scholarly journals The Numerical Simulation Study of the Oil–Water Seepage Behavior Dependent on the Polymer Concentration in Polymer Flooding

Energies ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 5125
Author(s):  
Qiong Wang ◽  
Xiuwei Liu ◽  
Lixin Meng ◽  
Ruizhong Jiang ◽  
Haijun Fan
Keyword(s):  
Relative Permeability ◽  
History Matching ◽  
Polymer Concentration ◽  
Polymer Flooding ◽  
Core Flooding ◽  
Relative Permeability Curve ◽  
Oil Water ◽  
Trapping Number ◽  
Relative Permeability Curves ◽  
Interpolation Factor

It is well acknowledged that due to the polymer component, the oil–water relative permeability curve in polymer flooding is different from the curve in waterflooding. As the viscoelastic properties and the trapping number are presented for modifying the oil–water relative permeability curve, the integration of these two factors for the convenience of simulation processes has become a key issue. In this paper, an interpolation factor Ω that depends on the normalized polymer concentration is firstly proposed for simplification. Then, the numerical calculations in the self-developed simulator are performed to discuss the effects of the interpolation factor on the well performances and the applications in field history matching. The results indicate that compared with the results of the commercial simulator, the simulation with the interpolation factor Ω could more accurately describe the effect of the injected polymer solution in controlling water production, and more efficiently simplify the combination of factors on relative permeability curves in polymer flooding. Additionally, for polymer flooding history matching, the interpolation factor Ω is set as an adjustment parameter based on core flooding results to dynamically consider the change of the relative permeability curves, and has been successfully applied in the water cut matching of the two wells in Y oilfield. This investigation provides an efficient method to evaluate the seepage behavior variation of polymer flooding.

An Inversion Method of Relative Permeability Curves in Polymer Flooding Considering Physical Properties of Polymer

SPE Journal ◽  
2018 ◽  
Vol 23 (05) ◽  
pp. 1929-1943 ◽  
Author(s):  
Yongge Liu ◽  
Jian Hou ◽  
Lingling Liu ◽  
Kang Zhou ◽  
Yanhui Zhang ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Simulation Model ◽  
Relative Permeability ◽  
Polymer Flooding ◽  
Inversion Method ◽  
Residual Resistance ◽  
Relative Permeability Curve ◽  
Nonsteady State ◽  
State Method ◽  
Relative Permeability Curves

Summary Reliable relative permeability curves of polymer flooding are of great importance to the history matching, production prediction, and design of the injection and production plan. Currently, the relative permeability curves of polymer flooding are obtained mainly by the steady-state, nonsteady-state, and pore-network methods. However, the steady-state method is extremely time-consuming and sometimes produces huge errors, while the nonsteady-state method suffers from its excessive assumptions and is incapable of capturing the effects of diffusion and adsorption. As for the pore-network method, its scale is very small, which leads to great size differences with the real core sample or the field. In this paper, an inversion method of relative permeability curves in polymer flooding is proposed by combining the polymer-flooding numerical-simulation model and the Levenberg-Marquardt (LM) algorithm. Because the polymer-flooding numerical-simulation model by far offers the most-complete characterization of the flowing mechanisms of polymer, the proposed method is able to capture the effects of polymer viscosity, residual resistance, diffusion, and adsorption on the relative permeability. The inversion method was then validated and applied to calculate the relative permeability curve from the experimental data of polymer flooding. Finally, the effects of the influencing factors on the inversion error were analyzed, through which the inversion-error-prediction model of the relative permeability curve was built by means of multivariable nonlinear regression. The results show that the water relative permeability in polymer flooding is still far less than that in waterflooding, although the residual resistance of the polymer has been considered in the numerical-simulation model. Moreover, the accuracy of the polymer parameters has great effect on that of the inversed relative permeability curve, and errors do occur in the inversed water relative permeability curve—the measurements of the polymer solution viscosity, residual resistance factor, inaccessible pore-volume (PV) fraction, or maximum adsorption concentration have errors.

scholarly journals Analysis and Evaluation of Oil-water Relative Permeability Curves

2015 ◽  
Vol 8 (1) ◽  
pp. 181-185
Author(s):  
Yang Manping ◽  
Xi Wancheng ◽  
Zhao Xiaojing ◽  
Cheng Yanhong
Keyword(s):  
Relative Permeability ◽  
Water Phase ◽  
Core Flooding ◽  
Displacement Efficiency ◽  
Analysis And Evaluation ◽  
Different Types ◽  
Oil Displacement Efficiency ◽  
Oil Water ◽  
Relative Permeability Curves ◽  
The Relationship

Oil-water relative permeability curves are the characteristic curves of evaluating the oil-water infiltrating fluid and also are an important part of reservoir engineering studies. Through a large number of core flooding experiments, based on the establishment of oil-water relative permeability calculation models, the use of the function of the relative permeability curves divided these into the water phase concave, water phase convex and a water phase linear categories. The relationship between different types of relative permeability curves with reservoir characteristics, moisture content, common infiltration points, common permeation range and oil displacement efficiency have been evaluated. Analysis the distribution of the reservoir usable remaining oil and reservoir irreducible oil of different types of relative permeability curves.

Obtaining Relative Permeability Curve of Carbonate Reservoir by the Weighted Method

2019 ◽  
Vol 13 (1) ◽  
pp. 83-91
Author(s):  
Bin Huang ◽  
Zhenzhong Shi ◽  
Ying Wang ◽  
Cheng Fu ◽  
Meng Cai
Keyword(s):  
Relative Permeability ◽  
Physical Simulation ◽  
Carbonate Reservoir ◽  
New Method ◽  
Hydrodynamic Characteristics ◽  
Relative Permeability Curve ◽  
Porosity And Permeability ◽  
Weight Method ◽  
Oil Water ◽  
Relative Permeability Curves

Background: The oil-water relative permeability curve is an important experimental data and basis for oilfield development scheme and dynamic prediction. The characteristics of oil and water relative permeability curves in different reservoirs are otherness. Objective: In order to enable various effects to be reflected in the standardized relative permeability curve, the standardized relative permeability curve can reflect the characteristics of each core. Method: The core is taken from core wells in a similar flow unit. The oil-water relative permeability curves are measured by indoor physical simulation experiments. The oil-water relative permeability curves of representativeness and conforming to hydrodynamic characteristics are screened. Because the porosity and permeability of different cores have different effects on the relative permeability curve, the weight of the porosity and permeability of each core is added to the standard relative permeability curve in the process of solving standardized relative permeability curve. Results: A new method that the weight method to be used to solve the problem of the standardized relative permeability curve is obtained. The comparison of the new method and the average method shows that both of them are highly consistent. Conclusion: The patent on the solution of the relative permeability curve is improved. Considered the effect of different cores of porosity and permeability on the relative permeability curve. Calculated the weight of the porosity and permeability of different cores. The representative normalized relative permeability curve is obtained by using the weight method.

scholarly journals Interpretation of Gas/Water Relative Permeability of Coal Using the Hybrid Bayesian-Assisted History Matching: New Insights

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 626
Author(s):  
Jiyuan Zhang ◽  
Bin Zhang ◽  
Shiqian Xu ◽  
Qihong Feng ◽  
Xianmin Zhang ◽  
...  
Keyword(s):  
Relative Permeability ◽  
Coalbed Methane ◽  
History Matching ◽  
Water Saturation ◽  
Unsteady State ◽  
Core Flooding ◽  
Rock Interaction ◽  
Interaction Mechanisms ◽  
True Value ◽  
Assisted History Matching

The relative permeability of coal to gas and water exerts a profound influence on fluid transport in coal seams in both primary and enhanced coalbed methane (ECBM) recovery processes where multiphase flow occurs. Unsteady-state core-flooding tests interpreted by the Johnson–Bossler–Naumann (JBN) method are commonly used to obtain the relative permeability of coal. However, the JBN method fails to capture multiple gas–water–coal interaction mechanisms, which inevitably results in inaccurate estimations of relative permeability. This paper proposes an improved assisted history matching framework using the Bayesian adaptive direct search (BADS) algorithm to interpret the relative permeability of coal from unsteady-state flooding test data. The validation results show that the BADS algorithm is significantly faster than previous algorithms in terms of convergence speed. The proposed method can accurately reproduce the true relative permeability curves without a presumption of the endpoint saturations given a small end-effect number of <0.56. As a comparison, the routine JBN method produces abnormal interpretation results (with the estimated connate water saturation ≈33% higher than and the endpoint water/gas relative permeability only ≈0.02 of the true value) under comparable conditions. The proposed framework is a promising computationally effective alternative to the JBN method to accurately derive relative permeability relations for gas–water–coal systems with multiple fluid–rock interaction mechanisms.

scholarly journals Insights, Trends and Challenges Associated with Measuring Coal Relative Permeability

2019 ◽  
Vol 89 ◽  
pp. 01004
Author(s):  
Dylan Shaw ◽  
Peyman Mostaghimi ◽  
Furqan Hussain ◽  
Ryan T. Armstrong
Keyword(s):  
Relative Permeability ◽  
Effective Stress ◽  
History Matching ◽  
Water Saturation ◽  
Laboratory Data ◽  
Stress Regime ◽  
Cross Point ◽  
Irreducible Water Saturation ◽  
Relative Permeability Curves ◽  
The Right

Due to the poroelasticity of coal, both porosity and permeability change over the life of the field as pore pressure decreases and effective stress increases. The relative permeability also changes as the effective stress regime shifts from one state to another. This paper examines coal relative permeability trends for changes in effective stress. The unsteady-state technique was used to determine experimental relativepermeability curves, which were then corrected for capillary-end effect through history matching. A modified Brooks-Corey correlation was sufficient for generating relative permeability curves and was successfully used to history match the laboratory data. Analysis of the corrected curves indicate that as effective stress increases, gas relative permeability increases, irreducible water saturation increases and the relative permeability cross-point shifts to the right.

A New Correction Method for Oil–Water Relative Permeability Curve on the Basis of Resistivity and Water Saturation Relationship

2015 ◽  
Vol 109 (3) ◽  
pp. 527-540 ◽  
Author(s):  
Wei Hu ◽  
Shenglai Yang ◽  
Guangfeng Liu ◽  
Zhilin Wang ◽  
Ping Wang ◽  
...  
Keyword(s):  
Relative Permeability ◽  
Water Saturation ◽  
Correction Method ◽  
Relative Permeability Curve ◽  
Oil Water

A Semianalytical Approach for Analysis of Wells Exhibiting Multiphase Transient Linear Flow: Application to Field Data

SPE Journal ◽  
2020 ◽  
Vol 25 (06) ◽  
pp. 3265-3279
Author(s):  
Hamidreza Hamdi ◽  
Hamid Behmanesh ◽  
Christopher R. Clarkson
Keyword(s):  
Numerical Model ◽  
Relative Permeability ◽  
History Matching ◽  
Volatile Oil ◽  
Low Permeability ◽  
Two Phase ◽  
Linear Flow ◽  
Field Case ◽  
Three Phase ◽  
Relative Permeability Curves

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.

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