Inversion of Array Induction Logs and Its Application

With the help of the modified geometrical factor theory, the Marquardt method was used to calculate the true electrical parameters of the formation from array induction logs. The inversion results derived from the assumed model and some practical cases show that the rebuilt formation profile determined by 2-ft resolution array induction logs is reasonable when the formation thickness is greater than 1 m, which thus indicates that the inversion method is reliable and can provide quantitative information for the discrimination of oil/gas or water zone.

Delineation of bed boundaries of array induction logging curves using deep learning

Delineation of bed boundaries based on resistivity logging curves is important prior information for the inversion and interpretation of resistivity logging data.Traditionally,the layering algorithm mainly use the derivatives of resistivity curves or other logging methods as reference.However,measurement error or resolution mismatch may lead to misjudgment of the boundary.In view of the shortcomings of traditional methods,this paper presents an automatic layering algorithm of array induction logging curves based on deep learning.In this algorithm,a locally connected convolution neural network is used,and the generalization ability of the network is improved by enlarging the training set,optimizing the window length and threshold,and strengthening the layering effect.Simulation and field data show the eff ectiveness of the proposed algorithm.

Forward modeling of tight sandstone permeability based on mud intrusion depth and its application in the south of the Ordos Basin

Permeability is an important index in reservoir evaluation,oil and gas accumulation control,and production effi ciency.At present,permeability can be obtained through several methods.However,these methods are not suitable for tight sandstone in general because the pore type in tight sandstone is mainly secondary pores and has the characteristics of low porosity and permeability,high capillary pressure,and high irreducible water saturation.Mud invasion depth is closely related to permeability during drilling.In general,the greater the permeability,the shallower the mud invasion depth,and the smaller the permeability,the deeper the mud invasion depth.Therefore,this paper builds a model to predict the permeability of tight sandstone using mud invasion depth.The model is based on the improvement of the Darcy flow equation to obtain permeability using mud invasion depth inversion of array induction logging.The influence of various permeability factors on the model is analyzed by numerical simulation.The model is used to predict the permeability of tight sandstone in the south of the Ordos Basin.The predicted permeability is highly consistent with the core analysis permeability,which verifi es the reliability of the method.