Real-time optimisation for gas production assets

Challenges in mature assets

  • Operating mature assets becomes more complex due to dynamic multiphase flow (combinations of oil, gas, and water) phenomena, which may cause flow instabilities and also results in operational constraints on topside equipment.
  • Mitigation measures, which are necessary to lengthen the economic life span of an asset (such as to prevent liquid loading), introduce new operational complexity (e.g. the need to divide available high pressure gas over multiple wells to ensure optimal and stable production).
  • Declining production rates make the need for efficient operation and low operational cost more urgent.
  • Gas network operators increasingly have to deal with dynamically changing supply of gas, because upstream processes do not provide a continuous stable flow anymore, and new parties with varying supply gain access to the network (e.g. biogas suppliers).
  • Strict contracts requiring operators to deliver the nominated flow within narrow bands to their customers include high penalties.

Control technology that:

  • Finds the optimal control strategy for the complex processes, taking constraints and operational costs into account.
  • Supports the operator in making the right decisions, by computing the effect of different control strategies and advising an optimal strategy.
  • Reliably and robustly works in practice, dealing appropriately with (frequently) changing operational constraints and changing infrastructure.


  • Safe and reliable operation of complex assets with less (skilled) staff available.
  • Significant energy savings in production.
  • Increased production from the mature fields.
  • Significant extension of the field life of mature fields.
  • More efficient use of topside production capacity.
  • Balanced demand and supply in dynamic networks.

Research objective
To develop a non-linear and on-line approach, which is currently not existing. This project aims at development of real-time optimisation technology to solve the dynamic optimisation problem for typical production asset complexity. The developed technology will be demonstrated with a representative practical case.


  1.  Applying new developments in dynamic optimisation technology developed in the past decade in the academic world. An important part of the research will be to investigate and develop the essential dynamics in the models.
  2. To develop real-time feedback methods for these processes to cope with the model-reality mismatch. By investigating the applicability of non-linear filtering techniques and research on the combination of these techniques with dynamic optimisation.
  3. To develop a robust mixed-integer optimisation procedure to handle binary control variables such as routing choices.

Demonstration test case The upstream asset F16-E18 of Wintershall Nederland B.V. is selected of which all necessary data will be provided by Wintershall Nederland B.V.

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