A method and system for simulating interwell oil-water dynamics in a water-drive reservoir

Abstract

This invention relates to a method and system for simulating the dynamic oil-water flow between wells in water-drive reservoirs. The method comprises: equating the reservoir seepage system to be simulated to an inter-well connectivity network composed of connectivity conductivity and connectivity volume, and constructing an inter-well connectivity model of the reservoir seepage system; determining the inter-well flow distribution and pressure distribution of the established inter-well connectivity model; and using the discontinuous Galerkin method to calculate the saturation of the established inter-well connectivity model to determine the dynamic data of the reservoir seepage system to be simulated. This invention can be widely applied in the field of dynamic oil-water simulation in water-drive reservoirs.

Description

Technical Field

[0001] This invention relates to the field of oil-water dynamic simulation in water-drive reservoirs, and in particular to a method and system for simulating oil-water dynamics between wells in water-drive reservoirs. Background Technology

[0002] Unlike finite difference classification methods, a new class of finite element methods has emerged in recent years. These methods have the advantage of being able to arbitrarily extend the computational accuracy of the algorithm. The discontinuous Galerkin method (DGM) is one of the most representative methods. This method was first applied to solving hyperbolic conservation law differential equations by using different approximation functions on each discrete element of the solution domain to obtain the numerical solution of the equation.

[0003] Existing technology discloses an INSIM (Information-Driven Simulation) data-driven prediction model based on connected units, which can simulate and calculate the oil-water dynamics of water-drive reservoirs. However, when using the finite difference method to solve for water saturation on connected units, the accuracy of the calculation results is insufficient for reservoirs with complex characteristics, resulting in inaccurate oil-water dynamics calculation results and affecting the effectiveness of historical fitting and future prediction of production dynamics. Summary of the Invention

[0004] To address the above problems, the purpose of this invention is to provide a method and system for simulating the dynamic oil-water relationship between wells in water-drive oil reservoirs with high accuracy in calculation results.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: Firstly, it provides a method for simulating the dynamic oil-water relationship between wells in a water-drive reservoir, comprising:

[0006] The reservoir seepage system to be simulated is equivalent to an inter-well connectivity network composed of connectivity conductivity and connectivity volume, and an inter-well connectivity model of the reservoir seepage system to be simulated is constructed.

[0007] The discontinuous Galerkin method was used to calculate the saturation of the established inter-well connectivity model and determine the dynamic data of the seepage system of the reservoir to be simulated.

[0008] Furthermore, the well connectivity model is established under the following conditions: considering only the oil-water two-phase flow and ignoring the influence of temperature, neglecting gravity and keeping the viscosity constant.

[0009] Furthermore, the discontinuous Galerkin method is used to calculate the saturation of the established inter-well connectivity model and determine the dynamic data of the reservoir seepage system to be simulated, including:

[0010] The discontinuous Galerkin method was used to calculate the saturation of the established well connectivity model and obtain the water cut information of the seepage system of the reservoir to be simulated.

[0011] Based on the water cut information of the seepage system of the reservoir to be simulated, the dynamic data of oil production and water production of the seepage system of the reservoir to be simulated are obtained.

[0012] Furthermore, the discontinuous Galerkin method is used to calculate the saturation of the established well connectivity model to obtain the water cut information of the reservoir seepage system to be simulated, including:

[0013] The well connectivity model is divided into multiple units, denoted as η = 1, 2, 3, ..., n. e ;

[0014] Let K be the region containing a certain unit, and let N be the degrees of freedom in K. K The corresponding finite element shape function is φ K,η Then the water saturation function S on K w Estimated as

[0015]

[0016] in, Let be the saturation of the ηth node in cell K; Water saturation S w The finite element estimation function on this element; x is the spatial coordinate on the one-dimensional connected element; t is time;

[0017] For the water-driven oil recovery problem, f(u) = f w (S w ), f(u) is a general abstract function, S w It is the independent variable, f w It is a function, f, representing the water cut information of the seepage system in the reservoir to be simulated. w This is a function used to calculate the water saturation.

[0018] Furthermore, a stability condition for the discontinuous Galerkin method is:

[0019]

[0020] Another stability condition is:

[0021]

[0022] Where, Δt max η is the maximum allowed time step when calculating saturation; η is the number of cells partitioned in the well connectivity model; Δt ηΔx is the allowable time step corresponding to the ηth element; Δx is the spatial step size on the connected elements when calculating water saturation; φ is the porosity of the connected elements; S w,2η-1 S w,2η+1 f represents the water saturation values ​​at the left and right ends of the ηth unit; w,2η-1 f w,2η+1 denoted as , where is the water content value corresponding to the water saturation values ​​at the left and right ends of the ηth unit; v is the velocity.

[0023] Furthermore, the method also includes:

[0024] Determine the flow and pressure distribution between wells in the established well connectivity model.

[0025] Furthermore, the determination of the inter-well flow rate distribution and pressure distribution in the established inter-well connectivity model includes:

[0026] The connected volume V of well i in the model simulating the inter-well connectivity of the reservoir seepage system. ik Establish a mass balance equation for the object;

[0027] The mass balance equation is rewritten using an implicit difference scheme to obtain a difference scheme for the mass balance equation.

[0028] Based on the difference scheme of the mass balance equation and the well point mobility value, the inter-well mobility value of well i and well j in layer k at time n is calculated.

[0029] Based on the flow velocity, drainage volume, and overall compressibility coefficient of each well in the reservoir seepage system to be simulated, the pressure expressions for each well at time n and time n-1 in the reservoir seepage system to be simulated are determined.

[0030] Based on the pressure expressions of each well in the seepage system of the reservoir to be simulated at time n and time n-1, the average pressure value of the single well control area of ​​each well in the seepage system of the reservoir to be simulated at any time is calculated.

[0031] Based on the average pressure value of the single-well control area of ​​each well in the reservoir seepage system to be simulated at any time and the calculated connectivity conductivity T i,j The flow velocity between well i and well j at time n in the k-th layer was calculated within the well connectivity model.

[0032] Secondly, a dynamic oil-water simulation system for water-drive reservoirs is provided, comprising:

[0033] The model building module is used to convert the reservoir seepage system to be simulated into an inter-well connectivity network composed of connectivity conductivity and connectivity volume, and to build an inter-well connectivity model of the reservoir seepage system to be simulated.

[0034] The saturation calculation module is used to calculate the saturation of the established well connectivity model using the discontinuous Galerkin method, and to determine the dynamic data of the seepage system of the reservoir to be simulated.

[0035] Thirdly, a processing device is provided, including computer program instructions, wherein when the computer program instructions are executed by the processing device, they are used to implement the steps corresponding to the above-mentioned water-drive reservoir well dynamic simulation method.

[0036] Fourthly, a computer-readable storage medium is provided, wherein computer program instructions are stored on the computer-readable storage medium, wherein the computer program instructions, when executed by a processor, are used to implement the steps corresponding to the above-described method for dynamic simulation of oil-water dynamics between wells in water-drive reservoirs.

[0037] The present invention has the following advantages due to the adoption of the above technical solutions:

[0038] 1. This invention can effectively improve the accuracy of solving water saturation on connected units in the method for simulating oil-water dynamics between wells in water-drive reservoirs, thereby simulating and calculating oil-water production dynamics more accurately.

[0039] 2. This invention can more accurately predict the distribution of remaining oil, and can improve the effect of historical fitting of production dynamics and future prediction of production dynamics.

[0040] In summary, this invention can be widely applied in the field of oil-water dynamic simulation of water-drive reservoirs. Attached Figure Description

[0041] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. In the drawings:

[0042] Figure 1 This is a schematic diagram of the structure of an inter-well connectivity model provided in an embodiment of the present invention;

[0043] Figure 2 This is a schematic diagram of a one-dimensional reservoir model provided in Example 1 of an embodiment of the present invention;

[0044] Figure 3 This is a comparative diagram showing the water content calculation results for a flow rate of 10 cubic meters per day in Example 1 provided by an embodiment of the present invention. Figure 3 (a) shows the water content calculation results using the finite difference method. Figure 3 (b) The moisture content calculation results using the method of the present invention;

[0045] Figure 4This is a comparative diagram showing the water content calculation results for a flow rate of 20 cubic meters per day in Example 1 provided by an embodiment of the present invention. Figure 4 (a) shows the water content calculation results using the finite difference method. Figure 4 (b) The moisture content calculation results using the method of the present invention;

[0046] Figure 5 This is a comparative diagram showing the water content calculation results for a flow rate of 30 cubic meters per day in Example 1 provided by an embodiment of the present invention. Figure 5 (a) shows the water content calculation results using the finite difference method. Figure 5 (b) The moisture content calculation results using the method of the present invention;

[0047] Figure 6 This is a comparative diagram showing the water content calculation results for a flow rate of 40 cubic meters per day in Example 1 provided by an embodiment of the present invention. Figure 6 (a) shows the water content calculation results using the finite difference method. Figure 6 (b) The moisture content calculation results using the method of the present invention;

[0048] Figure 7 This is a comparative diagram showing the water content calculation results for a flow rate of 500 cubic meters per day in Example 1 provided by an embodiment of the present invention. Figure 7 (a) shows the water content calculation results using the finite difference method. Figure 7 (b) The moisture content calculation results using the method of the present invention;

[0049] Figure 8 This is a schematic diagram of the "T"-shaped model of Example 2 provided in an embodiment of the present invention;

[0050] Figure 9 This is a schematic diagram of the moisture content calculation results for Example 2 provided in an embodiment of the present invention, wherein, Figure 9 (a) The water cut calculation results for production well W4 using the finite difference method. Figure 9 (b) is the water cut calculation result of production well W4 using the method of the present invention. Detailed Implementation

[0051] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the invention and to fully convey the scope of the invention to those skilled in the art.

[0052] It should be understood that the terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” as used herein may also include the plural forms. The terms “comprising,” “including,” “containing,” and “having” are inclusive and therefore indicate the presence of the stated features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or combinations thereof. The method steps, processes, and operations described herein are not construed as requiring them to be performed in a particular order described or illustrated unless the order of performance is explicitly indicated. It should also be understood that additional or alternative steps may be used.

[0053] Although terms such as first, second, third, etc., may be used in this document to describe multiple elements, components, regions, layers, and / or segments, these elements, components, regions, layers, and / or segments should not be limited by these terms. These terms may be used only to distinguish one element, component, region, layer, or segment from another. Unless the context clearly indicates otherwise, terms such as "first," "second," and other numerical terms used herein do not imply order or sequence. Therefore, the first element, component, region, layer, or segment discussed below may be referred to as the second element, component, region, layer, or segment without departing from the teachings of the exemplary embodiments.

[0054] The method and system for simulating the dynamic oil-water flow between wells in water-drive reservoirs provided in this invention use the discontinuous Galerkin method to solve reservoir seepage problems. Through numerical examples, it is shown that the discontinuous Galerkin method can obtain more accurate results than the finite difference method.

[0055] Example 1

[0056] This embodiment provides a method for simulating the dynamic oil-water relationship between wells in a water-drive reservoir, including the following steps:

[0057] 1) The reservoir seepage system to be simulated is equivalent to an inter-well connectivity network composed of connectivity conductivity and connectivity volume. The inter-well connectivity model of the reservoir seepage system to be simulated, namely the INSIM model, is constructed. This model is composed of several one-dimensional connectivity units.

[0058] Specifically, the INSIM model, a publicly available data-driven prediction model based on connected units, is used to represent the reservoir seepage system to be simulated as an inter-well connectivity network composed of connectivity conductivity and connectivity volume. Then, using dynamic well point data and the principle of mass balance front tracking, the traditional grid-centered three-dimensional flow is transformed into a semi-analytical flow solution of a series of one-dimensional interconnected networks between wells. This increases the calculation speed by hundreds or thousands of times compared to traditional numerical simulations. The INSIM model simplifies the complex reservoir injection and production system into a system composed of connectivity conductivity T... i,j and connected volume V P,i,j Two characteristic parameters characterize a one-dimensional connected unit, such as Figure 1 As shown in the figure, the control region of the initial interconnected volume between wells is the dashed elliptical region, the well points are the columnar bodies in the figure, and the initial conductivity between wells is the gray elliptical region.

[0059] Specifically, the INSIM model is established under the following conditions: considering only the two-phase flow of oil and water and ignoring the effect of temperature, neglecting gravity and keeping the viscosity constant.

[0060] 2) Determine the inter-well flow and pressure distributions in the established inter-well connectivity model, specifically:

[0061] 2.1) The connected volume V of well i in the well connectivity model of the reservoir seepage system to be simulated. ik Establish a mass balance equation for the object.

[0062] Specifically, based on the conditions for establishing the INSIM model, the connected volume V of well i in the reservoir seepage system to be simulated is... ik Establish a mass balance equation for the object:

[0063]

[0064] In the formula, N l N represents the reservoir layer number; k represents the layer number; i and j represent the well numbers; N w T represents the number of injection and production wells; t represents the production time in days; T ijk The average connectivity conductivity between layer k, well i, and well j is expressed in m. 3 ·d -1 ·MPa -1 ;p i and p j q represents the average pressure of wells i and j in the drainage area, in MPa; i Let i be the flow rate of well i, where injection is positive and production is negative, and the unit is m. 3 / d;V ik Let represent the oil drainage volume of well i in layer k. Here, it can be approximated as half the volume of its connection with the surrounding connected unit cells, in meters.3 C tk The comprehensive compressibility coefficient of the k-th reservoir is given in MPa. -1 .

[0065] 2.2) The mass balance equation is rewritten using an implicit difference scheme to obtain the difference scheme of the mass balance equation:

[0066]

[0067] in:

[0068]

[0069]

[0070]

[0071] In the formula, These represent the conductivity values ​​between well i and well j in layer k at the start time and time n, respectively, in m. 3 ·d -1 ·MPa -1 ; Let A be the overall compressibility coefficient of the reservoir in the k-th layer at time k; ijk and L ijk These represent the average seepage cross-sectional area and well distance between wells i and j in the k-th layer, respectively, in meters. 2 and m; These are the inter-well mobility values ​​of well i and well j in layer k at the start time and time n-1, respectively, in units of 10. -3 μm 2 ·(mPa·s) -1 ; These are the connected volumes of wells i and j in layer k at the start time and time n, respectively, in meters. 3 C rk C ok and C wk , respectively, are the compressibility coefficients of the k-th reservoir rock, reservoir crude oil, and reservoir water, in MPa. -1 S wik S oik These represent the water saturation and oil saturation at well i in layer k, respectively. and denoted as , where are the average pressures of wells i and j in the oil draining zone at time n.

[0072] 2.3) Based on the difference scheme of the mass balance equation and the well point mobility value, calculate the inter-well mobility value of well i and well j in layer k at time n.

[0073] Specifically, by combining the above formulas (2) to (5) with the wellpoint mobility values, the inter-well mobility values ​​of well i and well j in layer k at time n can be calculated.

[0074]

[0075] In the formula, K ijk The average permeability between well i and well j in layer k is expressed in units of 10. -3 μm 2 ;λ ik , λ jk These are the fluid mobility values ​​of wells i and j in layer k, respectively, in units of 10. -3 μm 2 ·(mPa·s) -1 ;k ro k rw These represent the relative permeability values ​​of formation crude oil and formation water, respectively; S wik S wjk These represent the water saturation values ​​at wells i and j in the k-th layer, respectively; u ok u wk These are the viscosity values ​​of crude oil and formation water in the k-th formation, respectively, in mPa·s.

[0076] 2.4) Based on the flow velocity, drainage volume, and overall compressibility coefficient of each well in the simulated reservoir seepage system, determine the pressure expressions for each well at time n and time n-1 in the simulated reservoir seepage system:

[0077]

[0078] Among them, E i G i M i The coefficients of the simplified terms are denoted as:

[0079]

[0080]

[0081]

[0082] In the formula, Δt n The time step size for the nth time step; The coefficient for the simplified term is denoted as...

[0083] 2.5) Based on the pressure expressions (7) of each well in the seepage system of the reservoir to be simulated at time n and time n-1, calculate the average pressure value of the single well control area of ​​each well in the seepage system of the reservoir to be simulated at any time.

[0084] Specifically, the pressure expression (7) represents N w By combining several linear equations, the average pressure value of the single-well control area of ​​each well in the simulated reservoir seepage system at any time can be calculated directly using the linear equation solution algorithm.

[0085] 2.6) Based on the average pressure value of the single-well control area of ​​each well in the seepage system of the reservoir to be simulated at any time and the calculated connectivity conductivity T i,j Calculate the flow velocity between well i and well j at time n in the k-th layer within the well connectivity model.

[0086]

[0087] Specifically, in obtaining the well connectivity model, the well flow distribution and pressure distribution (i.e., After obtaining the average pressure value, the next step is to calculate the saturation. Once the saturation is obtained, the water content information can be obtained, and then the dynamics of oil production and water production can be calculated.

[0088] 3) Using the discontinuous Galerkin method, saturation calculations are performed on the established inter-well connectivity model to obtain the water cut information of the seepage system of the reservoir to be simulated, and then dynamic data such as oil production and water production of the seepage system of the reservoir to be simulated are obtained, specifically:

[0089] 3.1) Using the discontinuous Galerkin method, the saturation of the established well connectivity model is calculated to obtain the water cut information f of the seepage system of the reservoir to be simulated. w Among them, the water cut information f of the reservoir seepage system to be simulated w This is a function used to calculate the water saturation.

[0090] Specifically, this embodiment uses a one-dimensional oil-water two-phase method as an example to illustrate the discontinuous Galerkin method:

[0091] The computational domain of the well connectivity model, i.e., the one-dimensional connected unit, is divided into multiple units, denoted as η = 1, 2, 3, ..., n. e .

[0092] Let K be the region containing a certain unit, and let N be the degrees of freedom (number of nodes) in K. K The corresponding finite element shape function is φ K,η Then the water saturation function S on K w Estimated as

[0093]

[0094] in, Let be the saturation of the ηth node in cell K; Water saturation S w The finite element estimation function on this element; x is the spatial coordinate on the one-dimensional connected element; t is time.

[0095] When capillary forces and compressibility are ignored, the one-dimensional water-driven oil displacement equation is:

[0096]

[0097] but:

[0098]

[0099] Among them, S w f represents water saturation. w v represents moisture content; x φ represents the total two-phase flow velocity on a one-dimensional connected unit; A represents the cross-sectional area of ​​the connected unit; and φ represents the porosity of the connected unit.

[0100] For the water-driven oil recovery problem, f(u) = f w (S w In the formula, in the two-dimensional case, v = (v x ,v y ), v y Let v be the component of velocity in the y-direction; in the one-dimensional case, v = v x In this context, f(u) is a general abstract function, u is the independent variable, and f is a function that, in the specific problem of water-driven oil recovery, represents f. w (S w This specific function, that is, S at this time w It is the independent variable, f w It is a function.

[0101] ∫ θK The discretization of [vf(u)]·ndx requires distinguishing between inflow and outflow boundaries:

[0102] K in ={x∈K|v·n<0},K out ={x∈K|v·n≥0} (15)

[0103]

[0104] Among them, K in K is the inflow boundary of unit K; out For the outflow boundary of unit K; f(S) w in f(S) represents the water content corresponding to the degree of freedom of water saturation within unit K; w out ) represents the water content corresponding to the degree of freedom of water saturation outside unit K.

[0105] For the one-dimensional water-driven oil displacement problem:

[0106]

[0107] in, φ is the moisture content at the ηth node in unit K at time step n; K,ξ Let ξ be the finite element shape function at the ξ-th node of element K.

[0108] The above formula (17) can be simplified as follows:

[0109]

[0110] in, The vector representing the degrees of freedom of water saturation within cell K; The vector represents the degrees of freedom of water saturation outside unit K.

[0111] According to the Euler forward scheme, we get:

[0112]

[0113] in, Let n be the degrees of freedom for water saturation in cell K at time step n.

[0114] Right now:

[0115]

[0116] For the above solution, a slope limiter is needed to reconstruct the solution to avoid oscillations. Let K be the region containing the ηth cell. η If a cell contains only the left and right endpoints, then we can obtain:

[0117]

[0118]

[0119]

[0120]

[0121]

[0122]

[0123]

[0124]

[0125] Au K =b (29)

[0126] and:

[0127]

[0128]

[0129]

[0130]

[0131]

[0132] Specifically, to ensure the stability of the discontinuous Galerkin method, a simple and effective stability condition is proposed. This condition is the most stringent and applicable to any saturation distribution:

[0133]

[0134] Where, Δt max Δx is the maximum allowed time step when calculating saturation; Δx is the spatial step size on the connecting element when calculating water saturation.

[0135] In addition, a dynamic stability condition is proposed to determine whether to partition the external time step, thereby further improving efficiency:

[0136]

[0137] Where, Δt η S represents the allowable time step for the ηth unit; w,2η-1 S w,2η+1 f represents the water saturation values ​​at the left and right ends of the ηth unit; w,2η-1 f w,2η+1 The water content values ​​are the values ​​corresponding to the water saturation values ​​at the left and right ends of the ηth unit.

[0138] When the saturation at both ends of each unit is similar, the conditions are significantly relaxed; if Δt max If the time step is greater than the external time step, then no partitioning is required.

[0139] 3.2) Based on the water cut information f of the seepage system of the reservoir to be simulated w Dynamic data on oil production and water production of the seepage system of the reservoir to be simulated are obtained.

[0140] Specifically, the oil production dynamics data of the reservoir seepage system to be simulated is q*(1-f w The dynamic water production data of the reservoir seepage system to be simulated is q*f. w , where q is the total flow rate of the two phases.

[0141] The following detailed embodiments illustrate the method for simulating the dynamic oil-water relationship between wells in water-driven oil reservoirs according to the present invention.

[0142] Example 1: One-dimensional reservoir model example

[0143] A one-dimensional reservoir model was established using the commercial numerical simulation software ECLIPSE, such as... Figure 2 As shown, the model has a grid size of 250×1×1, with grid lengths of 2m, 3m, and 5m in the x, y, and z directions, respectively. Other model parameters are shown in Table 1. The model includes one injection well (left end) and one production well (right end). The injection well injects water at a constant rate, and the production well produces liquid at a constant rate. The total production time is set to 300 days, with a time step of 30 days / step, for a total of 10 time steps.

[0144] Table 1: Model Parameter Information

[0145]

[0146]

[0147] To verify the accuracy of the method of the present invention, the water content calculation results of the finite difference method are used for comparison, and different flow rates are used to verify the computational stability of the method of the present invention. In the finite difference method calculation, the water content is calculated when the one-dimensional connection element is divided into 5, 10, 20, and 40 grids. In the method of the present invention, the water content is calculated when the one-dimensional connection element is divided into 5, 10, 20, and 40 nodes. Figures 3 to 7 The comparison of the calculated moisture content results when the flow rates are 10 cubic meters / day, 20 cubic meters / day, 30 cubic meters / day, 40 cubic meters / day and 500 cubic meters / day shows that the calculation results using the method of this invention are in good agreement with the calculation results using the finite difference method, and the method has good stability.

[0148] Example 2: Two-dimensional reservoir model example

[0149] A T-shaped two-dimensional reservoir model was established using the commercial numerical simulation software ECLIPSE, such as... Figure 8As shown, the model has a grid size of 250×125×1, with grid lengths of 2m, 2m, and 50m in the x, y, and z directions, respectively. The grid porosity is 0.2, the grid permeability is 300mD, and the initial water saturation is 0.2. Other parameters are consistent with those in Table 1. The model contains four wells: W1 and W2 are two injection wells, W4 is a production well, and W3 is a virtual well. The total production time is set to 660 days. In the first 360 days, the injection rate of injection wells W1 and W2 is 5 cubic meters per day, and the production rate of production well W4 is 10 cubic meters per day. In the last 300 days, the injection rate of injection wells W1 and W2 is 10 cubic meters per day, and the production rate of production well W4 is 20 cubic meters per day.

[0150] like Figure 9 As shown, Figure 9 (a) shows the water cut calculation results (production well W4) when the finite difference method is used to divide the grid into 5, 10, 20, and 40 grids respectively. Figure 9 (b) shows the water cut calculation results (production well W4) when the method of the present invention is used to split the nodes into 5, 10, 20, and 40. It can be seen that the calculation result using the finite difference method has only one time point at which the water cut of the production well changes abruptly, while the calculation result using the method of the present invention has two time points at which the water cut of the production well changes abruptly. Analysis shows that the injection well W1 is closer to the production well W4, while the injection well W2 is farther away from the production well W4. Water injected through injection well W1 will reach the production well W4 first, while water injected through injection well W2 will reach the production well W4 later. Injection wells W1 and W2 will produce two water drive fronts. Therefore, the calculation result using the method of the present invention has higher accuracy and is more consistent with the actual situation than the calculation result using the finite difference method, verifying the accuracy of the method of the present invention.

[0151] Example 2

[0152] This embodiment provides a water-drive reservoir well dynamic simulation system, including:

[0153] The model building module is used to convert the reservoir seepage system to be simulated into an inter-well connectivity network composed of connectivity conductivity and connectivity volume, and to build an inter-well connectivity model of the reservoir seepage system to be simulated.

[0154] The pressure distribution determination module is used to determine the inter-well flow and pressure distribution in the established inter-well connectivity model.

[0155] The saturation calculation module is used to calculate the saturation of the established well connectivity model using the discontinuous Galerkin method, thereby obtaining the water cut information of the seepage system of the reservoir to be simulated, and then obtaining the dynamic data of the seepage system of the reservoir to be simulated.

[0156] The system provided in this embodiment is used to execute the above-described method embodiments. For specific processes and details, please refer to the above embodiments, which will not be repeated here.

[0157] Example 3

[0158] This embodiment provides a processing device corresponding to the water-drive reservoir well dynamic simulation method provided in Embodiment 1. The processing device can be applied to client processing devices, such as mobile phones, laptops, tablets, desktop computers, etc., to execute the method of Embodiment 1.

[0159] The processing device includes a processor, a memory, a communication interface, and a bus. The processor, memory, and communication interface are connected via the bus to enable communication between them. The memory stores a computer program that can run on the processing device. When the processing device runs the computer program, it executes the water-water dynamic simulation method for water-drive reservoirs provided in Embodiment 1.

[0160] In some implementations, the memory may be high-speed random access memory (RAM), and may also include non-volatile memory, such as at least one disk storage device.

[0161] In other implementations, the processor can be any type of general-purpose processor, such as a central processing unit (CPU) or a digital signal processor (DSP), and there is no limitation here.

[0162] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, and can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0163] Those skilled in the art will understand that the structure of the above-described computing device is only a partial structure related to the solution of this application and does not constitute a limitation on the computing device to which the solution of this application is applied. A specific computing device may include more or fewer components, or combine certain components, or have different component arrangements.

[0164] Example 4

[0165] This embodiment provides a computer program product corresponding to the water-drive reservoir well dynamic simulation method provided in Embodiment 1. The computer program product may include a computer-readable storage medium on which computer-readable program instructions for executing the water-drive reservoir well dynamic simulation method described in Embodiment 1 are loaded.

[0166] A computer-readable storage medium can be a tangible device that holds and stores instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof.

[0167] The computer-readable storage medium provided in the above embodiments has a similar implementation principle and technical effect to the above method embodiments, and will not be described again here.

[0168] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0169] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0170] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0171] The above embodiments are only used to illustrate the present invention. The structure, connection method and manufacturing process of each component can be varied. All equivalent transformations and improvements made on the basis of the technical solution of the present invention should not be excluded from the protection scope of the present invention.

Claims

1. A method of modeling interwell oil and water performance in a water drive reservoir, characterized by, include: The reservoir seepage system to be simulated is equivalent to an inter-well connectivity network composed of connectivity conductivity and connectivity volume, and an inter-well connectivity model of the reservoir seepage system to be simulated is constructed. The intermittent Galerkin method was used to calculate the saturation of the established inter-well connectivity model and determine the dynamic data of the seepage system of the reservoir to be simulated. The discontinuous Galerkin method is used to calculate the saturation of the established inter-well connectivity model and determine the dynamic data of the seepage system of the reservoir to be simulated, including: The discontinuous Galerkin method was used to calculate the saturation of the established well connectivity model and obtain the water cut information of the seepage system of the reservoir to be simulated. Based on the water cut information of the seepage system of the reservoir to be simulated, the oil production dynamic data and water production dynamic data of the seepage system of the reservoir to be simulated are obtained. The discontinuous Galerkin method is used to calculate the saturation of the established inter-well connectivity model, obtaining the water cut information of the seepage system of the reservoir to be simulated, including: The interwell connectivity model is divided into a plurality of cells, denoted as ; Let the region where a certain element is located be , the degree of freedom in be , and the corresponding finite element shape function be , then the water saturation function on is estimated as in, For unit The Middle The saturation of each node; Water saturation Finite element estimation function on this element; These are the spatial coordinates on a one-dimensional connected unit. For time; Regarding the water-driven oil recovery problem , It is a general abstract function. It is the independent variable. It is a function representing the water cut information of the reservoir seepage system to be simulated. This is a function used to calculate the water saturation. in, As the independent variable; in the two-dimensional case , For speed in Components of direction; in the one-dimensional case , The total velocity of the two phases on a one-dimensional connected unit; For unit The inflow boundary; For unit The outflow boundary; for Time step in unit No. Moisture content values ​​at each node; For unit The Finite element shape functions at each node; The above solution needs to be reconstructed using a slope limiter; One stability condition for the discontinuous Galerkin method is: In addition, a dynamic stability condition is proposed to determine whether to partition the external time step: in, This represents the maximum allowed time step when calculating saturation. The cells used to divide the well connectivity model; For the first The allowable time step for each unit; The spatial step size on the connecting element when calculating water saturation; Porosity of connected units; , For the first Water saturation values ​​at both ends of each unit; , For the first The water content values ​​corresponding to the water saturation values ​​at both ends of each unit; For speed.

2. The method for simulating the dynamic oil-water relationship between wells in a water-drive reservoir as described in claim 1, characterized in that, The well connectivity model is established under the following conditions: considering only the oil-water two-phase flow and ignoring the influence of temperature, neglecting gravity and keeping the viscosity constant.

3. The method for simulating oil-water dynamics between wells in a water-drive reservoir as described in claim 1, characterized in that, The method also includes: Determine the flow and pressure distribution between wells in the established well connectivity model.

4. The method for simulating inter-well oil-water dynamics in a water-drive reservoir as described in claim 3, characterized in that, The well flow and pressure distributions of the established well connectivity model include: In the model of inter-well connectivity of reservoir seepage system to be simulated Connecting volume of the well Establish a mass balance equation for the object; The mass balance equation is rewritten using an implicit difference scheme to obtain a difference scheme for the mass balance equation. Based on the difference scheme of the mass balance equation and the wellpoint mobility value, the following calculations were performed: Time of the first layer Iwa Inter-well mobility value; Based on the flow velocity, drainage volume, and overall reservoir compressibility of each well in the simulated reservoir seepage system, the parameters of each well in the simulated reservoir seepage system are determined. Time and The expression of pressure at any given moment; Based on the wells in the reservoir seepage system to be simulated Time and The pressure expression at any given time is used to calculate the average pressure value of the single-well control area of ​​each well in the seepage system of the reservoir to be simulated at any given time. Based on the average pressure value of the single-well control area of ​​each well in the reservoir seepage system to be simulated at any time and the calculated connectivity conductivity... Calculate the inter-well connectivity model At the moment Layer Iwa The flow velocity between wells.

5. A dynamic oil-water simulation system for water-drive reservoirs, characterized in that, include: The model building module is used to convert the reservoir seepage system to be simulated into an inter-well connectivity network composed of connectivity conductivity and connectivity volume, and to build an inter-well connectivity model of the reservoir seepage system to be simulated. The saturation calculation module is used to calculate the saturation of the established inter-well connectivity model using the discontinuous Galerkin method, and to determine the dynamic data of the seepage system of the reservoir to be simulated. The discontinuous Galerkin method is used to calculate the saturation of the established inter-well connectivity model and determine the dynamic data of the seepage system of the reservoir to be simulated, including: The discontinuous Galerkin method was used to calculate the saturation of the established well connectivity model and obtain the water cut information of the seepage system of the reservoir to be simulated. Based on the water cut information of the seepage system of the reservoir to be simulated, the oil production dynamic data and water production dynamic data of the seepage system of the reservoir to be simulated are obtained. The discontinuous Galerkin method is used to calculate the saturation of the established inter-well connectivity model, obtaining the water cut information of the seepage system of the reservoir to be simulated, including: The well connectivity model is divided into multiple units, denoted as ______. ; Let the region where one of the units is located be , The degrees of freedom in The corresponding finite element shape functions are ,but water saturation function Estimated as : in, For unit The Middle The saturation of each node; Water saturation Finite element estimation function on this element; These are the spatial coordinates on a one-dimensional connected unit. For time; Regarding the water-driven oil recovery problem , It is a general abstract function. It is the independent variable. It is a function representing the water cut information of the reservoir seepage system to be simulated. This is a function used to calculate the water saturation. in, As the independent variable; in the two-dimensional case , For speed in Components of direction; in the one-dimensional case , The total velocity of the two phases on a one-dimensional connected unit; For unit The inflow boundary; For unit The outflow boundary; for Time step in unit No. Moisture content values ​​at each node; For unit The Finite element shape functions at each node; The above solution needs to be reconstructed using a slope limiter; One stability condition for the discontinuous Galerkin method is: In addition, a dynamic stability condition is proposed to determine whether to partition the external time step: in, This represents the maximum allowed time step when calculating saturation. The cells used to divide the well connectivity model; For the first The allowable time step for each unit; The spatial step size on the connecting element when calculating water saturation; Porosity of connected units; , For the first Water saturation values ​​at both ends of each unit; , For the first The water content values ​​corresponding to the water saturation values ​​at both ends of each unit; For speed.

6. A processing apparatus, characterized in that, It includes computer program instructions, wherein when the computer program instructions are executed by the processing device, they are used to implement the steps corresponding to the water-water dynamic simulation method between wells in water-drive reservoirs as described in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, wherein when the computer program instructions are executed by a processor, they are used to implement the steps corresponding to the water-water dynamic simulation method for water-drive reservoir wells as described in any one of claims 1-4.

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