Training Hybrid Neuro-Fuzzy System to Infer Permeability in Wells on Maracaibo Lake, Venezuela

2014/09/03 by Nuri Hurtado, Hurtado, Nuri, Raamses Díaz +3
Physics and Astronomy · #FOS: Physical sciences #Geophysics (physics.geo-ph) #physics.geo-ph

paper · pdf · doi:10.48550/arxiv.1409.1264

5 pages, 3 figures

arxiv created 2014/09/03 · arxiv updated 2014/09/05

Abstract

The high accuracy on inferrring of rocks properties, such as permeability (k), is a very useful study in the analysis of wells. This has led to development and use of empirical equations like Tixier, Timur, among others. In order to improve the inference of permeability we used a hybrid Neuro-Fuzzy System (NFS). The NFS allowed us to infer permeability of well, from data of porosity (ϕ) and water saturation (Sw). The work was performed with data from wells VCL-1021 (P21) and VCL-950 (P50), Block III, Maracaibo Lake, Venezuela. We evaluated the NFS equations (k_P50,i(ϕ_i,Sw_i)) with neighboring well data (P21), in order to verify the validity of the equations in the area. We have used ANFIS in MatLab.

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