Sheng-qi Yu, Yi-wang Huang, Yang Song, Jin-shan Fu
{"title":"基于有效密度流体近似反射模型的底参数反演方法","authors":"Sheng-qi Yu, Yi-wang Huang, Yang Song, Jin-shan Fu","doi":"10.1109/SPAWDA.2011.6167197","DOIUrl":null,"url":null,"abstract":"In order to obtain physical and geoacoustic properties of seafloor sediments, inversion method is presented with the reflection loss data at different grazing angles, which is derived from the reflection model based on effective density fluid approximation. In estimation of porosity, average grain size, mass density and bulk modulus of grains, genetic algorithm and particle swarm optimization are employed, respectively. Based on the above physical parameters, sound velocity and attenuation can be given. Numerical simulations show that both optimization algorithms have good performance in evaluating parameters with the exception of mean grain size and bulk modulus of grains. While the results inverted by particle swarm optimization are better than that of genetic algorithm in general.","PeriodicalId":285701,"journal":{"name":"2011 Symposium on Piezoelectricity, Acoustic Waves and Device Applications (SPAWDA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Inversion method for bottom parameters estimation by reflection model of effective density fluid approximation\",\"authors\":\"Sheng-qi Yu, Yi-wang Huang, Yang Song, Jin-shan Fu\",\"doi\":\"10.1109/SPAWDA.2011.6167197\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to obtain physical and geoacoustic properties of seafloor sediments, inversion method is presented with the reflection loss data at different grazing angles, which is derived from the reflection model based on effective density fluid approximation. In estimation of porosity, average grain size, mass density and bulk modulus of grains, genetic algorithm and particle swarm optimization are employed, respectively. Based on the above physical parameters, sound velocity and attenuation can be given. Numerical simulations show that both optimization algorithms have good performance in evaluating parameters with the exception of mean grain size and bulk modulus of grains. While the results inverted by particle swarm optimization are better than that of genetic algorithm in general.\",\"PeriodicalId\":285701,\"journal\":{\"name\":\"2011 Symposium on Piezoelectricity, Acoustic Waves and Device Applications (SPAWDA)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Symposium on Piezoelectricity, Acoustic Waves and Device Applications (SPAWDA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPAWDA.2011.6167197\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Symposium on Piezoelectricity, Acoustic Waves and Device Applications (SPAWDA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPAWDA.2011.6167197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Inversion method for bottom parameters estimation by reflection model of effective density fluid approximation
In order to obtain physical and geoacoustic properties of seafloor sediments, inversion method is presented with the reflection loss data at different grazing angles, which is derived from the reflection model based on effective density fluid approximation. In estimation of porosity, average grain size, mass density and bulk modulus of grains, genetic algorithm and particle swarm optimization are employed, respectively. Based on the above physical parameters, sound velocity and attenuation can be given. Numerical simulations show that both optimization algorithms have good performance in evaluating parameters with the exception of mean grain size and bulk modulus of grains. While the results inverted by particle swarm optimization are better than that of genetic algorithm in general.