Method, device and equipment for determining lithofacies of lacustrine carbonate rocks and medium

Abstract

The invention discloses a lithofacies determination method, device and equipment for lacustrine facies carbonate rocks and a medium. The method comprises the following steps: acquiring logging data of a target sampling point in a lacustrine facies carbonate rock stratum; wherein the logging data at least comprises a target natural gamma logging parameter and a target content parameter of a target type mineral in the stratum; determining target lithofacies identification parameters according to the logging data; and determining the lithofacies of the target sampling point according to the target lithofacies identification parameters and the target natural gamma logging parameters. According to the method, the lithofacies of the stratum is judged by adopting the natural gamma logging parameters and the content of the main minerals in the stratum, the problem that the carbonate mineral composition of the lacustrine facies is complex can be better solved, and the accuracy of lithofacies evaluation is improved.

Description

Technical Field

[0001] The invention relates to the technical field of petroleum geological exploration and well logging interpretation, and in particular to a method, device, equipment and medium for determining the lithofacies of lacustrine carbonate rocks. Background Art

[0002] Lacustrine carbonates are the most widely distributed type of terrestrial carbonates, and they refer to carbonates formed in inland lake basins. Affected by the sedimentary environment, lacustrine carbonates have a higher content of terrigenous debris than marine carbonates, with a faster change in mineral content in the vertical direction and a more complex mineral composition. They often show mixed depositional characteristics, which brings great difficulties to the evaluation of lithofacies by logging. Studies have found that traditional methods for evaluating lithofacies have poor results in identifying mixed depositional lacustrine carbonates. Summary of the invention

[0003] The present invention provides a method, device, equipment and medium for determining the lithofacies of lacustrine carbonate rocks, so as to solve the problem of unclear lithofacies identification caused by complex mineral components.

[0004] According to one aspect of the present invention, a method for determining the lithofacies of lacustrine carbonate rocks is provided, comprising:

[0005] Acquire logging data of a target sampling point in a lacustrine carbonate formation; wherein the logging data at least includes target natural gamma logging parameters and target content parameters of target type minerals in the formation;

[0006] Determine target lithofacies identification parameters based on well logging data;

[0007] The lithofacies of the target sampling point are determined based on the target lithofacies identification parameters and the target natural gamma logging parameters.

[0008] According to another aspect of the present invention, a device for determining the lithology of lacustrine carbonate rock is provided, characterized in that it comprises:

[0009] Data acquisition module: used to acquire logging data of target sampling points in lacustrine carbonate formations; wherein the logging data at least includes target natural gamma logging parameters and target content parameters of target type minerals in the formation;

[0010] Lithofacies identification parameter determination module: used to determine target lithofacies identification parameters based on well logging data;

[0011] Lithofacies determination module: used to determine the lithofacies of the target sampling point based on the target lithofacies identification parameters and the target natural gamma logging parameters.

[0012] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0013] at least one processor; and

[0014] a memory communicatively connected to the at least one processor; wherein,

[0015] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for determining the lithology of lacustrine carbonate rocks described in any embodiment of the present invention.

[0016] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the method for determining the lithology of lacustrine carbonate rocks described in any embodiment of the present invention when executed by a processor.

[0017] The technical solution of the embodiment of the present invention can better solve the problem of complex lacustrine carbonate mineral composition by using natural gamma logging parameters and the content of major minerals in the formation to determine the lithofacies of the formation, thereby improving the accuracy of lithofacies evaluation.

[0018] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 A flowchart of a method for determining the lithofacies of lacustrine carbonate rocks according to the first embodiment of the present invention;

[0021] Figure 2 A lithofacies cross-section diagram provided according to Example 1 of the present invention;

[0022] Figure 3 A cross-plot of lithofacies identification parameters and natural gamma logging parameters provided according to the first embodiment of the present invention;

[0023] Figure 4 A schematic diagram of the structure of a device for determining the lithology of lacustrine carbonate rocks provided in the second embodiment of the present invention;

[0024] Figure 5 A schematic diagram of the structure of an electronic device for implementing the method for determining the lithology of lacustrine carbonate rocks according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "candidate", "target", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] Embodiment 1

[0028] Figure 1 A flowchart of a method for determining the facies of lacustrine carbonate rock is provided for the first embodiment of the present invention. This embodiment is applicable to the situation where the mineral composition of lacustrine carbonate rock is complex and the facies is difficult to evaluate. The method can be executed by a lacustrine carbonate rock facies determination device, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0029] S110, obtaining logging data of a target sampling point in a lacustrine carbonate formation; wherein the logging data at least includes a target natural gamma logging parameter and a target content parameter of a target type of mineral in the formation.

[0030] The target sampling point may be a portion of a lacustrine carbonate formation that requires petrographic analysis, such as a core well S1 on a lacustrine carbonate formation in area Y of basin A. Well logging data may be data that can characterize rock properties when measuring formation rocks. In this embodiment, the well logging data includes at least target natural gamma logging parameters and target content parameters of target type minerals in the formation.

[0031] Among them, natural gamma logging is a method of measuring the natural gamma ray intensity of rock formations along the wellbore. According to the results of natural gamma logging, the geological profile of the borehole can be divided, the sandstone shale content in the sandstone shale profile can be determined, and the permeability of the rock formation can be qualitatively judged. Natural gamma logging parameters are used to characterize the natural radioactivity of formation rocks.

[0032] Furthermore, the natural gamma logging parameters are used as logging data because the higher the rock mud content, the finer the particles, and the stronger the radioactivity. For example, rocks contain natural radionuclides, mainly radioactive isotopes of uranium, thorium and potassium. The strength of the radioactivity of sedimentary rock formations is mainly determined by two factors: the content of clay minerals and the specific surface area of ​​the rock. Clay minerals in sedimentary rocks have the highest radioactivity, while chemical rocks such as gypsum and salt rock have the lowest radioactivity. Montmorillonite has the largest specific surface area, strong adsorption capacity for radioactive substances, contains more uranium oxide, and contributes the most to the radioactivity of mudstone; illite contains potassium, has a certain adsorption capacity for uranium oxide, and has a certain radioactivity. In addition, the finer the rock particles, the larger its specific surface area, the stronger its adsorption capacity for radioactive substances, and the larger the natural gamma value. The natural gamma value of the gray-dolomitic mudstone with the highest mud content and the finest rock particles is the highest, while the natural gamma value of the gray-dolomitic mudstone with the lowest mud content and the coarsest rock particles is the lowest. The mud content and rock grain size of micrite lime dolomite and laminated lime dolomite are between the first two, so the natural gamma is also between the two. Therefore, the use of natural gamma logging parameters can more intuitively observe the radioactivity of rocks, thereby better describing the characteristics of rocks.

[0033] The target type minerals in the stratum include at least calcite minerals, dolomite minerals and clay minerals. Further, the target type minerals in the stratum may also include quartz minerals, feldspar minerals, anhydrite minerals and the like.

[0034] Furthermore, the content parameters of target type minerals in the formation are used as logging data because the mineral composition and content of different lithofacies are different. For example, due to the influence of multiple factors such as the injection intensity of source materials during the sedimentary period, water salinity, hydrodynamic conditions and paleo-geomorphology, the mineral composition and content of different lithofacies are different. Granular lime dolomite develops at the top of the underwater depression and the upper part of the slope belt with strong hydrodynamics. The particles are mainly composed of well-sorted and highly rounded carbonate sand fragments and terrigenous debris, and the content of carbonate minerals (calcite and dolomite) is also the highest. Micritic lime dolomite develops in the middle of the slope belt with weak hydrodynamics. The main components are micritic carbonate and mud, and the content of carbonate minerals is lower than that of granular lime dolomite. The depositional environment of laminated lime dolomite is a quiet water body with rhythmic recharge from deeper water. The core has shale-like structural characteristics and is mainly formed by the superposition of dark lime-containing mud-silty terrigenous debris laminae and pure carbonate laminae. The content of carbonate minerals is slightly lower than that of micritic lime dolomite, and the content of clay minerals is higher. Gypsum mudstone is a shallow water low-energy evaporite deposit, and its composition is mainly clay minerals and anhydrite. Lime dolomitic mudstone develops in deep-water depressions with the weakest hydrodynamics. The main components are clay minerals, followed by micritic carbonate, and the content of clay minerals is the highest. Therefore, analyzing the composition of rock strata based on the composition and content of different minerals in the rock strata can better distinguish different rock strata, thereby improving the accuracy of lithofacies identification.

[0035] Furthermore, target natural gamma logging parameters and target content parameters of target type minerals in the formation can be measured using MAXIS-500 logging series instruments or CLS-5700 logging series instruments.

[0036] For example, the MAXIS-500 logging series instrument is used to measure the lacustrine carbonate formation, so as to obtain the target natural gamma logging parameters of the target sampling point in the lacustrine carbonate formation, the target content parameters of the target type of minerals in the formation, such as the target content W of the calcite mineral in the formation. cal , the target content of dolomite minerals in the formation W dol , the target content of clay minerals in the formation W cla .

[0037] S120, determining target lithofacies identification parameters according to the well logging data.

[0038] Among them, the lithofacies identification parameters are used to characterize the information for distinguishing different lithofacies according to the natural gamma logging parameters in the logging data and the content parameters of the target type of minerals in the formation. Specifically, the lithofacies identification parameters are determined according to the degree of influence of the natural gamma logging parameters in the logging data and the content parameters of the target type of minerals in the formation on the lithofacies.

[0039] Optionally, the target lithofacies identification parameters are determined based on the well logging data and can be expressed by the following formula:

[0040]

[0041] Among them, LF is the target lithofacies identification parameter, GR base is the mudstone baseline value, that is, the natural gamma logging parameter under pure mudstone in the lacustrine carbonate formation. In the conventional sandstone mudstone section, the natural gamma logging parameter of pure mudstone is relatively large, which can reach above 80API; in the sandstone section, the natural gamma logging parameter of pure mudstone is relatively small, generally below 40API; and in the muddy sandstone and sandy mudstone sections, the natural gamma logging parameter of pure mudstone is between 40 and 80API; GR is the target natural gamma logging parameter of the target sampling point, W cal is the target content of calcite minerals in the formation, W dol is the target content of dolomite minerals in the formation, W cla is the target content of clay minerals in the formation.

[0042] For example, the natural gamma ray logging parameter GR = 80, the mudstone baseline value GR base =150, target content of calcite minerals in the formation W cal = 25%, the target content of dolomite minerals in the formation W dol =35%, target content of clay minerals in the formation W cla =20%, and the target lithofacies identification parameter of the lacustrine carbonate formation is calculated using the lithofacies identification index formula as LF=210.

[0043] S130, determining the lithofacies of the target sampling point according to the target lithofacies identification parameters and the target natural gamma logging parameters.

[0044] Among them, the lithofacies include granular lime dolomite, mud-crystalline lime dolomite, laminated lime dolomite, gypsum mudstone and lime dolomitic mudstone.

[0045] Based on the influence relationship between the predetermined lithofacies identification parameters and natural gamma logging parameters on lithofacies, the lithofacies of the target sampling point are determined according to the target lithofacies identification parameters and the target natural gamma logging parameters. The influence relationship between the predetermined lithofacies identification parameters and the natural gamma logging parameters on lithofacies can be determined according to the cross plot of the pre-calibrated lithofacies identification parameters and the natural gamma logging parameters, or based on the fuzzy recognition algorithm, a classification criterion is established according to the pre-calibrated lithofacies identification parameters and the natural gamma logging parameters, and the influence of the lithofacies identification parameters and the natural gamma logging parameters on lithofacies is determined according to the classification criterion. The fuzzy recognition algorithm is a method for classifying the objects to be identified into the corresponding standard library under a given standard library. Classification is completed through classification criteria, and the commonly used classification criteria are the maximum membership principle and the proximity principle. The maximum membership principle: obtain the membership of each element to each category, and the element belongs to the class with the largest membership; the proximity principle is used to measure the closeness between two sets, usually expressed by σ(A,B). The greater the closeness, the closer and more similar the two fuzzy sets are.

[0046] Optionally, the lithofacies of the target sampling point is determined according to the relationship between the target lithofacies identification parameter and the target natural gamma logging parameter, including step A1:

[0047] Based on the cross plot of pre-calibrated lithofacies identification parameters and natural gamma logging parameters, the lithofacies of the target sampling point is determined according to the position information of the target lithofacies identification parameters and the target natural gamma logging parameters in the cross plot.

[0048] The cross plot can be a graph that can represent the relationship between formation logging parameters or other parameters. For example, the cross plot can be a cross plot, a frequency cross plot, a Z value plot or a histogram. The cross plot is mainly used to identify the mineral composition of rocks in the formation, the lithology combination of the formation, and calculate the geological parameters of the formation.

[0049] The positions of the target lithofacies identification parameters and the target natural gamma logging parameters are found in the crossplot, and the lithofacies corresponding to the positions are taken as the lithofacies of the target sampling points.

[0050] For example, the LF curve of a single well is calculated, and the GR and LF values ​​of each sampling point are matched to the area in the chart, and the lithofacies of the sampling point can be obtained. For example, GR = 120, LF = 100, and the lithofacies of the sampling point in the chart is gray-dolomite mudstone. By analogy, the lithofacies of each sampling point can be obtained, and thus the lithofacies of Well S1 can be obtained, and its lithofacies profile can be obtained, such as Figure 2 As shown, the depth section 3915m-3934m is compared with the core data, and the consistency rate is 87%.

[0051] Optionally, the calibration process of the cross plot of lithofacies identification parameters and natural gamma logging parameters includes steps B1-B3:

[0052] Step B1, obtaining core data of lacustrine carbonate rocks; wherein the core data includes calibrated lithofacies identification parameters of multiple calibration points, calibrated natural gamma logging parameters and calibrated lithofacies.

[0053] The core can be a columnar rock sample drilled out from the lacustrine carbonate formation. The core data can be obtained by using coring tools to take up the underground rocks, sort, describe and analyze them, obtain various parameters of the formation, and restore the original formation profile.

[0054] The calibration points may be points around the target sampling points of the lacustrine carbonate formation that can provide formation information.

[0055] During the drilling process, the underground rocks at the calibration point are taken out by coring tools, and the core data of lacustrine carbonate rocks are obtained through analysis and collation, namely the calibration lithofacies identification parameters, calibration natural gamma logging parameters and calibration lithofacies of the calibration point.

[0056] Step B2: Project the core data into the cross-plot.

[0057] According to the relationship between core data, the core data of different lithofacies are projected into the GR-LF cross plot. The core data can be projected into the cross plot using Excel or generated by code.

[0058] Step B3: Divide the areas of different types of lithofacies according to the data information of the calibration points in the cross-plot to obtain the final cross-plot.

[0059] Different types of lithofacies areas are divided according to the position of the data information of the calibrated points in the cross-plot, so as to obtain the final cross-plot, such as Figure 3 As shown, the distribution of five types of stratigraphic facies can be seen from the figure. Exemplarily, the location areas of different facies are determined based on the data aggregation results of the marked point data information in the intersection diagram.

[0060] The technical solution of this embodiment, by using natural gamma logging parameters and the content of major minerals in the formation to determine the lithofacies of the formation, can better solve the problem of complex lacustrine carbonate mineral composition and improve the accuracy of lithofacies evaluation.

[0061] Embodiment 2

[0062] Figure 4 This is a schematic diagram of the structure of a device for determining the facies of lacustrine carbonate rocks provided in the second embodiment of the present invention. Figure 4 As shown, the device includes: a data acquisition module 210, a lithofacies identification parameter determination module 220, and a lithofacies determination module 230. Among them,

[0063] The data acquisition module 210 is used to acquire the logging data of the target sampling point in the lacustrine carbonate formation; wherein the logging data at least includes the target natural gamma logging parameters and the target content parameters of the target type of minerals in the formation;

[0064] The lithofacies identification parameter determination module 220 is used to determine the target lithofacies identification parameters according to the well logging data;

[0065] The lithofacies determination module 230 is used to determine the lithofacies of the target sampling point according to the target lithofacies identification parameters and the target natural gamma logging parameters.

[0066] Optionally, in the data acquisition module 210, the target type minerals include at least calcite minerals, dolomite minerals and clay minerals.

[0067] Optionally, the lithofacies identification parameter determination module 220 is specifically used for:

[0068] The target lithofacies identification parameters are determined according to the following formula:

[0069]

[0070] Among them, LF is the target lithofacies identification parameter, GR base is the mudstone baseline value, i.e., the natural gamma logging parameter under pure mudstone in the lacustrine carbonate formation; GR is the target natural gamma logging parameter of the target sampling point, W cal is the target content of calcite minerals in the formation, W dol is the target content of dolomite minerals in the formation, W cla is the target content of clay minerals in the formation.

[0071] Optionally, the lithofacies determination module 230 is specifically used for:

[0072] Based on the cross plot of pre-calibrated lithofacies identification parameters and natural gamma logging parameters, the lithofacies of the target sampling point is determined according to the position information of the target lithofacies identification parameters and the target natural gamma logging parameters in the cross plot.

[0073] Optionally, the apparatus for determining the lithology of lacustrine carbonate rocks further comprises:

[0074] Calibration module: used to calibrate the crossplot of lithofacies identification parameters and natural gamma logging parameters based on core data of lacustrine carbonate rocks;

[0075] The above calibration module, the lithofacies include granular lime dolomite, micrite lime dolomite, laminated lime dolomite, gypsum mudstone and lime dolomitic mudstone, including:

[0076] A core data acquisition unit, used to acquire core data of lacustrine carbonate rocks; wherein the core data includes calibrated lithofacies identification parameters, calibrated natural gamma logging parameters and calibrated lithofacies of multiple calibration points;

[0077] A data projection unit, used to project the core data into the crossplot;

[0078] The cross-plot acquisition unit is used to divide the areas of different types of lithofacies according to the data information of the calibration points in the cross-plot to obtain the final cross-plot.

[0079] The apparatus for determining the lithofacies of lacustrine carbonate rocks provided in the embodiment of the present invention can execute the method for determining the lithofacies of lacustrine carbonate rocks provided in any embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method.

[0080] The acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws and regulations and do not violate public order and good morals.

[0081] Embodiment 3

[0082] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0083] Figure 5 A schematic diagram of the structure of an electronic device for implementing the method for determining the facies of lacustrine carbonate rocks of an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0084] like Figure 5As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0085] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0086] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the facies determination method of lacustrine carbonate rocks.

[0087] In some embodiments, the petrographic determination method of lacustrine carbonate rocks may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the petrographic determination method of lacustrine carbonate rocks described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the petrographic determination method of lacustrine carbonate rocks in any other appropriate manner (e.g., by means of firmware).

[0088] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific reference products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0089] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0090] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0091] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0092] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0093] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0094] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0095] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for determining the lithofacies of lacustrine carbonate rocks, characterized in that: The method includes: Acquire logging data of a target sampling point in a lacustrine carbonate formation; wherein the logging data at least includes target natural gamma logging parameters and target content parameters of target type minerals in the formation; determining target lithofacies identification parameters according to the well logging data; The lithofacies of the target sampling point is determined according to the target lithofacies identification parameters and the target natural gamma logging parameters.

2. The method according to claim 1, characterized in that The target type minerals include at least calcite minerals, dolomite minerals and clay minerals.

3. The method according to claim 2, characterized in that Determining target lithofacies identification parameters according to the logging data includes: The target lithofacies identification parameters are determined according to the following formula: Among them, LF is the target lithofacies identification parameter, GR base is the mudstone baseline value, i.e., the natural gamma logging parameter under pure mudstone in the lacustrine carbonate formation; GR is the target natural gamma logging parameter of the target sampling point, W cal is the target content of calcite minerals in the formation, W dol is the target content of dolomite minerals in the formation, W cla is the target content of clay minerals in the formation.

4. The method according to claim 1, characterized in that: Determining the lithofacies of the target sampling point according to the target lithofacies identification parameter and the target natural gamma logging parameter includes: Based on a cross plot of pre-calibrated lithofacies identification parameters and natural gamma logging parameters, the lithofacies of the target sampling point is determined according to position information of the target lithofacies identification parameters and the target natural gamma logging parameters in the cross plot.

5. The method according to claim 4, characterized in that The calibration process of the cross plot of the lithofacies identification parameters and the natural gamma logging parameters includes: Acquire core data of the lacustrine carbonate rock; wherein the core data includes calibrated lithofacies identification parameters, calibrated natural gamma logging parameters and calibrated lithofacies of multiple calibration points; Projecting the core data into the crossplot; The regions of different types of lithofacies are divided according to the data information of the calibration points in the cross-plot to obtain a final cross-plot.

6. The method according to claim 1, characterized in that The lithofacies include granular lime dolomite, micrite lime dolomite, laminated lime dolomite, gypsum mudstone and lime dolomitic mudstone.

7. A device for determining the facies of lacustrine carbonate rocks, characterized in that: include: Data acquisition module: used to acquire logging data of target sampling points in lacustrine carbonate formations; wherein the logging data at least includes target natural gamma logging parameters and target content parameters of target type minerals in the formation; A lithofacies identification parameter determination module is used to determine target lithofacies identification parameters according to the well logging data; The lithofacies determination module is used to determine the lithofacies of the target sampling point according to the target lithofacies identification parameters and the target natural gamma logging parameters.

8. The device according to claim 7, characterized in that The device also includes: Calibration module: used for calibrating the crossplot of lithofacies identification parameters and natural gamma logging parameters according to the core data of the lacustrine carbonate rock.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for determining the lithology of lacustrine carbonate rocks according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for determining the lithology of lacustrine carbonate rocks according to any one of claims 1 to 7 when executed.

Images