Well Logging Automatic Core Relocation Based of the Immune Particle Swarm Optimization Algorithm

There exist shortcomings of inaccuracy and subjective error in traditional manual core location. In order to overcome those disadvantages a new automatic method is proposed in this paper. There are relativities between the well logging curve and physical data at the same depth. Therefore the core location can be considered an optimization questions. Particle swarm optimization is a population-based optimization algorithm and it has been applied in many fields successfully. However, there exists some disadvantages and the main flow is prematurity because of the decrease of swarm diversity. Therefore, an improved particle swarm optimization algorithm combined with immune clone selection algorithm is proposed in this paper. Clone selection algorithm is used to keep the swarm diversity availably. The simulation results show that the improved algorithm is fairly effective and the automatic core location can be achieved through the particle swarm optimization algorithm.