Seepage Parameters Research Articles

Analytical Mini-Review of Different Sheet Pile Configuration Utilization for Dam Seepage Reduction and Applications on Iraqi Dams

Abstract Seepage is one of the main causes of dams and some other hydraulic structures' failure. Water movement beneath the dam’s base creates piping and uplift pressure under the structure, potentially leading to improper dam operation. This current study focuses on the utilization of a special technique to restrict the transfer of movement water via soil which includes sheet piles under the dam foundation. Sheet pile walls are interlocking pile segments that are embedded in soil to resist horizontal pressure, classified as a flexible retaining system, and capable of tolerating relatively large deformations. Sheet piles are made of various materials, such as wood, concrete, steel, and aluminum, which are suitable for different applications. The role of seepage can be affected by the cutoff utilization. In this study, some Iraqi dam issues due to seepage are explained, also the geological stratum beneath the dam is briefly discussed. the potential use of sheet piles with different configurations has been reviewed to detect the optimum situation for seepage parameters reduction based on their numbers, interval distances, inclinations, and places. Keywords: Seepage, sheet piles, impermeable foundation, Iraqi dams’ issues, and geological stratum.

Quantification of seepage characteristics in shale oil reservoirs: A triple medium model-driven approach

Shale oil is an important unconventional oil and gas resource depicting a complex microstructure with various pore types and fluid distribution. In particular, the fluid flow mechanism and the associated percolation characterization theory have recently gained notable interest. Here we establish a mathematical model to describe non-wetting and wetting phase imbibition in shale oil formation. The model is based on the triple continuum medium theory taking into account the wetting characteristics of the shale/oil/brine system, the percolation processes in inorganic and organic pores, and the dynamic process of adsorption and absorption of crude oil in kerogen. The experimental results of oil and water imbibition were fitted thereby obtaining seepage physical parameters and validating the realiability of the proposed model. The impact of physical properties (e.g. inorganic and organic permeability, equivalent cross-flow coefficient, and diffusion coefficient) on the dynamic characteristics of the imbibition process was also evaluated. The results show that the inorganic permeability is between 10−7–10−4μm2 and the organic permeability is between 10−10–10−6μm2. The imbibition rate demonstrates a positive correlation with inorganic and organic permeability, equivalent cross-flow coefficient, and diffusion coefficient. The larger the difference between inorganic and organic permeability, the more pronounced the “bi-horizontal segment” feature of the shale oil imbibition saturation curve. The proposed model effectively calculates the reserves in both organic and inorganic pores, thereby addressing the time-consuming challenges associated with experimentally obtaining seepage parameters. This study thus provides a theoretical basis for precisely evaluating fluid flow in shale oil reservoirs.

An Enhanced Reptile Search Algorithm for Inverse Modeling of Unsaturated Seepage Parameters in Clay Core Rockfill Dam Using Monitoring Data during Operation

The seepage characteristics of clay core walls are crucial for the seepage safety of core rockfill dams, with the permeability coefficient in the unsaturated zone being nonlinear. To accurately determine the unsaturated seepage parameters in clay core rockfill dams, this paper first proposes an enhanced reptile search algorithm (ERSA) by applying three improvement strategies: Arnold’s cat chaotic map, nonlinear evolutionary factor, and adaptive Cauchy–Gaussian mutation with variable weight. Then, by integrating the ERSA with the unsaturated seepage finite element method, an inverse modeling approach is developed. This approach is applied to an actual rockfill dam with operational monitoring data to determine the unsaturated seepage parameters of the clay core. Results indicate that the ERSA outperforms the original RSA in test functions, and the calculation results of the seepage parameters determined through inversion are consistent with the monitoring data, showing an overall mean absolute error of 1.086 m. The inverse modeling approach provides a valuable reference for determining unsaturated seepage parameters in similar clay core rockfill dams.

Imbibition models quantifying interfacial interactions: Based on nuclear magnetic resonance investigation and coupled structural characteristics

An investigation into spontaneous imbibition in porous media is of paramount scientific significance in various projects. However, a precise understanding of the interaction mechanisms between media structural characteristics and imbibition remains elusive, and quantitative analysis of the interfacial interaction is lacking. Therefore, to mitigate the influence of dispersion, this study first investigates cyclic imbibition experiments of coal samples to explore the interaction mechanism between pore-fracture structure (PFS) and imbibition. Nuclear magnetic resonance is used to visualize water transport during imbibition across all scales. Subsequently, the slake durability index is suggested to clarify the coupling relationship between water–coal interactions and imbibition. Two more comprehensive and accurate imbibition models are established, based on pore size and comprehensive seepage parameters, respectively. The results demonstrate that both new models exhibit superior conformity with experimental data compared to traditional models. The memory factor quantifies interface interaction within these models. Sensitivity analysis reveals that strong interface interaction diminishes the effective imbibition ratio, while the structural characteristics of porous media significantly influence the interaction. Furthermore, the fractal dimension quantitatively characterizes the PFS features of coal samples. An exploration of the relationship between fractal dimension and memory factor indicates the influence of porous media heterogeneity on imbibition.

A complex-network-based estimation of the representative elementary volume and equivalent permeability coefficient for fractured rock masses

The determination of the representative elementary volume (REV) and equivalent permeability coefficient (EPC) of fractured rock masses is crucial for studying the hydraulic behaviors of engineering rock masses. The complex network originated from graph theory and represents a rapidly developing interdisciplinary field in the 21st century. In this paper, we propose a novel method that utilizes complex-network-based metrics to estimate the REV and EPC of fractured rock masses. In this method, fractures and their intersections are treated as nodes and edges of a complex network, respectively. We propose a transformation procedure of a discrete fracture network (DFN) into a complex network, and the corresponding algorithms are conducted in MATLAB. Subsequently, we obtain a complex network, and several complex-network-based metrics, such as average degree, average clustering coefficient, and graph density, are calculated using Gephi software. We employ the average degree to estimate the REV size of DFN models, while the coefficient of variation is used to quantitatively assess changes in the average degree of multiple random models. Furthermore, we establish an empirical formula utilizing the average degree, average clustering coefficient, and graph density to estimate the EPC of a large-scale DFN model based on the EPC of a small-scale DFN model. To verify the developed method, we conduct numerical experiments using the MAFIC (Matrix/Fracture Interaction Code) solver within the FracMan software. This enabled us to calculate the EPC, which was then used to determine the REV. The results demonstrate that: (a) the REV size estimated by the average degree aligns with the REV size obtained through numerical simulations for both isotropic and anisotropic DFN models, and (b) the error rates between the average EPC calculated by the empirical formula and that obtained by numerical simulations are within 10%. Thus, the proposed seepage parameter estimation methods are deemed valid.

Pore-scale study of the dynamic evolution of multi-phase seepage parameters during hydrate dissociation in clayey silt hydrate-bearing sediments

Unlike conventional oil and gas sources, natural gas hydrate (NGH) is stored in solid form within the pores of loose submarine sediments. Production by any method poses a complex problem involving phase transition and multi-phase flow of gas and water. The evolution of hydrate dissociation from the solid phase to gas and liquid phases in a hydrate reservoir is a dynamic process incorporating pore structure and multi-phase seepage. The solid–gas-liquid phase dissociation of NGH affects reservoir seepage properties by altering the micropore structure of the hydrate-bearing sediments. This study, based on the lattice Boltzmann method of modeling fluids flow, clearly demonstrates the micropore-scale changes in pressure and heat transfer that take place during hydrate dissociation. Pore-scale heterogeneity is found to influence the complex development of hydrates in a porous clayey silt medium during dissociation. The effect of hydrate, gas and water saturation on the evolution of relative permeability is identified, and the relationship between relative permeability and hydrate saturation during hydrate dissociation is quantified. These findings provide theoretical support for the implementation of marine natural gas hydrate production testing and future commercial production in China.

A Data Assimilation Methodology to Analyze the Unsaturated Seepage of an Earth–Rockfill Dam Using Physics-Informed Neural Networks Based on Hybrid Constraints

Data assimilation for unconfined seepage analysis has faced significant challenges due to hybrid causes, such as sparse measurements, heterogeneity of porous media, and computationally expensive forward models. To address these bottlenecks, this paper introduces a physics-informed neural network (PINN) model to resolve the data assimilation problem for seepage analysis of unsaturated earth–rockfill dams. This strategy offers a solution that decreases the reliance on numerical models and enables an accurate and efficient prediction of seepage parameters for complex models in the case of sparse observational data. For the first attempt in this study, the observed values are obtained by random sampling of numerical solutions, which are then contributed to the synchronous constraints in the loss function by informing both the seepage control equations and boundary conditions. To minimize the effects of sharp gradient shifts in seepage parameters within the research domain, a residual adaptive refinement (RAR) constraint is introduced to strategically allocate training points around positions with significant residuals in partial differential equations (PDEs), which could facilitate enhancing the prediction accuracy. The model’s effectiveness and precision are evaluated by analyzing the proposed strategy against the numerical solutions. The results indicate that even with limited sparse data, the PINN model has great potential to predict seepage data and identify complex structures and anomalies inside the dam. By incorporating coupling constraints, the validity of our PINN model could lead to theoretically viable applications of hydrogeophysical inversion or multi-parameter seepage inversion. The results show that the proposed framework can predict the seepage parameters for the entire research domain with only a small amount of observation data. Furthermore, with a small amount of observation data, PINNs are able to obtain more accurate results than purely data-driven DNNs.

Quantifying the impact of geological and construction factors on hydraulic fracture dynamics in heterogeneous rock layers using the phase field method

Hydraulic fracturing, a pivotal practice for optimizing development in tight oil reservoirs, encounters challenges in accurately predicting propagation paths within heterogeneous rock formations. Existing phase models often overlook the influence of complex formations, especially in porous media with heterogeneous characteristics. Addressing this gap, we present a novel phase field method aligned with on-site practices. This innovative approach considers cracks, bedding planes, and faults as heterogeneous structures, integrating directional physical and mechanical properties. The key innovation lies in constructing assignment functions to characterize mechanical and seepage parameters of the rock matrix. Anchored in pore elasticity theory and the principle of energy minimization, we establish and validate a hydraulic coupled phase field model through plaster experiments. This model not only corrects the oversight of formation heterogeneity but also provides a comprehensive analysis of the impact of physical and construction parameters on crack propagation. The study extends to numerical simulation studies on three typical heterogeneous rock layers—natural fractures, bedding planes, and faults. Utilizing indicators like fracture pressure, crack extension length, and damage area, a random forest algorithm quantifies the degree of influence of each factor on fracturing. Our results underscore varying impacts from geological factors (natural fractures, bedding angle, stress difference, elastic modulus, matrix porosity, and permeability) and construction factors (cluster spacing, perforation length, fracturing fluid viscosity, displacement, well spacing, and perforation opening) on the fracturing effect of heterogeneous rock layers. In conclusion, our proposed phase field framework demonstrates predictive capability across diverse heterogeneous situations. This innovative model not only rectifies past oversights but also offers insights unattainable through traditional experimental testing, significantly advancing our understanding of hydraulic fracture dynamics.

Research on Fluid–Solid Coupling Mechanism around Openhole Wellbore under Transient Seepage Conditions

Hydraulic fracturing is one of the most important enhanced oil recovery technologies currently used to develop unconventional oil and gas reservoirs. During hydraulic fracture initiation, fluid seeps into the reservoir rocks surrounding the wellbore, inducing rock deformation and changes in the stress field. Analyzing the fluid–solid coupling mechanism around the wellbore is crucial to the construction design of fracturing technologies such as pulse fracturing and supercritical carbon dioxide fracturing. In this study, a new transient fluid–solid coupling model, capable of simulating the pore pressure field and effective stress field around the wellbore, was established based on the Biot consolidation theory combined with the finite difference method. The numerical results are in excellent agreement with the analytical solutions, indicating the reliability of the model and the stability of the computational approach. Using this model, the influence of seepage parameters and reservoir properties on the fluid–solid coupling around the open-hole wellbore was investigated. The simulation results demonstrate that, during wellbore pressurization, significant changes occur in the pore pressure field and effective stress field near the wellbore. The fluid–solid coupling effect around the wellbore returns to its initial state when the distance exceeds four times the radius away from the wellbore. As the fluid viscosity and wellbore pressurization rate decrease, the pore pressure field and effective circumferential stress (ECS) field around the wellbore become stronger. Adjusting the fluid viscosity and wellbore pressurization rate can control the effect of seepage forces on the rock skeleton during wellbore fluid injection. For the same injection conditions, rocks with q higher Young’s modulus and Poisson’s ratio exhibit stronger pore pressure fields and ECS fields near the wellbore. This model furnishes a dependable numerical framework for examining the fluid–solid coupling mechanism surrounding the open-hole wellbore in the initiation phase of hydraulic fractures.

Fractal mechanical model of variable mass seepage in karst collapse column of mine

Currently, the study of karst collapse column water inrush mechanism often ignores the effect of pore structure, and the traditional fractal seepage model ignores the effect of nonlinear seepage velocity field on model permeability. In order to solve this problem, the fractal seepage theory is combined with variable mass seepage theory, and the influence of seepage velocity field on model permeability is considered. The fractal seepage model of the third flow field of the settling column is established and improved, and the influence of different pore structure parameters and nonlinear seepage parameters on the macroscopic seepage of the settling column is analyzed.

A new approach for seepage parameter inversion of earth–rockfill dams based on an improved sparrow search algorithm

This paper introduces a novel seepage parameter inversion method for earth–rockfill dams. The method utilizes pore water pressure data and employs a radial basis function (RBF) neural network as a surrogate model, which is optimized with the improved chaos sparrow search algorithm (ICSSA) using a hybrid strategy. The improved surrogate model (ICSSA–RBF) establishes a nonlinear relationship between the seepage parameter and pore water pressure. Unlike the original algorithm, the algorithm proposed in this paper can avoid three principal problems: the optimization search falling into a local optimal value, the population diversity decreasing during the iteration process, and the RBF neural network being prone to overfitting. The ICSSA, which is proficient in recognizing an objective function's significant values, is also chosen for identifying the parameters. To validate the effectiveness of the proposed approach, four classical test functions, a numerical model, and an actual engineering project are considered for the comparative analysis. The study outcomes reveal that ICSSA–RBF exhibits an exceptional level of prediction accuracy, with a mean relative error of less than 5‰. The findings also affirm the potential of the proposed approach in parameter identification and its superiority in facilitating the evaluation of seepage parameters in earth–rockfill dams.

Sensitivity Analysis of Multi‐phase Seepage Parameters Affecting the Clayey Silt Hydrate Reservoir Productivity in the Shenhu Area, South China Sea

AbstractNatural gas hydrate (NGH) is an important future resource for the 21st century and a strategic resource with potential for commercial development in the third energy transition. It is of great significance to accurately predict the productivity of hydrate‐bearing sediments (HBS). The multi‐phase seepage parameters of HBS include permeability, porosity, which is closely related to permeability, and hydrate saturation, which has a direct impact on hydrate content. Existing research has shown that these multi‐phase seepage parameters have a great impact on HBS productivity. Permeability directly affects the transmission of pressure‐drop and discharge of methane gas, porosity and initial hydrate saturation affect the amount of hydrate decomposition and transmission process of pressure‐drop, and also indirectly affect temperature variation of the reservoir. Considering the spatial heterogeneity of multi‐phase seepage parameters, a depressurization production model with layered heterogeneity is established based on the clayey silt hydrate reservoir at W11 station in the Shenhu Sea area of the South China Sea. Tough + Hydrate software was used to calculate the production model; the process of gas production and seepage parameter evolution under different multi‐phase seepage conditions were obtained. A sensitivity analysis of the parameters affecting the reservoir productivity was conducted so that: (a) a HBS model with layered heterogeneity can better describe the transmission process of pressure and thermal compensation mechanism of hydrate reservoir; (b) considering the multi‐phase seepage parameter heterogeneity, the influence degrees of the parameters on HBS productivity were permeability, porosity and initial hydrate saturation, in order from large to small, and the influence of permeability was significantly greater than that of other parameters; (c) the production potential of the clayey silt reservoir should not only be determined by hydrate content or seepage capacity, but also by the comprehensive effect of the two; and (d) time scales need to be considered when studying the effects of changes in multi‐phase seepage parameters on HBS productivity.

Inversion of the Seepage Parameters of Earth/Rockfill Dams Considering the Coupling Effect of Seepage and Thermal Transfer

The estimation of inversion parameters for seepage models is very important for ensuring the safety of earth/rockfill dams. In most existing studies, only hydraulic characteristics have been determined based on seepage pressure or discharge observation information, which may result in inversion results that do not accurately characterize the true properties of dam materials. In this paper, an advanced parameter inversion method considering the coupling effect of seepage and thermal transfer is proposed. A seepage–thermal transfer coupled finite element model is established, and hydraulic head and temperature data of monitoring points are obtained through the forward simulation method. The entropy weight (EW) method is used to preprocess the hydraulic head and temperature data, and a universal kriging (UK) surrogate model is established to replace the time-consuming finite element simulations. The multi-island genetic algorithm (MIGA) is applied to find the optimal solution, thereby obtaining the inversion results. The effectiveness and accuracy of the proposed method are verified through laboratory tests involving seepage and thermal transfer monitoring of a core rockfill dam. Joint inversion based on temperature and hydraulic head observation information can result in improvement in the accuracy of the inversion results.

Productivity Equation of Fractured Vertical Well with Gas–Water Co-Production in High-Water-Cut Tight Sandstone Gas Reservoir

Due to the high water saturation in high-water-cut tight sandstone gas reservoirs, factors such as threshold pressure gradient (TPG) and stress sensitivity (SS) cannot be overlooked in terms of their impact on seepage parameters. Therefore, this paper primarily investigates the seepage mechanisms in tight, high-water-cut sandstone gas reservoirs. While considering the influence of water saturation on various seepage mechanisms, it establishes a gas well productivity equation under stable seepage conditions and presents an analysis of the influencing factors. In a comparison of the unobstructed flow rates calculated using the productivity equation developed in this paper with those obtained from conventional gas well productivity equations and actual gas well productivity tests, the new equation demonstrates smaller errors. This provides a theoretical basis for evaluating productivity and making rational production allocation decisions in high-water-cut tight sandstone gas reservoirs.

Effects of Dipping and Folded Structure on Gas Production from Hydrate-Bearing Sediments

Summary Due to a dipping and folded structure, hydrate-bearing sediments (HBS) have obvious fluctuation characteristics, and the internal temperature and pressure of HBS are unevenly distributed. Subsequently, gas and water production of natural gas hydrate (NGH) is affected. When using a numerical simulation method to predict effectively the productivity of HBS, it is necessary to establish a conceptual model that considers the formation fluctuation. However, few reported studies accurately describe the fluctuation characteristics of HBS in numerical simulation models. Therefore, the spatial evolution of gas production, water production, and seepage parameters of each model was compared by establishing the initial temperature and pressure model of each representative model pair, using the TOUGH + HYDRATE (T + H) code for a long-time simulation; the production process of gas and water and spatial evolution of seepage parameters of each model were compared; and then the spatial evolution of gas production, water production, and seepage parameters of the different dipping/folded HBS was obtained. The spatial evolution of water production and seepage parameters for different dipping/folded HBS is obtained. (a) The dipping and folded structure had an obvious influence on the spatial distribution of the initial temperature and pressure of HBS. (b) The limits of heat supply and seepage capacity of the fluctuating HBS gave lower gas production than in horizontal HBS. There should be more emphasis on heat supply conditions and the formation of secondary hydrates. (c) The additional pore water in fluctuating HBS is not conducive to the discharge of methane. Consequently, the development of improved water blocking measures is significant for the future large-scale production of NGH.

A Semi-Analytical Model for Production Prediction of Deep CBM Wells Considering Gas-Water Two-Phase Flow

The productivity prediction of deep coalbed methane (CBM) wells is significantly influenced by gas-water two-phase flow characteristics and seepage parameters of the fracture network. While numerical simulations offer a comprehensive approach, analytical models are favored for their faster and broader applicability. However, conventional analytical models often oversimplify the complex problem of two-phase seepage equations, leading to substantial errors in dynamic analysis outcomes. Addressing this shortcoming, we establish a gas-water two-phase productivity prediction model for deep CBM reservoirs. This model takes into account the two-phase flow characteristics within the reservoir and fracture network, as well as the stress sensitivity of the reservoir and fractures. Additionally, a modified trilinear flow model characterizes the fractured modification body. By integrating the flowing material balance equation with the Newton Iteration method, we gradually update the seepage model’s nonlinear parameters using the average formation pressure. We also linearize the gas-water two-phase model through successive iterations to derive a semi-analytical solution. The accuracy of the model was verified through comparison with commercial numerical simulation software results and field application. The model also enabled us to scrutinize the influence of reservoir and fracture network parameters on productivity. Our research findings suggest that the semi-analytical solution approach can efficiently address the nonlinear seepage problem of gas-water two-phase flow, enabling quick and accurate prediction of deep CBM well productivity. Moreover, appropriate fracture network parameters are paramount for enhancing the productivity of deep CBM wells. Lastly, during the development of deep CBM reservoirs, it is crucial to control the production pressure difference appropriately to minimize the stress sensitivity impact on production capacity.

A New Approach for Seepage Parameters Inversion Analysis Using Improved Whale Optimization Algorithm and Support Vector Regression

Seepage is the primary cause of dam failures. Conducting regular seepage analysis for dams can effectively prevent accidents from occurring. Accurate and rapid determination of seepage parameters is a prerequisite for seepage calculation in hydraulic engineering. The Whale Optimization Algorithm (WOA) was combined with Support Vector Regression (SVR) to invert the hydraulic conductivity. The good point set initialization method, a cosine-based nonlinear convergence factor, the Levy flight strategy, and the Quasi-oppositional learning strategy were employed to improve WOA. The effectiveness and practicality of Improved Whale Optimization Algorithm (IWOA) were evaluated via numerical experiments. As a case study, the seepage parameters of the Dono Dam located on the Baishui River in China were inversed, adopting the proposed inversion model. The calculated seepage field was reasonable, and the relative error between the simulated head and the measured value at each monitoring point was within 2%. This new inversion method is more feasible and accurate than the existing hydraulic conductivity estimation methods.

The influence of drain pipe location and diameter on seepage through an earth dam

Earth dams are built for various reasons these including storage of water, regulation of water flow, prevention of flooding, and the generation of hydroelectric power. The drain pipes within an earth dam, are considered one of the more important control devices used to reduce the effects of problems caused by seepage. As such, the role of drain pipes against seepage problems in an earth dam, has been studied numerically in this investigation. The effects of drain pipe location and their diameters (50, 75, 100, and 150 mm), were examined using different hydraulic heads. The analysis focuses on the characteristics of relative seepage flow, exit gradient, and factor of safety regarding sliding. A range of models of typical earth dams, with and without drain pipes, have been simulated using Geo-Studio software in SEEP/W and SLOPE/W applications, examining more than 200 different cases. By using the data computed from numerical models, new formulas for predicting the seepage parameters and factors of safety were developed in this study by using the multiple non-linear regression (NLR) approaches. The findings show that the presence of a drain pipe reduces seepage flow and the exit gradient, at the same time increasing the factor of safety. Regarding pipe diameter, the rate of seepage and exit gradient decreased while the factor of safety increased as the diameter of the pipe increased. The factor of safety increased by between 11 and 25% when the drain pipe was placed in an optimal position, allowing for a reduction in seepage flow and exit gradient.

A new coal seam seepage parameter prediction method based on gas pressure recovery curve for adjacent aquifer environment

Gas extraction is the primary approach for safe and efficient coal mining, its final effect depending on the coal seam seepage parameters (coal seam gas pressure and permeability coefficient), which generally reflect the possibility and intensity of gas protrusion. However, this method is limited by the high requirement for measurement of conditions, long duration, and large errors under complicated conditions (e.g., adjacent aquifers). Therefore, this study proposed a new method to accurately obtain the coal seam gas pressure in an adjacent aquifer and introduced an advanced tool for the rapid measurement of coal seepage parameters, which were verified by engineering. Results of the mercury intrusion porosimetry demonstrated that the effective pore percentage of the coal samples was approximately 32.67%, inducing a locally high gas pressure prone zone in the test area. The multi-physical parameter test showed substantial differences in the coal sample properties, pressure distribution, and seepage parameters in the eastern and western regions of the test site. The field engineering verification results of the prediction of gas pressure, showed that the pressure recovery curve method differed from the conventional method by 4–9.6%, but the time required was only 10–50% of the latter. In the prediction of the permeability coefficient, the pressure recovery curve method had an error between 24.63 and 43.32%, and this difference was consistent with the current method when classifying the extraction difficulty. These findings are significant for the determination of gas seepage parameters at coal mines.

Fast inversion method for seepage parameters of core earth-rock dam based on LHS-SSA-MKELM fusion surrogate model

The inversion of seepage parameters is an important research topic in the safety evaluation of earth-rock dams. Core earth-rock dam is a commonly used structural type in earth-rock dams. Most of the existing inversion methods focus on concrete dams, and few of them are aimed at earth-rock dams. These methods have the problems of slow inversion speed or low accuracy. Aiming at the above problems, this paper proposes a novel fast inversion method for the seepage parameters of core earth-rock dams based on the LHS-SSA-MKELM fusion surrogate model. The proposed fusion inversion model optimizes the selection of combination models based on the surrogate model framework, making it more suitable for the inversion calculation of seepage parameters in earth-rock dams. First, based on the seepage theory of earth-rock dams, the finite element numerical simulation model of core earth-rock dam seepage is constructed. The Latin Hypercube Sampling (LHS) method is used to obtain the parameter sample dataset according to the range of the seepage parameters, and the sample dataset is substituted into the finite element model to obtain the corresponding theoretical seepage pressure of different datasets. Then, the Mixed Kernel Extreme Learning Machine (MKELM) is used to establish the mapping relationship between seepage parameters and the theoretical seepage pressure. The MKELM parameters were optimized by using the Sparrow Search Algorithm (SSA) to further improve the accuracy of the surrogate model. Finally, taking the minimum error between the theoretical value and the measured value of the surrogate model as the objective function, the SSA algorithm is used to derive the optimal inversion value of seepage parameters. The results of engineering examples show that the mean absolute percentage error between the measured value of the core earth-rock dam seepage pressure and the simulated value after inversion is only 4.958%. In addition, the average inversion time of the proposed surrogate model is only 6.6 s, which greatly reduces the time-consuming problem of numerical simulation. The proposed method provides a new way for accurate and fast inversion of seepage parameters of core earth-rock dams after long-term operation.