Integration of rock physics, seismic inversion, and support vector machines for reservoir characterization in the Orinoco Oil Belt, Venezuela

2014 ◽  
Vol 33 (7) ◽  
pp. 774-782 ◽  
Author(s):  
Atilio Torres ◽  
Jorge Reverón
Keyword(s):  
Support Vector Machines ◽  
Reservoir Characterization ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Support Vector ◽  
Vector Machines

scholarly journals A Novel Homogenous Hybridization Scheme for Performance Improvement of Support Vector Machines Regression in Reservoir Characterization

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Kabiru O. Akande ◽  
Taoreed O. Owolabi ◽  
Sunday O. Olatunji ◽  
AbdulAzeez Abdulraheem
Keyword(s):  
Support Vector Machines ◽  
Reservoir Characterization ◽  
Petroleum Industry ◽  
Predictive Ability ◽  
Extraction Process ◽  
Superior Performance ◽  
Support Vector ◽  
Prediction Ability ◽  
Intelligent Algorithms ◽  
Vector Machines

Hybrid computational intelligence is defined as a combination of multiple intelligent algorithms such that the resulting model has superior performance to the individual algorithms. Therefore, the importance of fusing two or more intelligent algorithms to achieve better performance cannot be overemphasized. In this work, a novel homogenous hybridization scheme is proposed for the improvement of the generalization and predictive ability of support vector machines regression (SVR). The proposed and developed hybrid SVR (HSVR) works by considering the initial SVR prediction as a feature extraction process and then employs the SVR output, which is the extracted feature, as its sole descriptor. The developed hybrid model is applied to the prediction of reservoir permeability and the predicted permeability is compared to core permeability which is regarded as standard in petroleum industry. The results show that the proposed hybrid scheme (HSVR) performed better than the existing SVR in both generalization and prediction ability. The outcome of this research will assist petroleum engineers to effectively predict permeability of carbonate reservoirs with higher degree of accuracy and will invariably lead to better reservoir. Furthermore, the encouraging performance of this hybrid will serve as impetus for further exploring homogenous hybrid system.

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