeframe compared to the traditional flow assurance analysis process, which usually analyses a somewhat limited number of suspected worst-case scenarios selected based on engineering judgement. The bulk data resulting from the automated workflow enabled a single integrity limit criterion to be applied with a high level of confidence, namely the fluid temperature measured at a subsea corrosion probe. This simplified integrity limit allows the operators to easily maximise production for any combination of process and environmental conditions, whilst maintaining confidence that they are not exceeding the critical condensation rate.

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