Sensitivity Coefficients for History Matching Oil Displacement Processes

1975 ◽  
Vol 15 (01) ◽  
pp. 39-49 ◽  
Author(s):  
George J. Hirasaki
Keyword(s):  
Relative Permeability ◽  
Oil Recovery ◽  
History Matching ◽  
Mobility Ratio ◽  
Dimensional System ◽  
Relative Significance ◽  
One Dimensional ◽  
Relative Permeability Curve ◽  
Sensitivity Coefficients ◽  
Recovery Performance

Abstract An improved estimate of the reservoir parameters is made during the history-matching phase of a reservoir simulation study by determining the set of parameters that result in the best match of the simulated performance with the observed performance. Often, the process of determining which parameters are to be adjusted is a trial-and-error process. Graphs of the sensitivity coefficients for comparing the cumulative oil recovery with the reservoir parameters are presented to determine the relative significance of parameters are presented to determine the relative significance of the parameters and to provide guidelines for the magnitude of change to the parameters. The sensitivity coefficients are based on a one-dimensional system with dip, incompressible fluids, and polynomial relative-permeability curves. The recovery efficiency can be expressed as a function of the dimensionless cumulative injection with the gravity number (gravity/viscous-forces ratio), mobility ratio, and relative-permeability exponent as parameters. The sensitivity of the cumulative oil recovery (at a given value of cumulative injection) to the movable pore volume, mobility ratio, permeability, and the exponent of the relative-permeability curve permeability, and the exponent of the relative-permeability curve can be calculated from the expression for the recovery efficiency. The graphs of the sensitivity coefficients can be used to determine the relative significance of the parameters, if a unique set of parameters can be determined, and how much they should be adjusted. parameters can be determined, and how much they should be adjusted Introduction When the simulated oil-recovery performance differs from the observed performance history, the engineer must determineif the history match is satisfactory, orif not, which reservoir parameters are to be adjusted and how much. The purpose of this parameters are to be adjusted and how much. The purpose of this discussion is to provide guidelines for the engineer in choosing the parameter(s) to be adjusted and to determine the magnitude and direction of the change. This will be accomplished by first illustrating the sensitivity of water or gas displacement performance to the reservoir parameters so that the critical parameter(s) can be identified, and then graphically presenting the magnitude of the sensitivity coefficients to determine the magnitude of change in the parameter value necessary to achieve a match. The following guidelines will be limited in scope to two-phase displacement processes with negligible interfacial mass transfer (e.g., waterflood, natural water drive, gas injection, or gas-cap expansion). Processes such as solution gas drive or vaporizing gas drive will not be presented. The results will be expressed in terms of the gross fluids produced or injected rather than time. The analysis and results are based on a one-dimensional system. Although the recovery performance of a multidimensional system will be different from that of a one-dimensional system, the relative sensitivity of the recovery performance to the parameters should not differ significantly for most recovery processes. Examples of exceptions that cannot be represented with the one-dimensional system are where well coning is significant or where permeability barriers exist between the injection well and production well. production well. The reservoir parameters that are investigated arethe movable pore volume of the displacement process, SVp;the mobility ratio of the displacing fluid to the displaced fluid, M, where the mobilities are evaluated at the maximum saturation of each phase;the permeability, which is represented as a factor in the gravity number, N(G) if the formation is dipping; andthe shape of the relative permeability curve, expressed in terms of a single parameter, n. ASSUMPTIONS AND MODEL OF THE DISPLACEMENT PROCESS The following assumptions are made about the displacement process. process.The saturations, relative permeabilities, porosity, and permeability are averaged over the reservoir thickness. permeability are averaged over the reservoir thickness.The areal displacement is modeled with a linear system. SPEJ P. 39

A Nine-Point, Finite-Difference Reservoir Simulator for Realistic Prediction of Adverse Mobility Ratio Displacements

1979 ◽  
Vol 19 (04) ◽  
pp. 253-262 ◽  
Author(s):  
J.L. Yanosik ◽  
T.A. McCracken
Keyword(s):  
Finite Difference ◽  
Oil Recovery ◽  
Mobility Ratio ◽  
Spot Pattern ◽  
Oil Saturation ◽  
Grid Systems ◽  
Displacement Front ◽  
Grid Orientation ◽  
Recovery Performance ◽  
Reservoir Simulator

Abstract Reservoir simulators based on five-point difference techniques do not predict the correct recovery performance for unfavorable mobility-ratio, piston-type performance for unfavorable mobility-ratio, piston-type displacements. For a developed five-spot pattern, the predicted performance depends on the grid orientation predicted performance depends on the grid orientation (parallel or diagonal) used. This paper discusses the development and testing of a nine-point, finite-difference reservoir simulator. Developed five-spot-pattern flood predictions are presented for piston-type displacements predictions are presented for piston-type displacements with mobility ratios ranging from 0.5 to 50-0. We show that the predicted fronts are realistic and that very little or no difference exists between the results of parallel and diagonal grids. The maximum difference in the recovery curves is less than 1.5 %. The nine-point-difference method is extended to any grid network composed of rectangular elements. Results for two example problems - a linear flood and a direct line-drive flood - indicate the extension is correct. The techniques discussed here can be applied directly in the development of any reservoir simulator. We anticipate that the greatest utility will be in the development of simulators for the improved oil-recovery processes that involve unfavorable mobility ratio processes that involve unfavorable mobility ratio displacements. Examples are miscible flooding, micellar/ polymer flooding (water displacing polymer), and direct polymer flooding (water displacing polymer), and direct steam drive. Introduction Miscible displacement oil-recovery methods often are characterizedby a large viscosity ratio between the oil and its miscible fluid andby a very low immobile oil saturation behind the displacement front. These conditions represent an unfavorable mobility-ratio, piston-type displacement. They differ from a conventional piston-type displacement. They differ from a conventional gas drive, where a substantial mobile oil saturation remains behind the displacement front. Reservoir simulators based on five-point, finitedifference techniques do not predict the correct performance for unfavorable mobility-ratio, piston-type performance for unfavorable mobility-ratio, piston-type displacements. Results of an areal simulation for a developed five-spot flood depend on the grid orientation (diagonal or parallel, Fig. 1). Grid orientation significantly influences the predicted recovery performance and displacement front positions. performance and displacement front positions. A nine-point, finite-difference reservoir simulator is described. Predictions of piston-type displacements in a developed five-spot pattern are presented for mobility ratios ranging from 0.5 to 50. We show that the predicted fronts are realistic and that very little or no predicted fronts are realistic and that very little or no difference exists between the results of parallel and diagonal grid orientations. A formulation of the nine-point, finite-difference technique applicable to any rectangular grid network is presented. Results for two example two-dimensional presented. Results for two example two-dimensional problems, a linear flood, and a direct line-drive flood problems, a linear flood, and a direct line-drive flood indicate that the formulation is correct for nonsquare grid networks. Background Grid-orientation effects for five-point reservoir simulators were demonstrated by Todd et al. They studied two developed five-spot grid systems - a diagonal grid and a parallel grid. These grid systems are shown in Fig. 1. parallel grid. These grid systems are shown in Fig. 1. The diagonal grid represents a quarter of a five-spot pattern, with grid lines at 45 degrees to a line connecting the pattern, with grid lines at 45 degrees to a line connecting the injector and producer. The parallel grid represents one-half of a five-spot pattern, with grid lines either parallel or perpendicular to the lines connecting the parallel or perpendicular to the lines connecting the injector-producer pads. SPEJ P. 253

scholarly journals Mysteries behind the Low Salinity Water Injection Technique

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Emad Waleed Al-Shalabi ◽  
Kamy Sepehrnoori ◽  
Gary Pope
Keyword(s):  
Relative Permeability ◽  
Oil Recovery ◽  
History Matching ◽  
Water Injection ◽  
Residual Oil ◽  
Oil Saturation ◽  
Low Salinity ◽  
Low Salinity Water ◽  
Salinity Water ◽  
Low Salinity Water Injection

Low salinity water injection (LSWI) is gaining popularity as an improved oil recovery technique in both secondary and tertiary injection modes. The objective of this paper is to investigate the main mechanisms behind the LSWI effect on oil recovery from carbonates through history-matching of a recently published coreflood. This paper includes a description of the seawater cycle match and two proposed methods to history-match the LSWI cycles using the UTCHEM simulator. The sensitivity of residual oil saturation, capillary pressure curve, and relative permeability parameters (endpoints and Corey’s exponents) on LSWI is evaluated in this work. Results showed that wettability alteration is still believed to be the main contributor to the LSWI effect on oil recovery in carbonates through successfully history matching both oil recovery and pressure drop data. Moreover, tuning residual oil saturation and relative permeability parameters including endpoints and exponents is essential for a good data match. Also, the incremental oil recovery obtained by LSWI is mainly controlled by oil relative permeability parameters rather than water relative permeability parameters. The findings of this paper help to gain more insight into this uncertain IOR technique and propose a mechanistic model for oil recovery predictions.

A Novel Method To Model Low-Salinity-Water Injection in Carbonate Oil Reservoirs

SPE Journal ◽  
2015 ◽  
Vol 20 (05) ◽  
pp. 1154-1166 ◽  
Author(s):  
Emad W. Al-Shalabi ◽  
Kamy Sepehrnoori ◽  
Mojdeh Delshad ◽  
Gary Pope
Keyword(s):  
Capillary Pressure ◽  
Relative Permeability ◽  
Oil Recovery ◽  
Carbonate Rocks ◽  
History Matching ◽  
Water Injection ◽  
Low Salinity ◽  
Low Salinity Water ◽  
Salinity Water ◽  
Low Salinity Water Injection

Summary There are few low-salinity-water-injection (LSWI) models proposed for carbonate rocks, mainly because of incomplete understanding of complex chemical interactions of rock/oil/brine. This paper describes a new empirical method to model the LSWI effect on oil recovery from carbonate rocks, on the basis of the history matching and validation of recently published corefloods. In this model, the changes in the oil relative permeability curve and residual oil saturation as a result of the LSWI effect are considered. The water relative permeability parameters are assumed constant, which is a relatively fair assumption on the basis of history matching of coreflood data. The capillary pressure is neglected because we assumed several capillary pressure curves in our simulations in which it had a negligible effect on the history-match results. The proposed model is implemented in the UTCHEM simulator, which is a 3D multiphase flow, transport, and chemical-flooding simulator developed at The University of Texas at Austin (UTCHEM 2000), to match and predict the multiple cycles of low-salinity experiments. The screening criteria for using the proposed LSWI model are addressed in the paper. The developed model gives more insight into the oil-production potential of future waterflood projects with a modified water composition for injection.

The Effects of Interfacial Tension Dependent Relative Permeability on Sweep Efficiency and Oil Recovery Under Different Gas Injection Composition

2021 ◽  
Author(s):  
Mohd Ghazali Abd Karim ◽  
Wahyu Hidayat ◽  
Alzahrani Abdulelah
Keyword(s):  
Interfacial Tension ◽  
Simulation Model ◽  
Relative Permeability ◽  
Oil Recovery ◽  
Gas Injection ◽  
Sweep Efficiency ◽  
Reservoir Properties ◽  
Relative Permeability Curve ◽  
Compositional Model ◽  
The Impact

Abstract The objective of this paper is to investigate the effects of interfacial tension dependent relative permeability (Kr_IFT) on oil displacement and recovery under different gas injection compositions utilizing a compositional simulation model. Oil production under miscible gas injection will result in variations of interfacial tension (IFT) due to changes in oil and gas compositions and other reservoir properties, such as pressure and temperature. Laboratory experiments show that changes in IFT will affect the two-phase relative permeability curve (Kr), especially for oil-gas system. Using a single relative permeability curve during the process from immiscible to miscible conditions will result in inaccurate gas mobility against water, which may lead to poor estimation of sweep efficiency and oil recovery. A synthetic sector compositional model was built to evaluate the effects of this phenomenon. Several simulation cases were investigated over different gas injection compositions (lean, rich and CO2), fluid properties and reservoir characterizations to demonstrate the impact of these parameters. Simulation model results show that the application of Kr_IFT on gas injection simulation modelling has captured different displacement behavior to provide better estimation of oil recovery and identify any upside potential.

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.

Simulation of Immiscible Water-Alternating-Gas Injection in a Stratified Reservoir: Performance Characterization Using a New Dimensionless Number

SPE Journal ◽  
2020 ◽  
Vol 25 (04) ◽  
pp. 1711-1728 ◽  
Author(s):  
Jan Inge Nygård ◽  
Pål Østebø Andersen
Keyword(s):  
Gas Phase ◽  
Relative Permeability ◽  
Oil Recovery ◽  
Gravity Models ◽  
Mobility Ratio ◽  
Dimensionless Number ◽  
Low Permeability ◽  
Fluid Mixture ◽  
Gravity Segregation ◽  
Water Alternating Gas

Summary Water alternating gas (WAG) is a well-established enhanced-oil-recovery process where gas and water are injected in alternating fashion. Good volumetric sweep is achieved as water and gas target both the oil residing in low and high portions of the reservoir, respectively. Other important features in three-phase hysteretic flow include phase trapping, which is believed to be more strongly associated with the gas phase. With these aspects in mind, a vast simulation study has been performed investigating immiscible WAG injection focusing on mechanisms such as mobility, gravity, injected volume fractions, reservoir heterogeneity, gas entrapment, and relative permeability hysteresis. The aim of our work is to investigate the interplay between these mechanisms for a model system with sufficient complexity to be of relevance and then scale recovery performance using a new dimensionless number that incorporates the relevant model input parameters. A horizontally layered reservoir is considered where oil is displaced by water and gas alternately injected toward a producer. The model is a modified black-oil type, where hysteresis in the gas phase is modeled using the Land (1968) model for trapping and the Carlson (1981) model for relative permeability hysteresis. It is seen that gravity segregation in uniform models and increased heterogeneity in no-gravity models both lead to lower oil recovery. However, in heterogeneous models, gravity can divert flow from high-permeability layers into low-permeability layers and improve recovery. Hysteresis lowers gas mobility and hence improves gas/oil mobility ratio and reduces gravity segregation. The first effect is always positive, but the second is mainly positive in more uniform reservoirs where gravity segregation has a negative effect on recovery. In heterogeneous reservoirs, reducing gravity segregation can lead to the oil in low-permeability layers remaining unswept. The newly derived characteristic dimensionless number is effectively a WAG mobility ratio, termed M*, expressing how well the injected-fluid mixture is able to displace oil, whether it is because of fluid mobilities, heterogeneity, or other effects. At a value of M* near unity, optimal recovery is achieved, whereas logarithmic increase of M* reduces recovery.

A Case Study in Scaleup for Multicontact Miscible Hydrocarbon Gas Injection

1998 ◽  
Vol 1 (06) ◽  
pp. 575-582 ◽  
Author(s):  
G.R. Jerauld
Keyword(s):  
Relative Permeability ◽  
Oil Recovery ◽  
History Matching ◽  
Fine Grid ◽  
Full Field ◽  
Compositional Model ◽  
Three Phase ◽  
Solvent Retention ◽  
Hydrocarbon Gas ◽  
Relative Permeability Curves

Summary We describe the strategy and results of scaleup done to simulate a multicontact miscible hydrocarbon water alternating gas (WAG) injection process. To adequately model both oil recovery and solvent retention in WAG, one must model three-phase flow including gas trapping. Scaleup of the multicontact miscible gas process is particularly difficult because of the very fine-scale structure of the gas fingers and the miscible front. The case studied is a heterogeneous mixed wet reservoir with a transition zone down to an underlying aquifer. The objective was to develop pseudo relative permeability curves and other parameters that are suitable for running in a full-field limited compositional model with three hydrocarbon components. Both history-matching and systematic approaches were used to generate pseudo relative permeability curves that reproduced results of high-resolution, fully compositional (FC) reference simulations. Dynamic pseudoization techniques were used to derive first guesses at pseudos, but required further calibration to reproduce reference simulations successfully. In matching incremental miscible gas/oil recovery timing and solvent retention, varying three phase water relative permeability was much more effective than varying the mixing parameter. The predictive capability of pseudos was tested for changes with respect to slug size, WAG ratio, and solvent enrichment. Pseudos derived for one pattern or cross section were tested in other patterns or cross sections. Pseudos worked well with respect to changes in WAG ratio, fairly well with respect to changes in solvent enrichment, and moderately well for changes in slug size. They were less robust with respect to changes in description. Introduction Estimation of the incremental recovery and solvent utilization in a multicontact miscible hydrocarbon gas process is challenging. On one hand, important features of the process occur over small-length scales and cannot be estimated readily without very fine-grid, FC simulation. The condensing/vaporizing drive entails the concentration of enriching components into a narrow miscible front that is smeared by coarse areal gridding. High vertical grid refinement is needed to capture thin gas fingers that form within layers of high permeability. SPE 53006 was revised for publication from paper SPE 39626, first presented at the 1998 SPE/DOE Improved Oil Recovery Symposium, Tulsa, Oklahoma, 19-22 April.

Stabilization of Dominant Structures in an Ionic Reaction-Diffusion System

1998 ◽  
Vol 63 (6) ◽  
pp. 761-769 ◽  
Author(s):  
Roland Krämer ◽  
Arno F. Münster
Keyword(s):  
Reaction Diffusion ◽  
Dominant Mode ◽  
Reaction Diffusion System ◽  
Diffusion System ◽  
Local Perturbation ◽  
Dimensional System ◽  
One Dimensional ◽  
Brusselator Model ◽  
The One ◽  
Dominant Structure

We describe a method of stabilizing the dominant structure in a chaotic reaction-diffusion system, where the underlying nonlinear dynamics needs not to be known. The dominant mode is identified by the Karhunen-Loeve decomposition, also known as orthogonal decomposition. Using a ionic version of the Brusselator model in a spatially one-dimensional system, our control strategy is based on perturbations derived from the amplitude function of the dominant spatial mode. The perturbation is used in two different ways: A global perturbation is realized by forcing an electric current through the one-dimensional system, whereas the local perturbation is performed by modulating concentrations of the autocatalyst at the boundaries. Only the global method enhances the contribution of the dominant mode to the total fluctuation energy. On the other hand, the local method leads to simple bulk oscillation of the entire system.

scholarly journals Experimental investigation of the displacement flow mechanism and oil recovery in primary polymer flood operations

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Ruissein Mahon ◽  
Gbenga Oluyemi ◽  
Babs Oyeneyin ◽  
Yakubu Balogun
Keyword(s):  
Relative Permeability ◽  
Oil Recovery ◽  
Polymer Flooding ◽  
Mobility Control ◽  
List Type ◽  
Motor Oil ◽  
Flow Mechanism ◽  
Fractional Flow ◽  
Recovery Method ◽  
Polymer Flood

Abstract Polymer flooding is a mature chemical enhanced oil recovery method employed in oilfields at pilot testing and field scales. Although results from these applications empirically demonstrate the higher displacement efficiency of polymer flooding over waterflooding operations, the fact remains that not all the oil will be recovered. Thus, continued research attention is needed to further understand the displacement flow mechanism of the immiscible process and the rock–fluid interaction propagated by the multiphase flow during polymer flooding operations. In this study, displacement sequence experiments were conducted to investigate the viscosifying effect of polymer solutions on oil recovery in sandpack systems. The history matching technique was employed to estimate relative permeability, fractional flow and saturation profile through the implementation of a Corey-type function. Experimental results showed that in the case of the motor oil being the displaced fluid, the XG 2500 ppm polymer achieved a 47.0% increase in oil recovery compared with the waterflood case, while the XG 1000 ppm polymer achieved a 38.6% increase in oil recovery compared with the waterflood case. Testing with the motor oil being the displaced fluid, the viscosity ratio was 136 for the waterflood case, 18 for the polymer flood case with XG 1000 ppm polymer and 9 for the polymer flood case with XG 2500 ppm polymer. Findings also revealed that for the waterflood cases, the porous media exhibited oil-wet characteristics, while the polymer flood cases demonstrated water-wet characteristics. This paper provides theoretical support for the application of polymer to improve oil recovery by providing insights into the mechanism behind oil displacement. Graphic abstract Highlights The difference in shape of relative permeability curves are indicative of the effect of mobility control of each polymer concentration. The water-oil systems exhibited oil-wet characteristics, while the polymer-oil systems demonstrated water-wet characteristics. A large contrast in displacing and displaced fluid viscosities led to viscous fingering and early water breakthrough.

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