Sulfur Deposition Prediction Method for High-Sulfur Fractured Gas Reservoirs Based on Fractal Medium Theory

Abstract

The present invention discloses a method for predicting sulfur deposition in high-sulfur fractured gas reservoirs based on the fractal medium theory. This method collects experimental data on the sulfur solubility of acid gases under the temperature, pressure ranges and natural gas composition conditions of typical high-sulfur gas reservoirs, and uses statistical analysis and multiple regression analysis methods to establish a prediction model for the sulfur solubility of elemental sulfur applicable to such gas reservoirs. On this basis, combining the fractal medium theory, gas-water seepage theory and sulfur solubility pressure gradient function, a mathematical model for predicting sulfur deposition in gas wells of high-sulfur fractured gas reservoirs is established, and comparisons and verifications are carried out. The purpose of the present invention not only provides theoretical guidance and technical support for the reliable assessment of the sulfur plugging damage status of reservoirs in high-sulfur fractured gas reservoirs, but also lays a foundation for the optimization of the operating system of high-sulfur gas wells, the decision-making of plug removal measures and the treatment of sulfur deposition in gas reservoir reservoirs.

Description

Technical Field

[0001] The present invention belongs to the field of quantitative prediction and evaluation of sulfur deposition in acid gas reservoir reservoirs, and particularly relates to a method for predicting sulfur deposition in high-sulfur fractured gas reservoirs based on the fractal medium theory. Background Art

[0002] As an unconventional oil and gas resource, high-sulfur fractured gas reservoirs are widely distributed globally. In recent years, sulfur blockage problems in gas well bores and reservoirs have been common in the high-sulfur fractured gas reservoirs successively developed in China. Accurate prediction of elemental sulfur solubility and sulfur deposition in high-sulfur gas wells is the premise and foundation for optimizing the working system of such gas wells, treating sulfur deposition, and formulating plugging removal measures.

[0003] Generally, under the conditions of the original reservoir temperature and pressure, elemental sulfur in high-sulfur gas reservoirs generally exists in the form of compounds (mainly polysulfide hydrogen). During the exploitation of high-sulfur fractured gas reservoirs, as the reservoir pressure drops, the solubility of elemental sulfur in acid natural gas changes. When the reservoir reaches the critical temperature and pressure for sulfur precipitation, elemental sulfur begins to precipitate and deposit in pore spaces and fractures. In addition to sulfur deposition in the matrix, natural fractures, as important seepage channels for natural gas in fractured gas reservoirs, sulfur deposition can cause blockage of fractures, increasing the seepage resistance of the gas phase, and further leading to a decrease in reservoir porosity and permeability. With the continuous exploitation of the gas reservoir, the sulfur blockage problem in the near-wellbore area of the reservoir becomes increasingly serious, and a serious sulfur blockage pollution area is generated near the wellbore. As the pollution area gradually expands, when the sulfur blockage problem is serious, it may even lead to the shutdown of gas wells, increasing the workover and sulfur deposition treatment costs of gas wells. In addition, after the fractured gas reservoir is put into development, formation water or edge-bottom water is likely to flow into the wellbore along the fractures. Coupled with the sulfur blockage effect in the reservoir near the gas wellbore, the liquid-carrying capacity of the gas well may be insufficient, resulting in a significant decrease in the gas well production, ultimately affecting the gas reservoir development effect and economic benefits.

[0004] Therefore, accurately predicting the elemental sulfur solubility in acidic natural gas and the sulfur plugging condition of gas wells in high-sulfur fractured gas reservoirs at different development stages has important theoretical significance and practical value for guiding the development of such gas reservoirs. At present, the Roberts sulfur saturation model based on Darcy's law and the Roberts extension model of non-Darcy flow are widely used in the prediction of sulfur deposition in conventional gas reservoirs. Many scholars have also derived quantitative mathematical models of sulfur deposition in gas wells that are suitable for conventional gas reservoirs and consider different flow states and well types. However, there is a technical gap in the theoretical and technical research on the quantitative characterization and prediction of sulfur deposition in natural fractured gas reservoirs in China. The mathematical model and prediction method established with conventional gas reservoirs as the research object are difficult to reflect the real reservoir conditions and formation fluid seepage laws of high-sulfur fractured gas reservoirs. Applying them to such gas reservoirs will lead to a large deviation between the prediction results of reservoir sulfur deposition and the actual situation. In the development practice of such gas reservoirs, the mismatch between theoretical models and actual conditions is one of the key problems that plague gas reservoir measures decision-making. If the sulfur plugging of gas wells cannot be accurately predicted and evaluated, it will be difficult for technicians to truly understand the sulfur deposition dynamics of the formation near the gas wellbore, and it will be impossible to carry out sulfur removal and plugging removal measures in a timely manner. When sulfur plugging is serious, it will not only increase the plugging removal cycle and cost of the gas well, but may even cause the gas well to be scrapped.

[0005] The method for predicting sulfur deposition in high-sulfur fractured gas reservoirs based on fractal medium theory provided by the present invention not only provides theoretical guidance and technical support for reliable evaluation of sulfur plugging damage in gas wells in high-sulfur fractured gas reservoirs, but also lays a foundation for optimizing the working system of high-sulfur gas wells, making decisions on plugging relief measures and controlling sulfur deposition in gas reservoirs. Summary of the invention

[0006] The purpose of the present invention is to provide a method for predicting sulfur deposition in high-sulfur fractured gas reservoirs based on fractal medium theory, which solves the problem of poor applicability of conventional gas reservoir models and provides technical support for the efficient development of high-sulfur fractured gas reservoirs.

[0007] Specifically, the present invention collects experimental data on sulfur solubility of acidic natural gas under the conditions of temperature, pressure range and natural gas composition of typical high-sulfur gas reservoirs, and uses statistical analysis and multiple regression analysis methods to establish a prediction model for element sulfur solubility applicable to such gas reservoirs. On this basis, combined with fractal medium theory, gas-water seepage theory and sulfur solubility pressure gradient function, a mathematical model for predicting sulfur deposition in gas wells of high-sulfur fractured gas reservoirs is established, and the mathematical model of the present invention is compared and verified with the previous model, in order to provide a theoretical basis for the decision-making of reservoir plugging measures and the formulation of gas well working system for high-sulfur fractured gas reservoirs.

[0008] The technical route of the method for predicting sulfur deposition in high-sulfur fractured gas reservoirs based on fractal medium theory implemented by the present invention is as follows: Figure 1As shown in the figure. The overall technical route is divided into three major parts: the equation for the change in sulfur solubility with pressure in high-sulfur gas reservoirs, the mathematical model for predicting sulfur deposition in gas wells of high-sulfur fractured gas reservoirs, and field applications.

[0009] The premise for establishing the equation for the change in sulfur solubility with pressure in high-sulfur gas reservoirs is to establish a sulfur solubility equation for high-sulfur gas reservoir applicable to the reservoir temperature and pressure range of typical high-sulfur gas reservoirs. The theoretical basis for establishing the mathematical model for predicting sulfur deposition in gas wells of high-sulfur fractured gas reservoirs is the gas-water seepage theory and the fractal medium theory. The fractal medium requires mathematical characterization of the fractal porosity and permeability of the fractured medium, and the relative permeability of the fractured medium. On this basis, based on the seepage theory and the sulfur solubility pressure gradient function (or the equation for the change in sulfur solubility with pressure in high-sulfur gas reservoirs), a mathematical model for predicting sulfur deposition in gas wells of fractal fractured gas reservoirs is established.

[0010] To achieve the above object, the technical solution of the present invention is as follows:

[0011] I. Equation for the change in sulfur solubility with pressure in high-sulfur gas reservoirs

[0012] The equation for the change in sulfur solubility with pressure is the basis for establishing the sulfur deposition prediction model for high-sulfur fractured gas reservoirs based on the fractal medium theory. Since the experimental test cost of the solubility of acidic gas elemental sulfur is high, the experimental equipment requirements are high, and the H2S gas is toxic and there may be a leakage risk. Many researchers have established various empirical and semi-empirical formulas for predicting the solubility of acidic gas elemental sulfur. Chrastil (1982) established an empirical solubility equation based on thermodynamic principles, and this equation has been widely used to predict the solubility of elemental sulfur in mixed fluids (Equation 1).

[0013]

[0014] In the formula, C s is the solubility of elemental sulfur, g / m 3 ; ρ is the fluid density, kg / m 3 ; T is the temperature, K; k, M, N are empirical constants, which can be obtained by regression of experimental data.

[0015] The Chrastil (1982) model shows a large prediction error in predicting the sulfur solubility of acid gases. Many researchers have made various forms of extensions, such as del Valle & Aguilera, Adachi & Lu, and Méndez-Santiago & Teja, etc. For the above models, del Valle & Aguilera and Adachi & Lu only consider the effects of temperature and density on the sulfur solubility of acid gases, and the influence of pressure on sulfur solubility is only reflected through the change in the density of the mixed gas. The M-S-T model not only emphasizes the temperature and density dependence of sulfur solubility in acid gases but also reflects the direct influence of pressure on sulfur solubility. Therefore, the present invention uses the M-S-T model as the equation form of the sulfur solubility prediction model for high-sulfur gas reservoirs to reduce the sulfur solubility prediction error caused by the difference in the equation form of the prediction model.

[0016] The expression of the M-S-T model is as follows:

[0017] Tln(C s P) = A + Bρ + CT (2)

[0018] In the formula, C s is the molar fraction solubility of the solute, dimensionless; P is the pressure, Pa; T is the temperature, K; ρ is the density of the solvent in the saturated state, kg / m 3 ; A, B, and C are the experimental fitting coefficients of the equation, K, K·m 3 ·kg -1 , dimensionless.

[0019] By transforming the above formula, the equation form of the sulfur solubility prediction model in acid gases can be obtained as:

[0020]

[0021] The density of natural gas can be expressed by the following formula:

[0022]

[0023] In the formula, ρ is the density of sour natural gas, kg / m 3 ; M a is the molecular weight of air, 28.97 g / mol; γ g is the relative density of the gas; P is the pressure, MPa; Z is the gas deviation factor; T is the temperature, K; R is the universal gas constant, 8.314472 cm 3 ·MPa·mol -1 ·K -1 .

[0024] By combining Equation (3) and Equation (4), we can obtain

[0025]

[0026] When predicting sulfur deposition, for a specific high-sulfur gas reservoir, the underground fluid seepage is usually regarded as an isothermal process. Reservoir pressure, natural gas density, and gas composition are the key factors controlling sulfur deposition in high-sulfur gas reservoirs. By taking the derivative of the above equation with respect to pressure, the equation for the change in sulfur solubility with pressure in high-sulfur gas reservoirs can be obtained as follows:

[0027]

[0028] In the formula: is the change in sulfur solubility with pressure, dless.

[0029] II. Mathematical Model for Predicting Sulfur Deposition in Gas Wells of High-Sulfur Fractured Gas Reservoirs

[0030] Assumptions for model establishment: a. The reservoir is isotropic; b. The gas satisfies the high-speed non-Darcy seepage law, and the liquid phase satisfies the Darcy (linear) seepage law; c. Considering that the overall reservoir temperature changes little, the influence of temperature change on sulfur solubility can be ignored; d. The migration of precipitated sulfur is not considered; e. The sulfur saturation in the reservoir is zero under initial conditions; e. Consider the original formation water; f. The reservoir is a fractured reservoir; g. Other pollutions of the gas well (such as geometric skin, mechanical skin, mineralized skin, etc.) are not as serious as sulfur blockage pollution; h. The reservoir compaction effect is not considered.

[0031] (1) Fractal porosity and permeability of fracture media

[0032] There are microcracks, microfractures, fractures, and faults of different scales inside the reservoir of fractured gas reservoirs, and there is a certain degree of self-similarity among them. Fractal theory is a powerful tool for describing rough, irregular, complex, and self-similar structures. It was proposed by the French-American mathematician Mandelbrot to study complex phenomena with self-similar characteristics.

[0033] Currently, most modeling methods for multiple fractures are based on the flow of matrices / fractures at different scales, where it is assumed that the fracture network is connected and equivalent to a homogeneous medium of Euclidean geometry. To describe unconventional fractured reservoirs in more detail, the relationship between fractal permeability and porosity is introduced to represent the heterogeneity of the reservoir, and the fractional dimension D value can quantitatively describe the development degree of pores and fractures in the reservoir. Chang and Yortsos (1990) first proposed using fractal medium theory to describe natural fracture networks and gave the basic forms of fractal porosity and fractal permeability of fracture media in the radial coordinate system, and the expressions are as follows:

[0034]

[0035] where: D is the mass fractal dimension, dimensionless; θ is the conduction exponent, dimensionless; d is the Euclidean embedding dimension, dimensionless; for specific reservoir conditions, θ and d can generally be regarded as fixed values. A is the point density parameter, m -D ; V s is the volume of each point, m 3 ; G is the geometric coefficient, m 3-d ; m is the fracture network parameter, m θ+2 ; r is the radius from the wellbore center, m; φ is the porosity, in decimals; k is the permeability, m 2 .

[0036] The above equation is simplified

[0037]

[0038] where: k0, φ0, and r are the reservoir permeability, porosity, and radial distance respectively, m 2 , in decimals, m. The information of A, V s , G, and m in equations (7) and (8) is included in and terms. Thus, this equation serves as the general form of the relationship between the fractal porosity and permeability of a natural fracture reservoir.

[0039] (2) Relative permeability model of fractured media

[0040] Generally speaking, the spatial scale, direction, and morphology of the fracture network are essentially random, and the fluid flow path is very complex. Studying the characteristics of two phases in the fracture network is a huge challenge. Compared with porous media, the flow law of fluids in fractured media varies greatly. For fractured media, the relative permeability is no longer a single function of saturation and is affected by various factors. In addition, the models established by most scholars are affected by inherent assumptions to varying degrees. Therefore, choosing an appropriate relative permeability model for fractured media is particularly important in practical engineering calculations.

[0041] Many scholars have established various semi-empirical or empirical models for predicting the relative permeability of fractured media. A representative model is the "X" linear model (11) proposed by Romm (1966) based on the two-phase seepage experiment of ideal smooth fractures, which is widely used in many numerical simulators currently. This model assumes that the two-phase fluids do not interfere with each other when flowing in the fractures, ignoring the irreducible water saturation and gas-water capillary pressure. This model has poor adaptability to natural fractured reservoirs and does not consider the influence of flow regime changes on relative permeability.

[0042] K rw = S w (11)

[0043] K rg = S g (12)

[0044] The Corey (1954) model and its improved models are widely used to calculate the gas-water relative permeability of porous media. These models are derived from the Kozeny-Carman equation and capillary pressure function, and have good adaptability in porous media, but they cannot reflect the two-phase seepage characteristics of fractured media.

[0045]

[0046] Where:

[0047] The two-phase relative permeability model for fractured media systems derived by Fourar and Lenormand (2001) shows that relative permeability is not only a function of saturation, but also a function of fluid viscosity. However, the model does not consider the existence of irreducible fluids or capillary forces.

[0048]

[0049] For high-sulfur fractured gas reservoirs, when the reservoir pressure drops to the critical pressure for sulfur precipitation, elemental sulfur begins to deposit in the reservoir. The reservoir pore space and fractures will be occupied by the deposited sulfur, resulting in damage to the reservoir physical properties. The degree of damage to gas-phase flow caused by deposited sulfur depends on the relative permeability of the gas phase. Roberts (1997) provided an empirical formula for relative permeability and sulfur saturation:

[0050]

[0051] H. Mei et al. also proposed a similar empirical formula for relative permeability and sulfur saturation:

[0052] k rg = k g / k = (1 - S s ) m (18)

[0053] However, the influence law of sulfur deposition in fractured media on relative permeability is complex. The relative permeability functions adopted by Roberts (1997) and H. Mei (2006) above can only reflect the empirical relationship between gas-phase permeability and sulfur saturation in porous media. This function cannot reflect the inherent properties of the media, fluid properties, interactions between fluids, and the flow relationship of two-phase fluids after the influence of deposited sulfur on the media structure.

[0054] When Slavko Nesic (2020) studied the influence of suspended solids in injected water on relative permeability during water injection operations, he used the so-called rock quality index R under the influence of suspended solids RQI The pore size distribution parameter λ was modified to obtain the oil-water relative permeability relationship under the influence of suspended solids, and good prediction results were achieved. However, the definition of rock quality is relatively vague and has no clear physical meaning, still falling within the category of empirical relationships. The established relative permeability correction relationship is as follows:

[0055]

[0056] Many scholars have applied the generalized Corey model and achieved good calculation results. This model reflects the two-phase seepage law of fractured media by adjusting the pore size distribution parameter λ, and the expression is as follows:

[0057]

[0058]

[0059] When the pore size distribution parameter λ → ∞, this equation can be used to study the two-phase flow characteristics in fractures.

[0060] For high-sulfur fractured gas reservoirs, after the deposition of elemental sulfur in the reservoir, the pore-fracture structure and the pore size distribution of the fractured media will change, the reservoir porosity and permeability will decrease, and the relative permeability will also change accordingly. There are significant differences in the flow capacity between solids and gas-liquid fluids. The elemental sulfur precipitated from natural gas may deposit in place in the pore-fracture structure, and fine particles may also be suspended in the gas-liquid fluids and migrate in the fractured media. Experiments cannot accurately quantify the deposition sulfur saturation, nor can they obtain the relative permeability of the gas-liquid-solid three-phase. Currently, there are no relevant experimental methods and experimental standards. Based on the understanding of the sulfur plugging experiment test results, there is a certain relationship between the fracture pore size distribution and sulfur deposition. The following relationship is introduced to represent the deposition sulfur saturation S s The relationship with the pore size distribution parameter λ:

[0061]

[0062] In the formula: λ represents the pore size distribution parameter of the fractured media after sulfur deposition; λ i represents the pore size distribution parameter of the fractured media in the original state; a and b are experimental fitting coefficients.

[0063] A significant advantage of the above formula is that the influence of sulfur deposition on the gas-liquid relative permeability of the fractured media is reflected by changing the pore size distribution parameter λ, and only the relative change relationship of the gas-liquid relative permeability with saturation under the influence of sulfur deposition needs to be explored. It can meet the engineering calculation requirements both from the experimental and application perspectives.

[0064] Substituting the above empirical formula (23) into the generalized Corey model (Equations 21 - 22) can obtain the relative permeability function relationship that is finally applicable to fractured reservoirs and considers the influence of sulfur deposition (sulfur saturation).

[0065] (3) Mathematical model for predicting sulfur deposition in gas wells of fractal fractured gas reservoirs

[0066] With the continuous progress of production and development in high - sulfur gas reservoirs, elemental sulfur gradually precipitates in pore spaces and fractures. Based on the Robert (1997) formula, the sulfur deposition volume in the reservoir can be expressed as:

[0067]

[0068] In the formula, V s is the sulfur precipitation volume, m 3 ; ρ s is the sulfur density, kg / m 3 ; t is the production time of the gas well, d or s; P is the formation pressure, MPa (or Pa in the SI unit system); B g is the natural gas volume coefficient, dimensionless; q gsc is the gas production of the sulfur - containing gas well, m 3 / d (or m 3 / s in the SI unit system).

[0069] For porous media, the ratio of the deposited sulfur volume to the total pore volume in the initial state is defined as the sulfur saturation, denoted by the symbol S s . This parameter can accurately quantify the status or degree of elemental sulfur deposition in the reservoir. At the radial distance dr, the deposited sulfur saturation S s can be expressed by the following formula

[0070]

[0071] In the formula: φ i is the initial porosity of the porous media, in decimal; h is the thickness of the gas layer, m; r is the radial distance, m.

[0072] For fractal fracture media, the fractal porosity φ(r) can be used to replace φ i to obtain the deposited sulfur saturation S sf in fractal fracture media, as follows:

[0073]

[0074] During the high - speed production process of gas wells, high - speed non - Darcy effects are likely to occur in the near - wellbore zone. According to the quadratic equation proposed by Forchheimei, the gas phase satisfies the following formula:

[0075]

[0076] where k is the absolute permeability, 10 -3 μm 2 (or m in the SI unit system 2 ); P is the formation pressure, MPa (or Pa in the SI unit system); β is the Forchheimer coefficient, 1 / m; ρ g is the gas-phase density, kg / m 3 ; v g is the gas-phase seepage velocity, m / s; r is the radial distance, m; μ w , μ g are the viscosities of the aqueous phase and the gas phase, mPa·s (or Pa·s in the SI unit system), respectively.

[0077] For a fractured porous medium, the gas phase satisfies

[0078]

[0079] The gas-phase seepage velocity can be expressed as:

[0080]

[0081] where: q gsc is the surface volume flow rate of natural gas, 10 4 m 3 / d (or m 3 / s in the SI unit system); B g is the gas formation volume factor, dimensionless; h is the gas reservoir thickness, m.

[0082] Combining Equation (28) and Equation (29), we get

[0083]

[0084] Evans and Evans (1988) considered the gas-water two-phase seepage characteristics, replaced the absolute permeability k with the effective gas permeability k g , and corrected the porosity φ with the gas saturation S g to obtain the empirical equation for the (effective) non-Darcy flow coefficient in a two-phase system as follows:

[0085]

[0086] where Sg and Sgr are the gas saturation and the residual gas saturation, respectively, in decimals; φ is the porosity, in decimals; C β is the non-Darcy flow constant, m 3 / 2 ; χ and θ are experimental constants. Usually, χ takes the value of 5 / 4 and θ is 3 / 4. Wong (1970) obtained the non-Darcy flow constant C β with a value range of 3.2×10 -9~3.2×10 -7 m 3 / 2 。The non-Darcy flow constant is generally affected by the pore-fracture structure. For different rocks, the value of C β varies greatly, and the non-Darcy flow constant of cores with developed natural fractures is larger than that of sandstone cores.

[0087] Substituting Equation (24) into Equation (26), then

[0088]

[0089] Combining Equations (17-18), (23), and (30-32), the following equation holds:

[0090]

[0091] Simplifying the above equation, let

[0092]

[0093] where S w takes the average water saturation of the reservoir, in decimals.

[0094] Therefore, the change in sulfur saturation with time in the fractal fracture medium can be abbreviated as

[0095]

[0096] According to the principle of material balance, for a gas reservoir with active edge and bottom water at a certain development time, it should be satisfied that: the underground volume of the cumulative produced natural gas and formation water = the underground volume expansion of natural gas + the volume expansion of irreducible water and rock + the water influx volume. That is

[0097]

[0098] Rewriting Equation (35) as

[0099]

[0100] Obviously, the left end of Equation (36) is the increase in formation water saturation up to the current time. At this time, the formation water saturation is:

[0101]

[0102] Compared with the volume change of gas, the volume expansion of irreducible water and rock is very small and can be ignored. Therefore, there is:

[0103]

[0104] In the formula: G p is the cumulative gas production of the gas well, ×108 m 3 (or SI unit system m 3 ); B gi is the volume coefficient of natural gas in the original state, dimensionless; B g is the volume coefficient of natural gas, dimensionless; W p is the cumulative water production of the gas well, ×10 8 m 3 (or SI unit system m 3 ); B wi is the volume coefficient of formation water in the original state, dimensionless; B w is the volume coefficient of formation water, dimensionless; G is the original geological reserve of the gas well, ×10 8 m 3 (or SI unit system m 3 ); S wi is the initial formation water saturation, decimal; C w is the compressibility of formation water, MPa -1 (or SI unit system Pa -1 ); C f is the compressibility of rock, MPa -1 (or SI unit system Pa -1 ); Δp is the formation pressure drop, MPa (or SI unit system Pa); W e is the cumulative water influx, ×10 8 m 3 (or SI unit system m 3 ).

[0105] When t = 0, S sf = 0, from Equation (34), we can get

[0106]

[0107] Equation (39) is the prediction model of sulfur saturation in high-sulfur fractal fractured media. When the non-Darcy flow term B = 0, the above equation is the prediction model under Darcy flow conditions. The numerical integration method can be used to calculate the sulfur saturation at different positions.

[0108] It should be noted that the above equation cannot obtain an exact function expression through indefinite integral solution, and can only be solved by numerical integration method, and the matlab numerical solution can be used. Secondly, simple unit conversion is required for the above calculation, and the units can be unified to the SI unit system.

[0109] III. Field application.

[0110] Based on the basic static and dynamic data of a high-sulfur gas reservoir and a typical sulfur-bearing gas well, the sulfur deposition prediction method for high-sulfur fractured gas reservoirs based on the fractal medium theory proposed by the present invention can efficiently evaluate the damage of sulfur plugging in the reservoir during the production of gas wells in this type of gas reservoir, providing technical support for the decision-making of reservoir unplugging measures and efficient development of high-sulfur fractured gas reservoirs.

[0111] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0112] 1. The sulfur deposition prediction method for high-sulfur fractured gas reservoirs based on the fractal medium theory provided by the present invention solves the problem of poor reliability of current model predictions and provides technical support for the efficient development of high-sulfur fractured gas reservoirs;

[0113] 2. Based on the fractal medium theory and seepage theory, combined with the prediction model of the solubility of elemental sulfur in acidic gas, this method establishes a mathematical model for predicting sulfur deposition in gas wells of high-sulfur fractured gas reservoirs. This model provides theoretical guidance for the decision-making of reservoir unplugging measures and the formulation of gas well operating systems in high-sulfur fractured gas reservoirs. Description of the Drawings

[0114] Figure 1 is the technical roadmap implemented by the present invention.

[0115] Figure 2 is the production curve of a gas well in the main production area.

[0116] Figure 3 is the gas-water relative permeability curve.

[0117] Figure 4 is the variation diagram of high-pressure physical properties of sour natural gas with pressure.

[0118] Figure 5 is the variation curve of sulfur solubility with pressure.

[0119] Figure 6 is the variation curve of the change amount of sulfur solubility with pressure.

[0120] Figure 7 is the comparison diagram of the relationship curves between sulfur solubility and pressure.

[0121] Figure 8 is the relationship curve between sulfur saturation and production time.

[0122] Figure 9 is the variation curve of sulfur saturation with production time under different reservoir pressure conditions.

[0123] Figure 10 is the variation curve of sulfur saturation with production time under different mass fractal dimension conditions.

[0124] Figure 11is the sulfur saturation at different production times and radial distances. Detailed implementation manners

[0125] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0126] Figure 1 As shown, it is the technical roadmap of the sulfur deposition prediction method for high-sulfur fractured gas reservoirs based on the fractal medium theory implemented by the present invention. As shown in the figure, it is specifically divided into three parts: the equation for the change in sulfur solubility with pressure in high-sulfur gas reservoirs, the mathematical model for predicting sulfur deposition in gas wells in high-sulfur fractured gas reservoirs, and field applications.

[0127] The sulfur deposition prediction method for high-sulfur fractured gas reservoirs based on the fractal medium theory proposed by the present invention takes a certain gas field in Sichuan as an example, and the specific implementation steps are as follows:

[0128] S1. Reservoir and fluid characteristics of the target block.

[0129] The main gas-bearing formation of a certain gas field in Sichuan is the Changxing Formation. The natural gas is mainly methane, and the H2S content ranges from 3.38% to 17.05%. It belongs to a carbonate high-sulfur fractured gas field. The gas reservoir temperature is 380K, the original formation pressure is 67MPa, the current formation pressure is 52MPa, the effective thickness is 47.2m, the average porosity is 16.8%, and the average permeability is 10.52×10 -3 μm 2 , the natural gas viscosity is 0.027mPa·s, the relative density is 0.7517, and the gas supply radius is 700m. This gas reservoir has active edge water, and the production is relatively stable after production. In July 2019, the gas production decreased rapidly and the water production increased rapidly. Wellbore test data show that a large amount of precipitated sulfur has accumulated in the wellbore of this gas well, the wellbore liquid accumulation has gradually increased, and it is difficult for the gas well to carry liquid for production. In March 2021, the gas well stopped production. By taking various measures such as sulfur removal and plugging removal, optimizing the working system of the gas well, and drainage gas production, the productivity of the gas well has been gradually restored. At present, the reasonable plugging removal timing for this type of gas reservoir and the mechanism of elemental sulfur plugging in the reservoir are not clearly understood, and the accurate quantification of sulfur deposition has become a difficult point in the engineering calculation of high-sulfur fractured gas reservoirs.

[0130] Table 1 Experimental data of the well stream components of this well

[0131]

[0132] Table 2 Model calculation parameter table

[0133]

[0134]

[0135] S2. Calculate the unknown parameters in the sulfur solubility prediction model.

[0136] To obtain the unknown parameters in the sulfur solubility prediction model, a large number of experimental data on elemental sulfur solubility under typical sour gas reservoir conditions need to be collected. The unknown parameters in the model are obtained by fitting the experimental data, and the prediction error of the experiment is evaluated.

[0137] To avoid large prediction errors caused by broad prediction conditions (such as temperature, pressure) or component differences, a large number of experimental data that meet the reservoir conditions need to be collected for nonlinear regression. By analyzing the range of experimental values of sulfur solubility, data points that do not conform to the laws of thermodynamics are excluded to reduce the prediction error of the model. The data required for model establishment are from the experimental data reported by Brunner and Woll (1980). See Table 3 for the experimental data and model prediction results. See Table 4 for the fitting parameter values of the M-S-T model.

[0138] Table 3 Experimental data of elemental sulfur solubility under different experimental conditions (compiled from Brunner and Woll, 1980)

[0139]

[0140]

[0141]

[0142] Table 4 Regression coefficients and errors of the M-S-T sulfur solubility model

[0143]

[0144] As can be seen from Table 4, the prediction model R 2 reached 0.8497, the MAE was 0.000225, the MRE was 33.83%, and the RMAE was 0.0003. The prediction error of this model can meet the needs of engineering calculations.

[0145] S3. High-pressure physical properties parameters of sour natural gas.

[0146] In order to quantify the elemental sulfur deposition in high-sulfur fractured gas reservoirs, the calculation of formula (39) requires the participation of high-pressure physical property parameters of acidic gases. Due to the lack of complete experimental test data on the high-pressure physical properties of acidic gases in this well, the use of relevant empirical formulas, theoretical formulas and charts has become an effective option for obtaining high-pressure physical property parameters. Due to the influence of non-light components in the natural gas of high-sulfur gas reservoirs, using conventional calculation methods for high-pressure physical property parameters will result in large errors. According to the reservoir temperature and pressure conditions, combined with the PVT experimental results of this well, calculation methods for the deviation factor and viscosity applicable to high-sulfur natural gas are selected (mainly).

[0147] ① Deviation factor (or deviation coefficient) of acidic natural gas.

[0148] At present, there are many calculation methods for the deviation factor of natural gas, mainly including three categories: chart method, equation of state method and empirical formula method. The chart method is a simple and practical method. By calculating the reduced temperature and reduced pressure and referring to the chart, the deviation factor value under specific conditions can be obtained. However, the deviation factor results obtained when looking up the chart are greatly affected by human factors and are not conducive to programming calculation. The deviation factor calculated by the equation of state method has a certain accuracy, but the calculation process is relatively complex and not conducive to engineering applications.

[0149] The present invention calculates the deviation factor of the gas by using relevant empirical formulas. For

[0150] The presence of non-hydrocarbon gases such as H2S in high-sulfur acidic gas reservoirs makes the critical parameters of the gas different from those of conventional natural gas, and it must be corrected during the calculation process. The empirical calculation method for the deviation factor adopted in the present invention is the Hall-Yarborough (H-Y method), and the formula is as follows:

[0151]

[0152] In the formula: ρ r is the reduced density. The calculation formula of ρ r is:

[0153]

[0154] In the formula, p pr and T pr are the pseudo-reduced pressure and pseudo-reduced temperature of the gas respectively.

[0155]

[0156] In the formula: Z is the gas deviation factor, dimensionless; p pr is the pseudo-reduced pressure, dimensionless; T pr is the pseudo-reduced temperature, dimensionless; p pc is the pseudo-critical pressure, MPa; Tpc is the pseudo-critical temperature, K.

[0157] Combining Equation (40) and Equation (41) gives

[0158]

[0159] Applying the iterative method to solve Equation (44) can obtain the deviation factor at the corresponding pseudo-reduced pressure and pseudo-reduced temperature. The applicable range of this method is: 1.2 ≤ T pr ≤ 3.0; 0.1 ≤ P pr ≤ 24.0.

[0160] The Hall-Yarborough (H-Y method) has good applicability when calculating the deviation factor of natural gas with low non-hydrocarbon component content. However, when the content of non-hydrocarbon components such as H2S and CO2 is relatively high, there will be certain deviations in the critical parameters of the gas, and it is necessary to correct them. The present invention uses the commonly used Wichert-Aziz method to correct the deviation factor of sour gas.

[0161] This method obtains the correction coefficient ε according to the corrected curve chart, corrects the critical temperature and critical pressure of the sour gas, and then calculates the deviation factor. The correction formula is

[0162] T pc ′ = T pc - 0.556ε (45)

[0163]

[0164] Some scholars have proposed an empirical calculation formula for the value of ε, thus eliminating the trouble of looking up the curve chart. The calculation formula is:

[0165]

[0166] In the formula: p pc ′ is the corrected pseudo-reduced pressure, dimensionless; T pc ′ is the corrected pseudo-reduced temperature, dimensionless; ε is the correction coefficient; B is the molar content of H2S in natural gas, in decimals;

[0167] A is the molar content of CO2 and N2 in natural gas, in decimals.

[0168] Based on the reservoir temperature and pressure conditions, PVT experimental test data, etc., first use the Newton-Raphson iterative technique to solve the Hall-Yarborough equation, and use the Sutton method to calculate the critical parameters of sour gas (T pc = 212.723K, p pc= 5.21533 MPa), after obtaining the natural gas compressibility factor, the deviation factor of the sour gas is corrected using the Wichert-Aziz method. Calculate the relationship curve between the deviation factor of the sour gas and pressure, see Figure 4 .

[0169] ② Viscosity of sour natural gas.

[0170] Due to the presence of non-hydrocarbon components in the sour gas, the calculation formulas for the pseudo-critical parameters and viscosity need to be corrected. The Lee et al. method and the YJS correction method are selected to calculate the viscosity of the gas. The empirical formula for calculating viscosity by the Lee et al. method is:

[0171]

[0172] Where:

[0173]

[0174] X = 3.448 + 548 / T + 0.01M g (50)

[0175] Y = 2.447 - 0.224X (51)

[0176] The YJS correction method mainly corrects the K value, and the calculation formula is as follows:

[0177]

[0178] For natural gas with 0.6 < γ g < 1.0

[0179]

[0180] For natural gas with 1.0 < γ g < 1.52

[0181]

[0182] In the formula: μ g Viscosity of natural gas, mPa·s; ρ g Is the density of natural gas, g / cm 3 .

[0183] According to the above formulas, the physical property parameters of the natural gas in this gas reservoir (or gas well) can be calculated. See the change curve of sour natural gas with the gas reservoir pressure Figure 4 .

[0184] ③ Formation volume factor of natural gas.

[0185] The definition formula of the formation volume factor of natural gas is

[0186]

[0187] Under ground standard conditions, the volume of gas is expressed by the ideal gas state equation as:

[0188]

[0189] Under the conditions of reservoir pressure p and temperature T, the volume V occupied by the same amount of natural gas g is:

[0190]

[0191] Combining the above equations, the calculation formula for the natural gas volume coefficient is:

[0192]

[0193] In the formula: B g is the natural gas volume coefficient, dimensionless; V gsc is the volume of natural gas under ground standard conditions, m 3 ; V g is the volume of the same mass of natural gas under formation conditions, m 3 ; R is the universal gas constant, MPa·m 3 / kmol·K. For the curve of the natural gas volume coefficient varying with reservoir pressure, see Figure 4 .

[0194] ④ Natural gas density.

[0195] The density of natural gas is the mass of natural gas per unit volume, and its calculation formula is:

[0196]

[0197] The relative density of natural gas is the ratio of the density of natural gas to the density of air under the same temperature and pressure, which is:

[0198]

[0199] Combining Equation (59) and Equation (60), the calculation formula for the natural gas density is:

[0200]

[0201] In the formula: ρ g is the natural gas density, kg / m 3 ; γ g is the relative density of natural gas; M g is the molecular weight of natural gas; M air is the molecular weight of air, taking 28.96. The natural gas density varies with the reservoir pressure, seeFigure 4 。

[0202] S4, Average water saturation of the reservoir within the control range of the gas well.

[0203] Based on the material balance principle (Equation 38), calculate the current average water saturation of the formation within the control range of the gas well. Organize the production data of the gas well and calculate the relevant high-pressure physical property parameters using Equation (58). See Table 5.

[0204] Table 5 Calculation data of the average water saturation of the gas well

[0205]

[0206] The calculated average water saturation of the reservoir within the control range of the gas well is 0.3037.

[0207] S5, Comparative analysis of sulfur solubility calculation models.

[0208] The unknown parameters in the solubility prediction model were obtained through regression in Section S2. Combining with the calculation results of the high-pressure physical property parameters of the acid gas, the curve of sulfur solubility varying with pressure ( Figure 5 ) was calculated, and then the curve of the change amount of sulfur solubility varying with pressure and pressure ( Figure 6 ) was obtained.

[0209] Since the definitions and dimensions of units such as acid gas concentration in natural gas or sulfur solubility in mixed gas often vary in different countries and regions. The most commonly used units in the United States, Canada and other countries are percentage concentration (i.e., mole or volume percentage), 10 6 volume fraction, ppm, etc., while China adopts the SI international system of units, and the commonly used concentration units are kg / m 3 , g / m 3 or %(volume fraction). In this way, unnecessary errors are often caused due to inconsistent dimensions or definitions when comparing the calculation results of relevant sulfur solubility. In order to compare and analyze the prediction model established in this invention with the previous models, it is necessary to convert the concentration units first. The conversion derivation between mass and percentage concentration is as follows:

[0210] Assume that the mass concentration of acid gas or any other gas contained in 1 m 3 of natural gas is m (kg / m 3 ), and the percentage concentration is C (%, volume percentage). Then the mass of acid gas contained in 1 m 3 of natural gas and the mass concentration are equivalent in value. Therefore, the following gas state equation can be established:

[0211]

[0212] In the formula: P is the gas pressure, MPa; V is the gas volume, m3 ; m is 1 m 3 The mass of acid gas or other gas, kg; M is the molecular weight of the gas, kg / kmol, which can be obtained from the common component table; R is the universal gas constant, MPa·m 3 ·kmol -1 ·K -1 .

[0213] R can be determined by the following formula:

[0214]

[0215] At p sc = 0.101325 MPa, T sc = 293.15 K under standard conditions, Z sc = 1, V m = 22.4 m 3 / kmol, so it can be seen from formula (63) that:

[0216]

[0217] Under standard conditions, from formula (62), we can get:

[0218]

[0219] Substitute the values of Z sc and V m into formula (61) to get:

[0220]

[0221] Then the unit conversion relationship between mass concentration and volume percentage concentration is

[0222]

[0223] In the formula: the unit of mass concentration of m is kg / m 3 , if it is converted to the commonly used g / m 3 as the unit, then there is

[0224]

[0225] It can be seen from formula (68) that as long as the mass concentration is substituted, the corresponding volume percentage concentration can be obtained. Conversely, when the volume percentage concentration is known, the corresponding mass concentration can be obtained from formula (69), and the conversion relationship is as follows:

[0226]

[0227] Therefore, the relationship curve between sulfur solubility and pressure was converted into mass concentration and compared with the Roberts-Chrastil model (1997), the Li Hong (2015) model, and the Guo Xiao (2016) model. The summary table of the models is shown in Table 6.

[0228] Table 6 Summary of Sulfur Solubility Prediction Models

[0229]

[0230] From the comparison of the prediction results of the above models, it can be seen that the prediction results of the Roberts-Chrastil model are much higher than those of the Li Hong (2015), Guo Xiao (2016), and the model of the present invention. The possible reason is that the widely used Roberts-Chrastil model is established based on the experimental data of sulfur solubility in gases with specific compositions or single-component gases and is not applicable to the prediction of sulfur solubility in sour natural gas. The prediction results of the present invention and the Li Hong (2015) and Guo Xiao (2016) models have a high overall overlap, but there are certain differences in the prediction results within a certain local pressure range ( Figure 7 ). Using the publicly available experimental data of Brunner and Woll (1980) and under the same temperature, pressure, and sour gas density conditions, the Li Hong (2015), Guo Xiao (2016), and the model of the present invention were respectively used to predict the sulfur solubility under specific experimental conditions and sour gas properties, and the prediction results were compared (Table 7).

[0231] Table 7 Comparison of Experimental Data of Sulfur Solubility and Prediction Results of Multiple Models

[0232]

[0233]

[0234]

[0235] Table 8 Comparison of Average Error of Sulfur Solubility Prediction

[0236]

[0237] As can be seen from Tables 7 and 8, from the perspective of applicable conditions and average relative error, the prediction accuracy of the model of the present invention is higher and the application range is wider.

[0238] S6. Calculation results of sulfur deposition in gas wells of high-sulfur fractured gas reservoirs.

[0239] Based on the static and dynamic data of example blocks and gas wells, calculate the sulfur saturation near the wellbore of gas wells in high-sulfur fractured gas reservoirs. Since the overall prediction result of the sulfur solubility of the Roberts-Chrastil model is much higher than the experimental value and other prediction models. Therefore, only the sulfur saturation prediction results of the models of Li Hong (2015) and Guo Xiao (2016) are compared with the model of the present invention. Calculate the variation curve of sulfur saturation with time at a position 2 m away from the wellbore under the current reservoir conditions and natural gas composition, see Figure 8 .

[0240] From Figure 8 it can be seen that compared with the model of the present invention and the model of Guo Xiao (2016), the model of Li Hong (2015) has the problem of overestimating the sulfur saturation at the same production time. The reason is that under the current reservoir temperature and pressure conditions, the sulfur solubility prediction result of the model of Li Hong (2015) is significantly higher than other models ( Figure 8 ). Secondly, since under the current reservoir temperature and pressure conditions, the sulfur solubility prediction result of the present invention is close to that of the Guo Xiao model, the corresponding sulfur saturation prediction results are also very close ( Figure 8 ).

[0241] Calculate the variation curve of sulfur saturation with production time at a position 2 m away from the wellbore under different formation pressures with the current reservoir temperature and natural gas composition ( Figure 9 ). Generally, under the same reservoir temperature and natural gas composition, the higher the pressure, the higher the sulfur solubility of elemental sulfur in sour natural gas. Correspondingly, at the same production time, the sulfur saturation near the wellbore will also increase ( Figure 9 ). The above calculation results fully reflect the relationship between sulfur solubility and the corresponding sulfur saturation, and prove the correctness of the model of the present invention.

[0242] Use the model of the present invention to calculate the example gas well, and the variation curve of sulfur saturation with production time under different mass fractal dimension conditions (D takes 1, 2, 3) at a radial distance of 2 m, see Figure 10 .

[0243] From Figure 10It can be seen that as the mass fractal dimension increases, the sulfur deposition rate becomes slower. Only when the production time of the gas well is relatively long, serious sulfur deposition will occur at a position 2 m from the wellbore in the near-wellbore area. When the mass fractal dimension is smaller, sulfur deposition blockage is likely to occur at the position 2 m from the wellbore in the near-wellbore area soon after the gas well is put into production. Although in the example calculation, different mass fractal dimensions are assumed to compare and analyze the influence of the mass fractal dimension on sulfur deposition, it should be understood that generally, the higher the mass fractal dimension, the smaller the pore throats, and the more complex the fracture pore structure and capillary structure in the pores. Since the deposited sulfur is generated during the migration of sour natural gas in the formation, it is more difficult for natural gas to pass through the pore structure in a particularly tight reservoir. Correspondingly, it is also difficult for sulfur deposition particles to block in extremely fine pore spaces, that is, the smaller the pores, the greater the two-phase seepage resistance, and the less conducive to sulfur deposition. On the contrary, if the fracture pore medium has relatively more large pores, the effective permeability of the gas-water two-phase increases, and it is easier to have the condition of pore sulfur deposition blockage. For cores with well-developed natural fractures, the measured mass fractal dimensions usually vary significantly, which is determined by the extremely strong microscopic heterogeneity of fractured reservoirs. Therefore, the quantity and representativeness of core samples are the inevitable requirements for obtaining the average fractal characteristics of fractured reservoirs or fracture media.

[0244] The sulfur saturation change curves of the example gas well calculated by the model of the present invention at different production times and different radial distances (r takes 0.5 m, 2 m, 5 m) are shown in Figure 11 .

[0245] It can be Figure 11 seen that the closer to the wellbore, the greater the sulfur saturation at the same production time. The sulfur deposition position is mainly concentrated around 2 m near the wellbore. The closer to the wellbore, the more serious the sulfur blockage in the reservoir. If the reservoir plugging removal measures are not carried out in time or the gas production volume of the gas well is not adjusted, it will lead to greater difficulty and higher cost in future plugging removal. It is recommended to carry out sulfur removal and plugging removal measures once every about 2 - 3 years, and then appropriately adjust the sulfur removal and plugging removal frequency according to the productivity recovery and production organization situation in the later stage.

[0246] It should be noted that the purpose of comparing the sulfur solubility model of the present invention with the previous models is to verify the reliability of the model through comparison, rather than to deny the work of predecessors. The purpose of the present invention is to establish a sulfur deposition prediction method applicable to high-sulfur fractured gas reservoirs, solve the problem of mismatch between the theoretical model and the actual situation in the development practice of such gas reservoirs, and provide theoretical guidance and technical support for the reliable evaluation of the sulfur plugging damage situation of gas well reservoirs in high-sulfur fractured gas reservoirs.

[0247] The above are only the preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A prediction method for sulfur deposition in high-sulfur fractured gas reservoirs based on the fractal medium theory, characterized in that By collecting the experimental data of the sulfur solubility of acid gas under the temperature, pressure range and natural gas composition conditions of typical high-sulfur gas reservoirs, a statistical analysis and multiple regression analysis method is adopted to establish a prediction model for the solubility of elemental sulfur in gas reservoirs; Combined with the fractal medium theory, gas-water seepage theory and sulfur solubility pressure gradient function, a derivative relationship of sulfur saturation S sf with respect to time t was established: Simplify the above formula and let The change amount of sulfur saturation with time in the simplified high-sulfur fractured gas reservoir is When t = 0, S sf = 0, the final sulfur saturation S of the high-sulfur fractured gas reservoir can be obtained sf Integral relationship expression of the prediction model: The above formula is used as the prediction model for sulfur saturation in high-sulfur fractured gas reservoirs. When the non-Darcy flow term B = 0, the above formula is the prediction model under Darcy flow conditions, and the sulfur saturation at different positions is calculated by using the numerical integration method.

2. The sulfur deposition prediction method for high-sulfur fractured gas reservoirs based on the fractal medium theory according to claim 1, characterized in that The M-S-T model is used as the equation of the sulfur solubility prediction model for high-sulfur gas reservoirs. The expression of the M-S-T model is as follows Tln(C s P) = A + Bρ + CT where C s is the molar fraction solubility of the solute, g / m 3 or kg / m 3 or percentage concentration; P is the pressure, MPa or Pa; T is the temperature, K; ρ is the density of the solvent in the saturated state, kg / m 3 ; A, B, and C are the experimental fitting coefficients of the equation; Transform the M-S-T model into an explicit form as: To calculate the sulfur solubility using the above formula, it is first necessary to obtain the density of sour natural gas. According to the ideal gas state equation and the definition of relative density, the sulfur solubility prediction model is rewritten as The equation for the change amount of sulfur solubility with pressure in high-sulfur gas reservoirs is: Where: M a is the molecular weight of air, 28.97 g / mol; γ g is the relative density of the gas; P is the pressure, MPa; Z is the gas deviation factor; T is the temperature, K; R is the universal gas constant, 8.314472 cm 3 ·MPa·mol -1 ·K -1 , is the change in sulfur solubility with pressure, dless.

3. The sulfur deposition prediction method for high-sulfur fractured gas reservoirs based on the fractal medium theory according to claim 1, characterized in that The assumptions for establishing the mathematical model for predicting sulfur deposition in gas wells in high-sulfur fractured gas reservoirs include: a. The reservoir is isotropic; b. The gas satisfies the high-speed non-Darcy seepage law, and the liquid phase satisfies the Darcy linear seepage law; c. The reservoir temperature is constant; d. The migration of precipitated sulfur is not considered; e. The sulfur saturation is zero under the initial conditions; e. The original formation water is considered; f. The reservoir is a fractured reservoir; g. Other pollutions in the gas well are not serious compared with the sulfur blockage pollution; h. The reservoir compaction effect is not considered.

4. The sulfur deposition prediction method for high-sulfur fractured gas reservoirs based on the fractal medium theory according to claim 1, characterized in that The basic forms of the fractal porosity and fractal permeability of the fracture medium in the radial coordinate system are expressed as follows: where: k0, φ0, and r are the reservoir permeability, porosity, and radial distance, respectively, in m 2 , decimal, m; D is the mass fractal dimension, dimensionless; θ is the conduction exponent, dimensionless; d is the Euclidean embedding dimension, dimensionless.

5. The sulfur deposition prediction method for high-sulfur fractured gas reservoirs based on the fractal medium theory according to claim 1, characterized in that The following empirical relationship is used to quantify the sulfur deposition saturation S s The relationship with the pore size distribution parameter λ in the generalized Corey model; According to the understanding of the sulfur plugging experiment test results, for the porous medium polluted by sulfur plugging, the pore size distribution parameter λ and the sulfur saturation S s The empirical relationship is as follows:

6. The sulfur deposition prediction method for high-sulfur fractured gas reservoirs based on the fractal medium theory according to claim 1, wherein The relative permeability correction relationship is as follows: where: λ represents the pore size distribution parameter of the fractured medium after sulfur deposition; λ i represents the pore size distribution parameter of the fractured medium in its original state; a and b are experimental fitting coefficients; S w takes the average water saturation of the reservoir, %.

7. The sulfur deposition prediction method for high-sulfur fractured gas reservoirs based on the fractal medium theory according to claim 1, wherein The average water saturation in the reservoir within the control range of the gas well at different production times is determined based on the material balance principle of the water drive gas reservoir.

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