Determination of three-phase relative permeabilty values by using an artificial neural network model

Date

2004-08-01

Author

Karaman, T
Demiral, BMR

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

216
views

0
downloads

In this study, an artificial neural network (ANN) tool, which uses the data obtained from a pore network (PN) model, was developed in order to obtain three-phase relative permeability values. During the development of this ANN tool, four different stages were implemented in which ANN structures were changed in order to find the best architecture that would predict the oil isoperms correctly. By using the data obtained from the PN model, training was implemented and the prediction power of that tool was tested. When the data obtained from PN and ANN tools were compared, it has been found that irrelevant variables affected the ANN model negatively as decreasing its ability to learn perfectly. Finally, it has been observed that trends of the isoperms were effectively predicted and the overall quality of predictions was improved by changing the ANN structure.

Subject Keywords

Fuel Technology, Energy Engineering and Power Technology, General Chemical Engineering

URI

https://hdl.handle.net/11511/65836

Journal

ENERGY SOURCES

DOI

https://doi.org/10.1080/00908310490473

Collections

Department of Petroleum and Natural Gas Engineering, Article

Suggestions

OpenMETU
Core

Determination of two and three phase relative permeabilty values by using a pore network model Karaman, T; Demiral, BMR (Informa UK Limited, 2004-06-01) In this study, a Pore Network (PN) tool was developed in order to obtain two and three phase relative permeability values. It has been found that the observed results agree with published data. It has also been found that as contact angle increased, irreducible water saturation decreased, and oil relative permeability increased for two phase oil-water imbibition simulations. During the three phase displacement simulation by pore network simulation it was observed that water and gas relative permeabilities a...
Improving Oil-Rate Estimate in Capacitance/Resistance Modeling Using the Y-Function Method for Reservoirs Under Waterflood Temizel, Cenk; Artun, Emre; Yang, Zhengming (Society of Petroleum Engineers (SPE), 2019-08-01) Capacitance/resistance modeling (CRM) is an empirical waterflood modeling technique based on the signal correlations between injection rates and gross production rates. CRM can satisfactorily estimate the gross (liquid) production rate. The oil-production-rate forecast is based on fitting the empirical oil fractional-flow model, the Leverett (1941) oil fractional-flow model, or the Koval (1963) model to the historical production data. We observed that the oil-production-rate forecast in this approach is les...
Well test model identification by artificial neural networks Kök, Mustafa Verşan (Informa UK Limited, 2000-01-01) The aim of this research is to investigate the performance of artificial neural networks computing technology, to identify preliminary well test interpretation model based on derivative plot. The approach is based on training the neural network simulator uses back-propagation as the learning algorithm for a predefined range of analytically generated well test response. The trained network is then requested to identify the well test identification model for test data, which is not used during training sessio...
Limitations of three-phase Buckley-Leverett theory Akın, Serhat (Informa UK Limited, 2005-07-01) The broad objective of this study is to determine the limitations of the three-phase relative permeability estimation technique by using the experimental approach. In order to achieve this goal, three-phase relative permeability experiments were conducted on a Berea sandstone core plug by using brine, hexane and nitrogen gas. An unsteady-state analytical technique and a numerical technique where a black oil simulator was coupled with a global optimization algorithm in a least squares manner was used to comp...
RECONSTRUCTION OF PERMITTIVITY AND CONDUCTIVITY PROFILES OF A DIELECTRIC SLAB IN THE TIME DOMAIN BY DESCENT METHODS ONDER, M; Kuzuoğlu, Mustafa (Institution of Engineering and Technology (IET), 1992-10-01) An optimisation approach is presented for the problem of reconstructing the permittivity and conductivity profiles of a dielectric slab from the reflected and transmitted field data. The problem is treated as an optimal control problem where the norm of the difference of measured and calculated boundary data is minimised subject to the state equation governing the system. The original constrained optimisation problem is reduced to the evaluation of stationary points of an augmented functional which is obtai...

Citation Formats

T. Karaman and B. Demiral, “Determination of three-phase relative permeabilty values by using an artificial neural network model,” ENERGY SOURCES, pp. 903–914, 2004, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/65836.