復(fù)雜地質(zhì)條件下壩區(qū)初始地應(yīng)力場(chǎng)二次反演分析研究報(bào)告

李海波　裴啟濤　劉亞群

摘要：為準(zhǔn)確獲得南水北調(diào)西線工程加塔壩區(qū)初始地應(yīng)力分布規(guī)律，提出綜合反映工程區(qū)復(fù)雜地質(zhì)條件及地層剝蝕過(guò)程的地應(yīng)力場(chǎng)二次反演方法。首先，主要考慮工程附近大區(qū)域內(nèi)的地形地貌、斷層褶皺及河谷的發(fā)育演化史等因素，建立壩區(qū)大尺度計(jì)算模型，采用遺傳神經(jīng)網(wǎng)絡(luò)法及FLAC3D計(jì)算程序?qū)螀^(qū)初始地應(yīng)力場(chǎng)進(jìn)行一次反演；然后，考慮壩區(qū)附近主要地質(zhì)構(gòu)造，建立小尺度精細(xì)模型，通過(guò)從一次反演中提取小范圍模型邊界上的應(yīng)力值進(jìn)行擬合，初步獲得精細(xì)模型的非線性邊界條件，并采用遺傳神經(jīng)網(wǎng)絡(luò)法對(duì)邊界參數(shù)進(jìn)行優(yōu)化，對(duì)初始地應(yīng)力場(chǎng)進(jìn)行二次反演。研究結(jié)果表明：一次反演計(jì)算獲得的初始地應(yīng)力場(chǎng)在局部構(gòu)造附近與實(shí)測(cè)值相差較大；二次反演考慮局部地質(zhì)構(gòu)造的影響，同時(shí)結(jié)合一次反演的計(jì)算成果，各測(cè)點(diǎn)的應(yīng)力計(jì)算值與實(shí)測(cè)值吻合更好。

關(guān)鍵詞：地應(yīng)力場(chǎng)；反演；地層剝蝕；非線性邊界；遺傳神經(jīng)網(wǎng)絡(luò)

Abstract：In order to accurately obtain the distribution rule of initial geostress field in Jiata dam area in west route of South-to-North water transfer project，a new two-stage back analysis method of initial geostress field which considers the complex geological conditions and the ground denudation process is presented. Firstly，considering mainly the influence of topography，faults，folds，and developmental history of river valleys，a large-scale calculation model for the dam area is established. And the genetic neural network method as well as FLAC3D is applied to the first-stage back analysis of initial geostress field. Then，considering the main geological structures in the vicinity of the dam area，a small-scale refined model is created. The preliminary non-linear boundary conditions of the refined model can be obtained by fitting the stress values which are extracted from the large-scale model of the first-stage back analysis. After that，calculation for the second-stage back analysis of geostress field is conducted by optimizing the boundary parameters based on genetic neural network method. It is shown that the difference between the calculated results and the measured data is large in the vicinity of the local geological structures during the first-stage back analysis. And the calculated results are much closer to measured data in the second-stage back analysis by considering the small geological structures as well as the results in the first-stage back analysis. Therefore，the proposed method in this paper provides great reference to similar projects.

Keywords：geostress field；back analysis；ground denudation；non-linear boundary；genetic neural network