A coal bed acidizing fracturing method

Abstract

The present application relates to the technical field of coal mine gas disaster prevention and coalbed methane development, and particularly relates to a coal seam acidification fracturing method, which uniformly describes the cross-scale flow of acid liquid in coal body fissure and matrix through Brinkman equation, quantifies the surface reaction kinetics of organic acid and carbonate mineral by adopting double membrane theory, establishes a dynamic correlation model of porosity-permeability-specific surface area based on Kozeny-Carman theory, and realizes the two-way real-time feedback of mineral dissolution and pore evolution. The system carries out sensitivity analysis of acid liquid concentration, injection flow rate and pore heterogeneity, reveals the nonlinear response law of the transformation effect and parameters, determines the optimal concentration range and flow rate window, and adopts a segmented injection strategy for high heterogeneity coal seams. The present application can transform the traditional acidification fracturing which relies on experience into a predictable and controllable precision process, provide quantitative basis for on-site injection stopping time judgment, and significantly improve the acidification transformation effect of deep low-permeability coal seams.

Description

Technical Field

[0001] This invention relates to the field of coal mine gas disaster prevention and control and coalbed methane development technology, and in particular to a coal seam acid fracturing method. Background Technology

[0002] In the field of coal mine gas disaster prevention and coalbed methane development, acid fracturing and permeability enhancement technology is a key means to improve the seepage capacity of low-permeability coal seams. This technology injects organic acids into the coal seam to dissolve carbonate minerals such as calcite in the pores and fractures of the coal body, expands the pore throats, and clears the seepage channels, thereby breaking through the technical bottleneck of "injection not being able to penetrate, wetting not being able to seep out" in low-permeability coal seams, improving gas extraction efficiency and reducing the risk of coal and gas outbursts.

[0003] Current acid fracturing technologies largely rely on experience to design key parameters such as acid concentration, injection velocity, and operation time. Due to a lack of precise prediction capabilities regarding the flow, mass transfer, reaction, and structural evolution of acid within the complex pore network of coal, improper configuration of acid concentration and injection velocity parameters is frequently observed in practical engineering. Regarding acid concentration, high concentrations lead to excessively rapid reaction rates, causing premature consumption of acid near the injection port and insufficient deep penetration. Simultaneously, excessive local dissolution triggers non-uniform evolution of the pore structure. Regarding injection velocity, low velocities limit the acid's reach, while high velocities control rapid acid transfer through convection, but delay reaction consumption, making it impossible to accurately match the fracturing range with the coal's geological conditions.

[0004] More importantly, existing acidification simulation methods mostly use sandstone matrix acidification models for oil and gas reservoirs, failing to fully consider the unique fracture-matrix dual-pore structure and heterogeneous pore distribution characteristics of coal bodies, and thus cannot quantitatively characterize the spatiotemporal distribution of acid in the complex pore network of coal bodies and the propagation law of the dissolution front. Summary of the Invention

[0005] The purpose of this invention is to provide a coal seam acid fracturing method to solve the technical problems of existing coal seam acid fracturing technologies, such as the lack of quantitative basis for process parameter design, significant dissolution non-uniformity, and insufficient accuracy of numerical simulation prediction.

[0006] This invention provides a coal seam acid fracturing method, comprising: S1. The mineral composition of the coal body was determined by X-ray diffraction whole-rock analysis to calculate the relative content of calcite as a criterion for the feasibility of acid fracturing. The initial specific surface area was calculated based on the BET model through low-temperature nitrogen adsorption experiments. The initial permeability of the coal body was determined under simulated formation confining pressure conditions by steady-state method or pressure pulse method. The suitability of the coal seam for organic acid fracturing was determined based on whether the relative content of calcite meets the predetermined threshold and whether the initial permeability is lower than the criteria for low-permeability coal seams. S2. Based on the representative coal samples collected from the reservoir adaptation analysis, determine the initial porosity, initial average pore radius, initial specific surface area, coal skeleton density, surface reaction rate constant, effective acid diffusion coefficient, and pore distribution heterogeneity index. S3. Construct a four-field coupled mathematical model system covering deformation field, seepage field, chemical field and structural field. Among them, the flow field adopts the Brinkman equation to uniformly describe the cross-scale flow behavior of acid in coal fractures and matrix. The mass transfer-reaction field adopts the two-film theory to quantify the surface reaction kinetics between organic acid and carbonate minerals in coal. The structural field establishes a porosity-permeability-specific surface area dynamic correlation model based on Kozeny-Carman theory. S4. The coupled equations are solved by spatial discretization and time progression using the finite element method, and acid concentration sensitivity analysis, injection flow rate sensitivity analysis and pore heterogeneity sensitivity analysis are systematically carried out. S5. Based on the results of sensitivity analysis simulation, optimize the acid formulation and injection process parameters in a coordinated manner according to the geological properties of the target coal seam.

[0007] In some embodiments, S1 further includes: acquiring a three-dimensional pore structure image of the coal body through CT scanning, and calculating the pore distribution heterogeneity index based on image processing methods as a key input parameter for subsequent numerical simulation. In some embodiments, the governing equation of the Brinkman equation is expressed as follows:

[0008] in, p Pore ​​pressure, μ The dynamic viscosity of the acid solution. v The seepage velocity vector, K The permeability is dynamically varying with porosity; this equation provides a unified description of high-speed free flow in fractures and low-speed seepage in the matrix.

[0009] In some embodiments, the surface reaction rate R of the two-film theory is expressed as:

[0010] in, k s The surface reaction rate constant is... av Specific surface area C f This refers to the acid concentration. k c The mass transfer coefficient; by adjusting... k s and k c The ratio determines the response control mode, whenk s <<k c When the reaction is controlled, k s >> k c Mass transfer control guides the coordinated design of acid concentration and injection flow rate: enhancing mass transfer rate in reaction control mode and optimizing reactant supply intensity in mass transfer control mode.

[0011] In some embodiments, the dynamic correlation equation between permeability and porosity according to the Kozeny-Carman theory is expressed as:

[0012]

[0013]

[0014] in, K 0、 0、 a v0 These are initial permeability, initial porosity, and initial specific surface area, respectively. K , , av These are real-time parameters; r p0 and r p These represent the initial average pore radius and the real-time evolved average pore radius, respectively; this correlation system enables bidirectional real-time feedback of the evolution of pore structure caused by mineral dissolution to the flow field and the reaction field.

[0015] In some embodiments, the four-field coupling model establishes twelve bidirectional coupling paths between the deformation field, seepage field, chemical field, and structural field, including: The coupling paths include: effective stress acting on the coal skeleton causing mechanical deformation; mechanical deformation changing pore geometry; pore geometry changes feeding back to porosity evolution; porosity changes leading to dynamic permeability updates; permeability changes affecting seepage velocity distribution; seepage channel morphology changing with pore structure; convection-diffusion mass transfer process redistributing acid concentration field; chemical dissolution reactions consuming acid and generating soluble products; solute mass transfer under concentration gradient; solute changes causing local acid concentration fluctuations; concentration field changes feeding back to affect chemical reaction rates; and porosity evolution achieving closed-loop feedback through both chemical reactions and skeleton deformation.

[0016] In some embodiments, in S4, the acid concentration sensitivity analysis is performed by numerical simulation with a set concentration gradient to examine the variation law of the dissolution modification range and uniformity under different acid concentration conditions, to determine that the acid concentration and the modification effect have a non-monotonic relationship and to determine the optimal concentration range. The injection velocity sensitivity analysis revealed the influence mechanism of injection velocity on the propagation morphology and modification range of the dissolution front by numerical experiments with a set velocity gradient, and determined that there is an optimal velocity window for acid fracturing and the critical velocity threshold. Sensitivity analysis of pore heterogeneity simulates the flow and reaction behavior of acid fluid under coal seam conditions with different degrees of heterogeneity by changing the pore distribution heterogeneity index.

[0017] In some embodiments, for highly heterogeneous coal seams where the porosity heterogeneity index exceeds a predetermined threshold, the process parameter co-optimization step employs a segmented injection strategy instead of constant parameter injection, including: The first stage involves injecting a predetermined proportion of total acid at a relatively low flow rate to pre-dissolve the high-permeability channels and establish a uniform flow system. The second stage involves injecting the remaining acid at a relatively high flow rate, utilizing the established flow guidance system to promote the diffusion of the acid into the deep, low-permeability matrix. A simmering reaction time is set between the two stages to ensure that the near-well zone reacts fully before deep modification is carried out.

[0018] In some embodiments, the injection flow rate range for the first stage is 2 × 10⁻⁶. -4 Up to 2.5×10 -4 The injection rate is m / s, and the injection volume is 40% to 50% of the total acid volume. The injection time is controlled at 60 to 80 minutes. The injection flow rate range for the second stage is 5 × 10⁻⁶. -4 Up to 6×10 -4 m / s, injection time controlled between 90 and 120 minutes; The reaction time for well sealing is 20 to 30 minutes.

[0019] In some embodiments, the changes in injection pressure and the seepage status of the borehole are monitored in real time during the construction process. When the injection pressure drops to below a predetermined percentage of the initial pressure or when uniform seepage occurs around the borehole, it is determined to be the time to stop injection.

[0020] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention constructs a digital twin system for the acid fracturing process through a technical route of reservoir adaptation analysis + model parameter calibration + multi-field coupling modeling + sensitivity analysis + process synergistic optimization. This transforms the traditional experience-based black-box operation into a predictable and controllable precision process, significantly improving the scientific nature and reliability of acid fracturing. 2. This invention uses a multi-field coupled model based on the Brinkman equation and the two-film theory to uniformly describe the cross-scale flow and surface reaction dynamics of acid in coal fracture-matrix; and establishes a dynamic correlation model of porosity-permeability-specific surface area based on the Kozeny-Carman theory to realize the bidirectional real-time feedback of the evolution of pore structure caused by mineral dissolution to the flow field and reaction field, overcoming the limitation of traditional models that cannot characterize the dynamic evolution of coal pores. 3. This invention, through a systematic sensitivity analysis of key parameters such as acid concentration, injection flow rate, and pore heterogeneity, reveals the nonlinear response law of acidification modification, determines the existence of an optimal parameter window rather than a simple linear increase in the critical mechanism, avoids the contradiction between excessive local dissolution at high concentrations and insufficient deep penetration at low concentrations, and avoids the drawbacks of high flow rate response lag and low flow rate modification range limitation. 4. This invention targets highly heterogeneous coal seams. Numerical simulation guides the adoption of an optimization strategy that combines low flow rate with extended injection time, or a segmented injection process, to effectively suppress acid flow along dominant channels and promote uniform diffusion of acid into the low-permeability matrix. 5. Based on the dynamic correlation model of porosity-permeability-specific surface area, this invention realizes real-time feedback and updating of coal physical property parameters during acidification. By tracking the advancement morphology of the dissolution front and the evolution field of pore structure, the permeability increase factor can be accurately predicted, providing a quantitative basis for determining the timing of on-site injection cessation. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the coal seam acid fracturing principle of the present invention; Figure 2 This is a schematic diagram illustrating the construction of the multi-field coupling mathematical model of this invention; Figure 3 This is a schematic diagram of the acid concentration sensitivity analysis curve of the present invention; Figure 4 This is a schematic diagram of the injection flow rate sensitivity analysis curve of the present invention; Figure 5 This is a schematic diagram illustrating the influence of pore heterogeneity on the erosion morphology of the present invention. Detailed Implementation

[0023] The following will be based on embodiments of the present invention. Figures 1-4The technical solutions in the embodiments of the present invention will be clearly and completely described together. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0024] Application citation This invention provides an optimization method for coal seam acid fracturing, primarily addressing the technical bottleneck of "inability to inject, lubricate, or seep" faced by low-permeability coal seams rich in carbonate minerals during gas extraction and disaster prevention. This method achieves precise matching between acid fracturing process parameters and coal seam geological conditions by constructing a multi-field coupled numerical model and conducting systematic sensitivity analysis. This transforms the traditional experience-based, black-box operation into a predictable and controllable precision process.

[0025] Example 1 Optimization of acid fracturing process for conventional heterogeneous coal seams.

[0026] This embodiment takes a low-permeability coal seam in a coal mine working face as the research object. The coal seam is located between the roof strata and the floor strata. There is a geostress field inside the coal seam, which is represented by the red downward arrow.

[0027] After collecting representative coal samples from the target working face, the mineral composition of the coal body is first determined by X-ray diffraction whole-rock analysis, and the relative contents of carbonate minerals such as calcite are calculated.

[0028] The specific operating steps are as follows: The collected coal sample is crushed to below 200 mesh. An appropriate amount of powder is placed in the sample cell of an X-ray diffractometer. A Cu-Kα radiation source is used for scanning at 40kV voltage and 40mA current. The scanning angle range is set to 5° to 70°, and the scanning speed is 2° / min. Phase retrieval and quantitative analysis of the diffraction pattern are performed using Jade software. The relative calcite content is calculated as the primary criterion for the feasibility of acid fracturing. When the relative calcite content reaches a predetermined threshold (usually 5% to 15%) and the initial permeability is lower than the low-permeability coal seam judgment standard (usually 0.1mD), the coal seam is deemed suitable for organic acid fracturing stimulation.

[0029] Subsequently, the pore structure characteristics of the coal were determined through low-temperature nitrogen adsorption experiments, and the initial specific surface area was calculated using the BET model. The specific procedures were as follows: after degassing the coal sample under vacuum at 120℃ for 6 hours, a nitrogen adsorption experiment was conducted at 77K using a fully automated specific surface area and pore size analyzer. Adsorption isotherms were measured, and a BET linear plot was plotted. When the correlation coefficient R² was greater than 0.999, the slope and intercept were used to calculate the specific surface area value. The initial permeability of the coal was determined under simulated formation confining pressure (5MPa to 10MPa) using the steady-state method or pressure pulse method. The confining pressure was applied through a triaxial pressure chamber, and helium was used as a tracer gas in the permeability test to eliminate interference from chemical reactions.

[0030] Once it was determined that the coal seam was suitable for acidification modification, a three-dimensional pore structure image of the coal body was obtained by CT scanning. A microfocus computed tomography system was used to perform a 360° rotational scan on the coal sample to reconstruct the three-dimensional pore structure model. The pore distribution heterogeneity index was calculated as a key input parameter for subsequent numerical simulation.

[0031] Based on the representative coal samples obtained in the above steps, the characteristic parameters required for multi-field coupled numerical simulation were determined. Initial porosity was calculated using the BJH method after determining the adsorption isotherm by low-temperature nitrogen adsorption in a relative pressure range of 0.05 to 0.3; the initial average pore radius was determined by taking the weighted average of the pore size distribution curves obtained by mercury intrusion porosimetry; the initial specific surface area was calculated by linear fitting of isothermal adsorption experimental data with the BET model; the coal skeleton density was determined by the gas expansion method; the surface reaction rate constant was determined by indoor acid-rock reaction kinetic experiments under simulated formation temperature (25°C to 60°C) and pressure (5 MPa to 15 MPa). Specifically, thin sections of coal samples were placed in an acid-rock reactor and reacted with organic acids of different concentrations. The change in acid concentration before and after the reaction was determined by titration, and the reaction rate constant was calculated; the effective diffusion coefficient of the acid solution was determined by multiplying the molecular diffusion coefficient by a tortuosity correction factor, typically 0.3 to 0.6, considering the tortuosity effect of the coal pores.

[0032] Construct a mathematical model system that couples the flow, mass transfer, reaction, and structure fields, encompassing deformation field, seepage field, chemical field, and structural field. For example... Figure 2 The model has four core field blocks at its center, including stress field, seepage field, chemical field and structural field. The four fields are surrounded by bidirectional coupling arrows with strip numbers. The bottom of the figure lists five sets of core partial differential equations and two sets of auxiliary evolution relations. The right side is labeled with 1 to 12 coupling mechanism descriptions to characterize the bidirectional coupling relationship and real-time feedback closed-loop mechanism between the four fields.

[0033] The seepage field is uniformly described by the Brinkman equations, which describe the cross-scale flow behavior of acid in coal fractures and matrix. The governing equations are expressed as follows:

[0034] in, p Pore ​​pressure, μ The dynamic viscosity of the acid solution. v The seepage velocity vector, K The permeability is dynamically varying with porosity. This Brinkman equation overcomes the limitation of the traditional Darcy's law, which is only applicable to low-velocity seepage and cannot describe high-velocity free flow in fractures, and also overcomes the limitation of the Navier-Stokes equation, which ignores the seepage resistance of porous media, thus achieving a unified description of high-velocity free flow in fractures and low-velocity seepage in the matrix.

[0035] Chemical field analysis employs the two-film theory to quantify the surface reaction kinetics between organic acids and carbonate minerals in coal. Based on the two-film theory, the surface reaction rate R is expressed as:

[0036] in, k s The surface reaction rate constant is... av Specific surface area C f This refers to the acid concentration. k c The mass transfer coefficient; by adjusting... k s and k c The ratio determines the response control mode, when k s <<k c When the reaction is controlled, k s >> k c Mass transfer control is used to guide the coordinated design of acid concentration and injection flow rate. The criteria for reaction control mode and mass transfer control mode are directly used to guide the coordinated design of acid concentration and injection flow rate. That is, in reaction control mode, the mass transfer rate is enhanced by increasing the injection flow rate, and in mass transfer control mode, the reactant supply intensity is enhanced by optimizing the acid concentration.

[0037] A dynamic correlation model of porosity, permeability, and specific surface area based on Kozeny-Carman theory was established for the structural field, enabling real-time bidirectional feedback of the evolution of pore structure caused by mineral dissolution to the flow and reaction fields. The dynamic correlation equation between permeability and porosity is expressed as:

[0038]

[0039]

[0040] in, K 0、 0、 a v0 These are initial permeability, initial porosity, and initial specific surface area, respectively. K , , av These are real-time parameters; r p0 and r pThese represent the initial average pore radius and the real-time evolved average pore radius, respectively; this correlation system enables bidirectional real-time feedback of the evolution of pore structure caused by mineral dissolution to the flow field and the reaction field.

[0041] The four-field coupling model establishes a two-way coupling relationship between the deformation field, seepage field, chemical field, and structural field, specifically including twelve coupling paths: The first coupling path is the effective stress acting on the coal skeleton, causing mechanical deformation; The second coupling path involves mechanical deformation altering the pore geometry. The third coupling path is the feedback of pore geometry changes to porosity evolution; The fourth coupling path is the dynamic update of permeability caused by changes in porosity; The fifth coupling path is the influence of permeability changes on seepage velocity distribution; The sixth coupling path is that the morphology of the seepage channels changes with the pore structure; The seventh coupling path is the redistribution of the acid concentration field in the convection-diffusion mass transfer process; The eighth coupling path involves chemical dissolution reactions that consume acid and generate soluble products. The ninth coupling path is the mass transfer of solute under the influence of concentration gradient; The tenth coupling path is that changes in solute lead to fluctuations in local acid concentration; The eleventh coupling path is the feedback effect of concentration field changes on chemical reaction rates; The twelfth coupling path is to achieve closed-loop feedback of porosity evolution through a dual approach of chemical reaction and skeletal deformation.

[0042] Chemical dissolution and porosity changes constitute the core feedback loop of mineral dissolution and pore structure evolution.

[0043] The finite element method (FEM) was used to spatially discretize and temporally advance the coupled equations, establishing a two-dimensional or three-dimensional geometric model including injection holes and the coal seam reservoir. Initial boundary conditions and spatial distributions of physical properties were defined. In the geometric model, injection holes were located in the middle of the coal seam, and acid streamlines were represented by white streamlines indicating their migration path within the coal seam, while blue bubbles represented the distribution of acid within the pores. Based on the constructed numerical model, a three-dimensional sensitivity analysis was conducted on acid concentration, injection velocity, and pore heterogeneity.

[0044] like Figure 3 The acid concentration sensitivity analysis includes H on the left. +The graph shows the change of molar concentration with reaction time and the evolution of porosity with time on the right, along with a 2D plane concentration distribution cloud map and a 3D dissolution morphology map. The five curves in the graph correspond to the working conditions with initial acid concentrations of 3, 4.5, 6, 7.5, and 9 mol / L, respectively. The measuring points are set at different locations from the injection hole to monitor the changes in concentration and porosity.

[0045] Numerical simulations were conducted using a concentration gradient to investigate the variation of the dissolution modification range and uniformity under different acid concentrations. The results show that the relationship between acid concentration and modification effect is non-monotonic, exhibiting an optimal concentration range rather than a simple linear increasing relationship. In the low concentration range (3 to 6 mol / L), the acid rock reaction rate increases with increasing concentration, and the range of dissolution and modification expands accordingly; In the high concentration range (7.5 to 9 mol / L), the reaction rate is too fast, causing the acid to be consumed prematurely near the injection hole, limiting the ability to penetrate deep into the soil. Furthermore, excessive local dissolution can easily lead to non-uniform evolution of the pore structure, which in turn reduces the overall uniformity of the modification.

[0046] Through numerical simulation combined with indoor physical experiments, the optimal acid concentration range for this coal seam was determined to be 5 to 7 mol / L, achieving a dynamic balance between reaction rate and affected area.

[0047] Sensitivity analysis of injection velocity, conducted through numerical experiments with a set velocity gradient, reveals the mechanism by which injection velocity affects the propagation morphology and modification range of the dissolution front. For example... Figure 4 Its layout and Figure 3 Similarly, including the H on the left. + The graphs show the concentration versus time and porosity evolution, along with 2D planar and 3D spatial distribution cloud maps. The injection velocity curves illustrate the spatiotemporal evolution of acid concentration under different flow rates. The five curves correspond to injection velocities of 2×10⁻⁶ and 10⁻⁶ respectively. -4 3×10 -4 4×10 -4 5×10 -4 6×10 -4 Operating conditions at m / s.

[0048] Analysis results indicate that acid fracturing has an optimal flow rate window, rather than simply a matter of higher flow rates being better: under low flow rate conditions (2×10⁻⁶), -4 Up to 3×10 -4 The reaction process at m / s is dominant, with ample time for acid to contact minerals but limited impact range; under high flow rate conditions (5×10 m / s), the reaction process is dominant, with sufficient reaction time between acid and minerals but limited impact range; under high flow rate conditions (5×10 m / s), the reaction process is dominated by the acid-mineral contact reaction, but the reaction time is sufficient but the impact range is limited; under high flow rate conditions (5×10 m / s), the reaction process is dominated by the acid-mineral contact reaction -4 Up to 6×10 -4Convective mass transfer (m / s) controls the rapid transport of acid, but reaction consumption lags behind the advancement of the acid front. Excessive acid flow leads to insufficient contact and reaction time with the minerals. Numerical simulation determined the critical velocity threshold for this coal seam to be 3.5 × 10⁻⁶ m / s. -4 Up to 4.5×10 -4 m / s, the optimal velocity window is 4×10 -4 m / s.

[0049] Based on the sensitivity analysis simulation results, the acid solution formulation and process parameters were optimized synergistically according to the geological properties of the target coal seam. The concentration of organic acid in the acid solution formulation was determined to be 6 mol / L based on the optimal concentration range; the injection process parameters included the injection flow rate and injection time, with the injection flow rate determined to be 4 × 10⁻⁶ based on the optimal flow rate window. -4 The injection speed is m / s, and the injection time is determined to be 120 to 180 minutes based on the reasonable range determined by simulation. During construction, the changes in injection pressure and the seepage status of the borehole are monitored in real time. When the injection pressure drops to below 60% to 70% of the initial pressure or when uniform seepage occurs around the borehole, it is determined to be the time to stop injection, so as to achieve precise matching between the acidizing modification range and the geological conditions of the coal body.

[0050] Example 2 Optimization of segmented injection process in highly heterogeneous coal seams.

[0051] This embodiment focuses on the implementation details of the segmented injection process for coal seam conditions with high heterogeneity. When the coal body porosity heterogeneity index exceeds a predetermined threshold, typically 0.4 to 0.5, the process parameters are optimized as follows.

[0052] In sensitivity analysis, the focus is on examining the impact of heterogeneity on the dissolution morphology. For example... Figure 5 The figure comprises five columns of images. Red arrows at the bottom indicate increasing heterogeneity, ranging from uniform to random. Each column contains an upward concentration field distribution map and a downward porosity field distribution map. A two-color scale on the right represents H... + The concentration and porosity ranges visually demonstrate the spatial distribution characteristics of acid flow and mineral dissolution under different porosity distribution heterogeneity conditions. When the porosity distribution heterogeneity index increases from 0.1 to 0.6, the acid is more likely to form dendritic or finger-like dominant dissolution channels along high-permeability channels, significantly reducing the overall uniformity of the modification. The concentration field and porosity field exhibit strong coupling characteristics, forming a modification blind zone with strong main channels and weak edges.

[0053] For this highly heterogeneous coal seam, a segmented injection strategy was adopted instead of constant parameter injection. The first stage used a relatively low flow rate (2×10⁻⁶). -4 Up to 2.5×10 -4Injecting 40% to 50% of the total acid volume at a flow rate of 5 × 10 m / s is used to pre-dissolve high-permeability channels and establish a uniform flow system. The injection time is controlled at 60 to 80 minutes. This stage focuses on ensuring the acid fully reacts with minerals in the near-wellbore high-permeability zone, gradually expanding pore throats and clearing blocked channels. The second stage uses a relatively high flow rate (5 × 10 m / s). -4 Up to 6×10 - 4 Inject the remaining acid at a rate of (m / s), utilizing the established flow system from the first stage to promote acid diffusion into the deep, low-permeability matrix. The injection time is controlled between 90 and 120 minutes. During this stage, guided by the cleared channels, the acid effectively enters the deep matrix and reacts with the minerals. A 20-30 minute well-shutting reaction time is set between the two stages to ensure sufficient reaction in the near-wellbore area before deep stimulation. This allows the reaction products from the first stage to fully dissolve and be discharged with the flowback fluid, preventing product accumulation from affecting the deep stimulation effect. This synergistic optimization strategy effectively suppresses acid cross-flow and significantly improves the volume of deep matrix stimulation and the overall connectivity of the seepage network.

[0054] Example 3 Indoor physical simulation experiments to verify and evaluate the process effect.

[0055] This embodiment verifies the prediction accuracy of the multi-field coupling model and examines the effectiveness of the optimized process through indoor physical simulation experiments. A visualization experiment of coal sample acid fracturing is set up, including a true triaxial loading experiment, a micro-CT online scanning experiment, and an acid-rock dissolution experiment.

[0056] The true triaxial loading experiment used 100mm×100mm×100mm cubic coal sample specimens, placed in a true triaxial pressure testing machine. The difference in principal stresses in the two horizontal directions was set to simulate the tectonic stress environment of the formation, while the overlying strata pressure, equivalent to the burial depth, was applied vertically. The confining pressure range was 5 to 10 MPa. The micro-CT online scanning experiment used a microfocus CT scanning system to monitor the coal sample in real time during the acidification reaction. The scanning resolution was set to 10 to 20 μm, and three-dimensional images were acquired every 30 minutes to track and record the advancement morphology of the dissolution front and the evolution of the pore structure. The acid-rock dissolution experiment was conducted at a reaction vessel temperature of 45℃ and a pressure of 8 MPa. A 6 mol / L organic acid solution was used to react with the coal sample, and the Ca in the reaction solution was determined timed by titration. 2+ Changes in ion concentration are used to quantify the rate of mineral dissolution.

[0057] Multiple control experiments were set up for comparative analysis: The first group used a traditional constant-parameter injection process, with the acid concentration fixed at 9 mol / L and the injection flow rate fixed at 6 × 10⁻⁶. -4 m / s; The second group adopted the simulated and optimized process parameters and segmented injection strategy described in Example 1, with an acid concentration of 6 mol / L and an injection flow rate of 4 × 10⁻⁶. -4 m / s and employs a two-stage segmented injection method; The third group served as a blank control and was not subjected to any acidification treatment.

[0058] Real-time monitoring of the evolution of dissolution morphology using CT scans and comparative analysis show that: The second group of coal samples using the optimized process showed a uniform dissolution and modification morphology with no obvious dominant channels. The matrix dissolution rate was significantly improved, and the areas with increased local porosity exhibited a network pore structure. The dissolution front advanced steadily. In contrast, the first group using the traditional process showed obvious local over-dissolution and insufficient deep modification. An over-dissolution zone was formed near the well, while the deep matrix was hardly modified.

[0059] The final permeability and pore size distribution variation coefficient were measured for each group. The second group showed a permeability increase of 8 to 12 times and a pore size distribution variation coefficient reduced to 0.15 to 0.2, while the first group showed a permeability increase of only 3 to 5 times and a pore size distribution variation coefficient maintained at 0.35 to 0.45. The permeability evolution pattern of the second group showed good consistency with the numerical simulation prediction curve, verifying the accuracy of the multi-field coupling model and the effectiveness of the process optimization method described in this invention.

[0060] Based on experimental verification, for highly heterogeneous coal seams, this can be further extended to a multi-stage stepped injection process, by gradually increasing the flow rate, for example, 2×10 in the first stage. -4 m / s, second stage 3.5×10 -4 m / s, third stage 5×10 -4 The flow rate is measured in m / s, and the acid injection ratio for each stage is rationally allocated, for example, 30%, 40%, and 30%. This, combined with the controlled well-clogging reaction time between the two stages, ensures the smooth advancement of the dissolution front and further improves the uniformity of the stimulation. The injection time for each stage is dynamically adjusted based on numerical simulation predictions to ensure that the acid can fully react with the minerals and establish an effective flow channel under each flow rate condition.

[0061] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0062] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A method for acid fracturing of coal seams, characterized in that, include: S1. The mineral composition of the coal body was determined by X-ray diffraction whole-rock analysis to calculate the relative content of calcite as a criterion for the feasibility of acid fracturing. The initial specific surface area was calculated based on the BET model through low-temperature nitrogen adsorption experiments. The initial permeability of the coal body was determined under simulated formation confining pressure conditions by steady-state method or pressure pulse method. The suitability of the coal seam for organic acid fracturing was determined based on whether the relative content of calcite meets the predetermined threshold and whether the initial permeability is lower than the criteria for low-permeability coal seams. S2. Based on the representative coal samples collected from the reservoir adaptation analysis, determine the initial porosity, initial average pore radius, initial specific surface area, coal skeleton density, surface reaction rate constant, effective acid diffusion coefficient, and pore distribution heterogeneity index. S3. Construct a four-field coupled mathematical model system covering deformation field, seepage field, mass transfer-reaction field and structural field. Among them, the deformation field adopts the Navier equation of elasticity considering pore fluid pressure to describe the mechanical behavior of coal as a porous medium. The seepage field adopts the Brinkman equation to uniformly describe the cross-scale flow behavior of acid in coal fractures and matrix. The mass transfer-reaction field adopts the two-film theory to quantify the surface reaction kinetics between organic acid and carbonate minerals in coal. The structural field establishes a dynamic correlation model of porosity-permeability-specific surface area based on Kozeny-Carman theory. S4. The coupled equations are solved by spatial discretization and time progression using the finite element method, and acid concentration sensitivity analysis, injection flow rate sensitivity analysis and pore heterogeneity sensitivity analysis are systematically carried out. S5. Based on the results of sensitivity analysis simulation, optimize the acid formulation and injection process parameters in a coordinated manner according to the geological properties of the target coal seam.

2. The method according to claim 1, characterized in that, S1 further includes: acquiring three-dimensional pore structure images of coal through CT scanning, and calculating the pore distribution heterogeneity index based on image processing methods, which serves as a key input parameter for subsequent numerical simulations.

3. The method according to claim 1, characterized in that, The governing equations of the Brinkman equations are expressed as follows: in, p Pore ​​pressure, μ The dynamic viscosity of the acid solution. v The seepage velocity vector, K The permeability is dynamically varying with porosity; this equation provides a unified description of high-speed free flow in fractures and low-speed seepage in the matrix.

4. The method according to claim 1, characterized in that, The surface reaction rate R in the two-film theory is expressed as: in, k s The surface reaction rate constant is... av Specific surface area C f This refers to the acid concentration. k c The mass transfer coefficient; by adjusting... k s and k c The ratio determines the response control mode, when k s <<k c When the reaction is controlled, k s >> k c Mass transfer control guides the coordinated design of acid concentration and injection flow rate: enhancing mass transfer rate in reaction control mode and optimizing reactant supply intensity in mass transfer control mode.

5. The method according to claim 1, characterized in that, The dynamic correlation equation between permeability and porosity in the Kozeny-Carman theory is expressed as follows: in, K 0、 0、 a v0 These are initial permeability, initial porosity, and initial specific surface area, respectively. K , , av These are real-time parameters; r p0 and r p These represent the initial average pore radius and the real-time evolved average pore radius, respectively; this correlation system enables bidirectional real-time feedback of the evolution of pore structure caused by mineral dissolution to the flow field and the reaction field.

6. The method according to claim 1, characterized in that, The four-field coupling model establishes twelve bidirectional coupling paths between the stress field, chemical field, seepage field, and structural field, including: The coupling paths include: effective stress acting on the coal skeleton causing mechanical deformation; mechanical deformation changing pore geometry; pore geometry changes feeding back to porosity evolution; porosity changes leading to dynamic permeability updates; permeability changes affecting seepage velocity distribution; seepage channel morphology changing with pore structure; convection-diffusion mass transfer process redistributing acid concentration field; chemical dissolution reactions consuming acid and generating soluble products; solute mass transfer under concentration gradient; solute changes causing local acid concentration fluctuations; concentration field changes feeding back to affect chemical reaction rates; and porosity evolution achieving closed-loop feedback through both chemical reactions and skeleton deformation.

7. The method according to claim 1, characterized in that, In S4, the acid concentration sensitivity analysis is carried out by numerical simulation with a set concentration gradient to examine the variation law of the dissolution modification range and uniformity under different acid concentration conditions, to determine that the acid concentration and the modification effect have a non-monotonic relationship and to determine the optimal concentration range. The injection velocity sensitivity analysis revealed the influence mechanism of injection velocity on the propagation morphology and modification range of the dissolution front by numerical experiments with a set velocity gradient, and determined that there is an optimal velocity window for acid fracturing and the critical velocity threshold. Sensitivity analysis of pore heterogeneity simulates the flow and reaction behavior of acid fluid under coal seam conditions with different degrees of heterogeneity by changing the pore distribution heterogeneity index.

8. The method according to claim 1, characterized in that, For highly heterogeneous coal seams where the porosity heterogeneity index exceeds a predetermined threshold, the process parameter co-optimization step employs a segmented injection strategy instead of constant parameter injection, including: The first stage involves injecting a predetermined proportion of total acid at a relatively low flow rate to pre-dissolve the high-permeability channels and establish a uniform flow system. The second stage involves injecting the remaining acid at a relatively high flow rate, utilizing the established flow guidance system to promote the diffusion of the acid into the deep, low-permeability matrix. A simmering reaction time is set between the two stages to ensure that the near-well zone reacts fully before deep modification is carried out.

9. The method according to claim 7, characterized in that, The injection flow rate range for the first stage is 2×10. -4 Up to 2.5×10 -4 The injection rate is m / s, and the injection volume is 40% to 50% of the total acid volume. The injection time is controlled at 60 to 80 minutes. The injection flow rate range for the second stage is 5 × 10⁻⁶. -4 Up to 6×10 -4 m / s, injection time controlled between 90 and 120 minutes; The reaction time for well sealing is 20 to 30 minutes.

10. The method according to claim 1, characterized in that, During construction, the changes in injection pressure and the water seepage in the borehole are monitored in real time. When the injection pressure drops below a predetermined percentage of the initial pressure or when uniform water seepage occurs around the borehole, it is determined to be the time to stop injection.

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