不同幅度噪声和缺失数据对大地电磁正则化反演的影响

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 magnetoteiluric (MT) inversion for interpretation increases naturally. Therefore, the study on magnetoteiluric 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 magnetoteiluric 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.