Geological Modeling And Application Of Optimized Random Vector Functional Link In Tahe Condensate Gas Field,Tarim Basin,China

The reservoir development has recently entered a stage of production decline due to challenges such as geological formation complexity and serious heterogeneity connectivity.Therefore,a reasonable three dimensional(3D)geological model of reservoir storage is urgently required to improve gas field management.This study aims to accurately evaluate reservoirs and presents an efficient workflow approach for constructing a reliable three dimensional(3D)architecture geological model based on the standardization of geophysical well logs.Moreover,the proposed approach provides an accurate description of the inner architecture and visualization of reservoir heterogeneity.the approach in petrophysical modeling proved that the integrated 3D modeling workflow could be applied in many research areas.Substantial evidence demonstrated the efficiency of the artificial neural network(ANN)approach in petrophysical modeling and proved that the integrated 3D modeling workflow could be applied in many research areas.Moreover,an improved random vector functional link(RVFL)network is also proposed to predict production from the Tahe field in China.A spherical search optimizer(SSO)is applied to optimize the RVFL and enhance its performance,creating our proposed SSORVFL model.The proposed SSO-RVFL model is evaluated through extensive comparisons with several optimization methods.The results showed that SSO-RVFL achieved accurate predictions and outperformed several optimization methods.