scholarly journals Determination of Basic Reservoir Parameters in Shale Formations as a Solution of Inverse Problem in the Computer Assisted History Matching of their Simulation Models. Part I – Introduction to Methodology and Initial Tests

Nafta-Gaz ◽  
2015 ◽  
Vol 71 (11) ◽  
pp. 870-876
Author(s):  
Piotr Łętkowski ◽  
◽  
Wiesław Szott ◽  
Keyword(s):  
Inverse Problem ◽  
History Matching ◽  
Simulation Models ◽  
Computer Assisted ◽  
Shale Formations ◽  
Assisted History Matching

Parameters Estimation for Chemical Flooding Modeling Using Ensemble-Based Method

2021 ◽  
Author(s):  
Xindan Wang ◽  
Yin Zhang ◽  
Abhijit Dandekar ◽  
Yudou Wang
Keyword(s):  
Simulation Model ◽  
Oil Recovery ◽  
History Matching ◽  
Simulation Models ◽  
Parameters Estimation ◽  
Model Parameters ◽  
Chemical Flooding ◽  
Multiple Model ◽  
Assisted History Matching ◽  
Matching Techniques

Abstract Chemical flooding has been widely used to enhance oil recovery after conventional waterflooding. However, it is always a challenge to model chemical flooding accurately since many of the model parameters of the chemical flooding cannot be measured accurately in the lab and even some parameters cannot be obtained from the lab. Recently, the ensemble-based assisted history matching techniques have been proven to be efficient and effective in simultaneously estimating multiple model parameters. Therefore, this study validates the effectiveness of the ensemble-based method in estimating model parameters for chemical flooding simulation, and the half-iteration EnKF (HIEnKF) method has been employed to conduct the assisted history matching. In this work, five surfactantpolymer (SP) coreflooding experiments have been first conducted, and the corresponding core scale simulation models have been built to simulate the coreflooding experiments. Then the HIEnKF method has been applied to calibrate the core scale simulation models by assimilating the observed data including cumulative oil production and pressure drop from the corresponding coreflooding experiments. The HIEnKF method has been successively applied to simultaneously estimate multiple model parameters, including porosity and permeability fields, relative permeabilities, polymer viscosity curve, polymer adsorption curve, surfactant interfacial tension (IFT) curve and miscibility function curve, for the SP flooding simulation model. There exists a good agreement between the updated simulation results and observation data, indicating that the updated model parameters are appropriate to characterize the properties of the corresponding porous media and the fluid flow properties in it. At the same time, the effectiveness of the ensemble-based assisted history matching method in chemical enhanced oil recovery (EOR) simulation has been validated. Based on the validated simulation model, numerical simulation tests have been conducted to investigate the influence of injection schemes and operating parameters of SP flooding on the ultimate oil recovery performance. It has been found that the polymer concentration, surfactant concentration and slug size of SP flooding have a significant impact on oil recovery, and these parameters need to be optimized to achieve the maximum economic benefit.

An Evaluation of Assisted History Matching Methodologies for Giant Simulation Models

2015 ◽  
Author(s):  
Ali Alturki ◽  
Majdi Baddourah ◽  
Yusuf Pamuku ◽  
Fabio Ravanelli ◽  
Ehtesham Hayder
Keyword(s):  
History Matching ◽  
Simulation Models ◽  
Assisted History Matching

Computer Assisted History Matching - A Field Example

2013 ◽  
Author(s):  
R. H. Lind ◽  
O. Allottai ◽  
A. M. Gaaim ◽  
H. Almuallim
Keyword(s):  
History Matching ◽  
Computer Assisted ◽  
Assisted History Matching

A New Computer Assisted History Matching Method

2010 ◽  
Author(s):  
Fathe Suliman Abrahem ◽  
Zoltan E. Heinemann ◽  
Georg Martin Abrahem
Keyword(s):  
History Matching ◽  
Computer Assisted ◽  
Matching Method ◽  
Assisted History Matching
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