Low-cost preparation of mesoporous silica with high pore volume

Mesoporous silica materials with high pore volume were successfully prepared by the chemical precipitation method, with water glass and a biodegradable nonionic surfactant polyethylene glycol （PEG）. The obtained materials were characterized by transmission electron microscopy （TEM）, scanning electron microscopy （SEM）, thermo gravimetric analyzer and differential scanning calorimetry （TG-DSC）, nitrogen adsorption-desorption measurements, and X-ray diffraction （XRD）. The results showed that the changes of the pore parameters depended on both the surfactant content and heat treatment temperature. When the content of PEG was 10wt% and the obtained PEG/SiO2 composite was heated at 600℃, the mesoporous silica with a pore volume of 2.2 cma/g, a BET specific surface area of 361.55 m^2/g, and a diameter of 2-4 μm could be obtained. The obtained mesoporous silica materials have potential applications in the fields of paint and plastic, as thickening, reinforcing, and flatting agents.

Synthesis of Macro-Mesostructured γ-Al_2O_3 with Large Pore Volume and High Surface Area by a Facile Secondary Reforming Method

Through improving the aging process during synthesis of the support, γ-Al2O3 with large pore volume and high surface area was synthesized by a facile secondary reforming method. The synthesis parameters, such as the reaction temperature, the first aging temperature and the second aging temperature, were investigated. The textural properties of γ-Al2O3 were characterized by means of N2 adsorption-desorption isotherms, X-ray powder diffractometry （XRD）, scanning electron microscopy （SEM）, Fourier transform infrared （FTIR） spectroscopy and thermogravimetry （TG）. The experimental results indicated that AACH and amorphous A1OOH were the precursors of alumina, which were formed via precipitation from solutions after reaction of aluminum sulphate with ammonium hydrogen carbonate. The precursor nanocrystallites grew and re-assembled during the secondary reforming process, which resulted in an increased pore size and pore volume and a decreased bulk density. The as-synthesized γ-Al2O3 materials featured meso/macroporosity, large pore volume （2.175 cm^3/g）, high surface area （237.8 m^2/g）, and low bulk density （0.284 g/mL）.

Synthesis of silica powder with high pore volume by skeleton reinforcement

In this paper,a method composed of gelation of basic skeleton(first step)and skeleton reinforcement process(second step)was introduced to synthesize silica powder with high pore volume through the reaction between water glass and sulfuric acid.No organic solvents were involved in the entire preparation process and the final product was collected by spray drying.The effect of concentration of base solution,gelation point p H value and skeleton reinforcement time on the BET specific surface area and pore volume of the prepared silica powder were investigated intensively.The results show that,a basic skeleton with good dispersibility and high porosity was obtained when the concentration of base solution was 0.1 mol·L^(-1) and the gelation p H value reached 6.5.Then the basic skeleton grew into a more uniform porous structure after 30 min skeleton reinforcement.Under these optimum conditions,silica powder prepared by skeleton reinforcement method had a BET specific surface area of 358.0 m^(2)·g^(-1),and its pore volume reached 2.18 cm^(3)·g^(-1),which was much higher than that of prepared by skeleton-free method(1.62 cm^(3)·g^(-1))and by direct gelation method(0.31 cm^(3)·g^(-1)).

Estimating pore volume compressibility by spheroidal pore modeling of digital rocks

The real pores in digital cores were simplified into three abstractive types,including prolate ellipsoids,oblate ellipsoids and spheroids.The three-dimensional spheroidal-pore model of digital core was established based on mesoscopic mechanical theory.The constitutive relationship of different types of pore microstructure deformation was studied with Eshelby equivalent medium theory,and the effects of pore microstructure on pore volume compressibility under elastic deformation conditions of single and multiple pores of a single type and mixed types of pores were investigated.The results showed that the pore volume compressibility coefficient of digital core is closely related with porosity,pore aspect ratio and volumetric proportions of different types of pores.(1)The compressibility coefficient of prolate ellipsoidal pore is positively correlated with the pore aspect ratio,while that of oblate ellipsoidal pore is negatively correlated with the pore aspect ratio.(2)At the same mean value of pore aspect ratio satisfying Gaussian distribution,the more concentrated the range of pore aspect ratio,the higher the compressibility coefficient of both prolate and oblate ellipsoidal pores will be,and the larger the deformation under the same stress condition.(3)The pore compressibility coefficient increases with porosity.(4)At a constant porosity value,the higher the proportion of oblate ellipsoidal and spherical pores in the rock,the more easier for the rock to deform,and the higher the compressibility coefficient of the rock is,while the higher the proportion of prolate ellipsoidal pores in the rock,the more difficult it is for rock to deform,and the lower the compressibility coefficient of the rock is.By calculating pore compressibility coefficient of ten classical digital rock samples,the presented analytical elliptical-pore model based on real pore structure of digital rocks can be applied to calculation of pore volume compressibility coefficient of digital rock sample.

Prediction of pore volume compressibility by a new non-linear equation in carbonate reservoirs

Pore volume compressibility is an essential parameter in reservoir studies,as it plays a major role in recovery mechanisms.Over the past decades,many attempts have been made to establish a link between the pore compressibility and the porosity and other mechanical properties of the rock.Some scholars introduced analytical correlations between pore compressibility and rock mechanical properties,while others developed empirical formulas for estimating pore compressibility based on a porosity calculated by comparing nonlinear models to laboratory data.In this study,pore volume compressibility is measured on 55 carbonate samples and then applied to derive an empirical relationship between pore compressibility and porosity at each stress step,which is useful for predicting pore compressibility based on initial porosity.We take the net stress effect into account and derive an empirical correlation based on net effective stress and initial porosity to predict pore compressibility.In the end,we compare the measured pore compressibility with that predicted by the derived correlation and other non-leaner models,which indicates that the newly proposed non-linear equation outperforms those available in literature。

An adaptive physics-informed deep learning method for pore pressure prediction using seismic data

Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum engineering.Recent deep learning technique has been receiving more interest due to the great potential to deal with pore pressure prediction.However,most of the traditional deep learning models are less efficient to address generalization problems.To fill this technical gap,in this work,we developed a new adaptive physics-informed deep learning model with high generalization capability to predict pore pressure values directly from seismic data.Specifically,the new model,named CGP-NN,consists of a novel parametric features extraction approach(1DCPP),a stacked multilayer gated recurrent model(multilayer GRU),and an adaptive physics-informed loss function.Through machine training,the developed model can automatically select the optimal physical model to constrain the results for each pore pressure prediction.The CGP-NN model has the best generalization when the physicsrelated metricλ=0.5.A hybrid approach combining Eaton and Bowers methods is also proposed to build machine-learnable labels for solving the problem of few labels.To validate the developed model and methodology,a case study on a complex reservoir in Tarim Basin was further performed to demonstrate the high accuracy on the pore pressure prediction of new wells along with the strong generalization ability.The adaptive physics-informed deep learning approach presented here has potential application in the prediction of pore pressures coupled with multiple genesis mechanisms using seismic data.

Investigation of pore geometry influence on fluid flow in heterogeneous porous media:A pore-scale study

Brazilian pre-salt reservoirs are renowned for their intricate pore networks and vuggy nature,posing significant challenges in modeling and simulating fluid flow within these carbonate reservoirs.Despite possessing excellent petrophysical properties,such as high porosity and permeability,these reservoirs typically exhibit a notably low recovery factor,sometimes falling below 10%.Previous research has indicated that various enhanced oil recovery(EOR)methods,such as water alternating gas(WAG),can substantially augment the recovery factor in pre-salt reservoirs,resulting in improvements of up to 20%.Nevertheless,the fluid flow mechanism within Brazilian carbonate reservoirs,characterized by complex pore geometry,remains unclear.Our study examines the behavior of fluid flow in a similar heterogeneous porous material,utilizing a plug sample obtained from a vugular segment of a Brazilian stromatolite outcrop,known to share analogies with certain pre-salt reservoirs.We conducted single-phase and multi-phase core flooding experiments,complemented by medical-CT scanning,to generate flow streamlines and evaluate the efficiency of water flooding.Subsequently,micro-CT scanning of the core sample was performed,and two cross-sections from horizontal and vertical plates were constructed.These cross-sections were then employed as geometries in a numerical simulator,enabling us to investigate the impact of pore geometry on fluid flow.Analysis of the pore-scale modeling and experimental data unveiled that the presence of dead-end pores and vugs results in a significant portion of the fluid remaining stagnant within these regions.Consequently,the injected fluid exhibits channeling-like behavior,leading to rapid breakthrough and low areal swept efficiency.Additionally,the numerical simulation results demonstrated that,irrespective of the size of the dead-end regions,the pressure variation within the dead-end vugs and pores is negligible.Despite the stromatolite's favorable petrophysical properties,including relatively high porosity and permeability,as well as the presence of interconnected large vugs,the recovery factor during water flooding remained low due to early breakthrough.These findings align with field data obtained from pre-salt reservoirs,providing an explanation for the observed low recovery factor during water flooding in such reservoirs.

The impact of heterogeneity and pore network characteristics on single and multi-phase fluid propagation in complex porous media:An X-ray computed tomography study

This study investigates the impact of pore network characteristics on fluid flow through complex and heterogeneous porous media,providing insights into the factors affecting fluid propagation in such systems.Specifically,high-resolution or micro X-ray computed tomography(CT)imaging techniques were utilized to examine outcrop stromatolite samples of the Lagoa Salgada,considered flow analogous to the Brazilian Pre-salt carbonate reservoirs.The petrophysical results comprised two distinct stromatolite depositional facies,the columnar and the fine-grained facies.By generating pore network model(PNM),the study quantified the relationship between key features of the porous system,including pore and throat radius,throat length,coordination number,shape factor,and pore volume.The study found that the less dense pore network of the columnar sample is typically characterized by larger pores and wider and longer throats but with a weaker connection of throats to pores.Both facies exhibited less variability in the radius of the pores and throats in comparison to throat length.Additionally,a series of core flooding experiments coupled with medical CT scanning was designed and conducted in the plug samples to assess flow propagation and saturation fields.The study revealed that the heterogeneity and presence of disconnected or dead-end pores significantly impacted the flow patterns and saturation.Two-phase flow patterns and oil saturation distribution reveal a preferential and heterogeneous displacement that mainly swept displaced fluid in some regions of plugs and bypassed it in others.The relation between saturation profiles,porosity profiles,and the number of fluid flow patterns for the samples was evident.Only for the columnar plug sample was the enhancement in recovery factor after shifting to lower salinity water injection(SB)observed.

Modeling of multiphase flow in low permeability porous media:Effect of wettability and pore structure properties

Multiphase flow in low permeability porous media is involved in numerous energy and environmental applications.However,a complete description of this process is challenging due to the limited modeling scale and the effects of complex pore structures and wettability.To address this issue,based on the digital rock of low permeability sandstone,a direct numerical simulation is performed considering the interphase drag and boundary slip to clarify the microscopic water-oil displacement process.In addition,a dual-porosity pore network model(PNM)is constructed to obtain the water-oil relative permeability of the sample.The displacement efficiency as a recovery process is assessed under different wetting and pore structure properties.Results show that microscopic displacement mechanisms explain the corresponding macroscopic relative permeability.The injected water breaks through the outlet earlier with a large mass flow,while thick oil films exist in rough hydrophobic surfaces and poorly connected pores.The variation of water-oil relative permeability is significant,and residual oil saturation is high in the oil-wet system.The flooding is extensive,and the residual oil is trapped in complex pore networks for hydrophilic pore surfaces;thus,water relative permeability is lower in the water-wet system.While the displacement efficiency is the worst in mixed-wetting systems for poor water connectivity.Microporosity negatively correlates with invading oil volume fraction due to strong capillary resistance,and a large microporosity corresponds to low residual oil saturation.This work provides insights into the water-oil flow from different modeling perspectives and helps to optimize the development plan for enhanced recovery.

Concise extraction and characterization of the pore-throat network in unconventional hydrocarbon reservoirs: A new perspective

In this study,a new image-based method for the extraction and characterization of pore-throat network for unconventional hydrocarbon storage and exploitation is proposed.“Pore-throat solidity”,which is analogous to particle solidity,and a new method for automatic identification of pores and throats in tight sandstone oil reservoirs are introduced.Additionally,the“pore-throat combination”and“pure pore”are defined and distinguished by drawing the cumulative probability curve of the pore-throat solidity and by selecting an appropriate cutoff point.When the discrete grid set is recognized as a pore-throat combination,Legendre ellipse fitting and minimum Feret diameter are used.When the pore and throat grid sets are identified as pure pores,the pore diameter can be directly calculated.Using the new method,the analytical results for the physical parameters and pore radius agree well with most prior studies.The results comparing the maximum ball and the new model could also prove the accuracy of the latter's in micro and nano scales.The new model provides a more practical theoretical basis and a new calculation method for the rapid and accurate evaluation of the complex processes of oil migration.

Study on the evolution of solid–liquid–gas in multi-scale pore methane in tectonic coal

The rich accumulation of methane(CH_(4))in tectonic coal layers poses a significant obstacle to the safe and efficient extraction of coal seams and coalbed methane.Tectonic coal samples from three geologically complex regions were selected,and the main results obtained by using a variety of research tools,such as physical tests,theoretical analyses,and numerical simulations,are as follows:22.4–62.5 nm is the joint segment of pore volume,and 26.7–100.7 nm is the joint segment of pore specific surface area.In the dynamic gas production process of tectonic coal pore structure,the adsorption method of methane molecules is“solid–liquid adsorption is the mainstay,and solid–gas adsorption coexists”.Methane stored in micropores with a pore size smaller than the jointed range is defined as solid-state pores.Pores within the jointed range,which transition from micropore filling to surface adsorption,are defined as gaseous pores.Pores outside the jointed range,where solid–liquid adsorption occurs,are defined as liquid pores.The evolution of pore structure affects the methane adsorption mode,which provides basic theoretical guidance for the development of coal seam resources.

Pore structure and oxygen content design of amorphous carbon toward a durable anode for potassium/sodium-ion batteries

Both sodium-ion batteries(SIBs)and potassium-ion batteries(PIBs)are considered as promising candidates in grid-level energy storage devices.Unfortunately,the larger ionic radii of K+and Na+induce poor diffusion kinetics and cycling stability of carbon anode materials.Pore structure regulation is an ideal strategy to promote the diffusion kinetics and cyclic stability of carbon materials by facilitating electrolyte infiltration,increasing the transport channels,and alleviating the volume change.However,traditional pore-forming agent-assisted methods considerably increase the difficulty of synthesis and limit practical applications of porous carbon materials.Herein,porous carbon materials(Ca-PC/Na-PC/K-PC)with different pore structures have been prepared with gluconates as the precursors,and the amorphous structure,abundant micropores,and oxygen-doping active sites endow the Ca-PC anode with excellent potassium and sodium storage performance.For PIBs,the capacitive contribution ratio of Ca-PC is 82%at 5.0 mV s^(-1) due to the introduction of micropores and high oxygen-doping content,while a high reversible capacity of 121.4 mAh g^(-1) can be reached at 5 A g^(-1) after 2000 cycles.For SIBs,stable sodium storage capacity of 101.4 mAh g^(-1) can be achieved at 2 A g^(-1) after 8000 cycles with a very low decay rate of 0.65%for per cycle.This work may provide an avenue for the application of porous carbon materials in the energy storage field.

Hydrodynamic resistance of pore–throat structures and its effect on shale oil apparent permeability

Oil transport is greatly affected by heterogeneous pore–throat structures present in shale.It is therefore very important to accurately characterize pore–throat structures.Additionally,it remains unclear how pore–throat structures affect oil transport capacity.In this paper,using finite element(FE)simulation and mathematical modeling,we calculated the hydrodynamic resistance for four pore–throat structure.In addition,the influence of pore throat structure on shale oil permeability is analyzed.According to the results,the hydrodynamic resistance of different pore throat structures can vary by 300%.The contribution of additional resistance caused by streamline bending is also in excess of 40%,even without slip length.Fur-thermore,Pore–throat structures can affect apparent permeability by more than 60%on the REV scale,and this influence increases with heterogeneity of pore size distribution,organic matter content,and organic matter number.Clearly,modeling shale oil flow requires consideration of porous–throat structure and additional resistance,otherwise oil recovery and flow capacity may be overestimated.

NMR-based analysis of the effect of moisture migration on sandstone pore structure under alternating wetting and drying conditions

The wetting-drying(W-D)cycle is a type of water–rock interaction.The pore structure of rock,such as shape,size,distribution and pore throat,affects fluid storage and transport.Fractal theory and experimental research on the evolution characteristics of pore damage during the wet-dry erosion process are highly important for determining W-D damage.The mass and velocity of liquid migration are related to the pore size,porosity,fluid properties,etc.Experimental data show that the water absorption quality and velocity in rocks decrease with the number of wet-dry cycles.At the same test time,the mass and velocity of the SI water absorption method are smaller than those of the FI method.Under these two conditions,the amount and rate of water absorption represent the degree of water–rock interaction.Considering the pore evolution during the wet-dry cycling,an equation describing the motion of liquid in porous media was derived based on the imbibition-type separation model.The experimental data are in excellent agreement with the calculated values of the model.Permeability characteristics can affect the area and degree of rock deterioration as well as the development rate of pores and microcracks.Based on the interaction between permeability and pores,quantitative analysis of the weakening process(local damage)of rocks under W-D cycles can provide good reference indicators for evaluating the stability of geotechnical engineering.

A hybrid machine learning optimization algorithm for multivariable pore pressure prediction

Pore pressure is essential data in drilling design,and its accurate prediction is necessary to ensure drilling safety and improve drilling efficiency.Traditional methods for predicting pore pressure are limited when forming particular structures and lithology.In this paper,a machine learning algorithm and effective stress theorem are used to establish the transformation model between rock physical parameters and pore pressure.This study collects data from three wells.Well 1 had 881 data sets for model training,and Wells 2 and 3 had 538 and 464 data sets for model testing.In this paper,support vector machine(SVM),random forest(RF),extreme gradient boosting(XGB),and multilayer perceptron(MLP)are selected as the machine learning algorithms for pore pressure modeling.In addition,this paper uses the grey wolf optimization(GWO)algorithm,particle swarm optimization(PSO)algorithm,sparrow search algorithm(SSA),and bat algorithm(BA)to establish a hybrid machine learning optimization algorithm,and proposes an improved grey wolf optimization(IGWO)algorithm.The IGWO-MLP model obtained the minimum root mean square error(RMSE)by using the 5-fold cross-validation method for the training data.For the pore pressure data in Well 2 and Well 3,the coefficients of determination(R^(2))of SVM,RF,XGB,and MLP are 0.9930 and 0.9446,0.9943 and 0.9472,0.9945 and 0.9488,0.9949 and 0.9574.MLP achieves optimal performance on both training and test data,and the MLP model shows a high degree of generalization.It indicates that the IGWO-MLP is an excellent predictor of pore pressure and can be used to predict pore pressure.

Experimental investigation on coal pore-fracture variation and fractal characteristics synergistically affected by solvents for improving clean gas extraction

Chemical solvents instead of pure water being as hydraulic fracturing fluid could effectively increase permeability and improve clean methane extraction efficiency.However,pore-fracture variation features of lean coal synergistically affected by solvents have not been fully understood.Ultrasonic testing,nuclear magnetic resonance analysis,liquid phase mass spectrometry was adopted to comprehensively analyze pore-fracture change characteristics of lean coal treated by combined solvent(NMP and CS_(2)).Meanwhile,quantitative characterization of above changing properties was conducted using geometric fractal theory.Relationship model between permeability,fractal dimension and porosity were established.Results indicate that the end face fractures of coal are well developed after CS2and combined solvent treatments,of which,end face box-counting fractal dimensions range from 1.1227 to 1.4767.Maximum decreases in ultrasonic longitudinal wave velocity of coal affected by NMP,CS_(2)and combined solvent are 2.700%,20.521%,22.454%,respectively.Solvent treatments could lead to increasing amount of both mesopores and macropores.Decrease ratio of fractal dimension Dsis 0.259%–2.159%,while permeability increases ratio of NMR ranges from 0.1904 to 6.4486.Meanwhile,combined solvent could dissolve coal polar and non-polar small molecules and expand flow space.Results could provide reference for solvent selection and parameter optimization of permeability-enhancement technology.

Water-induced physicochemical and pore changes in limestone for surrounding rock across pressure aquifers

Osmotic water alters the physicochemical properties and internal structures of limestone.This issue is particularly critical in tunnel construction across mountainous regions with aquifers,where pressurized groundwater can destabilize the limestone-based surrounding rock.Thus,systematic research into the physicochemical properties and pore structure changes in the limestone under pressurized water is essential.Additionally,it is essential to develop an interpretable mathematical model to accurately depict how pressurized osmotic water weakens limestone.In this research,a specialized device was designed to simulate the process of osmotic laminar flow within limestone.Then,four main tests were conducted:mass loss,acoustic emission(AE),mercury intrusion porosimetry(MIP),and fluorescence analysis.Experimental results gained from tests led to the development of a“Particle-pore throat-water film”model.Proposed model explains water-induced physicochemical and pore changes in limestone under osmotic pressure and reveals evolutionary mechanisms as pressure increases.Based on experimental results and model,we found that osmotic pressure not only alters limestone composition but also affects pore throats larger than 0.1μm.Furthermore,osmotic pressure expands pore throats,enhancing pore structure uniformity,interconnectivity,and permeability.These effects are observed at a threshold of 7.5 MPa,where cohesive forces within the mineral lattice are surpassed,leading to the breakdown of erosion-resistant layer and a significant increase in hydrochemical erosion.

The Negative Thermal Expansion Property of NdMnO_(3) Based on Pores Effect and Phase Transition

A novel negative thermal expansion(NTE) material NdMnO_(3) was synthesized by solid-state method at 1 523 K. The crystal structure, phase transition, pores effect and negative expansion properties of NdMnO_(3) were investigated by variable temperature X-ray diffraction(XRD), scanning electron microscope(SEM) and variable temperature Raman spectra. The compound exhibits NTE properties in the orderly O' phase crystal structure. When the temperature is from 293 to 759 K, the ceramic NdMnO_(3) shows negative thermal expansion of-4.7×10^(-6)/K. As temperature increases, the ceramic NdMnO_(3) presents NTE property range from 759 to 1 007 K. The average linear expansion coefficient is-18.88×10^(-6)/K. The physical mechanism of NTE is discussed and clarified through experiments.

Free radicals trigger the closure of open pores in lignin-derived hard carbons toward improved sodium-storage capacity

The chemical activation of various precursors is effective for creating additional closed pores in hard carbons for sodium storage.However,the formation mechanism of closed pores under the influence of pore-forming agents is not well understood.Herein,an effective chemical activation followed by a high-temperature self-healing strategy is employed to generate interconnected closed pores in lignin-derived hard carbon(HCs).By systematic experimental design combined with electron paramagnetic res-onance spectroscopy,it can be found that the content of free radicals in the carbon matrix influences the closure of open pores at high temperatures.Excessively high activation temperature(>700 C)leads to a low free radical concentration,making it difficult to achieve self-healing of open pores at high tempera-tures.By activation at 700°C,a balance between pore making and self-healing is achieved in the final hard carbon.A large number of free radicals triggers rapid growth and aggregation of carbon microcrys-tals,blocking pre-formed open micropores and creating additional interconnected closed pores in as-obtained hard carbons.As a result,the optimized carbon anode(LK-700-1300)delivers a high reversible capacity of 330.8 mA h g^(-1) at 0.03 A g^(-1),which is an increase of 86 mA h g^(-1) compared to the pristine lignin-derived carbon anode(L-700-1300),and exhibits a good rate performance(202.1 mA h g^(-1) at 1 A g^(-1)).This work provides a universal and effective guidance for tuning closed pores of hard carbons from otherprecursors.

A novel box-counting method for quantitative fractal analysis of threedimensional pore characteristics in sandstone

Fractal theory offers a powerful tool for the precise description and quantification of the complex pore structures in reservoir rocks,crucial for understanding the storage and migration characteristics of media within these rocks.Faced with the challenge of calculating the three-dimensional fractal dimensions of rock porosity,this study proposes an innovative computational process that directly calculates the three-dimensional fractal dimensions from a geometric perspective.By employing a composite denoising approach that integrates Fourier transform(FT)and wavelet transform(WT),coupled with multimodal pore extraction techniques such as threshold segmentation,top-hat transformation,and membrane enhancement,we successfully crafted accurate digital rock models.The improved box-counting method was then applied to analyze the voxel data of these digital rocks,accurately calculating the fractal dimensions of the rock pore distribution.Further numerical simulations of permeability experiments were conducted to explore the physical correlations between the rock pore fractal dimensions,porosity,and absolute permeability.The results reveal that rocks with higher fractal dimensions exhibit more complex pore connectivity pathways and a wider,more uneven pore distribution,suggesting that the ideal rock samples should possess lower fractal dimensions and higher effective porosity rates to achieve optimal fluid transmission properties.The methodology and conclusions of this study provide new tools and insights for the quantitative analysis of complex pores in rocks and contribute to the exploration of the fractal transport properties of media within rocks.