Continental facies shale condensate gas reservoir horizontal well productivity numerical simulation method

Abstract

The invention discloses a continental facies shale condensate gas reservoir horizontal well productivity numerical simulation method which comprises the following steps: 1) obtaining production characteristic related data of related wells in a continental facies shale condensate gas reservoir research area, and comparing and analyzing the production characteristics of the wells; 2) carrying out gas reservoir modeling according to the production characteristic related data, and establishing a matrix and crack system multiphase multicomponent model; 3) solving the gas reservoir numerical model according to fluid-rock physical property parameters, well and production plan related data and initial condition related data; 4) on the basis of the established gas reservoir numerical model, fitting production history of each well, analyzing fluid phase state characteristics, and fitting phase state parameters of the gas reservoir numerical model; 5, productivity simulation is carried out through the optimized gas reservoir numerical model, development dynamic prediction is carried out on all wells, and a corresponding reasonable production allocation plant.The model established through the method is more suitable for the gas reservoir type of shale condensate gas reservoirs.

Description

Technical Field

[0001] The present invention relates to oil and gas development technology, and in particular to a method for numerically simulating the productivity of horizontal wells in continental shale condensate gas reservoirs. Background Art

[0002] Shale condensate is an emerging natural gas resource obtained through hydraulic fracturing and horizontal well drilling of shale rocks. Compared with traditional natural gas resources, shale condensate has a higher gas content and a wider distribution range, and is therefore considered a key component of the future natural gas industry.

[0003] The production patterns of condensate oil and gas in continental shale are still unclear. Initially, wells produce three phases: gas, oil, and water, making it difficult to properly allocate production. With continued development, as formation pressure decreases, the oil and gas phases separate into two, oil and gas, within the formation. This hinders oil and gas flow and leads to a rapid decline in production.

[0004] How to reasonably predict the production capacity of each well in continental shale condensate gas reservoirs is an urgent problem that needs to be solved. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method for numerical simulation of horizontal well productivity in continental shale condensate gas reservoirs in response to the defects in the prior art.

[0006] The technical solution adopted by the present invention to solve the technical problem is: a numerical simulation method for horizontal well productivity in continental shale condensate gas reservoirs, comprising the following steps: 1) Obtain production characteristics data of relevant wells in the continental shale condensate gas reservoir study area and compare and analyze the production characteristics of each well; The relevant production characteristics include analyzing pressure decline rate, production gas-oil ratio and elastic gas production; 2) Gas reservoir modeling is conducted based on production characteristic data. The numerical model of the gas reservoir uses a multiphase and multicomponent model of the microscopic migration mechanism of shale oil and gas. Considering the micro- and nanopore-confined phase state of shale condensate gas, gas molecular diffusion, and multicomponent adsorption and desorption effects, a multiphase and multicomponent model of the matrix and fracture system is established. 3) Solve the gas reservoir numerical model based on fluid-rock physical parameters, well and production plan data, and initial condition data; The fluid-rock physical parameters include porosity, permeability, compressibility, rock density, wetting angle, starting pressure gradient, stress sensitivity coefficient, mechanical properties, initial pressure of water, water viscosity, viscosity coefficient, density, density coefficient, volume coefficient, gas saturation, gas phase relative permeability, oil phase relative permeability, water saturation, and water phase relative permeability; The initial conditions and well and production plan include reference depth, initial oil phase pressure, initial water saturation, initial temperature, reservoir type, initial time step, simulation time, flow iteration tolerance, mechanical iteration tolerance, coupling iteration tolerance, well position coordinate parameters, and fracture position coordinate parameters; 4) Based on the established gas reservoir numerical model, the production history of each well is fitted, the fluid phase characteristics are analyzed, and the phase parameters of the gas reservoir numerical model are fitted; History matching experimental data includes dew point pressure, equal component expansion experimental test data, and constant volume depletion experimental test data; The fitted phase parameters include component critical temperature, critical pressure, and eccentricity factor; 5) Use the optimized gas reservoir numerical model to simulate production capacity, predict the development performance of each well, and obtain a corresponding reasonable production allocation plan.

[0007] According to the above scheme, in step 3), the phase equilibrium and flash calculation method considering nanoscale effects is used to solve the gas reservoir numerical model. The phase state of shale condensate gas fluid and the changes in oil and gas physical properties are described using phase equilibrium theory. By introducing the influence of capillary force and critical parameter changes, the confined phase effect in micro-nano pores is considered.

[0008] According to the above scheme, the method for numerical simulation of horizontal well productivity in continental shale condensate gas reservoirs according to claim 1 is characterized in that, in said step 3), an embedded discrete fracture model is used to process the complex fracture network when solving the gas reservoir numerical model. First, the entire reservoir is divided into an orthogonal grid. On this basis, the artificial fracture network obtained by Petrel simulation is directly embedded in the orthogonal grid. The fractures are gridded at the intersection points with the grid boundaries, and finally a grid system for numerical simulation calculation is formed.

[0009] According to the above scheme, the method for numerical simulation of horizontal well productivity in continental shale condensate gas reservoirs according to claim 1 is characterized in that the solving of the gas reservoir numerical model in step 3) further includes: establishing a component model numerical solver, using a structured grid for grid division, and performing a fully implicit solution of the model based on the finite volume method, and using the MRST open source program and MATLAB programming to realize the numerical simulation of the seepage of the shale condensate gas reservoir.

[0010] According to the above scheme, the gas reservoir numerical model is solved in step 3), specifically as follows: 3.1) Solving the multiphase and multicomponent model within the matrix of shale condensate gas reservoirs

[0011] 3.2) Solving the multi-component model in fractures of shale condensate gas reservoirs 3.3) Then solve the equation of motion of the fluid in the matrix and fracture system

[0012]

[0013] 3.4) Solve the matrix-fracture cross-flow equation

[0014] 3.5) Consider the effects of confined phase states in micro- and nanopores by introducing capillary forces and critical parameter variations. Solve the phase equilibrium and flash evaporation equations that account for nanoscale effects.

[0015] The chemical potential balance equation can be obtained from the thermodynamic equilibrium:

[0016] Then solve the fugacity balance equation.

[0017]

[0018] According to the definition of the fugacity coefficient, it is converted into the following form (the fugacity coefficient is calculated by the state equation) .

[0019] The present invention has the following beneficial effects: Compared with traditional shale gas simulation methods, this one establishes a phase equilibrium and flash calculation method that considers nanoscale effects. The phase state of shale condensate fluids and changes in oil and gas properties are described using phase equilibrium theory. By incorporating the effects of capillary forces and critical parameter variations, the effects of confined phase states in micro- and nano-pores are considered. The resulting model is more suitable for shale condensate reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The present invention will be further described below with reference to the accompanying drawings and embodiments, in which: Figure 1 is a flow chart of a method according to an embodiment of the present invention; Figure 2 is a crack model of an embodiment of the present invention; Figure 3 This is a daily oil production prediction curve diagram of a well in a certain basin according to an embodiment of the present invention; Figure 4 This is a cumulative oil production prediction curve diagram of a well in a certain basin according to an embodiment of the present invention; Figure 5 This is a daily gas production prediction curve diagram of a well in a certain basin according to an embodiment of the present invention; Figure 6 This is a cumulative gas production prediction curve diagram of a well in a certain basin according to an embodiment of the present invention; Figure 7This is a gas-oil ratio prediction curve diagram of a well in a certain basin according to an embodiment of the present invention; Figure 8 This is a gas-oil ratio distribution diagram of a well in a certain basin according to an embodiment of the present invention; Figure 9 This is a graph of the cumulative oil production of a well in a certain basin during gas injection development according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0022] like Figure 1 As shown, a method for numerically simulating the productivity of a horizontal well in a continental shale condensate gas reservoir comprises the following steps: 1) Obtain production characteristics data of relevant wells in the continental shale condensate gas reservoir study area and compare and analyze the production characteristics of each well; The relevant production characteristics include analyzing pressure decline rate, production gas-oil ratio and elastic gas production; 2) Gas reservoir modeling is conducted based on production characteristic data. The numerical model of the gas reservoir uses a multiphase and multicomponent model of the microscopic migration mechanism of shale oil and gas. Considering the micro- and nanopore-confined phase state of shale condensate gas, gas molecular diffusion, and multicomponent adsorption and desorption effects, a multiphase and multicomponent model of the matrix and fracture system is established. 3) Solve the gas reservoir numerical model based on fluid-rock physical parameters, well and production plan data, and initial condition data; The fluid-rock physical parameters include porosity, permeability, compressibility, rock density, wetting angle, starting pressure gradient, stress sensitivity coefficient, mechanical properties, initial pressure of water, water viscosity, viscosity coefficient, density, density coefficient, volume coefficient, gas saturation, gas phase relative permeability, oil phase relative permeability, water saturation, and water phase relative permeability; The initial conditions and well and production plan include reference depth, initial oil phase pressure, initial water saturation, initial temperature, reservoir type, initial time step, simulation time, flow iteration tolerance, mechanical iteration tolerance, coupling iteration tolerance, well location coordinate parameters, and fracture location coordinate parameters; When solving the numerical model of the gas reservoir, the phase equilibrium and flash calculation methods are used to consider the nanoscale effects. The phase state of shale condensate gas fluid and the changes in oil and gas physical properties are described using the phase equilibrium theory. By introducing the influence of capillary forces and critical parameter changes, the confined phase effects in micro-nano pores are considered.

[0023] like Figure 2, an embedded discrete fracture model is used to process complex fracture networks. First, the entire reservoir is divided into orthogonal grids. On this basis, the artificial fracture network obtained by Petrel simulation is directly embedded into the orthogonal grid. The fractures are gridded at the intersection of the fractures and the grid boundary, and finally a grid system for numerical simulation calculation is formed.

[0024] A numerical solver for the component model was established, structured grids were used for mesh generation, and the model was solved fully implicitly based on the finite volume method. The MRST open source program and MATLAB programming were used to implement numerical simulation of shale condensate gas reservoir seepage.

[0025] The details are as follows: 3.1) Solve the multi-phase and multi-component model within the matrix of shale condensate gas reservoirs;

[0026] 3.2) Solve the multi-concept and multi-component model in fractures of shale condensate gas reservoirs; 3.3) Then solve the equations of motion of the fluid in the matrix and fracture system;

[0027]

[0028] 3.4) Solve the matrix-fracture cross-flow equation;

[0029] 3.5) By introducing the effects of capillary forces and critical parameter variations, we consider the confined phase effects in micro- and nano-pores and solve the phase equilibrium and flash evaporation equations that take into account nanoscale effects. The chemical potential balance equation can be obtained from the thermodynamic equilibrium:

[0030] Then solve the fugacity balance equation;

[0031] According to the definition of the fugacity coefficient, it is converted into the following form (the fugacity coefficient is calculated by the state equation) .

[0032] 4) Based on the established gas reservoir numerical model, the production history of each well is fitted, the fluid phase characteristics are analyzed, and the phase parameters of the gas reservoir numerical model are fitted; History matching experimental data includes dew point pressure, equal component expansion experimental test data, and constant volume depletion experimental test data; The fitted phase parameters include component critical temperature, critical pressure, and eccentricity factor; 5) Use the optimized gas reservoir numerical model to simulate production capacity, predict the development performance of each well, and obtain a corresponding reasonable production allocation plan.

[0033] Specific embodiment (a well in Sichuan Basin), such as Figures 3 to 9 ; S1. Through analysis of production pressure data, production stability assessment, and liquid production characteristics, it was determined that the well had a high pressure decline rate, a high and unstable gas-oil ratio, and low elastic gas production. S2. Use the PVTi module in Eclipse to fit the phase parameters. Input experimental data such as component mole fractions, dew point pressure, isocratic expansion, and constant volume depletion through Edit | Experiments. Select the three-parameter PR equation of state for fitting. S3. Under original reservoir conditions (350K), the dew point pressure is 35.55 MPa. As the pressure drops below the dew point pressure, the condensate content gradually increases until it reaches the maximum reverse condensate pressure (28.6 MPa), at which the condensate saturation reaches 24.9%. Once below the maximum reverse condensate pressure, further pressure reduction decreases the condensate saturation. When the pore size drops below 20 nm, the dew point pressure decreases significantly, and the maximum reverse condensate saturation level decreases. Condensate is less likely to precipitate in the tight pores of the shale, helping to stabilize the gas-oil ratio during production. S4. Numerical simulation was performed by inputting relevant fluid component parameters and reservoir physical property parameters. The production history was fitted to obtain the initial production data. The current average matrix pressure is above 44 MPa and is maintained at a high level. Condensate oil is currently concentrated in fractures, with a small amount of condensate in the matrix. No large-scale retrograde condensation has occurred in the well area, resulting in a relatively stable gas-oil ratio in the early production period. S5. Productivity simulation and prediction revealed that after 30 years of development, the fractured zone was largely utilized, with condensate concentrated within the zone, and no retrograde condensate formed outside of it. The matrix pressure within the zone dropped significantly during the initial phase, while condensate saturation increased. Later, the pressure and condensate saturation remained relatively stable, indicating that after condensate formed within the matrix, the condensate was difficult to utilize. Cumulative condensate production over the 30 years of development was 3,066 m³, and cumulative gas production was 3.467 × 10⁷ m³. The gas-to-oil ratio remained stable for the first 1.5 years, but then, with the development of extensive retrograde condensate within the matrix, oil production declined and the gas-to-oil ratio rapidly increased. S6. Capacity predictions for different hydraulic fracture permeabilities show that as hydraulic fracture permeability increases, reservoir pressure decreases faster, the production gas-oil ratio increases faster, and the production gas-oil ratio plateau period shortens. Finally, capacity predictions for different matrix permeabilities show that increasing matrix permeability accelerates the production gas-oil ratio increase rate and shortens the production gas-oil ratio plateau period. In summary, the present application provides a method for the rational development of terrestrial shale condensate gas reservoirs, establishes a numerical simulation method for the productivity of shale condensate gas fractured horizontal wells, and reasonably predicts and allocates the productivity of each well. The fitted daily gas production and oil production are basically consistent with the actual production data, and the cumulative oil production and cumulative gas production can be well predicted. It can facilitate the selection of better methods for rational production allocation, increase production, and provide a reference for rational production allocation in terrestrial shale condensate gas reservoir blocks.

[0034] It should be understood that those skilled in the art can make improvements or changes based on the above description, and all such improvements and changes should fall within the scope of protection of the appended claims of the present invention.

Claims

1. A method for numerical simulation of horizontal well productivity in continental shale condensate gas reservoirs, characterized in that: The following steps are involved: 1) Obtain production characteristics data of relevant wells in the continental shale condensate gas reservoir study area and compare and analyze the production characteristics of each well; The relevant production characteristics include analyzing pressure decline rate, production gas-oil ratio and elastic gas production; 2) Gas reservoir modeling is conducted based on production characteristic data. The numerical model of the gas reservoir uses a multiphase and multicomponent model of the microscopic migration mechanism of shale oil and gas. Considering the micro- and nanopore-confined phase state of shale condensate gas, gas molecular diffusion, and multicomponent adsorption and desorption effects, a multiphase and multicomponent model of the matrix and fracture system is established. 3) Solve the gas reservoir numerical model based on fluid-rock physical parameters, well and production plan data, and initial condition data; The fluid-rock physical parameters include porosity, permeability, compressibility, rock density, wetting angle, starting pressure gradient, stress sensitivity coefficient, mechanical properties, initial pressure of water, water viscosity, viscosity coefficient, density, density coefficient, volume coefficient, gas saturation, gas phase relative permeability, oil phase relative permeability, water saturation, and water phase relative permeability; The initial conditions and well and production plan include reference depth, initial oil phase pressure, initial water saturation, initial temperature, reservoir type, initial time step, simulation time, flow iteration tolerance, mechanical iteration tolerance, coupling iteration tolerance, well location coordinate parameters, and fracture location coordinate parameters; 4) Based on the established gas reservoir numerical model, the production history of each well is fitted, the fluid phase characteristics are analyzed, and the phase parameters of the gas reservoir numerical model are fitted; History matching experimental data includes dew point pressure, equal component expansion experimental test data, and constant volume depletion experimental test data; The fitted phase parameters include component critical temperature, critical pressure, and eccentricity factor; 5) Use the optimized gas reservoir numerical model to simulate production capacity, predict the development performance of each well, and obtain a corresponding reasonable production allocation plan.

2. The method for numerical simulation of horizontal well productivity in continental shale condensate gas reservoirs according to claim 1, characterized in that: In step 3), when solving the gas reservoir numerical model, a phase equilibrium and flash calculation method is used to consider nanoscale effects. The phase state of shale condensate gas fluid and the changes in oil and gas physical properties are described using phase equilibrium theory. By introducing the influence of capillary forces and critical parameter changes, the confined phase effects in micro-nano pores are considered.

3. The method for numerical simulation of horizontal well productivity in continental shale condensate gas reservoirs according to claim 1, characterized in that: In step 3), when solving the gas reservoir numerical model, an embedded discrete fracture model is used to process the complex fracture network. First, the entire reservoir is divided into an orthogonal grid. On this basis, the artificial fracture network obtained by Petrel simulation is directly embedded into the orthogonal grid. The fractures are meshed at the intersection points with the grid boundaries, and finally a grid system for numerical simulation calculation is formed.

4. The method for numerical simulation of horizontal well productivity in continental shale condensate gas reservoirs according to claim 1, characterized in that: Solving the gas reservoir numerical model in step 3) further includes: establishing a component model numerical solver, using a structured grid for mesh generation, and performing a fully implicit solution to the model based on the finite volume method, and using the MRST open source program and MATLAB programming to implement numerical simulation of shale condensate gas reservoir seepage.

5. A server comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 3 is implemented.

6. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method according to any one of claims 1 to 3 when executed.

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