A Systematic Approach To The Relative Permeability Problem In Reservoir Simulation

1980 ◽  
Author(s):  
Nelson N. Molina
Keyword(s):  
Relative Permeability ◽  
Reservoir Simulation ◽  
Systematic Approach ◽  
Permeability Problem

Use of Transient Data To Calculate Absolute Permeability and Average Fluid Saturations

2010 ◽  
Vol 13 (02) ◽  
pp. 306-312 ◽  
Author(s):  
Medhat M. Kamal ◽  
Yan Pan
Keyword(s):  
Relative Permeability ◽  
Reservoir Simulation ◽  
Surface Flow ◽  
Absolute Permeability ◽  
Phase Flow ◽  
Simulation Studies ◽  
Flow Rates ◽  
Reservoir Performance ◽  
Transient Data ◽  
Relative Permeability Curves

Summary A new well-testing-analysis method is presented. The method allows for calculating the absolute permeability of the formation in the area influenced by the test and the average saturations in this area. Traditional pressure-transient-analysis methods have been developed and are completely adequate for single-phase flow in the reservoir. The proposed method is not intended for these conditions. The method applies to two-phase flow in the reservoir (oil and water or oil and gas). Future expansion to three-phase flow is possible. Current analysis methods yield only the effective permeability for the dominant flowing phase and the "total mobility" of all phases. The new method uses the surface-flow rates and fluid properties of the flowing phases and the same relative permeability relations used in characterizing the reservoir and predicting its future performance. The method has been verified by comparing the results from analyzing several synthetic tests that were produced by a numerical simulator with the input values. Use of the method with field data is also described. The new method could be applied wherever values of absolute permeability or fluid saturations are used in predicting well and reservoir performance. Probably, the major impact would be in reservoir simulation studies in which the need to transform welltesting permeability to simulator input values is eliminated and additional parameters (fluids saturations) become available to help history match the reservoir performance. This work will also help in predicting well flow rates and in situations in which absolute permeability changes with time (e.g., from compaction). Results showed that the values of absolute permeability in water/oil cases could be reproduced within 3% of the correct values and within 5% of the correct values in gas/oil cases. Errors in calculating the fluid saturations were even lower. One of the main advantages of this method is that the relative permeability curves used in calculating the absolute permeability and average saturations, and later on in numerical reservoir simulation studies, are the same, ensuring a consistent process. The proposed method does not address the question of which set of relative permeability curves should be used. This question should be answered by the engineer performing the reservoir engineering/simulation study. The proposed method mainly is meant to provide consistent results for predicting the reservoir performance using whatever relative permeability relations that are being used in the reservoir simulation model. The method does not induce any additional errors in determining the average saturation or absolute permeability over what may result from using these specific relative permeability curves in the reservoir simulation study. The impact of this study will be to expand the use of information already contained in transient data and surface flow rates of all phases. The results will provide engineers with additional parameters to improve and speed up history matching and the prediction of well and reservoir performances in just about all studies.

Lowering the phase-trap damage in tight-gas reservoirs by using interfacial tension (IFT) reducers

2013 ◽  
Vol 53 (1) ◽  
pp. 363
Author(s):  
Yangfan Lu ◽  
Hassan Bahrami ◽  
Mofazzal Hossain ◽  
Ahmad Jamili ◽  
Arshad Ahmed ◽  
...  
Keyword(s):  
Relative Permeability ◽  
Reservoir Simulation ◽  
Water Saturation ◽  
Tight Gas ◽  
Gas Reservoirs ◽  
Tight Gas Reservoirs ◽  
Water Based ◽  
Tight Formations ◽  
Tight Reservoirs ◽  
Relative Permeability Curves

Tight-gas reservoirs have low permeability and significant damage. When drilling the tight formations, wellbore liquid invades the formation and increases water saturation of the near wellbore area and significantly deceases permeability of this area. Because of the invasion, the permeability of the invasion zone near the wellbore in tight-gas formations significantly decreases. This damage is mainly controlled by wettability and capillary pressure (Pc). One of the methods to improve productivity of tight-gas reservoirs is to reduce IFT between formation gas and invaded water to remove phase trapping. The invasion of wellbore liquid into tight formations can damage permeability controlled by Pc and relative permeability curves. In the case of drilling by using a water-based mud, tight formations are sensitive to the invasion damage due to the high-critical water saturation and capillary pressures. Reducing the Pc is an effective way to increase the well productivity. Using the IFT reducers, Pc effect is reduced and trapped phase can be recovered; therefore, productivity of the TGS reservoirs can be increased significantly. This study focuses on reducing phase-trapping damage in tight reservoirs by using reservoir simulation to examine the methods, such use of IFT reducers in water-based-drilled tight formations that can reduce Pc effect. The Pc and relative permeability curves are corrected based on the reduced IFT; they are then input to the reservoir simulation model to quantitatively understand how IFT reducers can help improve productivity of tight reservoirs.

Rock Typing as an Effective Tool for Permeability and Water-Saturation Modeling: A Case Study in a Clastic Reservoir in the Oriente Basin

2007 ◽  
Vol 10 (06) ◽  
pp. 730-739 ◽  
Author(s):  
Genliang Guo ◽  
Marlon A. Diaz ◽  
Francisco Jose Paz ◽  
Joe Smalley ◽  
Eric A. Waninger
Keyword(s):  
Relative Permeability ◽  
Reservoir Simulation ◽  
Water Saturation ◽  
Rock Type ◽  
Permeability Model ◽  
Initial Water ◽  
Rock Types ◽  
Rock Typing ◽  
Relative Permeability Curves ◽  
Clastic Reservoirs

Summary In clastic reservoirs in the Oriente basin, South America, the rock-quality index (RQI) and flow-zone indicator (FZI) have proved to be effective techniques for rock-type classifications. It has long been recognized that excellent permeability/porosity relationships can be obtained once the conventional core data are grouped according to their rock types. Furthermore, it was also observed from this study that the capillary pressure curves, as well as the relative permeability curves, show close relationships with the defined rock types in the basin. These results lead us to believe that if the rock type is defined properly, then a realistic permeability model, a unique set of relative permeability curves, and a consistent J function can be developed for a given rock type. The primary purpose of this paper is to demonstrate the procedure for implementing this technique in our reservoir modeling. First, conventional core data were used to define the rock types for the cored intervals. The wireline log measurements at the cored depths were extracted, normalized, and subsequently analyzed together with the calculated rock types. A mathematical model was then built to predict the rock type in uncored intervals and in uncored wells. This allows the generation of a synthetic rock-type log for all wells with modern log suites. Geostatistical techniques can then be used to populate the rock type throughout a reservoir. After rock type and porosity are populated properly, the permeability can be estimated by use of the unique permeability/porosity relationship for a given rock type. The initial water saturation for a reservoir can be estimated subsequently by use of the corresponding rock-type, porosity, and permeability models as well as the rock-type-based J functions. We observed that a global permeability multiplier became unnecessary in our reservoir-simulation models when the permeability model is constructed with this technique. Consistent initial-water-saturation models (i.e., calculated and log-measured water saturations are in excellent agreement) can be obtained when the proper J function is used for a given rock type. As a result, the uncertainty associated with volumetric calculations is greatly reduced as a more accurate initial-water-saturation model is used. The true dynamic characteristics (i.e., the flow capacity) of the reservoir are captured in the reservoir-simulation model when a more reliable permeability model is used. Introduction Rock typing is a process of classifying reservoir rocks into distinct units, each of which was deposited under similar geological conditions and has undergone similar diagenetic alterations (Gunter et al. 1997). When properly classified, a given rock type is imprinted by a unique permeability/porosity relationship, capillary pressure profile (or J function), and set of relative permeability curves (Gunter et al. 1997; Hartmann and Farina 2004; Amaefule et al. 1993). As a result, when properly applied, rock typing can lead to the accurate estimation of formation permeability in uncored intervals and in uncored wells; reliable generation of initial-water-saturation profile; and subsequently, the consistent and realistic simulation of reservoir dynamic behavior and production performance. Of the various quantitative rock-typing techniques (Gunter et al. 1997; Hartmann and Farina 2004; Amaefule et al. 1993; Porras and Campos 2001; Jennings and Lucia 2001; Rincones et al. 2000; Soto et al. 2001) presented in the literature, two techniques (RQI/FZI and Winland's R35) appear to be used more widely than the others for clastic reservoirs (Gunter et al. 1997, Amaefule et al. 1993). In the RQI/FZI approach (Amaefule et al. 1993), rock types are classified with the following three equations: [equations]

Artificial-Intelligence Technology Predicts Relative Permeability of Giant Carbonate Reservoirs

2009 ◽  
Vol 12 (01) ◽  
pp. 96-103 ◽  
Author(s):  
Saud M. Al-Fattah ◽  
Hamad A. Al-Naim
Keyword(s):  
Experimental Data ◽  
Relative Permeability ◽  
Reservoir Simulation ◽  
Nonlinear Problems ◽  
Carbonate Reservoir ◽  
Carbonate Reservoirs ◽  
Porous Rocks ◽  
Data Set ◽  
Ann Models ◽  
Permeability Data

Summary Determination of relative permeability data is required for almost all calculations of fluid flow in petroleum reservoirs. Water/oil relative permeability data play important roles in characterizing the simultaneous two-phase flow in porous rocks and predicting the performance of immiscible displacement processes in oil reservoirs. They are used, among other applications, for determining fluid distributions and residual saturations, predicting future reservoir performance, and estimating ultimate recovery. Undoubtedly, these data are considered probably the most valuable information required in reservoir simulation studies. Estimates of relative permeability are generally obtained from laboratory experiments with reservoir core samples. In the absence of the laboratory measurement of relative permeability data, developing empirical correlations for obtaining accurate estimates of relative permeability data showed limited success, and proved difficult, especially for carbonate reservoir rocks. Artificial-neural-network (ANN) technology has proved successful and useful in solving complex structured and nonlinear problems. This paper presents a new modeling technology to predict accurately water/oil relative permeability using ANN. The ANN models of relative permeability were developed using experimental data from waterflood-core-tests samples collected from carbonate reservoirs of giant Saudi Arabian oil fields. Three groups of data sets were used for training, verification, and testing the ANN models. Analysis of results of the testing data set show excellent agreement with the experimental data of relative permeability. In addition, error analyses show that the ANN models developed in this study outperform all published correlations. The benefits of this work include meeting the increased demand for conducting special core analysis (SCAL), optimizing the number of laboratory measurements, integrating into reservoir simulation and reservoir management studies, and providing significant cost savings on extensive lab work and substantial required time.

Sign in / Sign up

Export Citation Format

Share Document