Gas reservoir gas content and productivity prediction method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a gas reservoir gas content and productivity prediction method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring at least two pieces of stratum attribute information of a to-be-explored gas reservoir; determining the formation pressure and the gas content of the to-be-explored gas reservoir according to the at least two pieces of formation attribute information; and predicting the productivity of the to-be-explored gas reservoir according to the at least two pieces of stratum attribute information, the stratum pressure and the gas content of the to-be-explored gas reservoir. By adopting the scheme, quantitative evaluation on the filling degree of the natural gas in the reservoir pores by utilizing the seismic data is realized for the first time, and a new tool is provided for accurately implementing the gas content of the natural gas in an earthquake. And the productivity prediction avoids the problem of low gas well yield prediction precision caused by relatively single consideration factors. Fusion calculation is carried out on the gas content, the formation pressure and the permeability of the gas reservoir, the precision of predicting the gas well productivity through the earthquake is improved, and a reliable basis is provided for gas reservoir reserve implementation and efficient oil field development.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of geophysics, and in particular to a method, device, electronic device and storage medium for predicting gas content and production capacity of a gas reservoir. Background Art

[0002] Gas-bearing seismic detection is one of the frontiers in the field of exploration geophysics, and the existing gas-bearing seismic detection technology has limitations. Most of the post-stack seismic amplitude, AVO attribute, and attenuation attribute gas reservoir identification methods are qualitative or semi-quantitative, and can only determine whether there is gas in the reservoir, but cannot determine the specific gas content.

[0003] Even the most quantitative gas saturation direct estimation gas reservoir identification method can only directly predict the volume occupied by the gas reservoir in the reservoir pores, but it is still impossible to accurately predict the gas production capacity of the reservoir using only gas saturation. The existing gas well pre-drilling capacity prediction methods have limitations. Currently, they mainly use formation coefficients or energy storage coefficients for prediction. These methods are relatively one-sided, and the factors considered are relatively single, so the prediction accuracy of gas reservoir capacity is poor. Summary of the invention

[0004] The embodiments of the present invention provide a method, device, electronic device and storage medium for predicting gas reservoir gas content and production capacity, so as to realize the prediction of gas reservoir gas content and production capacity, and improve the accuracy of seismic prediction of gas reservoir enrichment areas and high-yield gas wells.

[0005] In a first aspect, an embodiment of the present invention provides a method for predicting gas content and production capacity of a gas reservoir, comprising:

[0006] Acquire at least two formation attribute information of the gas reservoir to be explored; the formation attribute information includes P-wave velocity, porosity, saturation and density;

[0007] Determining the formation pressure and gas content of the gas reservoir to be explored based on the at least two formation attribute information;

[0008] The production capacity of the gas reservoir to be explored is predicted based on at least two formation property information, formation pressure and gas content of the gas reservoir to be explored.

[0009] In a second aspect, an embodiment of the present invention further provides a gas reservoir gas content and production capacity prediction device, comprising:

[0010] A formation attribute information acquisition module, used to acquire at least two formation attribute information of the gas reservoir to be explored; the formation attribute information includes P-wave velocity, porosity, saturation and density;

[0011] A gas content determination module, used to determine the formation pressure and gas content of the gas reservoir to be explored based on the at least two formation attribute information;

[0012] The gas reservoir productivity prediction module is used to predict the productivity of the gas reservoir to be explored based on at least two formation attribute information, formation pressure and gas content of the gas reservoir to be explored.

[0013] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0014] one or more processors;

[0015] A storage device for storing one or more programs;

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the gas reservoir gas content and production capacity prediction method described in any embodiment of the present invention.

[0017] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for predicting gas content and production capacity of a gas reservoir as described in any embodiment of the present invention.

[0018] The embodiment of the present invention provides a method, device, electronic device and storage medium for predicting the gas content and production capacity of a gas reservoir, by obtaining at least two formation attribute information of the gas reservoir to be explored; the formation attribute information includes longitudinal wave velocity, porosity, saturation and density; based on the at least two formation attribute information, the formation pressure and gas content of the gas reservoir to be explored are determined; based on the at least two formation attribute information of the gas reservoir to be explored, the formation pressure and gas content, the production capacity of the gas reservoir to be explored is predicted. The technical solution of the embodiment of the present invention solves the problem that conventional gas reservoir detection methods can only detect gas content but cannot predict the amount of natural gas contained in the reservoir, and for the first time realizes the quantitative evaluation of the degree of natural gas filling in the reservoir pores by seismic, providing a new tool for accurately determining natural gas reserves by seismic. The production capacity index prediction avoids the problem of low gas well production prediction accuracy caused by the conventional formation coefficient or energy storage coefficient method due to the relatively single consideration of factors. By integrating the gas content, formation pressure and permeability of gas storage capacity, the accuracy of seismic prediction of gas well production capacity is improved, providing a reliable basis for the confirmation of gas reservoir reserves, deployment of development wells and efficient development of oil fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Other features, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for the purpose of illustrating preferred embodiments and are not to be considered as limiting the present invention. Also, the same reference symbols are used throughout the drawings to represent the same parts. In the drawings:

[0020] Figure 1 It is a flow chart of a method for predicting gas content and production capacity of a gas reservoir provided in an embodiment of the present invention;

[0021] Figure 2 It is a schematic diagram of a gas reservoir gas content and production capacity prediction structure provided in an embodiment of the present invention;

[0022] Figure 3 is a schematic diagram of gas content of a QL16 well provided in an embodiment of the present invention;

[0023] Figure 4 A schematic diagram of gas content of a QL21 well provided in an embodiment of the present invention;

[0024] Figure 5 is a schematic diagram of formation pressure of each gas well provided in an embodiment of the present invention;

[0025] Figure 6 is a schematic diagram of the gas content of each gas well provided in an embodiment of the present invention;

[0026] Figure 7 A schematic diagram of the permeability of each gas well provided in an embodiment of the present invention;

[0027] Figure 8 is a schematic diagram of the production capacity of each gas well provided in an embodiment of the present invention;

[0028] Fig. 9 It is a structural schematic diagram of a gas reservoir gas content and production capacity prediction device provided in an embodiment of the present invention;

[0029] Fig.10 It is a structural schematic diagram of an electronic device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0031] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations (or steps) therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0032] Among them, the acquisition, storage, use and processing of data in the technical solution of this application are in compliance with the relevant provisions of national laws and regulations.

[0033] Figure 1 This is a flow chart of a method for predicting gas reservoir gas content and production capacity provided in an embodiment of the present invention. This embodiment is applicable to the case of predicting gas reservoir gas content and production capacity. The method of this embodiment can be executed by a gas reservoir gas content and production capacity prediction device, which can be implemented in hardware and / or software. The device can be configured in a server for predicting gas reservoir gas content and production capacity. The method specifically includes the following steps:

[0034] S110, obtaining at least two formation attribute information of the gas reservoir to be explored.

[0035] Among them, tight gas reservoirs are an important area for increasing oil and gas reserves and production. Due to their strong underground heterogeneity, low porosity, low permeability, and thin thickness, the degree of reserve realization is not high, the single-well gas reservoir production is low, and the stable production capacity is weak, which increases the cost of exploration and development. In terms of gas reservoir seismic prediction, there are many challenges such as rapid lateral changes in physical parameters, complex gas-water relationships, complex porosity-permeability relationships, and unclear main control factors for high production and enrichment. As a result, the existing gas content detection technology often has low accuracy in predicting reservoir distribution, making it difficult to accurately predict the high-yield enrichment zone of gas reservoirs, and the drilling cost is high. Therefore, the development of reservoir gas content prediction and production capacity prediction methods suitable for heterogeneous natural gas reservoirs is of great significance to meet the exploration, development and production needs of complex natural gas reservoirs, and has broad application prospects.

[0036] In an optional solution of the embodiment of the present invention, see Figure 2 Before predicting the gas content and production capacity of the gas reservoir to be explored, it is necessary to obtain the formation attribute information of the gas reservoir to be explored. The formation attribute information may refer to the attribute information that can describe the formation characteristics of the gas reservoir to be explored, and the formation attribute information includes but is not limited to P-wave velocity, porosity, saturation and density. Through the logging data and seismic inversion of the gas reservoir to be explored, elastic parameters such as P-wave velocity, S-wave velocity and density, reservoir parameters such as porosity, saturation and mud content, and modulus parameters such as fluid composition and mineral composition are obtained.

[0037] S120. Determine the formation pressure and gas content of the gas reservoir to be explored based on the at least two formation attribute information.

[0038] As an optional but non-limiting implementation, determining the formation pressure and gas content of the gas reservoir to be explored based on the at least two formation attribute information includes but is not limited to steps A1-A2:

[0039] Step A1: Determine the formation pressure and formation temperature of the gas reservoir to be explored based on the at least two formation attribute information.

[0040] Among them, the formation pressure can refer to the pressure acting on the fluid in the rock pores. Due to the strong heterogeneity of the gas reservoir to be explored and the poor permeability of the formation, the pore water is connected to the surface water, but its connectivity is poor, the fluid can penetrate slowly, and it is in a semi-closed state, so there is overburden formation pressure. At this time, the overburden formation pressure is shared by the pore fluid and the rock formation matrix, and the overburden formation pressure is greater than the formation pressure. Among them, the overburden formation pressure can refer to the pressure caused by the total weight of the overburden formation skeleton and the pore space fluid.

[0041] As an optional but non-limiting implementation, determining the formation pressure of the gas reservoir to be explored based on the at least two formation attribute information includes:

[0042] The formation pressure of the gas reservoir to be explored is calculated according to the following formula:

[0043] P p =P0-aP e (v / v e ) c

[0044] Among them, P p is the formation pressure, P0 is the overlying rock pressure, P e is the effective pressure of the formation in the normal compaction zone, v is the actual formation velocity, and v e is the formation velocity in the normal compaction zone; a and c are coefficients, which are related to the gas reservoir to be explored.

[0045] In an optional solution of the embodiment of the present invention, the determination of the formation pressure is related to the reservoir of the gas reservoir to be explored. The values ​​of coefficient a are different in different reservoirs, and the obtained formation pressure is also different. In the embodiment of the present invention, coefficient a=0.9043, c=-1.892.

[0046] In another optional solution of the embodiment of the present invention, P e It is the effective pressure of the formation in the normal compaction zone. The porosity of the rock in the normal compaction zone gradually decreases with the increase of burial depth. The fluid pressure in the pore system is always close to the hydrostatic pressure value P because the fluid is constantly discharged. w , so P e =P0-P w .

[0047] In another optional solution of the embodiment of the present invention, the formation temperature of the gas reservoir to be explored is:

[0048]

[0049] Among them, T z To calculate the ground temperature at depth point z, T0 is the temperature at the reference depth; dz i To calculate the thickness of each layer above the depth point z, N is the total number of points, q is the earth's heat flux, usually 50-60mW / m 2 ; i To calculate the thermal conductivity of each layer above the depth point z.

[0050]

[0051] Among them, λ i is the formation thermal conductivity, ρ is the density, V p is the longitudinal wave velocity, is the porosity, V sh is the mud content. Among them, the longitudinal wave velocity V p for:

[0052]

[0053] Step A2: Determine the gas content of the gas reservoir to be explored based on the at least two formation attribute information, the formation pressure and the formation temperature.

[0054] The gas content may refer to the total amount of natural gas contained in the rock formation converted to the standard state. In the embodiment of the present invention, the mass of the natural gas contained in the gas reservoir to be explored is used as the gas content.

[0055] As an optional but non-limiting implementation, determining the gas content of the gas reservoir to be explored based on the at least two formation attribute information, the formation pressure and the formation temperature includes:

[0056] The gas content of the gas reservoir to be explored is calculated according to the following formula:

[0057]

[0058] Among them, m g is the natural gas quality, P p is the formation pressure, S g is the gas saturation, is the porosity, M g is the relative molecular mass of natural gas, h is the formation thickness represented by each sample point, A is the area of ​​the bin, Z is the gas compression factor, T is the absolute temperature of natural gas, and R is the universal gas constant, 8.314 MPa·m3 / (mol·K).

[0059] In an optional solution of the embodiment of the present invention, the natural gas quality of the gas reservoir to be explored is the product of the gas reservoir volume and the gas reservoir density. The gas reservoir volume is the product of the gas reservoir stratum thickness and the stratum element area; the gas reservoir density is related to the stratum pressure.

[0060] In an optional solution of the embodiment of the present invention, taking gas reservoir A as an example, the gas content and production capacity of the gas reservoir A are predicted. Figure 3 Well QL16 is a high-yield industrial gas well with a gas production of 355,000 cubic meters. Well logging interpretation shows that the porosity of the high-quality reservoir is about 12% and the saturation is about 60%. Figure 3 The medium gas content curve is obtained by comprehensive prediction of porosity, saturation, pore pressure and formation temperature. The gas content of the main production layer No. 8 sand body is between 1.3-1.5 and the production capacity index reaches 60-100, indicating that this section of the gas reservoir has the characteristics of high production.

[0061] In another optional solution of the embodiment of the present invention, see Figure 4 Well QL21 is a low-yield gas well with a gas production of only 5,000 cubic meters. Well logging interpretation shows that the porosity of the high-quality reservoir is about 12% and the saturation is about 60%, which are close to the porosity and saturation of Well QL16. This shows that the gas reservoir A cannot accurately predict the gas production capacity of the reservoir using only porosity and saturation, and cannot determine the production capacity of the drilling well. The gas content curve of Well QL21 is obtained by comprehensive prediction of porosity, saturation, pore pressure and formation temperature. The gas content of the main production layer No. 8 sand body is less than 1, and the corresponding production capacity index is only about 20, which is significantly lower than that of Well QL16. This shows that the gas content and production capacity index predicted by the present invention have a good autocorrelation with the gas well production capacity, can indicate the production capacity of the reservoir, and are helpful to predict the enrichment degree of the gas reservoir and determine the location of high-yield wells.

[0062] S130: predicting the production capacity of the gas reservoir to be explored based on at least two formation property information, formation pressure and gas content of the gas reservoir to be explored.

[0063] Among them, productivity can refer to an indicator that can characterize the production capacity of a gas reservoir. Productivity is an important part of oil and gas field development planning and deployment, development plan design, development plan adjustment and development dynamic analysis.

[0064] As an optional but non-limiting implementation, the production capacity of the gas reservoir to be explored is predicted based on at least two formation attribute information, formation pressure and gas content of the gas reservoir to be explored, including but not limited to steps B1-B3:

[0065] Step B1: Determine the permeability of the gas reservoir to be explored based on at least two formation attribute information of the gas reservoir to be explored.

[0066] As an optional but non-limiting implementation, the determining the permeability of the gas reservoir to be explored based on at least two formation attribute information of the gas reservoir to be explored includes:

[0067] The permeability of the gas reservoir to be explored is calculated according to the following formula:

[0068]

[0069] Where K is the formation permeability, is the porosity; ε is the equivalent pore density, and ε is obtained by inverting the seismic P-wave impedance and reservoir porosity through the rock physics model. Here, α is the pore aspect ratio.

[0070] Step B2: Determine the productivity index of the gas reservoir to be explored based on the permeability, formation pressure and gas content of the gas reservoir to be explored.

[0071] Step B3: predicting the productivity of the gas reservoir to be explored based on the productivity index of the gas reservoir to be explored.

[0072] As an optional but non-limiting implementation, determining the productivity index of the gas reservoir to be explored based on the permeability, formation pressure and gas content of the gas reservoir to be explored includes:

[0073] The productivity index of the gas reservoir to be explored is calculated according to the following formula:

[0074] S=m g P p K

[0075] Among them, S is the capacity index, m g is the natural gas quality, P p is the formation pressure and K is the permeability.

[0076] The productivity of the gas reservoir to be explored is predicted based on the natural gas quality, formation pressure and permeability of the gas reservoir to be explored. Optionally, the embodiment of the present invention takes Well J203, Well J205 and Well J17 as examples, wherein Well J203 and Well J205 located in the lower part of the structure are two high productivity wells, and Well J17 located in the higher part of the structure is a low productivity well.

[0077] In an optional solution of the embodiment of the present invention, see Figure 5The target layer is located between the seismic layers J2s21 and J2s22. In the figure, Sand Group 8 represents the sand body of the No. 8 river channel, which is the main production layer of the oil field. The formation pressures measured in the reservoir sections of the three wells J17, J20 3 and J20 5 were 16.37, 21.75 and 25.9 MPa, respectively. It can be seen that the formation pressure of high-yield gas wells is higher than that of low-yield gas wells, which shows that the formation pressure plays a decisive role in the production capacity of the gas reservoir to be explored.

[0078] In another optional solution of the embodiment of the present invention, see Figure 6 , the gas content of Well J17, Well J203 and Well J205 was obtained. The low-yield gas Well J17 located at a high position has the lowest gas content, while the high-yield gas Well J205 located at a low position has the highest gas content. The seismic inversion results are consistent with the logging interpretation results, which shows that the gas content has nothing to do with the height of the sandstone reservoir, and the gas content is positively correlated with the production capacity of the gas well, which can accurately reflect the high-yield enrichment zone of the gas reservoir.

[0079] In another alternative embodiment of the present invention, see Figure 7 , the permeability of Well J17, Well J203 and Well J205 is obtained. The permeability of Well J17, which is located in a high position and has low gas production, is relatively high, while the permeability of Well J205 and Well 203, which are located in a low position and have high gas production, is relatively low. There is a certain difference between the seismic inversion results and the drilling results, which shows that the prediction of gas reservoir production capacity based only on permeability takes into account relatively single factors, and the obtained production capacity prediction results are inaccurate.

[0080] In another alternative embodiment of the present invention, see Figure 8 , the productivity of gas wells was comprehensively predicted by permeability, formation pressure and gas content, and the productivity of J17, J203 and J205 wells was obtained; among them, the productivity was characterized by the open flow rate per meter. The open flow rates per meter of J17, J203 and J205 wells were 0.0029, 0.026 and 0.048 cubic meters respectively. The unit open flow rate of J17 well with low gas production located in the high position was the lowest, while the unit open flow rate of J205 well with high gas production located in the low position was the highest. The seismic inversion results were consistent with the drilling results, which showed that the comprehensive prediction of gas reservoir permeability, formation pressure and gas content could effectively reflect the productivity of gas reservoirs and accurately reflect the high-yield enrichment zone of gas reservoirs.

[0081] The embodiment of the present invention provides a method for predicting the gas content and production capacity of a gas reservoir, by obtaining at least two formation attribute information of the gas reservoir to be explored; the formation attribute information includes longitudinal wave velocity, porosity, saturation and density; based on the at least two formation attribute information, the formation pressure and gas content of the gas reservoir to be explored are determined; based on the at least two formation attribute information of the gas reservoir to be explored, the formation pressure and gas content, the production capacity of the gas reservoir to be explored is predicted. The technical solution of the embodiment of the present invention solves the problem that conventional gas reservoir detection methods can only detect gas content but cannot predict the amount of natural gas contained in the reservoir, and for the first time realizes the quantitative evaluation of the degree of natural gas filling in the reservoir pores by seismic, providing a new tool for accurately determining natural gas reserves by seismic. The production capacity index prediction avoids the problem of low gas well production prediction accuracy caused by the conventional formation coefficient or energy storage coefficient method due to the relatively single consideration of factors. By integrating the gas content, formation pressure and permeability of gas storage capacity, the accuracy of seismic prediction of gas well production capacity is improved, providing a reliable basis for the confirmation of gas reservoir reserves, deployment of development wells and efficient development of oil fields.

[0082] Fig. 9 is a schematic diagram of the structure of a gas reservoir gas content and production capacity prediction device provided in an embodiment of the present invention, the device comprises: a formation attribute information acquisition module 910, a gas content determination module 920 and a gas reservoir production capacity prediction module 930; wherein,

[0083] The formation attribute information acquisition module 910 is used to acquire at least two formation attribute information of the gas reservoir to be explored; the formation attribute information includes P-wave velocity, porosity, saturation and density;

[0084] A gas content determination module 920 is used to determine the formation pressure and gas content of the gas reservoir to be explored based on the at least two formation attribute information;

[0085] The gas reservoir productivity prediction module 930 is used to predict the productivity of the gas reservoir to be explored based on at least two formation property information, formation pressure and gas content of the gas reservoir to be explored.

[0086] Based on the above embodiment, optionally, the gas content determination module includes:

[0087] Determining the formation pressure and the formation temperature of the gas reservoir to be explored based on the at least two formation attribute information;

[0088] The gas content of the gas reservoir to be explored is determined based on the at least two formation property information, the formation pressure and the formation temperature.

[0089] Based on the above embodiment, optionally, the gas content determination module further includes:

[0090] The formation pressure of the gas reservoir to be explored is calculated according to the following formula:

[0091] P p =P0-aP e (v / v e ) c

[0092] Among them, P p is the formation pressure, P0 is the overlying rock pressure, P e is the effective pressure of the formation in the normal compaction zone, v is the actual formation velocity, and v e is the formation velocity in the normal compaction zone; a and c are coefficients, which are related to the gas reservoir to be explored.

[0093] Based on the above embodiment, optionally, the gas content determination module further includes:

[0094] The gas content of the gas reservoir to be explored is calculated according to the following formula:

[0095]

[0096] Among them, m g is the natural gas quality, P p is the formation pressure, S g is the gas saturation, is the porosity, M g is the relative molecular mass of natural gas, h is the formation thickness represented by each sample point, A is the area of ​​the bin, Z is the gas compression factor, T is the absolute temperature of natural gas, and R is the universal gas constant, 8.314 MPa·m3 / (mol·K).

[0097] Based on the above embodiment, optionally, the gas reservoir production capacity prediction module includes:

[0098] Determining the permeability of the gas reservoir to be explored based on at least two formation attribute information of the gas reservoir to be explored;

[0099] Determining the productivity index of the gas reservoir to be explored based on the permeability, formation pressure and gas content of the gas reservoir to be explored;

[0100] The productivity of the gas reservoir to be explored is predicted based on the productivity index of the gas reservoir to be explored.

[0101] Based on the above embodiment, optionally, the gas reservoir production capacity prediction module further includes:

[0102] The permeability of the gas reservoir to be explored is calculated according to the following formula:

[0103]

[0104] Where K is the formation permeability, is the porosity; ε is the equivalent pore density, and ε is obtained by inverting the seismic P-wave impedance and reservoir porosity through the rock physics model.

[0105] Based on the above embodiment, optionally, the gas reservoir production capacity prediction module further includes:

[0106] The productivity index of the gas reservoir to be explored is calculated according to the following formula:

[0107] S=m g P p K

[0108] Among them, S is the capacity index, m g is the natural gas quality, P p is the formation pressure and K is the permeability.

[0109] The gas reservoir gas content and production capacity prediction device provided in the embodiments of the present invention can execute the gas reservoir gas content and production capacity prediction method provided in any of the above embodiments of the present invention, and has the corresponding functions and beneficial effects of executing the gas reservoir gas content and production capacity prediction method. For detailed processes, please refer to the relevant operations of the gas reservoir gas content and production capacity prediction method in the above embodiments.

[0110] Fig.10 1 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. The electronic device 10 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.

[0111] like Fig.10As 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. An input / output (I / O) interface 15 is also connected to the bus 14.

[0112] 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.

[0113] 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, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a gas reservoir gas content and production capacity prediction method.

[0114] In some embodiments, the gas reservoir gas content and productivity prediction method can 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 can 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 gas reservoir gas content and productivity prediction method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the gas reservoir gas content and productivity prediction method in any other appropriate manner (for example, by means of firmware).

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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).

[0119] 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.

[0120] 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.

[0121] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0122] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for predicting gas content and production capacity of a gas reservoir, characterized in that: The method comprises: Acquire at least two formation attribute information of the gas reservoir to be explored; the formation attribute information includes P-wave velocity, porosity, saturation and density; Determining the formation pressure and gas content of the gas reservoir to be explored based on the at least two formation attribute information; The production capacity of the gas reservoir to be explored is predicted based on at least two formation property information, formation pressure and gas content of the gas reservoir to be explored.

2. The method according to claim 1, characterized in that Determining the formation pressure and gas content of the gas reservoir to be explored based on the at least two formation attribute information includes: Determining the formation pressure and the formation temperature of the gas reservoir to be explored based on the at least two formation attribute information; The gas content of the gas reservoir to be explored is determined based on the at least two formation property information, the formation pressure and the formation temperature.

3. The method according to claim 2, characterized in that Determining the formation pressure of the gas reservoir to be explored based on the at least two formation attribute information includes: The formation pressure of the gas reservoir to be explored is calculated according to the following formula: P p =P0-aP e (v / v e , c Among them, P p is the formation pressure, P0 is the overlying rock pressure, P e is the effective pressure of the formation in the normal compaction zone, v is the actual formation velocity, and v e is the formation velocity in the normal compaction zone; a and c are coefficients, which are related to the gas reservoir to be explored.

4. The method according to claim 2, characterized in that: Determining the gas content of the gas reservoir to be explored based on the at least two formation attribute information, the formation pressure and the formation temperature includes: The gas content of the gas reservoir to be explored is calculated according to the following formula: Among them, m g is the natural gas quality, P p is the formation pressure, S g is the gas saturation, is the porosity, M g is the relative molecular mass of natural gas, h is the formation thickness represented by each sample point, A is the area of ​​the bin, Z is the gas compression factor, T is the absolute temperature of natural gas, and R is the universal gas constant, 8.314 Mpa·m 3 / (mol·K).

5. The method according to claim 1, characterized in that The method of predicting the production capacity of the gas reservoir to be explored based on at least two formation attribute information, formation pressure and gas content of the gas reservoir to be explored includes: Determining the permeability of the gas reservoir to be explored based on at least two formation attribute information of the gas reservoir to be explored; Determining the productivity index of the gas reservoir to be explored based on the permeability, formation pressure and gas content of the gas reservoir to be explored; The productivity of the gas reservoir to be explored is predicted based on the productivity index of the gas reservoir to be explored.

6. The method according to claim 5, characterized in that The step of determining the permeability of the gas reservoir to be explored based on at least two formation attribute information of the gas reservoir to be explored comprises: The permeability of the gas reservoir to be explored is calculated according to the following formula: Where K is the formation permeability, is the porosity; ε is the equivalent pore density, and ε is obtained by inverting the seismic P-wave impedance and reservoir porosity through the rock physics model.

7. The method according to claim 5, characterized in that Determining the productivity index of the gas reservoir to be explored based on the permeability, formation pressure and gas content of the gas reservoir to be explored includes: The productivity index of the gas reservoir to be explored is calculated according to the following formula: S=m g P g K Among them, S is the capacity index, m g is the natural gas quality, P p is the formation pressure and K is the permeability.

8. A gas reservoir gas content and production capacity prediction device, characterized in that: The device comprises: A formation attribute information acquisition module, used to acquire at least two formation attribute information of the gas reservoir to be explored; the formation attribute information includes P-wave velocity, porosity, saturation and density; A gas content determination module, used to determine the formation pressure and gas content of the gas reservoir to be explored based on the at least two formation attribute information; The gas reservoir productivity prediction module is used to predict the productivity of the gas reservoir to be explored based on at least two formation attribute information, formation pressure and gas content of the gas reservoir to be explored.

9. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the gas reservoir gas content and production capacity prediction method as described in any one of claims 1-7.

10. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions are used to execute the gas reservoir gas content and production capacity prediction method as described in any one of claims 1-7 when executed by a computer processor.

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