A numerical simulation adaptive time step method and apparatus

Abstract

The present application relates to the technical field of oil exploration and development, and more particularly to a numerical simulation adaptive time step method and device. The method comprises establishing a percolation model of mud filtrate invasion into a reservoir, obtaining a water phase formula, an oil phase formula and a mud filtrate phase formula; dividing the calculation area into difference grids according to the water phase formula, the oil phase formula and the mud filtrate phase formula, obtaining a finite number of grid nodes, and replacing the continuous solution domain with the finite number of grid nodes; and calculating the saturation and the time step corresponding to the saturation according to the solution domain. In the deduction of the numerical simulation of mud invasion, the numerical simulation of mud invasion based on mass conservation obtains reasonable results, and a reasonable invasion time step is set to determine the change relationship between the saturation and the invasion time, the invasion radius and the like. The present application solves the problem of reasonable value selection of the mud invasion simulation time step in the prior art, and further determines the rationality of the mud invasion simulation results.

Description

Technical Field

[0001] This invention relates to the field of petroleum exploration and development technology, and in particular to a numerical simulation adaptive time step method and apparatus. Background Technology

[0002] Resistivity logging is a primary method for determining reservoir oil content and calculating hydrocarbon content. However, the intrusion of drilling mud filtrate alters the radial water saturation and formation water salinity of the reservoir, causing resistivity logging values ​​to deviate from the original formation resistivity and affecting the accuracy of reservoir evaluation. For formation resistivity correction due to mud intrusion, domestic and international logging companies mainly utilize correction charts. However, different logging instruments and different intrusion conditions require different charts, resulting in low correction efficiency, limited results, and low accuracy. Therefore, a precise and efficient technique is needed to evaluate the impact of mud intrusion on resistivity logging.

[0003] Drilling mud invasion has always been a difficult problem in oil and gas field exploration and development. The invasion of mud filtrate and fine particles alters the original state of the reservoir around the well, making reservoir logging evaluation difficult. Currently, most physical simulations of mud invasion at home and abroad are based on core or sand-filled models. The simulation conditions differ significantly from actual formation conditions, and the experimental results or laws often cannot be directly used to explain the mud invasion phenomenon in downhole reservoirs. Numerical simulation of reservoir mud invasion is a commonly used method and tool for studying the dynamic characteristics of mud invasion. However, due to the significant differences between low-porosity and permeability sandstone reservoirs and medium- and high-porosity and permeability reservoirs in terms of pore structure, physical properties, and fluid flow characteristics, it is necessary to improve the numerical simulation method of mud invasion. Many numerical simulation studies have also failed to obtain the relationship between saturation and invasion time, invasion radius, etc. One very important reason is the unreasonable setting of the invasion time step. When iterating with a very small invasion radius, the time step directly overrides the minimum time at that time, resulting in skipping the correct invasion process and instantaneously invading to equilibrium. Summary of the Invention

[0004] In view of this, the present invention provides a numerical simulation adaptive time step method and apparatus, which are used in the deduction of numerical simulation of mud intrusion to obtain reasonable results of mud intrusion numerical simulation based on mass conservation, and to set a reasonable intrusion time step to determine the relationship between saturation and intrusion time, intrusion radius, etc.

[0005] In a first aspect, the present invention provides a numerical simulation adaptive time step method, the method comprising:

[0006] Step 1: Establish a seepage model for mud filtrate intrusion into the reservoir. In a radial one-dimensional cylindrical coordinate system, perform constant calculations on the aqueous phase, oil phase, and mud filtrate phase using the mass continuity equation to obtain the aqueous phase formula, oil phase formula, and mud filtrate phase formula.

[0007] Step 2: Based on the aqueous phase formula, oil phase formula, and mud filtrate phase formula in Step 1, the computational domain is divided into a differential grid to obtain a finite number of grid nodes, and the continuous solution domain is replaced by the finite number of grid nodes.

[0008] Step 3: Based on the solution domain in Step 2, calculate and obtain the saturation and the time step corresponding to the saturation.

[0009] Optionally, the step of calculating and obtaining the saturation and the time step corresponding to the saturation based on the solution domain in step two includes:

[0010] Step S1: Establish a system of algebraic equations with the values ​​at the grid nodes as unknowns, and calculate the saturation in the j-th cell, where j is a positive integer;

[0011] Step S2: Based on the saturation in the j-th cell in step S1, obtain the j-th time step corresponding to the saturation in the j-th cell, take the saturation in the (j+1)-th cell as the saturation in the j-th cell, and continue to execute the steps of establishing a system of algebraic equations with the values ​​on the grid nodes as unknowns, and calculating and obtaining the saturation in the j-th cell.

[0012] Optionally, the aqueous phase formula is:

[0013]

[0014] The oil phase formula is:

[0015]

[0016] The formula for the mud filtrate phase is:

[0017]

[0018] Where r is the invasion radius, ρ w ρ is the density of water. o Let ρ be the density of the oil. m Let K be the density of the mud, and K be the absolute permeability. rw K represents the relative permeability of water. ro K represents the relative permeability of the oil. rm P represents the relative permeability of the mud. w For the pressure of water, P o For the oil pressure, P m For the pressure of the mud, S represents the porosity of the rock. w S represents the water phase saturation. o S represents the oil phase saturation. m q represents the saturation of the mud filtrate phase. wv For water volume source term, qov For the oil volume source term, q mv This is the volume source term for mud filtrate.

[0019] Optionally, the saturation in the j-th cell includes the water phase saturation. oil phase saturation and mud filtrate phase saturation

[0020] The water phase saturation oil phase saturation and the saturation of the mud filtrate phase The formulas are as follows:

[0021]

[0022] in, Let be the slope of the water phase saturation in the j-th cell as a function of time; Let be the slope of the oil phase saturation in the j-th cell as a function of time. Let Δt be the slope of the mud filtrate phase saturation in the j-th cell as a function of time. j Let j be the j-th time step.

[0023] Optionally, the slope The formula is:

[0024]

[0025] Where i is w, o, or m; n represents time, ΔQ Lj πH(r1) represents the volume increment of fluid L in the j-th cell per unit time; 2 -r0 2 Let ) be the volume of the j-th cell; Total porosity.

[0026] Optionally, the j-th time step Δt j The formula is:

[0027]

[0028] Among them, F j This is the weight value.

[0029] Secondly, the present invention provides a numerical simulation adaptive time step device, the device comprising:

[0030] The acquisition module is used to establish a seepage model of mud filtrate intruding into the reservoir. In a radial one-dimensional cylindrical coordinate system, the mass continuity equation is used to perform constant calculations on the aqueous phase, oil phase, and mud filtrate phase respectively to obtain the aqueous phase formula, oil phase formula, and mud filtrate phase formula.

[0031] The node module is used to divide the computational domain into a differential grid based on the aqueous phase formula, the oil phase formula, and the mud filtrate phase formula, thereby obtaining a finite number of grid nodes, and using the finite number of these grid nodes to replace the continuous solution domain.

[0032] The calculation module is used to calculate and obtain the saturation and the time step corresponding to the saturation based on the solution domain.

[0033] Optionally, the computing module includes:

[0034] The calculation submodule is used to establish a system of algebraic equations with the values ​​at the grid nodes as unknowns, and to calculate the saturation in the j-th cell, where j is a positive integer;

[0035] The acquisition submodule is used to obtain the j-th time step corresponding to the saturation in the j-th cell based on the saturation in the j-th cell, take the saturation in the (j+1)-th cell as the saturation in the j-th cell, and trigger the calculation submodule to continue to execute the steps of establishing a system of algebraic equations with the values ​​on the grid nodes as unknowns, and calculating and obtaining the saturation in the j-th cell.

[0036] Thirdly, the present invention provides a computer-readable storage medium comprising a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the numerical simulation adaptive time step method in the first aspect or any possible implementation thereof.

[0037] Fourthly, the present invention provides an electronic device comprising: one or more processors; a memory; and one or more computer programs, wherein the one or more computer programs are stored in the memory, and the one or more computer programs include instructions that, when executed by the device, cause the device to perform the numerical simulation adaptive time step method in the first aspect or any possible implementation thereof.

[0038] The technical solution provided by this invention includes establishing a seepage model for mud filtrate intrusion into the reservoir. In a radial one-dimensional cylindrical coordinate system, the mass continuity equation is used to perform constant calculations on the aqueous phase, oil phase, and mud filtrate phase to obtain aqueous phase formulas, oil phase formulas, and mud filtrate phase formulas. Based on these formulas, the computational domain is divided into a differential grid, resulting in a finite number of grid nodes, which are then used to replace the continuous solution domain. Based on the solution domain, the saturation and the corresponding time step are calculated. In the numerical simulation of mud intrusion, the mass conservation principle ensures reasonable results, and a reasonable intrusion time step is set. Furthermore, the change in saturation with the intrusion radius clearly reflects the intrusion zone, determining the relationship between saturation and intrusion time, intrusion radius, etc. This invention solves the problem of reasonably selecting the time step in mud intrusion simulation in the prior art, thereby determining the rationality of the mud intrusion simulation results. Attached Figure Description

[0039] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 A flowchart of the numerical simulation adaptive time step method provided in the embodiments of the present invention;

[0041] Figure 2 A schematic diagram illustrating saturation changes provided in an embodiment of the present invention;

[0042] Figure 3 A schematic diagram of the well wall provided in an embodiment of the present invention;

[0043] Figure 4 A schematic diagram of a cell provided in an embodiment of the present invention;

[0044] Figure 5 A schematic diagram illustrating the experimental results provided in the embodiments of the present invention;

[0045] Figure 6 A schematic diagram illustrating another experimental result provided in an embodiment of the present invention;

[0046] Figure 7 A schematic diagram of a numerical simulation adaptive time step device provided in an embodiment of the present invention;

[0047] Figure 8 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] It should be understood that the described embodiments are merely some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0050] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0051] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0052] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0053] The adaptive time step method for numerical simulation can be applied to situations where other variables are obtained during iteration time, including numerical simulations of intrusion, natural gas extraction, and carbon dioxide flooding. In this embodiment of the invention, the numerical simulation of mud filtrate intrusion is used as an example for description.

[0054] Figure 1 The flowchart of the numerical simulation adaptive time step method provided in the embodiments of the present invention is as follows: Figure 1 As shown, the method includes:

[0055] Step 1: Establish a seepage model for mud filtrate intrusion into the reservoir. In a radial one-dimensional cylindrical coordinate system, perform constant calculations on the aqueous phase, oil phase, and mud filtrate phase using the mass continuity equation to obtain the aqueous phase formula, oil phase formula, and mud filtrate phase formula.

[0056] In this embodiment of the invention, a seepage model for mud filtrate intruding into the reservoir is established based on Darcy's flow theory. Darcy's flow theory is the basic law of fluid movement in porous media and is also a statistical law describing the seepage process from a macroscopic perspective. This theory was summarized from a large number of experiments to solve the problem of water purification.

[0057] In this embodiment of the invention, the numerical simulation assumptions are as follows:

[0058] (1) Only three phases of seepage, namely mud filtrate, water and oil, exist in the reservoir. The mud filtrate, water and oil are immiscible and each conforms to Darcy's law.

[0059] (2) Ignoring the effect of capillary force: P w =P o =P m =P.

[0060] (3) Ignore gravity.

[0061] In this embodiment of the invention, all parameters in the numerical simulation include porosity, absolute permeability, pressure difference, initial saturation of water, oil, mud filtrate, bound water saturation, residual oil saturation, viscosity of the three phases, compressibility coefficient of the three phases and compressibility coefficient of the rock, etc. These coefficients can be adjusted arbitrarily according to the actual situation to obtain the desired intrusion simulation results.

[0062] In this embodiment of the invention, the mass continuity equation is a mass conservation equation based on Darcy's seepage theory. The formula for the mass conservation equation is:

[0063] In this embodiment of the invention, the aqueous phase formula is:

[0064]

[0065] The oil phase formula is:

[0066]

[0067] The formula for the mud filtrate phase is:

[0068]

[0069] Where r is the invasion radius, ρ w ρ is the density of water. o Let ρ be the density of the oil. m Let K be the density of the mud, and K be the absolute permeability. rwK represents the relative permeability of water. ro K represents the relative permeability of the oil. rm P represents the relative permeability of the mud. w For the pressure of water, P o For the oil pressure, P m For the pressure of the mud, S represents the porosity of the rock. w S represents the water phase saturation. o S represents the oil phase saturation. m q represents the saturation of the mud filtrate phase. wv For water volume source term, q ov For the oil volume source term, q mv The volumetric source term for mud filtrate is the mass injected per unit time.

[0070] In this embodiment of the invention, the saturation is normalized to 1, and the formula is as follows:

[0071] S w +S o +S m =1.

[0072] In this embodiment of the invention, q wv q ov and q mv All are 0.

[0073] Step 2: Based on the aqueous phase formula, oil phase formula, and mud filtrate phase formula from Step 1, divide the computational domain into a differential grid to obtain a finite number of grid nodes, and replace the continuous solution domain with the finite number of grid nodes.

[0074] In this embodiment of the invention, the finite difference method is used for calculation. The finite difference method uses Taylor series expansion and other methods to discretize the derivatives in the governing equations (such as seepage partial differential equations) in the form of the difference quotients of function values ​​on the grid nodes. Combined with the initial conditions and boundary conditions, a system of algebraic equations with the values ​​on the grid nodes as unknowns is established.

[0075] In this embodiment of the invention, the initial conditions and boundary conditions are as follows:

[0076] P r | t＝0 =P0, P r | r＝r0 =P d ,

[0077]

[0078]

[0079] In the formula, r0 is the wellbore radius, r eWhere P is the outer boundary radius, P0 is the formation fluid pressure, and P d For wellbore pressure, S w0 S represents the initial water saturation of the formation. o0 S represents the initial oil saturation. m0 This represents the initial mud saturation.

[0080] Step 3: Based on the solution domain in Step 2, calculate and obtain the saturation and the corresponding time step.

[0081] In this embodiment of the invention, the aqueous phase formula, the oil phase formula, and the mud filtrate phase formula are added together to obtain:

[0082]

[0083] Discretized along the radial radius r, the resulting sequence is shown below:

[0084] {r0=r0,r1,…,r j-1 r j r j+1 , ..., r N-1 r N After performing the transformation x = ln(r) - ln(r0), we obtain an equally spaced monotonically increasing sequence on the variable x.

[0085] In this embodiment of the invention, the unknowns that need to be solved include: pressure P and water phase saturation. oil phase saturation and mud filtrate phase saturation

[0086] The sequence of pressure P is:

[0087]

[0088] water phase saturation The sequence is:

[0089]

[0090] When n = 0,

[0091] oil phase saturation The sequence is:

[0092]

[0093] When n = 0,

[0094] Saturation of mud filtrate phase The sequence is:

[0095]

[0096] In this embodiment of the invention, step three specifically includes:

[0097] Step S1: Establish a system of algebraic equations with the values ​​at the grid nodes as unknowns, and calculate the saturation in the j-th cell, where j is a positive integer.

[0098] In this embodiment of the invention, the saturation in the j-th cell includes the water phase saturation. oil phase saturation and mud filtrate phase saturation

[0099] water phase saturation oil phase saturation and mud filtrate phase saturation The formulas are as follows:

[0100]

[0101] in, Let be the slope of the water phase saturation in the j-th cell as a function of time; Let be the slope of the oil phase saturation in the j-th cell as a function of time; Let Δt be the slope of the mud filtrate phase saturation in the j-th cell as a function of time. j Let j be the j-th time step.

[0102] In this embodiment of the invention, the slope The formula is:

[0103]

[0104] Where i is w, o, or m; n represents time, ΔQ Lj πH(r1) represents the volume increment of fluid L in the j-th cell per unit time; 2 -r0 2 Let ) be the volume of the j-th cell; Total porosity.

[0105] In this embodiment of the invention, the slope It is a function of saturation and follows the upstream weighting method.

[0106] In this embodiment of the invention, the relative permeability value is relatively complex for multiphase flow. Relative permeability is not only a function of saturation, but also related to the flow, and is a function of both space and time.

[0107] The so-called relative permeability upstream weight method is: the relative permeability of a grid node is calculated from the saturation value of the upstream edge of the flow at that node, and the formula is:

[0108]

[0109] The upstream rights method is crucial for handling the intrusion of mud filtrate into the formation.

[0110] Step S2: Based on the saturation in the j-th cell in step S1, obtain the j-th time step corresponding to the saturation in the j-th cell, take the saturation in the (j+1)-th cell as the saturation in the j-th cell, and continue to execute the steps of establishing a system of algebraic equations with the values ​​on the grid nodes as unknowns, and calculating and obtaining the saturation in the j-th cell.

[0111] Figure 2 This is a schematic diagram of saturation changes provided in an embodiment of the present invention, such as... Figure 2 As shown, the horizontal axis t represents time, and the vertical axis S represents saturation. The target value for saturation. This is the calculated value for saturation. Figure 2 The diagram illustrates the change in saturation with time t, and the risks associated with large step sizes after linearization.

[0112] In this embodiment of the invention, the j-th time step Δt j The formula is:

[0113]

[0114] Among them, F j This is the weight value.

[0115] In this embodiment of the invention, different weight values ​​can be selected according to different numerical simulations. For example, when performing a numerical simulation of mud intrusion, F j =1.

[0116] In this embodiment of the invention, after each pressure calculation, the time step Δt is MT times. j = Δt / MT to calculate That is, adaptive time step Δt j The time step adapts to changes in radius to ensure the simulation can proceed smoothly. By solving the problem through programming, accurate simulation results can be obtained.

[0117] In this embodiment of the invention, each step can be performed by an electronic device. For example, electronic devices include, but are not limited to, tablet computers, portable PCs, and desktop PCs.

[0118] In embodiments of the present invention, such as Figure 3 As shown, using Indicates r wThe inner surface of the arc, i.e., the wellbore. Because the pressure inside the well is high when the mud filtrate enters, it is the upstream of the flow; the wellbore is defined as cell 0, and the saturation in cell 0 is:

[0119]

[0120] According to the upstream weights method, the relative permeability of the wellbore is calculated using the saturation in cell 0, yielding:

[0121]

[0122] Only by considering the aforementioned relative permeability can the expression of the wellbore intrusion term of mud filtrate in the discrete equations be effectively handled.

[0123] In this embodiment of the invention, the mud filtrate intrusion term is expressed in the discrete equation as follows:

[0124] From the first unit ( Figure 3 (The shadow overlay) begins the deduction.

[0125] The radius of the flow per unit time is r0 = r w Quality of the well wall arc surface:

[0126]

[0127]

[0128]

[0129] because So Q w0 =0; because So Q o0 =0. Q m0 This refers to the mass of mud filtrate that intrudes per unit time.

[0130] In embodiments of the present invention, such as Figure 4 As shown, in cylindrical coordinates, the differential equation is:

[0131]

[0132] The proof of the above equation is as follows:

[0133]

[0134] Similarly, it can be proven that:

[0135]

[0136] The mass increment in the j-th cell translates into changes in saturation, volume, and density. From the differential equation of pressure, we can obtain:

[0137] The differential separation equation for the aqueous phase is:

[0138]

[0139] The differential separation equation for the oil phase is:

[0140]

[0141] The differential dispersion equation for the mud filtrate phase is:

[0142]

[0143] From t n to t n+1 The increase in water volume per unit time and unit volume. After discretization, from t n to t n+1 The increase in water volume caused by the change in saturation per unit time, i.e.:

[0144]

[0145] From t n to t n+1 The increase in water volume per unit time due to the compression of pore volume in the rock skeleton Right now:

[0146]

[0147] From t n to t n+1 The increase in water volume per unit time due to fluid compression, i.e.:

[0148]

[0149] In this embodiment of the invention, the difference discretization starts from the above equation, discretizes over time t, and from t n to t n+1 Within a time interval; discrete with respect to radius r, from r j-1 to r j ;get:

[0150]

[0151] Right now:

[0152]

[0153] Therefore, we can conclude that:

[0154]

[0155]

[0156]

[0157] Using S w +S o +S m =1, then we have:

[0158]

[0159]

[0160] Multiply both sides of the above equation by and ρ w ρ o and ρ m If we treat it as a constant, then we get:

[0161]

[0162] The left side represents the (inflow volume - outflow volume) ΔQ of the j-th cell. wj +ΔQ oj +ΔQ mj For the total volume V of the unit j The ratio:

[0163]

[0164] Perform a logarithmic transformation along the radial direction: r = r w e x After further discretization, the volume increment of the j-th cell (inflow - outflow) is: ΔQ wj ΔQ oj and ΔQ mj They are respectively:

[0165]

[0166] Volume of the j-th cell From the above formula, we get:

[0167]

[0168]

[0169] P j n+1 Move the term to the left side of the equation, P j n The right side of the equation. The Δt here still uses... To estimate.

[0170] In this embodiment of the invention, the formula for saturation can be obtained from the above formula as follows:

[0171]

[0172]

[0173]

[0174] After deformation and arrangement, we get:

[0175]

[0176] From the above formula, we can get:

[0177]

[0178] The above formula is the calculation formula for each saturation.

[0179] In the embodiment of the present invention, as Figure 5 shown, the experimental result is the result obtained without adopting self - adaptation, and as Figure 6 shown, the experimental result is the result obtained by adopting self - adaptation. From Figure 5 it can be seen that when there is no self - adaptation time, the three phases of water phase, oil phase and mud filtrate phase quickly reach equilibrium, and the invaded radius is short. Even if the invasion time is increased, the invasion proceeds very fast and does not truly reflect the real situation of invasion; Figure 6 Compared with Figure 5 which also has an invasion time of 5 days, from Figure 6 it can be seen that the invasion proceeds relatively slowly, and clearly shows the flushed zone and invaded annulus of the invasion. The flushed zone is the relatively flat section of the water - phase curve at the beginning, and the invaded annulus is the bulging section of the oil - phase curve. Figure 6 The result in

[0180] Figure 7 is the schematic diagram of the numerical simulation self - adaptation time step device provided by the embodiment of the present invention. As Figure 7 shown, the device includes: acquisition module 1, node module 2 and calculation module 3.

[0181] The acquisition module 1 is connected to the node module 2, and the node module 2 is connected to the calculation module 3.

[0182] The acquisition module 1 is used to establish a seepage model of mud filtrate invading the reservoir. In the radial one - dimensional cylindrical coordinate system, the water phase, oil phase and mud filtrate phase are respectively calculated by the mass continuity equation to obtain the water - phase formula, oil - phase formula and mud filtrate - phase formula; the node module 2 is used to divide the calculation area into differential grids according to the water - phase formula, oil - phase formula and mud filtrate - phase formula, obtain a finite number of grid nodes, and replace the continuous solution domain with the finite number of grid nodes; the calculation module 3 is used to calculate and obtain the saturation and the time step corresponding to the saturation.

[0183] In an embodiment of the present invention, the calculation module 3 is specifically configured to establish an algebraic equation system with the values at grid nodes as unknowns according to the solution domain, and calculate and obtain the saturation in the j-th cell, where j is a positive integer; obtain the j-th time step corresponding to the saturation in the j-th cell according to the saturation in the j-th cell, and use the saturation in the (j + 1)-th cell as the saturation in the j-th cell, and continue to execute the steps of establishing an algebraic equation system with the values at grid nodes as unknowns according to the solution domain and calculating and obtaining the saturation in the j-th cell.

[0184] In the technical solution of the operator compilation device provided by the present invention, the method includes establishing a seepage model of mud filtrate invading the reservoir. In a radial one-dimensional cylindrical coordinate system, the mass continuity equation is used to perform a constant calculation on the aqueous phase, oil phase, and mud filtrate phase respectively to obtain the aqueous phase formula, oil phase formula, and mud filtrate phase formula; according to the aqueous phase formula, oil phase formula, and mud filtrate phase formula, the calculation area is divided into differential grids to obtain a finite number of grid nodes, and the continuous solution domain is replaced by the finite number of grid nodes; according to the solution domain, calculate and obtain the saturation and the time step corresponding to the saturation. In the deduction of the numerical simulation of mud invasion, based on mass conservation, a reasonable result is obtained for the numerical simulation of mud invasion, and a reasonable invasion time step is set. Moreover, the change of saturation with the invasion radius can clearly reflect the invasion annulus, and the change relationship between saturation and invasion time, invasion radius, etc. is determined. The present invention solves the problem of reasonable value selection of the time step in the existing mud invasion simulation, and further determines the rationality of the mud invasion simulation result.

[0185] An embodiment of the present invention provides a computer-readable storage medium. The computer-readable storage medium includes a stored program. When the program runs, it controls the electronic device where the computer-readable storage medium is located to execute the embodiment of the above numerical simulation adaptive time step method.

[0186] Figure 8 It is a schematic diagram of an electronic device provided by an embodiment of the present invention. As Figure 8 shown, the electronic device 21 includes: a processor 211, a memory 212, and a computer program 213 stored in the memory 212 and executable on the processor 211. When the computer program 213 is executed by the processor 211, it implements the numerical simulation adaptive time step method in the embodiment. To avoid repetition, it will not be elaborated here one by one.

[0187] The electronic device 21 includes, but is not limited to, a processor 211 and a memory 212. Those skilled in the art can understand that Figure 8This is only an example of the electronic device 21, which does not constitute a limitation on the electronic device 21. It may include more or fewer components than those shown in the figure, or combine some components, or different components. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0188] The so-called processor 211 may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, or the processor may also be any conventional processor, etc.

[0189] The memory 212 may be an internal storage unit of the electronic device 21, such as the hard disk or memory of the electronic device 21. The memory 212 may also be an external storage device of the electronic device 21, such as a plug-in hard disk equipped on the electronic device 21, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory 212 may also include both the internal storage unit and the external storage device of the electronic device 21. The memory 212 is used to store computer programs and other programs and data required by the network device. The memory 212 may also be used to temporarily store data that has been output or will be output.

[0190] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0191] The above are only the preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A numerical simulation adaptive time step method, characterized in that, The method includes: Step 1: Establish a seepage model for mud filtrate intrusion into the reservoir. In a radial one-dimensional cylindrical coordinate system, perform constant calculations on the aqueous phase, oil phase, and mud filtrate phase using the mass continuity equation to obtain the aqueous phase formula, oil phase formula, and mud filtrate phase formula. Step 2: Based on the aqueous phase formula, oil phase formula, and mud filtrate phase formula in Step 1, the computational domain is divided into a differential grid to obtain a finite number of grid nodes, and the continuous solution domain is replaced by the finite number of grid nodes. Step 3: Based on the solution domain in Step 2, calculate and obtain the saturation and the time step corresponding to the saturation; Step three includes: Step S1: Establish a system of algebraic equations with the values ​​at the grid nodes as unknowns, and calculate the saturation in the j-th cell, where j is a positive integer; Step S2: Based on the saturation in the j-th cell in step S1, obtain the j-th time step corresponding to the saturation in the j-th cell, take the saturation in the (j+1)-th cell as the saturation in the j-th cell, and continue to execute the steps of establishing a system of algebraic equations with the values ​​on the grid nodes as unknowns, and calculating and obtaining the saturation in the j-th cell.

2. The method according to claim 1, characterized in that, The aqueous phase formula is: ； The oil phase formula is: ； The formula for the mud filtrate phase is: ； in, For the radius of invasion, The density of water, The density of the oil, The density of the mud. For absolute penetration rate, The relative permeability of water. The relative permeability of oil. The relative permeability of the mud. For the pressure of water, For the pressure of oil, For the pressure of the mud, Porosity of the rock For water phase saturation, For oil phase saturation, The saturation of the mud filtrate phase. For water volume source items, For oil volume source term, This is the volume source term for mud filtrate.

3. The method according to claim 1, characterized in that, The saturation in the j-th cell includes water phase saturation. Oil phase saturation and mud filtrate phase saturation ; The water phase saturation The oil phase saturation and the saturation of the mud filtrate phase The formulas are as follows: in, Let be the slope of the water phase saturation in the j-th cell as a function of time; Let be the slope of the oil phase saturation in the j-th cell as a function of time. Let be the slope of the change in the saturation of the mud filtrate phase in the j-th cell over time; Let j be the j-th time step.

4. The method according to claim 3, characterized in that, The slope The formula is: ； Where i represents w, o, or m; n represents time. This represents the volume increment of fluid L in the j-th cell per unit time. Let J be the volume of the j-th cell; Porosity of the rock.

5. The method according to claim 3, characterized in that, The j-th time step The formula is: 0.001F j / ； Among them, F j This is the weight value.

6. A numerical simulation adaptive time step device, characterized in that, The apparatus is used to implement the numerical simulation adaptive time step method according to claim 1, and the apparatus includes: The acquisition module is used to establish a seepage model of mud filtrate intruding into the reservoir. In a radial one-dimensional cylindrical coordinate system, the mass continuity equation is used to perform constant calculations on the aqueous phase, oil phase, and mud filtrate phase respectively to obtain the aqueous phase formula, oil phase formula, and mud filtrate phase formula. The node module is used to divide the computational domain into a differential grid based on the aqueous phase formula, the oil phase formula, and the mud filtrate phase formula, thereby obtaining a finite number of grid nodes, and using the finite number of these grid nodes to replace the continuous solution domain. The calculation module is used to calculate and obtain the saturation and the time step corresponding to the saturation based on the solution domain; The computing module includes: The calculation submodule is used to establish a system of algebraic equations with the values ​​at the grid nodes as unknowns, and to calculate the saturation in the j-th cell, where j is a positive integer; The acquisition submodule is used to obtain the j-th time step corresponding to the saturation in the j-th cell based on the saturation in the j-th cell, take the saturation in the (j+1)-th cell as the saturation in the j-th cell, and trigger the calculation submodule to continue to execute the steps of establishing a system of algebraic equations with the values ​​on the grid nodes as unknowns, and calculating and obtaining the saturation in the j-th cell.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the numerical simulation adaptive time step method according to any one of claims 1 to 5.

8. An electronic device, characterized in that, include: One or more processors; Memory; And one or more computer programs, wherein the one or more computer programs are stored in the memory, the one or more computer programs including instructions that, when executed by the device, cause the device to perform the numerical simulation adaptive time step method according to any one of claims 1 to 5.

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