The most accurate heuristic-based algorithms for estimating the oil formation volume factor
Created by W.Langdon from
gp-bibliography.bib Revision:1.8110
- @Article{Mahdiani:2016:Petroleum,
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author = "Mohammad Reza Mahdiani and Ghazal Kooti",
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title = "The most accurate heuristic-based algorithms for
estimating the oil formation volume factor",
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journal = "Petroleum",
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volume = "2",
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number = "1",
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pages = "40--48",
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year = "2016",
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ISSN = "2405-6561",
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DOI = "doi:10.1016/j.petlm.2015.12.001",
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URL = "http://www.sciencedirect.com/science/article/pii/S240565611600002X",
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abstract = "There are various types of oils in distinct
situations, and it is essential to discover a model for
estimating their oil formation volume factors which are
necessary for studying and simulating the reservoirs.
There are different correlations for estimating this,
but most of them have large errors (at least in some
points) and cannot be tuned for a specific oil. In this
paper, using a wide range of experimental data points,
an artificial neural network model (ANN) has been
created. In which its internal parameters (number of
hidden layers, number of neurons of each layer and
forward or backward propagation) are optimized by a
genetic algorithm to improve the accuracy of the model.
In addition, four genetic programming (GP)-based models
have been represented to predict the oil formation
volume factor In these models, the accuracy and the
simplicity of each equation are surveyed. As well as,
the effect of modifying of the internal parameters of
the genetic programming (by using some other values for
its nodes or changing the tree depth) on the created
model. Finally, the ANN and GP models are compared with
fifteen other models of the most common previously
introduced ones. Results show that the optimized
artificial neural network is the most accurate and
genetic programming is the most flexible model, which
lets the user set its accuracy and simplicity. Results
also recommend not adding another operator to the basic
operators of the genetic programming.",
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keywords = "genetic algorithms, genetic programming, Neural
network, Modelling",
- }
Genetic Programming entries for
Mohammad Reza Mahdiani
Ghazal Kooti
Citations