Predicting Physical Properties of Reservoir Rocks from the Microstructural Analysis of Petrographic Thin Sections (original) (raw)
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Petrophysical properties of porous medium from Petrographic Image Analysis data
Colloids and Surfaces A: Physicochemical and Engineering Aspects, 2001
Petrographic Image Analysis (PIA) is a well-established rapid two-dimensional (2D) method to quantify pore and solid space in reservoirs and different porous materials. This paper aims to describe a method of characterization and quantification of petrophysical properties in carbonate pore systems using Petrographic Image Analysis over more than three orders of magnitude, from a submicron to a millimeter scale. We integrated two kinds of multiscaled digital image: the transmitted-light-colored petrographic images which allowed us to characterize the macroporosity; the Back-Scattered Electrons (BSE) grey level images which gave us information about microporosity. This technique enabled us to measure different classical petrophysical properties such as pore area, specific surface area, average pore diameter, distribution of pore size, pore shape factor, macroporosity and microporosity. We used image parameters in order to obtain the model of capillary pressure curve versus saturation (P c-S). On the other hand, using empirical equations of permeability derived from Carman-Kozeny expression and a bundle of capillary tubes model, we were able to calculate the permeability of carbonate pore systems from different image parameters. The same petrophysical parameters were directly measured on core through classical three-dimensional petrophysical techniques (3D), such as Hg-injection porosimetry, permeametry and the BET technique. Finally, we compared the values different petrophysical properties of carbonate pore systems, obtained from 2D image analysis (PIA) and 3D classical petrophysical techniques.
Journal of Chemical and Petroleum Engineering, 2023
Digital rock technology has emerged as a powerful tool for analyzing reservoir rocks in the petroleum industry. Technically, Digital Rock Physics (DRP) is an effective method for determining reservoir rock properties. The article reviews the history of digital rock, from its origins in the study of porous media to its development into a practical tool for the petroleum industry. The features of digital rock are discussed, including the use of X-ray microcomputed tomography and pore-scale modeling, which allow for the analysis of rock samples at the pore-scale. The philosophy and science behind digital rock are explored, emphasizing the importance of understanding the fundamental physics of fluid flow in porous media. The applications of digital rock in the petroleum industry are discussed, including its use in reservoir characterization, fluid flow simulation, and enhanced oil recovery. The benefits and limitations of digital rock are examined, highlighting the need for careful interpretation of results and the importance of complementary laboratory techniques. The role of pore network modeling in digital rock technology is also discussed, which allows for the simulation of fluid flow in porous media at the pore-scale. Finally, the article discusses future directions for digital rock, including the development of new imaging and modeling techniques and the integration of digital rock with other data sources. Overall, digital rock technology, including pore network modeling, is a promising tool for the petroleum industry that has the potential to improve
Prediction of Permeability from the Skeleton of Three-Dimensional Pore Structure
SPE Reservoir Evaluation & Engineering, 1999
Summary The main purpose of the present work is to predict the permeability of a porous medium from its three-dimensional (3D) porous structure network. In this work, 3D porous structure is reconstructed by the truncated Gaussian method using Fourier transform and starting from a 2D binary image obtained from a thin section of a porous sample. The skeleton of the 3D porous structure provides a way of visualizing the graph of the pore network. It is determined using a thinning algorithm, which is conceived to preserve topology. It gives both visual and quantitative information about the connectivity of the pore space, the coordination number for every node and local hydraulic radius. Once the network of the pore structure is obtained, the macroscopic transport properties, such as the permeability, can be predicted. The method is applied to a 500 mD Berea sandstone and the predicted permeability is in good agreement with the experimental value and empirical correlations.
SPE 145751 Application of Real Rock Pore-throat Statistics to a Regular Pore Network Model
This work reports the application of real rock statistical data to a previously developed regular pore network model in an attempt to produce an accurate simulation tool with low computational overhead. A core plug from the St. Peter Sandstone formation in Indiana was scanned with a high resolution micro CT scanner. The pore-throat statistics of the three-dimensional reconstructed rock were extracted and the distribution of the pore-throat sizes was applied to the regular pore network model. In order to keep the equivalent model regular, only the throat area or the throat radius was varied. Ten realizations of randomly distributed throat sizes were generated to simulate the drainage process and relative permeability was calculated and compared with the experimentally determined values of the original rock sample. The numerical and experimental procedures are explained in detail and the performance of the model in relation to the experimental data is discussed and analyzed. Petrophysical properties such as relative permeability are important in many applied fields such as production of petroleum fluids, enhanced oil recovery, carbon dioxide sequestration, ground water flow, etc. Relative permeability data are used for a wide range of conventional reservoir engineering calculations and in numerical reservoir simulation. Two-phase oil water relative permeability data are generated on the same core plug from both pore network model and experimental procedure. The shape and size of the relative permeability curves were compared and analyzed and good match has been observed for wetting phase relative permeability but for non-wetting phase, simulation results were found to be deviated from the experimental ones. Efforts to determine petrophysical properties of rocks using numerical techniques are to eliminate the necessity of regular core analysis, which can be time consuming and expensive. So a numerical technique is expected to be fast and to produce reliable results. In applied engineering, sometimes quick result with reasonable accuracy is acceptable than the more time consuming results. Present work is an effort to check the accuracy and validity of a previously developed pore network model for obtaining important petrophysical properties of rocks based on cutting-sized sample data
FOR CITATIONS: SALEM, H.S., 2000. Fluid-flow characterization of porous media (for the example of the Jeanne d'Arc Basin consolidated reservoirs). Energy Sources. 22(6), July: 557-572. ABSTRACT: Flow of fluids in porous media is a complicated process governed by several physical parameters and properties of the solid particles and fluid molecules, as well as the interactions between them. The Kozeny-Carman equation is one of the powerful equations that provides a better understanding of fluid flow. The equation can be successfully applied to viscous flow and laminar flow through unconsolidated and consolidated porous media if some of its elements are known. One of these elements is the Kozeny-Carman coefficient (Kcc ), which has a specific influence on the mechanism of fluid flow in porous media. In this study, Kcc , along with other cc parameters, was obtained numerically from well-log measurements for several wells penetrating the Canadian offshore Jeanne d’Arc Basin reservoirs, which consist of consolidated and heterogeneous rocks characterized by a complex network of pores and pore channels. It is shown that Kcc is not a constant but a variable depending on several physical parameters and lithological attributes and strongly related to fluid flow as well as to electric-current conduction in porous media. The Kozeny-Carman coefficient, obtained as tortuosity (t ) times shape factor (Shf ) agrees well with that obtained as (t) times Archie cementation factor (m). This observation suggests that Shf and m are analogous to each other. An average value of 7.5 was obtained for Kcc , which can be used for similar media instead of the value of 5.0 that is inaccurately used for consolidated porous media. Also, an average value of 3.3 was obtained for (t) and an average value of 2.28 was obtained for Shf (analogous to m). Empirical equations linking Kcc and a variety of petrophysical parameters were also obtained."
Porosity and porevolume prediction in a gas storage reservoir
EAGE 63rd Conference & Technical Exhibition — Amsterdam, 2001
The aim of any reservoir characterization study is to describe the properties of the reservoir in the appropriate detail. The result is a prediction model of the physical and geological properties of the subsurface. To reach this goal we must integrate spatially distributed seismic data measured in two way time and local informations from wells measured in units of depth. To handle these data of different character and scale a neural network training approach was selected to provide various attribute maps without well (unsupervised) and with well control (supervised) finally leading to volumes of distributed properties as lithology, porosity and porevolumes. The procedure of distributing well properties to 3D space, called volume transformation, can be repeated for newly acquired or modeled 3D seismic data such leading to a tool for monitoring or predicting the properties of the reservoir. In this study we use a 3D seismic volume with an interpreted horizon and 12 wells located in the area with the following logs: sonic, density, porosity and lithofacies. The paper describes a case study of quantitative interpretation using modelled log and seismic data in order to simulate and predict the responses of a gas storage reservoir in the Paris Basin.
2013
Petrophysical flow unit concept can be used to resolve some of the key challenge faced in characterization of hydrocarbon reservoir. The aim of this study, after evaluation of porosity and permeability, these flow unit types were used to reveal that one key to understand the relationship between porosity and permeability and so predict the performance of reservoir in spite of the present lithology type by represent them as combinations of different flow units, each with uniform pore throat size distribution and similar performance. Also Winland's approach of using multiple regression analysis to develop an empirical equation for calculating pore throat that corresponds to the 35 percentile was examined. In this study, the relationships between porosity and permeability of certain pore throat flow unit types were established on a data base of sandstone and limestone samples from 21 different stratigraphic units, which range in age between Cretaceous and Pliocene. These formations...
2004
Five relevant digital image analysis parameters for fluid flow are obtained from 2-D image analysis of carbonate rocks: 2-D image porosity, amount of pores, pore shape, total perimeter per area and dominant pore size range. Micro-porosity leads to low permeable, highly porous rocks. 2-D image porosity represents the macro-porosity because the resolution subtracts the small pores from the porosity. Compared to the total porosity, it improves the prediction of permeability by an order of magnitude in the high porosity range. Pore shape factor γ reduces the uncertainty in permeability prediction to 2 orders of magnitude. Pore shape factor analysis is restricted to samples with more than 4000 pores/cm 2 . CT scans of plugs reveals that the pore shape factor γ is a relatively constant measure of the pore shape (+/-0.2) throughout the sample plug. The larger the average pore size, the higher the velocity at a given porosity. The average pore size can be quantified by the upper limit of the dominant pore size range.
2015
Various techniques have been developed over the years for characterizing pore structure beyond a simple visual description. These tests provide qualitative data for both reservoir evaluations in the short run and reservoir simulation in the long run. In this study, mercury porosimetry (MP), low field (2MHz) nuclear magnetic resonance (NMR) relaxometry, centrifuge drainage tests and flow tests were run on 11 plugs of a mix of sandstones, limestones, dolomites and chalk. Initially, a representative elemental volume (REV) which uses pore size distribution (PSD) data and porosity to simulate the pore network is discussed. The model is later used to predict permeability and predictions were compared with gas flow measurements. NMR and centrifuge data are coupled to derive capillary pressure curves and the results are compared with MP derived capillary curves. The results indicate that there is significant difference between the two capillary curves based on the degree of heterogeneity of...
Transport in Porous Media, 2012
We present results from a systematic study of relative permeability functions derived from two-phase lattice Boltzmann (LB) simulations on X-ray microtomography pore space images of Bentheimer and Berea sandstone. The simulations mimic both unsteadyand steady-state experiments for measuring relative permeability. For steady-state flow, we reproduce drainage and imbibition relative permeability curves that are in good agreement with available experimental steady-state data. Relative permeabilities from unsteady-state displacements are derived by explicit calculations using the Johnson, Bossler and Naumann method with input from simulated production and pressure profiles. We find that the nonwetting phase relative permeability for drainage is over-predicted compared to the steady-state data. This is due to transient dynamic effects causing viscous instabilities. Thus, the calculated unsteady-state relative permeabilities for the drainage is fundamentally different from the steady-state situation where transient effects have vanished. These effects have a larger impact on the invading nonwetting fluid than the defending wetting fluid. Unsteady-state imbibition relative permeabilities are comparable to the steady-state ones. However, the appearance of a piston-like front disguises most of the displacement and data can only be determined for a restricted range of saturations. Relative permeabilities derived from unsteady-state displacements exhibit clear rate effects, and residual saturations depend strongly on the capillary number. We conclude that the LB method can provide a versatile tool to compute multiphase flow properties from pore space images and to explore the effects of imposed flow and fluid conditions on these properties. Also, dynamic effects are properly captured by the method, giving the opportunity to examine differences between steady and unsteady-state setups.