Capillary Pressure Curves Research Articles

Effect of Organosilane Structures on Mineral Surface Energy and Wettability.

The use of organosilanes has been shown to be an effective method for wettability alteration. This work explored for the first time how the structure of organosilanes impacts their ability to modify the wettability of different mineral surfaces, including pure quartz, pure calcite, sandstone, and limestone. Seven organosilanes were selected with different numbers of hydrolyzable groups, alkyl chain lengths, alkyl chain structures, and number of silicon atoms. Contact angle measurements, residual fluid saturations, and capillary pressure curves consistently showed that more hydrolyzable groups create more hydrophobic surfaces. As the number of carbon atoms increases in the silane alkyl chain, the hydrophobicity increases. The structure of the alkyl chain does not have an observable impact on the degree of wettability alteration. Finally, dipodal silanes with two silicon atoms create a much less hydrophobic surface than a single silicon atom silane. By understanding organosilane structure-property relationships with sandstone and limestone surfaces, it is possible to design tailored treatments for specific subsurface applications. Particularly in geosystems engineering, the results presented here can offer insights into enhanced oil recovery processes such as improving gas well deliverability and addressing injectivity issues during water-alternating-gas injection, as well as geological carbon sequestration processes such as improving storage capacity and caprock integrity.

Reservoir type classification and water yield prediction based on petrophysical conversion models

In the Chaixi region of the Qaidam Basin’s Qigequan tectonic zone, the compact sandstones are characterized by their low porosity and permeability, featuring intricate pore-throat formations, varied lithologies, assorted clay minerals, and pronounced unevenness among the reservoirs. There’s a weak link between reservoir metrics and logging reactions, making it challenging to assess these reservoir parameters. The microscopic pore structure of the reservoir can be illustrated through both the nuclear magnetic resonance relaxation time distribution and the capillary pressure curve. By using fractal dimensions to classify the reservoir, a conversion model between the transverse relaxation time in nuclear magnetic resonance logging and the capillary pressure in the mercury injection curve is established, enabling the conversion of pseudo-capillary pressure curves. Key elements of the pseudo-capillary pressure curve, specifically discharge and drive pressure, median pressure, and sorting coefficient, were analyzed and integrated with the generalized regression neural network for accurate reservoir type classification. An efficient categorization of reservoir types was accomplished by isolating three key elements from the pseudo capillary pressure curve—displacement pressure, median pressure, and sorting coefficient—and integrating them with the generalized regression neural network. Utilizing a rock physics framework, a correlation between transverse relaxation time of nuclear magnetic resonance and relative permeability conversion was formulated to accurately forecast the rate of water generation in the reservoirs of the western Qaidam Basin. The anticipated outcomes demonstrated a strong link with the real rate of water production. This technique presents an innovative method to forecast the comparative permeability of oil-water stages and the rates of water generation in compact sandstone reservoirs.

Study on Quantitative Characterization Method of Micro-Pore Structure of Carbonate Reservoir Based on Nuclear Magnetic Resonance Logging

Carbonate reservoirs have various types of reservoir spaces and complex pore structures, so the evaluation of microscopic pore structures is of great significance to favorable reservoir identification. In order to accurately characterize the micro-pore structure of carbonate reservoir, this paper uses the NMR experiment, high-pressure mercury injection, and NMR logging data to establish a conversion model between the NMR T2 spectrum and the capillary pressure curve by piecewise power function method. The nuclear magnetic T2 spectrum of the reservoir is mainly bimodal, with small pore T2 ranging from 0.1 to 6 ms, the peak value being about 2 ms, and the large pore throat T2 ranging from 100 to 6000 ms. The throat radius of small pores is 0.04–0.1 μm, the peak value is 0.08 μm, and the throat of large pores is 0.1–10 μm. The Bash layer has the smallest pore throat radius and median radius, higher median pressure, and poorer pore structure. By converting the T2 spectrum of nuclear magnetic logging into a pseudo-capillary pressure curve, the continuous and quantitative characterization of reservoir pore structure parameters was achieved vertically. The secondary method has important reference significance for the quantitative characterization of pore structure in reservoirs of the same type.

Pore Structure and Fractal Characteristics of the H Formation of the K Structure in the Eastern X Depression

To address the limited understanding of the pore structure in the H reservoir of the K structure in the eastern X depression, a fractal analysis method was employed to analyze the reservoir pores. Through the integration of experimental techniques, including casting thin sections, X-ray diffraction, and mercury intrusion, the study identified the reservoir's pore types, pore-throat distribution characteristics, and fractal properties. Additionally, it explored the relationships between fractal dimensions, reservoir physical properties, pore structure parameters, and mineral compositions.The results indicate that the pore types in the reservoir of the study area are primarily primary intergranular pores, intergranular dissolution pores, and intragranular dissolution pores. The reservoir's mineral composition is dominated by quartz and feldspar, with chlorite being the most abundant among clay minerals.Based on the morphology of capillary pressure curves, the reservoir pore structures are classified into four types: Type I, Type II, Type III, and Type IV. Their storage capacity and permeability decrease sequentially, while heterogeneity gradually increases.The reservoir pores exhibit multifractal characteristics, with the pore space divided into macropores (megapores and macropores), mesopores, and micropores (micropores and nanopores). The pore structure of macropores and mesopores is superior to that of micropores. The fractal dimension is unrelated to reservoir porosity but shows good correlations with permeability, pore structure parameters, and mineral composition.This study reveals the pore size distribution characteristics of the reservoir from the perspective of multifractal theory, providing a basis for the development of the H reservoir in the K structure of the X depression in the eastern region.

Enhanced numerical models for two-component fluid flow in multiscale porous structures

Multi-component fluid flow simulations in multiscale porous structures, many parts of which are likely to be under-resolved at practical resolution, often require a high-fidelity numerical model to account for the contribution of under-resolved structures to the fluid flow. In previous studies, a numerical model was proposed for viscous and capillary forces from under-resolved regions. It successfully showed comparable results in absolute permeability, capillary pressure, and relative permeability when compared to an equivalent fully resolved case up to ten times higher resolution. In this study, we show further extensions of the model to handle various types of structures and to capture detailed fluid behavior. First, we introduce the controllability of surface tension in the pseudo-potential lattice Boltzmann model while keeping the interface thickness and the spurious current at the same level. This helps to resolve more detailed interface dynamics in under-resolved regions. Second, we develop a numerical model to capture the residual fluid component in the under-resolved structure. Since it is difficult to capture such cell-sized or less-than-cell-sized fluid components with diffusive interface models, we try to consider them separately using local constitutive relations, such as the absolute and relative permeability and capillary pressure curves. Third, we introduce a tensorial resistivity model to handle under-resolved heterogeneous structures, such as a fiber bundle. After calculating the principal axis for resistivity using the Hessian and the gradient of the local porosity field, the tensorial resistivity is rotated in the proper direction. Through a series of benchmark test cases, including cases using practical rock geometries, these enhancements are validated and show significant accuracy improvements with respect to the transient interface dynamics, capture of local irreducible fluid components, and directionality effects of under-resolved structures.

On correct accounting of capillary forces when simulating oil displacement processes when flooding productive formations

The work is devoted to solving the problem of correctly determining capillary pressure functions during mathematical modeling of oil displacement processes during flooding of productive formations. It is shown that the use of these functions, determined in laboratory conditions using traditional methods using capillarimeters and high-speed centrifuges, when modeling processes of oil displacement from low-permeability productive reservoirs can lead to significant errors. The work notes that when conducting laboratory studies in rock samples, there is no formation of residual oil in a stationary form, while in real conditions of displacement of oil by water from productive formations, residual oil is formed in the rock, and in low-permeability formations the residual oil saturation can reach 50% or more of the pore volume. To obtain capillary pressure curves that more reliably reflect the real processes in productive formations during their flooding, it is proposed that when preparing rock samples for laboratory research, it is proposed to provide for the process of preliminary formation of residual oil saturation in these samples. This will make it possible to more reliably simulate the processes of oil displacement during waterflooding of productive formations in real conditions, especially when developing low-permeability oil and gas reservoirs.

Global Sensitivity Analysis of Relative Permeability and Capillary Pressure in Unsteady-State Core-Flooding Experiment

Numerical simulation stands as a pivotal method within the petroleum industry, enabling the prediction of fluid flow in porous media. Its primary goal lies in analyzing behavior and forecasting oil production through fluid injection. However, the necessity for numerous simulations, each encompassing diverse multidimensional and compositional characteristics, presents a challenge. This leads to a significant accumulation of physical information, exacerbating the computational demands on the numerical model, particularly in terms of computational cost. To address this challenge, one potential solution is to determine the essential input parameters required for accurate oil production prediction. Global sensitivity analysis emerges as a powerful tool for this purpose, aiming to identify which input parameters exert the most significant influence on the numerical model's response, thus optimizing computation time. Unlike traditional approaches that focus on sensitivity around a single operating point, this study adopts a holistic perspective, assessing sensitivity across the entire sample space of the inputs. Specifically, this research investigates the impact of changes in parameters related to relative permeability and capillary pressure curves within a plug during unsteady-state core-flooding experiments. The key metrics under scrutiny include water saturation profiles, pressure differentials, and cumulative oil production. Sobol indices, a method for quantifying global sensitivity, are employed to assess the contribution of each input parameter's variance to the outputs' variance. The mathematical framework employed here is based on the multiphase (water/oil) Darcy equation, incorporating capillarity effects in one-dimensional longitudinal flow, incompressible flow assumptions, and constant injection flow, commonly known as the Black Oil model. The model is solved utilizing an implicit finite difference methodology with time step control, with relative permeability and capillary pressure parameterized by the LET model. The outcomes of this analysis provide valuable insights, notably in reducing the number of estimable parameters in inverse problems on a global scale. This reduction significantly diminishes computing costs, offering greater flexibility in constructing surrogate models for future simulations.

Impact of Corner‐Bridge Flow on Capillary Pressure Curve: Insights From Microfluidic Experiments and Pore‐Network Modeling

AbstractThe capillary pressure curve is essential for predicting multiphase flow processes in geological systems. At low saturations, wetting films form and become important, but how wetting films control this curve remains inadequately understood. In this study, we combine microfluidic experiments with pore‐network modeling to investigate the impact of corner‐bridge flow on the capillary pressure curve in porous media. Using a CMOS camera and a confocal laser scanning microscopy, we directly observe the corner‐bridge flow under quasi‐static drainage displacement, revealing that corner‐bridge flow serves as an additional flow path to drain trapped water. Consequently, the capillary pressure curve shifts toward lower saturations, resulting in a reduced water residual saturation. We establish a theoretical criterion for the occurrence of corner‐bridge flow and develop a pore‐network model to simulate quasi‐static drainage, taking into account this additional flow path. Pore‐network modeling results agree well with our experimental observation. On this basis, we employ our pore‐network model to systematically analyze the impact of corner‐bridge flow on capillary pressure curve across varying porosity, pore‐scale disorder, and system size. Results indicate that the impact of corner‐bridge flow becomes more pronounced as porosity decreases and shape factor increases. Our findings demonstrate that the maximum decrease of water residual saturation is 0.19 when porosity is at its minimum, and the shape factor is at its maximum. This work bridges the gap between the pore‐scale mechanism and capillary pressure behavior and has significant implications for estimating the amount of extractable water and the CO2 storage capacity.

Controlling parameters of co-current and counter-current imbibition in naturally fractured reservoirs

Controlling parameters of co-current and counter-current imbibition in naturally fractured reservoirs

Thermodynamically consistent interfacial curvatures in real pore geometries: Implications for pore-scale modeling of two-phase displacement processes

Thermodynamically consistent interfacial curvatures in real pore geometries: Implications for pore-scale modeling of two-phase displacement processes

Prediction of Capillary Pressure Curves Based on Particle Size Using Machine Learning

Capillary pressure curves are usually obtained through mercury injection experiments, which are mainly used to characterize pore structures. However, mercury injection experiments have many limitations, such as operation danger, a long experiment period, and great damage to the sample. Therefore, researchers have tried to predict capillary pressure data based on NMR data, but NMR data are expensive and unstable to obtain. This study aims to accurately predict capillary pressure curves. Based on rock particle size data, various machine learning methods, such as traditional machine learning and artificial neural networks, are used to build prediction models and predict different types of capillary pressure curves, aiming at studying the best prediction algorithm. In addition, through adjusting the amount of particle size characteristic data, the best amount of particle size characteristic data is explored. The results show that three correlation coefficients of the four optimal algorithms can reach more than 0.92, and the best performance is obtained using the Levenberg–Marquardt method. The prediction performance of this algorithm is excellent, with the three correlation coefficients being all higher than 0.96 and the root mean square error being only 5.866. When partial particle size characteristics are selected, the training performance is gradually improved with an increase in the amount of feature data, but it is far less than the performance of using all the features. When the interpolation increases the particle size characteristics, the best performance is achieved when the feature data volume is 50 groups and the root mean square error is the smallest, but the Kendall correlation coefficient decreases. This study provides a new way to obtain capillary pressure data accurately.

Using the total chemical potential to generalize the capillary pressure concept and therefrom derive a governing equation for two-phase flow in porous media

Using the total chemical potential to generalize the capillary pressure concept and therefrom derive a governing equation for two-phase flow in porous media

Enhancing Oil Recovery in Eagle Ford Shale: A Multiscale Simulation Study of Surfactant Huff ’n’ Puff Methodology

Summary In this paper, we present a simulation case study of a surfactant huff ’n’ puff pilot in the black oil window of the Eagle Ford (EF) Shale. The target horizontal well, which had been depleted for nearly 8 years, underwent stimulation via a surfactant huff ’n’ puff treatment. The surfactant was selected through laboratory screening using reservoir rock and fluid samples. After a 17-hour injection and a 1-month shut-in period, the well’s production increased fivefold from the baseline oil rate, sustaining incremental oil production for at least 2 years. The surfactant enhances oil recovery by altering rock wettability toward a more water-wet state and moderating oil/water interfacial tension (IFT). This process is modeled by surfactant adsorption in the simulator, indicating the degree of dynamic changes in relative permeability (krl) and capillary pressure (Pc) curves. We propose a comprehensive workflow comprising three stages: development of core-scale and field-scale models, sequential model calibrations, and multiobjective optimization to integrate laboratory measurements and field data from this pilot into multiscale numerical simulations. By matching oil recoveries from imbibition experiments on the core model and field production histories on the field model, krl and Pc profiles of two extreme states, basic reservoir properties, and additional reservoir properties altered during huff ’n’ puff operations are characterized. The matched core model reproduces a 15.1% incremental oil recovery for surfactant-assisted spontaneous imbibition (SASI) process relative to pure brine imbibition process. The matched reservoir model predicts the surfactant huff ’n’ puff treatment increases the oil production by 21.9% relative to water huff ’n’ puff treatment and by 52.9% relative to primary depletion for a 4-year period. The calibrated reservoir model also serves as a base case for optimizing well operation schedules through the implementation of a multiobjective genetic algorithm. The surfactant injection rate, injection time, and well shut-in time of the base case are varied to achieve higher oil production and reduced surfactant usage. Statistical analysis of eight trade-off cases indicates that optimal well operations, compared with existing practices, frequently involve increased injection rates [16.6–18.9 barrels per minute (bpm)], shorter injection periods (10–11.3 hours), and prolonged shut-indurations (49–65 days). This workflow offers valuable insights into surfactant huff ’n’ puff treatments for unconventional reservoirs, thereby facilitating the optimization of well operations and maximizing tertiary oil recovery.

A New model of gas-water two-phase seepage based on Newton's law of motion

A New model of gas-water two-phase seepage based on Newton's law of motion

Modified Low-Field NMR Method for Improved Pore Space Analysis in Tight Fe-Bearing Siliciclastic and Extrusive Rocks

Abstract Understanding the filtration and storage properties of tight reservoirs is crucial for efficient resource exploitation, particularly in unconventional formations. This study presents two low-field nuclear magnetic resonance (LF-NMR) techniques: standard cut-off and modified differential approaches combined with mercury injection capillary pressure (MICP) and X-ray diffraction (XRD) studies to evaluate porosity and pore size distribution (PSD) in such formations. The differential technique involves subtracting the dry sample signal from a 100% water-saturated one, allowing the chemically bound water compound to be eliminated and facilitating PSD analysis. Through the application of the percolation theory, we established a power–law relationship between LF-NMR transverse relaxation time (T2) and MICP pore-throat diameter, enabling the derivation of PSD and pseudo capillary pressure curves. Our methodology was validated on a sample set representing tight sandstones, conglomerates, and extrusive rocks with high clay and iron mineral content, demonstrating the superior accuracy of the modified differential method in estimating effective porosity and absolute PSD in comparison with the standard approach. While the use of the percolation theory in PSD conversion was successful for rocks with unimodal distributions, it often failed for rocks with larger voids. The study also revealed that the relationship between the LF-NMR transverse relaxation times and MICP pore sizes is both nonlinear and challenging to describe with a universal equation, especially in the presence of para- and ferro-magnetic elements in the rock matrix. Despite obstacles to the complete elimination of the influence of these minerals on the T2 distribution, employing the modified differential LF-NMR method significantly mitigated this effect and offered a precise and noninvasive way of characterizing the petrophysical properties of tight reservoir rocks. Consequently, our studies offer a significant step toward a more precise assessment of pore structures in unconventional reservoirs that could be translated into more efficient strategies for locating geothermal heat and hydrocarbon resources.

(Digital Presentation) Multiscale Modeling of Two-Phase Transport in the Membrane Electrode Assembly of Polymer Electrolyte Membrane Fuel Cells: Effect of Relative Humidity and Temperature

Water management plays an important role in the performance and durability of polymer electrolyte membrane fuel cells (PEMFCs). Achieving enhanced water removal at high current density without membrane dehydration requires an optimal design of the membrane electrode assembly (MEA) and MEA-channel interaction depending on operating conditions. The analysis of two-phase transport is challenged by the wide range of pore sizes found in porous layer assemblies, varying from 1-100 nm in the catalyst layer (CL), 50-1000 nm in the microporous layer (MPL) and 10 µm in the gas diffusion layer (GDL), up to the millimeter-sized channel. In this work, a hybrid multiscale model is presented to describe two-phase transport and performance of a representative unit cell as a function of relative humidity (RH) and temperature [1-3]. A control volume (CV) decomposition is used to represent the multiscale pore space of the GDL, MPL and CL in terms of local effective transport properties (porosity, effective diffusivity, permeability, thermal/electrical conductivity and entry capillary pressure) [4]. The model incorporates a macroscopic continuum formulation for gas flow and species, energy, liquid-phase pressure, water dissolved in ionomer, and electronic and ionic potentials [5]. Liquid water transport is modeled by means of a multi-cluster invasion-percolation algorithm, which is coupled to the macroscopic continuum formulation by the phase-change source term of water (evaporation/condensation). Water clusters with a net condensation rate grow by invading the adjacent dry CV with the lowest entry capillary pressure, while clusters with a net evaporation rate shrink by drying the wet CV of the cluster with the lowest entry capillary pressure. An all-or-nothing invasion law is adopted for saturation in the GDL (one pore per CV), while a macroscopic description in terms of capillary pressure curve at the representative elementary volume scale (REV) is used for the MPL and the GDL (thousands to millions of pores per CV). An example of the saturation distribution in the cathode MEA is shown in Figure 1. Local saturation remains between 0.1-0.4 in REVs of the CL and the MPL, increasing up to 1 in macropores of the GDL. Water condenses preferentially under the ribs and transport by capillary action to the GDL/channel interface, where the water flow is released to the channel. The channel saturation remains low, around 0.1, due to the large gas flow velocity used in the differential cell.[1] P.A. García-Salaberri, Modeling diffusion and convection in thin porous transport layers using a composite continuum-network model: Application to gas diffusion layers in polymer electrolyte fuel cells, 167 (2021) 120824.[2] D. Zapardiel, P.A. García-Salaberri, Modeling the interplay between water capillary transport and species diffusion in gas diffusion layers of proton exchange fuel cells using a hybrid computational fluid dynamics formulation, J. Power Sources 520 (2022) 230735.[3] P.A. García-Salaberri, Effect of thickness and outlet area fraction of macroporous gas diffusion layers on oxygen transport resistance in water injection simulations, Transp. Porous Media 145 (2022) 413-440.[4] P.A. García-Salaberri, I.V. Zenyuk, A General-Purpose Tool for Modeling Multifunctional Thin Porous Media (POREnet): From Pore Network To Effective Property Tensors, Heliyon (2023), submitted.[5] P.A. García-Salaberri, A. Sánchez-Ramos, A numerical analysis of the effect of layer-scale and microscopic parameters of membrane electrode assembly in proton exchange fuel cells under two-phase conditions, J. Power Sources (2023), accepted. Figure 1. Saturation distribution in the cathode MEA of a PEMFC operated at 70 oC and RH=0.95 at high stoichiometric conditions. The current density is I=0.5 A cm-2.- Figure 1

Experimental investigation of capillary pressure diagram in oil/water transition zone of low-permeability reservoirs

The oil/water transition zone, particularly pronounced in low-permeability formations with small pore diameters and high capillary pressure, contains a substantial portion of original oil in place. The capillary pressure curves provide essential data for the calculation of the original oil in place as well as the oilfield development simulation. However, the traditional single capillary pressure curve cannot provide enough information. To address this challenge, an experimental investigation was conducted to explore the capillary pressure diagrams within the oil/water transition zone of low-permeability reservoirs. The results shed light on the complex behavior of capillary pressure, the influence of initial water saturation, and the relationship between initial oil saturation and residual oil saturation. Incorporating the behavior of capillary pressure into reservoir simulation models can enhance reservoir characterization and improve the accuracy of oil production performance in low-permeability reservoirs.

Correlating Capillary Pressure and Resistivity Index for Carbonate Reservoir

Capillary pressure is a significant parameter in characterizing and modeling petroleum reservoirs. However, costly laboratory measurements may not be sufficiently available in some cases. The problem amplifies for carbonate reservoirs because relatively enormous capillary pressure curves are required for reservoir study due to heterogeneity. In this work, the laboratory measurements of capillary pressure and formation resistivity index were correlated as both parameters are functions of saturation. Forty-one core samples from an Iraqi carbonate reservoir were used to develop the correlation according to the hydraulic flow units concept. Flow zone indicator (FZI) and Pore Geometry and Structure (PGS) approaches were used to identify the reservoir hydraulic flow units. The experimentally derived correlations can be used to predict capillary pressure from resistivity, which is widely available from welllogs. FZI and PGS rock typing methods were applied to characterize the reservoir rock types. For both methods, the log-log plot of Leverett J-function and capillary pressure versus resistivity index for each rock type represent a power-law model relationship between these parameters. Despite the good permeability-porosity prediction results, the FZI approach did not yield a good correlation between J and I. PGS resulted in a better performance in terms of both permeability-porosity prediction and Pc with I correlation because PGS honors the pore geometry and structure relationship with the mean hydraulic radius more than FZI. This work introduces a new correlating approach that aims to assist in reservoir characterization and simulation.

Classification of rock types of porous limestone reservoirs: case study of the A oilfield

Rock types with similar lithological components and pore structures form the basic units of porous limestone reservoirs; this influences the reservoir evaluation efficiency and water injection development. As the main oil and gas pay zone in central Iraq, the Cretaceous Khasib Formation reservoirs are influenced by deposition, dissolution, and cementation. There is strong vertical heterogeneity in the most important zone of the Kh2 layer, with diverse rock types and complex pore structures. Based on core observation and casting thin-section identification, the Kh2 layer in the study area was divided into eight lithofacies types as argillaceous bioclastic wackestone, planktic foraminiferium wackestone, lamellar bioclastic wackestone, intraclastic–bioclastic packstone, patchy green algae packstone, green algae and pelletoid packstone, benthic foraminiferium–bioclastic packstone, and intraclastic grainstone. Along with the reservoir void space types of the lithofacies, capillary pressure curves are used to quantitatively analyze the throat and pore features of the different lithofacies. From the porosity–permeability cross-plot characteristics and distribution of pore types, 14 petrophysical facies are obtained. Finally, based on the differences between the lithofacies and petrophysical facies, the Kh2 member is divided into 13 rock types with different geological origins and petrophysical characteristics. Among these, the rock type RT1-8-14 has the best and rock type RT1-1-1 has the worst physical properties among the reservoir rock types. This study provides an optimization method for carbonate reservoir evaluation and is expected to be beneficial for efficient development of similar carbonate reservoirs.

On the question of comparability of relative phase permeabilities obtained by different methods

The article discusses four methods for obtaining functions of relative phase permeability (RPP): 1) approximation of point laboratory data by known correlations of Corey and LET; 2) calculation of RPP by capillary pressure curves using Burdine, Cory and Cory–Brooks models; 3) calculation of RPP by field data; 4) modification of RPP when setting up a hydrodynamic model. A new method is proposed for obtaining RPP based on field data. In this method, it is assumed that the values of the Buckley–Leverett function are equivalent to the values of the well water-cut, and the water saturation can be determined by the formula linking the accumulated oil production and the initial geological oil reserves. The methods of obtaining RPP have been tested on the example of two real objects. The results of the approbation showed that all pairs of RPPs differ markedly from each other, while different trends take place for the objects considered. The article provides an explanation of the possible reasons for the difference in the RPP. At the same time, it was found that the scale factor is not the most significant. The expediency of the conducted research is due to the need to study the level of correspondence between the functions of the RPP obtained by different methods. This will allow for a more reasoned justification of the functions of the RPP when creating and adapting a hydrodynamic model of an oil deposit.