A low-permeability gas reservoir branch well productivity physical simulation experiment method and device

Abstract

This invention discloses a physical simulation experimental method and apparatus for the productivity of branch wells in low-permeability gas reservoirs. Based on the principle of hydroelectric similarity, a similarity criterion system is constructed to transform the complex seepage field of a branch well in a low-permeability gas reservoir into an easily measurable electric field. This restores the wellbore interference effect and reservoir seepage law, enabling visualized observation of the seepage field and quantitative analysis of productivity. It boasts advantages such as low experimental cost, short cycle, and strong parameter adaptability, and can efficiently complete the sensitivity analysis and optimization design of branch well structural parameters, providing reliable quantitative experimental support for the efficient development of branch wells in low-permeability gas reservoirs.

Description

Technical Field

[0001] This invention relates to the field of production capacity simulation technology, and in particular to a physical simulation experimental method and apparatus for production capacity of a branch well in a low-permeability gas reservoir. Background Technology

[0002] Low-permeability to ultra-low-permeability gas reservoirs are an important replacement area for increasing natural gas reserves and production. Branch well technology can significantly increase the reservoir drainage area and improve the development efficiency of single wells. It is a key technology for the efficient development of this type of gas reservoir. Accurate production prediction and well structure optimization are prerequisites for ensuring development results.

[0003] Currently, numerical simulation is the mainstream method for evaluating and optimizing the production capacity of branch wells. This method is mostly based on idealized seepage mathematical models, which makes it difficult to accurately characterize the complex features of low-permeability gas reservoirs, such as strong heterogeneity, interference effects between multiple branch wells, and wellbore-reservoir coupled seepage. This results in a large deviation between the production capacity prediction results and the actual production data on site, and cannot provide a reliable quantitative basis for well structure optimization.

[0004] Existing physical simulation technologies are mostly adapted to conventional reservoirs or simple well types such as vertical and horizontal wells. For specialized simulation schemes for complex branch wells in low-permeability gas reservoirs, there are generally problems such as high experimental costs, long cycles, and inability to simultaneously achieve visualized observation and accurate quantitative analysis of the seepage field. These problems make it difficult to meet the actual needs of on-site branch well optimization design. Therefore, there is an urgent need to develop an efficient and accurate physical simulation experimental method for the productivity of branch wells in low-permeability gas reservoirs. Summary of the Invention

[0005] This invention provides a physical simulation method and apparatus for the productivity of branch wells in low-permeability gas reservoirs, so as to achieve efficient and accurate simulation of the productivity of branch wells in low-permeability gas reservoirs.

[0006] According to one aspect of the present invention, a physical simulation experimental method for the productivity of a branch well in a low-permeability gas reservoir is provided, comprising:

[0007] Based on a pre-defined similarity criterion system for hydroelectric similarity simulation, a physical simulation model is constructed, comprising reservoir simulation units and branch wellbore simulation units. Specifically, an electrolyte is used to simulate the reservoir medium of the target low-permeability gas reservoir, and a conductive array is used to simulate the wellbore structure of the target branch well. This achieves matching between the electrolyte conductivity and reservoir fluid mobility, and geometric scaling matching between the conductive array structure parameters and the actual branch wellbore structure. The similarity criterion system is constructed based on the actual geological parameters, fluid properties of the target low-permeability gas reservoir, and the wellbore structure parameters of the target branch well. The similarity criterion system includes geometric similarity coefficients, pressure similarity coefficients, flow similarity coefficients, flow similarity coefficients, and resistance similarity coefficients.

[0008] A DC voltage is applied to the boundary of the reservoir simulation unit to simulate the gas reservoir formation supply boundary pressure. The wellbore flow process under production pressure differential is simulated through a circuit system connected to the branch wellbore simulation unit. Real-time current data at the simulated wellbore outlet and voltage field distribution data inside the physical simulation model are collected.

[0009] The actual production capacity data of the branch well of the target gas reservoir is determined based on the real-time current data and the flow similarity coefficient. The actual pressure field distribution data inside the gas reservoir is determined based on the voltage field distribution data and the pressure similarity coefficient. The wellbore interference effect and reservoir seepage law of the branch well are analyzed based on the actual production capacity data and the actual pressure field distribution data.

[0010] By adjusting the structural parameters of the branch well simulation unit, real-time current data and voltage field distribution data are repeatedly collected to obtain branch well productivity data under different combinations of structural parameters. The influence of each structural parameter on the branch well is analyzed, and the optimal structural parameter scheme for the branch well corresponding to the target gas reservoir is output.

[0011] Optionally, the similarity criterion system is defined in the following manner:

[0012] The geometric similarity coefficient is the ratio of the length of the physical simulation model to the actual reservoir length; the pressure similarity coefficient is the ratio of the voltage difference in the physical simulation model to the actual reservoir production pressure difference; the flow similarity coefficient is the ratio of the loop current in the physical simulation model to the actual gas well production; the flow similarity coefficient is the ratio of the electrolyte conductivity in the physical simulation model to the fluid mobility in the reservoir; and the resistance similarity coefficient is the ratio of the resistance at any location in the physical simulation model to the seepage resistance at the corresponding location in the reservoir.

[0013] Optionally, a copper sulfate solution is used as the electrolyte, and the corresponding preparation and parameter matching of the electrolyte includes:

[0014] The volume of the reservoir simulation tank is calculated based on the geometric similarity coefficient, and the volume of distilled water is determined.

[0015] The target electrolyte conductivity is determined based on the flow similarity coefficient, and the required mass of copper sulfate solute is calculated based on the correspondence between the conductivity and concentration of the copper sulfate solution.

[0016] By adjusting the concentration of the electrolyte, low-permeability and ultra-low-permeability reservoirs with different permeability rates are simulated.

[0017] Optionally, when the target low-permeability gas reservoir is a heterogeneous reservoir, multiple sets of mutually isolated electrolyte chambers are set in the reservoir simulation tank. Different concentrations of copper sulfate electrolyte are filled in different chambers, corresponding to the permeability parameters of different regions of the reservoir, so as to carry out physical simulation of planar or vertical heterogeneous reservoirs.

[0018] By changing the electrolyte concentration, a productivity simulation experiment was conducted on the branch wells of heterogeneous reservoirs under different permeability levels.

[0019] Optionally, the conductive array is made of highly conductive oxygen-free copper rods, and the diameter of the copper rods is determined by scaling the actual wellbore size proportionally according to the geometric similarity coefficient; the spatial parameters of the conductive array include the number of branches, the branch angle, the branch length, the main wellbore length, and the branch spatial arrangement.

[0020] Optionally, the circuit system includes a DC regulated power supply, a resistor network connected in series with the conductor of each simulated branch wellbore, an ammeter, and a voltmeter; wherein, the DC regulated power supply is used to simulate the production pressure differential of the gas reservoir; the resistor network uses digitally controllable resistors to achieve continuous automatic adjustment of the resistance value through program instructions to simulate the wellbore friction of the branch wellbore and the skin effect of near-wellbore contamination in the reservoir.

[0021] Optionally, the simulated wellbore friction and skin effect of near-wellbore contamination in the branch wellbore include:

[0022] Based on the actual wellbore size, wellbore roughness, drilling fluid contamination depth and contamination degree of the target branch wells, calculate the target friction resistance value and skin effect equivalent resistance value corresponding to each branch wellbore.

[0023] The resistance values ​​of the resistor network connected in series with each branch wellbore are adjusted by the program instructions to simulate the independent wellbore friction and skin effect of a single branch.

[0024] Analysis of the productivity loss pattern of branch wells under different pollution levels was conducted by adjusting the resistance value using gradients.

[0025] Optionally, the voltage field distribution data is acquired by a three-dimensional movable coordinate arm integrated with a voltage probe on the physical simulation model; wherein the three-dimensional movable coordinate arm performs automated scanning and acquisition according to a preset three-dimensional grid path.

[0026] Optionally, the structural parameters of the branch well include at least one of the following: number of branches, branch angle, branch length, main wellbore length, branch spatial layer, and branch spacing; the analysis of the influence of each structural parameter on the branch well, and the output of the optimal structural parameter scheme for the branch well corresponding to the target gas reservoir, includes:

[0027] The sensitivity analysis of each of the structural parameters on the dimensionless production and dimensionless production pressure difference of the branch well was conducted using the single-factor variable method, and the influence weight and influence law of each of the structural parameters on the production capacity were quantified.

[0028] The influence of multi-parameter coupling was analyzed by orthogonal experimental design. With the optimization objectives of maximizing production efficiency and optimizing drilling engineering costs, the optimal combination of structural parameters for the branch wells corresponding to the target gas reservoir was output.

[0029] According to another aspect of the present invention, a physical simulation experimental apparatus for the productivity of a branch well in a low-permeability gas reservoir is provided, comprising:

[0030] The physical simulation model construction unit is used to construct a physical simulation model containing reservoir simulation units and branch wellbore simulation units based on a pre-calibrated similarity criterion system for hydroelectric similarity simulation. Specifically, the reservoir medium of the target low-permeability gas reservoir is simulated using an electrolyte, and the wellbore structure of the target branch well is simulated using a conductive array. This achieves matching between the electrolyte conductivity and reservoir fluid mobility, and geometric scaling matching between the conductive array structure parameters and the actual branch wellbore structure. The similarity criterion system is constructed based on the actual geological parameters, fluid properties of the target low-permeability gas reservoir, and the wellbore structure parameters of the target branch well. The similarity criterion system includes geometric similarity coefficients, pressure similarity coefficients, flow similarity coefficients, flow similarity coefficients, and resistance similarity coefficients.

[0031] The data acquisition unit is used to apply a DC voltage to the boundary of the reservoir simulation unit to simulate the gas reservoir formation supply boundary pressure, simulate the wellbore flow process under production pressure differential through the circuit system connected to the branch wellbore simulation unit, and acquire real-time current data at the simulated wellbore outlet, as well as voltage field distribution data inside the physical simulation model.

[0032] The reservoir seepage law determination unit is used to determine the actual production capacity data of the target gas reservoir branch well based on the real-time current data and the flow similarity coefficient, determine the actual pressure field distribution data inside the gas reservoir based on the voltage field distribution data and the pressure similarity coefficient, and analyze the wellbore interference effect and reservoir seepage law of the branch well based on the actual production capacity data and the actual pressure field distribution data.

[0033] The parameter scheme output unit is used to repeatedly collect real-time current data and voltage field distribution data by adjusting the structural parameters of the branch well simulation unit to obtain branch well production capacity data under different combinations of structural parameters, analyze the influence of each structural parameter on the branch well, and output the optimal structural parameter scheme of the branch well corresponding to the target gas reservoir.

[0034] The technical solution of this invention constructs a similarity criterion system based on the principle of hydroelectric similarity, transforms the complex seepage field of a branch well in a low-permeability gas reservoir into an easily measurable electric field, restores the wellbore interference effect and reservoir seepage law, realizes visualized observation of the seepage field and quantitative analysis of production capacity, and has the advantages of low experimental cost, short cycle and strong parameter adaptability. It can efficiently complete the sensitivity analysis and optimization design of the structural parameters of the branch well, and provide reliable quantitative experimental support for the efficient development of branch wells in low-permeability gas reservoirs.

[0035] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0037] Figure 1 This is a flowchart of a physical simulation experiment method for the productivity of a branch well in a low-permeability gas reservoir provided in an embodiment of the present invention;

[0038] Figure 2 This is a schematic diagram of the structure of a physical simulation experimental device applicable to an embodiment of the present invention;

[0039] Figure 3 This is a schematic diagram of a conductive array for a simulated branch wellbore applicable to an embodiment of the present invention;

[0040] Figure 4 This is a comparative schematic diagram of the voltage field under different branch angles applicable to the embodiments of the present invention;

[0041] Figure 5 This is a curve illustrating the influence of different branching angles on dimensionless output and dimensionless production pressure difference, applicable to embodiments of the present invention.

[0042] Figure 6 This is a schematic diagram of the structure of a physical simulation experimental device for the productivity of a branch well in a low-permeability gas reservoir provided in an embodiment of the present invention. Detailed Implementation

[0043] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0044] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0045] Figure 1 This is a flowchart of a physical simulation experiment method for the productivity of a branch well in a low-permeability gas reservoir, provided by an embodiment of the present invention. This embodiment is applicable to simulating the productivity of branch wells in low-permeability gas reservoirs, such as... Figure 1 As shown, the method includes:

[0046] S110. Based on the pre-calibrated similarity criterion system for hydroelectric similarity simulation, construct a physical simulation model that includes reservoir simulation units and branch wellbore simulation units. Specifically, the reservoir medium of the target low-permeability gas reservoir is simulated using an electrolyte, and the wellbore structure of the target branch well is simulated using a conductive array. This achieves matching between the electrolyte conductivity and reservoir fluid mobility, and geometric scaling matching between the conductive array structure parameters and the actual branch wellbore structure. The similarity criterion system is constructed based on the actual geological parameters, fluid properties of the target low-permeability gas reservoir, and the wellbore structure parameters of the target branch well. The similarity criterion system includes geometric similarity coefficients, pressure similarity coefficients, flow similarity coefficients, flow similarity coefficients, and resistance similarity coefficients.

[0047] Specifically, the physical simulation model includes reservoir simulation units corresponding to the underground reservoir space and branch wellbore simulation units corresponding to the underground wellbore. The laboratory-scale model serves as a mapping to the actual development scenario of the target gas reservoir and as a carrier for the production capacity simulation experiment. Using an electrolyte with continuous and uniform conductivity, the spatial and media basis for continuous natural gas seepage in the porous underground media of a low-permeability gas reservoir is reproduced. An array of conductive materials with high conductivity and low resistance is used to reproduce the low-resistance collection and flow production function of the branch wellbore for formation fluids, thus reproducing the reservoir seepage process and the wellbore flow collection process. By calibrating the conductivity of the electrolyte, the physical flow similarity between the model's conductive process and the actual reservoir seepage process is achieved. Through proportional scaling and calibration of the actual wellbore dimensions and spatial structure, the geometric similarity between the model and the field prototype is achieved. The similarity criterion system refers to a system that is customized for specific target gas reservoirs and target branch well types. It takes the real geological conditions of the target block, the physical characteristics of formation fluids, and the structural parameters of the branch well to be designed as inputs to ensure that the similarity criterion system is highly adaptable to the actual development scenario on site and avoids the deviation of simulation results caused by general criteria.

[0048] The coefficients of the similarity criterion system correspond to the similarity calibration standards of the model and the prototype in five dimensions: spatial size, pressure field and voltage field mapping, gas well production and loop current mapping, seepage and electrical physical processes, and flow resistance characteristics.

[0049] In this embodiment of the invention, the similarity criterion system is defined in the following manner:

[0050] The geometric similarity coefficient is the ratio of the length of the physical simulation model to the actual reservoir length; the pressure similarity coefficient is the ratio of the voltage difference in the physical simulation model to the actual reservoir production pressure difference; the flow similarity coefficient is the ratio of the loop current in the physical simulation model to the actual gas well production; the flow similarity coefficient is the ratio of the electrolyte conductivity in the physical simulation model to the fluid mobility in the reservoir; and the resistance similarity coefficient is the ratio of the resistance at any location in the physical simulation model to the seepage resistance at the corresponding location in the reservoir.

[0051] Specifically, the similarity criterion in this embodiment of the invention is derived based on the similarity of the governing equations of Darcy's law (seepage field) and Ohm's law (electric field). The expression for Darcy's law is: Where v is the seepage velocity, k is the reservoir permeability, and ų is the fluid viscosity. The pressure gradient is given by Ohm's law. Where J is the current density and σ is the conductivity. The voltage gradient is used. By employing dimensional analysis, the two governing equations are made consistent in form, corresponding to the similarity relationships between flow velocity v and current density J, the ratio of permeability to viscosity μk (fluid mobility) and conductivity σ, and pressure p and voltage U. This leads to the derivation of five similarity coefficients: geometric similarity coefficient Cl, pressure similarity coefficient Cp, flow similarity coefficient Cq, flow similarity coefficient Cρ, and resistance similarity coefficient Cr, ensuring the mechanical similarity between the seepage field and the electric field.

[0052] S120. Apply DC voltage to the boundary of the reservoir simulation unit to simulate the gas reservoir formation supply boundary pressure. Simulate the wellbore flow process under production pressure differential through the circuit system connected to the branch wellbore simulation unit. Collect real-time current data at the simulated wellbore outlet and voltage field distribution data inside the physical simulation model.

[0053] Specifically, by applying a stable DC voltage to the boundary conductive plate of the reservoir simulation unit, the formation constant pressure supply boundary of the target low-permeability gas reservoir is reproduced. In gas reservoir development, the formation supply boundary is the power source for maintaining reservoir pressure stability and driving natural gas to flow into the wellbore. The purpose of applying a stable DC voltage to the boundary in the laboratory is to establish a constant potential difference for the simulated reservoir composed of electrolyte, forming an electric field that drives the current flow. The voltage amplitude is strictly set according to the pre-calibrated pressure similarity coefficient to ensure that the model voltage corresponds to the actual formation pressure.

[0054] The voltage difference between the supply voltage applied at the boundary of the circuit system and the voltage at the wellbore end corresponds to the production pressure difference between the formation supply pressure and the wellbore flowing pressure during gas reservoir development. The adjustable resistor connected in series in the circuit can accurately simulate the flow friction and near-wellbore fouling skin effect in the wellbore. The process of current flowing from the electrolyte reservoir into the conductive wellbore and then forming a closed circuit is similar to the flow process of natural gas seeping from the reservoir into the wellbore and then being lifted and produced along the wellbore. This realizes the coupled simulation of formation seepage and wellbore flow, and solves the problem that traditional methods are difficult to accurately characterize the wellbore-reservoir interaction.

[0055] The real-time current data at the simulated wellbore outlet is mapped to the actual production of the target gas reservoir branch wells through a pre-calibrated flow similarity coefficient. The total loop current can be directly used to calculate the total production capacity of the entire well. The branch current of each branch wellbore can be used to quantify the production capacity contribution of a single branch. Real-time acquisition ensures that the data is taken from the stable value after the system reaches steady state, thus guaranteeing the accuracy of the production capacity calculation. The voltage field distribution data inside the physical simulation model corresponds to the formation pressure field distribution inside the gas reservoir. Through voltage probe scanning and acquisition of full-space voltage data, the isobaric distribution within the visualized reservoir, the pressure interference range between branch wellbores, and the low-pressure discharge area are determined, and the seepage law and wellbore interference effect of multi-branch wells are analyzed.

[0056] S130. Determine the actual production capacity data of the branch wells of the target gas reservoir based on real-time current data and flow similarity coefficient. Determine the actual pressure field distribution data inside the gas reservoir based on voltage field distribution data and pressure similarity coefficient. Analyze the wellbore interference effect and reservoir seepage law of the branch wells based on the actual production capacity data and actual pressure field distribution data.

[0057] Specifically, by using the real-time current data collected at the wellbore outlet after the system reaches steady state in the experiment and performing linear conversion through the flow similarity coefficient, the actual natural gas production capacity data under the branch well structure corresponding to the target gas reservoir can be obtained. Among them, the total current of the entire loop can be used to calculate the total production capacity of the branch well, and the branch current collected separately from each branch wellbore can quantify the production capacity contribution ratio of each branch. This provides quantitative results based on measured data for the evaluation of branch well production capacity, and solves the problem that traditional numerical simulation methods are difficult to predict the production capacity of a single well or a single branch in multi-branch wells.

[0058] By converting the voltage field distribution data of each measuring point in the entire space inside the model collected during the experiment using the pressure similarity coefficient, the actual formation pressure value and overall pressure field distribution characteristics at any spatial location inside the reservoir during the development of the target gas reservoir can be restored. This solves the problem that in field development, only single-point pressure data can be obtained through downhole measuring points, and the overall picture of the reservoir pressure field cannot be fully grasped. It can characterize the pressure drop law, leakage boundary range and pressure transmission characteristics within the reservoir.

[0059] The wellbore interference effect of branch wells refers to the interaction effect where the pressure fields of each branch overlap and the drainage areas overlap when multiple branch wells are producing simultaneously, leading to changes in the production efficiency of a single branch. The reservoir seepage law refers to the seepage morphology, flow characteristics, and main controlling factors of natural gas in low-permeability gas reservoirs under the branch well development mode. By quantifying the impact of wellbore interference on production capacity under different branch structures through actual production data, and by identifying the interference range, pressure field overlap, and utilization efficiency of the drainage area between branches through actual pressure field distribution data, the combination of these two methods can analyze the influence mechanism of structural parameters such as branch angle, number, and length on the wellbore interference effect, and simultaneously determine the reservoir seepage pattern and flow law under the branch well development of low-permeability gas reservoirs.

[0060] S140. By adjusting the structural parameters of the branch well simulation unit, real-time current data and voltage field distribution data are repeatedly collected to obtain branch well production data under different combinations of structural parameters. The influence of each structural parameter on the branch well is analyzed, and the optimal structural parameter scheme for the branch well corresponding to the target gas reservoir is output.

[0061] Specifically, based on production capacity data and pressure field distribution data obtained from multiple sets of experiments, the system clarifies the mechanism and variation law of the effect of each structural parameter of the branch well on the development effect. During the analysis, through single-factor sensitivity analysis, the influence magnitude and nonlinear variation characteristics of the single parameter change on the dimensionless production, dimensionless production pressure difference, and drainage range of the branch well are quantified, and the weight ranking of the influence of each parameter on production capacity is determined. Through multi-factor coupling analysis, the wellbore interference effect variation mechanism and reservoir seepage law under the joint action of multiple parameters are determined. At the same time, combined with pressure field distribution data, the intrinsic seepage mechanism of parameter influence is determined, and the branch well structural parameter-production capacity influence law system is obtained, which is used to screen the optimal wellbore structure.

[0062] With the optimization objectives of maximizing the comprehensive benefits of development investment and production capacity based on the actual geological conditions of the target gas reservoir, the feasibility of on-site drilling engineering, and the overall benefits of development investment and production capacity, the optimal combination of branch well structure parameters is selected based on the parameter influence law. An optimized chart of branch well structure parameters and production capacity correlation adapted to the target block is generated, providing a reference for the design of well locations in the same block.

[0063] In this embodiment of the invention, copper sulfate solution is used as the electrolyte, and the corresponding electrolyte preparation and parameter matching include:

[0064] The volume of the reservoir simulation tank is calculated based on the geometric similarity coefficient, and the volume of distilled water is determined.

[0065] The conductivity of the target electrolyte is determined based on the flow similarity coefficient, and the required mass of copper sulfate solute is calculated based on the correspondence between the conductivity and concentration of the copper sulfate solution.

[0066] Copper sulfate solution was chosen as the electrolyte for simulating low-permeability gas reservoirs because it possesses characteristics suitable for hydroelectric simulation requirements: the conductivity of copper sulfate solution has a stable linear relationship with solute concentration, and the conductivity can be controlled by adjusting the concentration to match the simulation requirements of reservoirs with different permeability; the solution has uniform ion migration characteristics and no obvious local conductivity anomalies, which can reproduce the uniform or heterogeneous seepage characteristics of low-permeability reservoirs; at the same time, it has good electrochemical compatibility with the copper conductor in the simulated wellbore, and problems such as electrode polarization and corrosion are not likely to occur during the experiment.

[0067] The internal dimensions of the reservoir simulation tank are calculated proportionally using geometric similarity coefficients, based on the actual leakage range and reservoir thickness of the target gas reservoir. The effective volume is then calculated from the tank's length, width, and height, determining the volume of distilled water to be used as the electrolyte solvent. The distilled water must ensure the electrolyte submerges the conductive array of the simulated branch wellbore, replicating the three-dimensional seepage space of the target reservoir. The target conductivity of the electrolyte is calculated using flow similarity coefficients to ensure physical similarity between the model's conductive process and the actual reservoir seepage process. At a fixed temperature, the conductivity of copper sulfate solution corresponds to its solute concentration. Given the determined volume of distilled water, the required mass of copper sulfate solute can be calculated by matching the target conductivity to the corresponding solution concentration.

[0068] In this embodiment of the invention, when the target low-permeability gas reservoir is a heterogeneous reservoir, multiple sets of mutually isolated electrolyte chambers are set in the reservoir simulation tank. Different concentrations of copper sulfate electrolyte are filled in different chambers, which correspond to the permeability parameters of different regions of the reservoir, so as to perform physical simulation of planar or vertical heterogeneous reservoirs.

[0069] By changing the electrolyte concentration, a productivity simulation experiment was conducted on the branch wells of heterogeneous reservoirs under different permeability levels.

[0070] Specifically, the heterogeneity of low-permeability gas reservoirs refers to the differences in permeability, porosity, and other physical properties in different regions of the reservoir in planar or vertical space. This is a factor that leads to deviations in the production capacity prediction of branch wells and unsatisfactory development results. By setting up mutually isolated chambers in the reservoir simulation tank, the miscibility of electrolytes of different concentrations is avoided, which would destroy the zonal differences in conductivity. Based on the linear correspondence between the conductivity and concentration of copper sulfate solution, different concentrations of electrolyte are filled in different chambers, so that the conductivity of each chamber matches the permeability parameters of the corresponding region of the target reservoir. This reproduces the real geological features such as strip heterogeneity in the reservoir plane and interlayer heterogeneity in the vertical direction.

[0071] Permeability gradient refers to the ratio of permeability between high-permeability and low-permeability regions in a reservoir. It determines the fluid flow patterns, interference effects between branch wells, and production capacity in heterogeneous reservoirs. By changing the concentration of copper sulfate electrolyte, the electrolyte concentration of a single chamber can be adjusted individually, and the concentration combination of multiple chambers can be adjusted simultaneously to change the permeability parameters of different regions of the simulated reservoir, forming different permeability gradients to cover various heterogeneity scenarios that may occur in the target gas reservoir. Based on this, repeating the branch well production capacity simulation experiment can obtain branch well production capacity data and pressure field distribution characteristics under different permeability gradients.

[0072] In this embodiment of the invention, the conductive array is made of highly conductive oxygen-free copper rods, and the diameter of the copper rods is determined by scaling the actual wellbore size proportionally according to the geometric similarity coefficient. The spatial parameters of the conductive array include the number of branches, the branch angle, the branch length, the main wellbore length, and the branch spatial arrangement.

[0073] Specifically, oxygen-free copper has high electrical conductivity and low resistivity, which can reproduce the function of low-resistance collection and low-friction flow production of formation fluids in actual oil and gas wells. At the same time, its chemical properties are stable and it has excellent electrochemical compatibility with copper sulfate electrolyte. It is not prone to oxidation corrosion, electrode polarization and other problems during the experiment. The diameter of the copper rod is determined according to the actual wellbore size and scaled proportionally based on the geometric similarity coefficient to ensure the geometric similarity between the model wellbore and the actual wellbore in the field. The number of branches refers to the total number of branch wells laid on the main wellbore, which determines the total drainage area and reservoir control range of the branch wells; the branch angle refers to the angle between the axis of the branch wellbore and the axis of the main wellbore, which affects the degree of pressure interference between multiple branch wells and the distribution of planar drainage areas; the branch length refers to the extension length of a single branch wellbore, which determines the reservoir control reserves and production capacity contribution of a single branch; the main wellbore length refers to the total extension length of the main horizontal wellbore of the branch well, which is the basis for the layout of branch wells and determines the overall longitudinal / planar distribution range of the branch wells; the branch spatial arrangement method includes planar symmetrical / asymmetrical arrangement of branches, longitudinal layered three-dimensional arrangement, etc., which can be adapted to the sand body distribution characteristics, planar and longitudinal heterogeneity of the target gas reservoir, and realize the simulation of the wellbore structure of various branch wells in the field.

[0074] In this embodiment of the invention, the circuit system includes a DC regulated power supply, a resistor network connected in series with a conductor of each simulated branch wellbore, an ammeter, and a voltmeter; wherein, the DC regulated power supply is used to simulate the production pressure differential of the gas reservoir; the resistor network adopts a digitally controllable resistor, which is used to realize continuous automatic adjustment of the resistance value through program instructions to simulate the wellbore friction of the branch wellbore and the skin effect of near-wellbore contamination in the reservoir.

[0075] Specifically, the circuit system, the boundary conductive plate of the reservoir simulation unit, and the conductive array of the branch wellbore simulation unit form a closed conductive loop. The DC regulated power supply provides the potential drive for the loop, and the resistor network connected in series with each branch conductor can control the flow characteristics of a single branch wellbore. The ammeter and voltmeter are responsible for measuring the loop current and the voltage of each node, respectively. The design of a single-branch independent series resistor network can realize the simulation of differentiated parameters of different branch wellbores, adapting to the actual working conditions of different wellbore sizes and pollution levels in the field.

[0076] In gas reservoir development, the production pressure differential refers to the difference between the formation supply boundary pressure and the wellbore bottom flowing pressure. It is the driving force that propels natural gas from the reservoir into the wellbore and then into production. Correspondingly, in a circuit system, the stable DC voltage difference applied by the DC regulated power supply between the conductive plate at the boundary of the reservoir simulation tank and the conductor in the wellbore is the driving force that propels the current from the electrolyte reservoir into the conductor in the wellbore and then along the loop. The output voltage amplitude can be set according to a pre-calibrated pressure similarity coefficient to achieve a correspondence between the model voltage difference and the actual production pressure differential in the field. At the same time, the DC regulated power supply has a highly stable output characteristic, which can ensure the constant potential drive during the experiment and avoid deviations in current and voltage measurement data caused by voltage fluctuations.

[0077] Digitally controllable resistors can achieve continuous, stepless automatic adjustment of resistance values ​​via host computer program commands. By connecting the resistor network in series with the conductor of each branch wellbore individually, parameters can be adjusted for different branch wellbores, replicating the differences in flow resistance caused by variations in wellbore size, well trajectory, and drilling contamination levels in the field. Among these, wellbore friction is the flow resistance along the wellbore caused by friction of the pipe wall and changes in the flow channel when natural gas flows along the wellbore in actual production. This corresponds to the resistance of the series resistor in the circuit to the current. The larger the resistance value, the stronger the resistance to the current, and the higher the wellbore friction and the higher the flow pressure loss in the wellbore. The skin effect of near-wellbore contamination is the additional seepage resistance caused by the intrusion of drilling fluid during drilling and completion, which leads to a decrease in near-wellbore reservoir permeability. This can also be simulated by increasing the resistance value of the series resistor.

[0078] In this embodiment of the invention, simulating wellbore friction of branch wells and the skin effect of near-wellbore contamination includes:

[0079] Based on the actual wellbore size, wellbore roughness, drilling fluid contamination depth and contamination degree of the target branch wells, calculate the target friction resistance value and skin effect equivalent resistance value corresponding to each branch wellbore.

[0080] The resistance values ​​of the resistor network connected in series with each branch wellbore are adjusted separately by program commands to simulate the friction and skin effect of a single branch wellbore independently.

[0081] Analysis of the productivity loss pattern of branch wells under different pollution levels was conducted by adjusting the resistance value using gradients.

[0082] Specifically, the actual wellbore size and wellbore roughness determine the magnitude of the frictional resistance along the flow of natural gas through the wellbore. The actual flow friction in the wellbore is converted into the corresponding target frictional resistance value in the circuit based on the resistance similarity coefficient. The drilling fluid contamination depth and degree are the basis for calculating the equivalent resistance value of the skin effect. Contamination will lead to a decrease in reservoir permeability in the near-wellbore zone, generating additional seepage resistance. The magnitude of this resistance can be quantified by the skin coefficient, and then the conversion from the additional seepage resistance in the field to the equivalent resistance value in the circuit is completed by the resistance similarity coefficient.

[0083] By using instructions from the host computer program, target resistance values ​​are set for each resistor network connected in series with the conductor of the branch wellbore. This reproduces the differences in flow resistance caused by different branches in multi-branch wells due to different wellbore conditions and contamination levels. By simulating the obstruction effect of wellbore friction and skin effect on natural gas flow through the resistance's effect on the loop current, the obstruction effect of wellbore friction and skin effect is simulated.

[0084] By adjusting the resistance value of the resistor network connected in series with the branch wellbore through a preset gradient sequence, the simulation covers the full range of drilling fluid contamination levels from no contamination, slight contamination to severe contamination. Simultaneously, steady-state productivity simulation experiments are conducted, and wellbore outlet current data under different resistance values ​​are collected and the corresponding actual productivity is calculated. This allows for the quantitative establishment of the correspondence between resistance value (corresponding to the degree of contamination) and the productivity loss of the branch well, determining the productivity loss pattern under different contamination levels, and identifying the critical skin coefficient for productivity decline caused by drilling contamination. This provides experimental basis for reservoir protection scheme design during the drilling process and can also simultaneously analyze the differences in the well type's resistance to drilling contamination under different branch well structural parameters.

[0085] In this embodiment of the invention, voltage field distribution data is collected from the physical simulation model by a three-dimensional movable coordinate arm integrated with a voltage probe; wherein, the three-dimensional movable coordinate arm achieves automated scanning and collection according to a preset three-dimensional grid path.

[0086] Specifically, a three-dimensional movable coordinate arm integrating a high-precision voltage probe is used as the core hardware for data acquisition. Through the coordinate arm's three-dimensional spatial movement and positioning capabilities, the voltage probe can be moved to any three-dimensional spatial point within the electrolyte of the physical simulation model, enabling point-to-point measurement of the voltage value throughout the model. Simultaneously, the voltage probe possesses millivolt-level measurement accuracy, capable of capturing minute voltage gradient changes within the model. The designed three-dimensional grid path is a pre-planned three-dimensional spatial scanning trajectory with equal or variable step sizes, based on the geometric dimensions of the physical simulation model and the seepage characteristics analysis requirements of the target reservoir. The grid step size can be adjusted according to experimental accuracy requirements, enabling intensive data acquisition of seepage-sensitive areas around branch wellbores and areas with drastic pressure gradient changes, while also covering non-sensitive areas. The host computer program controls the three-dimensional movable coordinate arm to complete fully automated scanning and acquisition along a preset path, avoiding the deviation caused by manual measurement. It can also ensure that the acquisition path is consistent for multiple sets of repeated experiments and experiments with different branch structure parameters, and ensure that the experimental data of each set have a unified comparison benchmark. At the same time, the acquired gridded voltage data can be synchronized to the host computer to generate a three-dimensional voltage field distribution cloud map, which intuitively reflects the formation pressure field distribution characteristics of the corresponding reservoir.

[0087] In this embodiment of the invention, the structural parameters of the branch well include at least one of the following: number of branches, branch angle, branch length, main wellbore length, branch spatial layer, and branch spacing; the influence of each structural parameter on the branch well is analyzed, and the optimal structural parameter scheme for the branch well corresponding to the target gas reservoir is output, including:

[0088] The sensitivity analysis of each structural parameter on the dimensionless production output and dimensionless production pressure difference of the branch well was conducted using the single-factor variable method, and the influence weight and influence law of each structural parameter on the production capacity were quantified.

[0089] The influence of multi-parameter coupling was analyzed by orthogonal experimental design. With the optimization objectives of maximizing production efficiency and optimizing drilling engineering costs, the optimal combination of structural parameters for the branch wells corresponding to the target gas reservoir was output.

[0090] Specifically, the number of branches, branch angle, branch length, and main wellbore length determine the planar distribution and drainage area of ​​the branch wells. The spatial strata of the branches can adapt to the three-dimensional development needs of multiple reservoirs in the target gas reservoir. The branch spacing determines the strength of pressure interference between multiple branch wellbores. The single-factor variable method refers to adjusting only one structural parameter of the target analysis during the experiment, while keeping other parameters unchanged, and conducting multiple sets of repeated steady-state experiments to determine the independent impact of a certain parameter change on the development effect of the branch wells. Using dimensionless production and dimensionless production pressure difference as evaluation indicators can more objectively quantify the development efficiency and seepage characteristics of the branch wells. Through the analysis of this step, the influence magnitude of different structural parameters on production capacity is ranked, i.e., the influence weight, and the nonlinear relationship between parameter changes and production capacity changes, i.e., the influence law, is determined. For example, the critical value of decreasing production capacity increase when the branch angle increases, and the inflection point of decreasing marginal benefit of production capacity when the number of branches increases.

[0091] Orthogonal experimental design is a highly efficient scientific experimental method for multi-factor, multi-level experimental scenarios. Based on the effective control range of parameters obtained from single-factor analysis, it can design orthogonal experimental schemes covering different combinations of multiple parameters at different levels. It can accurately obtain the production capacity impact law under the coupling effect of multiple parameters with the fewest number of experimental groups. The optimization objectives are to maximize production capacity benefits and optimize drilling engineering costs, that is, to address the issues of gas production revenue from branch well development and increased drilling costs, construction difficulty, and operational risks caused by the increase in the number and length of branches. This method is more in line with the actual production and operation needs of gas field development and obtains the optimal combination of structural parameters.

[0092] The following describes the solution of the above embodiments of the present invention in detail through a feasible example:

[0093] Experiment 1: Branch Angle Sensitivity Analysis Experiment.

[0094] A low-permeability gas reservoir (average permeability 1.0 mD) is used as the simulation object. Geometric similarity coefficients are set according to the similarity criteria. (That is, the actual wellbore length of 2000 meters corresponds to a model length of 0.4 meters), pressure similarity coefficient Traffic similarity coefficient Accordingly, a 0.1 mol / L copper sulfate solution was prepared as the electrolyte to meet the predetermined conductivity (corresponding to the flow similarity coefficient). The simulated main wellbore used a copper rod with a proportionally scaled diameter and a length of 0.4 meters. The number of branches was fixed at 3, with each branch length being 0.6 times the length of the main wellbore.

[0095] Figure 2 This is a schematic diagram of a physical simulation experimental device applicable to an embodiment of the present invention. Figure 3 This is a schematic diagram of a conductive array for a simulated branch wellbore applicable to an embodiment of the present invention, in which copper rods are arranged in a specific configuration. Figure 3The circuit was installed in the simulation tank, with the initial branch angle set to 30°. A 10V voltage was applied to the conductive plate at the boundary of the simulation tank via the DC regulated power supply of the circuit system to simulate a formation pressure of 40MPa. After the system stabilized, the data acquisition system began operation. The three-dimensional coordinate arm drove the voltage probe to scan the internal space of the model along a preset grid path, and the data acquisition card automatically recorded the voltage values ​​at each point. Simultaneously, the total current value in the loop was recorded. The branch angle was then adjusted sequentially to 45°, 60°, 75°, and 90°, and the above steps were repeated.

[0096] The measured current value is converted into actual output using the flow similarity coefficient Cq, and the voltage field data is converted into pressure field using the pressure similarity coefficient Cp. Figure 4 This is a comparative schematic diagram of the voltage field under different branch angles applicable to the embodiments of the present invention. The left side is 30° and the right side is 90°. It can be seen that the low voltage area is larger at 90°, indicating a wider control range. Figure 5 This is a graph illustrating the influence of different branching angles on dimensionless output and dimensionless production pressure differential, applicable to embodiments of the present invention. Quantitative analysis shows that output increases with increasing angle, but the rate of increase decreases. For example, the dimensionless output at 90° is approximately 1.21 times that at 30°, demonstrating that 60°-75° may be the optimal range for engineering efficiency.

[0097] Experiment 2: Simulation experiment on reservoir heterogeneity and drilling contamination.

[0098] In addition to the baseline parameters (same as Experiment 1), heterogeneous reservoirs with permeabilities of 0.5 mD, 1.0 mD, and 2.0 mD were simulated by changing the electrolyte concentrations (e.g., 0.05 mol / L, 0.1 mol / L, and 0.2 mol / L copper sulfate solutions). Different degrees of drilling fluid skin contamination were simulated by adjusting the resistance value of the adjustable precision resistor network connected in series with the copper rods in each branch wellbore.

[0099] With a fixed branching structure (e.g., three branches, 60° angle), the measurement steps in Experiment 1 were repeated under different combinations of electrolyte concentrations (simulating different permeabilities) and resistance values ​​(simulating different levels of contamination). Experimental results show that increasing the permeability from 0.5 mD to 2.0 mD significantly improves production capacity (approximately 3.3 times) more than increasing the branching angle from 30° to 90° (approximately 1.2 times). Simultaneously, an increase in the simulated contamination skin coefficient can lead to a significant decrease in production capacity of over 20%.

[0100] Experiment 3: Application of branch well structure optimization design.

[0101] Using the actual geological parameters of the X gas field as input, the similarity coefficient was set in the same way as in Experiment 1, but the number of branches (2, 3, 5), the ratio of branch length (0.6, 0.8, 1.0), and the branch angle (30° to 90°) were changed systematically. Dozens of experiments were conducted, and the production capacity data under each set of structural parameters were measured.

[0102] The host computer's built-in algorithm library automatically processes the data, generating a relationship chart such as "Number of Branches - Branch Angle - Dimensionless Production". Analysis of the chart yields optimization suggestions: For this block with a permeability of approximately 1.0 mD, a structure with 3 branches, a 60° angle, and a branch length 0.8 times that of the main wellbore can achieve the best balance between production capacity and drilling costs.

[0103] Figure 6 This is a schematic diagram of a physical simulation experimental device for the productivity of a branch well in a low-permeability gas reservoir, provided in an embodiment of the present invention. Figure 6 As shown, the device includes:

[0104] The physical simulation model construction unit 610 is used to construct a physical simulation model containing reservoir simulation units and branch wellbore simulation units based on a pre-calibrated similarity criterion system for hydroelectric similarity simulation. Specifically, the electrolyte simulates the reservoir medium of the target low-permeability gas reservoir, and the conductive array simulates the wellbore structure of the target branch well, achieving matching between the electrolyte conductivity and reservoir fluid mobility, and geometric scaling matching between the conductive array structure parameters and the actual branch wellbore structure. The similarity criterion system is constructed based on the actual geological parameters, fluid properties of the target low-permeability gas reservoir, and the wellbore structure parameters of the target branch well. The similarity criterion system includes geometric similarity coefficients, pressure similarity coefficients, flow similarity coefficients, flow similarity coefficients, and resistance similarity coefficients.

[0105] The data acquisition unit 620 is used to apply a DC voltage to the boundary of the reservoir simulation unit to simulate the gas reservoir formation supply boundary pressure, simulate the wellbore flow process under production pressure differential through the circuit system connected to the branch wellbore simulation unit, and acquire real-time current data at the simulated wellbore outlet, as well as voltage field distribution data inside the physical simulation model.

[0106] The reservoir seepage law determination unit 630 is used to determine the actual production capacity data of the target gas reservoir branch well based on real-time current data and flow similarity coefficient, determine the actual pressure field distribution data inside the gas reservoir based on voltage field distribution data and pressure similarity coefficient, and analyze the wellbore interference effect and reservoir seepage law of the branch well based on the actual production capacity data and actual pressure field distribution data.

[0107] The parameter scheme output unit 640 is used to repeatedly collect real-time current data and voltage field distribution data by adjusting the structural parameters of the branch well simulation unit to obtain branch well production data under different combinations of structural parameters, analyze the influence of each structural parameter on the branch well, and output the optimal structural parameter scheme of the branch well corresponding to the target gas reservoir.

[0108] The physical simulation experimental device for the productivity of branch wells in low-permeability gas reservoirs provided in this embodiment of the invention can execute the physical simulation experimental method for the productivity of branch wells in low-permeability gas reservoirs provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0109] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0110] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A physical simulation experimental method for the productivity of a branch well in a low-permeability gas reservoir, characterized in that, include: Based on a pre-defined similarity criterion system for hydroelectric similarity simulation, a physical simulation model is constructed, comprising reservoir simulation units and branch wellbore simulation units. Specifically, an electrolyte is used to simulate the reservoir medium of the target low-permeability gas reservoir, and a conductive array is used to simulate the wellbore structure of the target branch well. This achieves matching between the electrolyte conductivity and reservoir fluid mobility, and geometric scaling matching between the conductive array structure parameters and the actual branch wellbore structure. The similarity criterion system is constructed based on the actual geological parameters, fluid properties of the target low-permeability gas reservoir, and the wellbore structure parameters of the target branch well. The similarity criterion system includes geometric similarity coefficients, pressure similarity coefficients, flow similarity coefficients, flow similarity coefficients, and resistance similarity coefficients. A DC voltage is applied to the boundary of the reservoir simulation unit to simulate the gas reservoir formation supply boundary pressure. The wellbore flow process under production pressure differential is simulated through a circuit system connected to the branch wellbore simulation unit. Real-time current data at the simulated wellbore outlet and voltage field distribution data inside the physical simulation model are collected. The actual production capacity data of the branch well of the target gas reservoir is determined based on the real-time current data and the flow similarity coefficient. The actual pressure field distribution data inside the gas reservoir is determined based on the voltage field distribution data and the pressure similarity coefficient. The wellbore interference effect and reservoir seepage law of the branch well are analyzed based on the actual production capacity data and the actual pressure field distribution data. By adjusting the structural parameters of the branch well simulation unit, real-time current data and voltage field distribution data are repeatedly collected to obtain branch well productivity data under different combinations of structural parameters. The influence of each structural parameter on the branch well is analyzed, and the optimal structural parameter scheme for the branch well corresponding to the target gas reservoir is output.

2. The method according to claim 1, characterized in that, The similarity criterion system is defined in the following manner: The geometric similarity coefficient is the ratio of the length of the physical simulation model to the actual reservoir length; the pressure similarity coefficient is the ratio of the voltage difference of the physical simulation model to the actual reservoir production pressure difference. The flow similarity coefficient is the ratio of the loop current in the physical simulation model to the actual gas well production. The flow similarity coefficient is the ratio of the electrolyte conductivity in the physical simulation model to the fluid mobility in the reservoir. The resistance similarity coefficient is the ratio of the resistance at any location within the physical simulation model to the seepage resistance at the corresponding location in the reservoir.

3. The method according to claim 1, characterized in that, Copper sulfate solution is used as the electrolyte, and the preparation and parameter matching of the electrolyte include: The volume of the reservoir simulation tank is calculated based on the geometric similarity coefficient, and the volume of distilled water is determined. The target electrolyte conductivity is determined based on the flow similarity coefficient, and the required mass of copper sulfate solute is calculated based on the correspondence between the conductivity and concentration of the copper sulfate solution. By adjusting the concentration of the electrolyte, low-permeability and ultra-low-permeability reservoirs with different permeability rates are simulated.

4. The method according to claim 3, characterized in that, When the target low-permeability gas reservoir is a heterogeneous reservoir, multiple sets of mutually isolated electrolyte chambers are set in the reservoir simulation tank. Different concentrations of copper sulfate electrolyte are filled in different chambers, corresponding to the permeability parameters of different regions of the reservoir, so as to carry out physical simulation of planar or vertical heterogeneous reservoirs. By changing the electrolyte concentration, a productivity simulation experiment was conducted on the branch wells in heterogeneous reservoirs with different permeability levels.

5. The method according to claim 1, characterized in that, The conductive array is made of highly conductive oxygen-free copper rods, and the diameter of the copper rods is determined by scaling the actual wellbore size proportionally according to the geometric similarity coefficient. The spatial parameters of the conductive array include the number of branches, the branch angle, the branch length, the main wellbore length, and the branch spatial arrangement.

6. The method according to claim 1, characterized in that, The circuit system includes a DC regulated power supply, a resistor network connected in series with the conductor of each simulated branch wellbore, an ammeter, and a voltmeter; wherein, the DC regulated power supply is used to simulate the production pressure differential of the gas reservoir; the resistor network adopts a digitally controllable resistor, which is used to realize continuous automatic adjustment of the resistance value through program instructions to simulate the wellbore friction of the branch wellbore and the skin effect of near-wellbore contamination in the reservoir.

7. The method according to claim 6, characterized in that, The simulated branch wellbore friction and skin effect of near-wellbore contamination include: Based on the actual wellbore size, wellbore roughness, drilling fluid contamination depth and contamination degree of the target branch wells, calculate the target friction resistance value and skin effect equivalent resistance value corresponding to each branch wellbore. The resistance values ​​of the resistor network connected in series with each branch wellbore are adjusted by the program instructions to simulate the independent wellbore friction and skin effect of a single branch. Analysis of the productivity loss pattern of branch wells under different pollution levels was conducted by adjusting the resistance value using gradients.

8. The method according to claim 1, characterized in that, The voltage field distribution data is acquired by a three-dimensional movable coordinate arm with an integrated voltage probe on the physical simulation model; wherein the three-dimensional movable coordinate arm automatically scans and acquires data according to a preset three-dimensional grid path.

9. The method according to claim 1, characterized in that, The structural parameters of the branch wells include at least one of the following: number of branches, branch angle, branch length, main wellbore length, branch spatial layer, and branch spacing; the analysis of the influence of each structural parameter on the branch wells, and the output of the optimal structural parameter scheme for the branch wells corresponding to the target gas reservoir, includes: The sensitivity analysis of each of the structural parameters on the dimensionless production and dimensionless production pressure difference of the branch well was conducted using the single-factor variable method, and the influence weight and influence law of each of the structural parameters on the production capacity were quantified. The influence of multi-parameter coupling was analyzed by orthogonal experimental design. With the optimization objectives of maximizing production efficiency and optimizing drilling engineering costs, the optimal combination of structural parameters for the branch wells corresponding to the target gas reservoir was output.

10. A physical simulation experimental device for the productivity of a branch well in a low-permeability gas reservoir, characterized in that, include: The physical simulation model construction unit is used to construct a physical simulation model containing reservoir simulation units and branch wellbore simulation units based on a pre-calibrated similarity criterion system for hydroelectric similarity simulation. Specifically, the reservoir medium of the target low-permeability gas reservoir is simulated using an electrolyte, and the wellbore structure of the target branch well is simulated using a conductive array. This achieves matching between the electrolyte conductivity and reservoir fluid mobility, and geometric scaling matching between the conductive array structure parameters and the actual branch wellbore structure. The similarity criterion system is constructed based on the actual geological parameters, fluid properties of the target low-permeability gas reservoir, and the wellbore structure parameters of the target branch well. The similarity criterion system includes geometric similarity coefficients, pressure similarity coefficients, flow similarity coefficients, flow similarity coefficients, and resistance similarity coefficients. The data acquisition unit is used to apply a DC voltage to the boundary of the reservoir simulation unit to simulate the gas reservoir formation supply boundary pressure, simulate the wellbore flow process under production pressure differential through the circuit system connected to the branch wellbore simulation unit, and acquire real-time current data at the simulated wellbore outlet, as well as voltage field distribution data inside the physical simulation model. The reservoir seepage law determination unit is used to determine the actual production capacity data of the target gas reservoir branch well based on the real-time current data and the flow similarity coefficient, determine the actual pressure field distribution data inside the gas reservoir based on the voltage field distribution data and the pressure similarity coefficient, and analyze the wellbore interference effect and reservoir seepage law of the branch well based on the actual production capacity data and the actual pressure field distribution data. The parameter scheme output unit is used to repeatedly collect real-time current data and voltage field distribution data by adjusting the structural parameters of the branch well simulation unit to obtain branch well production capacity data under different combinations of structural parameters, analyze the influence of each structural parameter on the branch well, and output the optimal structural parameter scheme of the branch well corresponding to the target gas reservoir.

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