A systematic approach for estimation of reservoir rock properties using Ant Colony Optimization

author

Abstract:

Optimization of reservoir parameters is an important issue in petroleum exploration and production. The Ant Colony Optimization(ACO) is a recent approach to solve discrete and continuous optimization problems. In this paper, the Ant Colony Optimization is usedas an intelligent tool to estimate reservoir rock properties. The methodology is illustrated by using a case study on shear wave velocityestimation from petrophysical data by the linear and nonlinear ACO models. The results of this research show that the ACO is a fast,robust and cost-effective method for rock properties estimation. It is proposed that ant colony optimization aids in future reservoircharacterization studies.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

a systematic approach for estimation of reservoir rock properties using ant colony optimization

optimization of reservoir parameters is an important issue in petroleum exploration and production. the ant colony optimization(aco) is a recent approach to solve discrete and continuous optimization problems. in this paper, the ant colony optimization is usedas an intelligent tool to estimate reservoir rock properties. the methodology is illustrated by using a case study on shear wave velocity...

full text

Estimation of Global Solar Irradiance Using a Novel combination of Ant Colony Optimization and Empirical Models

In this paper, a novel approach for the estimation of global solar irradiance is proposed based on a combination of empirical correlation and ant colony optimization. Empirical correlation has been used to estimate monthly average of daily global solar irradiance on a horizontal surface. The Ant Colony Optimization (ACO) algorithm has been applied as a swarm-intelligence technique to tune the c...

full text

Reservoir Operation by Ant Colony Optimization Algorithms

In this paper, ant colony optimization (ACO) algorithms are proposed for reservoir operation. Through a collection of cooperative agents called ants, the near-optimum solution to the reservoir operation can be effectively achieved. To apply ACO algorithms, the problem is approached by considering a finite horizon with a time series of inflow, classifying the reservoir volume to several interval...

full text

Hybrid ANFIS with ant colony optimization algorithm for prediction of shear wave velocity from a carbonate reservoir in Iran

Shear wave velocity (Vs) data are key information for petrophysical, geophysical and geomechanical studies. Although compressional wave velocity (Vp) measurements exist in almost all wells, shear wave velocity is not recorded for most of elderly wells due to lack of technologic tools. Furthermore, measurement of shear wave velocity is to some extent costly. This study proposes a novel methodolo...

full text

OPTIMIZATION OF TREE-STRUCTURED GAS DISTRIBUTION NETWORK USING ANT COLONY OPTIMIZATION: A CASE STUDY

An Ant Colony Optimization (ACO) algorithm is proposed for optimal tree-structured natural gas distribution network. Design of pipelines, facilities, and equipment systems are necessary tasks to configure an optimal natural gas network. A mixed integer programming model is formulated to minimize the total cost in the network. The aim is to optimize pipe diameter sizes so that the location-alloc...

full text

Improved Ant Colony Optimization Algorithm for Reservoir Operation

In this paper, an improved Ant Colony Optimization (ACO) algorithm is proposed for reservoir operation. Through a collection of cooperative agents called ants, the near-optimum solution to the reservoir operation can be e ectively achieved. To apply the proposed ACO algorithm, the problem is approached by considering a nite horizon with a time series of in ow, classifying the reservoir volume t...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 5  issue 1

pages  7- 17

publication date 2015-03-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023