A model for estimation of permeability and free flowing porosity. (1st December 2016)

• Record Type: Journal Article
• Authors: Barati-Harooni, Ali; Najafi-Marghmaleki, Adel; Hosseini, Seyed Moein; Moradi, Siyamak; Lee, Moonyong; Bahadori, Alireza
• Is Part Of: Petroleum science and technology. Volume 34:Number 23(2016)
• Page Start: 1872
• Page End: 1879
• Publication Date: 2016-12-01
• Subjects: Crude oil -- oil production -- permeability -- modeling -- flowing porosity -- oil reservoir; Liquid fuels -- Periodicals; Petroleum -- Periodicals; 665.505
• DOI: 10.1080/10916466.2016.1233251
• Languages: English
• ISSNs: 1091-6466

Abstract

ABSTRACT: This work highlights the application of an adaptive neuro-fuzzy inference system (ANFIS) for predictions of NMR log parameters including free flowing porosity (FFP) and permeability by using field log data. The input parameters of model were neutron porosity, sonic transit time, bulk density, and electrical resistivity. The outputs of model were also permeability and FFP values. The ANFIS model was trained by using hybrid method. Results showed that the developed model is effective in prediction of field NMR log data. Outcomes of this study can be used in areas of petroleum engineering where accurate and immediate predictions of logging data are required.