An Improved Unsteady-State Procedure for Determining the Relative-Permeability Characteristics of Heterogeneous Porous Media (includes associated papers 8028 and 8777 )

Sigmund, P.M.; McCaffery, F.G.

doi:10.2118/6720-pa

Cited by 153 publications

(71 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, due to the idealized hypothesis, the precision usually cannot be guaranteed when using analytical methods to calculate the water-oil or oil-gas relative permeability curve. To improve the precision of the estimated result, Sigmund and McCaffery applied a nonlinear regression to the problem of history matching laboratory coreflood data for the first time and proposed a numerical inversion method for the wateroil relative permeability curve (Sigmund and McCaffery 1979). In contrast to the existing analytical methods, when the numerical inversion methods are adopted to interpret laboratory coreflood data, production performance prior to and after water breakthrough can be utilized comprehensively.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the water–oil–gas relative permeability curve from immiscible WAG coreflood experiments using the cubic B-spline model

Wang

Sun

et al. 2016

Pet. Sci.

View full text Add to dashboard Cite

Immiscible water-alternating-gas (WAG) flooding is an EOR technique that has proven successful for water drive reservoirs due to its ability to improve displacement and sweep efficiency. Nevertheless, considering the complicated phase behavior and various multiphase flow characteristics, gas tends to break through early in production wells in heterogeneous formations because of overriding, fingering, and channeling, which may result in unfavorable recovery performance. On the basis of phase behavior studies, minimum miscibility pressure measurements, and immiscible WAG coreflood experiments, the cubic B-spline model (CBM) was employed to describe the three-phase relative permeability curve. Using the Levenberg-Marquardt algorithm to adjust the vector of unknown model parameters of the CBM sequentially, optimization of production performance including pressure drop, water cut, and the cumulative gas-oil ratio was performed. A novel numerical inversion method was established for estimation of the water-oil-gas relative permeability curve during the immiscible WAG process. Based on the quantitative characterization of major recovery mechanisms, the proposed method was validated by interpreting coreflood data of the immiscible WAG experiment. The proposed method is reliable and can meet engineering requirements. It provides a basic calculation theory for implicit estimation of oil-water-gas relative permeability curve.

show abstract

Section: Introductionmentioning

confidence: 99%

Estimation of the water–oil–gas relative permeability curve from immiscible WAG coreflood experiments using the cubic B-spline model

Wang

Sun

et al. 2016

Pet. Sci.

View full text Add to dashboard Cite

show abstract

“…Archer and Wong (1973) used a trial and error approach (manual history matching) to estimate relative permeability curves by history matching laboratory core flood data and Sigmund and McCaffery (1979) used automatic history matching (nonlinear regression) for the same purpose. However, both authors estimated only the two parameters defining the shape of power-law relative permeability curves.…”

Section: Adjustment Of Relative Permeabilitiesmentioning

confidence: 99%

Data Integration for the Generation of High Resolution Reservoir Models

Reynolds

Oliver

et al. 2009

View full text Add to dashboard Cite

The goal of this three-year project was to develop a theoretical basis and practical technology for the integration of geologic, production and time-lapse seismic data in a way that makes best use of the information for reservoir description and reservoir performance predictions. The methodology and practical tools for data integration that were developed in this research project have been incorporated into computational algorithms that are feasible for large scale reservoir simulation models. As the integration of production and seismic data require calibrating geological/geostatistical models to these data sets, the main computational tool is an automatic history matching algorithm. The following specific goals were accomplished during this research. (i) We developed algorithms for calibrating the location of the boundaries of geologic facies and the distribution of rock properties so that production and time-lapse seismic data are honored. (ii) We developed and implemented specific procedures for conditioning reservoir models to time-lapse seismic data. (iii) We developed and implemented algorithms for the characterization of measurement errors which are needed to determine the relative weights of data when conditioning reservoir models to production and time-lapse seismic data by automatic history matching. (iv) We developed and implemented algorithms for the adjustment of relative permeability curves during the history matching process. (v) We developed algorithms for production optimization which accounts for geological uncertainty within the context of closed-loop reservoir management. (vi) To ensure the research results will lead to practical public tools for independent oil companies, as part of the project we built a graphical user interface for the reservoir simulator and history matching software using Visual Basic.iii

show abstract

“…After determination of saturation and relative permeability end point values, relative permeability curvatures in mathematical function can be adjusted until the flow behavior match the laboratory observations. Therefore, an automatic history match like method could be developed to optimize curvatures (Sigmund and McCaffery 1979;Kerig and Watson 1987;Bech et al 2000;Toth et al 2001;Jaber 2013). For these relevant references, the determination of relative permeability curves is executed by representing it with two functions, each of which contains one coefficient to be adjusted to match the observations.…”

Section: Introductionmentioning

confidence: 99%

Acquisition and analysis of transient data through unsteady-state core flooding experiments

Liang¹,

Lee²,

Wang³

et al. 2016

J Petrol Explor Prod Technol

View full text Add to dashboard Cite

Dynamic displacement experiments and numerical two-phase flow estimation program are presented in this study. Unsteady-state core-flooding system was designed and utilized for oil-water dynamic displacement experiment. Two in situ sandstone core plug samples were used to investigate relative permeability via diesel and 3 wt % brine as non-wetting and wetting phase fluids. The transient data (pressure drop and produced fluid volume) were collected automatically for oil-water relative permeability computation. For relative permeability analysis, an inverse method program was constructed with four components: (a) an IMPE finite-difference numerical simulator of the flow through the core; (b) functional Corytype power law model of relative permeability in terms of a set of adjustable parameters found by minimizing an objective function; (c) the objective function formed by the sum of the square of the differences between the observations and calculated data; (4) the Gauss-Newton with Levenberg-Marquardt modification procedure for the leastsquares problem to minimize the objective function definition. All the above processes are embodied in relativepermeability calculation program, RCP, which is constructed in this study using FORTRAN language.

show abstract

An Improved Unsteady-State Procedure for Determining the Relative-Permeability Characteristics of Heterogeneous Porous Media (includes associated papers 8028 and 8777 )

Cited by 153 publications

References 4 publications

Estimation of the water–oil–gas relative permeability curve from immiscible WAG coreflood experiments using the cubic B-spline model

Estimation of the water–oil–gas relative permeability curve from immiscible WAG coreflood experiments using the cubic B-spline model

Data Integration for the Generation of High Resolution Reservoir Models

Acquisition and analysis of transient data through unsteady-state core flooding experiments

Contact Info

Product

Resources

About