Joint inversion of one-dimensional time-frequency electromagnetic data with constraints 带约束的一维时频电磁联合反演研究

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.