In this study, we present a practical technique of transforming cross-hole EM data into the inter-well resistivity distribution. The a priori information constraint is incorporated into an iterative regularized invers...In this study, we present a practical technique of transforming cross-hole EM data into the inter-well resistivity distribution. The a priori information constraint is incorporated into an iterative regularized inversion procedure and a variable roughness is added into the inversion process. Finite element approximation based on a two and a half-dimensional （2.5D） model has been developed for the forward problem and the ＂pseudo-forward＂ problem needed for constructing the sensitivity matrix and synthetic data set. The regularized least-squares inversion scheme, constrained with the a priori information obtained from well logs, was adopted to reconstruct the inter-well resistivity profile from two synthetic electromagnetic data sets and field data acquired in the Gudao Oil Field, East China. The partial derivatives of the sensitivity matrix were computed by the adjoint equation based on the reciprocity principle. Inversion results of the synthetic and field data examples suggest that our method is robust and stable in the presence of random noise in the field data and can be used for cross-hole EM field data interpretation.展开更多
文摘In this study, we present a practical technique of transforming cross-hole EM data into the inter-well resistivity distribution. The a priori information constraint is incorporated into an iterative regularized inversion procedure and a variable roughness is added into the inversion process. Finite element approximation based on a two and a half-dimensional （2.5D） model has been developed for the forward problem and the ＂pseudo-forward＂ problem needed for constructing the sensitivity matrix and synthetic data set. The regularized least-squares inversion scheme, constrained with the a priori information obtained from well logs, was adopted to reconstruct the inter-well resistivity profile from two synthetic electromagnetic data sets and field data acquired in the Gudao Oil Field, East China. The partial derivatives of the sensitivity matrix were computed by the adjoint equation based on the reciprocity principle. Inversion results of the synthetic and field data examples suggest that our method is robust and stable in the presence of random noise in the field data and can be used for cross-hole EM field data interpretation.
