Optimization of field development

Optimization of field development

This is a topic page to show an overview of a sub field of Integrated operations, describing the knowledge developed by the IO Center

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The optimal location of a new well or the capacity of a subsea separator, cannot be determined without considering the reservoir drainage strategy. How you produce from nearby wells is just as important for the new wells recovery, as the production strategy of the new well itself. Well placement or asset development, and control optimization in oil field development are commonly performed in a sequential manner. In this work we propose a joint approach that embeds well control optimization within the search for optimum well placement or asset configuration.
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For many years, reservoir and production network simulation has been part of the engineer’s workflow when deciding on where to drill a new well, or how to design the subsea production system. The engineer typically simulates alternative development strategies in a what-if study, and chooses the best alternative. Hence, the prediction of system behavior is automated through simulations. The selection of scenarios to test in the what-if study, however, is chosen manually. 

 

In this activity we address the what-if study and try to automate parts of this work process by utilizing optimization algorithms. This is not a trivial task, since the optimal location of a new well or the capacity of a subsea separator cannot be determined without considering the reservoir drainage strategy. How you produce from nearby wells is just as important for the new wells recovery, as the production strategy of the new well itself. Therefore, to find the best possible design strategy, one also needs to perform a well control optimization when searching for the optimum well placement or asset configuration. 

 

In e.g. a brown field development program, one might want to place a new injector and producer. Further, one considers an ESP on one of the existing producers and a subsea separation unit in order to relieve the topside processing plant. To find the best possible tradeoff between alternative system designs, considering investment cost and increased recovery, is essentially an impossible task. There are several reasons. First, the large amount of design decisions make up a countless number of alternatives with effects cannot be isolated. What if you increase the effect on the ESP, can you reduce the efficiency on the subsea separator? Or maybe you should place the new injector slightly further away? Secondly, since producing a reservoir is a batch process, one also needs to take into account the timing. The increase in effect on the ESP might enable you do postpone the installation of the subsea separator or the new injector. In an NPV setting, it is not only the system design that matters, the timing is also important. 

 

To evaluate a possible development strategy, a coupled reservoir and production network simulator can provide you with an estimate of what rates you can produce with and the final recovery, considering the bottlenecks of your production system. Given the investment and operational costs, one can compute the corresponding NPV. Due to uncertainty, particularly in the reservoir, these numbers are of course guestimates, which complicates even further. Still, the coupled simulation is a very good start in the search for the best possible development strategy. 

 

Adding an optimization algorithm on top of the coupled simulator is quite easy, however the suggestion it provides you with might be far off what’s considered an interesting development strategy. The main reason is that the problem is simply too large and too tricky for a “brute force” approach. In light of the potential benefit of finding better or the best development strategies, the complexity of finding it, and IO Center’s competence on optimization of integrated systems, we were motivated to conduct this research. Within our ongoing research activity on this subject, we are addressing two pilots, and one software development activity, outlined below. 

 

Pilot projects 

IO4 has three ongoing research activities on this topic, which are outlined here:

  • Since 2010 has IO4 been working together with Petrobras on design optimization of subsea development, to test and develop the SmartOpt method on a semi realistic case. The goal is to find the optimal efficiency and capacity, and timing of installation of a subsea separator and boosting equipment. The reader is reffered to the ongoing research page for more details.
  • IO4 started a pilot study with Total in 2012 on optimal well placement . In parallel to reservoir engineers at Total, is one of our PhD students applying a method that jointly takes both the well placement and production strategy into account, while running an advanced optimization strategy in search for the best possible location of the new wells in a green field. The findings of the PhD student are communicated to Total for them to consider. For more information see ongoing research.
  • After more than six years of research on optimization of reservoir management and production optimization, IO4 has accumulated a large amount of results and extensive experience within the area. Late 2011 we decided to integrate the results and experience into an optimization framework called ResOpt. This is a research tool that is continuously developed and expanded. As of today it integrates with both GPRS from Stanford, and MRST from Sintef. It has an implementation of the Begs and Brill correlation for steady-state pressure drop through pipelines or optionally a table lookup and interpolation algorithm. Further, it runs both the derivative free Nomad algorithm, and the gradient based bonmin algorithm from COIN-OR. ResOpt is now used in the pilot project with Petrobras addressing the subsea investment decision, and for benchmark testing our new discoveries within day to day production optimization. More information and a demo can be found here.

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