Permeability Curves Research Articles

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.

Water and Oil Volume Measurement Using UV–Visible Spectroscopy

Fluid saturation in relative permeability experiments is typically determined by volumetric or gravimetric measurements, as well as in-situ saturation monitoring (ISSM). Gravimetric measurements tend to have larger error due to grain loss. The conventional volumetric method used can be a challenge because produced volumes for oil and water must be separated and measured manually. ISSM method is also a costly technique. In this study, an UV–visible spectroscopy was used to continuously and cost effectively measure oil and water volumes. A water-oil unsteady state relative permeability was performed to investigate the feasibility of calculating oil and water volumes using UV–visible spectroscopy. UV–visible spectroscopy is a quantitative technique in analytical chemistry to determine concentrations of known solutes. A UV–visible spectroscope was located in the flow line immediately after the core holder and used to quantify fluid volumes (oil and water) produced from a core sample during unsteady state relative permeability study. A volumetric separator was also used to compare production volumes obtained from UV–visible spectroscope. The relative permeabilities were calculated using JBN method from both volumetric and UV-visible spectroscope measurements and then history matched with Sendra (PRORES AS). The final oil volume produced, oil and water relative permeability curves obtained from UV–visible spectroscope measurements were in good agreement with volumetric measurements. The Corey relative permeability curves simulated from Sendra also were closely matched with analytical relative permeability curves obtained using volume measurements from volumetric and UV–visible spectroscope data. Nuclear Magnetic Resonance (NMR) on post relative permeability experiment was also in good agreement with UV–visible spectroscope measurement. UV–visible spectroscopy was also used to measure the breakthrough time of the injected fluid. Breakthrough time estimated using in-line UV–visible spectrophotometer was 0.634 PVI compared to 0.617 and 0.673 PVI from pressure data and volumetric observations.Graphic

A Novel Simulation Model of Shielding Performance Based on the Anisotropic Magnetic Property of Magnetic Shields.

To achieve a near-zero magnetic field environment, the use of permalloy sheets with high-performance magnetic properties is essential. However, mainstream welding processes for magnetically shielded rooms (MSRs), such as argon arc welding and laser welding, can degrade the magnetic properties of the material. Additionally, neglecting the anisotropy of permalloy sheets can introduce unpredictable errors in the evaluation of MSR performance. To address this issue, this paper proposes a modified model for calculating the shielding factor (SF) of MSRs that incorporates the anisotropic magnetic characteristics of permalloy sheets. These characteristics were measured using a two-dimensional single sheet tester (2D-SST). A high-precision measurement system was developed, comprising a 2D-SST (to generate two-dimensional magnetic fields and sense the induced B and H signals) and a control system (to apply in-phase 2D excitation signals and amplify, filter, and record the B and H data). Hysteresis loops were tested at low frequencies (0.1-9 Hz) and under different magnetization states (0.1-0.6 T) in two orientations-parallel and perpendicular to the annealing magnetic field-to verify anisotropy under varying conditions. Initial permeability, near-saturation magnetization, and basic magnetization curves (BM curves) were measured across different directions to provide parameters for simulations and theoretical calculations. Based on these measurements and finite element simulations, a mathematical model was developed to adjust the empirical coefficient λ used in theoretical SF calculations. The results revealed that the ratio of empirical coefficients in different directions is inversely proportional to the ratio of magnetic permeability in the corresponding directions. A verification group was established to compare the original model and the modified model. The mean squared error (MSE) between the original model and the finite element simulation was 49.97, while the MSE between the improved model and the finite element simulation was reduced to 0.13. This indicates a substantial improvement in the computational accuracy of the modified model.

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.

Assessment of the uncertainties' impact of relative permeability curves on mature field oil production: a case study in unisim-i-h

Relative permeability is a crucial parameter in reservoir characterization as it directly influences the behavior of the rock-fluid system and, consequently, oil production. However, estimating this parameter is difficult due to uncertainties that can originate from various sources, such as geological, parametrical modelling, computational, and so on. If not properly examined, these uncertainties might undermine prediction accuracy and impair final production. Over time, several correlations were created to estimate relative permeability better. Although no parametrical correlation can adequately predict the exact shape of the curve, most of them reasonably approximate it within specific uncertainty limits. For mature oil fields, a novel kind of industry for Brazil, the research of relative permeability and associated uncertainties is still in its early stages. The main objective of this study is to numerically investigate the effects of uncertainties on relative permeability curves via software CMG® and the geological model UNISIM-I-H developed by UNICAMP. The LET correlation was used to estimate the relative permeability curves. Initially, a base case known as UNISIM-I-H was simulated, upon which the remaining analyses were built. This case consisted of a 15-year production phase followed by a 5-year production pause, a 10-year production restart, the abandonment of the three less productive wells and the drilling of the three new wells to represent a mature oil field better. Four cases were created with relative permeability parameter uncertainties increased by 5%, 10%, 15%, and 20%. The effects of these uncertainties on the relative permeability curve, production curve, net product value, and recovery factor were then examined. The data analysis revealed that these uncertainties mostly affect the forecasts relating to net product value, reservoir recovery factor, and cumulative production, with the latter being the most impacted. Every uncertainty case increased the maximum and minimum values of the curves. Compared to the base case, an intriguing pattern also showed up, where the maximum increased much more quickly than the minimum, suggesting that the risk of estimating the values for each curve above the actual is significantly higher with increasing uncertainty than the opposite.

Machine learning-based nuclear magnetic resonance measurements of hydraulic properties in hydrate-bearing sediments

Permeability and water retention curves of hydrate-bearing sediments play pivotal roles in comprehending the dynamics of fluids within geologic hydrate systems and have direct impacts on gas production efficiency. Previous investigations into these hydraulic properties have been constrained to cursory field estimates or laboratory assessments of localized small samples. This hinders high-fidelity numerical simulations with regard to the evolution of widely distributed gas hydrate in subsurface and the evaluation of its potential as an energy resource. This study represents the inaugural comprehensive compilation of permeability data measured in global hydrate survey areas, aiming to develop a data-driven characterization of hydraulic properties from nuclear magnetic resonance (NMR) measurements. Interpretable machine learning substantially improves the conventional Schlumberger-Doll Research (SDR) equation, establishing correlations with clay content, porosity, formation factor, and hydrate saturation to accommodate diverse lithologies across regions. By combining Kozeny's theory on the nature of the pore system with the data-driven SDR equation, NMR data can be used to efficiently furnish precise and reliable assessments of permeability and water retention curves for hydrate-bearing sediments, prior to extensive specialized core measurements. The results show that our model achieves an overall predictive accuracy for permeability of R2 = 0.924 and MAE = 0.319 across typical hydrate occurrence zones, with 97.6% of samples displaying absolute errors within one order of magnitude.

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

Naturally fractured formations are complex petroleum reservoirs that are poor candidates for waterflooding due to difficulties in controlling sweep. Injected water can readily propagate through the fracture system, bypassing the hydrocarbon stored in the matrix. Instead, such systems rely on spontaneous imbibition (SI) from the matrix into the extensive fracture gathering system. SI is a crucial recovery mechanism that relies on capillary pressure-dominated fluid movement. SI can occur through two modes, co-current (COSI) and counter-current (COUSI), depending on the relative direction of fluid movement in response to prevailing boundary conditions. Analytical solutions that incorporate the diffusivity coefficient, which combines relative permeability and capillary pressure curves, are used to describe co-current and counter-current imbibition mechanisms. The perturbation method is one approach in solving these analytical equations. In-situ water saturation profiles, ascertained through experimental CT scanning, serve as validation benchmarks for both co-current and counter-current models. The understanding of the SI process can give more details about the fracture-matrix interactions and the exchange function. Sensitivity studies with respect to the parameterization of the driving force for imbibition, capillary pressure, and the resistive forces, captured in relative permeability curves, can guide experimental study planning and aid in inverse problem analysis in the characterization of naturally fractured reservoirs. The results of a parametric study show that capillary pressure curve parameters, such as capillary entry pressure and capillary exponent, significantly affect the position of the waterfront which indicates the imbibition rate. In addition, the water relative permeability exponent has greater impact on both shape and position of water profile than other relative permeability parameters. The nonwetting phase parameters, like oil endpoint relative permeability and oil exponent, have the least influence on water saturation profile.

Hydrogen, Methane, Brine Flow Behavior, and Saturation in Sandstone Cores During H2 and CH4 Injection and Displacement

Large-scale underground hydrogen storage (UHS) is a critical component in the emerging hydrogen economy. Knowledge of multiphase flow behavior involving hydrogen in storage reservoir formations is crucial to characterizing hydrogen transport properties and essential for the deliverability and storage operations of UHS. There are still many gaps in fully understanding hydrogen–methane–brine multiphase phase flow that require further investigation. In this work, H2 and CH4 were injected through brine-saturated sandstone cores using a tri-axial core holder system fitted with flow rate meters and pressure transducers, while the effluent gas concentrations were analyzed using an online micro gas chromatograph. Brine displacement, permeability, and gas breakthrough curves were measured. We studied the flow behavior of hydrogen and methane in sandstone cores through testing brine displacement by gas injection and comparing the hydrogen displacement of methane with the methane displacement of hydrogen. We also tested the differences between horizontal and vertical flow in brine displacement. The results showed that brine displacement was more efficient in a core with higher permeability and porosity, resulting in a higher initial gas saturation. A higher gas injection rate brought about faster gas breakthrough measured by pore volume and sharper concentration curves. Hydrogen did not exhibit abnormal flow in the sandstone when the flow was horizontal and downward vertical. Gas overriding was observed in brine displacements when the flow was horizontal, with hydrogen showing this behavior more profoundly compared to methane. Downward vertical gas injection induced higher efficiency brine displacement compared to horizontal displacement and resulted in a higher initial gas saturation in the sandstone cores. These findings address critical knowledge gaps regarding gas flow patterns and displacement behaviors during hydrogen injection and recovery phases in UHS facilities using methane as the cushion gas. The insights from this research offer valuable guidance for optimizing UHS systems, ensuring operational efficiency, and advancing sustainable energy solutions in alignment with decarbonization goals.

Retrograde Condensation in Gas Reservoirs from Microporous to Field-Scale Simulation

Hydrocarbon fields that contain non-associated gas, such as gas condensate, are highly valuable in terms of production. They yield significant amounts of condensate alongside the gas, but their unique behavior presents challenges. These reservoirs experience constant changes in composition and phases during production, which can lead to condensate blockage near wells. This blockage forms condensate bridges that hinder flow and potentially decrease gas production. To address these challenges, engineers rely on numerical simulation as a crucial tool to determine the most effective project management strategy for producing these reservoirs. In particular, relative permeability curves are used in these simulations to represent the physical phenomenon of interest. However, the representativeness of these curves in industry laboratory tests has limitations. To obtain more accurate inputs, simulations at the pore network level are performed. These simulations incorporate models that consider alterations in interfacial tension and flow velocity throughout the reservoir. The validation process involves reproducing a pore network flow simulation as close as possible to a commercial finite difference simulation. A scale-up methodology is then proposed, utilizing an optimization process to ensure fidelity to the original relative permeability curve at a microporous scale. This curve is obtained by simulating the condensation process in the reservoir phenomenologically, using a model that captures the dependence on velocity. To evaluate the effectiveness of the proposed methodology, three relative permeability curves are compared based on field-scale productivities and the evolution of condensate saturation near the wells. The results demonstrate that the methodology accurately captures the influence of condensation on well productivity compared to the relative permeability curve generated from laboratory tests, which assumes greater condensate mobility. This highlights the importance of incorporating more realistic inputs into numerical simulations to improve decision-making in project management strategies for reservoir development.

An Analysis of Vertical Infiltration Responses in Unsaturated Soil Columns from Permafrost Regions

Rainfall infiltration affects permafrost-related slope stability by changing the pore water pressure in soil. In this study, the infiltration responses under rainfall conditions were elucidated. The instantaneous profile method and filter paper method were used to obtain the soil–water characteristic curve (SWCC) and hydraulic conductivity function (HCF). During the rainfall infiltration test, the vertical patters of volumetric moisture contents, total hydraulic head or suction and wetting front were recorded. Advancing displacement and rate of the wetting front, the cumulative infiltration, the instantaneous infiltration rate, and the average infiltration rate were determined to comprehensively assess the rainfall infiltration process, along with SWCC and HCF. Additionally, the effects of dry density and runoff on the one-dimensional vertical infiltration process of soil columns were evaluated. The results showed that the variation curve of wetting front displacement versus time obeys a power function relationship. In addition, the infiltration rate–time relationship curve and the unsaturated permeability curve could be roughly divided into three stages, and the SWCC and HCF calculated by volumetric moisture content are more sensitive to changes in dry density than to changes in runoff or hydraulic head height.

Multiscale Characterization of the Albian-Cenomanian Reservoir System Behavior: A Case Study from the North East Abu Gharadig Basin, North Western Desert, Egypt

Since its discovery in 2010, the NEAG 2 has been one of the most productive oil fields of the Badr El-Din Petroleum Company (BAPETCO) in the northern Western Desert of Egypt. The Albian-Cenomanian reservoir system has a unique performance but suffers from several issues hindering its production. The latest production report in 2023, NEAG-2 Field was producing 1760 bbls of oil with 36500 bbls of water, i.e., 95% water cut. Despite that, the field has reached a 39% recovery factor but the reservoir forecast suggests a much higher recovery factor. Therefore, the NEAG 2 Field requires a comprehensive geological model to depict its reservoir heterogeneities better. We introduce a solid and integrated workflow to investigate the reservoir characters among different scales of geological heterogeneity and offer solutions to overcome some data gaps. After characterizing the reservoir elements by the structural, stratigraphic, petrographic, and petrophysical analyses, a machine learning-based method was applied to overcome the missing whole rock cores in creating a detailed electro-facies log for all field wells. The Neural-Network algorithm required the facies types to be grouped into definitive reservoir qualities to be applied. The resultant electro-facies log had a very good match with the input logs, which validated the facies grouping. This was followed by the porosity-permeability transforms, estimated from mobility data, to create a permeability curve for all field wells, despite the unavailability of core data. The reservoir was categorized into three rock types, each with a specific range of quality, signifying their different flow abilities which were supported by dynamic data. The Lower Bahariya-Kharita in NEAG 2 was ultimately concluded to be a complex heterogeneous reservoir with varying flow abilities and production behaviors. The recovery factor mismatch is due to unrecovered reserves, and a new production strategy should be introduced to reach the ultimate recovery. This integration of geologic and dynamic data is strongly recommended for any reservoir characterization study to avoid oversimplifying the reservoir system and to design the right reservoir development plan.

Pore-scale modeling of wettability alteration coupled two-phase flow in carbonate porous media

The Middle East marine carbonate reservoirs are the primary targets for global crude oil exploration and production. In contrast to the clastic rock reservoirs, the marine carbonate reservoirs have undergone more complicated deposition, diagenesis and transformation, and the rock surface tends to be oil-wet or mixed-wet. One of the most effective methods for enhancing oil recovery in marine carbonate reservoirs is the use of an ion matched (IM)-surfactant (S) system to alter the wettability of rock surfaces. In this paper, we propose a microscale mathematical model of wettability alteration-coupled fluid flow by considering oil–water two-phase flow, wettability alteration, solute advection- diffusion and surfactant adsorption. The proposed microscale mathematical model is solved using the multi-component lattice Boltzmann model, and its accuracy is further verified. Finally, the effects of displacing fluid, ion-matched water concentration and surfactant concentration on oil mobilization at pore-scale are studied. Results show that, ion-matched water has a positive effect on wettability alteration, and typically shifts the cross-point of oil–water relative permeability curve to the right. The concentration of ion-matched water primarily affects fluid morphology of the wetting-phase and has little effect on phase permeability. After adding surfactant to the ion-matched water, the Euler coefficient of oil-phase gradually increases as the displacement continues, a large amount of remaining oil is gradually dispersed into scattered oil droplets and the oil-phase relative permeability is further improved.

A pore-scale investigation of viscous coupling effect on immiscible two-phase flow in porous media

Viscous coupling effect plays a significant role in immiscible two-phase flow within porous media, while its influence on relative permeability remains uncertain. In this paper, an improved MRT-based viscosity-modified multicomponent multiphase (MCMP) pseudopotential lattice Boltzmann model, capable of handling high viscosity ratio, is employed to simulate two-phase flow with different viscosities in a cross-array circular structure and a real rock structure, respectively. The applicability of this model for two-phase flow with various viscosity ratios has been verified by some typical tests. Systematically, the effects of viscosity ratio, structural configuration, and wetting condition on the relative permeability curves are investigated in conjunction with their component distributions and velocity fields at different two-phase saturations. These results indicate that due to the two-phase flow competition under different structural conditions, the viscous coupling effect has varying degrees of impacts on the mobility of thin phase and viscous phase. Further, the mechanism of two-phase lubricating effect is also discussed under different wetting conditions at Darcy flow regime.

Characterization and Inversion Method of Relative Permeability of Emulsion Flooding.

Relative permeability curves are one of the crucial factors that control the behavior of multiphase flow in petroleum reservoirs. Accurate prediction of the relative permeability curve involving emulsification and emulsion transport in emulsion flooding is vital to enhancing heavy oil recovery. In this study, a relative permeability characterization model including the emulsification mechanism and emulsion transport is developed, in which residual oil saturation and end-point permeability for water are parametrized as functions of emulsion concentration and capillary number. Based on the built characterization model, an inversion method (ensemble Kalman filter) is used to estimate the relative permeability curves of emulsion flooding. The inversion results of four sets of emulsion flooding experiments show that the errors of end points between the Johnson-Bossler-Neumann method and inversion method are less than 10%. For the continuous emulsification process in the in situ emulsion flooding tests, the inversed relative permeability curves shift between the upper and the inferior limits of the permeability. The error of residual oil saturation between the inversion and the experiment is less than 10%. In summary, this study demonstrates the feasibility of using the characterization model and inversion method to infer the relative permeability curves of emulsion flooding, which can aid in the predictions of multiphase flow in heavy oil reservoirs.

Strong effect of often-overlooked initial spilled oil distribution on subsequent soil remediation: A pore-scale perspective

The removal of spilled oil within soil by water injection is essentially an immiscible fluid displacement process. Numerous studies have been conducted to investigate the way to achieve a higher displacement efficiency. However, these studies often assumed that the pore space was initially saturated by oil only, ignoring the effect of initial oil distribution on the remediation, which led to incorrectly computed flow field and biased analysis. This work aimed to reveal the effect of initial oil distribution on flow physics during the remediation. Based on a pore-scale model and the phase-field method, the spilled oil invasion and remediation in a heterogeneous porous media were investigated, and the dynamic evolution of the phase interface was examined in particular. Four different distribution patterns of spilled oil were obtained through various velocities during the oil invasion stage, which were considered as initial states for the subsequent remediation stage. The results showed that ignoring the oil invasion process led to a more than 10% reduction in the ultimate remediation efficiency. However, the maximum interfacial area of fluids was larger and the obtained relative permeability curve was much smoother for the scenario considering the oil invasion. Besides, a higher initial water saturation led to a lower starting pressure. This work provided new pore-scale insights into the often-overlooked roles of initial phase distribution in fluid dynamics behind the remediation of oil-contaminated soil by water injection, which was of fundamental importance to the development of effective response strategy for soil contamination.

A prediction method of oil recovery for hot water chemical flooding in heavy oil reservoirs: Semi-analytical stream tube model

Abstract Chemical agents (polymer and surfactant) assisted hot water flooding is an effective means of enhancing oil recovery in heterogeneous and heavy oil reservoirs. The rapid prediction of oil recovery through hot water chemical flooding is very important. The stream tube model is a fast analytical method for predicting water flooding recovery, but it is not suitable for hot water chemical flooding. In this paper, a permeability distribution model for multi-stream tubes is established based on permeability variation coefficient using normal distribution function for reservoir heterogeneity, Using GOMPERTZ growth function model to characterize the changes in stream tube temperature, polymer viscosity, and surfactant concentration with injection volume, Using Brooks-Corey model to describe the influence of interfacial tension and temperature on the relative permeability curve. Finally, an analytical stream tube model for hot water chemical flooding of heavy oil reservoirs was established. The time discrete method is used to solve the model, then the graphs of the relationship between oil recovery and water cut are obtained. Compared with numerical simulation methods, the prediction error of oil recovery is less than 2%, and the calculation time is reduced by 89%. This model has been successfully applied to X oilfield. Based on historical fitting, it is predicted that hot water chemical flooding can enhance oil recovery by 6.3% compared to water flooding. This paper provides a fast calculation method for predicting and evaluating the effectiveness of hot water chemical flooding in heavy oil reservoirs.

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.

Evaluation of CO2/Water Imbibition Relative Permeability Curves in Sandstone Core Flooding—A CFD Study

Greenhouse gases such as CO2 can be safely captured and stored in geologic formations, which in turn can reduce the carbon imprint in the Earth’s atmosphere and therefore help toward reducing global warming. The relative permeability characteristics in CO2/brine or CO2/water systems provide insight into the CO2 trapping efficacy of formations such as sandstone rocks. In this research, CO2/water imbibition relative permeability characteristics in a typical sandstone core sample are numerically evaluated. This work uses transient computational fluid dynamics (CFD) simulations to study relative permeability characteristics, and a sensitivity analysis is performed based on two different injection pressures and absolute permeability values of the sandstone rock material. Results show that when the irreducible water fraction remains unchanged, the imbibition relative permeability to the non-wetting phase decreases with an increase in injection pressure within the sandstone core sample. Also, with the irreducible water fraction being unchanged, relative permeabilities to both non-wetting and wetting phases decrease with an increase in the absolute permeability of the rock material. Finally, at irreducible water saturation, relative permeability to the gas phase decreases with an increase in injection pressure.

A Saturation Correction Method Based on Static and Dynamic Parameters

Abstract The saturation analysis date of sealed coring wells can provide the most direct quantitative data for studying remaining oil distribution. However, the oil/water saturation values measured in laboratory test usually deviate form the true values of underground conditions due to multiple factors, and they must be corrected for exact data. Most existing calibration methods consider the changes in pressure and pore conditions during the coring process, ignoring the differences in the oil/water saturation values caused by lithology and electrical properties. In this paper, well J2-6-A145 is selected as the study object. Firstly, the lithology and oil water loss rate are determined as the main influencing factors of oil water saturation by using the Analytic Hierarchy Process. Then a classification statistical correction chart based on lithology and oil-water loss rate is established in sequence, with correlation coefficients ranging from 0.92 to 0.97. Finally, based on the Electrical Property Water Content Relationship Chart of mining production statistics, considered the differences in oil water volatilization under different content levels. The oil-water saturation under different Oiliness is corrected by combining production dynamics chart and permeability curve. A saturation correction method based on statistical regression is obtained by considering multiple factors such as lithology, oil-water loss rate, oiliness, permeability and production dynamics. This method improves correlation after segmented regression, better reflects the oil content of the formation by considering dynamic factors, and provides an accurate data foundation for understanding and evaluating the distribution pattern of remaining oil.

The invention relates to a method for simulating phase permeability curve based on conventional logging data

Abstract Phase permeability curve is the curve of relative permeability (effective permeability/oil phase permeability in bound water) and water saturation change obtained through core phase permeability experiment. It is an indispensable data in oilfield development calculation, dynamic analysis, determination of oil-water saturation distribution in reservoirs and other water-driven oil related calculations, and an important index for reservoir evaluation. The study of effective permeability and relative permeability is of great significance for controlling the uniform advance of oil-water or oil-gas boundary and rationally developing oil and gas fields. The only effective way to study the phase infiltration is the core phase infiltration experiment, but the number of lithology samples is very limited, so the phase infiltration in oilfield development and application is still in the estimation stage, the accuracy is low, and the practical application is not strong. In order to improve the applicability of the phase permeability curve, it is necessary to establish a set of electrical interpretation methods associated with logging curves to realize electrical simulation instead of core measurement. In this paper, an electrical interpretation model of oil-water phase permeability is established based on flowable porosity and pore radius, and the effective seepage dynamic prediction and inversion of oil-water phase in each development stage of each reservoir is realized, which lays a solid foundation for the fine development of the reservoir.