【摘要】：微震源定位是微震監(jiān)測(cè)技術(shù)的核心。微震源定位問(wèn)題中的已知參數(shù)幾乎都存在誤差,現(xiàn)有微震源定位算法通常通過(guò)最小化所有檢波器的到時(shí)(差)值函數(shù),但得到的定位結(jié)果往往會(huì)偏離震源實(shí)際位置。針對(duì)現(xiàn)有微震源定位算法的不足,提出一種由兩步反演構(gòu)成的微震源定位新方法;在新方法中,一次反演識(shí)別異常檢波器,二次反演實(shí)現(xiàn)震源空間坐標(biāo)的精確搜索�；诰鶆蛩俣燃僭O(shè),分別建立3參數(shù)、4參數(shù)和5參數(shù)的反演模型。應(yīng)用多目標(biāo)遺傳算法(Non-dominated Sorting Genetic Algorithm Ⅱ,簡(jiǎn)稱NSGA Ⅱ)實(shí)現(xiàn)一次反演,為實(shí)現(xiàn)震源的精確搜索和減少計(jì)算時(shí)間,二次反演建議采用單目標(biāo)優(yōu)化算法實(shí)現(xiàn)。將提出的方法用于某礦井工程震源定位實(shí)例中,計(jì)算結(jié)果表明:提出方法能夠有效的識(shí)別異常檢波器,定位結(jié)果也較未剔除異常檢波器時(shí)有了大幅度提升,且相對(duì)而言,4參數(shù)反演模型的定位結(jié)果優(yōu)于5參數(shù)模型。該文方法可作為微震源定位的一種參考。
[Abstract]:Microsource location is the core of microseismic monitoring technology. Almost all known parameters in the problem of micro-source location have errors. The existing micro-source localization algorithms usually minimize the arrival (difference) function of all geophone, but the location results often deviate from the actual location of the source. In view of the shortcomings of the existing micro-source localization algorithms, a new micro-source location method consisting of two-step inversion is proposed. In the new method, the anomaly geophone is identified by the first inversion, and the precise search of the focal space coordinates is realized by the secondary inversion. Based on the assumption of uniform velocity, the inversion models with 3 parameters, 4 parameters and 5 parameters are established respectively. The multiobjective genetic algorithm (Non-dominated Sorting Genetic Algorithm 鈪，

本文編號(hào)：2331822