Improved ant colony algorithm for parameter estimation on the BISQ model

In this paper, based on the Biot/Squirt model including the Biot-flow and squirt-flow mechanism simultaneously, we estimated reservoir parameters using the improved ant colony algorithm, that is, the niche ant colony algorithm (NACA) based on fitness sharing principle. We used the improved ACA in a multi-modal function optimization problem and verified the effectiveness of the NACA. We then estimated reservoir parameters, such as porosity and permeability using the improved ACA based on the unsaturated porous media Biot/Squirt model. The numerical results indicate that the relative error of the inversion of a single parameter can be maintained at less than 0.08%, similar to that of the inversion of two parameters (porosity and saturation). In addition, the effect of the inversion of three parameters (porosity, solid density and fluid density) was found to be slightly weak, but the relative error can still be maintained at less than 4%. Moreover, we compared the inversion results with those obtained using the niche genetic algorithm. The comparison shows that the former has higher precision over the latter. The results of the numerical simulation demonstrate that the proposed approach is an effective convergent optimization method.