Optimization of Production Portfolio with Dynamic Compositional Fluid Properties from Rock to Stock - A Successful Case Study for a Countrywide Network
Authors: Asarpota Jyotsna , Rodriguez Jose Antonio , Hernandez Labrador Cristina , Ge Haoyou , Pires Joshua , Mogensen Kristian , Saputelli Luigi A 
Published: November 2020

ADNOC has completed the second phase of its ambitious integrated capacity model (ICM) with the overall aim to optimize its fluid production portfolio from the well level to the processing facilities. The business drivers are to establish capabilities to optimize high-value products and proactively react to market demand changes effectively. Such capabilities required a robust thermodynamics engine with component-wise tracking based on a country-wide capacity model network comprised of a myriad of wells, pipelines, and separators.

Fluid samples are not available for all the wells in a field. An innovative workflow was created to assign appropriate composition at the well level based on the data set available for a subset of wells. The captured compositions were then passed to the ICM's hydraulic calculation engine to track the fluid compositions at the required nodes across the network.

The existing data model was expanded and user interfaces were created to capture the complexities within the network and visualize the changes in fluid properties, particularly composition, density, and flow rates, at the defined nodes.

This digital transformation initiative had to overcome the following complexities to improve accuracy and enable faster decision-making:

Incorporation of data from more than 20 fields, 150+ reservoirs, 5000+ wells Optimizing the country-wide network model comprised of wells, pipelines, and separators Performing multiple pre-conceived daily scenarios with 60-month forecasts for production and injection rates Accounting for lateral and vertical composition variation within a reservoir Mixing of fluids at different points in the network at different pressures Implementation of a unified equation of state (EOS) to enable component tracking

The network model successfully captured this complexity and predicted capacities for all custody-transfer points between upstream and downstream networks demonstrating a good match (&gt;90%) between the actual laboratory-based measurements and the ICM results. The tool also offered the capability to maximize production of desired components at the source level to meet the dynamic energy demands of the country, allowing a 1-3% profit improvement in the base operating plans. Alternate scenarios offer additional views on how to obtain the same upstream liquid production targets while maximizing downstream gas revenues, hence overall country profitability. The ICM recommended suitable targets during crisis conditions to react accurately to unexpected market fluctuations.

Implementation of the unified EOS along with component tracking creates new avenues for digital transformation by allowing the operator to optimize high value products and answer to demand changes quickly. Multiple scenarios can be analysed and visualised to support decision makers to increase profitability in a highly competitive hydrocarbon market from rock to stock.