Prediction method and device for natural declining rate of deepwater gas-driven oil field, equipment and medium

Abstract

The invention relates to a method and device for predicting the natural declining rate of a deepwater gas-driven oil field, equipment and a medium, and relates to the technical field of oil and gas exploitation, and the method comprises the steps: obtaining basic parameters of a target deepwater gas-driven oil field; calculating according to the basic parameters to obtain a gas-oil fluidity ratio and a Welge coefficient; according to the basic parameters, the gas-oil fluidity ratio and the Welge coefficient, the production gas-oil ratio and the production gas-oil ratio rising rate are obtained through calculation; the natural declining rate is calculated according to the basic parameters, the production gas-oil ratio and the production gas-oil ratio rising rate; and predicting the natural declining rate of the oil field according to the relationship among the production gas-oil ratio, the production gas-oil ratio rising rate, the natural declining rate and the movable oil reserve recovery degree. According to the prediction method provided by the invention, the designed calculation process is adopted, and the natural decline rate of the deepwater gas-driven oil field is predicted by considering the upper limit condition of the output gas treatment capacity of the deepwater floating type production oil storage tanker and the rising of the oil field production gas-oil ratio.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and natural gas exploitation, and specifically to a method and device, equipment, and medium for predicting the natural decline rate of a deepwater gas drive oil field, and more particularly to a method for predicting the natural decline rate of an oil field under the condition that there is an upper limit on the gas processing capacity of a deepwater offshore floating production storage and offloading vessel (FPSO). Background Art

[0002] Deepwater oilfields (water depth > 500m) generally adopt an engineering model of joint development of offshore floating production storage and offloading vessels (FPSO) + underwater wellheads, and FPSO has an upper limit on the daily processing capacity of produced crude oil and produced gas. For deepwater oilfields developed by gas drive, before the gas produced by the oilfield reaches the upper limit of the daily processing capacity, the oilfield produces stably at the upper limit of the daily crude oil processing capacity of the FPSO, that is, it is in the peak stable production stage.

[0003] After the injection gas breakthrough, as the gas-oil ratio gradually increases, when the output gas reaches the daily processing limit, production restrictions will be taken to maintain the daily gas production at the upper limit of the FPSO processing capacity, and the oil field will enter the decline stage. Unlike onshore oil fields or shallow water oil fields developed by conventional gas drive (output gas is transported to nearshore processing terminals), the decline of oil fields is constrained by the FPSO processing capacity, so it is difficult to predict.

[0004] At present, the natural decline rate of deepwater gas-driven oil fields is mainly predicted by reservoir numerical simulation methods. However, for deepwater gas-driven sandstone reservoirs, even if the long production history is fitted, the reservoir numerical simulation model still has great uncertainty. Therefore, it is necessary to propose a natural decline rate prediction method for deepwater gas-driven oil fields to guide the production prediction of deepwater gas-driven oil fields, thereby ensuring the efficient exploitation of deepwater gas-driven oil fields. Summary of the invention

[0005] In view of the problems existing in the prior art, the purpose of the present invention is to provide a method and device, equipment and medium for predicting the natural decline rate of deepwater gas drive oil fields, so as to solve the defect of poor prediction accuracy of the natural decline rate of deepwater gas drive oil fields.

[0006] To achieve this object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a method for predicting the natural decline rate of a deepwater gas drive oil field, the prediction method comprising:

[0008] Obtain basic parameters of target deepwater gas drive oil fields;

[0009] The gas-oil mobility ratio M and Welge coefficient ω are calculated based on basic parameters;

[0010] The production gas-oil ratio R is calculated based on basic parameters, gas-oil mobility ratio M and Welge coefficient ω. s Relationship and production gas-oil ratio increase rate R s 'Relational formula;

[0011] Based on basic parameters, production gas-oil ratio R s Relationship and production gas-oil ratio increase rate R s 'The natural decline rate D is calculated by the relationship o Relational;

[0012] Based on the production gas-oil ratio R s , production gas-oil ratio increase rate R s ', natural decline rate D o The recovery rate of movable oil reserves R f The relationship between the natural decline rate D of the oil field is predicted o .

[0013] The prediction method provided by the present invention, by adopting a designed calculation process, realizes a method for predicting the natural decline rate of deepwater gas-driven oil fields by taking into account the upper limit conditions of the gas processing capacity of the deepwater offshore floating production storage and offloading vessel (FPSO) and the increase in the gas-to-oil ratio of the oil field production, thereby solving the problem that the current natural decline rate prediction of deepwater gas-driven oil fields relying on reservoir numerical simulation methods has large uncertainty, long time consumption and low efficiency.

[0014] As a preferred technical solution of the present invention, the basic parameters include the oil field geological reserves N o , oil and gas relative permeability parameters, fluid parameters and FPSO parameters.

[0015] As a preferred technical solution of the present invention, the oil-gas relative permeability parameter includes the gas phase index n g , oil phase index n o , residual oil saturation S or , bound gas saturation S gi , gas phase relative permeability K at residual oil saturation rg (S or ) and the oil phase relative permeability K at bound gas saturation ro (S gi ).

[0016] Preferably, the fluid parameters include the crude oil viscosity μ under formation conditions. o 、Gas viscosity μ g 、Original gas-oil ratio R si 、Crude oil volume coefficient B o and gas volume coefficient B g .

[0017] Preferably, the FPSO parameters include an upper limit Q of the produced gas processing capacity.gc and the upper limit of FPSO's oil production processing capacity Q oc .

[0018] As a preferred technical solution of the present invention, the calculation formula of the gas-oil flow ratio M is as follows (1):

[0019]

[0020] Where: μ o is the viscosity of crude oil under formation conditions, mPa·s; μ g B is the gas viscosity under formation conditions, mPa·s; o is the crude oil volume coefficient; B g is the gas volume coefficient; K rg (S or ) is the gas phase relative permeability at residual oil saturation; S or is the residual oil saturation; K ro (S gi ) is the relative permeability of the oil phase at bound gas saturation; S gi is the bound gas saturation.

[0021] Preferably, the calculation formula of the Welge coefficient ω is as follows (2):

[0022]

[0023] Where n g is the gas phase index, n o is the oil phase index.

[0024] As a preferred technical solution of the present invention, the production gas-oil ratio R s The calculation formula is as follows (3):

[0025]

[0026] In the formula, R si is the original gas-oil ratio, m 3 / m 3 ; R f It is the extent of recovery of movable oil reserves.

[0027] Preferably, the production gas-oil ratio increase rate R s The calculation formula of ' is as follows (4):

[0028]

[0029] In the formula, E d is the oil displacement efficiency, f.

[0030] As a preferred technical solution of the present invention, the natural decline rate D oThe calculation formula is as follows (5):

[0031]

[0032] Where: T is the annual effective production days, that is, the annual calendar days multiplied by the production time rate, d; Q gc is the upper limit of FPSO’s gas processing capacity, m 3 / d;N o To utilize geological reserves, 10 4 m 3 .

[0033] As a preferred technical solution of the present invention, the development method of the deepwater gas drive oil field includes one of associated gas reinjection, external gas injection or natural gas top drive.

[0034] Preferably, the deepwater gas drive oil field is in a production decline stage.

[0035] In a second aspect, the present invention provides a prediction device for the natural decline rate of a deepwater gas drive oil field, the prediction device comprising:

[0036] Basic parameter acquisition module, used to obtain basic parameters of target deepwater gas drive oil fields;

[0037] The first calculation module is used to calculate the gas-oil mobility ratio M and the Welge coefficient ω according to the basic parameters;

[0038] The second calculation module is used to calculate the production gas-oil ratio R based on the basic parameters, gas-oil mobility ratio M and Welge coefficient ω s Relationship and production gas-oil ratio increase rate R s 'Relational formula;

[0039] The third calculation module is used to calculate the gas-oil ratio R according to the basic parameters and production s Relationship and production gas-oil ratio increase rate R s 'The natural decline rate D is calculated by the relationship o Relational;

[0040] The prediction curve acquisition module is used to obtain the production gas-oil ratio R s , production gas-oil ratio increase rate R s ', natural decline rate D o The recovery rate of movable oil reserves R f The relationship between the natural decline rate D of the oil field is predicted o .

[0041] In a third aspect, the present invention provides an electronic device, the electronic device comprising:

[0042] at least one processor; and a memory communicatively coupled to the at least one processor;

[0043] Wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for predicting the natural decline rate of deepwater gas drive oil fields described in the first aspect.

[0044] In a fourth aspect, an embodiment of the present invention provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and when the computer executable instructions are executed by a processor, the method for predicting the natural decline rate of a deepwater gas drive oil field described in the first aspect is implemented.

[0045] Compared with the prior art solutions, the present invention has the following beneficial effects:

[0046] The prediction method provided by the present invention realizes a method for predicting the natural decline rate of deepwater gas-driven oil fields by optimizing the calculation process, taking into account the upper limit conditions of the gas processing capacity of the deepwater offshore floating production storage and offloading vessel (FPSO) and the increase in the gas-to-oil ratio of the oil field production, thereby realizing high-precision and high-efficiency prediction of the natural decline rate of deepwater gas-driven oil fields, and providing solid theoretical support for the production prediction of deepwater gas-driven oil fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flow chart of a method for predicting the natural decline rate of a deepwater gas drive oil field provided by an embodiment of the present invention;

[0048] Figure 2 It is a schematic diagram of a device for predicting the natural decline rate of a deepwater gas drive oil field provided by an embodiment of the present invention;

[0049] Figure 3 is a schematic diagram of an electronic device provided by an embodiment of the present invention;

[0050] Figure 4 is the oil-gas relative permeability curve of the overseas L deepwater oil field in Example 1 of the present invention;

[0051] Figure 5 is the gas-oil ratio R obtained in Example 1 of the present invention s The recovery rate of movable oil reserves R f The relationship curve of

[0052] Figure 6 is the production gas-oil ratio increase rate R obtained in Example 1 of the present invention s ′ and the recovery rate of movable oil reserves R f The relationship curve of

[0053] Figure 7 is the natural decline rate D obtained in Example 1 of the present invention o The recovery rate of movable oil reserves R frelationship curve.

[0054] In the figure: 10 - electronic device, 11 - processor, 12 - ROM, 13 - RAM, 14 - bus, 15 - I / O interface, 16 - input unit, 17 - output unit, 18 - storage unit, 19 - communication unit.

[0055] The present invention is further described in detail below. However, the following examples are only simplified examples of the present invention and do not represent or limit the scope of protection of the present invention. The scope of protection of the present invention shall be subject to the claims. DETAILED DESCRIPTION

[0056] To better illustrate the present invention and facilitate understanding of the technical solution of the present invention, typical but non-limiting embodiments of the present invention are as follows:

[0057] This embodiment provides a method for predicting the natural decline rate of a deepwater gas drive oil field. Figure 1 As shown, the prediction method includes:

[0058] Obtain basic parameters of target deepwater gas drive oil fields;

[0059] The gas-oil mobility ratio M and Welge coefficient ω are calculated based on basic parameters;

[0060] The production gas-oil ratio R is calculated based on basic parameters, gas-oil mobility ratio M and Welge coefficient ω. s Relationship and production gas-oil ratio increase rate R s 'Relational formula;

[0061] Based on basic parameters, production gas-oil ratio R s Relationship and production gas-oil ratio increase rate R s 'The natural decline rate D is calculated by the relationship o Relational;

[0062] Based on the production gas-oil ratio R s , production gas-oil ratio increase rate R s ', natural decline rate D o The recovery rate of movable oil reserves R f The relationship between the natural decline rate D of the oil field is predicted o .

[0063] In the present invention, the production gas-oil ratio R s , production gas-oil ratio increase rate R s ', natural decline rate D o The recovery rate of movable oil reserves R f The relationship can be selected in the form of a functional expression or a relationship curve graph.

[0064] Among them, the basic parameters include the oil field geological reserves N o , oil and gas relative permeability parameters, fluid parameters and FPSO parameters.

[0065] The oil-gas relative permeability parameters include the gas phase index n g , oil phase index n o , residual oil saturation S or , bound gas saturation S gi , gas phase relative permeability K at residual oil saturation rg (S or ) and the oil phase relative permeability K at bound gas saturation ro (S gi ).

[0066] The fluid parameters include the crude oil viscosity μ under formation conditions. o 、Gas viscosity μ g 、Original gas-oil ratio R si 、Crude oil volume coefficient B o and gas volume coefficient B g .

[0067] The FPSO parameters include the upper limit of the gas processing capacity Q gc and the upper limit of FPSO's oil production processing capacity Q oc .

[0068] The calculation formula of the gas-oil flow ratio M is as follows (1):

[0069]

[0070] Where: μ o is the viscosity of crude oil under formation conditions, mPa·s; μ g B is the gas viscosity under formation conditions, mPa·s; o is the crude oil volume coefficient; B g is the gas volume coefficient; K rg (S or ) is the gas phase relative permeability at residual oil saturation; S or is the residual oil saturation; K ro (S gi ) is the relative permeability of the oil phase at bound gas saturation; S gi is the bound gas saturation.

[0071] The calculation formula of the Welge coefficient ω is as follows (2):

[0072]

[0073] Where n g is the gas phase index, no is the oil phase index.

[0074] Wherein, the production gas-oil ratio R s The calculation formula is as follows (3):

[0075]

[0076] In the formula, R si is the original gas-oil ratio, m 3 / m 3 ; R f The degree of recovery of movable oil reserves.

[0077] Among them, the production gas-oil ratio increase rate R s The calculation formula of ' is as follows (4):

[0078]

[0079] In the formula, E d is the oil displacement efficiency, f;

[0080] Wherein, the natural decline rate D o The calculation formula is as follows (5):

[0081]

[0082] Where: T is the annual effective production days, that is, the annual calendar days multiplied by the production time rate, d; Q gc is the upper limit of FPSO’s gas processing capacity, m 3 / d;N o To utilize geological reserves, 10 4 m 3 .

[0083] Furthermore, this embodiment provides a prediction device for the natural decline rate of a deepwater gas drive oil field, such as Figure 2 As shown, the prediction device comprises:

[0084] Basic parameter acquisition module, used to obtain basic parameters of target deepwater gas drive oil fields;

[0085] The first calculation module is used to calculate the gas-oil mobility ratio M and the Welge coefficient ω according to the basic parameters;

[0086] The second calculation module is used to calculate the production gas-oil ratio R based on the basic parameters, gas-oil mobility ratio M and Welge coefficient ω s Relationship and production gas-oil ratio increase rate R s 'Relational formula;

[0087] The third calculation module is used to calculate the gas-oil ratio R according to the basic parameters and production sRelationship and production gas-oil ratio increase rate R s 'The natural decline rate D is calculated by the relationship o Relational;

[0088] The prediction curve acquisition module is used to obtain the production gas-oil ratio R s , production gas-oil ratio increase rate R s ', natural decline rate D o The recovery rate of movable oil reserves R f The relationship between the natural decline rate D of the oil field is predicted o .

[0089] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0090] Further, the present invention provides an electronic device, which is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0091] like Figure 3 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The I / O interface 15 is also connected to the bus 14.

[0092] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0093] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, such as a method for predicting the natural decline rate of a deepwater gas drive oil field.

[0094] In some embodiments, the method for predicting the natural decline rate of a deepwater gas drive oil field may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for predicting the natural decline rate of a deepwater gas drive oil field described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the method for predicting the natural decline rate of a deepwater gas drive oil field by any other appropriate means (e.g., by means of firmware).

[0095] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0096] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0097] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0098] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0099] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0100] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0101] The server provided in this embodiment includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for predicting the natural decline rate of a deepwater gas drive oil field is implemented.

[0102] Unless otherwise specifically stated, terms such as processing, computing, calculating, determining, displaying, etc. may refer to the actions and / or processes of one or more processing or computing systems, or similar devices, which operate and convert data represented as physical (e.g., electronic) quantities within registers or memories of a processing system into other data similarly represented as physical quantities within memories, registers, or other such information storage, transmission, or display devices of the processing system. Information and signals may be represented using any of a variety of different techniques and methods. For example, data, instructions, commands, information, signals, bits, symbols, and chips mentioned throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, light fields or particles, or any combination thereof.

[0103] Those skilled in the art will also appreciate that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments of the present invention may all be implemented as electronic hardware, computer software, or a combination thereof. In order to clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described around their functions. Whether such functions are implemented as hardware or software depends on the specific application and the design constraints imposed on the entire system. A skilled person may implement the described functions in an alternative manner for each specific application, but such implementation decisions should not be interpreted as departing from the scope of protection of the present disclosure.

[0104] The steps of the method or algorithm described in conjunction with the embodiments herein may be directly embodied as hardware, a software module executed by a processor, or a combination thereof. The software module may be located in a RAM memory, a flash memory, a ROM memory, an EPROM memory, an EEPROM memory, a register, a hard disk, a mobile disk, a CD-ROM, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor so that the processor can read information from the storage medium and can write information to the storage medium. Of course, the storage medium may also be an integral part of the processor. The processor and the storage medium may be located in an ASIC. The ASIC may be located in a user terminal. Of course, the processor and the storage medium may also be present in a user terminal as discrete components.

[0105] For software implementation, the techniques described in the present invention can be implemented with modules (e.g., procedures, functions, etc.) that perform the functions described in the present application. These software codes can be stored in a memory unit and executed by a processor. The memory unit can be implemented within the processor or outside the processor. In the latter case, it is coupled to the processor in a communication manner via various means, which are well known in the art.

[0106] Further, in order to illustrate the prediction effect that can be achieved by the prediction method for the natural decline rate of deepwater gas drive oil fields provided by the present invention, an actual example is used for illustration, as follows:

[0107] Example 1

[0108] This example takes the L deepwater gas drive oil field overseas as an example to predict the natural decline rate of the deepwater gas drive oil field, as follows:

[0109] S1. Collect and determine basic parameters, as follows: Utilize crude oil geological reserves N o =26073×10 4 m 3 , the initial production gas-oil ratio of the oil field is R si =220m 3 / m3 FPSO gas processing capacity upper limit Q gc =566×10 4 m 3 / d; FPSO oil production processing capacity upper limit Q oc =2.4×10 4 m 3 / d; Annual effective production days T = 350d; Oil and gas relative permeability curve as shown in Figure 4 As shown, the gas phase index n g =2.759, oil phase index n o =2.789; Crude oil viscosity under formation conditions μ o =0.47mPa·s; gas viscosity under formation conditions μ g =0.03mPa·s; crude oil volume coefficient B o =1.5; gas volume coefficient B g =0.03; residual oil saturation S or =0.4554; bound gas saturation S gi =0; oil recovery efficiency E d =0.5446; gas phase relative permeability K at residual oil saturation rg (S or )=0.667; Oil phase relative permeability K at bound gas saturation ro (S gi )=1.0;

[0110] S2. Substitute the basic parameters determined in S1 into the following formula to calculate the gas-oil mobility ratio M and the Welge coefficient ω:

[0111]

[0112] ω=0.88

[0113] S3, Substitute the basic parameters determined in S1 and the calculated gas-oil mobility ratio M and Welge coefficient ω into the following formula to calculate the production gas-oil ratio R s and the production gas-oil ratio increase rate R s ′:

[0114]

[0115]

[0116] S4. Use the basic parameters to generate the crude oil geological reserves N o =26073×10 4 m 3 、FPSO gas processing capacity upper limit Q gc =566×10 4 m3 / d, annual effective production days T = 350d and the calculated production gas-oil ratio R s Relationship, production gas-oil ratio increase rate R s Substitute the relationship into the following formula to calculate the natural decline rate D o :

[0117]

[0118] (4) According to the production gas-oil ratio R s Relationship, production gas-oil ratio increase rate R s ′Relationship and natural decline rate D o Relationship, respectively draw the production gas-oil ratio R s , production gas-oil ratio increase rate R s ', natural decline rate D o The recovery rate of movable oil reserves R f The curve, such as Figure 5 , Figure 6 and Figure 7 shown.

[0119] According to the production gas-oil ratio R s Relationship, production gas-oil ratio increase rate R s ′Relationship and natural decline rate D o Relational or Figure 5 , Figure 6 and Figure 7 The recovery degree R of different movable oil reserves can be obtained quickly and accurately f The production gas-oil ratio R s , production gas-oil ratio increase rate R s ', natural decline rate D o Values, such as movable oil reserves recovery rate R f =0.35, the production gas-oil ratio R s =553.4m 3 / m 3 , production gas-oil ratio increase rate R s ′=99.7m 3 / m 3 , annual natural decline rate D o =24.7%, thereby realizing the prediction of natural decline rate with the help of the recovery degree of movable oil reserves in existing oil fields.

[0120] It is stated that the present invention illustrates the detailed structural features of the present invention through the above embodiments, but the present invention is not limited to the above detailed structural features, that is, it does not mean that the present invention must rely on the above detailed structural features to be implemented. Those skilled in the art should understand that any improvement of the present invention, equivalent replacement of the components selected by the present invention, addition of auxiliary components, selection of specific methods, etc., all fall within the protection scope and disclosure scope of the present invention.

[0121] The preferred embodiments of the present invention are described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the technical concept of the present invention, a variety of simple modifications can be made to the technical solution of the present invention, and these simple modifications all belong to the protection scope of the present invention.

[0122] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not further describe various possible combinations.

[0123] In addition, various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the present invention, they should also be regarded as the contents disclosed by the present invention.

Claims

1. A method for predicting the natural decline rate of a deepwater gas drive oil field, characterized in that: The prediction method comprises: Obtain basic parameters of target deepwater gas drive oil fields; The gas-oil mobility ratio M and Welge coefficient ω are calculated based on basic parameters; The production gas-oil ratio R is calculated based on basic parameters, gas-oil mobility ratio M and Welge coefficient ω. s Relationship and production gas-oil ratio increase rate R s 'Relational formula; Based on basic parameters, production gas-oil ratio R s Relationship and production gas-oil ratio increase rate R s 'The natural decline rate D is calculated by the relationship o Relational; Based on the production gas-oil ratio R s , production gas-oil ratio increase rate R s ', natural decline rate D o The recovery rate of movable oil reserves R f The relationship between the natural decline rate D of the oil field is predicted o .

2. The prediction method according to claim 1, characterized in that: The basic parameters include the oilfield geological reserves N o , oil and gas relative permeability parameters, fluid parameters and FPSO parameters.

3. The prediction method according to claim 2, characterized in that: The oil-gas relative permeability parameters include the gas phase index n g , oil phase index n o , residual oil saturation S or , bound gas saturation S gi , gas phase relative permeability K at residual oil saturation rg (S or ) and the oil phase relative permeability K at bound gas saturation ro (S gi ); Preferably, the fluid parameters include the crude oil viscosity μ under formation conditions. o 、Gas viscosity μ g 、Original gas-oil ratio R si 、Crude oil volume coefficient B o and gas volume coefficient B g ; Preferably, the FPSO parameters include an upper limit Q of the produced gas processing capacity. gc and the upper limit of FPSO's oil production processing capacity Q oc .

4. The prediction method according to any one of claims 1 to 3, characterized in that: The calculation formula of the gas-oil flow ratio M is as follows (1): Where: μ o is the viscosity of crude oil under formation conditions, mPa·s; μ g B is the gas viscosity under formation conditions, mPa·s; o is the crude oil volume coefficient; B g is the gas volume coefficient; K rg (S or ) is the gas phase relative permeability at residual oil saturation; S or is the residual oil saturation; K ro (S gi ) is the relative permeability of the oil phase at bound gas saturation; S gi is the bound gas saturation; Preferably, the calculation formula of the Welge coefficient ω is as follows (2): Where n g is the gas phase index, n o is the oil phase index.

5. The prediction method according to any one of claims 1 to 4, characterized in that: The production gas-oil ratio R s The calculation formula is as follows (3): In the formula, R si is the original gas-oil ratio, m 3 / m 3 ; R f is the extent of recovery of movable oil reserves; Preferably, the production gas-oil ratio increase rate R s The calculation formula of ' is as follows (4): In the formula, E d is the oil displacement efficiency, f.

6. The prediction method according to any one of claims 1 to 5, characterized in that: The natural decline rate D o The calculation formula is as follows (5): Where: T is the annual effective production days, that is, the annual calendar days multiplied by the production time rate, d; Q gc is the upper limit of FPSO’s gas processing capacity, m 3 / d;N o To utilize geological reserves, 10 4 m 3 .

7. The prediction method according to any one of claims 1 to 6, characterized in that: The development method of the deepwater gas drive oil field includes one of associated gas reinjection, external gas injection or natural gas top drive; Preferably, the deepwater gas drive oil field is in a production decline stage.

8. A device for predicting the natural decline rate of a deepwater gas drive oil field, characterized in that: The prediction device comprises: Basic parameter acquisition module, used to obtain basic parameters of target deepwater gas drive oil fields; The first calculation module is used to calculate the gas-oil mobility ratio M and the Welge coefficient ω according to the basic parameters; The second calculation module is used to calculate the production gas-oil ratio R based on the basic parameters, gas-oil mobility ratio M and Welge coefficient ω s Relationship and production gas-oil ratio increase rate R s 'Relational formula; The third calculation module is used to calculate the gas-oil ratio R according to the basic parameters and production s Relationship and production gas-oil ratio increase rate R s 'The natural decline rate D is calculated by the relationship o Relational; The prediction curve acquisition module is used to obtain the production gas-oil ratio R s , production gas-oil ratio increase rate R s ', natural decline rate D o The recovery rate of movable oil reserves R f The relationship between the natural decline rate D of the oil field is predicted o .

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; Wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for predicting the natural decline rate of a deepwater gas drive oil field as described in any one of claims 1-7.

10. A computer storage medium, characterized in that: The computer storage medium stores computer executable instructions, which, when executed by a processor, implement the method for predicting the natural decline rate of a deepwater gas drive oil field as described in any one of claims 1 to 7.

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