Numerical processing method, device and equipment for inter-salt shale oil reservoir and storage medium

Abstract

The application discloses an inter-salt shale oil reservoir numerical processing method, device and equipment and a storage medium. The method comprises the following steps: establishing a numerical simulation model of an inter-salt shale oil reservoir to be simulated; obtaining initial characteristic parameters in the numerical simulation model and water passing multiples of each time step after water injection; according to the water passing multiple of each time step, adopting a preset reservoir porosity-permeability change mathematical representation model, respectively calculating the porosity-permeability parameter change multiple of each time step under the action of salt dissolution and recrystallization; and based on the initial characteristic parameters and the porosity-permeability parameter change multiple of each time step under the action of salt dissolution and recrystallization, respectively obtaining the porosity-permeability parameters of each time step under the action of salt dissolution and recrystallization. According to the application, the porosity-permeability parameters of each time step can be quantitatively obtained, the porosity-permeability change is reflected, and the production capacity of an actual production well in which salt dissolution and recrystallization phenomena occur can be accurately predicted.

Description

Technical Field

[0001] This invention relates to the field of oil and gas extraction technology, and in particular to a numerical processing method, apparatus, equipment, and storage medium for intersalt shale oil reservoirs. Background Technology

[0002] Inter-salt shale oil reservoirs contain a large amount of salt minerals. During hydraulic fracturing and water injection development, water entering the reservoir can cause the dissolution of these salt minerals. For example, salt minerals generally include mirabilite and halite. Mirabilite is a mixture of sodium sulfate and calcium sulfate. In this mixture, sodium sulfate dissolves in water, while calcium sulfate crystallizes to form gypsum. Furthermore, these salt minerals are water-soluble and are carried near the wellbore during extraction. With changes in concentration, temperature, and pressure, these salt minerals can recrystallize, blocking seepage channels and the wellbore near the wellbore.

[0003] It is evident that salt dissolution and recrystallization lead to changes in reservoir porosity and permeability, affecting the reservoir's seepage capacity and ultimately impacting the production dynamics of production wells. However, there is currently no quantitative analysis of the changes in porosity and permeability caused by salt dissolution and recrystallization, making it impossible to accurately analyze seepage capacity and thus hinder accurate production prediction. Summary of the Invention

[0004] The technical problem to be solved by this invention is that the existing technology lacks quantitative analysis of the changes in porosity and permeability of reservoirs caused by salt dissolution and recrystallization, which leads to inaccurate production prediction.

[0005] To address the aforementioned technical problems, this invention provides a numerical processing method, apparatus, equipment, and storage medium for intersalt shale oil reservoirs.

[0006] A numerical processing method for intersalt shale oil reservoirs, comprising:

[0007] Establish a numerical simulation model for the salt-interspinous shale oil reservoir to be simulated;

[0008] Obtain the initial characteristic parameters and the water overflow ratio at each time step after water injection in the numerical simulation model;

[0009] Based on the water permeation factor at each time step, a preset mathematical characterization model for reservoir porosity and permeability changes is used to calculate the porosity and permeability parameter change factors at each time step under salt dissolution and recrystallization.

[0010] Based on the initial characteristic parameters and the change factor of the porosity parameters at each time step under salt dissolution and recrystallization, the porosity parameters at each time step under salt dissolution and recrystallization are obtained respectively.

[0011] In one embodiment, the initial characteristic parameters include initial pore volume and initial conductivity, the pore permeability parameters include pore volume and conductivity, and the pore permeability parameter variation factor includes pore volume variation factor and conductivity variation factor.

[0012] In one embodiment, the preset mathematical characterization model for reservoir porosity and permeability changes includes a mathematical characterization model for permeability changes, a mathematical characterization model for porosity changes under salt dissolution, and a mathematical characterization model for porosity changes under recrystallization. The step of calculating the porosity and permeability parameter change factors for each time step under salt dissolution and recrystallization, based on the water permeation multiple at each time step, using the preset mathematical characterization model for reservoir porosity and permeability changes, includes:

[0013] Based on the water permeation factor at each time step, the porosity change factor under salt dissolution is calculated using a mathematical characterization model of porosity change under salt dissolution, thus obtaining the pore volume change factor under salt dissolution.

[0014] Based on the water permeation factor at each time step, the porosity change factor under recrystallization is calculated using a mathematical characterization model of porosity change under recrystallization, thus obtaining the pore volume change factor under recrystallization.

[0015] Based on the porosity change factor under salt dissolution and the porosity change factor under recrystallization, respectively, and using the mathematical characterization model of permeability change, the permeability change factor under salt dissolution and the permeability change factor under recrystallization are calculated to obtain the conductivity change factor under salt dissolution and the conductivity change factor under recrystallization.

[0016] In one embodiment, the mathematical characterization model of porosity change under salt dissolution includes:

[0017]

[0018] Where φ is the current porosity, dimensionless; φ0 is the initial porosity, dimensionless. The dimensionless factor is the multiple of porosity change; m sample The mass of the rock sample is expressed in grams (g); a NaCl ρ represents the mass percentage of NaCl in the rock sample, dimensionless; NaCl PV represents the density of NaCl, in g / L. flow This is a multiple of water flow, dimensionless; b is the porosity multiple of water required for complete dissolution of NaCl in the rock sample, dimensionless; glauberite ρ represents the mass percentage of calcium sulfate in the rock sample, as a decimal. glauberite ρ represents the density of sodium sulfate, in g / L; C is the recrystallization coefficient of sodium sulfate, dimensionless. V is the dimensionless multiple of water porosity required for the complete dissolution of calcium sulfate in the rock sample; sample The volume of the rock sample is expressed in liters (L).

[0019] In one embodiment, the mathematical characterization model of porosity change under recrystallization includes:

[0020]

[0021] Where φ is the current porosity, dimensionless; φ0 is the initial porosity, dimensionless. PV is a dimensionless multiple of porosity change. flow out α is the multiple of water flow, dimensionless; NaCl The NaCl crystallization rate at the current temperature and pressure is expressed in g / L; ρ NaCl β is the density of NaCl, in g / L; glauberite The precipitation rate of sodium sulfate crystals at the current temperature and pressure is expressed in g / L; ρ glauberite V represents the density of Glauber's salt, in g / L; sample The volume of the rock sample is expressed in liters (L).

[0022] In one embodiment, the mathematical representation model of the permeability change includes:

[0023] K(φ) / K0=(φ / φ0) ckpower ×[(1-φ0) / (1-φ)] 2 ;

[0024] Where K(φ) is the current permeability in D; K0 is the initial permeability in D; K(φ) / K0 is the permeability change factor, dimensionless; φ is the current porosity, dimensionless; φ0 is the initial porosity, dimensionless; φ0 is the porosity change factor, dimensionless; ckpower is the exponent, dimensionless.

[0025] In one embodiment, the step of obtaining the porosity parameters at each time step under salt dissolution and recrystallization based on the initial characteristic parameters and the change factor of the porosity parameters at each time step under salt dissolution and recrystallization includes:

[0026] Based on the initial characteristic parameters and the change factor of the porosity parameters in the first time step under salt dissolution, the porosity parameters in the first time step under salt dissolution are calculated.

[0027] Based on the initial characteristic parameters and the change factor of the porosity parameters in the first time step under recrystallization, the porosity parameters in the first time step under recrystallization are calculated.

[0028] Based on the porosity parameters of the previous time step under salt dissolution and the change factor of the porosity parameters of the next time step under salt dissolution, the porosity parameters of the next time step under salt dissolution are calculated.

[0029] Based on the porosity parameters of the first time step under recrystallization and the change factor of the porosity parameters of the next time step under recrystallization, the porosity parameters of the next time step under recrystallization are calculated.

[0030] In one embodiment, after obtaining the porosity parameters at each time step under salt dissolution and recrystallization based on the initial characteristic parameters and the change factor of the porosity parameters at each time step under salt dissolution and recrystallization, the method further includes:

[0031] Update the pore permeability parameters at each time step in the numerical simulation model.

[0032] In one embodiment, after obtaining the porosity parameters at each time step under salt dissolution and recrystallization based on the initial characteristic parameters and the change factor of the porosity parameters at each time step under salt dissolution and recrystallization, the method further includes:

[0033] Based on the pore permeability parameters and the preset calculation equations, the seepage characteristic parameters in the numerical simulation model are obtained.

[0034] A numerical processing device for intersalt shale oil reservoirs includes:

[0035] The model building module is used to build a numerical simulation model of the salt inter-salt shale oil reservoir to be simulated.

[0036] The data reading module is used to acquire the initial characteristic parameters and the water flow ratio at each time step after water injection in the numerical simulation model.

[0037] The calculation and processing module is used to calculate the change factor of pore permeability parameters at each time step under salt dissolution and recrystallization, respectively, based on the water flow ratio at each time step and using a preset mathematical characterization model of reservoir pore permeability change.

[0038] The parameter acquisition module is used to acquire the porosity parameters at each time step under salt dissolution and recrystallization based on the initial characteristic parameters and the change factor of the porosity parameters at each time step under salt dissolution and recrystallization.

[0039] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program performing the following steps:

[0040] Establish a numerical simulation model for the salt-interspinous shale oil reservoir to be simulated;

[0041] Obtain the initial characteristic parameters and the water overflow ratio at each time step after water injection in the numerical simulation model;

[0042] Based on the water permeation factor at each time step, a preset mathematical characterization model for reservoir porosity and permeability changes is used to calculate the porosity and permeability parameter change factors at each time step under salt dissolution and recrystallization.

[0043] Based on the initial characteristic parameters and the change factor of the porosity parameters at each time step under salt dissolution and recrystallization, the porosity parameters at each time step under salt dissolution and recrystallization are obtained respectively.

[0044] A computer-readable storage medium having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0045] Establish a numerical simulation model for the salt-interspinous shale oil reservoir to be simulated;

[0046] Obtain the initial characteristic parameters and the water overflow ratio at each time step after water injection in the numerical simulation model;

[0047] Based on the water permeation factor at each time step, a preset mathematical characterization model for reservoir porosity and permeability changes is used to calculate the porosity and permeability parameter change factors at each time step under salt dissolution and recrystallization.

[0048] Based on the initial characteristic parameters and the change factor of the porosity parameters at each time step under salt dissolution and recrystallization, the porosity parameters at each time step under salt dissolution and recrystallization are obtained respectively.

[0049] Compared with existing technologies, one or each embodiment of the above-mentioned scheme may have the following advantages or beneficial effects: By establishing a numerical simulation model of the inter-salt shale oil reservoir to be simulated, and based on the water permeability multiples obtained at each time step in the numerical simulation model and the mathematical characterization model of reservoir porosity and permeability changes, the change multiples of porosity and permeability parameters at each time step under salt dissolution and recrystallization are obtained. Based on the initial characteristic parameters and the change multiples of porosity and permeability parameters under salt dissolution and recrystallization, the porosity and permeability parameters at each time step are obtained. In this way, a numerical simulation method for porosity and permeability changes caused by salt dissolution and recrystallization in inter-salt shale oil reservoirs can be established, which can quantitatively obtain the porosity and permeability parameters at each time step and reflect the porosity and permeability changes. The analysis of porosity and permeability changes is quantitative and accurate, and can be used to accurately analyze seepage capacity and accurately predict the production capacity of actual production wells with salt dissolution and recrystallization phenomena. Attached Figure Description

[0050] The scope of this disclosure can be better understood by reading the following detailed description of exemplary embodiments in conjunction with the accompanying drawings. The accompanying drawings are:

[0051] Figure 1 This is a flowchart illustrating a numerical processing method for intersalt shale oil reservoirs in one embodiment;

[0052] Figure 2 This is a schematic diagram illustrating the specific process of calculating the change factor of pore permeability parameters at each time step under salt dissolution and recrystallization, based on the water permeation multiple at each time step and using a preset mathematical characterization model of reservoir pore permeability change.

[0053] Figure 3 This is a schematic diagram of a numerical simulation model in one embodiment;

[0054] Figure 4 for Figure 3 The diagram shows the fold change in pore volume and conductivity at a certain time step for the model shown.

[0055] Figure 5 for Figure 3 The field diagram of pore volume and conductivity of the model shown after updating at a certain time step;

[0056] Figure 6 for Figure 3 The diagram shows the impact of salt dissolution and recrystallization on production dynamics in the model shown.

[0057] Figure 7 This is a schematic diagram of the structure of a numerical processing device for intersalt shale oil reservoirs in one embodiment. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of the present invention clearer, the implementation method of the present invention will be described in detail below with reference to the accompanying drawings and embodiments, so that the process of how the present invention uses technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0060] As described in the background section, existing technologies lack quantitative analysis of reservoir porosity and permeability changes caused by salt dissolution and recrystallization, and lack numerical processing methods to describe these changes. For example, a method for calculating in-situ porosity and establishing water saturation in water-bearing dissolved salt reservoir cores is an experimental method for core analysis during oil and gas exploration and development, rather than a numerical simulation method for changes in porosity and permeability caused by salt dissolution. Similarly, a method for correcting oil-water relative permeability curves considering time-varying permeability at different water saturations is not a numerical simulation method that considers changes in porosity and thus permeability. One core experiment evaluation of salt dissolution in inter-salt shale oil reservoirs primarily utilizes salt dissolution experiments, percolation experiments, and high-temperature, high-pressure nuclear magnetic resonance (NMR) online testing to establish an evaluation method for salt dissolution in oil-bearing cores of inter-salt shale oil. The impact of salt dissolution on spontaneous percolation and permeability is analyzed, and the influence of salt dissolution on porosity and permeability is studied experimentally. However, this method does not establish a model for changes in porosity and permeability, nor is it a numerical simulation method for changes in porosity and permeability caused by salt dissolution. Another study investigates the impact of injected water salinity on the physical properties of inter-salt shale oil reservoirs. This study focuses on the salt dissolution and formation collapse problems caused by water injection development in inter-salt shale oil reservoirs. Through core percolation-displacement experiments, using NMR and scanning electron microscopy, the effects of injected water with different salinities on the core pore structure and permeability are studied from microscopic and macroscopic perspectives. However, this is not a numerical simulation method. An analysis of the impact of calcium sulfate recrystallization on intersalt reservoirs was conducted. The main method used was to study the recrystallization law of calcium sulfate under different temperature and pressure conditions using experimental methods. However, no mathematical model was established for the changes in porosity and permeability caused by calcium sulfate recrystallization, and no numerical simulation was used.

[0061] With the development of inter-salt shale oil, there is an urgent need to address issues such as historical data matching and production prediction for production wells exhibiting salt dissolution and recrystallization phenomena. Based on this, this application provides a numerical processing method for inter-salt shale oil reservoirs.

[0062] Example 1

[0063] like Figure 1 As shown, a numerical processing method for inter-salt shale oil reservoirs is provided, which includes the following steps:

[0064] S110: Establish a numerical simulation model for the salt inter-salt shale oil reservoir to be simulated.

[0065] The inter-salt shale oil reservoir to be simulated is one where porosity and permeability variations need to be analyzed. The numerical simulation model is generated using numerical simulation software. This model can be an actual reservoir model or a mechanistic model. The numerical simulation model must include at least one production well, which can be a vertical or horizontal well. For example, Intersect numerical simulation software can be used to establish the numerical simulation model of the inter-salt shale oil reservoir to be simulated.

[0066] S130: Obtain the initial characteristic parameters in the numerical simulation model and the water overflow ratio at each time step after water injection.

[0067] The initial characteristic parameters can specifically be the characteristic parameters of the inter-salt shale oil reservoir to be simulated when it is not injected with water; the initial characteristic parameters and the water filling ratio can be read from the numerical simulation model. The time step is a time period with a preset interval, and the number of time steps can be set according to actual needs. For example, one month can be used as one time step, and ten time steps can be set.

[0068] S150: Based on the water permeation multiple at each time step, a preset mathematical characterization model of reservoir porosity and permeability changes is used to calculate the porosity and permeability parameter change multiples at each time step under salt dissolution and recrystallization.

[0069] The pre-defined mathematical characterization model for reservoir porosity and permeability changes is a calculation model used to calculate the multiples of porosity and permeability parameter changes. Specifically, it can calculate the multiples of porosity and permeability parameter changes under salt dissolution and recrystallization. This mathematical characterization model can be pre-defined. The multiples of porosity and permeability parameter changes represent the magnitude of these changes. Specifically, based on the water flow multiple at a given time step and the pre-defined mathematical characterization model, the multiples of porosity and permeability parameter changes under salt dissolution and recrystallization at that time step can be calculated.

[0070] S170: Based on the initial characteristic parameters, the change factor of the porosity permeability parameters at each time step under salt dissolution and recrystallization, the porosity permeability parameters at each time step under salt dissolution and recrystallization are obtained respectively.

[0071] Pore ​​permeability parameters are parameters that reflect the fluid's seepage capacity, and may include parameters related to pore size and permeability. Initial characteristic parameters are parameters related to the type of pore permeability parameters; for example, initial characteristic parameters may be the values ​​of pore permeability parameters before water injection. Specifically, based on the initial characteristic parameters and the change factor of pore permeability parameters under salt dissolution at each time step, the pore permeability parameters under salt dissolution at each time step can be obtained; similarly, based on the initial characteristic parameters and the change factor of pore permeability parameters under recrystallization at each time step, the pore permeability parameters under recrystallization at each time step can be obtained. These obtained pore permeability parameters can be used to assess the fluid seepage capacity in the simulated inter-salt shale oil reservoir, thereby predicting production capacity.

[0072] The aforementioned numerical processing method for inter-salt shale oil reservoirs establishes a numerical simulation model of the reservoir to be simulated. Based on the water permeability multiples obtained at each time step in the numerical simulation model and the mathematical characterization model of reservoir porosity and permeability changes, the method calculates the porosity and permeability parameter changes at each time step under salt dissolution and recrystallization. Based on the initial characteristic parameters and the porosity and permeability parameter changes under salt dissolution and recrystallization, the porosity and permeability parameters for each time step are obtained. Thus, a numerical simulation method for porosity and permeability changes caused by salt dissolution and recrystallization in inter-salt shale oil reservoirs is established. This method can quantitatively obtain the porosity and permeability parameters at each time step, reflecting the porosity and permeability changes. The analysis of porosity and permeability changes is quantitative and highly accurate, and can be used to accurately analyze seepage capacity and accurately predict the production capacity of actual production wells exhibiting salt dissolution and recrystallization phenomena.

[0073] Specifically, the numerical simulation model is a grid model comprising multiple grids. The water flow factor at each time step includes the water flow factor of each grid at each time step, the porosity-permeability parameter change factor at each time step includes the porosity-permeability parameter change factor of each grid at each time step, and the porosity-permeability parameter at each time step includes the porosity-permeability parameter of each grid at each time step. That is, step S130 obtains the initial characteristic parameters of each grid in the numerical simulation model and the water flow factor of each grid at each time step after water injection; step S150, based on the water flow factor of each grid at each time step, uses a preset mathematical characterization model of reservoir porosity-permeability change to calculate the porosity-permeability parameter change factor of each grid at each time step under salt dissolution and recrystallization respectively; step S170, based on the initial characteristic parameters of each grid and the porosity-permeability parameter change factor of each grid at each time step under salt dissolution and recrystallization respectively, obtains the porosity-permeability parameters of each grid at each time step under salt dissolution and recrystallization respectively.

[0074] For example, Python can be used in the user edit module of the PetrelRe software platform to programmatically iterate through each grid in the numerical simulation model and read the water flow ratio and initial characteristic parameters of each grid during production. By refining the calculation of porosity parameters to each grid in the numerical simulation model, high accuracy is achieved.

[0075] Example 2

[0076] The numerical processing method for intersalt shale oil reservoirs includes steps S110 to S170, as described in Example 1, and will not be repeated here. Specifically, initial characteristic parameters may include initial pore volume and initial conductivity, and porosity-permeability parameters may include pore volume and conductivity. Correspondingly, the change factors of pore volume and conductivity parameters include the change factors of pore volume and conductivity. Pore volume reflects pore size, and conductivity reflects permeability. The size of pore volume and conductivity affects seepage capacity, thus affecting production. By quantitatively calculating the pore volume and conductivity at each time step using numerical simulation methods, it can be used to accurately analyze the changes in pore volume and conductivity, accurately reflect changes in seepage capacity, and thus accurately predict production capacity.

[0077] Example 3

[0078] The numerical processing method for inter-salt shale oil reservoirs includes steps S110 to S170, as described in Examples 1 and 2, and will not be repeated here. Specifically, the preset mathematical characterization models for reservoir porosity and permeability changes include a permeability change mathematical characterization model, a porosity change mathematical characterization model under salt dissolution, and a porosity change mathematical characterization model under recrystallization. The porosity change mathematical characterization model and the permeability change mathematical characterization model are mathematical models obtained based on experimental and theoretical studies; among them, the permeability change mathematical characterization model is used to calculate the permeability change factor, the porosity change mathematical characterization model under salt dissolution is used to calculate the porosity change factor under salt dissolution, and the porosity change mathematical characterization model under recrystallization is used to calculate the porosity change factor under recrystallization.

[0079] like Figure 2 As shown, step S150 includes steps S151 to S155.

[0080] S151: Based on the water permeation multiple at each time step, calculate the porosity change multiple under salt dissolution based on the mathematical characterization model of porosity change under salt dissolution, and obtain the pore volume change multiple under salt dissolution.

[0081] Specifically, for a numerical simulation model comprising multiple grids, the porosity change factor of each grid at each time step is calculated based on the water permeation factor of each grid at each time step, using a mathematical characterization model of porosity change under salt dissolution. Specifically, the porosity change factor is taken as equal to the pore volume change factor; that is, after calculating the porosity change factor, its value is equal to the pore volume change factor.

[0082] S153: Based on the water permeation factor at each time step, calculate the porosity change factor under recrystallization using a mathematical characterization model of porosity change under recrystallization, and obtain the pore volume change factor under recrystallization.

[0083] Specifically, for a numerical simulation model that includes multiple grids, the porosity change factor of each grid at each time step is calculated based on the porosity change mathematical characterization model under recrystallization, according to the porosity multiple of each grid at each time step.

[0084] S155: Based on the porosity change factor under salt dissolution and the porosity change factor under recrystallization, respectively, and using the mathematical characterization model of permeability change, calculate the permeability change factor under salt dissolution and the permeability change factor under recrystallization, and obtain the conductivity change factor under salt dissolution and the conductivity change factor under recrystallization.

[0085] Specifically, for a numerical simulation model comprising multiple grids, based on the porosity change factor of the grid at each time step under salt dissolution, and using a mathematical characterization model of permeability change, the permeability change factor of the grid at each time step under salt dissolution is calculated. Similarly, based on the porosity change factor of the grid at each time step under recrystallization, and using the same mathematical characterization model of permeability change, the permeability change factor of the grid at each time step under recrystallization is calculated. Specifically, the permeability change factor is taken as equal to the conductivity change factor; that is, after calculating the permeability change factor, its value is equal to the conductivity change factor.

[0086] Based on experiments and theoretical derivations, mathematical characterization models of porosity and permeability changes under salt dissolution and recrystallization in intersalt shale oil reservoirs are established. These models allow for accurate calculation of the porosity and permeability changes, thereby accurately obtaining the pore volume and conductivity changes.

[0087] Example 4

[0088] Based on Example 3, optionally, the mathematical characterization model for porosity changes under salt dissolution includes:

[0089]

[0090] In formula (1), φ is the current porosity, which is dimensionless; φ0 is the initial porosity, which is dimensionless. The dimensionless factor is the multiple of porosity change; m sample The mass of the rock sample is expressed in grams (g); a NaCl The mass percentage of NaCl in the rock sample is %, dimensionless; ρ NaCl PV represents the density of NaCl, in g / L. flow The water permeability factor, i.e., the water permeability factor in the mathematical characterization model of porosity change under salt dissolution, is dimensionless; b is the porosity multiple of water required for complete dissolution of NaCl in the rock sample, dimensionless; glauberite ρ represents the mass percentage of sodium sulfate in the rock sample, in %, and as a decimal. glauberite ρ represents the density of sodium sulfate, in g / L; C is the recrystallization coefficient of sodium sulfate, dimensionless. V is the dimensionless multiple of water porosity required for the complete dissolution of calcium sulfate in the rock sample; sample PV represents the volume of the rock sample, in liters (L). The rock sample can refer to a rock sample from an inter-salt shale oil reservoir to be simulated. In the experiment for establishing a mathematical model of porosity changes under salt dissolution, PV... flow The porosity ratio of the injected water in the rock core was used.

[0091] The inventors comprehensively considered the mechanism and influencing factors of salt dissolution, and based on the content of calcium sulfate and NaCl in the mixed salt in the rock sample, the solubility (saturation concentration), density, reaction rate, and water permeation ratio of the salt, established a mathematical characterization model of porosity change under salt dissolution as shown in formula (1), which can accurately calculate the porosity change ratio under salt dissolution.

[0092] Specifically, in formula (1), we have:

[0093]

[0094]

[0095]

[0096] In formulas (2)-(4), ρ solvent ξ represents the density of the solvent, expressed in g / L. For example, water is typically injected into intersalt shale oil reservoirs. NaCl A dimensionless coefficient representing the combined effect of the contact area between NaCl and the solvent and the NaCl reaction rate; S NaCl The solubility of NaCl, expressed as the mass percentage of solute to solution in a saturated solution, is dimensionless; ξ glauberite A dimensionless coefficient representing the combined effect of the contact area between sodium sulfate and the solvent and the reaction rate of sodium sulfate; S glauberiteV represents the solubility of calcium sulfate, dimensionless; V is the current pore volume in L; V0 is the initial pore volume in L.

[0097] As can be seen from formula (4), the porosity change factor is equal to the pore volume change factor. In the numerical simulation calculation process, porosity is a static initial parameter and generally does not change over time. Therefore, the pore volume change factor is used here to characterize the porosity change factor.

[0098] Optionally, mathematical characterization models for porosity changes under recrystallization include:

[0099]

[0100] In formula (5), φ is the current porosity, which is dimensionless; φ0 is the initial porosity, which is dimensionless. PV is a dimensionless multiple of porosity change. flow out α is the water displacement factor, i.e., the water displacement factor in the mathematical characterization model of porosity change under recrystallization, which is dimensionless; NaCl The NaCl crystallization rate at the current temperature and pressure is expressed in g / L; ρ NaCl β is the density of NaCl, in g / L; glauberite The precipitation rate of sodium sulfate crystals at the current temperature and pressure is expressed in g / L; ρ glauberite V represents the density of Glauber's salt, in g / L; sample PV represents the volume of the rock sample, in liters (L). In the experiment establishing the mathematical characterization model of porosity changes under recrystallization, PV... flow out The porosity ratio of the produced water in the core was used.

[0101] The inventors’ research on recrystallization experiments of salt minerals shows that the amount of salt crystallization is related to the volume of the saturated solution and the salt crystallization precipitation rate under different temperature and pressure conditions. Based on this, a mathematical characterization model of porosity change under recrystallization, as shown in formula (5), was established, which can accurately calculate the porosity change factor under recrystallization.

[0102] Optionally, the mathematical representation model of permeability change includes:

[0103] K(φ) / K0=(φφ0) ckpower ×[(1-φ0) / (1-φ)] 2 (6)

[0104] In formula (6), K(φ) is the current permeability in D; K0 is the initial permeability in D; K(φ) / K0 is the permeability change factor, dimensionless; φ is the current porosity, dimensionless; φ0 is the initial porosity, dimensionless; φ / φ0 is the porosity change factor, dimensionless; ckpower is the exponent, dimensionless. Specifically, if it is necessary to calculate the permeability change factor under salt dissolution, then φ / φ0 in formula (6) is substituted into the porosity change factor under salt dissolution, and the corresponding calculated K(φ) / K0 is the permeability change factor under salt dissolution; if it is necessary to calculate the permeability change factor under recrystallization, then φ / φ0 in formula (6) is substituted into the porosity change factor under recrystallization, and the corresponding calculated K(φ) / K0 is the permeability change factor under recrystallization.

[0105] Based on the functional relationship between permeability and porosity, the inventors developed a mathematical model for permeability change, as shown in formula (6), which can accurately calculate the permeability change factor based on the porosity change factor.

[0106] Example 5

[0107] The numerical processing method for intersalt shale oil reservoirs includes steps S110 to S170, as described in Example 1, and will not be repeated here. Specifically, step S170 includes steps (a1) to (a4).

[0108] Step (a1): Calculate the porosity parameters of the first time step under salt dissolution based on the initial characteristic parameters and the change factor of the porosity parameters in the first time step under salt dissolution.

[0109] For example, the porosity parameters at the first time step under salt dissolution can be obtained by multiplying the initial characteristic parameters and the change factor of the porosity parameters at the first time step under salt dissolution. Specifically, for a numerical simulation model comprising multiple grids, the porosity parameters of the grid at the first time step under salt dissolution are calculated based on the initial characteristic parameters of the grid and the change factor of the porosity parameters of the grid at the first time step under salt dissolution.

[0110] Step (a2): Based on the initial characteristic parameters and the change factor of the porosity parameters in the first time step under recrystallization, calculate the porosity parameters in the first time step under recrystallization.

[0111] For example, the porosity and permeability parameters at the first time step under recrystallization can be obtained by multiplying the initial characteristic parameters and the change factor of the porosity and permeability parameters at the first time step under recrystallization. Specifically, for a numerical simulation model comprising multiple grids, the porosity and permeability parameters of the grid at the first time step under recrystallization can be calculated based on the initial characteristic parameters of the grid and the change factor of the porosity and permeability parameters of the grid at the first time step under recrystallization.

[0112] Step (a3): Based on the porosity parameters of the previous time step under salt dissolution and the change factor of the porosity parameters of the next time step under salt dissolution, calculate the porosity parameters of the next time step under salt dissolution.

[0113] Specifically, for a numerical simulation model comprising multiple grids, the porosity parameter of the grid at the first time step under salt dissolution is calculated as the product of the change factor of the porosity parameter of the grid at the second time step, to obtain the porosity parameter of the grid at the second time step under salt dissolution; then, the product of the porosity parameter of the grid at the second time step under salt dissolution and the change factor of the porosity parameter of the grid at the third time step is calculated, to obtain the porosity parameter of the grid at the third time step under salt dissolution; and so on, based on the porosity parameter of the previous time step and the change factor of the porosity parameter of each time step, the porosity parameter of the grid at each time step under salt dissolution is obtained.

[0114] Step (a4): Based on the porosity parameters of the previous time step under recrystallization and the change factor of the porosity parameters of the next time step under recrystallization, calculate the porosity parameters of the next time step under recrystallization.

[0115] Specifically, for a numerical simulation model comprising multiple grids, the porosity-permeability parameter of the grid at the first time step under recrystallization is calculated as the product of the change factor of the porosity-permeability parameter of the grid at the second time step, to obtain the porosity-permeability parameter of the grid at the second time step under recrystallization; then, the product of the porosity-permeability parameter of the grid at the second time step under recrystallization and the change factor of the porosity-permeability parameter of the grid at the third time step is calculated, to obtain the porosity-permeability parameter of the grid at the third time step under recrystallization; and so on, based on the porosity-permeability parameter of the previous time step and the change factor of the porosity-permeability parameter of each time step, the porosity-permeability parameter of the grid at each time step under recrystallization is obtained.

[0116] By iteratively calculating the porosity parameters of each grid at each time step based on the change factor of the porosity parameters at each time step, the trend of porosity parameters changing over time can be analyzed based on the porosity parameters at each time step. This can be used to analyze the changes in seepage capacity and thus predict production capacity.

[0117] Further, the initial characteristic parameters include initial pore volume and initial conductivity; the pore-permeability parameters include pore volume and conductivity; and the pore-permeability parameter change factors include pore volume change factors and conductivity change factors. Step (a1) specifically involves calculating the pore volume at the first time step under salt dissolution based on the initial pore volume and the pore volume change factor at the first time step under salt dissolution; and calculating the conductivity at the first time step under salt dissolution based on the initial conductivity and the conductivity change factor at the first time step under salt dissolution. Step (a2) specifically involves calculating the pore volume at the first time step under recrystallization based on the initial pore volume and the pore volume change factor at the first time step under recrystallization; and calculating the conductivity at the first time step under recrystallization based on the initial conductivity and the conductivity change factor at the first time step under recrystallization. Step (a3) ​​specifically involves calculating the pore volume of the next time step under salt dissolution based on the pore volume of the previous time step under salt dissolution and the pore volume change factor of the next time step under salt dissolution; and calculating the conductivity of the next time step under salt dissolution based on the conductivity of the previous time step under salt dissolution and the conductivity change factor of the next time step under salt dissolution. Step (a4) specifically involves calculating the pore volume of the next time step under recrystallization based on the pore volume of the previous time step under recrystallization and the pore volume change factor of the next time step under recrystallization; and calculating the conductivity of the next time step under recrystallization based on the conductivity of the previous time step under recrystallization and the conductivity change factor of the next time step under recrystallization.

[0118] Example 6

[0119] The numerical processing method for intersalt shale oil reservoirs includes steps S110 to S170, as described in Example 1, and will not be repeated here. In this example, after step S170, the method further includes updating the porosity and permeability parameters of each time step in the numerical simulation model.

[0120] Specifically, the attribute values ​​corresponding to the porosity and permeability parameters can be updated in the numerical simulation model. For example, the attribute values ​​corresponding to the porosity and permeability parameters can be color values ​​representing the depth of color. Each time step corresponds to a model image, so the color values ​​of each grid in the corresponding model image can be changed according to the calculated porosity and permeability parameters of each grid at each time step. By changing the porosity and permeability parameters in the numerical simulation model, the model can intuitively display the changes in the porosity and permeability parameters, making it convenient for users to view.

[0121] Example 7

[0122] Furthermore, step S170 may also include: obtaining the seepage characteristic parameters in the numerical simulation model based on the pore seepage parameters and the preset calculation equations.

[0123] Among these, seepage characteristic parameters are those influenced by porosity and permeability parameters, such as fluid seepage velocity, pressure, and fluid saturation. The calculation equations can be pre-established based on the correspondence between porosity and permeability parameters and seepage characteristic parameters. By further calculating the seepage characteristic parameters at each time step based on porosity and permeability parameters, it is easier to analyze the changes in seepage characteristic parameters in inter-salt shale oil reservoirs, leading to a more comprehensive analysis of production capacity. For example, based on changes in pore volume and conductivity, changes in pressure field, saturation field, and seepage field can be calculated and analyzed, ultimately simulating the impact of salt dissolution and recrystallization mechanisms on the production dynamics of inter-salt shale oil.

[0124] To facilitate understanding of the solutions and effects of the embodiments of this application, a specific application example is given below. Those skilled in the art should understand that this example is only for the purpose of understanding this application, and any specific details therein are not intended to limit this application in any way. A numerical processing method for inter-salt shale oil reservoirs according to this application may include:

[0125] 1. In the Intersect numerical simulation software, establish a mechanistic model for the numerical simulation, such as... Figure 3 As shown. The model has a horizontal well in the middle, with a length of 600m. The model mesh size is 201*121*5. The mesh step size in the X, Y, and Z directions is 5m*5m*2m. The initial permeability of the model is 1mD, and the porosity is 13%.

[0126] 2. Set the working system of the production well. In the user edit module of the PetrelRe software platform, use Python language to program and iterate through each grid in the model to read the water flow ratio, initial pore volume and initial conductivity of each grid at each time step in the production process. Figure 4 The graph shows the changes in pore volume and conductivity at a certain time step. Different colors represent different pore volumes. The vertical bars on the left side of the graph represent the corresponding pore volumes in different colors, with a gradient from blue to green to yellow, orange, and red from bottom to top. The black part of the model in the middle of the graph is actually displayed as red, corresponding to 7.2. The red part is surrounded by a greenish-yellow color, corresponding to approximately 6.9.

[0127] 3. Using mathematical characterization models of porosity changes under salt dissolution, recrystallization, and permeability changes, and based on the water permeation multiple of each grid at each time step, calculate the pore volume change multiple and conductivity change multiple caused by salt dissolution and recrystallization for each grid and at each time step. Figure 5The diagram shows the field plot of pore volume and conductivity after a certain time step update. Different colors represent different conductivity values. The vertical bars on the left side of the diagram represent the corresponding conductivity values ​​in different colors. From bottom to top, the colors are blue, green, yellow, orange, and red. The black part of the model in the middle of the diagram is actually displayed as red, indicating a value of 0.05.

[0128] 4. By calculating the pore volume change factor and conductivity change factor of each grid, the pore volume and conductivity of each grid are updated in real time at each time step, and the updated pore volume and conductivity are applied to the calculation of the next time step. Figure 6 The diagram shows the impact of salt dissolution and recrystallization on production dynamics in the model. In the diagram, the solid line represents the liquid production and the dashed line represents the oil production.

[0129] 5. Based on the changes in pore volume and conductivity, the changes in pressure field, saturation field, and seepage field in the calculation model are used to finally simulate the impact of salt dissolution and recrystallization mechanisms on the dynamics of intersalt shale oil production.

[0130] It should be understood that, although Figures 1-2 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order in which these steps are executed, and they can be performed in other orders. Figures 1-2 At least some of the steps in the process may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the steps or stages in other steps.

[0131] Example 8

[0132] like Figure 7 As shown, a numerical processing device for intersalt shale oil reservoirs is provided, including a model building module 710, a data reading module 730, a calculation and processing module 750, and a parameter acquisition module 770.

[0133] The model building module 710 is used to build a numerical simulation model of the inter-salt shale oil reservoir to be simulated. The data reading module 730 is used to acquire the initial characteristic parameters and the water permeation ratio at each time step after water injection in the numerical simulation model. The calculation and processing module 750 is used to calculate the change factor of porosity and permeability parameters at each time step under salt dissolution and recrystallization, respectively, based on the water permeation ratio at each time step and using a preset mathematical characterization model of reservoir porosity and permeability changes. The parameter acquisition module 770 is used to acquire the porosity and permeability parameters at each time step under salt dissolution and recrystallization, respectively, based on the initial characteristic parameters and the change factor of porosity and permeability parameters at each time step under salt dissolution and recrystallization.

[0134] The aforementioned numerical processing device for inter-salt shale oil reservoirs establishes a numerical simulation model of the inter-salt shale oil reservoir to be simulated. Based on the water permeability multiples obtained at each time step in the numerical simulation model and the mathematical characterization model of reservoir porosity and permeability changes, it calculates the porosity and permeability parameter change multiples at each time step under salt dissolution and recrystallization. Based on the initial characteristic parameters and the porosity and permeability parameter change multiples under salt dissolution and recrystallization, it obtains the porosity and permeability parameters for each time step. Thus, by establishing a numerical simulation of porosity and permeability changes caused by salt dissolution and recrystallization in inter-salt shale oil reservoirs, it can quantitatively obtain the porosity and permeability parameters at each time step, reflecting the porosity and permeability changes. The analysis of porosity and permeability changes is quantitative and highly accurate, and can be used to accurately analyze seepage capacity and accurately predict the production capacity of actual production wells exhibiting salt dissolution and recrystallization phenomena.

[0135] Specifically, the numerical simulation model is a grid model comprising multiple grids. The water flow factor at each time step includes the water flow factor of each grid at each time step, the porosity-permeability parameter change factor at each time step includes the porosity-permeability parameter change factor of each grid at each time step, and the porosity-permeability parameter at each time step includes the porosity-permeability parameter of each grid at each time step. That is, the data reading module 730 acquires the initial characteristic parameters of each grid in the numerical simulation model and the water flow factor of each grid at each time step after water injection; the calculation and processing module 750, based on the water flow factor of each grid at each time step, uses a preset mathematical characterization model of reservoir porosity-permeability change to calculate the porosity-permeability parameter change factor of each grid at each time step under salt dissolution and recrystallization respectively; the parameter acquisition module 770, based on the initial characteristic parameters of each grid and the porosity-permeability parameter change factor of each grid at each time step under salt dissolution and recrystallization respectively, acquires the porosity-permeability parameter of each grid at each time step under salt dissolution and recrystallization respectively.

[0136] For example, Python can be used in the user edit module of the PetrelRe software platform to programmatically iterate through each grid in the numerical simulation model and read the water flow ratio and initial characteristic parameters of each grid during production. By refining the calculation of porosity parameters to each grid in the numerical simulation model, high accuracy is achieved.

[0137] Optionally, the initial characteristic parameters may include initial pore volume and initial conductivity, and the pore-permeability parameters may include pore volume and conductivity. Correspondingly, the change factors of the pore-permeability parameters include the change factors of pore volume and conductivity. Pore volume reflects pore size, and conductivity reflects permeability. The size of pore volume and conductivity affects seepage capacity, thus affecting production. By quantitatively calculating the pore volume and conductivity at each time step through numerical simulation, it is possible to accurately analyze the changes in pore volume and conductivity, accurately reflect changes in seepage capacity, and thus accurately predict production capacity.

[0138] Optionally, the pre-defined mathematical characterization models for reservoir porosity and permeability changes include a mathematical characterization model for permeability changes, a mathematical characterization model for porosity changes under salt dissolution, and a mathematical characterization model for porosity changes under recrystallization. The porosity change mathematical characterization model and the permeability change mathematical characterization model are mathematical models obtained based on experimental and theoretical studies; specifically, the permeability change mathematical characterization model is used to calculate the permeability change factor, the porosity change mathematical characterization model under salt dissolution is used to calculate the porosity change factor under salt dissolution, and the porosity change mathematical characterization model under recrystallization is used to calculate the porosity change factor under recrystallization.

[0139] The calculation and processing module 750 is used to calculate the porosity change factor under salt dissolution based on the water flow factor at each time step and the mathematical characterization model of porosity change under salt dissolution, thereby obtaining the pore volume change factor under salt dissolution; based on the water flow factor at each time step and the mathematical characterization model of porosity change under recrystallization, it calculates the porosity change factor under recrystallization, thereby obtaining the pore volume change factor under recrystallization; based on the porosity change factor under salt dissolution and the porosity change factor under recrystallization, respectively, it calculates the permeability change factor under salt dissolution and the permeability change factor under recrystallization based on the permeability change mathematical characterization model, thereby obtaining the conductivity change factor under salt dissolution and the conductivity change factor under recrystallization.

[0140] Based on experiments and theoretical derivations, mathematical characterization models of porosity and permeability changes under salt dissolution and recrystallization in intersalt shale oil reservoirs are established. These models allow for accurate calculation of the porosity and permeability changes, thereby accurately obtaining the pore volume and conductivity changes.

[0141] Optionally, mathematical models representing porosity changes under salt dissolution include:

[0142]

[0143] In the formula, φ is the current porosity, which is dimensionless; φ0 is the initial porosity, which is dimensionless. The dimensionless factor is the multiple of porosity change; m sample The mass of the rock sample is expressed in grams (g); a NaCl The mass percentage of NaCl in the rock sample, %; ρ NaCl PV represents the density of NaCl, in g / L. flow The water permeability factor, i.e., the water permeability factor in the mathematical characterization model of porosity change under salt dissolution, is dimensionless; b is the porosity multiple of water required for complete dissolution of NaCl in the rock sample, dimensionless; glauberite The mass percentage of calcium sulfate in the rock sample, %; ρ glauberite ρ represents the density of sodium sulfate, in g / L; C is the recrystallization coefficient of sodium sulfate, dimensionless. V is the dimensionless multiple of water porosity required for the complete dissolution of calcium sulfate in the rock sample; sample The volume of the rock sample is expressed in liters (L). The rock sample can refer to a rock sample from the intersalt shale oil reservoir to be simulated.

[0144] Taking into account the mechanism and influencing factors of salt dissolution, the inventors established a mathematical characterization model of porosity changes under salt dissolution based on the content of calcium sulfate and NaCl in the mixed salt in the rock sample, the solubility (saturation concentration), density, reaction rate, and water permeation factor of the salt. This model can accurately calculate the porosity change factor under salt dissolution.

[0145] Specifically, there are:

[0146]

[0147]

[0148]

[0149] In the formula, ρ solvent ξ represents the density of the solvent, expressed in g / L. For example, water is typically injected into intersalt shale oil reservoirs. NaCl A dimensionless coefficient representing the combined effect of the contact area between NaCl and the solvent and the NaCl reaction rate; S NaCl ξ represents the solubility of NaCl, dimensionless; glauberite A dimensionless coefficient representing the combined effect of the contact area between sodium sulfate and the solvent and the reaction rate of sodium sulfate; S glauberiteV represents the solubility of calcium sulfate, dimensionless; V is the current pore volume in L; V0 is the initial pore volume in L.

[0150] As can be seen from the above formula, the porosity change factor is equal to the pore volume change factor. In the numerical simulation calculation process, porosity is a static initial parameter and generally does not change over time. Therefore, the pore volume change factor is used here to characterize the porosity change factor.

[0151] Optionally, mathematical characterization models for porosity changes under recrystallization include:

[0152]

[0153] In the formula, φ is the current porosity, which is dimensionless; φ0 is the initial porosity, which is dimensionless. PV is a dimensionless multiple of porosity change. flow out α is the water displacement factor, i.e., the water displacement factor in the mathematical characterization model of porosity change under recrystallization, which is dimensionless; NaCl The NaCl crystallization rate at the current temperature and pressure is expressed in g / L; ρ NaCl β is the density of NaCl, in g / L; glauberite The precipitation rate of sodium sulfate crystals at the current temperature and pressure is expressed in g / L; ρ glauberite V represents the density of Glauber's salt, in g / L; sample The volume of the rock sample is expressed in liters (L).

[0154] The inventors' research on recrystallization experiments of salt minerals shows that the amount of salt crystallization is related to the volume of the saturated solution and the salt crystallization precipitation rate under different temperature and pressure conditions. Based on this, a mathematical characterization model of porosity change under recrystallization was established, which can accurately calculate the porosity change factor under recrystallization.

[0155] Optionally, the mathematical representation model of permeability change includes:

[0156] K(φ) / K0=(φ / φ0) ckpower ×[(1-φ0) / (1-φ)] 2 ;

[0157] In the formula, K(φ) is the current permeability in D; K0 is the initial permeability in D; K(φ) / K0 is the permeability change factor, dimensionless; φ is the current porosity, dimensionless; φ0 is the initial porosity, dimensionless; φ / φ0 is the porosity change factor, dimensionless; ckpower is the exponent, dimensionless.

[0158] Based on the functional relationship between permeability and porosity, the inventors developed a mathematical model to represent permeability changes, which can accurately calculate the permeability change factor based on the porosity change factor.

[0159] Optionally, the parameter acquisition module 770 is used to: calculate the porosity parameters of the first time step under salt dissolution based on the initial characteristic parameters and the change factor of the porosity parameters of the first time step under salt dissolution; calculate the porosity parameters of the first time step under recrystallization based on the initial characteristic parameters and the change factor of the porosity parameters of the first time step under recrystallization; calculate the porosity parameters of the next time step under salt dissolution based on the porosity parameters of the previous time step under salt dissolution and the change factor of the porosity parameters of the next time step under salt dissolution; and calculate the porosity parameters of the next time step under recrystallization based on the porosity parameters of the previous time step under recrystallization and the change factor of the porosity parameters of the next time step under recrystallization.

[0160] By iteratively calculating the porosity parameters of each grid at each time step based on the change factor of the porosity parameters at each time step, the trend of porosity parameters changing over time can be analyzed based on the porosity parameters at each time step. This can be used to analyze the changes in seepage capacity and thus predict production capacity.

[0161] Optionally, the numerical processing device for intersalt shale oil reservoirs described above may also include an update module (not shown) for updating the porosity and permeability parameters at each time step in the numerical simulation model.

[0162] Specifically, the attribute values ​​corresponding to the porosity and permeability parameters can be updated in the numerical simulation model. For example, the attribute values ​​corresponding to the porosity and permeability parameters can be color values ​​representing the depth of color. Each time step corresponds to a model image, so the color values ​​of each grid in the corresponding model image can be changed according to the calculated porosity and permeability parameters of each grid at each time step. By changing the porosity and permeability parameters in the numerical simulation model, the model can intuitively display the changes in the porosity and permeability parameters, making it convenient for users to view.

[0163] Optionally, the numerical processing device for intersalt shale oil reservoirs may also include an equation calculation module (not shown) for obtaining seepage characteristic parameters in the numerical simulation model based on pore permeability parameters and preset calculation equations.

[0164] Among these, seepage characteristic parameters are those influenced by porosity and permeability parameters, such as fluid seepage velocity, pressure, and fluid saturation. The calculation equations can be pre-established based on the correspondence between porosity and permeability parameters and seepage characteristic parameters. By further calculating the seepage characteristic parameters at each time step based on porosity and permeability parameters, it is easier to analyze the changes in seepage characteristic parameters in inter-salt shale oil reservoirs, leading to a more comprehensive analysis of production capacity. For example, based on changes in pore volume and conductivity, changes in pressure field, saturation field, and seepage field can be calculated and analyzed, ultimately simulating the impact of salt dissolution and recrystallization mechanisms on the production dynamics of inter-salt shale oil.

[0165] Specific limitations regarding the numerical processing device for inter-salt shale oil reservoirs can be found in the above-described limitations on the numerical processing method for inter-salt shale oil reservoirs, and will not be repeated here. Each module in the aforementioned numerical processing device for inter-salt shale oil reservoirs can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module. It should be noted that the module division in this embodiment is illustrative and only represents a logical functional division; other division methods may be used in actual implementation.

[0166] Example 9

[0167] A computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the methods in the above embodiments.

[0168] The aforementioned computer equipment, since it can implement the steps of the methods in the above embodiments, can similarly obtain the pore permeability parameters at each time step and reflect the changes in pore permeability. The analysis of changes in pore permeability is quantitative and highly accurate, and can be used to accurately analyze seepage capacity and accurately predict the production capacity of actual production wells that have salt dissolution and recrystallization phenomena.

[0169] Example 10

[0170] A computer-readable storage medium is provided on which a computer program is stored, which, when executed by a processor, implements the steps of the methods in the above embodiments.

[0171] The aforementioned computer-readable storage medium, since it can implement the steps of the methods in the above embodiments, similarly can quantitatively obtain the porosity permeability parameters at each time step, reflect the changes in porosity permeability, and provide highly quantitative and accurate analysis of changes in porosity permeability. It can be used to accurately analyze seepage capacity and accurately predict the production capacity of actual production wells that exhibit salt dissolution and recrystallization phenomena.

[0172] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0173] In the description of this specification, references to terms such as "some embodiments," "other embodiments," and "ideal embodiments" indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative descriptions of the above terms do not necessarily refer to the same embodiments or examples.

[0174] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of each technical feature in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0175] While the embodiments disclosed in this invention are as described above, the content is merely for the purpose of facilitating understanding of the invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope disclosed herein; however, the scope of protection of this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A method for numerical processing of inter-salt shale oil reservoirs, characterized by, include: Establish a numerical simulation model for the salt-interspinous shale oil reservoir to be simulated; Obtain the initial characteristic parameters and the water overflow ratio at each time step after water injection in the numerical simulation model; Based on the water permeation factor at each time step, a preset mathematical characterization model for reservoir porosity and permeability changes is used to calculate the porosity and permeability parameter change factors at each time step under salt dissolution and recrystallization. Based on the initial characteristic parameters, the change factor of the porosity parameters at each time step under salt dissolution and recrystallization, the porosity parameters at each time step under salt dissolution and recrystallization are obtained respectively. The initial characteristic parameters include initial pore volume and initial conductivity; the pore permeability parameters include pore volume and conductivity; and the pore permeability parameter variation factor includes pore volume variation factor and conductivity variation factor. The preset mathematical characterization model for reservoir porosity and permeability changes includes a mathematical characterization model for permeability changes, a mathematical characterization model for porosity changes under salt dissolution, and a mathematical characterization model for porosity changes under recrystallization. The step of calculating the porosity and permeability parameter changes at each time step under salt dissolution and recrystallization, based on the water permeation multiple at each time step, using the preset mathematical characterization model for reservoir porosity and permeability changes, includes: Based on the water permeation factor at each time step, the porosity change factor under salt dissolution is calculated using a mathematical characterization model of porosity change under salt dissolution, thus obtaining the pore volume change factor under salt dissolution. Based on the water permeation factor at each time step, the porosity change factor under recrystallization is calculated using a mathematical characterization model of porosity change under recrystallization, thus obtaining the pore volume change factor under recrystallization. Based on the porosity change factor under salt dissolution and recrystallization respectively, and using the mathematical characterization model of permeability change, the permeability change factor under salt dissolution and recrystallization are calculated to obtain the conductivity change factor under salt dissolution and recrystallization respectively. The mathematical characterization model for porosity changes under salt dissolution includes: ； in, The current porosity is dimensionless. The initial porosity is dimensionless. This is a dimensionless factor representing the change in porosity. The mass of the rock sample is expressed in grams (g). The mass percentage of NaCl in the rock sample is dimensionless. The density of NaCl is expressed in g / L. The water injection ratio is dimensionless. The porosity multiple of water required for complete dissolution of NaCl in the rock sample is dimensionless. This represents the mass percentage of calcium mirabilite in the rock sample, as a decimal. This refers to the density of Glauber's salt, expressed in g / L. is the recrystallization coefficient of Glauber's salt, dimensionless; The dimensionless multiple of water porosity required for complete dissolution of calcium mirabilite in the rock sample. Volume of the rock sample, in liters (L). The mathematical characterization model for porosity changes under recrystallization includes: ； in, The current porosity is dimensionless. The initial porosity is dimensionless. This is a dimensionless factor representing the change in porosity. The water dilution ratio of the produced water is dimensionless. This represents the NaCl crystallization rate under the current temperature and pressure, expressed in g / L. The density of NaCl is expressed in g / L. The precipitation rate of Glauber's salt crystals under the current temperature and pressure is expressed in g / L. This refers to the density of Glauber's salt, expressed in g / L. Volume of the rock sample, in liters (L). The mathematical representation model for permeability change includes: ； wherein, is the current permeability, unit D; is the initial permeability, unit D; is the permeability change factor, dimensionless; is the current porosity, dimensionless; is the initial porosity, dimensionless; is the porosity change factor; is the exponent, dimensionless.

2. The method of claim 1, wherein, The method of obtaining the porosity parameters at each time step under salt dissolution and recrystallization based on the initial characteristic parameters, the change factor of the porosity parameters at each time step under salt dissolution and recrystallization includes: Based on the initial characteristic parameters and the change factor of the porosity parameters in the first time step under salt dissolution, the porosity parameters in the first time step under salt dissolution are calculated. Based on the initial characteristic parameters and the change factor of the porosity parameters in the first time step under recrystallization, the porosity parameters in the first time step under recrystallization are calculated. Based on the porosity parameters of the previous time step under salt dissolution and the change factor of the porosity parameters of the next time step under salt dissolution, the porosity parameters of the next time step under salt dissolution are calculated. Based on the porosity parameters of the first time step under recrystallization and the change factor of the porosity parameters of the next time step under recrystallization, the porosity parameters of the next time step under recrystallization are calculated.

3. The method of claim 1, wherein, After obtaining the porosity parameters at each time step under salt dissolution and recrystallization based on the initial characteristic parameters and the change factor of the porosity parameters at each time step under salt dissolution and recrystallization, the method further includes: Update the pore permeability parameters at each time step in the numerical simulation model.

4. The method of claim 1, wherein, After obtaining the porosity parameters at each time step under salt dissolution and recrystallization based on the initial characteristic parameters and the change factor of the porosity parameters at each time step under salt dissolution and recrystallization, the method further includes: Based on the pore permeability parameters and the preset calculation equations, the seepage characteristic parameters in the numerical simulation model are obtained.

5. A numerical processing device for inter-salt shale oil reservoirs according to the method of any one of claims 1 to 4, characterized in that, include: The model building module is used to build a numerical simulation model of the salt inter-salt shale oil reservoir to be simulated. The data reading module is used to acquire the initial characteristic parameters and the water flow ratio at each time step after water injection in the numerical simulation model. The calculation and processing module is used to calculate the change factor of pore permeability parameters at each time step under salt dissolution and recrystallization, respectively, based on the water flow ratio at each time step and using a preset mathematical characterization model of reservoir pore permeability change. The parameter acquisition module is used to acquire the porosity parameters at each time step under salt dissolution and recrystallization based on the initial characteristic parameters and the change factor of the porosity parameters at each time step under salt dissolution and recrystallization. 6.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-5 when the computer program is executed by the processor. When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having stored thereon a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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