Abstract
A hybrid GP-fuzzy approach to model reservoir permeability is presented. This approach uses a two-step divide-and-conquer process for modelling. First, GP is applied to construct classifiers that identify permeability ranges. Within each range, ANFIS is employed to build a Takagi-Sugeno-Kang fuzzy inference system that gives permeability estimation. We applied this method to five well log data sets. The results show that this hybrid system gives more accurate permeability estimation than other previous works.
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Yu, T., Wilkinson, D., Xie, D. (2003). A Hybrid GP-Fuzzy Approach for Resevoir Characterization. In: Riolo, R., Worzel, B. (eds) Genetic Programming Theory and Practice. Genetic Programming Series, vol 6. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-8983-3_17
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DOI: https://doi.org/10.1007/978-1-4419-8983-3_17
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