Field production optimization can bring considerable increases in daily production value.
However, the complexities of most production systems mean that rigorous mathematical optimization is an essential tool to address the complexity.
The challenge
Field production optimization can bring considerable increases in daily production value. This is an important consideration for operators whose fixed cost structure means that they can benefit from “oil now” rather than deferred production.
The complexities of most production systems mean that it is virtually impossible to determine the optimal mode of operation for an asset through engineering judgment or trial-and-error techniques on the asset itself.
Rigorous mathematical optimization is thus an essential tool to address the complexity. However, if the production optimization boundary is drawn too narrowly – i.e. a “sand-face-to-separators” approach that does not include facilities models – there is a risk that:
- the optimum identified may not be achievable in practice because of facilities (e.g. compression) constraints. This renders the results meaningless with the likely outcome that the optimizer is discredited and ignored by operators.
- the results from the ‘optimization’ are in fact sub-optimal.
The gPROMS Oilfield solution
The solution is to combine the production model with a facilities model – utilising the gPROMS platform’s extensive libraries of process models such as heat exchangers and compressors – and optimize the entire system simultaneously.
This ensures that all interactions and constraints are taken into account, to result in the optimal feasible solution.
For further information, see the recent Integrated Asset Optimization webinar available on-demand and a paper published via SPE on New Integrated Technology for Full Production and Facilities Modelling and Optimization (right).
