带约束的一维时频电磁联合反演研究

利用时频电磁资料可同时获取时间域及频率域电磁信息。相比单一时间域或频率域电磁信号，综合利用时频电磁信息可明显提高电性反演精度。为获得精细地电模型，基于正则化反演方法，融合数据约束、模型约束及步长约束，提出一种一维自适应时频电磁联合反演算法。该算法对时间域和频率域数据平衡因子及正则化因子采用自适应调整方案，同时将模型参数搜索范围约束与WOLFE准则相结合，在限制参数搜索范围的同时约束迭代步长，确保反演的稳定性和精度。使用经典层状模型、含噪声的页岩气地电模型及实测数据对该反演方法进行测试与分析，结果表明带约束的时频电磁联合反演方法可有效提高复杂模型电阻率反演的分辨率，对提高时频电磁方法油气藏识别精度具有实际意义。

Joint inversion of one-dimensional time-frequency electromagnetic data with constraints

Time-frequency electromagnetic data can be used to simultaneously obtain electromagnetic information in the time domain and frequency domain. Compared with electromagnetic signals in a single time domain or frequency domain, comprehensive time-frequency electromagnetic information can significantly improve the inversion accuracy of electrical properties. In order to obtain a refined geoelectric model, this paper proposes a one-dimensional adaptive time-frequency electromagnetic joint inversion algorithm by using the regularization inversion method and combining data constraints, model constraints, and step size constraints. The algorithm adopts an adaptive adjustment scheme for weighting balance factors and regularization factors of time domain and frequency domain data. At the same time, the model parameter search range constraint is combined with the WOLFE criterion to constrain the iterative step size while limiting the parameter search range, which ensures the stability and accuracy of the inversion process. The classical layered model, shale gas geo-electric model with noise, and measured data are used to test and analyze the inversion method. The results show that the constrained time-frequency electromagnetic joint inversion method can effectively improve the resolution of resistivity inversion of complex models. Therefore, it is of practical significance to improve the recognition accuracy of time-frequency electromagnetic methods for oil and gas reservoirs.