Integrated Field Modelling of the Miskar Field
Authors: Madray Ravi , Coll Carolina , Veitch Gordon , Chiboub Chokri , Butter Machiel , Azouzi Samy , Bahri Sami , Yaich Brahim , Saada Tamer 
Published: June 2014

This paper describes the implementation of the Integrated Field Modelling project in the Miskar Field, Tunisia. Integrated Asset/Field Models (IAM) are based on the concept of having a fully integrated asset model that goes from reservoir to wells, topsides and production facilities.

The IAM tools are then integrated with data feeds to allow online surveillance monitoring and automation of client field/business management workflows. The project has been implemented in two phases. Phase I, which has already been concluded, links reservoir models to wells models and topsides whereas Phase-II (ongoing) will integrate the onshore processing plant and economic models. This unified model is achieved by linking the various models from simulation models at the reservoir level up, to nodal analysis at the wells, to topsides models and production system models that replicate the processing of hydrocarbons. The integrated model should be robust and incorporate the basic physics at each step from the reservoir to the production networks. The connection to economic models closes the evaluation cycle enabling production and economic optimization. One of the major drivers to implement this system in Tunisia was to be able to forecast, in real time using high frequency data, the gas composition at the platform (CO2/H2S/N2) and liquids production of the Miskar Field after infill drilling. Production Optimization routines are being implemented to: maximize gas and liquid production within the constraints of the current Miskar platform facilitiesmonitor the gas blend that is sent to the beach to ensure that the blend is maintained within the current operational constraints of the Hannibal plant and Miskar export.

In Phase I this was accomplished by building an integrated model from reservoir to inlet of the onshore facilities. The resulting model shows the interaction of the various elements in the production system. Further, from this full field model, we can then run full field production optimization and forecasting linked to the economic models. The optimization scenarios can be defined as tasks or as an event list that control a forecast period. Running multiple scenarios allow integrated teams to make informed decisions on a daily basis for production and/or regarding the future production of the field. The integrated sub-surface team can collaborate with production engineering teams to implement rule sets which ensure the long term versus short term optimisation objectives are observed within the forecasting workflows.

The project has also linked-up the models to the existing real time Production Data Management System (PDMS) to enable real time optimization for gas composition. This results in a ‘real-time' monitoring and surveillance of the field. The real time monitoring consists of well rate estimation of gas, water and condensate, as well as the gas compositions for blending forecast.

The loading of regular well tests and the use of customized workflows results in a semi-automated well test validation and analysis procedure. This makes regular updates of the reservoir model easier to carry out. Use of this type of real time full field modelling integration can leverage workflows to validate the full model on a much more regular basis. This results in time reductions for model calibration and quality control which then leads to greater confidence in model advisories and performance.

The tool that has been deployed to integrate data and workflows is Integrated Field Management (IFM) from Petroleum Experts which is built upon their existing Integrated Production Modelling (IPM) Architecture.