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In addition, by analyzing the results of the optimization histories, appropriate design criteria are derived for both accelerating and decelerating nozzle shapes.
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Optimization, history matching and optimal design of the reservoir require to run the forward model for many times.
A performance index is developed for monitoring the optimization process and is used as a termination criterion in the optimization algorithm so that the global optimum can be selected from the optimization history.
The optimization history matching algorithm is used in this step to iterate the relative permeability until the error between the target and simulated volume of produced water is minimized.
Then, the previous design test cases are re-computed coupling the extended adjoint formulation with commercial and open source flow solvers, without noticing any relevant difference in the optimization convergence histories.
In this paper a combined valve optimization and history-matching procedure is presented and applied.
In applications such as production optimization and history matching, thousands of simulation runs may be required.
The Well Placement Optimization, Field Development Scheduling, History Matching with Multiple Models, Global Optimization of Oil Production Systems are procedures related to Reservoir Engineering realized generally with base in a very large number of reservoir simulations which can yield slow developments and large computational effort.
Artificial intelligence algorithms have been used to solve production optimization and history matching problems for a long time.
A relatively new and superior optimization method, history driven differential evolution (HDDE), has been introduced and employed to develop planning solutions efficiently [26].
In terms of production optimization and history matching, researchers have applied various calculation methods including numerical perturbation, sensitivity equation, and adjoint method, as summarized in Table 2.
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