A method and apparatus for quantitative correction of the volume of carbonate karst cave-type reservoirs

Abstract

This invention provides a method, apparatus, computer-readable storage medium, and electronic device for quantitative volume correction of carbonate karst cavernous reservoirs. Based on processing the apparent volumetric carving data of caverns, this method uses a preset percentage energy value as a threshold to predict cavern width after uniformizing the amplitude, achieving automated batch volume correction across the entire area. This method provides technical support for the quantitative prediction of volume, reserve calculation, and well location deployment of carbonate karst cavernous reservoirs, improving the speed and accuracy of volume correction.

Description

Technical Field

[0001] This invention relates to the field of oil and gas seismic exploration technology, and in particular to a method, apparatus, computer-readable storage medium, and electronic device for quantitative correction of the volume of carbonate karst cave-type reservoirs. Background Technology

[0002] Carbonate fracture-vuggy reservoirs mainly consist of dissolution spaces such as caverns, pores, and fractures, and are the main oil and gas storage spaces in the Tarim Oilfield. However, current calculations of static reserves of caverns often differ significantly from actual production. Building upon current volumetric sculpting work, further improving the accuracy of quantitative prediction of cavern volume is of great significance for accurate reserve calculations and the formulation of development plans in the later stages.

[0003] Currently, the quantitative description of cavernous reservoirs mainly utilizes post-stack impedance for prediction. First, based on the impedance inversion work, the cavern impedance threshold value of the work area is calibrated and the porosity is assigned in combination with well and seismic data. Based on this impedance threshold value, the apparent volume of the cavern is uniformly sculpted.

[0004] Based on forward modeling analysis of cavern scale, it is found that, under multi-attribute comparison, impedance has the highest prediction accuracy for cavern top, while the energy value corresponding to 60% of the amplitude after energy homogenization has the highest prediction accuracy for cavern width. Therefore, current work on cavern calibration and apparent volumetric sculpting has completed the prediction of cavern height, but has not accurately predicted the lateral scale of the cavern. Therefore, in order to achieve volume correction of cavernous reservoirs, it is only necessary to continue width correction based on the previous sculpting results.

[0005] However, due to varying energy intensities, the 60% energy value corresponding to the uniformized amplitude differs for each cavity. This means that width correction requires sequential correction of each cavity individually based on the apparent volumetric sculpting results, rather than applying a uniform threshold value across the entire area. Alternatively, it necessitates first performing local energy uniformization on each cavity and then finding the 60% energy value corresponding to the uniformized energy for phase control. Building upon the current sculpting work, further quantitative characterization of the caves, and achieving automated correction across the entire area, remains a significant challenge in implementing the current theoretical framework.

[0006] The main methods for early volume correction include scaled depiction and correction of caves, which involves scaled calibration, carving, and correction of the caves, and are relatively complex; and sequential correction of individual caves, which is highly subjective and slow. Overall, none of these methods have achieved an efficient, unified correction method that is closely integrated with the current cave depiction process. Summary of the Invention

[0007] To address the aforementioned problems, embodiments of the present invention provide a method, apparatus, computer-readable storage medium, and electronic device for quantitatively correcting the volume of carbonate karst cave-type reservoirs.

[0008] In a first aspect, embodiments of the present invention provide a method for quantitatively correcting the volume of carbonate karst cave-type reservoirs, including:

[0009] S100, Based on the impedance threshold calibration results of the work area, establish the apparent volume model of the karst cave in the work area, and discretize the apparent volume model of the karst cave to obtain a discrete grid model. Each karst cave in the discrete grid model has its corresponding number.

[0010] S200, based on the energy distribution of the work area, assign an energy value to each cave in the apparent volume model of the cave to obtain the energy-cave apparent volume model;

[0011] S300, export the data volume of the discrete grid model and the data volume of the energy-cavity apparent volume model, and merge these two sets of data volumes into a data matrix, which records the information of the number and energy value corresponding to each grid.

[0012] S400, Add a discrimination column for correction to the data matrix, and perform the following correction steps for each cavern:

[0013] Calculate the correction threshold value for the lateral scale of each cave based on the maximum energy value in each cave.

[0014] For each grid in the cavern, determine whether the energy value corresponding to that grid is greater than the correction threshold value:

[0015] If the energy value corresponding to the grid is greater than the correction threshold value, then the initial value of the corresponding element in the discrimination column is modified to a reserved value, wherein the reserved value indicates that the data of the grid is retained;

[0016] If the energy value corresponding to the grid is less than or equal to the correction threshold value, then the initial value of the corresponding element in the discrimination column is modified to the discard value, which means that the data of the grid is discarded;

[0017] S500, based on the corrected data, conducts analysis and research on the karst caves in the work area.

[0018] According to an embodiment of the present invention, in step S200, the energy value is the root mean square energy value.

[0019] According to an embodiment of the present invention, when a discriminant column for correction is added to the data matrix, the initial value of each element in the discriminant column is 0.

[0020] According to an embodiment of the present invention, the retention value is 1, and the discard value is 0.

[0021] According to an embodiment of the present invention, the correction threshold value of the lateral scale is calculated based on the forward lateral scale quantization theory.

[0022] According to an embodiment of the present invention,

[0023] Correction threshold value = (maximum energy value - background energy value) * preset percentage + background energy value.

[0024] According to an embodiment of the present invention, the preset percentage is 60%.

[0025] Secondly, the present invention also provides a volume quantification and correction device for carbonate karst cave-type reservoirs, comprising:

[0026] The first modeling module is used to establish a karst cave apparent volume model of the work area based on the impedance threshold value calibration result of the work area, and to discretize the karst cave apparent volume model to obtain a discrete mesh model. Each karst cave in the discrete mesh model has its corresponding number.

[0027] The second modeling module is used to assign energy values ​​to each cave in the apparent volume model of the cave based on the energy distribution of the work area, so as to obtain an energy-cave apparent volume model.

[0028] The data merging module is used to export the data volume of the discrete grid model and the data volume of the energy-cavity apparent volume model, and merge these two sets of data volumes into a data matrix. The data matrix records the information of the number and energy value corresponding to each grid.

[0029] The grid correction module adds a discrimination column for correction to the data matrix, and performs the following correction steps for each cavern:

[0030] Calculate the correction threshold value for the lateral scale of each cave based on the maximum energy value in each cave.

[0031] For each grid in the cavern, determine whether the energy value corresponding to that grid is greater than the correction threshold value:

[0032] If the energy value corresponding to the grid is greater than the correction threshold value, then the initial value of the corresponding element in the discrimination column is modified to a reserved value, wherein the reserved value indicates that the data of the grid is retained;

[0033] If the energy value corresponding to the grid is less than or equal to the correction threshold value, then the initial value of the corresponding element in the discrimination column is modified to the discard value, which means that the data of the grid is discarded;

[0034] The analysis and research module is used to conduct analysis and research on the karst caves in the work area based on the corrected data.

[0035] Thirdly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for quantitative correction of the volume of carbonate karst cave-type reservoirs as described in the first aspect above.

[0036] Fourthly, embodiments of the present invention provide an electronic device comprising:

[0037] processor;

[0038] Memory used to store the processor's executable instructions;

[0039] The processor is configured to execute the instructions to implement a method for quantitative correction of the volume of carbonate karst cave-type reservoirs as described in the first aspect above.

[0040] Compared with the prior art, the above-mentioned technical solution of the present invention has the following beneficial effects:

[0041] This invention provides a method for quantitatively correcting the volume of carbonate karst cavernous reservoirs. Based on processing the apparent volumetric carving data of the caverns, and using a preset percentage energy value as a threshold after uniformizing the amplitude, the predicted cavern width more closely approximates this principle. Addressing the issue of varying lateral correction thresholds for individual caverns within a work area, this invention provides a method for automated batch correction across the entire area. This method provides technical support for the quantitative prediction of volume, reserve calculation, and well placement of carbonate karst cavernous reservoirs. This method significantly improves the speed and accuracy of volume correction. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart illustrating the steps of the carbonate karst cave-type reservoir volume quantitative correction method according to an embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram of the cave discretization model and the energy-cave apparent volume model according to an embodiment of the present invention;

[0045] Figure 3 This is a schematic diagram of the cyclic structure for quantifying and correcting the volume of a cave in accordance with an embodiment of the present invention;

[0046] Figure 4 This is a schematic diagram comparing the overall volume of a unit karst cave in the Tarim Oilfield before and after volume correction, according to an embodiment of the present invention.

[0047] Figure 5 This is a schematic diagram comparing the number of karst caves before and after volume correction in a unit of the Tarim Oilfield according to an embodiment of the present invention;

[0048] Figure 6 This is a schematic diagram of the local correction effect of a standard hole according to an embodiment of the present invention;

[0049] Figure 7 This is a schematic diagram illustrating the local correction effect of the irregular hole according to an embodiment of the present invention;

[0050] Figure 8 This is a schematic diagram comparing the karst cave in the ductile well 1 before and after correction according to an embodiment of the present invention;

[0051] Figure 9 This is a schematic diagram comparing the karst cave correction before and after in a volumetric well 2 according to an embodiment of the present invention;

[0052] Figure 10 This is a schematic diagram of the composition of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] Example 1

[0055] The present invention aims to provide a method for the quantitative correction of the volume of carbonate cavernous reservoirs. This method first derives a model grid data volume containing cavern numbers and a model grid data volume containing the root-mean-square energy distribution within the caverns, based on an existing impedance threshold calibration and a cavern apparent volume sculpting model. Both sets of model grid data volumes contain corresponding grid coordinates. These two sets of model grid data volumes are merged to form a data matrix, ensuring that each grid in the data matrix has corresponding root-mean-square energy and cavern number information. A column is then added after this data matrix as a correction discrimination column. Next, for all caverns, the following iterative steps are performed: the maximum energy value in each cavern is found, and a lateral correction threshold value is calculated based on the forward modeling lateral scaling quantization theory. Furthermore, each grid in the cavern is iteratively compared; if the energy corresponding to the grid is greater than the correction threshold value, the corresponding element in the discrimination column is set to 1, and the grid is retained; if the energy corresponding to the grid is less than the correction threshold value, the corresponding element in the discrimination column is set to 0, and the grid is corrected. Finally, the corrected matrix is ​​imported into a constructed geological model. The above methods are of great significance for the lateral scale prediction and accurate reserve calculation of cavernous reservoirs.

[0056] The following is in conjunction with the appendix Figure 1 The specific steps to implement the above method are explained in detail below:

[0057] (1) Processing and exporting of carving results

[0058] First, an apparent volume model of the cave is obtained through impedance calibration and model building. Then, a discretized model is obtained through discretization operations (such as...). Figure 2 As shown in part a), each cave in this discretized model has a corresponding number. An energy value (root mean square amplitude energy) is assigned to the interior of the cave's apparent volume model to obtain the energy-cave apparent volume model (as shown in part a). Figure 2 (as shown in part b).

[0059] Data from the discretized model and the energy-cavity apparent volume model were exported, resulting in two sets of data volumes: the first set of data volume has 8 columns, namely i, j, k, x, y, z, 1, caveID; the second set of data volume has 7 columns, namely i, j, k, x, y, z, AMP. Here, i, j, k, x, y, z are coordinates, caveID is the cave number, and AMP is the energy value.

[0060] (2) Data merging

[0061] The first six columns of the two sets of data indicate the grid coordinates of the model, and each row of the two sets of data corresponds one-to-one. In practice, the caveID column of the first set of data can be added to the end of the seven columns i, j, k, x, y, z, AMP of the second set of data to complete the data merging, thus combining them into a single file named cave_AMP_id.

[0062] (3) Execute the volume correction cycle

[0063] like Figure 3 As shown, after adding a column of 0 to the data body cave_AMP_id, a cave volume correction loop is executed: a cave-level loop, performing the same operation for each individual cave in the work area. For example, in cave 1, firstly, the maximum energy value AMPmax1 inside cave 1 is found, and then the width correction threshold value TRD1 of cave 1 is calculated as (AMPmax1 - background energy value) * preset percentage + background energy value, obtaining the correction threshold value of the lateral scale of cave 1. Subsequently, the loop judgment of the grid scale of cave 1 is entered, that is, the energy value corresponding to each grid in cave 1 is judged. If it is greater than the correction threshold value TRD1, it is recorded as 1, which means that the grid has not been corrected. If the energy value in the grid is less than the correction threshold value, it is recorded as 0, which means that the grid has been corrected. Through the processing of the volume correction loop statement, the data body cave_final is obtained, which has 9 columns, namely i, j, k, x, y, z, AMP, caveID and 0 or 1.

[0064] (4) Analysis of calibration results

[0065] Import the data volume cave_final into the model module of the application software (such as a 3D geological model) to display the corrected 3D model, analyze the correction amount, and compare the dynamic reserves of the fixed-volume well.

[0066] The following section takes a unit in the Tarim Oilfield as an example, and describes the specific steps implemented according to the above method to achieve unified volume correction in the work area.

[0067] (1) Overall effect before and after correction

[0068] Overall, the total number of grid cells in the work area before correction was 693,731, and after correction it was 278,339, achieving a correction rate of 40% (e.g., Figure 4 (As shown); Before correction, the total number of discrete caves in the work area was 2025, and after correction, it was 2304, an increase of 279 caves (as shown). Figure 5 (As shown).

[0069] (2) Local effects before and after correction

[0070] From a local perspective, the correction effect of the standard hole achieved the prediction results of the top and bottom while preserving the carving results, and corrected the hole width based on 60% of the homogenized energy (e.g. Figure 6 As shown). Some irregularly shaped caves were divided into several caves after correction (such as...). Figure 7 (As shown).

[0071] (3) Comparison with dynamic reserves of constant volume wells

[0072] To verify the accuracy of this method in predicting the final geological volume, static reserves were calculated for the karst caves corresponding to two typical constant-volume wells in the work area. The results were quite close to the dynamic reserves calculated from the well dynamic data.

[0073] For well 1 with constant volume, the corrected foresight volume is 590,000 cubic meters, with a static reserve of 177,000 tons. The corrected backsight volume is 280,000 cubic meters, with an effective volume of 112,000 tons. Using the energy reduction method, the dynamic reserve of this well is calculated to be 120,000 tons (e.g., ...). Figure 8 (As shown). For well 2, the corrected foresight volume is 1.1 million cubic meters, with an effective volume of 330,000 cubic meters. The corrected backsight volume is 460,000 tons, with an effective volume of 184,000 tons. Using the energy reduction method, the dynamic reserves of this well are calculated to be 150,000 tons (e.g., ...). Figure 9 (As shown).

[0074] In summary, the quantitative correction method for the volume of carbonate karst cave-type reservoirs has improved the prediction accuracy of cave width and volume, providing support for the next step of calculating the reserves of fractured cave bodies and well location deployment.

[0075] This invention processes data from a volumetric sculpted model of a cave to calculate a lateral correction threshold and correct the width of each cave, thus achieving volumetric correction. The method of this invention significantly improves the speed and accuracy of volumetric correction.

[0076] Example 2

[0077] 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 disclosed in the embodiments of the apparatus of the present invention, please refer to the embodiments of the method of the present invention.

[0078] This embodiment provides a device for quantitatively correcting the volume of carbonate karst cave-type reservoirs, characterized in that it includes:

[0079] The first modeling module is used to establish a karst cave apparent volume model of the work area based on the impedance threshold value calibration result of the work area, and to discretize the karst cave apparent volume model to obtain a discrete mesh model. Each karst cave in the discrete mesh model has its corresponding number.

[0080] The second modeling module is used to assign energy values ​​to each cave in the apparent volume model of the cave based on the energy distribution of the work area, so as to obtain an energy-cave apparent volume model.

[0081] The data merging module is used to export the data volume of the discrete grid model and the data volume of the energy-cavity apparent volume model, and merge these two sets of data volumes into a data matrix. The data matrix records the information of the number and energy value corresponding to each grid.

[0082] The grid correction module adds a discrimination column for correction to the data matrix, and performs the following correction steps for each cavern:

[0083] Calculate the correction threshold value for the lateral scale of each cave based on the maximum energy value in each cave.

[0084] For each grid in the cavern, determine whether the energy value corresponding to that grid is greater than the correction threshold value:

[0085] If the energy value corresponding to the grid is greater than the correction threshold value, then the initial value of the corresponding element in the discrimination column is modified to a reserved value, wherein the reserved value indicates that the data of the grid is retained;

[0086] If the energy value corresponding to the grid is less than or equal to the correction threshold value, then the initial value of the corresponding element in the discrimination column is modified to the discard value, which means that the data of the grid is discarded;

[0087] The analysis and research module is used to conduct analysis and research on the karst caves in the work area based on the corrected data.

[0088] Example 3

[0089] This embodiment provides a computer-readable medium storing a computer program that, when executed by a processor, implements the various steps of a carbonate karst cave-type reservoir volume quantification correction method as described in the above embodiment.

[0090] It should be noted that all or part of the processes in the methods of the above embodiments of the present invention can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. Of course, there are other readable storage media, such as quantum memories, graphene memories, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0091] Example 4

[0092] Figure 10 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Figure 10 As shown, at the hardware level, this electronic device includes a processor, and optionally also includes an internal bus, a network interface, and memory. The memory may include main memory, such as high-speed random-access memory (RAM), or it may include non-volatile memory, such as at least one disk drive. Of course, this electronic device may also include other hardware required for other business operations.

[0093] The processor, network interface, and memory can be interconnected via an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. This bus can be categorized as an address bus, data bus, control bus, etc. For ease of illustration, only line segments are used in the diagram, but this does not imply that there is only one bus or one type of bus.

[0094] A memory is used to store programs. Specifically, the program may include program code, which includes computer operation instructions. The memory may include main memory and non-volatile memory, and provides instructions and data to the processor. The processor reads the corresponding computer program from the non-volatile memory into main memory and then runs it. The processor executes the program stored in the memory to perform all the steps in the aforementioned method for quantitative correction of carbonate karst cavernous reservoir volume.

[0095] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus. The communication interface is used for communication between the above electronic devices and other devices.

[0096] A bus, including hardware, software, or both, is used to couple the aforementioned components together. For example, a bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, a bus may include one or more buses. Although specific buses are described and illustrated in embodiments of the invention, the invention contemplates any suitable bus or interconnect.

[0097] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0098] The memory may include a large-capacity storage device for data or instructions. For example, and not limitingly, the memory may include a hard disk drive (HDD), a floppy disk drive, flash memory, an optical disk drive, a magneto-optical disk drive, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where suitable, the memory may include removable or non-removable (or fixed) media. In a particular embodiment, the memory is a non-volatile solid-state memory. In a particular embodiment, the memory includes a read-only memory (ROM). Where suitable, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0099] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0100] It should be noted that those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this invention. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0101] The apparatus, device, system, module, or unit described in the above embodiments can be implemented by a computer chip or entity, or by a product with a certain function. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, an in-vehicle human-machine interaction device, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0102] While this invention provides the method operation steps as described in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-inventive means. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual devices or terminal products, the methods shown in the embodiments or drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed data processing environment).

[0103] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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 illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0104] 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.

[0105] 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.

[0106] It should be noted that, in this document, relational terms such as "first" and "second" are used merely 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 a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0107] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, electronic devices, and readable storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0108] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A method for quantitatively correcting the volume of carbonate karst cave-type reservoirs, characterized in that, Includes the following steps: S100, Based on the impedance threshold calibration results of the work area, establish the apparent volume model of the karst cave in the work area, and discretize the apparent volume model of the karst cave to obtain a discrete grid model. Each karst cave in the discrete grid model has its corresponding number. S200, based on the energy distribution of the work area, assign an energy value to each cave in the apparent volume model of the cave to obtain the energy-cave apparent volume model; S300, export the data volume of the discrete grid model and the data volume of the energy-cavity apparent volume model, and merge these two sets of data volumes into a data matrix, which records the information of the number and energy value corresponding to each grid. S400, Add a discrimination column for correction to the data matrix, and perform the following correction steps for each cavern: Based on the maximum energy value in each cave, the correction threshold value for the lateral dimension of the cave is calculated according to the following formula: Correction threshold value = (maximum energy value - background energy value) * preset percentage + background energy value; For each grid in the cavern, determine whether the energy value corresponding to that grid is greater than the correction threshold value: If the energy value corresponding to the grid is greater than the correction threshold value, then the initial value of the corresponding element in the discrimination column is modified to a reserved value, wherein the reserved value indicates that the data of the grid is retained; If the energy value corresponding to the grid is less than or equal to the correction threshold value, then the initial value of the corresponding element in the discrimination column is modified to the discard value, which means that the data of the grid is discarded; S500, based on the corrected data, conducts analysis and research on the karst caves in the work area.

2. The method for quantitatively correcting the volume of carbonate karst cave-type reservoirs as described in claim 1, characterized in that, In step S200, the energy value is the root mean square energy value.

3. The method for quantitatively correcting the volume of carbonate karst cave-type reservoirs as described in claim 2, characterized in that, When a discriminant column for correction is added to the data matrix, the initial value of each element in the discriminant column is 0.

4. The method for quantitatively correcting the volume of carbonate karst cave-type reservoirs as described in claim 2, characterized in that, The retention value is 1, and the discard value is 0.

5. The method for quantitatively correcting the volume of carbonate karst cave-type reservoirs as described in claim 1, characterized in that, The preset percentage is 60%.

6. A device for quantitatively correcting the volume of carbonate karst cave-type reservoirs, characterized in that, include: The first modeling module is used to establish a karst cave apparent volume model of the work area based on the impedance threshold value calibration result of the work area, and to discretize the karst cave apparent volume model to obtain a discrete mesh model. Each karst cave in the discrete mesh model has its corresponding number. The second modeling module is used to assign energy values ​​to each cave in the apparent volume model of the cave based on the energy distribution of the work area, so as to obtain an energy-cave apparent volume model. The data merging module is used to export the data volume of the discrete grid model and the data volume of the energy-cavity apparent volume model, and merge these two sets of data volumes into a data matrix. The data matrix records the information of the number and energy value corresponding to each grid. The grid correction module adds a discrimination column for correction to the data matrix, and performs the following correction steps for each cavern: Based on the maximum energy value in each cave, the correction threshold value for the lateral dimension of the cave is calculated according to the following formula: Correction threshold value = (maximum energy value - background energy value) * preset percentage + background energy value; For each grid in the cavern, determine whether the energy value corresponding to that grid is greater than the correction threshold value: If the energy value corresponding to the grid is greater than the correction threshold value, then the initial value of the corresponding element in the discrimination column is modified to a reserved value, wherein the reserved value indicates that the data of the grid is retained; If the energy value corresponding to the grid is less than or equal to the correction threshold value, then the initial value of the corresponding element in the discrimination column is modified to the discard value, which means that the data of the grid is discarded; The analysis and research module is used to conduct analysis and research on the karst caves in the work area based on the corrected data.

7. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements a method for quantitative correction of the volume of carbonate karst cave-type reservoirs as described in any one of claims 1 to 5.

8. An electronic device comprising: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement a method for quantitative correction of carbonate karst cave-type reservoir volume as described in any one of claims 1 to 5.

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