Reservoir Heterogeneity Research Articles

Investigation of EOR Formulations with Engineered Brines Utilizing Bespoke Polymer for a Candidate Offshore Heterogeneous Sandstone Reservoir

Investigation of EOR Formulations with Engineered Brines Utilizing Bespoke Polymer for a Candidate Offshore Heterogeneous Sandstone Reservoir

Dynamic Simulation Research on Microprofile Control Mechanism of Foam in Fractured Media Based on Level Set Method.

Fractured reservoirs are an important source of oil and gas energy. After depletion of production, the production capacity of this reservoir decreases rapidly. Effective profile control is needed to improve the sweep efficiency and reservoir heterogeneity. Foam can solve such problems, but its profile control mechanism is not fully understood. Based on this, this paper uses the level set method to study the microscale control mechanism of foam in fractured media. The results show that artificial fractures and high-permeability microfractures are tighter than natural fractures, the Jamin effect of foam is stronger, and the secondary foaming ability is better. Therefore, the plugging ability of foam to natural fractures is far less than that of foam to artificial fractures and high-permeability microfractures. The larger the fracture opening, the larger the foam volume and the smaller the flow rate. As the opening ratio increases gradually, the generated foam flows more to the natural fractures with a large opening, and the effect of foam blocking large fractures becomes worse. The diversion rate curves of different opening ratios show that the foam has a good profile control effect when the opening ratios are 4:1 and 2:1, and even the diversion rate overturns, while the profile control diversion effect is poor when the opening ratio is 10:1, so it cannot play an effective role in profile control. The foam shows the profile control process of preferentially plugging the high-permeability area and allowing more subsequent fluids to enter the low-permeability area. The research reveals the profile control mechanism of foam on fractured reservoirs from the micro level, which is the supplement and verification of relevant macro research and provides a theoretical basis for the efficient development of fractured reservoirs.

Prediction Technology of a Reservoir Development Model While Drilling Based on Machine Learning and Its Application

In order to further understand the complex spatial distribution caused by the extremely strong heterogeneity of buried hill reservoirs, this paper proposes a new method for predicting the development pattern of buried hill reservoirs based on the traditional pre-drilling prediction and post-drilling evaluation methods that mainly rely on seismic, logging, and core data, which are difficult to meet the timeliness and accuracy of drilling operations. Firstly, the box method and normalization formula are used to process and normalize the abnormal data of element logging and engineering logging, and then the stepwise regression analysis method is used to optimize the sensitive parameters of element logging and engineering logging. The Light Gradient Boosting Machine (LightGBM) algorithm, deep neural network (DNN), and support vector machine (SVM) are used to establish a new method for predicting the development pattern of buried hill reservoirs. Lastly, a comprehensive evaluation index F1 score for the model is established to evaluate the prediction model for the development pattern of buried hill reservoirs. The F1 score value obtained from this model’s comprehensive evaluation index indicates that the LightGBM model achieves the highest accuracy, with 96.7% accuracy in identifying weathered zones and 95.8% accuracy in identifying interior zones. The practical application demonstrates that this method can rapidly and accurately predict the development mode of buried hill reservoirs while providing a new approach for efficient on-site exploration and decision-making in oil and gas field developments. Consequently, it effectively promotes exploration activities as well as enhances the overall process of oil and gas reservoir exploration.

Study on Plugging the Multiscale Water Channeling in Low-Permeability Heterogeneous Porous Media Based on the Growth of Bacteria

Summary To promote the effect of waterflooding of a heterogeneous low-permeability reservoir in the Ordos Basin, a microbial plugging agent is developed to plug the multiscale water channeling. Based on the characteristics of the growth of bacteria, the microbial plugging agent can plug both porous media and microfractures with different scales. The microbial plugging agent is prepared by activating the native bacteria present in low-permeability reservoirs by using the fermentation nutrients. After growing in the fermentation nutrient solution for 4 days in a beaker, the growth of microbial strains begins to stabilize. After that, the main particle size of the prepared microbial plugging agent is between 40 μm and 160 μm and the median particle size (D50) is near 90 μm. The microbial plugging agent has good shear resistance, salt resistance, and stability. At the initial state, due to good injectivity, the microbial plugging agent can smoothly enter into a low-permeability core, a heterogeneous core, and a fractured core, respectively. Thus, it can grow and reproduce in the cores. Based on the characteristics of growth, it can match with the spatial scale of pore or fracture in the cores, so that it cannot only plug the porous media water channeling with different scales but also plug the microfracture water channeling with different scales. This phenomenon has been confirmed by microscopic visualization flow experiments and core flow experiments. The developed microbial plugging agent can be applied to plug the multiscale water channeling to enhance oil recovery of low-permeability heterogeneous reservoirs.

Vertical displacement of a non-Newtonian Bingham plastic by a Newtonian phase in an axially composite reservoir

In general, oil reservoirs may consist of composite sedimentary structures composed of materials such as sand, clay, or limestone, which exhibit varying lithology due to sedimentary processes. A comprehensive knowledge of this lithology is essential for accurately assessing their hydrocarbon storage and production capacity. Additionally, this information is indispensable for the implementation of various recovery techniques such as waterflooding, gas injection, surfactant injection, polymer injection, alkaline water solution injection, and others. Highly viscous oil can exhibit non-Newtonian behavior during water injection in certain cases. The use of surfactants, alkaline, or polymer solutions in enhanced oil recovery also introduces non-Newtonian behavior. Recovery methods face challenges when non-Newtonian phases, gravity, and reservoir heterogeneity are combined. Against this backdrop, this work presents a mathematical model for immiscible two-phase flow in an axially composite reservoir with a periodic-layered structure. The model considers a non-Newtonian plastic Bingham-type phase extension of the Buckley-Leverett model. To address the porous medium’s heterogeneity with discontinuous flux functions, the numerical solutions were obtained using the Lax-Friedrichs and Lagrangian-Eulerian schemes. The numerical solutions were compared to analytical solutions obtained using an extended version of Oleinik’s geometric construction for discontinuous flux functions. The outcomes display shock and rarefaction waves, as well as a fixed shock due to the porous medium heterogeneity. The numerical results closely correspond with the analytical solutions, seen particularly in the greater accuracy of the Lagrangian-Eulerian method compared to the Lax-Friedrichs method.

An Artificial Neural Network Model for Infill Well Placement and Control Optimization During Foam Injection in Heterogeneous Oil Reservoirs

An Artificial Neural Network Model for Infill Well Placement and Control Optimization During Foam Injection in Heterogeneous Oil Reservoirs

Permeability modelling in a highly heterogeneous tight carbonate reservoir using comparative evaluating learning-based and fitting-based approaches

Permeability modelling is considered a complex task in reservoir characterization and a key component of reservoir simulation. A common method for permeability modelling involves performing static rock typing (SRT) using routine core analysis data and developing simple fitting-based mathematical relations that link permeability to reservoir rock porosity. In the case of carbonate reservoirs, which are associated with high heterogeneities, fitting-based approaches may fail due to porosity–permeability data scattering. Accurate modelling of permeability using petrophysical well log data seems more promising since they comprise a vast array of information about the intrinsic properties of the geological formations. Furthermore, well log data exhibit continuity throughout the entire reservoir interval, whereas core data are discrete and limited in availability and coverage. In this research work, porosity, permeability and log data of two oil wells from a tight carbonate reservoir were used to predict permeability at un-cored intervals. Machine learning (ML) and fitting models were used to develop predictive models. Then, the developed ML models were compared to exponential and statistical fitting modelling approaches. The integrated ML permeability model based on Random Forest method performed significantly superior to exponential and statistical fitting-based methods. Accordingly, for horizontal and vertical permeability of test samples, the Root Mean Squared Error (RMSE) values were 3.7 and 4.5 for well 2, and 1.7 and 0.86 for well 4, respectively. Hence, using log data, permeability modelling was improved as it incorporates more comprehensive reservoir rock physics. The outcomes of this reach work can be used to improve the distribution of both horizontal and vertical permeability in the 3D model for future dynamic reservoir simulations in such a complex and heterogeneous reservoir system.

CAPILLARY PROCESSES DURING FLOODING OF LAYERED-HETEROMOGENEOUS PRODUCTIVE FORMATIONS

The paper presents an analysis of existing laboratory methods for determining capillary pressure functions used in mathematical and computer modeling of the processes of capillary impregnation of low-permeability layers of layered heterogeneous hydrophilic reservoirs during their flooding.It is shown that in existing methods for determining capillary pressure functions in rock samples using capillarimeters and high-speed centrifuges, the factor of the formation of residual oil in the pore space of the rock is not taken into account. At the same time, the processes of displacement of oil by water from productive formations and, in particular, the processes of capillary impregnation of the rock, are characterized by the processes of formation of microvolumes precisely of immobile residual oil in its pore space. Meanwhile, when conducting laboratory studies of rock samples using existing methods, another process is physically reproduced — the process of displacement of water by oil, during which microvolumes of residual water, rather than oil, are formed.This difference in the structure of the oil-water medium leads to a significant difference between the capillary pressure functions determined by traditional methods and the capillary pressure functions that control the distribution of oil and water phases in the pore space of rocks in the processes of displacement of oil from them by water pumped into the reservoir.This difference is especially significant when flooding low-permeability rocks characterized by high capillary pressure values.The work suggests possible approaches to conducting laboratory studies of rock cores that are more consistent with the structural features of the oil-water environment during flooding of productive formations.For the most complete capillary impregnation of low-permeable layers of a layered heterogeneous formation with water from quickly watered high-permeability layers, a method is proposed that consists in the fact that the water pumped into the formation must contain the minimum required amount of oil, ensuring the mobility (connectivity) of the oil phase in the watered high-permeability layers.For this purpose, water from production wells containing a certain amount of residual oil can be used for injection into the reservoir. The economic feasibility of the proposed method should be justified by the results of computer modeling of capillary impregnation processes, taking into account the described features of capillary pressure functions characteristic ofprocesses of oil displacement from productive formations during their waterflooding.

Zastosowanie „aproksymacji dyfuzyjnej” do opisu procesu zagospodarowania złóż ropy naftowej

Analysis of the interaction of wells in the process of oil field development is based in particular on calculating the correlation coefficient of two adjacent wells. However, due to reservoir heterogeneity, this approach fails to consider the possibility of interactions between wells located at significantly greater distances. The non-equilibrium of the system is attributed to its openness, associated with environmental impacts (flooding process and changes in the stock of existing wells). The oil field development is a complex process, subject to complex works such as well grid compaction, carrying out a wide range of geological and technical operations, etc. From this point of view, the development and exploitation of fields needs a “volumetric” approach, i.e. a diffusion approximation. A crucial aspect of oil production is the timely regulation of both current production rates and water impact on the reservoir system. The oscillatory nature of the time series of measurements of oil, water, and liquid production rates carries information about the state and behavior of the reservoir system. Analysis of the features of oscillatory processes of the technological indicators of well operation across the entire area of the deposit as a whole enables early diagnosis of changes in the state of the system. The approach of the production well stock analysis in terms of the amplitude-frequency characteristics of the dynamics of oil, water, “mobile” water, and flooding, as well as the specific ratios of produced oil to the volume of water injected into the reservoir (an indicator of the effectiveness of water stimulation) allows us to consider the development as a diffusion-like process.

Integrating Rock Typing and Petrophysical Evaluations to Enhance Reservoir Characterization for Mishrif Formation in Garraf Oil Field

Accurate reservoir characterization is essential for successful hydrocarbon extraction, especially in complex fields such as the Garraf Oil Field. This study aims to enhance reservoir characterization by integrating different petrophysical assessments and rock typing methodologies. Density, neutron, and sonic porosity evaluations were used to assess porosity, while gamma-ray logs and resistivity measurements were used to determine shale volume. The Archie equation was employed to estimate water saturation and sensitivity analysis was used to determine the cutoff values. The study also utilized rock typing techniques, including hydraulic flow unit assessment and Rock fabric number cross-plots, to categorize reservoir rocks into flow units and identify unique rock types. The combination of these approaches led to the precise identification of reservoir heterogeneities and optimal oil production zones. The results showed that the Gamma-ray log is the best method for determining shale volume, and the closest method for porosity determination is the density log. The water resistivity value was estimated at 0.016, while the Archie parameters (a,m,n) were 1.1, 2.1, and 3.7, respectively, with cutoff values of 0.22 for shale volume, 0.11 for porosity, and 0.56 for water saturation. The study identified five rock types ranging from packstone, pack to wackstone, wackstone, wack to mudstone, and mudstone. Overall, the integration of petrophysical evaluations and rock typing techniques facilitates the accurate delineation of oil-rich zones with enhanced reservoir connectivity.

Low-Salinity Waterflooding for EOR in Field A of Western Offshore Basin: A Pilot Study Analysis with Laboratory and Simulation Studies—Early Observations

Carbonate reservoirs hold vast oil reserves, but their complex properties make traditional enhanced oil recovery (EOR) methods challenging. This study explores the application of low-salinity water flooding (LSWF) as a novel EOR method for India’s largest offshore carbonate oil field. Conventional EOR techniques were deemed unsuitable due to reservoir heterogeneity, pressure decline, high temperature, and the offshore location. Favorable factors for LSWF included successful seawater flooding history, medium-weight crude oil, and existing infrastructure. Following core flooding experiments demonstrating a 6–16% increase in oil recovery, a multi-pronged evaluation process was implemented. Single-well chemical tracer tests (SWCTT) and reservoir simulations confirmed the potential of LSWF. A specific target area was chosen based on reservoir characteristics, production data, and available facilities. Simulations predicted a 1.5% incremental oil recovery using diluted seawater (25% salinity) at 30% pore volume injection. After a positive techno-economic analysis, the first offshore LSWF project in India was completed within 3 years. Initial monitoring results are encouraging. This study highlights the successful journey of LSWF from concept to field deployment in a challenging carbonate reservoir, showcasing its potential for revitalizing such fields. Furthermore, this work provides valuable data relevant to Indian offshore environments, where factors like salinity, mineralogy, and crude oil composition pose unique challenges compared to other LSWF applications. These detailed data fill a critical gap in the existing literature.

Effect of pore structure characteristics on gas-water seepage behaviour in deep carbonate gas reservoirs

The study of gas-water two-phase flow behavior has always been a focus and a difficult problem in the field of oil and gas seepage, and it is related to the formulation of reasonable development plans for oil and gas reservoirs. Deep carbonate gas reservoirs (depth>4500m) develop cross-scale porous media, which have extremely strong heterogeneity and very complex seepage characteristics. To the best of our knowledge, there has been no systematic study on the two-phase flow patterns of gas and water in deep carbonate gas reservoirs. This paper uses cast thin sections, scanning electron microscopy (SEM) and nuclear magnetic resonance (NMR) to study the influence of carbonate rock pore structure characteristics on gas storage and seepage capabilities. The results show that the existence of cavities enhances the gas storage capacity of the reservoir and improves the seepage capacity of pore-throat space near the cavity. Fractures can effectively communicate with isolated cavities, enhance reservoir connectivity, and thereby significantly improve the overall seepage capacity of the reservoir. The centrifugal technique was combined with NMR to study the movable fluid characteristics of carbonate reservoirs. The critical flow throat radius and movable fluid saturation of the reservoir reveal that the degree of development of cavities and fractures determines the mobility of the fluid in the reservoir. The fluid mobility in the fracture-cavity-type reservoir is the strongest, while the fluid mobility in the pore-type reservoir is the weakest. Analysis of the normalized curve of gas-water relative permeability under high temperature and pressure reveals that formation water preferentially enters connected pores with low seepage resistance, and the strong storage capacity of cavities can effectively delay the non-uniform intrusion of formation water. The results of water invasion simulation experiments show that the water invasion phenomenon can improve the gas production rate and recovery rate of pore-type reservoirs. However, the formation water flow and channeling phenomena caused by reservoir heterogeneity will cause a large amount of gas to be sealed in the pore space of cavity-type and fracture-cavity-type reservoirs, reducing the recovery rate and economic benefits of these reservoirs. These findings further provide solid fundamentals for efficient and effective exploitation of deep carbonate gas reservoirs.

Pore Structure Characteristics and Reservoir Classification of Tight Sandstones within the Upper Permian Longtan Formation in the Laoshan Uplift, South Yellow Sea Basin: Implications for Hydrocarbon Exploration

The Upper Permian Longtan Formation in the Laoshan Uplift of the South Yellow Sea Basin hosts thick and distinctive tight sandstones. However, a comprehensive understanding of its pore structure and reservoir classification remains lacking. This study investigates the fully cored well, CSDP-2, utilizing thin section analysis, scanning electron microscopy, energy spectrum analysis, X-ray diffraction, high-pressure mercury intrusion, and nuclear magnetic resonance to characterize its petrophysical properties, pore space, and movable fluid characteristics. Additionally, fractal principles are further employed to examine reservoir heterogeneity and conduct a quantitative assessment, considering the complexity of tight sandstone pore structures. The findings reveal that the sandstones predominantly comprise feldspathic litharenites, with an average porosity of 1.567% and permeability of 0.099 mD, primarily containing intragranular pores. Two distinct sets of pores with significantly different sizes (r < 2 μm; r > 6 μm) were identified, displaying relatively high fractal dimensions and discrete distribution. Movable fluids primarily occupy pores with radii > 0.019 μm, reflecting pronounced overall heterogeneity. The reservoir was classified into three categories utilizing permeability, median radius, and movable fluid saturation as key evaluation parameters, with Class I representing a relatively high-quality reservoir. These findings advance our understanding of the pore development mechanism of tight sandstone reservoirs and provide geological evidence for further hydrocarbon exploration in this study area.

Development of a convolutional neural network based geomechanical upscaling technique for heterogeneous geological reservoir

Geomechanical assessment using coupled reservoir-geomechanical simulation is becoming increasingly important for analyzing the potential geomechanical risks in subsurface geological developments. However, a robust and efficient geomechanical upscaling technique for heterogeneous geological reservoirs is lacking to advance the applications of three-dimensional (3D) reservoir-scale geomechanical simulation considering detailed geological heterogeneities. Here, we develop convolutional neural network (CNN) proxies that reproduce the anisotropic nonlinear geomechanical response caused by lithological heterogeneity, and compute upscaled geomechanical properties from CNN proxies. The CNN proxies are trained using a large dataset of randomly generated spatially correlated sand-shale realizations as inputs and simulation results of their macroscopic geomechanical response as outputs. The trained CNN models can provide the upscaled shear strength (R2 > 0.949), stress-strain behavior (R2 > 0.925), and volumetric strain changes (R2 > 0.958) that highly agree with the numerical simulation results while saving over two orders of magnitude of computational time. This is a major advantage in computing the upscaled geomechanical properties directly from geological realizations without the need to perform local numerical simulations to obtain the geomechanical response. The proposed CNN proxy-based upscaling technique has the ability to (1) bridge the gap between the fine-scale geocellular models considering geological uncertainties and computationally efficient geomechanical models used to assess the geomechanical risks of large-scale subsurface development, and (2) improve the efficiency of numerical upscaling techniques that rely on local numerical simulations, leading to significantly increased computational time for uncertainty quantification using numerous geological realizations.

Synthesis, investigation of temperature and salt resistant polyacrylamide microspheres used for deep sealing and profile control and function strengthening mechanism

AbstractBased on the requirements of deep sealing and profile control for the excellent temperature and salt resistance on polyacrylamide microspheres, the Poly‐AM/AMPS was prepared depends on aqueous solution polymerization method to improving oil and gas recovery efficiency in low‐permeability and heterogeneous reservoirs resulted by water channeling. The key technical parameters were established through single‐factor experimental methods, and the chemical structure was studied by infrared spectrum analysis (FTIR), energy spectrum analysis, and x‐ray diffraction analysis, and then the thermal stability was investigated depends on the thermogravimetric (TG) and differential thermogravimetric (DTG) distribution curves, moreover, the particle size and distribution, microstructure, and surface morphology were further studied. As a result, the results confirmed that the molecular structure of Poly‐AM/AMPS meets the expected design, and the quality retention rate at 800°C is 17.4%, the median particle size of Poly‐AM/AMPS particles is 35.88 μm, and the particle size distribution range is about 1.94–497.8 μm. Further, the Poly‐AM/AMPS was modified by maleic anhydride, sodium styrenesulfonate, and dimethyl diallyl ammonium chloride through conventional functional strengthening and modification, modified by nano‐SiO2, GO, and S‐CaCO3 through nano‐functional strengthening and modification. Additionally, the functional strengthening and modification mechanism was studied depends on the FTIR, TG, and DTG methods.

CORRIGENDUM to “Optimization of Fast-steam-assisted gravity drainage for the energy-efficient operations at a heterogeneous oil-sands reservoir”

CORRIGENDUM to “Optimization of Fast-steam-assisted gravity drainage for the energy-efficient operations at a heterogeneous oil-sands reservoir”

A Method to Identify Pore Fluids in Heterogeneous Conglomerate Reservoirs Using a Nuclear Magnetic Resonance Log with Oil-Based Mud Invasion

Summary Nuclear magnetic resonance (NMR) logging has been extensively utilized for identifying pore fluids in recent years. However, after oil-based mud (OBM) invasion, OBM filtrate partially takes the place of the original fluid in the reservoir and the morphology of the NMR T2 (transverse relaxation time) spectrum changes. OBM invasion makes it difficult to identify the formation fluid using routine NMR fluid identification methods. In this study, we took heterogeneous conglomerate formation in the northwestern Junggar Basin as a case study and carried out core experiments under four conditions (viz., water-saturated, OBM displacing water, oil-saturated, and OBM displacing oil) and simulated the states of OBM invasion into water and hydrocarbon-bearing formation. Comparative analysis finds that when the OBM invades the water layer, the movable peak of the T2 spectrum primarily reflects the bulk relaxation characteristics of OBM filtrate, whereas when the OBM invades into the oil layer, the T2 spectrum may exhibit a three-peak distribution, where the first peak mainly indicates irreducible water, the second peak reflects OBM filtrate, and the third peak primarily reflects nondisplaced oil. To facilitate fluid identification, two T2 cutoffs are adopted to divide the T2 spectrum into three segments, and combined with the T2 geometric average, a fluid identification factor (ifluid) is proposed. Finally, identification criteria for reservoir type are established on the NMR logging and drillstem test data. The field application verifies the reliability of the proposed methods. These methods realize the identification of oil layers under OBM drilling and guide the subsequent production and development of oil reservoirs.

A novel reservoir classification method for sandstone reservoir evaluation using multi-scale digital rock method

The formulation of an effective development plan, optimizing exploitation efficiency, relies heavily on accurate reservoir characterization. However, existing reservoir classification methodologies, which rely on macroscopic geological observations and well-logging data, have limitations in data availability and fail to capture micro-scale pore structure characteristics accurately. The emerging technology of digital rock, widely employed in the petroleum industry, also faces challenges in accurately capturing reservoir heterogeneity due to its single-scale nature and limited application for reservoir classification. To overcome these challenges, this study presents an innovative reservoir classification approach based on the multi-scale digital rock method. This approach integrates qualitative assessment of micro-CT images for particle contact relationships and pore types with quantitative evaluation of multi-scale characteristic parameters, obtained from micro-CT and scanning electron microscopy (SEM) images. The proposed classification method demonstrates excellent agreement with the prioritization of development and production data for offshore sandstone reservoirs. By establishing a robust evaluation methodology, this classification method facilitates exploration potential assessment and development strategy optimization within the field.

Expanding role of borehole image logs in reservoir fracture and heterogeneity characterization: A review

Expanding role of borehole image logs in reservoir fracture and heterogeneity characterization: A review

The Mechanism Study of Fracture Porosity in High-Water-Cut Reservoirs

Many onshore oil fields currently adopt water flooding as a means to supplement reservoir energy. However, due to reservoir heterogeneity, significant differences in permeability exist not only between different reservoirs but also within the same reservoir across different planar orientations. After prolonged fluid flushing in the near-wellbore zone of injection wells, the resulting increased flow resistance between layers exacerbates inefficient and ineffective circulation. A considerable amount of remaining oil is left unexploited in untouched areas, significantly impacting the overall recovery. To investigate the multiscale plugging mechanisms of fracture-dominated pore channels in high-water-cut oil reservoirs and achieve efficient management of fractured large channels, this study explores the formation of the fracture-flushing zone-low saturation oil zone. A physical experimental model with fractures and high-intensity flushing is established to analyze changes in pore structure, mineral composition, residual oil distribution, and other characteristics at different positions near the fractures. The research aims to clarify the mechanism behind the formation of large channels with fracture structures. The results indicate that under high-intensity water flushing, cementing materials are washed away by the flowing water, clay particles are carried to the surface with the injected fluid, and permeability significantly increases, forming high-permeability zones with fracture structures. In the rock interior away from the fracture end, channels, corners, and clustered oil content noticeably decrease, while the content of film-like oil substantially increases, and clay minerals are not significantly washed away. Under strong flushing conditions, the number of residual clay particles near the fracture end is mainly influenced by flow velocity and flushing time; thus, the greater the flushing intensity, the faster the water flow, and the longer the flushing time, the fewer residual clay particles near the fracture end.