摘要
对野外实测大地电磁数据进行反演解释时,由于人文噪声的干扰和采集的数据不完全,增加了地球物理反演解释的难度,所以研究不同噪声和缺失数据信息对大地电磁正则化反演的影响非常必要。利用正则化理论研究不同噪声、数据"信息不完全"下对大地电磁反演的影响,分析解释最平坦模型、最平滑模型和最小模型的特点。结果表明:合适的正则化反演初始模型的选择,对反演的结果至关重要。最平坦模型、最平滑模型较好,最小模型效果一般;随着噪声的增加,反演效果逐渐变差;数据信息不完全的时候,如果其它先验信息丰富,仍然能够得到较好的反演结果。
Because human noise and incomplete data information were existed when the data was collected in the field, the difficulty of magnetotelluric （MT） inversion for interpretation increases naturally. Therefore, the study on magnetotellurie regular inversion on human noise and incomplete data information becomes necessary. Using the results of different amplitudes of Gaussian noise and the data of incomplete information studied with regularization theory, the characteristics of the flattest model, the smoothest model and the smallest model were analyzed and interpreted. The results show that： a suitable initial model is the essential choice to inversion, the flattest model and the smoothing model are better for magnetotellurie inversion than the smallest model; as the noise increases, the inversion becomes worse. If the additional prior information is rich, a good inversion results can still be got from the data incomplete information.
出处
《中国有色金属学报》
EI
CAS
CSCD
北大核心
2012年第3期915-921,共7页
The Chinese Journal of Nonferrous Metals
基金
国家自然科学基金资助项目(41174103)
教育部博士点基金资助项目(20110162130008)
国家科技支撑计划资助项目(2011BAB04B08)
中国地质调查局科研资助项目(资[2011]03-01-64)
有色资源与地质灾害探查湖南省重点实验室项目(2010TP4012-6)
关键词
高斯噪声
缺失数据
正则化反演
大地电磁测深
Gaussian noise
missing data
regularized inversion
maguetotelluric sounding
