Decision Support Framework for Well Location at Martin Linge Oil Field (IO13 poster)

Decision Support Framework for Well Location at Martin Linge Oil Field (IO13 poster)

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We present an optimization framework for well placement decision support at the Martin Linge oil reservoir. The framework optimizes jointly for well placement and controls using derivative-free methods for well location, and a gradient-based routine for optimization of well control settings (e.g., bottom hole pressures). A well configuration based on the fixed strategy solution and run on the field's original ECLIPSE field model yields a total field oil production increase of more than 10%. However, a significant part of the increase is attributed to longer wells which are too close to the reservoir boundary. The introduction of well length constraints to the optimization framework is currently underway. This pilot is a collaboration between NTNU IO Center and operator Total E&P Norge AS. This poster was created for presentation at the 2013 IO Conference held September 24-25 in Trondheim, Norway.

An optimization framework is implemented for well placement decision support at the Martin Linge oil field. For optimization purposes, the ECLIPSE field model is transferred to an approximate reservoir model run with ADGPRS. A work process loop describes the collaboration between Industry Partner and IO Center Research Team.


Two solutions for well placement configuration are determined using a joint approach with embedded control optimzation and a simplified strategy with fixed control settings. Results from the optimization framework yield increases in total field oil production of 34% and 29% for the joint approachand fixed strategy, respectively.

A well configuration based on the solution from the fixed strategy and run in the original ECLIPSE model yields an increase in total field oil production of more than 10%. This solution is associated with a high degree of uncertainty due to long wells drilled near the reservoir boundary. A maximum well length constraint will be introduced in future optimization runs.

The optimization framework will be extended to include a set of model realizations to increase the robustness of well placement solutions with respect to geological uncertainty.

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