Well testing curve automatic matching of fractured horizontal well based on group particle swarm optimization

Key words:  fractured horizontal well  group swarm  particle swarm optimization  well test  automatic matching

Abstract:

In order to improve the accuracy, speed and stability of multi-parameters automatic matching for fractured horizontal well test analysis, a new parallel group particle swarm optimization algorithm combined with traditional method, intelligence algorithm and parallel algorithm wa$ proposed. "Hie proposed algorithm was combined with Gauss-Newton algorithm and solved by OpenMP parallel algorithm. The results show that in the particle swarm optimization algorithm, the searching direction of particle 叩proaches to linear by clusterir^ particles. The shortcoming of the local optimization is avoided and searching speed is increased. Tlie algorithm combines Gauss-Newton algorithm with particle swarm optimization, which ensures its stability. Meanwhile, OpenMP parallel optimization algorithm can reduce the compiexity of the model and improve the calcuiation efficiency. Compared with other optimization calculation algorithms, the algorithm shows high accuracy, high efficiency and the capability of dividing flow stage to some extent in well teat interpretation for multi-fractures horizontal well，