FieldOpt: A powerful and effective programming framework tailored for field development optimization

Petroleum field development involves critical decisions such as well location, well completion design and optimal control setting that have a significant impact on revenues and costs. These decisions are associated with a large degree of engineering effort that commonly involves time-consuming reservoir simulations to compute the performance of different field development scenarios. Increasingly within the petroleum industry, software tools and optimization methodology are developed and implemented to support and augment the various decision-making processes. The overall aim of these tools is to increase productivity and improve decision quality. Within this context, this work introduces an open-source, extensible, tailor-made programming framework: FieldOpt. FieldOpt's primary purpose is rapid prototyping and testing of optimization procedures to solve critical field development problems. The framework is implemented in C++ and provides an efficient integration of mathematical optimization procedures with reservoir simulation. FieldOpt's modular architecture and use of object-oriented programming allow the users to adapt and extend the code with ease. The architecture has proven successful in facilitating new optimization algorithms, new use cases, and new methodology for optimization with minimal effort and change to internal data structures and data flow. Three use cases are presented to demonstrate the optimization capabilities of FieldOpt as well as the flexibility and ease-of-use of the software regarding configuring various optimization procedures to solve a range of field development problems. The three use cases presented optimize on well control, well completion design and well placement parameters, respectively. For each case, both the configuration of the algorithms and problems within FieldOpt as well as the final solution and performance of the different optimization procedures are discussed. In all three cases, FieldOpt was able to find significant improvements or crucial information to decision making.