Using Committee Machine with Intelligent Systems for Permeability Prediction, A case study of South Pars Gas Field, Persian Gulf, Iran

Hatampour, Amir; Ghiasi-Freez, Javad; Adelzadeh, Mohammad Reza

doi:10.1109/iccisci.2012.6297270

Cited by 4 publications

(1 citation statement)

References 2 publications

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“…Hitherto, several researchers have investigated the individual applicability of these tools to geosciences-related problems [10][11][12][13][14][15][16]. This study comprises two major parts.…”

Section: Introductionmentioning

confidence: 99%

Neuro-fuzzy reaping of shear wave velocity correlations derived by hybrid genetic algorithm-pattern search technique

Asoodeh

Bagheripour

2013

Open Geosciences

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Abstract:Shear wave velocity is a critical physical property of rock, which provides significant data for geomechanical and geophysical studies. This study proposes a multi-step strategy to construct a model estimating shear wave velocity from conventional well log data. During the first stage, three correlation structures, including power law, exponential, and trigonometric were designed to formulate conventional well log data into shear wave velocity. Then, a Genetic Algorithm-Pattern Search tool was used to find the optimal coefficients of these correlations. Due to the different natures of these correlations, they might overestimate/underestimate in some regions relative to each other. Therefore, a neuro-fuzzy algorithm is employed to combine results of intelligently derived formulas. Neuro-fuzzy technique can compensate the effect of overestimation/underestimation to some extent, through the use of fuzzy rules. One set of data points was used for constructing the model and another set of unseen data points was employed to assess the reliability of the propounded model. Results have shown that the hybrid genetic algorithm-pattern search technique is a robust tool for finding the most appropriate form of correlations, which are meant to estimate shear wave velocity. Furthermore, neuro-fuzzy combination of derived correlations was capable of improving the accuracy of the final prediction significantly.

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