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.
Journal article
A model for estimation of permeability and free flowing porosity
Petroleum Science and Technology, Vol.34(23), pp.1872-1879
2016
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Abstract
Details
- Title
- A model for estimation of permeability and free flowing porosity
- Creators
- Ali Barati-Harooni - Islamic Azad University, Ahvaz, IranAdel Najafi-Marghmaleki - Islamic Azad University, Ahvaz, IranSeyed Moein Hosseini - University of Technology, Ahvaz, IranSiyamak Moradi - Petroleum University of TechnologyMoonyong Lee - Yeungnam UniversityAlireza Bahadori - Southern Cross University
- Publication Details
- Petroleum Science and Technology, Vol.34(23), pp.1872-1879
- Identifiers
- 4067; 991012821497102368
- Academic Unit
- School of Environment, Science and Engineering; Faculty of Science and Engineering
- Resource Type
- Journal article