Digitalization for Effective Performance Management Using Key Performance Indicators in Miscible Gas Injection Projects in South Oman

Abstract

South Oman has several pre-Cambrian reservoirs that are highly pressured (400-1000 bar), deep (3-5 km) and critically sour (H2S up to 10%). The combined STOIIP of these reservoirs makes it one of the largest gas EOR projects in the world. The objective here is to highlight the key performance indicators and digitalization techniques used for continuous and effective well, reservoir and facility management (WRFM) and production optimization, while honoring the facility constraints and gas export requirements. Real time pressure data such as tubing head pressures, injection/production rates along with other data including maps, static pressures and production logs are used to define an appropriate set of performance metric at various levels, e.g. reservoir, sector or well. Digitalization of surveillance data helps in real time production optimization such as offtake management based on creaming curves according to gas sink availability and facility constraints. Key business performance indicators include gas utilization efficiency; MGI performance indicators include incremental oil, throughput, instantaneous and cumulative voidage replacement ratios, gas breakthrough level and time, ratio of reservoir pressure to the target minimum miscibility pressure; and facility constraints are optimized through gas balance, along with tracking field performance against the initial FDP forecasts. Real time performance data is tracked using a commercial Real-Time Data Analysis tool (RTDA) and Database Analytics Visualization Tool (DAVT), with surveillance indicators targeted at well, reservoir and facility level. The above-defined Key Performance Indicators (KPI) are tracked against predictions from the field development plan in web-based portal developed at PDO (Nibras). Digitalization has enabled quick and effective monitoring of these KPI, short-term optimization of injection distribution and offtake rates to maximize oil production and overall value within facilities constraints and varying export gas commitments based on South Oman Gas Line (SOGL) network optimization. Using dimensionless plots and a standardized set of parameters help in developing a common understanding and benchmarking the MGI reservoir response with analogs and amongst different reservoirs. This work presents a set of performance KPIs and short-term optimization methodology using digitalization and LEAN framework that are tracked in a web-based portal, RTDA and DAVT. It provides means to facilitate offtake decisions to meet variable export requirements while honoring facilities constraints, assess reservoir performance, providing valuable insights that helps in speedy reservoir management decisions. This process has been replicated across PDO for all related MGI projects and can benefit other development types, e.g. chemical/steam injection.