Research on Oil-CO2-Water Relative Permeability of the Low Permeability Reservoir based on History Matching

2010 ◽  
Author(s):  
Renjing Liu ◽  
Huiqing Liu ◽  
Xiusheng Li ◽  
Jing Wang ◽  
Changting Pang

1996 ◽  
Vol 11 (03) ◽  
pp. 168-173 ◽  
Author(s):  
Chen Tielong ◽  
Zhao Yong ◽  
Peng Kezong ◽  
Pu Wanfeng

SPE Journal ◽  
2020 ◽  
Vol 25 (06) ◽  
pp. 3265-3279
Author(s):  
Hamidreza Hamdi ◽  
Hamid Behmanesh ◽  
Christopher R. Clarkson

Summary Rate-transient analysis (RTA) is a useful reservoir/hydraulic fracture characterization method that can be applied to multifractured horizontal wells (MFHWs) producing from low-permeability (tight) and shale reservoirs. In this paper, we applied a recently developed three-phase RTA technique to the analysis of production data from an MFHW completed in a low-permeability volatile oil reservoir in the Western Canadian Sedimentary Basin. This RTA technique is used to analyze the transient linear flow regime for wells operated under constant flowing bottomhole pressure (BHP) conditions. With this method, the slope of the square-root-of-time plot applied to any of the producing phases can be used to directly calculate the linear flow parameter xfk without defining pseudovariables. The method requires a set of input pressure/volume/temperature (PVT) data and an estimate of two-phase relative permeability curves. For the field case studied herein, the PVT model is constructed by tuning an equation of state (EOS) from a set of PVT experiments, while the relative permeability curves are estimated from numerical model history-matchingresults. The subject well, an MFHW completed in 15 stages, produces oil, water, and gas at a nearly constant (measured downhole) flowing BHP. This well is completed in a low-permeability,near-critical volatile oil system. For this field case, application of the recently proposed RTA method leads to an estimate of xfk that is in close agreement (within 7%) with the results of a numerical model history match performed in parallel. The RTA method also provides pressure–saturation (P–S) relationships for all three phases that are within 2% of those derived from the numerical model. The derived P–S relationships are central to the use of other RTA methods that require calculation of multiphase pseudovariables. The three-phase RTA technique developed herein is a simple-yet-rigorous and accurate alternative to numerical model history matching for estimating xfk when fluid properties and relative permeability data are available.


Fractals ◽  
2018 ◽  
Vol 26 (03) ◽  
pp. 1850037 ◽  
Author(s):  
MINGCHAO LIANG ◽  
YINHAO GAO ◽  
SHANSHAN YANG ◽  
BOQI XIAO ◽  
ZHANKUI WANG ◽  
...  

Jamin effect, which is a capillary pressure obstructing the drop/bubble flow through the narrow throat, has an important effect on the multiphase flow in the low permeability reservoir porous media. In this work, a novel model for the relative permeability with Jamin effect is developed to study the two-phase flow through porous media based on the fractal theory. The proposed relative permeability is expressed as a function of the applied pressure difference, shape parameters of the drop/bubble, the physical parameters of the wetting and nonwetting fluids, and microstructural parameters of porous media. Good agreement between model predictions and available experimental data is obtained, and the advantage of the present fractal model can be highlighted by comparisons with the empirical model predictions. Additionally, the influences of Jamin effect on the two-phase relative permeability are discussed comprehensively and in detail. The model reveals that the length ratios ([Formula: see text] and [Formula: see text]) have significant effects on the relative permeabilities. It is also found that the nonwetting phase relative permeability strongly depends on the interfacial tension, applied pressure difference, viscosity ratio and porosity of porous media at the lower wetting phase saturation. Furthermore, the fractal model will shed light on the two-phase transport mechanism of the low permeability reservoir porous media.


Author(s):  
Clark Huffman

Abstract The ability to predict well inflow performance for varying well and reservoir conditions is important when optimizing production. Many methods exist to estimate a well’s current productive capacity (IPR curve) and extensions to the methods are available for predicting future well performance. The extensions to predict future inflow performance behavior account for changes in relative permeability and assume an average reservoir pressure. The applicability and accuracy of the methods depends on knowledge of reservoir parameters which may be difficult to obtain in low permeability reservoirs. Several authors have presented methods of analyzing and history matching well performance. These methods typically yield reservoir parameters which may be used in the well inflow performance methods in order to investigate the results of varying well production parameters. These methods are particularly useful in low permeability settings where interpretable welltest data may be difficult to obtain or prohibitively expensive. Currently, the analytical history matching approach is most accurate when applied to single-phase systems. Predictions of black oil reservoir performance below the bubble point can exhibit large error since depletion of the total reservoir energy is not accounted for using the constant gas-oil ratio approach typical for these methods. This paper presents a method to analyze well performance of black oil systems below the bubble point. The method incorporates a material balance approach to account for changing gas-oil ratios as the reservoir is depleted. Prediction of future well performance is also presented. Along with reservoir characterization, another benefit of the method is the ability to construct IPR curves at any point in order to optimize production. The proposed method uses a pseudo pressure transform to account for changes in fluid properties as the reservoir pressure is depleted. Relative permeability changes can be incorporated in the pseudo pressure transform. Comparisons to finite difference simulation results and actual productio data are presented. Comparisons of future IPR curves generated by other methods are also presented.


2014 ◽  
Vol 7 (1) ◽  
pp. 55-63 ◽  
Author(s):  
Haiyong Zhang ◽  
Shunli He ◽  
Chunyan Jiao ◽  
Guohua Luan ◽  
Shaoyuan Mo

2015 ◽  
Vol 33 (4) ◽  
pp. 491-514 ◽  
Author(s):  
Shuheng Du ◽  
Yongmin Shi ◽  
Xiangqian Bu ◽  
Wenqi Jin ◽  
Guoquan Mu

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