Method and system for calculating recoverable reserves of strong bottom water drive oil reservoir, computer storage medium and equipment

Abstract

The invention discloses a strong bottom water drive reservoir recoverable reserve calculation method, which comprises the following steps of: calculating a first regression correlation linear parameter through a formula ln {arcos [exp (A3. Wp)]} on the basis of cumulative liquid production data; calculating a second regression-related linear parameter through a formula ln (Np) based on the cumulative oil production data; based on the first regression correlation linear parameter and the second regression correlation linear parameter obtained through calculation, a generalized water drive characteristic curve is established, and the expression of the generalized water drive characteristic curve is ln {arcos [exp (A3. Wp)]} = D.ln (Np) + E; and based on the established generalized water drive characteristic curve, fitting values of adjustment parameters A3, D and E, then calculating recoverable reserves through a formula # imgabs0 #, and forming a strong bottom water reservoir recoverable reserve change chart at different stages.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas field exploration and development, and in particular, relates to a method, system, computer storage medium and equipment for calculating recoverable reserves of a strong bottom water drive oil reservoir. Background Art

[0002] Offshore bottom water reservoirs have large reserves and high production, with proven reserves of about 1 billion cubic meters and annual production contribution accounting for 40%, making them the main force in increasing reserves and production in offshore oil fields. After years of rapid development, bottom water reservoirs are mostly in the "double-high" stage of "high recovery and high comprehensive water content", with development wells 400 to 600 meters apart, and well locations generally occupy advantageous positions such as high structural parts, large effective thickness, and developed interlayers. As the overall development enters the adjustment stage, there are fewer and fewer advantageous well locations in unused areas. Accurate evaluation of recoverable reserves is the key to further adjustment and potential tapping of bottom water reservoirs. For the early stage of development, it determines the accurate deployment of the primary well network; for the later stage of development, it determines the density limit of the secondary well network.

[0003] At present, there are four main methods for calculating recoverable reserves: water drive characteristic curve method, empirical formula method, numerical simulation method, and analogy method. Among them, the most commonly used are type A and type B water drive characteristic curve methods, which have the advantages of simple and fast operation. However, the existing water drive characteristic curves are derived based on the exponential oil-water relative permeability curve. In fact, the Krw / Kro value in the oil-water two-phase relative permeability curve can only be expressed by exponential expression in the middle part of the two-phase seepage zone, and there may be certain deviations in the low water content period or the ultra-high water content period. In the low water content period, due to the difference in pore structure and seepage characteristics, the oil phase relative permeability Kro may produce a "hysteresis decline" phenomenon. In the high water content period, due to long-term scouring, the oil phase relative permeability Kro may produce a "stable operation" phenomenon. Therefore, the Krw / Kro value in the low water content and ultra-high water content period does not conform to the exponential law. When the conventional water drive characteristic curve is used for recoverable reserves fitting prediction, the fitting effect is often poor and the prediction error is large. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention provides a method for calculating recoverable reserves of a strong bottom water drive oil reservoir. By introducing trigonometric functions, the application scope of conventional water drive characteristic curves in recoverable reserves calculation is expanded, and the water drive law from low water cut period to high water cut period can be better described. At the same time, based on the single well production dynamic data of offshore bottom water oil reservoirs, a chart of recoverable reserves changes in different stages is formed, laying a foundation for the adjustment and potential tapping of bottom water oil reservoirs in the later stage.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present invention provides a method for calculating recoverable reserves of a strong bottom water drive oil reservoir, comprising the following steps:

[0007] Based on the cumulative production data, the first regression related linear parameters are calculated, wherein the calculation formula of the first regression related linear parameters is: ln{arcos[exp(A3·W p )]}, A3 is a constant, W P is the cumulative fluid production;

[0008] Based on the cumulative oil production data, the second regression related linear parameters are calculated, where the calculation formula of the second regression related linear parameters is: ln(N p ), N P is the cumulative oil production;

[0009] Based on the calculated first regression related linear parameters and second regression related linear parameters, a generalized water drive characteristic curve is established, where the expression of the generalized water drive characteristic curve is: ln{arcos[exp(A3·W p )]}=D·LN(N p )+E, A3, D, E are all adjustment parameters;

[0010] Based on the established generalized water drive characteristic curve, the values ​​of adjustment parameters A3, D, and E are fitted, and then the formula Calculate recoverable reserves and form a chart of recoverable reserves changes in strong bottom water reservoirs at different stages, N r Recoverable reserves.

[0011] As a preferred method, the specific process of establishing a generalized water drive characteristic curve is as follows:

[0012] According to the definition of oil-water relative permeability parameters used in conventional water flooding characteristic curves, there are:

[0013] S wd =(S we -S wi ) / (1-S wi -S or )(1.1)

[0014] In the middle region of two-phase flow, the relative permeability of oil and water can be expressed as:

[0015]

[0016] K ro =(1-S wd ) no (1.3)

[0017]

[0018] In formulas (1.1) to (1.4), K rw , K ro are the relative permeabilities of water phase and oil phase, respectively; S wi is the bound water saturation; S we is the water saturation at the outlet; S or is the residual oil saturation; S wd is the movable oil saturation; nw, no, a, b are all constants;

[0019] Transform equation (1.4) and introduce the mixed trigonometric function expression, namely:

[0020]

[0021] In formula (1.5), A and B are constants;

[0022] Under the condition of stable seepage in water flooding, the relationship between the oil-water phase permeability ratio and the oil-water production is:

[0023]

[0024] In the formula, Q o , μ o , B o are daily oil production, oil viscosity, and oil volume coefficient; Q w , μ w , B w They are daily water production, water viscosity, and water volume coefficient;

[0025] Substituting equation (1.6) into equation (1.5), the daily water production can be expressed as:

[0026]

[0027] It is known that the relationship between the oil saturation at the outlet and the daily oil production can be expressed as:

[0028]

[0029] Where N o is the geological reserves of crude oil;

[0030] The cumulative liquid production of the oil field W p It can be expressed as:

[0031]

[0032] Substituting equation (1.5), equation (1.7) and equation (1.8) into equation (1.9), we get:

[0033]

[0034] in,

[0035]

[0036] Integrating equation (1.10), we get:

[0037]

[0038] In the formula, A2, B1, and C1 are all constants; C1=0, the special solution of formula (1.12) is:

[0039]

[0040] Re-order We can get:

[0041] ln{arcos[exp(A3·W p )]}=B1·ln(N p )+B2 (1.14)

[0042] Or simplified as:

[0043] ln{Y}=D·ln(N p )+E (1.15)

[0044] ln{arcos[exp(A3·W p )]}=D·ln(N p )+E

[0045] Formula (1.15) is the expression of the derived generalized water drive characteristic curve.

[0046] As a preference, when fitting the adjustment parameters A3, D, and E, the fitting end point is when the first regression-related linear parameter and the second regression-related linear parameter reach 99%.

[0047] Preferably, the recoverable reserves variation charts of strong bottom water reservoirs at different stages include the chart of the relationship between initial water content and single well recoverable increment, the chart of the relationship between initial daily oil production and single well recoverable increment, the chart of the relationship between the oil field's annual production level and the single well recoverable increment of the adjustment well, and the chart of the relationship between the remaining well-controlled reserves and the single well recoverable increment of the adjustment well.

[0048] In a second aspect, the present invention provides a system for calculating recoverable reserves of a strong bottom water drive oil reservoir, comprising:

[0049] The first processing unit is used to calculate the first regression related linear parameter based on the cumulative fluid production data, wherein the calculation formula of the first regression related linear parameter is: ln{arcos[exp(A3·W p )]}, A3 is a constant, W P is the cumulative fluid production;

[0050] The second processing unit is used to calculate the second regression related linear parameter based on the cumulative oil production data, wherein the calculation formula of the second regression related linear parameter is: ln(N p ), N P is the cumulative oil production;

[0051] The third processing unit is used to establish a generalized water drive characteristic curve based on the calculated first regression related linear parameter and the second regression related linear parameter, wherein the expression of the generalized water drive characteristic curve is: ln{arcos[exp(A3·W p )]}=D·ln(N p )+E, A3, D, E are all adjustment parameters;

[0052] The fourth processing unit is used to fit the values ​​of the adjustment parameters A3, D, and E based on the established generalized water drive characteristic curve, and then use the formula Calculate recoverable reserves and form a chart of recoverable reserves changes in strong bottom water reservoirs at different stages, N r Recoverable reserves.

[0053] In a third aspect, the present invention provides a computer storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the method for calculating recoverable reserves of a strong bottom water drive oil reservoir described in the first aspect of the present invention are implemented.

[0054] In a fourth aspect, the present invention provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for calculating recoverable reserves of a strong bottom water drive oil reservoir as described in the first aspect of the present invention when executing the computer program.

[0055] The present invention adopts the above technical solution, which has the following advantages:

[0056] Based on the traditional water drive characteristic curve, the present invention introduces trigonometric functions to achieve accurate fitting of water drive laws in low-medium-high-extra-high water content stages, thereby achieving accurate prediction of recoverable reserves in all stages, and forming a set of recoverable reserves change charts of bottom water drive oil reservoirs based on the prediction results, laying a foundation for subsequent adjustment and potential tapping of bottom water oil reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Throughout the accompanying drawings, the same reference numerals are used to represent the same components. In the accompanying drawings:

[0058] Figure 1This is a graph showing the relationship between initial water content and recoverable increment of a single well;

[0059] Figure 2 This is a chart showing the relationship between initial daily oil production and recoverable increment of a single well;

[0060] Figure 3 It is a chart showing the relationship between the oilfield's annual production level and the recoverable increment of the adjustment well;

[0061] Figure 4 It is a chart showing the relationship between the remaining well-controlled reserves and the recoverable increment of the adjustment well;

[0062] Figure 5 Comparison of water flooding fitting effects for Well A1 in Oilfield A. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0064] The method for calculating recoverable reserves of a strong bottom water drive oil reservoir provided by the present invention comprises the following steps: based on the cumulative production data, the formula ln{arcos[exp(A3·W p )]} calculate the first regression related linear parameters; based on the cumulative oil production data, the formula ln(N p ) calculates the second regression related linear parameters; based on the calculated first regression related linear parameters and second regression related linear parameters, establishes a generalized water drive characteristic curve, whose expression is: ln{arcos[exp(A3·W p )]}=D·ln(N p )+E; Based on the established generalized water drive characteristic curve, the values ​​of adjustment parameters A3, D, and E are fitted, and then the formula Calculate recoverable reserves and form a chart of recoverable reserves changes in strong bottom water reservoirs at different stages. Based on the traditional water drive characteristic curve, the present invention introduces trigonometric functions to accurately fit the water drive law in the low-medium-high-ultra-high water content stages, thereby achieving accurate prediction of recoverable reserves in all stages, and forms a set of recoverable reserves change charts for bottom water drive reservoirs based on the prediction results, laying the foundation for subsequent adjustment and potential tapping of bottom water reservoirs.

[0065] The recoverable reserves calculation method and system of a strong bottom water drive oil reservoir provided by an embodiment of the present invention are described in detail below with reference to the accompanying drawings.

[0066] Embodiment 1:

[0067] See also Figure 1 The method for calculating recoverable reserves of a strong bottom water drive oil reservoir provided in an embodiment of the present invention comprises the following steps:

[0068] S100. Based on the accumulated fluid production data, the first regression related linear parameter is calculated, wherein the calculation formula of the first regression related linear parameter is: ln{arcos[exp(A3·W p )]}, A3 is a constant, W P is the cumulative fluid production;

[0069] S200. Based on the cumulative oil production data, calculate the second regression related linear parameters, wherein the calculation formula of the second regression related linear parameters is: ln(N p ), N P is the cumulative oil production;

[0070] S300. Based on the first regression-related linear parameter calculated in step S100 and the second regression-related linear parameter calculated in step S200, a generalized water drive characteristic curve is established, wherein the expression of the generalized water drive characteristic curve is: ln{arcos[exp(A3·W p )]}=D·ln(N p )+E, A3, D, E are all adjustment parameters;

[0071] S400. Based on the generalized water drive characteristic curve established in step S300, the values ​​of adjustment parameters A3, D, and E are fitted, with the first regression-related linear parameter and the second regression-related linear parameter reaching 99% as the fitting end point, and then the formula Calculate recoverable reserves and form a chart of recoverable reserves changes in strong bottom water reservoirs at different stages, N r Recoverable reserves.

[0072] In the above embodiment, preferably, the specific process of establishing the generalized water flooding characteristic curve is as follows:

[0073] According to the definition of oil-water relative permeability parameters used in conventional water flooding characteristic curves, there are:

[0074] S wd =(S we -S wi ) / (1-S wi -S or ) (1.1)

[0075] Generally speaking, in the middle region of two-phase flow, the oil-water relative permeability can be expressed as:

[0076]

[0077] K ro =(1-S wd )no (1.3)

[0078]

[0079] In formulas (1.1) to (1.4), K rw , K ro are the relative permeabilities of water phase and oil phase, respectively; S wi is the bound water saturation; S we is the water saturation at the outlet; S or is the residual oil saturation; S wd is the movable oil saturation; nw, no, a, and b are all constants.

[0080] Considering that equations (1.2) to (1.4) are difficult to accurately describe the complete form of the phase permeability curve at low water saturation and high water saturation, equation (1.4) is transformed and a mixed trigonometric function expression is introduced, namely:

[0081]

[0082] In formula (1.5), A and B are both constants. rw / K ro The latest expression can more broadly describe the complete morphology of various non-exponential permeability curves.

[0083] Under the condition of stable seepage in water flooding, the relationship between the oil-water phase permeability ratio and the oil-water production is:

[0084]

[0085] In the formula, Q o , μ o , B o are daily oil production, oil viscosity, and oil volume coefficient; Q w , μ w , B w They are daily water production, water viscosity and water volume coefficient respectively.

[0086] Substituting equation (1.6) into equation (1.5), the daily water production can be expressed as:

[0087]

[0088] It is known that the relationship between the oil saturation at the outlet and the daily oil production can be expressed as:

[0089]

[0090] Where N o Geological reserves of crude oil.

[0091] The cumulative liquid production of the oil field Wp It can be expressed as:

[0092]

[0093] Substituting equation (1.5), equation (1.7) and equation (1.8) into equation (1.9), we get:

[0094]

[0095] in,

[0096]

[0097] Integrating equation (1.10), we get:

[0098]

[0099] In the formula, A2, B1, and C1 are all constants. C1=0, the special solution of formula (1.12) is:

[0100]

[0101] Re-order We can get:

[0102] ln{arcos[exp(A3·W p )]}=B1·ln(N p )+B2 (1.14)

[0103] Or simplified as:

[0104] ln{Y}=D·ln(N p )+E (1.15)

[0105] ln{arcos[exp(A3·W p )]}=D·ln(N p )+E

[0106] Formulas (1.14) and (1.15) are the expressions of the derived generalized water drive characteristic curve, which can describe the water drive law based on different complex phase permeability forms. Moreover, it is not difficult to see from the expression of the generalized water drive characteristic curve that the recoverable reserves can be directly and conveniently calculated from the values ​​of the adjustment parameters D and E of the fitting curve:

[0107]

[0108] Based on formula (1.16), we can generate a chart of the changes in recoverable reserves of strong bottom water reservoirs at different stages, including a chart of the relationship between initial water content and single well recoverable increment (see Figure 1), the relationship between initial daily oil production and single well recoverable increment (please refer to Figure 2 ), the relationship between the oilfield's annual production level and the incremental production of the adjustment well (please refer to Figure 3 ) and the relationship between remaining well-controlled reserves and the incremental recoverable reserves of the adjustment wells (see Figure 4 ).

[0109] The method of the present invention is further described below by means of specific embodiments:

[0110] Embodiment 1

[0111] Oilfield A is located in the southeast of central China. The main oil-bearing strata are the Tertiary system. It is a porous edge-bottom water reservoir with sufficient water energy. The original formation pressure is 32.6MPa, and the average permeability of the oil layer is 130×10 4 μm 2 , porosity 15.5%, formation oil viscosity 1.6mPa·s, crude oil volume coefficient 1.36, the oil field is developed by natural energy exhaustion, and one typical production well A1 has produced 419.01×10 4 bbl (1bbl = 0.14t), water content 55%. A1 well produced until 2013 when the water content was 12%. At that time, due to the production needs of the oil field, the water drive law was analyzed and the recoverable reserves N were predicted. r (f w =98%).

[0112] Combined with Table 1 and Figure 5 The water drive fitting and recoverable reserves prediction results of the production well A1 in the middle are shown, and the fitting effect is jointly judged by the water drive characteristic curve fitting correlation coefficient and the size of the residual square sum of the fitting. From the data comparison, it can be seen that the recoverable reserves calculation method of the present invention has a smaller correlation coefficient and residual square sum, a better fitting effect, and has good applicability in different production periods and water-containing stages.

[0113] Table 1 Comparison of fitting results of single wells in different reservoirs

[0114]

[0115] Embodiment 2:

[0116] The above-mentioned embodiment 1 provides a method for calculating the recoverable reserves of a strong bottom water drive oil reservoir. Correspondingly, this embodiment provides a system for calculating the recoverable reserves of a strong bottom water drive oil reservoir. The system for calculating the recoverable reserves of a strong bottom water drive oil reservoir provided in this embodiment can implement the method for calculating the recoverable reserves of a strong bottom water drive oil reservoir in embodiment 1. The system for calculating the recoverable reserves of a strong bottom water drive oil reservoir can be implemented by software, hardware, or a combination of software and hardware. For example, the system for calculating the recoverable reserves of a strong bottom water drive oil reservoir can include integrated or separate functional modules or functional units to execute the corresponding steps in each method of embodiment 1. Since the system for calculating the recoverable reserves of a strong bottom water drive oil reservoir in this embodiment is basically similar to the method embodiment, the process described in this embodiment is relatively simple. For the relevant parts, please refer to the partial description of embodiment 1. The system for calculating the recoverable reserves of a strong bottom water drive oil reservoir in this embodiment is only schematic.

[0117] The recoverable reserves calculation system of the strong bottom water drive oil reservoir provided in this embodiment includes:

[0118] The first processing unit is used to calculate the first regression related linear parameter based on the cumulative fluid production data, wherein the calculation formula of the first regression related linear parameter is: ln{arcos[exp(A3·W p )]}, A3 is a constant, W P is the cumulative fluid production;

[0119] The second processing unit is used to calculate the second regression related linear parameter based on the cumulative oil production data, wherein the calculation formula of the second regression related linear parameter is: ln(N p ), N P is the cumulative oil production;

[0120] The third processing unit is used to establish a generalized water drive characteristic curve based on the calculated first regression related linear parameter and the second regression related linear parameter, wherein the expression of the generalized water drive characteristic curve is: ln{arcos[exp(A3·W p )]}=D·ln(N p )+E, A3, D, E are all adjustment parameters;

[0121] The fourth processing unit is used to fit the values ​​of the adjustment parameters A3, D, and E based on the established generalized water drive characteristic curve, and then use the formula Calculate recoverable reserves and form a chart of recoverable reserves changes in strong bottom water reservoirs at different stages, N r Recoverable reserves.

[0122] Embodiment 3:

[0123] This embodiment provides a processing device for implementing the method for calculating recoverable reserves of strong bottom water drive oil reservoirs provided in this embodiment 1. The processing device can be a processing device for a client, such as a mobile phone, a laptop computer, a tablet computer, a desktop computer, etc., to execute the method of embodiment 1.

[0124] The processing device includes a processor, a memory, a communication interface and a bus, and the processor, the memory and the communication interface are connected through the bus to complete mutual communication. The memory stores a computer program that can be run on the processor, and the processor executes the method for calculating recoverable reserves of a strong bottom water drive reservoir provided in this embodiment 1 when running the computer program.

[0125] Preferably, the memory may be a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory.

[0126] Preferably, the processor may be a central processing unit (CPU), a digital signal processor (DSP) or other general-purpose processors of various types, which are not limited here.

[0127] Embodiment 4:

[0128] The method for calculating recoverable reserves of a strong bottom water drive oil reservoir of this embodiment 1 can be specifically implemented as a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for executing the method described in this embodiment 1.

[0129] Computer readable storage media can be tangible devices that hold and store instructions used by instruction execution devices. Computer readable storage media can be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any combination thereof.

[0130] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and they should all be included in the scope of the claims and specification of the present application. In particular, as long as there is no structural conflict, the various technical features mentioned in the various embodiments can be combined in any way. The present application is not limited to the specific embodiments disclosed herein, but includes all technical solutions that fall within the scope of the claims.

Claims

1. A method for calculating recoverable reserves of strong bottom water drive oil reservoirs. It is characterized in that The following steps are involved: Based on the cumulative production data, the first regression related linear parameters are calculated, where the calculation formula of the first regression related linear parameters is: ln{arcos[exp(A 3 ·W p )]},A 3 is a constant, W P is the cumulative fluid production; Based on the cumulative oil production data, the second regression related linear parameters are calculated, where the calculation formula of the second regression related linear parameters is: ln(N p ), N P is the cumulative oil production; Based on the calculated first regression related linear parameters and second regression related linear parameters, a generalized water drive characteristic curve is established, where the expression of the generalized water drive characteristic curve is: ln{arcos[exp(A 3 ·W p )]}=D·ln(N p )+E,A 3 , D, and E are all adjustment parameters; Based on the established generalized water drive characteristic curve, the adjustment parameter A is fitted. 3 , D, E values, and then through the formula Calculate recoverable reserves and form a chart of recoverable reserves changes in strong bottom water reservoirs at different stages, N r Recoverable reserves.

2. The method for calculating recoverable reserves of a strong bottom water drive oil reservoir according to claim 1, It is characterized in that The specific process of establishing the generalized water drive characteristic curve is as follows: According to the definition of oil-water relative permeability parameters used in conventional water flooding characteristic curves, there are: S wd =(S we -S wi ) / (1-S wi -S or ) (1.1) In the middle region of two-phase flow, the relative permeability of oil and water can be expressed as: K ro =(1-S wd ) no (1.3) In formulas (1.1) to (1.4), K rw , K ro are the relative permeabilities of water phase and oil phase, respectively; S wi is the bound water saturation; S we is the water saturation at the outlet; S or is the residual oil saturation; S wd is the movable oil saturation; nw, no, a, b are all constants; Transform equation (1.4) and introduce the mixed trigonometric function expression, namely: In formula (1.5), A and B are constants; Under the condition of stable seepage in water flooding, the relationship between the oil-water phase permeability ratio and the oil-water production is: In the formula, Q o , μ o , B o are daily oil production, oil viscosity, and oil volume coefficient; Q w , μ w , B w They are daily water production, water viscosity, and water volume coefficient; Substituting equation (1.6) into equation (1.5), the daily water production can be expressed as: It is known that the relationship between the oil saturation at the outlet and the daily oil production can be expressed as: Where N o is the geological reserves of crude oil; The cumulative liquid production of the oil field W p It can be expressed as: Substituting equation (1.5), equation (1.7) and equation (1.8) into equation (1.9), we get: in, Integrating equation (1.10), we get: In the formula, A 2 , B 1 , C 1 are all constants; let C 1 =0, the special solution of formula (1.12) is: Re-order We can get: ln{arcos[exp(A 3 ·W p )]}=B 1 ·ln(N p )+B 2 (1.14) Or simplified as: ln{Y}=D·ln(Np ) +E (1.15) ln{arcs[exp(A 3 ·W p )]}D·ln(N p )+E Formula (1.15) is the expression of the derived generalized water drive characteristic curve.

3. The method for calculating recoverable reserves of a strong bottom water drive oil reservoir according to claim 1, It is characterized in that In the fitting adjustment parameter A 3 , D, and E, the fitting end point is when the first regression related linear parameter and the second regression related linear parameter reach 99%.

4. The method for calculating recoverable reserves of a strong bottom water drive oil reservoir according to claim 1, It is characterized in that The recoverable reserves change charts of strong bottom water oil reservoirs at different stages include the relationship chart between initial water content and single well recoverable increment, the relationship chart between initial daily oil production and single well recoverable increment, the relationship chart between the oil field's annual production level and the single well recoverable increment of the adjustment well, and the relationship chart between remaining well-controlled reserves and single well recoverable increment of the adjustment well.

5. A system for calculating recoverable reserves of strong bottom water drive oil reservoirs. It is characterized in that include: The first processing unit is used to calculate the first regression related linear parameter based on the cumulative fluid production data, wherein the calculation formula of the first regression related linear parameter is: ln{arcos[exp(A 3 ·W p )]},A 3 is a constant, W P is the cumulative fluid production; The second processing unit is used to calculate the second regression related linear parameter based on the cumulative oil production data, wherein the calculation formula of the second regression related linear parameter is: ln(N p ), N P is the cumulative oil production; The third processing unit is used to establish a generalized water drive characteristic curve based on the calculated first regression related linear parameter and the second regression related linear parameter, wherein the expression of the generalized water drive characteristic curve is: ln(arcos[exp(A 3 ·W p )]}=D·ln(N p )+E,A 3 , D, and E are all adjustment parameters; The fourth processing unit is used to fit the adjustment parameter A based on the established generalized water drive characteristic curve. 3 , D, E values, and then through the formula Calculate recoverable reserves and form a chart of recoverable reserves changes in strong bottom water reservoirs at different stages, N r Recoverable reserves.

6. A computer storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, the steps of the method for calculating recoverable reserves of a strong bottom water drive oil reservoir described in any one of claims 1 to 4 are implemented.

7. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the computer program, the steps of the method for calculating recoverable reserves of a strong bottom water drive oil reservoir according to any one of claims 1 to 4 are implemented.

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