A method, system, apparatus, and medium for quantitatively predicting production of a fracture-vug reservoir

Abstract

The application discloses a method, system, device and medium for quantitatively predicting production of a fracture-cave type reservoir, and the method comprises the following steps: obtaining reservoir P-wave impedance data through seismic inversion; counting upper limit values of the P-wave impedance of a cave type and a pore type revealed by an existing drilling, determining a P-wave impedance threshold value of a static reservoir sculpture, and obtaining a relative volume of the reservoir by sculpting P-wave impedance data smaller than the P-wave impedance threshold value, and further obtaining reservoir morphology and spatial relationship; dividing a range controlled by a single well and a range controlled by a connected well group; calculating static relative volumes of different types of reservoirs in a control unit of the single well and the connected well group; respectively counting cumulative oil and water production of a shut-in well; performing correlation fitting on the static relative volumes and the oil and water production to obtain a functional relationship; and converting the relative volume of the reservoir into dynamic matching production, to obtain predicted cumulative production and remaining production of each well. The method solves the problem that it is difficult to determine static prediction of production of a fracture-cave type carbonate reservoir.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas reservoir exploration and development, and relates to a method, system, equipment and medium for quantitatively predicting the production of fractured-vuggy reservoirs. Background Technology

[0002] Currently, with increasing energy demand and in-depth oil and gas field exploration, fractured-vuggy carbonate oil and gas reservoirs are gradually becoming new oil and gas reserve targets and key areas for exploration and development. The reservoirs of most fractured-vuggy carbonate oil and gas reservoirs utilize secondary fractures, pores, and cavities as effective storage spaces. The fracture-vuggy development zones in carbonate reservoirs appear as "elliptical, beaded, or banded" on amplitude variation maps. In engineering, a combination of vertical and horizontal wells is commonly used for development, and acid fracturing is frequently employed for production enhancement. However, when the fracture-vuggy development zones in carbonate reservoirs are isolated fracture-vuggy systems, their spatial distribution is discontinuous, causing differences in the fluid seepage characteristics between the reservoir and those in homogeneous sandstone oil reservoirs. Dynamic prediction studies of this type of oil and gas reservoir cannot utilize the seepage theory of sandstone oil and gas reservoirs. Compared to production capacity studies of homogeneous sandstone oil and gas reservoirs, there are fewer studies using static methods to predict the production of fractured-vuggy carbonate oil and gas reservoirs.

[0003] Commonly used yield forecasting methods both domestically and internationally include neural networks, the declining curve method, the Weng's cycle method, and combined forecasting. [1] However, conventional methods are no longer suitable for complex oil and gas reservoirs with highly nonlinear characteristics. There is very little research on static production calculation methods for highly heterogeneous fractured-vuggy carbonate oil and gas reservoirs; most research focuses on dynamic reserve calculation methods. Depending on the required parameters and the adaptability of the methods, commonly used methods include the mass balance method. [2-3] Modern declining output method [4-6] Water drive curve method [7-19] Establish a system of dynamic reserve calculation methods. Dynamic methods can only characterize the reserves of utilized oil and gas units, and their control range is limited. They cannot predict the reserves and production of unutilized oil and gas reservoirs. Existing static reserve calculation methods mainly include the volumetric method and the cavernous pore volume comparison method. The volumetric method formula is: Where: N - crude oil geological reserves, 10 4 t; A - Oil-bearing area, km² 2 h - Effective thickness of the evaluation (calculation) unit, in meters; - Effective porosity of the oil reservoir, decimal; Soi - Original formation oil saturation, decimal; Boi - Original crude oil volume factor, dimensionless; ρ - Density of degassed crude oil at the surface, t / m³ 3Existing methods all require determining the reservoir's porosity, thickness, and area before effectively calculating reserve size. Reservoir area and thickness are relatively easy to obtain using seismic inversion, while porosity often requires multivariate regression calculations using well logging curves. This method has good applicability in the quantitative calculation of reserves in conventional clastic oil and gas reservoirs. However, due to the extremely high heterogeneity of karst fractured-vuggy reservoirs, well logging curves often cannot represent the wellbore conditions. Many high-yield wells experience venting during drilling, and there are no well logging curves for the target interval, indicating that production is achieved through acid fracturing. Therefore, relying on the volumetric method for calculation has a major drawback: it cannot accurately determine the reservoir porosity.

[0004] Existing quantitative porosity prediction methods mainly rely on multiple regression or cloud transformation between well logging curves and well logging porosity. However, these methods lack a material basis in karst carbonate reservoirs, meaning they cannot interpret porosity through well logging. Karst carbonate reservoirs are highly heterogeneous, with significant differences between the wellbore environment and the surrounding environment. Furthermore, there is a lack of effective well logging data within large cavernous reservoirs. This results in either unrepresentative porosity or a complete absence of well logging interpretation. Consequently, conventional volumetric methods for quantitatively calculating reservoir reserves lead to significant discrepancies between static estimates and actual dynamic data. Volumetric methods and other quantitative methods based on porosity calculations are difficult to apply to karst fractured-vuggy oil and gas reservoirs. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method, system, equipment and medium for quantitatively predicting the production of fractured-vuggy reservoirs. This method is simple and easy to implement, and the evaluation results are in good agreement with the production dynamics, thus solving the problem that it is difficult to determine the static production of fractured-vuggy carbonate reservoirs.

[0006] To achieve the above objectives, the present invention employs the following technical solution:

[0007] A method for quantitatively predicting the production of fractured-vuggy reservoirs includes the following steps;

[0008] Step 1: Obtain P-wave impedance data for cavernous and porous reservoirs through seismic inversion;

[0009] Step 2: Statistically analyze the upper limit values ​​of P-wave impedance revealed by existing wells for cave-type and pore-type reservoirs, determine the P-wave impedance threshold value for static reservoir carving, carve P-wave impedance data smaller than the P-wave impedance threshold value, obtain the relative volume of cave-type and pore-type reservoirs, and then obtain the morphology and spatial relationship of cave-type and pore-type reservoirs.

[0010] Step 3: Based on reservoir morphology and spatial relationships, delineate the control range of a single well and the control range of interconnected well groups;

[0011] Step 4: Based on the control units defined in Step 3, calculate the static relative volume of different types of reservoirs within the control units of a single well and connected well groups.

[0012] Step 5: Compile statistics on the cumulative oil and water production of the shut-in wells;

[0013] Step six: Use the static relative volume calculated in step four and the oil and water production rates statistically analyzed in step five to perform correlation fitting, and obtain the functional relationship between the static relative volume and the dynamic production rate.

[0014] Step 7: Using the functional relationship obtained in Step 6, the relative reservoir volume in Step 2 is converted into a production rate that matches the dynamics, thereby obtaining the predicted cumulative production and remaining production of each well.

[0015] Preferably, in step one, unconstrained reflection coefficient inversion of seismic data is performed, and the resulting reflection coefficient sequence and low-frequency trend model are combined and integrated for wave impedance calculation, thereby obtaining P-wave impedance data.

[0016] Furthermore, after obtaining the P-wave impedance data, the existing drilling information is used to perform quality control on the obtained P-wave impedance data to obtain P-wave impedance data that conforms to the geological understanding of the study area.

[0017] Preferably, step two includes performing well logging rock physics analysis to obtain well logging P-wave impedance frequency histograms for different types of reservoirs and non-reservoirs, determining the P-wave impedance threshold values ​​for static carving of different types of reservoirs and non-reservoirs, performing static carving based on the threshold values, and then obtaining the three-dimensional spatial reservoir morphology and spatial relationships.

[0018] Preferably, the specific process of step three is to conduct statistical analysis of the production status of drilled wells in the study area to obtain the understanding of the connectivity between well groups, and then, in combination with the reservoir morphology and spatial relationship obtained in step two, to delineate the control range of a single well and the control range of connected well groups.

[0019] Preferably, step five involves statistically analyzing the oil, gas, and water production data of the shut-in wells in different control units within the study area.

[0020] Preferably, in step six, the functional relationship between the static relative volume and the dynamic production volume is: y = f(x), where y is the production volume, x is the reservoir carving volume, and f is the fitting function relationship between the production volume and the reservoir carving volume.

[0021] A system for quantitatively predicting the production of fractured-vuggy reservoirs, comprising:

[0022] The seismic inversion module is used to obtain P-wave impedance data of cavernous and porous reservoirs through seismic inversion.

[0023] The static sculpting module is used to statistically analyze the upper limit of P-wave impedance of cave-type and pore-type reservoirs revealed by existing drilling, determine the P-wave impedance threshold value for static reservoir sculpting, sculpt P-wave impedance data volumes smaller than the P-wave impedance threshold value, obtain the relative volume of cave-type and pore-type reservoirs, and then obtain the morphology and spatial relationship of cave-type and pore-type reservoirs.

[0024] The control unit partitioning module is used to partition the control range of a single well and the control range of a connected well group based on reservoir morphology and spatial relationships.

[0025] The static relative volume calculation module is used to calculate the static relative volume of different types of reservoirs in a single well and connected well group control units, based on the control unit division module.

[0026] The cumulative production statistics module is used to separately calculate the cumulative oil and water production of shut-in wells;

[0027] The correlation fitting module is used to perform correlation fitting between the static relative volume calculated by the cumulative production statistics module and the oil and water production volume statistically obtained in step five, so as to obtain the functional relationship between the static relative volume and the dynamic production volume.

[0028] The static volume conversion module is used to convert the relative reservoir volume of the static carving module into a production volume that matches the dynamic model, based on the functional relationship obtained by the correlation fitting module, thereby obtaining the predicted cumulative production and remaining production of each well.

[0029] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the method for quantitatively predicting the production of fractured-vuggy reservoirs as described in any of the preceding claims.

[0030] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method for quantitatively predicting the production of fractured-vuggy reservoirs as described in any of the preceding claims.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] This invention, based on geostatistically inverted P-wave impedance data, carves out the "relative" volume of cavernous and porous reservoirs according to reservoir type, eliminating the need for correlation fitting with logging porosity and thus directly avoiding the calculation of porosity. The cumulative production of closed wells is used to correct the carved "relative" volume within the control unit, thereby correcting the overall reservoir volume. This relationship allows for the calculation of predicted cumulative production and remaining production for each well, achieving the goal of using seismic information to address the heterogeneity problem of carbonate rocks. Based on seismic data, it fully utilizes the spatial predictive nature of seismic data to characterize the heterogeneity of carbonate reservoirs. Since the target interval of fractured-vuggy carbonate oil and gas reservoirs lacks logging data and the logging data is not representative, this technical solution avoids the heavy reliance on logging curves in existing conventional techniques. It directly connects the seismically inverted P-wave impedance data with the production volume of producing wells, utilizing the lateral variation advantage of 3D seismic data to quantitatively calculate the volume of unexplored and undeveloped oil and gas reservoirs. This method provides quantitative calculation results that match production well, which is beneficial for predicting stable oilfield production, preparing technological processes, modifying oilfield surface construction projects, formulating development plans, and adjusting production measures. The method is simple and easy to implement, and the evaluation results are consistent with production dynamics, thus solving, to some extent, the problem of difficulty in determining the static production of fractured-vuggy carbonate reservoirs. Attached Figure Description

[0033] Figure 1 This is a flowchart of the method for quantitatively predicting the production of fractured-vuggy reservoirs according to the present invention;

[0034] Figure 2 This is a cross-sectional view of lithological bodies and P-wave impedance obtained from well geostatistical inversion according to the present invention.

[0035] Figure 3 This is a three-dimensional display diagram of the relative volume of the static engraving of the present invention;

[0036] Figure 4 This is a fitting graph showing the relationship between reservoir carving volume and production rate in this invention. Detailed Implementation

[0037] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0038] It should be noted that the terms “front,” “back,” “left,” “right,” “up,” and “down” used in the following description refer to the directions shown in the attached diagram, while the terms “inside” and “outside” refer to the directions toward or away from the geometric center of a specific component, respectively.

[0039] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the specification of this invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0040] like Figure 1 The method for quantitatively predicting the production of fractured-vuggy reservoirs according to the present invention includes the following steps:

[0041] Step 1: Seismic inversion.

[0042] Wave impedance data volume is a crucial parameter in this invention. The three-dimensional wave impedance data volume needs to be obtained using deterministic inversion and geostatistical inversion methods. Seismic inversion utilizes known seismic data, eliminates wavelet influence, retains the reflection coefficients, and then calculates physical parameters reflecting changes in stratigraphic properties from the reflection coefficients. Wave impedance is in the reflectivity domain. First, unconstrained reflection coefficient inversion is performed on the seismic data. The resulting reflection coefficient sequence and low-frequency trend model are then combined and integrated for wave impedance calculation.

[0043] Seismic reservoir prediction and inversion based on time-domain pure wave data mainly includes three aspects: 1. Seismic data quality control and analysis: Quality control of seismic data is carried out. The quality control standard is that the seismic data at the target layer is not affected by the acquisition footprint. At the same time, the dominant frequency of the seismic data at the target layer is analyzed. Combined with forward modeling research, the reservoir development range is identified through special geological body identification technology. 2. Deterministic inversion: ① Conduct multi-well seismic calibration to determine the comprehensive wavelet used for inversion, including wavelet length, wavelet amplitude and phase; ② Establish a reasonable low-frequency model, which includes the initial low-frequency model establishment, inversion iteration, and determination of the reasonable low-frequency model; ③ Inversion parameter testing, which includes sparsity constraint factor testing, seismic signal-to-noise ratio testing, wavelet scale factor testing, and merging frequency testing; ④ Post-stack deterministic inversion result analysis. 3. Geostatistical Inversion: ① Based on the fracture-cavity boundary results, reservoir and non-reservoir probability volumes are established through lithofacies fluid probability analysis; ② Based on deterministic inversion, cavernous reservoir development areas are identified through lithofacies fluid probability analysis; combined with the previous reservoir probability volume, fracture-cavity reservoir probability volumes are derived; ③ Seismic data and wavelets are loaded, and the tested geostatistical parameters are called to carry out geostatistical inversion, generating several equally probable geostatistical inversion results. The purpose of geostatistical inversion is to fuse multiple information sources to invert reasonable cavernous and fracture-cavity reservoirs.

[0044] Finally, P-wave impedance data for different types of reservoirs and non-reservoirs were obtained through seismic inversion.

[0045] Step 2: Static sculpting of relative reservoir volume.

[0046] Quality control of P-wave impedance data obtained from seismic inversion was performed using existing drilling information. Rock physics analysis suggests that carbonate reservoirs and P-wave impedance are negatively correlated, meaning that the smaller the P-wave impedance value, the more developed the reservoir.

[0047] By statistically analyzing the upper limits of P-wave impedance revealed in existing wells for cavernous and pore-shaped reservoirs, well logging petrophysical analysis was performed to obtain P-wave impedance frequency histograms for different reservoir types and non-reservoir types. This allowed for the determination of P-wave impedance threshold values ​​for static reservoir sculpting in different reservoir types and non-reservoir types. Then, by sculpting P-wave impedance data volumes below the threshold values, the relative volumes of different reservoir types could be obtained, leading to the three-dimensional spatial morphology and spatial relationships of cavernous and pore-shaped reservoirs.

[0048] Step 3: Division of control units for single wells or interconnected well groups.

[0049] Step two allows for the carving of cave-type and perforated reservoir morphologies and spatial relationships. By analyzing the production status of wells within the area, the connectivity between well groups can be understood, and the control range of a single well and the control range of connected well groups can be delineated.

[0050] Step 4: Calculate the static relative volume of a single well or a connected well group.

[0051] This step involves calculating the static relative volume of different types of reservoirs within the control units of a single well and connected well groups, based on the control units defined in step three.

[0052] Step 5: Cumulative production statistics for single wells or interconnected well groups.

[0053] The main purpose of this step is to obtain the cumulative production of the shut-in wells, which can effectively calibrate the relative volume obtained in step two. Based on the actual situation in the study area, the cumulative production of oil, gas, and water from the shut-in wells is statistically analyzed separately. Considering the volume compression effect of natural gas in ultra-deep formations, generally only the dynamic fluid production of a single well or connected well group is statistically analyzed, that is, the cumulative production of oil and water.

[0054] Step 6: Fitting the correlation between static volume and dynamic reserves.

[0055] By using the static relative volume of the reservoir calculated in step four and the production volume (oil and water) statistically obtained in step five, a correlation fitting is performed to obtain the functional relationship between the static relative volume and the dynamic production volume: y = f(x), where y is the production volume, x is the reservoir carving volume, and f is the fitting function relationship between the production volume and the reservoir carving volume.

[0056] Step 7: Static volume conversion.

[0057] Using the static volume conversion function obtained in step six, the relative reservoir volume in step two is converted into a production volume that matches the dynamics, thereby estimating the predicted cumulative production and remaining production of each well.

[0058] The specific embodiments of the present invention will be further described in detail below. The illustrative examples and descriptions of the present invention are used to explain the present invention, but are not intended to limit the present invention.

[0059] 1. Based on preliminary research, the Zhonggu 43II block of Tarim Oilfield was selected for research based on a combination of dynamic and static analysis. The carbonate reservoirs in the study area are mainly composed of pore and cavern reservoirs.

[0060] 2. The sensitive elastic parameter of pore and cavern reservoirs is the P-wave impedance, which can be obtained from lithological bodies and P-wave impedance using post-stack geostatistical inversion, such as... Figure 2 As shown. Comparison with actual wells yielded a P-wave impedance threshold of 1.65*10⁻⁶ for the carbonate reservoir. 7 kg / m 3 *m / s.

[0061] 3. The reservoir is sculpted based on the longitudinal wave impedance threshold value to obtain the relative volume of the reservoir, such as... Figure 3 As shown.

[0062] 4. The production output of each shut-in well in this block is shown in Table 1.

[0063] Table 1. Statistics on Well Production in the Work Area

[0064]

[0065] Analysis and statistics on the relationship between the cumulative fluid production of each shut-in well and the volume of reservoir erosion encountered during drilling revealed a significant correlation, such as... Figure 4 As shown, the following relationship can be fitted between the production volume and the relative volume of the static carving, and this relationship can be used to convert the relative volume of the static carving into a production volume that matches the dynamic model. This allows for the estimation of the potential cumulative production and remaining production of oil and gas reservoir units controlled by other producing wells in the block, enabling timely adjustments to measures or development plans.

[0066] Liquid production = 0.1338e^(0.0006 * engraving volume).

[0067] The following are embodiments of the apparatus of the present invention, which can be used to execute embodiments of the method of the present invention. For details not omitted in the apparatus embodiments, please refer to the embodiments of the method of the present invention.

[0068] In another embodiment of the present invention, a system for quantitatively predicting the production of fractured-vuggy reservoirs is provided. This system can be used to implement the above-mentioned method for quantitatively predicting the production of fractured-vuggy reservoirs. Specifically, the system for quantitatively predicting the production of fractured-vuggy reservoirs includes a seismic inversion module, a static carving module, a control unit partitioning module, a static relative volume calculation module, a cumulative production statistics module, a correlation fitting module, and a static volume conversion module.

[0069] The system comprises several modules: a seismic inversion module to obtain P-wave impedance data for cavernous and pore-shaped reservoirs; a static sculpting module to statistically analyze the upper limits of P-wave impedance revealed by existing wells for cavernous and pore-shaped reservoirs, determine the P-wave impedance threshold for static reservoir sculpting, sculpt P-wave impedance data volumes smaller than the threshold, obtain the relative volumes of cavernous and pore-shaped reservoirs, and thus determine their morphology and spatial relationships; a control unit partitioning module to delineate the control range of a single well and the control range of connected well groups based on reservoir morphology and spatial relationships; and a static relative volume calculation module to partition the control unit partitioning module. The control unit calculates the static relative volume of different types of reservoirs within the control units of a single well and connected well groups; the cumulative production statistics module is used to statistically analyze the cumulative oil and water production of shut-in wells; the correlation fitting module is used to perform correlation fitting between the static relative volume calculated by the cumulative production statistics module and the oil and water production statistics in step five, obtaining a functional relationship between the static relative volume and the dynamic production; the static volume conversion module is used to convert the reservoir relative volume of the static carving module into a production volume that matches the dynamic production through the functional relationship obtained by the correlation fitting module, thereby obtaining the predicted cumulative production and remaining production of each well.

[0070] In another embodiment of the present invention, a terminal device is provided, comprising a processor and a memory. The memory stores a computer program, the computer program including program instructions, and the processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), or field-programmable gate arrays (FPGAs). Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., are the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to realize the corresponding method flow or corresponding function; the processor described in this embodiment of the invention can be used in the operation of a method for quantitatively predicting the production of fractured-vuggy reservoirs, including: Step 1, obtaining P-wave impedance data of cave-type and porosity-type reservoirs through seismic inversion; Step 2, statistically analyzing the upper limit values ​​of P-wave impedance revealed by existing wells for cave-type and porosity-type reservoirs, determining the P-wave impedance threshold value for static reservoir carving, carving P-wave impedance data smaller than the P-wave impedance threshold value, and obtaining the phase of cave-type and porosity-type reservoirs. The process involves several steps: First, determining the volume of the reservoir to obtain the morphology and spatial relationships of cavernous and porous reservoirs. Second, using the reservoir morphology and spatial relationships, defining the control area of ​​a single well and the control area of ​​connected well groups. Third, calculating the static relative volume of different types of reservoirs within the control units of a single well and connected well groups based on the control units defined in Step 3. Fourth, statistically analyzing the cumulative oil and water production of shut-in wells. Fifth, performing correlation fitting between the static relative volume calculated in Step 4 and the oil and water production statistics from Step 5 to obtain a functional relationship between the static relative volume and the dynamic production. Sixth, using the functional relationship obtained in Step 6, converting the relative reservoir volume from Step 2 into a production volume that matches the dynamic relationship, thereby obtaining the predicted cumulative production and remaining production of each well.

[0071] In another embodiment, the present invention also provides a computer-readable storage medium (Memory), which is a memory device in a terminal device for storing programs and data. It is understood that the computer-readable storage medium here may include both the built-in storage medium in the terminal device and extended storage media supported by the terminal device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor, which may be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here may be high-speed RAM or non-volatile memory, such as at least one disk storage device.

[0072] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the method for quantitatively predicting the production of fractured-vuggy reservoirs in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by the processor as follows: Step 1, obtaining P-wave impedance data of cave-type and pore-type reservoirs through seismic inversion; Step 2, statistically analyzing the upper limit values ​​of P-wave impedance of cave-type and pore-type reservoirs revealed by existing wells, determining the P-wave impedance threshold value for static reservoir carving, carving P-wave impedance data smaller than the P-wave impedance threshold value, obtaining the relative volume of cave-type and pore-type reservoirs, and thus obtaining the morphology and spatial relationship of cave-type and pore-type reservoirs; Step 3 Step 3: Based on reservoir morphology and spatial relationships, delineate the control range of a single well and the control range of connected well groups. Step 4: Based on the control units delineated in Step 3, calculate the static relative volume of different types of reservoirs within the control units of a single well and connected well groups. Step 5: Statistically analyze the cumulative oil and water production of shut-in wells. Step 6: Perform correlation fitting between the static relative volume calculated in Step 4 and the oil and water production statistics in Step 5 to obtain a functional relationship between the static relative volume and the dynamic production. Step 7: Using the functional relationship obtained in Step 6, convert the relative reservoir volume from Step 2 into a production volume that matches the dynamics, thereby obtaining the predicted cumulative production and remaining production of each well.

[0073] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0074] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0075] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0076] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0077] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0078] It should be understood that the above description is for illustrative purposes and not for limitation. Many embodiments and applications beyond the provided examples will be apparent to those skilled in the art upon reading the above description. Therefore, the scope of this teaching should not be determined by reference to the above description, but rather by reference to the foregoing claims and the full scope of their equivalents. For purposes of completeness, all articles and references, including patent applications and publications, are incorporated herein by reference. The omission of any aspect of the subject matter disclosed herein in the foregoing claims is not intended as a waiver of that subject matter, nor should it be construed as an indication that the applicant has not considered that subject matter as part of the disclosed inventive subject matter.

Claims

1. A method for quantitatively predicting the production of fractured-vuggy reservoirs, characterized in that, Includes the following steps; Step 1: Obtain P-wave impedance data for cavernous and porous reservoirs through seismic inversion; Step 2: Statistically analyze the upper limit values ​​of P-wave impedance revealed by existing wells for cave-type and pore-type reservoirs, determine the P-wave impedance threshold value for static reservoir carving, carve P-wave impedance data smaller than the P-wave impedance threshold value, obtain the relative volume of cave-type and pore-type reservoirs, and then obtain the morphology and spatial relationship of cave-type and pore-type reservoirs. Well logging rock physics analysis is performed to obtain well logging P-wave impedance frequency histograms for different types of reservoirs and non-reservoirs. The P-wave impedance threshold values ​​for static carving of different types of reservoirs and non-reservoirs are determined. Based on the threshold values, static carving is performed to obtain the three-dimensional spatial morphology and spatial relationships of the reservoir. Step 3: Based on reservoir morphology and spatial relationships, delineate the control range of a single well and the control range of interconnected well groups; Statistical analysis of the production status of drilled wells in the study area was conducted to obtain an understanding of the connectivity between well groups. Combined with the reservoir morphology and spatial relationship obtained in step two, the control range of a single well and the control range of connected well groups were then delineated. Step 4: Based on the control units defined in Step 3, calculate the static relative volume of different types of reservoirs within the control units of a single well and connected well groups. Step 5: Compile statistics on the cumulative oil and water production of the shut-in wells; Step six: Use the static relative volume calculated in step four and the oil and water production rates statistically analyzed in step five to perform correlation fitting, and obtain the functional relationship between the static relative volume and the dynamic production rate. Step 7: Using the functional relationship obtained in Step 6, the relative reservoir volume in Step 2 is converted into a production rate that matches the dynamics, thereby obtaining the predicted cumulative production and remaining production of each well.

2. The method for quantitatively predicting the production of fractured-vuggy reservoirs according to claim 1, characterized in that, In step one, unconstrained reflection coefficient inversion of seismic data is performed. The resulting reflection coefficient sequence and low-frequency trend model are combined and integrated for wave impedance calculation, thereby obtaining P-wave impedance data.

3. The method for quantitatively predicting the production of fractured-vuggy reservoirs according to claim 2, characterized in that, After obtaining the P-wave impedance data, the existing drilling information is used to perform quality control on the obtained P-wave impedance data to obtain P-wave impedance data that conforms to the geological understanding of the study area.

4. The method for quantitatively predicting the production of fractured-vuggy reservoirs according to claim 1, characterized in that, Step five involves statistically analyzing the oil, gas, and water production data of shut-in wells within different control units in the study area.

5. The method for quantitatively predicting the production of fractured-vuggy reservoirs according to claim 1, characterized in that, In step six, the functional relationship between static relative volume and dynamic production volume is: y=f(x), where y is the production volume, x is the reservoir carving volume, and f is the fitting function relationship between the production volume and the reservoir carving volume.

6. A system for quantitatively predicting the production of fractured-vuggy reservoirs, characterized in that, include; The seismic inversion module is used to obtain P-wave impedance data of cavernous and porous reservoirs through seismic inversion. The static sculpting module is used to statistically analyze the upper limit of P-wave impedance of cave-type and pore-type reservoirs revealed by existing drilling, determine the P-wave impedance threshold value for static reservoir sculpting, sculpt P-wave impedance data volumes smaller than the P-wave impedance threshold value, obtain the relative volume of cave-type and pore-type reservoirs, and then obtain the morphology and spatial relationship of cave-type and pore-type reservoirs. Well logging rock physics analysis is performed to obtain well logging P-wave impedance frequency histograms for different types of reservoirs and non-reservoirs. The P-wave impedance threshold values ​​for static carving of different types of reservoirs and non-reservoirs are determined. Based on the threshold values, static carving is performed to obtain the three-dimensional spatial morphology and spatial relationships of the reservoir. The control unit partitioning module is used to partition the control range of a single well and the control range of a connected well group based on reservoir morphology and spatial relationships. Statistical analysis of the production status of drilled wells in the study area was conducted to obtain an understanding of the connectivity between well groups. Combined with the reservoir morphology and spatial relationship obtained in step two, the control range of a single well and the control range of connected well groups were then delineated. The static relative volume calculation module is used to calculate the static relative volume of different types of reservoirs in a single well and connected well groups based on the control units divided by the control unit division module. The cumulative production statistics module is used to separately calculate the cumulative oil and water production of shut-in wells; The correlation fitting module is used to perform correlation fitting between the static relative volume calculated by the cumulative production statistics module and the oil and water production volume statistically obtained in step five, so as to obtain the functional relationship between the static relative volume and the dynamic production volume. The static volume conversion module is used to convert the relative reservoir volume of the static carving module into a production volume that matches the dynamic model, based on the functional relationship obtained by the correlation fitting module, thereby obtaining the predicted cumulative production and remaining production of each well.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for quantitatively predicting the production of fractured-vuggy reservoirs as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method for quantitatively predicting the production of fractured-vuggy reservoirs as described in any one of claims 1 to 5.

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