Shear Wave Velocity Prediction Method Based On Improved Particle Swarm Algorithm

With the recovery of the global economy,our country social economy increase steadily year by year,energy is the motive force of economic development.Constantly improve people's environmental protection consciousness,the new energy by continual development and promotion,but the application of new energy still have limitations,the traditional energy,especially,the demand for oil and gas resources is more apparent,this also led to the exploration and exploitation of oil and gas reservoirs.Along with the increasing of exploration and development,the conventional reservoir reserves decrease year by year,which makes the direction of the development gradually become modalities of lithology reservoir in reservoir,makes the exploration difficulty greatly ascend,exploration methods for further improvement.Because of the further reservoir exploration,for seismic reservoir prediction accuracy also has a new ascension.Need not only starting from the prediction of the growing degree of the reservoir,contained more requirements to the prediction of reservoir fluid properties,such as the elastic properties of the rock further understanding,so as to improve the reservoir exploration and development in the practical production of realizability,greatly reduce the risk of development.Rock physics research purpose is to explore the rock elastic properties and the corresponding relationship between the rock parameters,to facilitate our further study of geological structure and rock strata pore fluid influence on seismic response,so the rock physics research is based on the seismic response and a bridge between logging data,but also the important physical basis of reservoir seismic exploration.In the exploration and development,seismic inversion as an important link,is the mainstream of reservoir prediction and fluid identification method.Shear wavevelocity information is not only a prestack inversion of the most important information needed and prestack seismic numerical model indispensable parameter information.In actual production,often the result of shear wave velocity information put forward high cost,difficult to pick up at the beginning,not as widely used,so if it finds an effective prediction method of shear wave velocity is of vital significance.Will be from the perspective of rock physical model,this paper introduces the particle swarm algorithm and put forward the improvement train of thought,the improved particle swarm optimization(pso)algorithm is introduced into shear velocity prediction,using traditional traversal search method and the improved particle swarm algorithm two kinds of method to calculate the best pore aspect ratio,the theory of p-wave velocity and minimum error between the actual p-wave velocity,shear wave velocity prediction,the prediction results and the measured shear velocity contrast,the introduction of particle swarm algorithm is verified the validity and the accuracy of prediction method of shear wave velocity.At the same time,by changing the rock physical model of shear wave velocity prediction to do further research,this paper selected the SCA model,SCA + Gassmann model,Hudson model,Chapman model,the four kinds of models for shear wave velocity prediction analysis.The SCA+ Gassmann model based prediction of shear wave,the most close to real data,forecasting curve with the actual shear wave curve fitting the highest;Hudson model based prediction of shear wave velocity,shear wave velocity contrast based on other three kinds of rock physics model predicted results,the error is highest,the curve fitting is the worst.