摘要
针对直流电测深数据等值性反演的病态性(等值性层参数及层参数间的狭长平坦的强相关性),尝试采用自适应单纯形模拟退火(ASSA)方法反演具等值性电测深模型,通过与Lamarckian-marked-constraint(LMC)算法对比,发现ASSA方法能较好地解决电测深等值性反演问题,且反演精度较高。目前地球物理反演多基于数据误差为高斯分布和空间不相关(非对角元素为零)的假设,对贝叶斯反演而言,后一假设如果运用不当往往会低估反演结果的不确定性,从而导致对反演结果可靠性的误判。为了合理评价反演结果的不确定性,文中采用Runs-test非参数化判别方法,通过对等值性模型的归一化数据残差的判别,确定数据误差是空间相关的。由此得出的协方差矩阵应用于贝叶斯反演,进而对反演结果的不确定性、相关性等进行更合理、准确的评价。
Aiming at the ill-posed electrical sounding data equivalence inversion,an adaptive simplex simulated annealing(ASSA)approach is applied to invert electrical sounding data with equivalence.Compared with Lamarckian-marked-constraint(LMC),the inversion result proves that ASSA can better perform electrical sounding equivalence inversion and the inversion precision is higher.Presently,many geophysical inversions are performed based on the assumption that data errors are Gaussian-distributed and spatially uncorrelated(off-diagonal elements are zero for covariance matrix).For Bayesian inversion,the latter assumption is not valid,and it may lead to the less-estimation of uncertainty to inversion data and a wrong decision about the reliability of inversion result.In order to reasonably evaluate the uncertainty of inversion result,nonparametric Runs-test method is used to estimate the full covariance matrix from data residuals of equivalence model,and determine if data errors are spatially correlated.The covariance matrix obtained is applied to Bayesian inversion,thus the uncertainty,correlation of inversion data is more correctly and reasonably evaluated.
出处
《石油地球物理勘探》
EI
CSCD
北大核心
2017年第5期1077-1084,共8页
Oil Geophysical Prospecting
基金
国家自然科学基金青年基金资助项目(41202223
51409013)资助
关键词
电测深等值性
贝叶斯反演
ASSA
数据误差相关性
不确定性
相关性
vertical electrical sounding equivalence
Bayesian inversion
adaptive simplex simulated annealing(ASSA)
correlation of data error
uncertainty
correlation
作者简介
付代光 1987年生；2011年毕业于中国地质大学（武汉）应用地球物理专业，获学士学位；2013年毕业于中国地质大学（武汉）地质工程专业，获硕士学位；目前在长江水利委员会长江科学院主要从事地球物理正、反演的相关研究。
