A method, device, medium and equipment for identifying a high-quality carbonate reservoir

Abstract

Embodiments of the present application disclose a method, device, medium and equipment for identifying high-quality reservoirs of carbonate rocks. The method comprises: obtaining oil testing data and core analysis data of a region to be identified; determining high-quality reservoir cutoff information of the region to be identified according to the oil testing data and the core analysis data; the high-quality reservoir cutoff information comprises a carbonate mineral content threshold and a dolomitization intensity threshold; and determining high-quality reservoirs of the region to be identified according to the high-quality reservoir cutoff information and pre-acquired logging data. The technical solution can determine high-quality reservoir cutoff information of the region to be identified by using oil testing data and core analysis data, and then determine high-quality reservoirs by using the high-quality reservoir cutoff information. The solution greatly saves coring cost and realizes accurate and rapid identification of high-quality reservoirs of carbonate rocks.

Description

Technical Field

[0001] This application relates to the field of geophysical technology, and in particular to a method, apparatus, medium and equipment for identifying high-quality carbonate reservoirs. Background Technology

[0002] Lacustrine carbonate rocks are the most widely distributed type of terrestrial carbonate rocks, referring to carbonate rocks formed in inland lacustrine basins. Compared with marine carbonate rocks, lacustrine carbonate rocks have a higher content of terrigenous clastic material, faster vertical mineral content variations, and severe mixing characteristics, which poses significant challenges to well logging reservoir evaluation. Identifying high-quality reservoirs is one of the key issues in the exploration and development of lacustrine carbonate oil and gas reservoirs.

[0003] Currently, most logging methods for rapid identification of high-quality lacustrine carbonate reservoirs follow the methods used for evaluating marine carbonate reservoirs. These methods mainly focus on porosity, permeability calculation, and pore structure evaluation, specifically including: (1) using compensated neutrons to determine the resistivity and acoustic transit time of the matrix rock, and then comparing the differences between the two and the deep lateral resistivity and acoustic transit time, thereby comprehensively identifying different fracture development sections of the reservoir; (2) using the cumulative porosity and cumulative area parameters of fractures calculated from electrical imaging logging data, and combining them with daily gas production to establish a standard for classifying and dividing tight carbonate fractured reservoirs; (3) using conventional logging + electrical imaging logging with special processing to calculate matrix porosity and secondary dissolution pore surface porosity, which can be used to evaluate the reservoir's reservoir capacity, and using deep and shallow dual lateral logging + electrical imaging logging + Stoneley wave energy data, which can be used to evaluate the reservoir's permeability.

[0004] Existing methods rely heavily on core samples and experimental analysis. Furthermore, the procedures are cumbersome in practical applications, making them impractical and unable to quickly identify high-quality reservoirs. Summary of the Invention

[0005] This application provides a method, apparatus, medium, and equipment for identifying high-quality carbonate reservoirs. It can determine the cutoff information of high-quality reservoirs in the area to be identified by using oil testing data and core analysis data, thereby achieving the purpose of identifying high-quality reservoirs.

[0006] In a first aspect, embodiments of this application provide a method for identifying high-quality carbonate reservoirs, the method comprising:

[0007] Obtain oil testing data and core analysis data for the area to be identified;

[0008] Based on the oil testing data and the core analysis data, the cutoff information for high-quality reservoirs in the area to be identified is determined; the cutoff information for high-quality reservoirs includes the carbonate mineral content threshold and the dolomization intensity threshold.

[0009] Based on the cutoff information of the high-quality reservoir and the pre-acquired logging data, the high-quality reservoir in the area to be identified is determined.

[0010] Secondly, embodiments of this application provide a device for identifying high-quality carbonate reservoirs, the device comprising:

[0011] The data acquisition module is used to acquire oil testing data and core analysis data of the area to be identified.

[0012] The high-quality reservoir cutoff information determination module is used to determine the high-quality reservoir cutoff information of the area to be identified based on the oil test data and the core analysis data; the high-quality reservoir cutoff information includes carbonate mineral content threshold and dolomization intensity threshold;

[0013] The high-quality reservoir identification module is used to identify high-quality reservoirs in the area to be identified based on the high-quality reservoir cutoff information and the pre-acquired logging data.

[0014] Thirdly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for identifying high-quality carbonate reservoirs as described in embodiments of this application.

[0015] Fourthly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements a method for identifying high-quality carbonate reservoirs as described in embodiments of this application.

[0016] The technical solution provided in this application obtains oil testing data and core analysis data of the area to be identified. Based on these data, it determines the cutoff information for high-quality reservoirs in the area, namely the carbonate mineral content threshold and dolomization intensity threshold. Then, using the high-quality reservoir cutoff information and pre-acquired logging data, it identifies the high-quality reservoirs in the area. This solution significantly reduces coring costs and achieves accurate and rapid identification of high-quality carbonate reservoirs. Attached Figure Description

[0017] Figure 1A This is a flowchart of a method for identifying high-quality carbonate reservoirs provided in Embodiment 1 of this application;

[0018] Figure 1B This is a schematic diagram showing the relationship between carbonate mineral content and porosity in region F of the Qaidam Basin in Embodiment 1 of the present invention;

[0019] Figure 1C This is a schematic diagram illustrating the relationship between dolomization intensity and porosity in region F of the Qaidam Basin in Embodiment 1 of the present invention.

[0020] Figure 1D This is a schematic diagram showing the relationship between carbonate mineral content and dolomitization intensity in region F of the Qaidam Basin in Embodiment 1 of the present invention.

[0021] Figure 2A This is a flowchart of a method for identifying high-quality carbonate reservoirs according to Embodiment 2 of the present invention;

[0022] Figure 2B This is a schematic diagram illustrating the interpretation results of well F2 in area F of the Qaidam Basin in Embodiment 2 of the present invention;

[0023] Figure 3 This is a schematic diagram of the structure of a device for identifying high-quality carbonate reservoirs provided in Embodiment 3 of the present invention;

[0024] Figure 4 This is a schematic diagram of the structure of an electronic device provided in Embodiment 5 of this application. Detailed Implementation

[0025] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the application and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present application, not the entire structure.

[0026] Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the steps as sequential processes, many of these steps can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the steps can be rearranged. The process can be terminated when its operation is complete, but may also have additional steps not included in the figures. The process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0027] Example 1

[0028] Figure 1A This is a flowchart of a method for identifying high-quality carbonate reservoirs provided in Embodiment 1 of this application. This embodiment can be applied to any scenario for identifying high-quality carbonate reservoirs. The method can be executed by a device for identifying high-quality carbonate reservoirs provided in this embodiment of the application. The device can be implemented by software and / or hardware and can be integrated into an electronic device.

[0029] like Figure 1A As shown, the method for identifying high-quality carbonate reservoirs includes:

[0030] S110: Obtain oil testing data and core analysis data for the area to be identified.

[0031] This procedure can be executed using electronic equipment such as helium porosimeters, X-ray diffractometers, logging tools, and computers. Oil testing involves introducing fluids (including oil, gas, and water) from the oil-bearing reservoir identified and evaluated through drilling, integrated logging, and electrical logging into the wellbore through various methods such as perforation, displacement spraying, and induced spraying, allowing the fluids to flow to the surface. This yields data on the properties of the fluids, the production of various fluids, the reservoir pressure, and pressure changes during fluid flow. These data are then analyzed and processed using electronic equipment such as analyzers to obtain various physical property parameters of the reservoir for evaluation. Specifically, the oil testing data may include porosity, saturation, and thickness. Core analysis data can be obtained through drilling and coring, and experimental analysis of the core samples. The core analysis data may include porosity data, calcite content data, and dolomite content data. This core analysis data can be obtained using electronic equipment such as helium porosimeters and X-ray diffractometers.

[0032] S120, Based on the oil testing data and the core analysis data, determine the cutoff information for high-quality reservoirs in the area to be identified; the cutoff information for high-quality reservoirs includes a carbonate mineral content threshold and a dolomitization intensity threshold.

[0033] Based on oil testing data and core analysis data, electronic equipment can determine the cutoff information for high-quality reservoirs in the area to be identified. This cutoff information can be geological information that distinguishes between high-quality and non-high-quality reservoirs. There can be one or more cutoff information points. Specifically, the cutoff information can include a carbonate mineral content threshold and a dolomization intensity threshold. The reason for using the carbonate mineral content threshold and dolomization intensity threshold as the cutoff information for high-quality reservoirs in the area to be identified is that the quality of lacustrine carbonate reservoirs is mainly controlled by two parameters: carbonate mineral content and dolomization intensity.

[0034] Specifically, the higher the carbonate mineral content, the better the reservoir quality. Influenced by the sedimentary environment, lacustrine carbonate rocks have a higher content of terrigenous clastic materials (quartz, feldspar, clay minerals, etc.). Compared to marine carbonate rocks, lacustrine carbonate rocks have relatively lower carbonate mineral content, and the content varies more rapidly vertically. Carbonate minerals are important media and carriers for the development of pores in carbonate rocks; the more carbonate minerals present, the more developed the pores, the higher the porosity, and the better the reservoir quality. Figure 1B This is a schematic diagram illustrating the relationship between carbonate mineral content and porosity in region F of the Qaidam Basin, as described in Embodiment 1 of the present invention. Figure 1B The results show that there is a positive correlation between carbonate mineral content and porosity in lacustrine carbonate rocks, and the correlation is good.

[0035] Higher dolomization intensity corresponds to better reservoir quality. The main pore types in lacustrine carbonate rocks are dolomite intercrystalline pores and dissolution pores, both of which are closely related to dolomization. The stronger the dolomization, the more developed the dolomite intercrystalline pores and dissolution pores, resulting in higher porosity and better reservoir quality. Figure 1C This is a schematic diagram illustrating the relationship between dolomization intensity and porosity in region F of the Qaidam Basin, as described in Embodiment 1 of the present invention. Figure 1C As shown, there is a positive correlation between dolomization intensity and porosity in lacustrine carbonate rocks, and the correlation is good.

[0036] Figure 1D This is a schematic diagram illustrating the relationship between carbonate mineral content and dolomization intensity in region F of the Qaidam Basin, as described in Embodiment 1 of the present invention. Figure 1D As shown, triangles indicate non-high-quality reservoirs, and dots indicate high-quality reservoirs. The relationship between carbonate mineral content and dolomization intensity is divided into four regions: ①, ②, ③, and ④. Region ① has a high carbonate mineral content and strong dolomization intensity; most data points for high-quality reservoirs are distributed in this region. Region ②, although with strong dolomization intensity, has a low carbonate mineral content and lacks the medium and carrier for porosity development, resulting in low porosity; most data points in this region are non-high-quality reservoirs. Region ③ has a low carbonate mineral content and weak dolomization intensity, both unfavorable for porosity development; most data points in this region are non-high-quality reservoirs. Region ④ has a high carbonate mineral content but weak dolomization; although there is a carrier for porosity development, it is unfavorable for the development of intercrystalline pores and dissolution pores in dolomite, resulting in low porosity; most data points in this region are non-high-quality reservoirs.

[0037] Accordingly, determining the cutoff information for high-quality reservoirs in the area to be identified based on the oil testing data and the core analysis data includes:

[0038] Based on the oil testing data and the porosity data, determine the high-quality reservoir sample data;

[0039] Based on the high-quality reservoir sample data, the calcite content data, and the dolomite content data, the cutoff information for high-quality reservoirs in the area to be identified is determined.

[0040] Electronic equipment can obtain porosity data of high-quality reservoirs in the area to be identified through statistical analysis based on oil testing data. By comparing the porosity data of high-quality reservoirs with the porosity data in core analysis data, the electronic equipment can determine the sample data of high-quality reservoirs from the core analysis data.

[0041] Based on the high-quality reservoir sample data, calcite content data and dolomite content data in the core analysis data, the cutoff information for high-quality reservoirs in the area to be identified is determined.

[0042] This method allows for the extraction of high-quality reservoir sample data through core sampling from a limited number of wells. Using the high-quality reservoir cutoff information, the location of high-quality reservoirs within the entire area to be identified can be determined using well logging data. This method significantly reduces drilling and core sampling costs while enabling accurate and rapid identification of high-quality reservoirs.

[0043] S130, Based on the high-quality reservoir cutoff information and the pre-acquired logging data, determine the high-quality reservoir in the area to be identified.

[0044] By using the cutoff information of high-quality reservoirs as a basis for judgment, the content of carbonate minerals and dolomitization intensity in the logging data of the entire area to be identified can be evaluated to determine the location of high-quality reservoirs in the area to be identified.

[0045] The technical solution provided in this application obtains oil testing data and core analysis data of the area to be identified. Based on these data, it determines the cutoff information for high-quality reservoirs in the area, namely the carbonate mineral content threshold and dolomization intensity threshold. Then, using the high-quality reservoir cutoff information and pre-acquired logging data, it identifies the high-quality reservoirs in the area. This solution significantly reduces coring costs and achieves accurate and rapid identification of high-quality carbonate reservoirs.

[0046] Example 2

[0047] Figure 2A This is a flowchart of a method for identifying high-quality carbonate reservoirs according to Embodiment 2 of the present invention. This embodiment is an optimization based on the above embodiment.

[0048] like Figure 2A As shown, the method in this embodiment specifically includes the following steps:

[0049] S210: Obtain oil testing data and core analysis data for the area to be identified.

[0050] S220, Based on the oil testing data, determine the lower limit of high-quality reservoir porosity in the area to be identified.

[0051] Understandably, electronic equipment can obtain the lower limit of porosity of high-quality reservoirs in the area to be identified through statistical analysis based on oil testing data.

[0052] S230, Based on the comparison results between the porosity data and the lower limit of porosity of the high-quality reservoir, determine the sample data of the high-quality reservoir.

[0053] Based on the comparison between the porosity data in the core analysis data and the lower limit of porosity of high-quality reservoirs, electronic equipment can screen out high-quality reservoir sample data from the core analysis data.

[0054] Specifically, determining the high-quality reservoir sample data based on the comparison between the porosity data and the lower limit of the high-quality reservoir porosity includes:

[0055] If the porosity is greater than or equal to the lower limit of the porosity of the high-quality reservoir, then the sample corresponding to the porosity is a high-quality reservoir.

[0056] If the porosity is less than the lower limit of the porosity of the high-quality reservoir, then the sample corresponding to the porosity is a non-high-quality reservoir.

[0057] Using the lower limit of porosity to screen high-quality reservoir sample data can comprehensively obtain high-quality reservoir sample data, avoid the omission of high-quality reservoir sample data, and thus achieve effective statistical analysis, which is conducive to determining the cutoff information of high-quality reservoirs with discriminative power.

[0058] S240, Based on the calcite content data and the dolomite content data, determine the carbonate mineral content data and the dolomite intensity data.

[0059] It is readily understood that the carbonate mineral content can be calculated from the calcite and dolomite content, which can be the sum of the calcite and dolomite contents. Similarly, the dolomization intensity can also be calculated from the calcite and dolomite content, which can be the ratio of the dolomite content to the carbonate mineral content. Accordingly, based on the calcite and dolomite content data in the core analysis data, electronic equipment can calculate the carbonate mineral content and dolomization intensity data.

[0060] S250, based on the carbonate mineral content data and the dolomization intensity data, determine the cutoff information for high-quality reservoirs in the area to be identified.

[0061] By statistically analyzing carbonate mineral content data and dolomization intensity data, electronic equipment can determine the cutoff information for high-quality reservoirs in the area to be identified, namely the carbonate mineral content threshold and the dolomization intensity threshold.

[0062] Based on the above scheme, optionally, determining the cutoff information for high-quality reservoirs in the area to be identified based on the carbonate mineral content data and the dolomization intensity data includes:

[0063] The high-quality reservoir sample data are sorted according to carbonate mineral content to obtain a sorting result based on carbonate mineral content; and the high-quality reservoir sample data are sorted according to dolomization intensity to obtain a sorting result based on dolomization intensity.

[0064] Based on the ranking results of carbonate mineral content and dolomization intensity, the cutoff information for high-quality reservoirs in the area to be identified is determined.

[0065] Specifically, the electronic device can sort all high-quality reservoir sample data according to carbonate mineral content, obtaining a sorting result based on carbonate mineral content. Simultaneously, the electronic device can also sort the high-quality reservoir sample data according to dolomization intensity, obtaining a sorting result based on dolomization intensity. Based on the sorting results for carbonate mineral content and dolomization intensity, the carbonate mineral content and dolomization intensity at the end of the sorting results are selected as the cutoff information for high-quality reservoirs in the area to be identified.

[0066] This scheme sets cutoff information for high-quality reservoirs through a simple sorting method, which facilitates accurate and convenient identification of high-quality reservoirs.

[0067] In this scheme, optionally, before determining the cutoff information for high-quality reservoirs in the area to be identified based on the carbonate mineral content ranking results and dolomization intensity ranking results, the method further includes:

[0068] According to the first preset rule, the sorting results of the carbonate mineral content are truncated to obtain the sorting results of the carbonate mineral content; and according to the second preset rule, the sorting results of the dolomization intensity are truncated to obtain the sorting results of the dolomization intensity.

[0069] Based on the sorting results of carbonate mineral content and dolomization intensity, the cutoff information for high-quality reservoirs in the area to be identified is determined.

[0070] When there is a large amount of high-quality reservoir sample data, outliers are prone to appear. In order to save computing resources and output reliable high-quality reservoir cutoff information, electronic devices can be set with preset rules to truncate the results of carbonate mineral content sorting and dolomization intensity sorting, so as to ensure that the obtained high-quality reservoir cutoff information is stable and reliable.

[0071] Correspondingly, electronic devices can determine the cutoff information of high-quality reservoirs in the area to be identified based on the sorting results of carbonate mineral content and dolomization intensity.

[0072] This solution can reduce the impact of outliers in large-scale high-quality reservoir sample data and ensure the reliability of cutoff information for high-quality reservoirs.

[0073] Taking the Neogene strata in area F of the Qaidam Basin as an example, the steps for identifying high-quality reservoirs can be as follows:

[0074] The Qaidam Basin, a saline lacustrine basin under an arid climate during the Neogene, contains multiple lacustrine carbonate sedimentary hydrocarbon-bearing strata. The reservoir lithology primarily consists of algal limestone, algal dolomite, micritic limestone, and micritic dolomite. This geological condition justifies the application of this technical approach. To verify the method's versatility, data were obtained from cored wells in the F area of ​​the Qaidam Basin. Total porosity was obtained using an UltraPore-400 fully automated helium porosimeter; calcite and dolomite mineral content was obtained using a PHILIPS Xpert X-ray diffractometer; and relevant logging data were acquired using a MAXIS-500 system. Based on actual oil testing data, the lower limit of porosity for high-quality reservoirs in this area was determined to be 6%.

[0075] Table 1 shows the core analysis data from systematically cored wells in the F area of ​​the Qaidam Basin. (As shown in Table 1...) Porosity is expressed as a percentage (%); C, D, and W represent the mass of calcite, dolomite, and carbonate mineral content, respectively, in percentage (%); R represents the calculated dolomitization intensity, in percentage (%). A total of 433 sets of core analysis data were obtained from systematically cored wells in this area. Among them, 142 sets of data showed porosity greater than or equal to 6%, representing high-quality reservoirs; while 291 sets of data showed porosity less than 6%, representing low-quality reservoirs.

[0076] Table 1:

[0077]

[0078]

[0079]

[0080]

[0081]

[0082]

[0083]

[0084]

[0085]

[0086]

[0087]

[0088] The 142 sets of high-quality reservoir data were arranged in descending order of carbonate mineral content, and then in descending order of dolomization intensity. This yielded the cutoff information for high-quality reservoirs, which is defined as reservoirs that simultaneously meet the conditions of carbonate mineral content greater than 46.2% and dolomization intensity greater than 56.33%.

[0089] By utilizing the processed and interpreted logging data, continuous calcite and dolomite mineral content information along the vertical direction of a single well can be obtained, thereby calculating the carbonate mineral content and dolomization intensity. Intervals within the target formation that simultaneously meet the conditions of carbonate mineral content greater than 46.2% and dolomization intensity greater than 56.33% are considered high-quality reservoirs.

[0090] Figure 2B This is a schematic diagram illustrating the interpretation results of well F2 in area F of the Qaidam Basin in Embodiment 2 of the present invention. Figure 2B As shown, the first track represents natural gamma ray, the second track represents depth, the third track represents calcite content, the fourth track represents dolomite content, the fifth track represents carbonate mineral content, the sixth track represents dolomization intensity, and the seventh track represents the interpretation conclusion. Tracks 5 and 6 use the high-quality reservoir cutoff value as the baseline, and the layers meeting the high-quality reservoir conditions are indicated by filling in the gaps, thus identifying three layers as high-quality reservoirs, which are marked in track 7 as layers 1, 2, and 3. After comprehensive logging interpretation, layers 1 and 3 are considered water layers, and layer 2 is considered an oil layer. Oil testing was conducted on layer 2, yielding 56.2 tons of oil per day, consistent with the interpretation conclusion, confirming it as a high-quality reservoir.

[0091] The technical solution provided in this application obtains oil testing data and core analysis data of the area to be identified. Based on these data, it determines the cutoff information for high-quality reservoirs in the area, namely the carbonate mineral content threshold and dolomization intensity threshold. Then, using the high-quality reservoir cutoff information and pre-acquired logging data, it identifies the high-quality reservoirs in the area. This solution significantly reduces coring costs and achieves accurate and rapid identification of high-quality carbonate reservoirs.

[0092] Example 3

[0093] Figure 3 This is a schematic diagram of a device for identifying high-quality carbonate reservoirs according to Embodiment 3 of the present invention. This device can execute a method for identifying high-quality carbonate reservoirs provided in any embodiment of the present invention, and possesses the corresponding functional modules and beneficial effects of the method. Figure 3 As shown, the device may include:

[0094] Data acquisition module 310 is used to acquire oil testing data and core analysis data of the area to be identified;

[0095] The high-quality reservoir cutoff information determination module 320 is used to determine the high-quality reservoir cutoff information of the area to be identified based on the oil test data and the core analysis data; the high-quality reservoir cutoff information includes carbonate mineral content threshold and dolomization intensity threshold;

[0096] The high-quality reservoir determination module 330 is used to determine the high-quality reservoir in the area to be identified based on the high-quality reservoir cutoff information and the pre-acquired logging data.

[0097] In this scheme, optionally, the core analysis data includes porosity data, calcite content data, and dolomite content data;

[0098] Accordingly, the high-quality reservoir cutoff information determination module 320 includes:

[0099] The sample data determination unit is used to determine high-quality reservoir sample data based on the oil test data and the porosity data.

[0100] The cutoff information determination unit is used to determine the cutoff information of the high-quality reservoir in the area to be identified based on the high-quality reservoir sample data, the calcite content data, and the dolomite content data.

[0101] Based on the above scheme, optionally, the sample data determining unit includes:

[0102] The lower porosity limit determination subunit is used to determine the lower porosity limit of the high-quality reservoir in the area to be identified based on the oil testing data.

[0103] The sample data determination subunit is used to determine the high-quality reservoir sample data based on the comparison result between the porosity data and the lower limit of the porosity of the high-quality reservoir.

[0104] Specifically, the sample data determination subunit is used for:

[0105] If the porosity is greater than or equal to the lower limit of the porosity of the high-quality reservoir, then the sample corresponding to the porosity is a high-quality reservoir.

[0106] If the porosity is less than the lower limit of the porosity of the high-quality reservoir, then the sample corresponding to the porosity is a non-high-quality reservoir.

[0107] In one feasible solution, optionally, the cutoff information determining unit includes:

[0108] The data determination subunit is used to determine the carbonate mineral content data and dolomite intensity data based on the calcite content data and the dolomite content data.

[0109] The cutoff information determination subunit is used to determine the cutoff information of high-quality reservoirs in the area to be identified based on the carbonate mineral content data and the dolomization intensity data.

[0110] Based on the above embodiments, optionally, the cutoff information determining subunit is specifically used for:

[0111] The high-quality reservoir sample data are sorted according to carbonate mineral content to obtain a sorting result based on carbonate mineral content; and the high-quality reservoir sample data are sorted according to dolomization intensity to obtain a sorting result based on dolomization intensity.

[0112] Based on the ranking results of carbonate mineral content and dolomization intensity, the cutoff information for high-quality reservoirs in the area to be identified is determined.

[0113] Optionally, the cutoff information determining subunit is further used for:

[0114] According to the first preset rule, the sorting results of the carbonate mineral content are truncated to obtain the sorting results of the carbonate mineral content; and according to the second preset rule, the sorting results of the dolomization intensity are truncated to obtain the sorting results of the dolomization intensity.

[0115] Based on the sorting results of carbonate mineral content and dolomization intensity, the cutoff information for high-quality reservoirs in the area to be identified is determined.

[0116] The above-mentioned product can perform the method for identifying high-quality carbonate reservoirs provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects of the method.

[0117] Example 4

[0118] Embodiment 4 of the present invention provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a method for identifying high-quality carbonate reservoirs as provided in all embodiments of the present application:

[0119] Obtain oil testing data and core analysis data for the area to be identified;

[0120] Based on the oil testing data and the core analysis data, the cutoff information for high-quality reservoirs in the area to be identified is determined; the cutoff information for high-quality reservoirs includes the carbonate mineral content threshold and the dolomization intensity threshold.

[0121] Based on the cutoff information of the high-quality reservoir and the pre-acquired logging data, the high-quality reservoir in the area to be identified is determined.

[0122] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0123] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including—but not limited to—electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of transmitting, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0124] The program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0125] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0126] Example 5

[0127] Embodiment 5 of this application provides an electronic device. Figure 4 This is a schematic diagram of the structure of an electronic device provided in Embodiment 5 of this application. Figure 4 As shown, this embodiment provides an electronic device 400, which includes: one or more processors 420; and a storage device 410 for storing one or more programs. When the one or more programs are executed by the one or more processors 420, the one or more processors 420 implement a method for identifying high-quality carbonate reservoirs provided in this application embodiment. The method includes:

[0128] Obtain oil testing data and core analysis data for the area to be identified;

[0129] Based on the oil testing data and the core analysis data, the cutoff information for high-quality reservoirs in the area to be identified is determined; the cutoff information for high-quality reservoirs includes the carbonate mineral content threshold and the dolomization intensity threshold.

[0130] Based on the cutoff information of the high-quality reservoir and the pre-acquired logging data, the high-quality reservoir in the area to be identified is determined.

[0131] Of course, those skilled in the art will understand that the processor 420 also implements the technical solution of the method for identifying high-quality carbonate reservoirs provided in any embodiment of this application.

[0132] Figure 4 The electronic device 400 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0133] like Figure 4 As shown, the electronic device 400 includes a processor 420, a storage device 410, an input device 430, and an output device 440; the number of processors 420 in the electronic device can be one or more. Figure 4 Taking a processor 420 as an example; the processor 420, storage device 410, input device 430, and output device 440 in the electronic device can be connected via a bus or other means. Figure 4 For example, China and Israel are connected via bus 450.

[0134] Storage device 410, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and module units, such as the program instructions corresponding to a method for identifying high-quality carbonate reservoirs in an embodiment of this application.

[0135] Storage device 410 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a given function; the data storage area may store data created based on terminal usage. Furthermore, storage device 410 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory, or other non-volatile solid-state storage device. In some instances, storage device 410 may further include memory remotely located relative to processor 420, which can be connected via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0136] Input device 430 can be used to receive input digital, character, or voice information, and to generate key signal inputs related to user settings and function control of the electronic device. Output device 440 may include electronic devices such as a display screen and a speaker.

[0137] The electronic device provided in this application embodiment can determine the cutoff information of high-quality reservoirs in the area to be identified by using oil testing data and core analysis data, thereby identifying high-quality reservoirs. This greatly reduces core sampling costs while achieving accurate and rapid identification of high-quality carbonate reservoirs.

[0138] The device, medium, and electronic equipment for identifying high-quality carbonate reservoirs provided in the above embodiments can execute the method for identifying high-quality carbonate reservoirs provided in any embodiment of this application, and have the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in the above embodiments can be found in the method for identifying high-quality carbonate reservoirs provided in any embodiment of this application.

[0139] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for identifying high-quality carbonate reservoirs, characterized in that, The method includes: Obtain oil testing data and core analysis data for the area to be identified; Based on the oil testing data and the core analysis data, the cutoff information for high-quality reservoirs in the area to be identified is determined; the cutoff information for high-quality reservoirs includes the carbonate mineral content threshold and the dolomization intensity threshold. Based on the cutoff information of the high-quality reservoir and the pre-acquired logging data, the high-quality reservoir in the area to be identified is determined. The core analysis data includes porosity data, calcite content data, and dolomite content data. Accordingly, determining the cutoff information for high-quality reservoirs in the area to be identified based on the oil testing data and the core analysis data includes: Based on the oil testing data and the porosity data, determine the high-quality reservoir sample data; Based on the high-quality reservoir sample data, the calcite content data, and the dolomite content data, determine the cutoff information for high-quality reservoirs in the area to be identified. The step of determining the cutoff information for high-quality reservoirs in the area to be identified based on the high-quality reservoir sample data, the calcite content data, and the dolomite content data includes: Based on the calcite content data and the dolomite content data, determine the carbonate mineral content data and dolomization intensity data; Based on the carbonate mineral content data and the dolomization intensity data, the cutoff information for high-quality reservoirs in the area to be identified is determined. Wherein, the carbonate mineral content is the sum of the calcite and dolomite contents, and the dolomization intensity is the ratio of the dolomite content to the carbonate mineral content.

2. The method according to claim 1, characterized in that, The step of determining high-quality reservoir sample data based on the oil testing data and the porosity data includes: Based on the oil testing data, determine the lower limit of high-quality reservoir porosity in the area to be identified; Based on the comparison between the porosity data and the lower limit of porosity of the high-quality reservoir, the sample data of the high-quality reservoir are determined.

3. The method according to claim 2, characterized in that, The step of determining high-quality reservoir sample data based on the comparison between the porosity data and the lower limit of porosity of high-quality reservoirs includes: If the porosity is greater than or equal to the lower limit of the porosity of the high-quality reservoir, then the sample corresponding to the porosity is a high-quality reservoir. If the porosity is less than the lower limit of the porosity of the high-quality reservoir, then the sample corresponding to the porosity is a non-high-quality reservoir.

4. The method according to claim 1, characterized in that, The step of determining the cutoff information for high-quality reservoirs in the area to be identified based on the carbonate mineral content data and the dolomization intensity data includes: The high-quality reservoir sample data are sorted according to carbonate mineral content to obtain a sorting result based on carbonate mineral content; and the high-quality reservoir sample data are sorted according to dolomization intensity to obtain a sorting result based on dolomization intensity. Based on the ranking results of carbonate mineral content and dolomization intensity, the cutoff information for high-quality reservoirs in the area to be identified is determined.

5. The method according to claim 4, characterized in that, Before determining the cutoff information for high-quality reservoirs in the area to be identified based on the carbonate mineral content ranking results and dolomization intensity ranking results, the method further includes: According to the first preset rule, the sorting results of the carbonate mineral content are truncated to obtain the sorting results of the carbonate mineral content; and according to the second preset rule, the sorting results of the dolomization intensity are truncated to obtain the sorting results of the dolomization intensity. Based on the sorting results of carbonate mineral content and dolomization intensity, the cutoff information for high-quality reservoirs in the area to be identified is determined.

6. A device for identifying high-quality carbonate reservoirs, characterized in that, The device includes: The data acquisition module is used to acquire oil testing data and core analysis data of the area to be identified. The high-quality reservoir cutoff information determination module is used to determine the high-quality reservoir cutoff information of the area to be identified based on the oil test data and the core analysis data; the high-quality reservoir cutoff information includes carbonate mineral content threshold and dolomization intensity threshold; The high-quality reservoir identification module is used to identify high-quality reservoirs in the area to be identified based on the high-quality reservoir cutoff information and pre-acquired logging data. The core analysis data includes porosity data, calcite content data, and dolomite content data. Accordingly, the high-quality reservoir cutoff information determination module includes: The sample data determination unit is used to determine high-quality reservoir sample data based on the oil test data and the porosity data. The cutoff information determination unit is used to determine the cutoff information of the high-quality reservoir in the area to be identified based on the high-quality reservoir sample data, the calcite content data, and the dolomite content data. The cutoff information determination unit includes: The data determination subunit is used to determine the carbonate mineral content data and dolomite intensity data based on the calcite content data and the dolomite content data. The cutoff information determination subunit is used to determine the cutoff information of high-quality reservoirs in the area to be identified based on the carbonate mineral content data and the dolomization intensity data. Wherein, the carbonate mineral content is the sum of the calcite and dolomite contents, and the dolomization intensity is the ratio of the dolomite content to the carbonate mineral content.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements a method for identifying high-quality carbonate reservoirs as described in any one of claims 1-5.

8. An electronic 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 a method for identifying high-quality carbonate reservoirs as described in any one of claims 1-5.

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