Metaheuristic algorithm integrated neural networks for well-test analyses of petroleum reservoirs.

In recent years, well-test research has witnessed several works to automate reservoir model identification and characterization using computer-assisted models. Since the reservoir model identification is a classification problem, while its characterization is a regression-based task, their simultaneous accomplishment is always challenging. This work combines genetic algorithm optimization and artificial neural networks to identify and characterize homogeneous reservoir systems from well-testing data automatically.