Method and device for predicting production parameters of sour gas reservoir and computer equipment

Abstract

The application provides a kind of acid gas reservoir production parameter prediction method, device and computer equipment, belong to numerical simulation technical field, method includes: using the first prediction model based on numerical simulation, according to reservoir characteristic parameter, current well bottom pressure value simulation reservoir sulfur deposition under the current value of production parameter;Using the second prediction model considering wellbore sulfur deposition, according to the production parameter obtained in the last step, current well bottom pressure value is solved under the current value of gas production under the action of wellbore sulfur deposition;Step 3, compare whether the gas production in the production parameter under the action of reservoir sulfur deposition and the gas production under the action of wellbore sulfur deposition are consistent;If yes, the current value of production parameter is determined as the predicted value of production parameter, otherwise, update the current well bottom pressure value until the two gas productions are consistent. The above method improves the accuracy of production parameter prediction by considering the reservoir-wellbore coupling integrated simulation under the influence of wellbore sulfur deposition.

Description

Technical Field

[0001] This application belongs to the field of numerical simulation technology for gas reservoir engineering, specifically relating to a method for predicting production parameters of sour gas reservoirs, a device for predicting production parameters of sour gas reservoirs, a machine-readable storage medium, and a computer device. Background Technology

[0002] Acidic gas reservoirs refer to gas reservoirs containing acidic gases (such as H2S or CO2). In the mid-to-late stages of acidic gas reservoir development, particularly high-sulfur reservoirs, sulfur deposition due to temperature and pressure drops has severely impacted normal natural gas production. Damage to reservoirs and wellbores caused by sulfur deposition is becoming increasingly common. Therefore, clarifying the patterns of sulfur deposition and exploring its impact on production is crucial. Current research on sulfur deposition prediction and calculation mainly focuses on two aspects: wellbore and reservoir. Firstly, existing technologies for predicting sulfur deposition in wellbores generally concentrate on establishing and optimizing sulfur solubility models. Based on these models and combined with heat and mass transfer theories, mathematical prediction models of wellbore temperature, pressure, and sulfur deposition are established to explore the impact of sulfur deposition on gas well production indicators. Secondly, existing technologies for predicting sulfur deposition in reservoirs mainly focus on the establishment and optimization of numerical simulation models for sulfur deposition in reservoirs. For example, in a numerical simulation technology for an ultra-deep acidic gas reservoir that considers liquid sulfur precipitation, a reservoir numerical simulation model considering liquid sulfur precipitation was established based on the gas-liquid sulfur phase permeability curve and applied to the dynamic study of gas wells.

[0003] However, as mentioned above, most simulation and prediction schemes for sulfur deposition in acidic gas reservoirs treat the wellbore and reservoir as independent research objects without considering them simultaneously, which greatly affects the accuracy of gas well production parameter prediction. Gas well production parameters include gas production (wellhead gas production), bottom hole pressure (flowing bottom hole pressure, bottom hole flowing pressure), and wellhead pressure. Summary of the Invention

[0004] The purpose of this application is to provide a method for predicting production parameters of acidic gas reservoirs, a device for predicting production parameters of acidic gas reservoirs, a machine-readable storage medium, and a computer device to overcome the shortcomings of the prior art, which cannot simultaneously consider the inaccurate prediction data of gas well production parameters caused by wellbore sulfur deposition and reservoir sulfur deposition.

[0005] To achieve the above objectives, the first aspect of this application provides a method for predicting production parameters of sour gas reservoirs, comprising:

[0006] Step 1: Using the first prediction model to perform numerical simulation of production parameters on reservoir characteristic parameters and bottom hole pressure, the current value of production parameters under dynamic changes in reservoir sulfur deposition is simulated based on the obtained reservoir characteristic parameters of the study area and the current bottom hole pressure value selected between the reservoir pressure value and the wellbore outlet pressure value.

[0007] Step 2: Utilize a multiphase flow control model based on partial production parameters including bottom hole pressure to solve for a second prediction model that predicts production parameters different from the partial production parameters. Based on the current values ​​of water production and sulfur production in the production parameters obtained under reservoir sulfur deposition, and the current bottom hole pressure value, calculate the current value of gas production under dynamically changing wellbore sulfur deposition.

[0008] Step 3: Compare the current value of gas production in the production parameters under reservoir sulfur deposition with the current value of gas production under wellbore sulfur deposition. If they are consistent, the current value of the production parameters is determined as the current value of the production parameters in the study area. Otherwise, the bottom hole pressure value is selected again from the reservoir pressure value and the wellbore outlet pressure value as the updated value of the current bottom hole pressure value, and the process is skipped to trigger the execution of Step 1.

[0009] In a specific embodiment of this application, the first prediction model is a numerical simulation model based on a component model.

[0010] In specific embodiments of this application, the reservoir characteristic parameters include reservoir temperature, reservoir pressure, water saturation, and sulfur saturation.

[0011] In a specific embodiment of this application, the multiphase flow control model includes a wellbore miscible flow model. The equations of the wellbore miscible flow model include the liquid holdup equation, the mass conservation equation, the energy conservation equation, the momentum conservation equation, and the phase drift velocity equation, wherein:

[0012] The liquid holdup equation is expressed as:

[0013] The phase drift velocity equation is expressed as: u w =βu g +γ;

[0014] In the above formulas, A represents the effective cross-sectional area of ​​sulfur deposition dynamics, and α w Indicates liquid holdup, u w U represents the velocity of the water phase. g denoted by β, denoted by γ, denoted by x, and t, which represents the time step when solving the multiphase flow control model.

[0015] In a specific embodiment of this application, the mass conservation equation, momentum conservation equation, and energy conservation equation are expressed as follows:

[0016] mass conservation equation:

[0017] Momentum conservation equation:

[0018] Energy conservation equation:

[0019] In the above formulas, A represents the effective cross-sectional area of ​​sulfur deposition dynamics, and α w α represents the liquid holdup. g U represents the gas phase volume fraction. w U represents the velocity of the water phase. g ρ represents the gas phase velocity. g P represents gas phase density, T represents pressure, and F represents temperature. wall ρ represents the wall friction coefficient. m C represents the average density of the phase. m U represents the specific heat capacity of a miscible fluid. m K represents the average velocity of a miscible fluid. wall The wellbore heat transfer coefficient is represented by g, g is represented by gravitational acceleration, θ is represented by the wellbore inclination angle, D is represented by the wellbore diameter, and T is represented by T. wall This indicates the wellbore temperature.

[0020] In a specific embodiment of this application, the multiphase flow control model includes a sulfur precipitation model, the equation of which is expressed as follows:

[0021] q GS =k·Amax(C S -C 溶解度 ,0);

[0022] Where, q GS The term represents the sulfur precipitation term, k represents the sulfur precipitation relaxation factor, A represents the effective cross-sectional area of ​​sulfur deposition dynamics, and C represents the sulfur precipitation term. S C represents the total concentration of elemental sulfur. 溶解度 This represents the maximum solubility of solid sulfur, which is determined based on experimental data of solid sulfur physical dissolution. max() represents the function that takes the largest value.

[0023] In a specific embodiment of this application, the multiphase flow control model includes a sulfur transport model, and the sulfur transport equations of the sulfur transport model are expressed as follows:

[0024] Total sulfur mass conservation equation:

[0025] Sulfur transport equation:

[0026] Where, q sets =A·γ(C SS ,u m )·β(P,T)·C SS ,

[0027] In the above formulas, A represents the effective cross-sectional area of ​​sulfur deposition dynamics, and C S C represents the total concentration of elemental sulfur. SS q represents the sulfur fixation concentration. GS q represents the sulfur precipitation term. sets Represents the sulfur fixation deposition term, γ(C SS ,u m ) represents the sulfur deposition rate on the wall, β(P,T) represents the nucleation factor reflecting the degree of sulfur precipitation, P represents pressure, T represents temperature, and u m denoted by , x represents the average velocity of the multiphase fluid, x represents the wellbore diameter position, and t represents the time step when solving the multiphase flow control model.

[0028] In a specific embodiment of this application, the initial value of the current bottom hole pressure value selected from the reservoir pressure value and the wellbore outlet pressure value is the average value of the reservoir pressure value and the wellbore outlet pressure value. If the current value of gas production in the production parameters under reservoir sulfur deposition is greater than the current value of gas production under wellbore sulfur deposition, then the updated value of the current bottom hole pressure value is the average value of the reservoir pressure value and the current bottom hole pressure value. If the current value of gas production in the production parameters under reservoir sulfur deposition is less than the current value of gas production under wellbore sulfur deposition, then the updated value of the current bottom hole pressure value is the average value of the wellbore outlet pressure value and the current bottom hole pressure value.

[0029] In a specific embodiment of this application, when the current value of the dynamically changing gas production under the sulfur deposition in the wellbore is obtained by calculating the current value of the water production and sulfur production in the production parameters under the sulfur deposition in the reservoir and the current bottom hole pressure, the liquid holdup equation is solved explicitly, the prediction step of the velocity parameters in the multiphase flow control model is solved semi-implicitly, the correction step of the pressure parameters in the multiphase flow control model is expressed as a tridiagonal linear equation system and solved implicitly, the correction step of the velocity parameters in the multiphase flow control model is solved explicitly, and the temperature solution based on the energy conservation equation is solved semi-implicitly.

[0030] In a specific embodiment of this application, when the current value of the water production and sulfur production in the production parameters obtained under the sulfur deposition in the reservoir is calculated, and the current bottom hole pressure value is calculated, the current value of the gas production under the sulfur deposition in the wellbore is dynamically changed, the sulfur solidification and transport equation is explicitly solved.

[0031] A second aspect of this application provides a device for predicting production parameters of an acidic gas reservoir, comprising:

[0032] The first prediction module is used to perform numerical simulation of production parameters using the first prediction model that performs numerical simulation of production parameters based on the reservoir characteristic parameters and bottom hole pressure of the study area. Based on the obtained reservoir characteristic parameters of the study area and the current bottom hole pressure value selected between the reservoir pressure value and the well outlet pressure value, the module simulates the current value of production parameters under the dynamic change of reservoir sulfur deposition.

[0033] The second prediction module is used to execute a multiphase flow control model that reflects the wellbore sulfur deposition phenomenon based on specific production parameters including bottom hole pressure to predict a second prediction model that is different from the specific production parameters. The module calculates the current value of gas production under the dynamic change of wellbore sulfur deposition based on the current values ​​of water production and sulfur production in the production parameters under reservoir sulfur deposition and the current bottom hole pressure value.

[0034] The comparison module is used to compare whether the current value of gas production in the production parameters under reservoir sulfur deposition is consistent with the current value of gas production under wellbore sulfur deposition. If they are consistent, the current value of the production parameters is determined as the current value of the production parameters in the study area. Otherwise, the bottom hole pressure value is selected again from the reservoir pressure value and the wellbore outlet pressure value as the updated value of the current bottom hole pressure value, and the process jumps to trigger the execution of the first prediction model that uses the reservoir characteristic parameters and bottom hole pressure to perform numerical simulation of the production parameters. Based on the obtained reservoir characteristic parameters of the study area and the current bottom hole pressure value selected from the reservoir pressure value and the wellbore outlet pressure value, the dynamic changes in the current value of the production parameters under reservoir sulfur deposition are simulated.

[0035] A third aspect of this application provides a computer device, comprising:

[0036] The memory is configured to store instructions; and

[0037] The processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the method for predicting production parameters of an acidic gas reservoir according to the first aspect of this application.

[0038] A fourth aspect of this application provides a machine-readable storage medium storing instructions for causing a machine to perform a method for predicting production parameters of an acidic gas reservoir according to a first aspect of this application.

[0039] The above technical solution employs a first prediction model and a second prediction model. The first prediction model is a numerical simulation model that considers reservoir sulfur deposition, while the second prediction model is a multiphase flow control model that reflects wellbore sulfur deposition. The gas production prediction results of the second prediction model are used to constrain the gas production prediction results of the first prediction model. That is, by iteratively changing the bottom hole pressure value and repeatedly applying the first and second prediction models to simulate production parameters, the simulation is completed until the gas production of the first prediction model and the second prediction model are consistent under the same bottom hole pressure. Thus, the influence of wellbore sulfur deposition is considered in the process of predicting production parameters under reservoir sulfur deposition using the first prediction model. This achieves integrated reservoir-wellbore coupled simulation and prediction considering the influence of wellbore sulfur deposition, improving the prediction accuracy of production parameters for acidic gas reservoirs.

[0040] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0041] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings:

[0042] Figure 1 This schematically illustrates a first flowchart of a method for predicting production parameters of an acidic gas reservoir according to an embodiment of this application;

[0043] Figure 2 A second flowchart illustrating a method for predicting production parameters of an acidic gas reservoir according to an embodiment of this application is shown schematically.

[0044] Figure 3 The illustration shows a schematic diagram of an ideal three-dimensional geological model in a practical application example;

[0045] Figure 4 The illustration shows the bottom hole pressure obtained by conventional numerical simulation software and reservoir-wellbore coupling simulation process that simultaneously considers reservoir sulfur deposition and wellbore sulfur deposition in a practical application example without considering sulfur deposition.

[0046] Figure 5 The illustration shows the gas production obtained by conventional numerical simulation software and reservoir-wellbore coupling simulation process that simultaneously considers reservoir sulfur deposition and wellbore sulfur deposition in a practical application example without considering sulfur deposition.

[0047] Figure 6 This schematic diagram illustrates the bottom hole pressure obtained from a reservoir-wellbore coupling simulation process that takes into account the effects of wellbore sulfur deposition in a real-world application example.

[0048] Figure 7 This illustration shows a schematic diagram of the gas production obtained from a reservoir-wellbore coupling simulation process that takes into account the effects of wellbore sulfur deposition in a real-world application example.

[0049] Figure 8 This schematic diagram illustrates the composition of a production parameter prediction device for an acidic gas reservoir according to an embodiment of this application.

[0050] Figure 9 A schematic block diagram of a computer device according to an embodiment of this application is shown. Detailed Implementation

[0051] The specific implementation methods of the embodiments of this application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific implementation methods described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application.

[0052] If the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0053] To predict production parameters such as gas production, bottom hole pressure, and wellhead pressure in acidic gas reservoirs, numerical simulation software is used in an engineering application. Currently, commonly used numerical simulation software performs numerical simulation calculations that include both the reservoir and the wellbore. However, the wellbore simulation part uses ordinary pipe flow calculations, which do not consider fluid behavior and the production loss caused by sulfur deposition on the wellbore wall. However, for acidic gas reservoirs, sulfur deposition on the wellbore wall has a significant impact on production. Therefore, it is necessary to overcome the shortcomings of commonly used numerical simulation software in that it cannot consider the large errors in the simulation prediction of production parameters caused by sulfur deposition in the wellbore.

[0054] To overcome the above-mentioned defects, such as Figure 1 As shown in the embodiments, this application proposes a technical concept for reservoir-wellbore coupled numerical simulation considering the influence of wellbore sulfur deposition, and predicts the production parameters of acidic gas reservoirs based on the aforementioned technical concept. Specifically, the method for predicting the production parameters of acidic gas reservoirs in this application includes steps 1 to 3.

[0055] Step 1: Using the first prediction model to perform numerical simulation of production parameters on reservoir characteristic parameters and bottom hole pressure, the current value of production parameters under dynamic changes in reservoir sulfur deposition is simulated based on the obtained reservoir characteristic parameters of the study area and the current bottom hole pressure value selected between the reservoir pressure value and the wellbore outlet pressure value.

[0056] Step 2: Utilize a multiphase flow control model based on partial production parameters including bottom hole pressure to solve for a second prediction model that predicts one or more production parameters other than the partial production parameters described above. Based on the current values ​​of water production and sulfur production in the production parameters obtained under reservoir sulfur deposition, and the current bottom hole pressure value, calculate the current value of gas production under dynamically changing wellbore sulfur deposition.

[0057] Step 3: Compare the current value of gas production in the production parameters under reservoir sulfur deposition with the current value of gas production under wellbore sulfur deposition. If they are consistent, the current value of the production parameters under reservoir sulfur deposition is determined as the current value of the production parameters in the study area. Otherwise, the bottom hole pressure value is selected again from the reservoir pressure value and the wellbore outlet pressure value as the updated value of the current bottom hole pressure value, and the process is skipped to trigger the execution of Step 1.

[0058] Specifically, as mentioned above, reservoir characteristic parameters refer to reservoir parameters with multiple dimensions that affect changes in gas reservoir production parameters. For example, in a specific application, reservoir characteristic parameters include reservoir temperature, reservoir pressure, water saturation, and sulfur saturation. The specific selection of which dimensions of reservoir parameters to use for dynamic simulation of gas reservoir production parameters depends on the specific reservoir, and this application does not elaborate on each one in its embodiments. Sulfur saturation is calculated based on the total concentration of elemental sulfur. Some production parameters that include bottom hole pressure include bottom hole pressure, water production, and sulfur production.

[0059] The above embodiment combines a first prediction model and a second prediction model. The first prediction model is a numerical simulation model that considers reservoir sulfur deposition. This numerical simulation model uses reservoir characteristic parameters and bottom hole pressure as input parameters to predict gas reservoir production parameters. The second prediction model is a multiphase flow control model that considers wellbore sulfur deposition. The gas production predicted by the second prediction model constrains the gas production predicted by the first prediction model. The constraint means that by changing the bottom hole pressure value, the first prediction model and the second prediction model are used iteratively to simulate the production parameters until the gas production predicted by the first prediction model and the second prediction model are consistent. That is, under the same bottom hole flowing pressure conditions, the gas production predicted by the first prediction model and the second prediction model are consistent. Based on production practice, when gas production and bottom hole pressure are consistent, other production parameters are also consistent. Therefore, the above embodiment predicts production parameters based on the reservoir-wellbore coupling method that simultaneously considers reservoir sulfur deposition and wellbore sulfur deposition, and uses bottom hole pressure and gas production as verification variables in the iterative process. This incorporates the negative impact of wellbore sulfur deposition into the commonly used numerical simulation model that considers reservoir sulfur deposition, thereby improving the accuracy of production parameter prediction for acidic gas reservoirs.

[0060] It is important to understand that, firstly, the gas reservoir production parameters are dynamically changing throughout the entire gas reservoir development period. The current values ​​of production parameters under reservoir sulfur deposition or the current values ​​of gas production under wellbore sulfur deposition refer to the predicted values ​​of production parameters at the current time step in the numerical simulation. Secondly, to complete the simulation and prediction of production parameters throughout the entire gas reservoir development period, steps 1 to 3 need to be repeated at each time step. Finally, it is known that wellbore sulfur deposition is essentially a multiphase flow problem involving heat and mass transfer processes, involving the transport of gas, water, liquid sulfur, and solid sulfur particles in the wellbore. For such complex processes, numerical methods are usually used to solve the complex multiphase flow control equations. Therefore, in the existing technology, the multiphase flow control model reflecting wellbore sulfur deposition mainly includes the following two parts: 1) wellbore multiphase flow modeling and solving; 2) sulfur transport and deposition modeling and solving.

[0061] As an example, for modeling and solving multiphase flow in wellbores, a pressure balance model can be used. This involves treating the multiphase fluid as a miscible fluid and mathematically modeling its pressure balance. For instance, the pressure drop in the wellbore can be considered as the sum of several components, including the gravity of the miscible fluid, wall resistance, and convection. For modeling and solving sulfur transport and deposition, a sulfur solubility model is typically used to consider the temperature and pressure conditions for solid sulfur precipitation and to model sulfur deposition.

[0062] As an example, the first prediction model can be a numerical simulation model based on a compositional model. In practical applications, compositional models from known and publicly available numerical simulation software can be used as the first prediction model. Alternatively, the first prediction model can also adopt other known and publicly available numerical simulation models of reservoir sulfur deposition constructed through reservoir sulfur deposition prediction studies. Those skilled in the art can also use variations or improvements of these numerical simulation models of reservoir sulfur deposition in specific applications.

[0063] In one optional embodiment of this application, the initial value setting and updating of the current bottom hole pressure value adopts a bisection method. That is, the initial value of the current bottom hole pressure value selected between the reservoir pressure value and the wellbore outlet pressure value is the average of the reservoir pressure value and the wellbore outlet pressure value. If the current value of gas production in the production parameters under reservoir sulfur deposition is greater than the current value of gas production under wellbore sulfur deposition, then the updated value of the current bottom hole pressure value is the average of the reservoir pressure value and the current bottom hole pressure value. If the current value of gas production in the production parameters under reservoir sulfur deposition is less than the current value of gas production under wellbore sulfur deposition, then the updated value of the current bottom hole pressure value is the average of the wellbore outlet pressure value and the current bottom hole pressure value. Setting the bottom hole pressure value using the bisection method accelerates the convergence process of the gas production in the production parameters under reservoir sulfur deposition and the gas production in the production parameters under wellbore sulfur deposition, thereby improving the efficiency of production parameter prediction for acidic gas reservoirs.

[0064] As mentioned above, the construction and solution process of the complex multiphase flow control equations considering wellbore sulfur deposition still has room for optimization. For example, the influence of the actual gas compressibility effect and the effective cylinder diameter's friction on the wall after sulfur deposition are not considered. Based on this, in an improved embodiment of this application, an improved multiphase flow control model reflecting wellbore sulfur deposition is proposed. This multiphase flow control model is consistent with the prior art, including a wellbore miscible flow model, a sulfur precipitation model, and a sulfur transport model. However, the improved wellbore miscible flow model's equations include liquid holdup equations, mass conservation equations, energy conservation equations, momentum conservation equations, and phase shift velocity equations. That is, based on the control equations of the miscible fluid constructed based on the three fundamental conservation laws of physics (mass conservation, momentum conservation, and energy conservation), the model further models the multiphase wall friction and the slip rate between phases, completing the closure conditions of the control equations. Thus, complete modeling of non-isothermal transient multiphase flow is achieved. Furthermore, the improved sulfur transport model is based on the sulfur nucleation mechanism, and its sulfur deposition prediction results are more accurate than other sulfur transport modeling methods. This allows the sulfur deposition prediction results to be consistent with field observations, and it can be used as a model for realizing real-time sulfur removal. In practical applications, after matching with field construction measures, real-time sulfur removal can be achieved, thereby avoiding the impact of wellbore sulfur deposition on the production of acidic gas reservoirs.

[0065] The equations for the wellbore miscible flow model are shown below:

[0066] Liquid holdup equation:

[0067] mass conservation equation:

[0068] Momentum conservation equation:

[0069] Energy conservation equation:

[0070] Phase drift velocity equation: u w =βu g +γ;

[0071] In the above equations: A represents the effective cross-sectional area of ​​sulfur deposition dynamics, in m². 2 ;α w Indicates liquid holdup, in percentages (%); α g This indicates the gas phase volume fraction, expressed in %; u w This represents the velocity of the water phase, measured in m / s; u g ρ represents the gas phase velocity, with units of m / s; g This represents the density of the gas phase, expressed in kg / m³. 3 P represents pressure; T represents temperature; F represents pressure. wall ρ represents the wall friction coefficient, which is dimensionless; m This represents the average density of the phase, expressed in kg / m³. 3 C m The specific heat capacity of a miscible fluid is expressed in J / (kg·K); u m K represents the average velocity of a miscible fluid, measured in m / s. wall This represents the heat transfer coefficient of the wellbore, with units of J / (m²). 2 ·s·℃); β represents the flow pattern factor, dimensionless; γ represents the interphase slip rate, in m / s; x represents the wellbore diameter position; t represents the time step when solving the multiphase flow control model; g represents gravitational acceleration; θ represents the wellbore inclination angle; D represents the wellbore diameter; T wall This indicates the wellbore temperature.

[0072] The equations for the sulfur precipitation model are shown below:

[0073] q GS =k·Amax(C S -C 溶解度 ,0);

[0074] In the above formula, q GS This represents the sulfur precipitation term, with units of g / (s·m). 3); k represents the sulfur precipitation relaxation factor, which is dimensionless; A represents the effective cross-sectional area of ​​sulfur deposition dynamics, in m². 2 C S This indicates the total concentration of elemental sulfur, in g / m³. 3 C 溶解度 This indicates the maximum solubility of sulfur, expressed in g / m³. 3 The maximum solubility of solid sulfur is determined based on the experimental data of solid sulfur physical dissolution, and max() represents the function of taking the largest value.

[0075] The equations for the sulfur transport model are shown below:

[0076] Total sulfur mass conservation equation:

[0077] Sulfur transport equation:

[0078] Where, q sets =A·γ(C SS ,u m )·β(P,T)·C SS ,

[0079] In the above formulas, A represents the effective cross-sectional area of ​​sulfur deposition dynamics, in m². 2 C S This indicates the total concentration of elemental sulfur, in g / m³. 3 C SS This indicates the sulfur fixation concentration, expressed in g / m³. 3 ;q GS This represents the sulfur precipitation term, with units of g / (s·m). 3 );q sets This represents the sulfur deposition term, with units of g / (s·m). 3 );γ(C SS ,u m ) represents the sulfur deposition rate on the wall, in m / s; β(P,T) represents the nucleation factor reflecting the degree of sulfur precipitation, which is dimensionless; P represents pressure; T represents temperature.

[0080] As mentioned above, the solution process for complex multiphase flow control equations considering wellbore sulfur deposition often employs fully implicit iterative methods, which limit computational efficiency. Based on these shortcomings, an improved embodiment of this application proposes a solution method for an improved multiphase flow control model. This solution method uses a second-order TVD scheme for numerical discretization, which offers higher accuracy and smaller numerical dissipation error compared to the traditional first-order upwind scheme. In terms of solution strategy, this method adopts a semi-implicit iterative solution strategy for discrete systems, requiring only an implicit solution of a tridiagonal linear equation system (which can be solved quickly using the catch-up method). Compared with the traditional fully implicit method, which uses a block diagonal matrix solution, this method is more efficient. Specifically, it explicitly solves the liquid holdup equation, semi-implicitly solves the velocity parameter prediction step in the multiphase flow control model, expresses the pressure parameter correction step in the multiphase flow control model as a tridiagonal linear equation system and solves it implicitly, explicitly solves the velocity parameter correction step in the multiphase flow control model, semi-implicitly solves the temperature equation based on the energy conservation equation, and explicitly solves the sulfur solidification transport equation.

[0081] As an example, the sulfur transport equation based on the explicit solution method can be expressed as follows:

[0082]

[0083] In the above formulas, A represents the effective cross-sectional area of ​​sulfur deposition dynamics, and C S q represents the total concentration of elemental sulfur. GS q represents the sulfur precipitation term. sets Indicates the sulfur fixation deposition term, u m C represents the average velocity of a miscible fluid. SS denoted by , n represents the sulfur concentration, n represents the iteration step number, and i represents the grid number.

[0084] As an example, solving the temperature equation based on a semi-implicit solution method can be represented as follows:

[0085]

[0086] In the formula, A represents the dynamic effective cross-sectional area of ​​sulfur deposition, T represents the temperature, and ρ m C represents the average density of the phase. m U represents the specific heat capacity of a miscible fluid. m K represents the average velocity of a miscible fluid. wall T represents the heat transfer coefficient of the wellbore. wall T represents the wellbore temperature.

[0087] As an example, the liquid holdup equation, solved using an explicit solution method, can be expressed as follows:

[0088]

[0089] In the formula, A represents the effective cross-sectional area of ​​sulfur deposition dynamics, and α w Indicates liquid holdup, u w This indicates the velocity of the water phase.

[0090] As an example, the solution for the velocity prediction step based on a semi-implicit solution method can be represented as follows:

[0091]

[0092] In the formula, A represents the effective cross-sectional area of ​​sulfur deposition dynamics, and α g U represents the gas phase volume fraction. w U represents the velocity of the water phase. g ρ represents the gas phase velocity. g P represents gas phase density, T represents pressure, and F represents temperature. wall This represents the wall friction coefficient, and * represents the prediction step.

[0093] As an example, the solution to the pressure correction step based on the implicit solution method of the tridiagonal linear equation system can be expressed as follows:

[0094]

[0095] In the formula, A represents the effective cross-sectional area of ​​sulfur deposition dynamics, and α g ρ represents the gas phase volume fraction. g C represents the density of the gas phase. g This represents the gas compressibility factor, and * indicates the prediction step.

[0096] As an example, the solution for the velocity correction step based on the explicit solution method can be represented as follows:

[0097]

[0098] In the formula, u w U represents the velocity of the water phase. g β represents the gas phase velocity, γ represents the flow pattern factor, γ represents the interphase slip rate, * represents the prediction step, and a represents the matrix coefficient.

[0099] like Figure 2As shown, in one specific embodiment, the first prediction model adopts a component model from a known publicly available numerical simulation software, and the second prediction model uses the improved multiphase flow control model reflecting wellbore sulfur deposition phenomena described above. In the following application example, the improved multiphase flow control model reflecting wellbore sulfur deposition phenomena is named the sulfur deposition prediction module. Therefore, the process of predicting production parameters considering reservoir sulfur deposition and wellbore sulfur deposition in a reservoir-wellbore coupling manner may include steps 102 to 116. It should be understood that in a specific embodiment, all steps 102 to 116 may be included, or only some steps 102 to 116 may be included.

[0100] Step 102: Obtain a three-dimensional geological model of the study area for the development of acidic gas reservoirs. The three-dimensional geological model includes gas production wells and carbonate rock layers.

[0101] Step 104: Obtain numerical simulation parameters of the acidic gas reservoir and wellbore in the study area, namely the reservoir characteristic parameters mentioned above, including reservoir temperature, reservoir pressure, water saturation and sulfur saturation, etc. These parameters can be exported by numerical simulation software.

[0102] Step 106, set the initial bottom hole pressure value corresponding to the time step. The calculation process is as follows: P wf =(P max +P min ) / 2, P max P represents the reservoir pressure value corresponding to the current time step. min P represents the wellbore outlet pressure value. wf This indicates the current bottom hole pressure value.

[0103] Step 108: Calculate the production parameters of the acidic gas reservoir using numerical simulation software. Set the current bottomhole pressure value P in the numerical simulation software. wf Then, numerical simulation software is used to perform simulation calculations and record production parameters, such as the output data of gas, water, and sulfur. The gas production is recorded as Q. g,R .

[0104] Step 110, use the sulfur deposition prediction module to simulate and calculate gas production: combine the water and sulfur production data obtained in step 108 with the set bottom hole pressure value P. wf As input to the sulfur deposition prediction module, the sulfur deposition prediction module is called to calculate the gas production rate, which is denoted as Q. g,W .

[0105] Step 112: Compare the gas production Q calculated by the numerical simulation software. g,R Gas production Q calculated by the sulfur deposition prediction module g,W If Q g,R Q g,WThis indicates that the calculated bottom hole pressure is too low, resulting in even lower wellbore gas production. The bottom hole pressure is then calculated using the bisection method, and the bottom hole pressure value for the next iteration step k is set to P. wf =(P max +P k-1,wf ) / 2, P k-1,wf Indicates the bottom pressure of the current iteration step k-1, then proceeds to step 114; if Q g,R g,W This indicates that the calculated bottom hole pressure is too high, resulting in a larger gas production in the wellbore. Therefore, the bottom hole pressure value for the next iteration step k is set to P. wf =(P min +P k-1,wf ) / 2, then proceed to step 114; if Q g,R =Q g,W If so, proceed to step 116.

[0106] Step 114: After updating the current bottom hole pressure value using the bottom hole pressure value calculated by the bisection method, return to step 108 and continue to call the numerical simulation software and the sulfur deposition prediction module until convergence, that is, under the same bottom hole pressure, the gas production predicted by the numerical simulation software is consistent with the gas production predicted by the sulfur deposition prediction module.

[0107] Step 116: Return to step 106 and proceed to the next time step iteration until the simulation and prediction of gas reservoir production parameters are completed throughout the entire gas reservoir development period.

[0108] In the first practical application example, the simulation and prediction of gas reservoir production parameters are carried out for an ideal three-dimensional geological model of sulfur-free sedimentary gas reservoir. The main steps include:

[0109] Step A1: Establish an ideal three-dimensional geological model with an initial reservoir temperature of 120℃, a storage pressure of 57.67MPa, a permeability of 10mD, and a grid size of 31*31*30. A gas production well, Well 1, is located in the center of the model. Figure 3 The image shown is an ideal three-dimensional geological model.

[0110] Step A2: Export numerical simulation parameters of the acidic gas reservoir and wellbore using numerical simulation software. For example, the exported reservoir temperature is 120℃, the reservoir pressure is 57.67MPa, the water saturation is 0%, and the sulfur saturation is 0%.

[0111] Step A3: Set the initial bottom hole pressure value corresponding to the time step. The calculation process for the initial bottom hole pressure value is as follows: Reservoir pressure value P max =57.67MPa, wellbore outlet pressure value P min =8MPa, set the bottom hole pressure value P wf =(P max ​+P min ) / 2 = 32.835 MPa.

[0112] Step A4: Set the bottom hole pressure value to P in the numerical simulation software input file. wf =32.835MPa, use numerical simulation software to calculate for a certain period of time, record the gas production data, and denote the gas production data as Q. g,R Current gas production Q in the current time step g,R = 632,500 cubic meters / day.

[0113] Step A5, set the bottom hole pressure value P wf As input to the sulfur deposition prediction module, the sulfur deposition prediction module is invoked to predict the gas production rate, which is denoted as Q. g,W Q in the current time step gW = 643,700 cubic meters / day.

[0114] Step A6: Compare the gas production Q predicted by the numerical simulation software. g,R Gas production Q predicted by the sulfur deposition prediction module g,W Because of Q g,R g,W This indicates that the calculated bottom hole pressure is too high, so the bottom hole pressure in the next iteration step k is set to P. wf =(P min +P k-1,wf ) / 2, P k-1,wf Given the bottom hole pressure at the current iteration step k-1, therefore, the bottom hole pressure P at the next iteration step k is... wf =(P min +P k-1,wf ) / 2 = 20.4175 MPa.

[0115] Step A7, update the bottom hole pressure P wf Then return to step A4 and continue to call the numerical simulation software and sulfur deposition prediction module until convergence. When the first time step converges, the bottom hole pressure predicted by the numerical simulation software and the sulfur deposition prediction module are 25.98052 MPa and 25.98312 MPa, respectively.

[0116] Step A8: Return to step A3 and proceed to the iterative prediction for the next time step. (Example) Figure 4 The diagram shows the bottom hole pressure obtained by conventional numerical simulation software and the reservoir-wellbore coupled simulation process of this application, which considers both reservoir sulfur deposition and wellbore sulfur deposition, without considering sulfur deposition. Figure 5 The diagram shows the gas production obtained by conventional numerical simulation software and the reservoir-wellbore coupled simulation process of this application, which considers both reservoir sulfur deposition and wellbore sulfur deposition, without considering sulfur deposition. Figure 4 ​The blue box in the image represents the bottom hole pressure value calculated in this application. Figure 4 The blue line in the image represents the bottom hole pressure value calculated by conventional numerical simulation software. Figure 5 The blue box in the figure represents the gas production calculated in this application. Figure 5 The blue line in the figure represents the gas production calculated by conventional numerical simulation software. Combined with... Figure 4 and Figure 5 It can be seen that the errors in the bottom hole pressure and gas production predicted in this application are very small, which confirms the accuracy of the reservoir-wellbore coupled numerical simulation method that simultaneously considers wellbore sulfur deposition and reservoir sulfur deposition.

[0117] In the second practical application example, the simulation and prediction of gas reservoir production parameters are carried out for an ideal three-dimensional geological model of sulfurous sedimentary deposits in an acidic gas reservoir. The main steps include:

[0118] Step B1: Establish an ideal three-dimensional geological model with an initial reservoir temperature of 120℃, a storage pressure of 57.67MPa, a permeability of 10mD, and a grid size of 31*31*30. A gas production well, Well 1, is located in the center of the model. Figure 3 The image shown is an ideal three-dimensional geological model.

[0119] Step B2: Export numerical simulation parameters of the acidic gas reservoir and wellbore using numerical simulation software. For example, the exported reservoir temperature is 120℃, the reservoir pressure is 57.67MPa, the water saturation is 0%, and the sulfur saturation is 0.56%.

[0120] Step B3: Set the initial bottomhole pressure value corresponding to the time step. The calculation process for the initial bottomhole pressure value is as follows: Reservoir pressure value P max =40MPa, wellbore outlet pressure value P min =8MPa, set the bottom hole pressure value P wf =(P max +P min ) / 2 = 24MPa.

[0121] Step B4: Set the bottom hole pressure value to P in the numerical simulation software input file. wf =24MPa, call numerical simulation software to calculate for a certain period of time, record the gas production data, and denote the gas production data as Q. g,R Current gas production Q in the current time step g,R = 577,000 cubic meters / day.

[0122] Step B5: Combine the sulfur production data calculated in step B4 with the set bottomhole pressure value P. wf As input to the sulfur deposition prediction module, the sulfur deposition prediction module is invoked to predict the gas production rate, which is denoted as Q. g,W Q in the current time stepg,W = 562,000 cubic meters / day.

[0123] Step B6: Compare the gas production Q predicted by the numerical simulation software. g,R Gas production Q predicted by the sulfur deposition prediction module g,W Because of Q g,R Q g,W This indicates that the calculated bottom hole pressure is too low, resulting in a smaller predicted gas production by the sulfur deposition prediction module. Therefore, the bottom hole pressure for the next iteration step k is set to P. wf =(P max +P k-1,wf ) / 2, P k-1,wf Given the bottom hole pressure at the current iteration step k-1, therefore, the bottom hole pressure P at the next iteration step k is... wf =(P max +P k-1,wf ) / 2 = 32MPa.

[0124] Step B7, update bottom hole pressure P wf Then return to step B4 and continue to call the numerical simulation software and sulfur deposition prediction module until convergence. When the first time step converges, the bottom hole pressure is 26.51 MPa.

[0125] Step B8 returns to step B3 to begin iterative prediction for the next time step. (Example) Figure 6 The diagram shows the bottom hole pressure obtained from the reservoir-wellbore coupling simulation process, which considers both reservoir sulfur deposition and wellbore sulfur deposition in this application, under the condition of sulfur deposition. Figure 7 The diagram shows the gas production obtained from the reservoir-wellbore coupling simulation process, which considers both reservoir sulfur deposition and wellbore sulfur deposition in this application, taking into account sulfur deposition. Figure 6 The black dot in the middle represents the bottom hole pressure value obtained from the reservoir-wellbore coupling simulation process in this application. Figure 7 The black dots represent the gas production obtained from the reservoir-wellbore coupling simulation process in this application. (Combined with...) Figures 4 to 7 As can be seen, compared with the first practical application example, the bottom hole pressure simulated using the reservoir-wellbore coupled simulation process of this application, which simultaneously considers reservoir sulfur deposition and wellbore sulfur deposition, is higher than the bottom hole pressure simulated by conventional numerical simulation software. This is because this additional pressure drop needs to overcome the greater lift resistance caused by sulfur deposition. Furthermore, the gas production decreases significantly after considering wellbore sulfur deposition. Therefore, considering the wellbore sulfur deposition mechanism is crucial in the later stages of acidic gas reservoir production. This application, through reservoir-wellbore coupled simulation prediction that simultaneously considers both reservoir and wellbore sulfur deposition, overcomes the problem of large production errors caused by neglecting the temperature and pressure reduction and severe wellbore sulfur deposition phenomena in the later stages of acidic gas reservoir development.

[0126] Corresponding to the acidic gas reservoir production parameter prediction method in the above embodiments, Figure 8 The diagram illustrates the composition of the acid gas reservoir production parameter prediction device 500 provided in the embodiments of this application. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0127] like Figure 8 As shown, the acid gas reservoir production parameter prediction device 500 includes:

[0128] The first prediction module 510 is used to perform numerical simulation of production parameters using a first prediction model that performs numerical simulation of production parameters based on reservoir characteristic parameters and bottom hole pressure. Based on the obtained reservoir characteristic parameters of the study area and the current bottom hole pressure value selected between the reservoir pressure value and the well outlet pressure value, the module simulates the current value of production parameters under dynamic changes in reservoir sulfur deposition.

[0129] The second prediction module 520 is used to execute a multiphase flow control model based on partial production parameters including bottom hole pressure to predict a second prediction model that is different from the partial production parameters. The current value of water production and sulfur production in the production parameters under reservoir sulfur deposition and the current bottom hole pressure value are used to calculate the current value of gas production under dynamically changing wellbore sulfur deposition.

[0130] The comparison module 530 is used to compare whether the current value of gas production in the production parameters under reservoir sulfur deposition is consistent with the current value of gas production under wellbore sulfur deposition. If they are consistent, the current value of the production parameters is determined as the current value of the production parameters in the study area. Otherwise, the bottom hole pressure value is selected again from the reservoir pressure value and the wellbore outlet pressure value as the updated value of the current bottom hole pressure value, and the process is redirected to trigger the execution of the first prediction model that performs numerical simulation of production parameters using reservoir characteristic parameters and bottom hole pressure. Based on the obtained reservoir characteristic parameters of the study area and the current bottom hole pressure value selected from the reservoir pressure value and the wellbore outlet pressure value, the dynamic changes in the current value of the production parameters under reservoir sulfur deposition are simulated.

[0131] As an embodiment of this application, the acidic gas reservoir production parameter prediction device 500 can achieve the following: Figure 1 The embodiments shown are as well as other related method embodiments in this application.

[0132] The process by which each module in the acid gas reservoir production parameter prediction device 500 provided in this application implements its respective function can be specifically referred to the foregoing. Figure 1 The descriptions of the embodiments shown and other related method embodiments are not repeated here.

[0133] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. Their specific functions and technical effects can be found in the method embodiments section, and will not be repeated here. Furthermore, all of the above modules can be applied to computing devices that include memory and a processor.

[0134] Figure 9 A schematic block diagram of a computer device according to an embodiment of the present application is shown. In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown. Figure 9 As shown in the figure, the computer device includes a processor A01, a network interface A02, a display screen A04, an input device A05, and a memory (not shown) connected via a system bus. The processor A01 provides computing and control capabilities. The memory includes internal memory A03 and a non-volatile storage medium A06. The non-volatile storage medium A06 stores an operating system B01 and a computer program B02. The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 stored in the non-volatile storage medium A06. The network interface A02 is used for communication with external terminals via a network connection. When the computer program is executed by the processor A01, it implements a method for predicting production parameters of an acidic gas reservoir. The display screen A04 can be a liquid crystal display (LCD) or an e-ink display. The input device A05 can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0135] Those skilled in the art will understand that Figure 9 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0136] In one embodiment, the acid gas reservoir production parameter prediction device 500 provided in this application can be implemented as a computer program, which can be implemented in, for example... Figure 9 The computer device shown operates on the computer. The computer device's memory can store various program modules that constitute the sour gas reservoir production parameter prediction device 500. The computer program, composed of the various program modules, causes the processor to execute the steps in the sour gas reservoir production parameter prediction methods of the various embodiments of this application described in this specification.

[0137] In one embodiment, this application also provides a machine-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for predicting production parameters of sour gas reservoirs in the above embodiments.

[0138] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0139] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0140] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for predicting production parameters of an acidic gas reservoir, characterized in that, include: Step 1: Using the first prediction model to perform numerical simulation of production parameters on reservoir characteristic parameters and bottom hole pressure, the current value of production parameters under dynamic changes in reservoir sulfur deposition is simulated based on the obtained reservoir characteristic parameters of the study area and the current bottom hole pressure value selected between the reservoir pressure value and the wellbore outlet pressure value. Step 2: Utilize a multiphase flow control model based on partial production parameters including bottom hole pressure to solve for a second prediction model that predicts production parameters different from the partial production parameters. Based on the current values ​​of water production and sulfur production in the production parameters obtained under reservoir sulfur deposition, and the current bottom hole pressure value, calculate the current value of gas production under dynamically changing wellbore sulfur deposition. Step 3: Compare the current values ​​of gas production in the production parameters under reservoir sulfur deposition and the current values ​​of gas production under wellbore sulfur deposition to see if they are consistent; If so, the current value of the production parameter is determined as the current value of the production parameter in the study area; otherwise, the bottom hole pressure value is selected again from the reservoir pressure value and the wellbore outlet pressure value as the updated value of the current bottom hole pressure value, and the process jumps to trigger the execution of step 1.

2. The method for predicting production parameters of acidic gas reservoirs according to claim 1, characterized in that, The first prediction model is a numerical simulation model based on the component model.

3. The method for predicting production parameters of acidic gas reservoirs according to claim 1, characterized in that, The reservoir characteristic parameters include reservoir temperature, reservoir pressure, water saturation, and sulfur saturation.

4. The method for predicting production parameters of acidic gas reservoirs according to claim 1, characterized in that, The multiphase flow control model includes a wellbore miscible flow model. The equations of the wellbore miscible flow model include the liquid holdup equation, mass conservation equation, energy conservation equation, momentum conservation equation, and phase drift velocity equation, wherein: The liquid holdup equation is expressed as: The phase drift velocity equation is expressed as: u w =βu g +γ; In the above formulas, A represents the effective cross-sectional area of ​​sulfur deposition dynamics, and α w Indicates liquid holdup, u w U represents the velocity of the water phase. g denoted by β, denoted by γ, denoted by x, and t, which represents the time step when solving the multiphase flow control model.

5. The method for predicting production parameters of acidic gas reservoirs according to claim 4, characterized in that, The mass conservation equation, momentum conservation equation, and energy conservation equation are expressed as follows: mass conservation equation: Momentum conservation equation: Energy conservation equation: In the above formulas, A represents the effective cross-sectional area of ​​sulfur deposition dynamics, and α w α represents the liquid holdup. g U represents the gas phase volume fraction. w U represents the velocity of the water phase. g ρ represents the gas phase velocity. g P represents gas phase density, T represents pressure, and F represents temperature. wall ρ represents the wall friction coefficient. m C represents the average density of the phase. m U represents the specific heat capacity of a miscible fluid. m K represents the average velocity of a miscible fluid. wall The wellbore heat transfer coefficient is represented by g, g is represented by gravitational acceleration, θ is represented by the wellbore inclination angle, D is represented by the wellbore diameter, and T is represented by T. wall This indicates the wellbore temperature.

6. The method for predicting production parameters of acidic gas reservoirs according to claim 1, characterized in that, The multiphase flow control model includes a sulfur precipitation model, the equations of which are expressed as follows: q GS =k·Amax(C S -C 溶解度 ,0); Where, q GS The term represents the sulfur precipitation term, k represents the sulfur precipitation relaxation factor, A represents the effective cross-sectional area of ​​sulfur deposition dynamics, and C represents the sulfur precipitation term. S C represents the total concentration of elemental sulfur. 溶解度 This represents the maximum solubility of solid sulfur, which is determined based on experimental data of solid sulfur physical dissolution. max() represents the function that takes the largest value.

7. The method for predicting production parameters of acidic gas reservoirs according to claim 1, characterized in that, The multiphase flow control model includes a sulfur transport model, and the sulfur transport equations of the sulfur transport model are expressed as follows: Total sulfur mass conservation equation: Sulfur transport equation: among them, q sets =A·γ(C SS ,u m )·β(P,T)·C SS , In the above formulas, A represents the effective cross-sectional area of ​​sulfur deposition dynamics, and C S C represents the total concentration of elemental sulfur. SS q represents the sulfur fixation concentration. GS q represents the sulfur precipitation term. sets Represents the sulfur fixation deposition term, γ(C SS ,u m ) represents the sulfur deposition rate on the wall, β(P,T) represents the nucleation factor reflecting the degree of sulfur precipitation, P represents pressure, T represents temperature, and u m denoted by , x represents the average velocity of the multiphase fluid, x represents the wellbore diameter position, and t represents the time step when solving the multiphase flow control model.

8. The method for predicting production parameters of sour gas reservoirs according to claim 1, characterized in that, The initial value of the current bottom hole pressure, selected from the reservoir pressure value and the wellbore outlet pressure value, is the average of the reservoir pressure value and the wellbore outlet pressure value. If the current value of gas production in the production parameters under reservoir sulfur deposition is greater than the current value of gas production under wellbore sulfur deposition, then the updated value of the current bottom hole pressure value is the average of the reservoir pressure value and the current bottom hole pressure value. If the current value of gas production in the production parameters under reservoir sulfur deposition is less than the current value of gas production under wellbore sulfur deposition, then the updated value of the current bottom hole pressure value is the average of the wellbore outlet pressure value and the current bottom hole pressure value.

9. The method for predicting production parameters of acidic gas reservoirs according to claim 5, characterized in that, When calculating the current value of gas production under dynamic wellbore sulfur deposition based on the current values ​​of water production and sulfur production in the production parameters obtained under reservoir sulfur deposition, and the current bottom hole pressure value, the liquid holdup equation is explicitly solved, the prediction step of velocity parameters in the multiphase flow control model is semi-implicitly solved, the correction step of pressure parameters in the multiphase flow control model is expressed as a tridiagonal linear equation system and implicitly solved, the correction step of velocity parameters in the multiphase flow control model is explicitly solved, and the temperature solution based on the energy conservation equation is semi-implicitly solved.

10. The method for predicting production parameters of acidic gas reservoirs according to claim 7, characterized in that, When the current values ​​of water production and sulfur production in the production parameters obtained under the sulfur deposition in the reservoir are calculated, and the current bottom hole pressure is calculated, the current value of gas production under the dynamically changing sulfur deposition in the wellbore is obtained, and the sulfur solidification and transport equation is solved explicitly.

11. A device for predicting production parameters of an acidic gas reservoir, characterized in that, include: The first prediction module is used to perform numerical simulation of production parameters using the first prediction model that performs numerical simulation of production parameters based on the reservoir characteristic parameters and bottom hole pressure of the study area. Based on the obtained reservoir characteristic parameters of the study area and the current bottom hole pressure value selected between the reservoir pressure value and the well outlet pressure value, the module simulates the current value of production parameters under the dynamic change of reservoir sulfur deposition. The second prediction module is used to execute a multiphase flow control model that reflects the wellbore sulfur deposition phenomenon based on some production parameters including bottom hole pressure to predict a second prediction model that is different from the aforementioned partial production parameters. The module calculates the current value of gas production under the dynamic change of wellbore sulfur deposition based on the current values ​​of water production and sulfur production in the production parameters obtained under the reservoir sulfur deposition and the current bottom hole pressure value. The comparison module is used to compare whether the current value of gas production in the production parameters under reservoir sulfur deposition is consistent with the current value of gas production under wellbore sulfur deposition. If so, the current value of the production parameter is determined as the current value of the production parameter in the study area; otherwise, the bottom hole pressure value is selected again from the reservoir pressure value and the wellbore outlet pressure value as the updated value of the current bottom hole pressure value, and the process jumps to trigger the execution of the first prediction model that uses the reservoir characteristic parameters and bottom hole pressure to perform numerical simulation of the production parameters. Based on the obtained reservoir characteristic parameters of the study area and the current bottom hole pressure value selected from the reservoir pressure value and the wellbore outlet pressure value, the current value of the production parameter under the dynamic change of reservoir sulfur deposition is simulated.

12. A computer device, characterized in that, include: The memory is configured to store instructions; as well as The processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the method for predicting production parameters of an acidic gas reservoir according to any one of claims 1 to 10.

13. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores instructions for causing the machine to perform the method for predicting production parameters of an acidic gas reservoir according to any one of claims 1 to 10.

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