Well logging curve standardization method and device, electronic equipment and storage medium

Abstract

The invention discloses a logging curve standardization method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a well logging curve and data of a target layer section drilling well in a research area; according to the data and the logging curve, the carbonate rock compact layer of the target layer section is identified, and the compact layer is determined; taking multiple sets of compact layers of the single well as standard layers, determining a frequency distribution histogram of the standard layers, and determining curve characteristic values of the standard layers based on the frequency distribution histogram; averaging the curve characteristic values to obtain a standard value of the standard layer; and according to the standard value, standardizing the logging curves of all wells by adopting a translation method to obtain a target logging curve. According to the technical scheme, fine standardization processing can be carried out on stratums which are high in heterogeneity and free of stable and continuous distribution standard stratums, the high-quality logging curve meeting the reservoir inversion requirement is obtained, the precision of multi-well logging curve reservoir prediction is improved, and great significance is achieved on reservoir evaluation of heterogeneity stratums.

Description

Technical Field

[0001] The present invention relates to the technical field of petroleum exploration and development, and in particular to a logging curve standardization method, device, electronic equipment and storage medium. Background Art

[0002] In the process of logging curve collection, the logging curves of the wells in a research block are often collected at different times by different staff using different logging instruments. Therefore, there are inevitably certain systematic errors in the logging curves between different wells. The standardization of logging curves can eliminate the systematic errors in the logging curves between multiple wells and increase the comparability of the logging curves between multiple wells. Therefore, the standardization of logging curves is the basis for comprehensive evaluation of reservoir logging and joint well-seismic inversion.

[0003] At present, the commonly used methods for logging curve standardization are mostly the mean method, histogram method and trend surface method. Different standardization methods are used according to the different geological and data conditions in the study area. The theoretical basis for logging curve standardization is that in the same sedimentary environment, strata with similar lithology have similar logging response characteristics. Therefore, no matter which method is used, selecting a stable standard layer with little thickness change in the vertical direction and continuous distribution in the horizontal direction in the study area is the key to logging curve standardization.

[0004] Due to the complexity of stratum deposition in continental sedimentary environments, strata have strong heterogeneity, making it difficult to find a standard layer with stable distribution. Due to the influence of various factors such as diverse rock types, variable sedimentary environments, and structures and diagenesis, marine strata have stronger heterogeneity, making it more difficult to construct a standard layer, which affects the evaluation and research of carbonate reservoirs. Summary of the invention

[0005] The present invention provides a logging curve standardization method, device, electronic equipment and storage medium, which can perform fine standardization processing on formations with strong heterogeneity and no stable and continuously distributed standard layers, obtain high-quality logging curves that meet the requirements of reservoir inversion, improve the accuracy of reservoir prediction of multi-well logging curves, and have important significance for reservoir evaluation of heterogeneous formations.

[0006] According to one aspect of the present invention, a method for normalizing a well logging curve is provided, the method comprising:

[0007] Obtaining logging curves and data of drilling in the target layer section of the study area; wherein the logging curves include acoustic time difference logging curves, compensated neutron logging curves and compensated density logging curves; the data include coring, logging lithology, geological stratification and oil testing data;

[0008] Identify the carbonate rock dense layer in the target layer section according to the data and the logging curve, and determine the dense layer;

[0009] Taking multiple sets of dense layers in a single well as standard layers, determining a frequency distribution histogram of the standard layers, and determining a curve characteristic value of the standard layers based on the frequency distribution histogram;

[0010] Calculating the average of the characteristic values ​​of the curve to obtain the standard value of the standard layer;

[0011] According to the standard value, the well logging curves of all wells are standardized by using the translation method to obtain the target well logging curve.

[0012] According to another aspect of the present invention, a logging curve standardization device is provided, the device comprising:

[0013] The logging curve and data acquisition module is used to obtain the logging curve and data of the target layer section in the study area; wherein the logging curve includes the acoustic time difference logging curve, the compensated neutron logging curve and the compensated density logging curve; the data includes the coring, logging lithology, geological stratification and oil testing data;

[0014] A dense layer identification module is used to identify the dense carbonate layer in the target layer section according to the data and the logging curve, and determine the dense layer;

[0015] A curve characteristic value determination module is used to take multiple sets of dense layers in a single well as standard layers, determine a frequency distribution histogram of the standard layers, and determine the curve characteristic value of the standard layers based on the frequency distribution histogram;

[0016] A standard value obtaining module is used to calculate the average of the characteristic values ​​of the curve to obtain the standard value of the standard layer;

[0017] The logging curve standardization module is used to standardize the logging curves of all wells using a translation method according to the standard value to obtain a target logging curve.

[0018] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0019] at least one processor; and

[0020] a memory communicatively connected to the at least one processor; wherein,

[0021] 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 a logging curve normalization method described in any embodiment of the present invention.

[0022] 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 enable a processor to implement a logging curve standardization method described in any embodiment of the present invention when executed.

[0023] The technical solution of the embodiment of the present invention obtains the logging curves and data of the target layer section in the study area, identifies the carbonate rock dense layer in the target layer section according to the data and the logging curves, determines the dense layer, and then uses multiple sets of dense layers in a single well as standard layers to determine the frequency distribution histogram of the standard layer, and determines the curve characteristic value of the standard layer based on the frequency distribution histogram, calculates the average of the curve characteristic value, obtains the standard value of the standard layer, and uses the translation method to standardize the logging curves of all wells according to the standard value to obtain the target logging curve. This technical solution can perform fine standardization on formations with strong heterogeneity and no stable and continuously distributed standard layers, obtain high-quality logging curves that meet the requirements of reservoir inversion, improve the accuracy of reservoir prediction of multi-well logging curves, and is of great significance for reservoir evaluation of heterogeneous formations.

[0024] 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

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. 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.

[0026] Figure 1 is a flow chart of a logging curve standardization method provided according to Embodiment 1 of the present invention;

[0027] Figure 2 This is a schematic diagram of identifying a dense carbonate layer in a single well provided in Example 1 of the present application;

[0028] Figure 3 It is a diagram of the acoustic time difference and compensated neutron intersection between the reservoir and the dense layer before the well logging curve is normalized provided in Example 1 of the present application;

[0029] Figure 4 It is a diagram of the acoustic time difference and compensated neutron intersection between the reservoir and the dense layer after the well logging curve is standardized provided in Example 1 of the present application;

[0030] Figure 5 A schematic diagram of the structure of a well logging curve standardization device provided in the second embodiment of the present invention;

[0031] Figure 6 It is a structural schematic diagram of an electronic device for implementing a logging curve standardization method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] 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.

[0033] It should be noted that the term "target" and the like 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 of their variations 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.

[0034] Embodiment 1

[0035] Figure 1 1 is a flow chart of a logging curve standardization method provided according to the first embodiment of the present invention. This embodiment is applicable to the case of standardizing the logging curve. The method can be executed by a logging curve standardization device. The logging curve standardization device can be implemented in the form of hardware and / or software. The logging curve standardization device can be configured in an electronic device. Figure 1 As shown, the method includes:

[0036] S110, obtaining logging curves and data of drilling in the target layer section of the study area; wherein the logging curves include acoustic time difference logging curves, compensated neutron logging curves and compensated density logging curves; the data include coring, logging lithology, geological stratification and oil testing data.

[0037] In this scheme, the target layer section may refer to the homogeneous carbonate rock formation in the study area.

[0038] Among them, acoustic time difference logging is a logging method developed based on the acoustic physical properties of rocks. It measures the velocity of formation sound waves. Compensated neutron logging is a neutron logging method that overcomes the influence of irregular changes in the borehole after performing layout correction on the basis of neutron logging. It simultaneously records two neutron curves with different source distances, which are used to calculate porosity in open holes or cased wells. Since the detection depth of density logging is not large and is generally limited to the flushing zone, the mud cake and other media between the instrument and the well wall have a greater impact on the logging results and must be corrected. Therefore, density logging often uses a dual detector device with a long source distance and a short source distance to correct the influence of media such as mud cake. This dual source distance density logging is also called compensated density logging.

[0039] In this embodiment, coring is a method of lowering a coring device into the well using a logging cable, driving the coring device into the well wall using explosives, and removing small pieces of rock to understand the properties of the rock and the fluid therein; logging is a method of interpreting and locating lithology based on comprehensive on-site geological data, on-site logging data, and comprehensive analysis and testing data to determine the oil, gas, and water production conditions; geological stratification refers to the division of rock layers in the stratigraphic profile of a region; the main purpose of oil testing is to test whether the fluid in a certain formation is oil or water.

[0040] In this plan, the logging curves and data of the target layer section in the study area can be obtained through exploration drilling, that is, the sonic time difference, compensated neutron and compensated density logging curves of the target layer section in the study area, as well as the coring, logging lithology, geological stratification, and oil testing data can be obtained.

[0041] S120. Identify the carbonate rock dense layer in the target layer segment according to the data and the logging curve, and determine the dense layer.

[0042] In this embodiment, the natural potential logging curve of a large section of mudstone is generally taken as the mudstone baseline, and the well section deviating from the mudstone baseline can be considered as a permeable rock formation. The formation with very poor permeability is often called a dense layer, and its natural potential logging curve is close to the mudstone baseline or the amplitude of the curve is abnormally small.

[0043] In this scheme, the tight layer of carbonate formation can be identified by using three-porosity logging curves in combination with oil test data and lithology data, that is, the tight layer of carbonate formation can be identified by using acoustic time difference logging curves, compensated neutron logging curves and compensated density logging curves.

[0044] Optionally, identifying the carbonate rock dense layer in the target layer section according to the data and the well logging curve to determine the dense layer includes:

[0045] Determine the dense layer discrimination value based on the data and the logging curve;

[0046] The carbonate rock dense layer of the target layer section is identified based on the dense layer discrimination amount to determine the dense layer.

[0047] In this scheme, two porosity logging curves that are most sensitive to reservoir physical properties can be selected, for example, the sonic time difference and the compensated neutron curve. That is, a dense layer discrimination formula is established through the sonic time difference and the compensated neutron curve to identify the dense layer in the target layer section of each well.

[0048] Specifically, the dense layer discrimination value can be determined by the established dense layer discrimination formula, and the carbonate rock dense layer in the target layer section can be identified based on the dense layer discrimination value.

[0049] Optionally, the dense layer of carbonate rock in the target layer segment is identified based on the dense layer discriminant to determine the dense layer, including:

[0050] When the dense layer discrimination value is less than a preset layer segment identification threshold, the target layer segment is determined as a dense layer.

[0051] The layer segment identification threshold can be set according to the dense layer identification requirements. For example, the layer segment identification threshold can be set to -20.

[0052] In this scheme, two porosity logging curves that are most sensitive to reservoir physical properties can be selected to construct a dense layer discriminant, and the dense layer discriminant is compared with the layer segment identification threshold to determine whether the target layer segment is a dense layer.

[0053] By determining the dense layer, a standard layer can be constructed based on the dense layer, so that the well logging curve can be standardized based on the standard layer.

[0054] Optionally, determining the dense layer discrimination value according to the data and the logging curve includes:

[0055] The dense layer discrimination amount is determined in the following manner;

[0056] A=CNLp-ACp;

[0057] Wherein, A represents the dense layer discrimination value, CNLp represents the normalized curve value of the compensated neutron logging curve, and ACp represents the anti-normalized curve value of the acoustic time difference logging curve.

[0058] In this solution, the acoustic time difference curve is denormalized, that is, the maximum scale is normalized to 0, and the minimum scale is normalized to 100. Specifically, the acoustic time difference curve is denormalized using the following formula;

[0059] AC p =(AC max -AC) / (AC max -AC min )×100;

[0060] Among them, AC p is the curve value after the acoustic time difference curve is denormalized, dimensionless; AC max The maximum value of the acoustic time difference curve of the target layer, in μs·m -1 ;AC min It is the minimum value of the acoustic time difference curve of the target layer, in μs·m -1 ; AC is the logging value of the acoustic time difference curve of the target layer, unit: μs·m -1 .

[0061] In this embodiment, the normalization process of the compensated neutron curve is to normalize the maximum scale to 100 and the minimum scale to 0. Specifically, the normalization process of the compensated neutron curve is performed using the following formula:

[0062] CNL p =(CNL-CNL min ) / (CNL max -CNL min )×100;

[0063] Among them, CNL p The normalized curve value to compensate for the neutron curve is dimensionless; CNL max The maximum value of the neutron curve compensation for the target layer, in %; CNL min is the minimum value of the compensated neutron curve of the target layer, in %; CNL is the logging value of the compensated neutron curve of the target layer, in %.

[0064] Furthermore, a dense layer discrimination formula is established to identify the dense layer in the target layer section of each well: A=CNLp-ACp, A<-20 is a dense layer.

[0065] By determining the dense layer, a standard layer can be constructed based on the dense layer, so that the well logging curve can be standardized based on the standard layer.

[0066] In this embodiment, Figure 2 Schematic diagram of single well carbonate rock tight layer identification provided in Example 1 of the present application, such as Figure 2 As shown in the figure, the dense layer discrimination formula is used to identify the dense carbonate layer in the target layer, and the identification result (A) is consistent with the qualitative identification (AC-CNL curve overlap method) result.

[0067] S130, taking multiple sets of dense layers in a single well as standard layers, determining a frequency distribution histogram of the standard layers, and determining a curve characteristic value of the standard layers based on the frequency distribution histogram.

[0068] In this scheme, multiple sets of dense layers in a single well can be used as a standard layer, a frequency distribution histogram can be made for the standard layer of each well, and the curve characteristic value of the standard layer can be determined based on the frequency distribution histogram.

[0069] Optionally, determining the curve characteristic value of the standard layer based on the frequency distribution histogram includes:

[0070] The main peak value of the frequency distribution histogram is used as the curve characteristic value of the standard layer.

[0071] In this embodiment, multiple sets of dense layers in a single well can be used as a standard layer, a frequency distribution histogram is made for the standard layer of each well, and the main peak value of the frequency distribution histogram is used as the curve characteristic value of the standard layer.

[0072] By determining the characteristic values ​​of the curves, standard values ​​can be constructed based on the characteristic values ​​of the curves, so that formations with strong heterogeneity and no stable and continuously distributed standard layers can be finely standardized to obtain high-quality logging curves that meet the needs of reservoir inversion, thereby improving the accuracy of reservoir prediction of multi-well logging curves, which is of great significance for reservoir evaluation of heterogeneous formations.

[0073] S140, calculating the average of the characteristic values ​​of the curve to obtain the standard value of the standard layer.

[0074] Specifically, multiple wells with complete logging data, reliable quality and oil test data are selected, and the arithmetic average of the curve characteristic values ​​of their standard layers is calculated, and the average value is taken as the standard value of the standard layer of the key well. The average of multiple wells with high logging quality is selected as a key well to avoid the situation where the scale of the logging curve may be too high or too low and inconsistent with the actual formation logging value due to selecting a well as a key well.

[0075] S150. Based on the standard value, the well logging curves of all wells are standardized by using a translation method to obtain a target well logging curve.

[0076] Translation refers to moving all points on a figure the same distance in a straight line direction within the same plane.

[0077] In this scheme, the standard value is used as a benchmark and the translation method is used to standardize the logging curves of all wells.

[0078] Optionally, according to the standard value, the well logging curves of all wells are standardized by using a translation method to obtain a target well logging curve, including:

[0079] Subtracting the standard value from the curve characteristic value to obtain a correction amount for the standard layer;

[0080] The well logging curves of all wells are standardized according to the correction amount to obtain a target well logging curve.

[0081] In this scheme, the standard value can be subtracted from the curve characteristic value of the standard layer of each well to obtain the correction amount of the standard layer.

[0082] Furthermore, the well logging curves of all wells are corrected according to the correction amount, so as to achieve standardization of the well logging curves and obtain a standardized target well logging curve.

[0083] For formations with strong heterogeneity and no stable and continuously distributed standard layers, fine standardization processing can be performed to obtain high-quality logging curves that meet the needs of reservoir inversion, improve the accuracy of reservoir prediction of multi-well logging curves, and have important significance for reservoir evaluation of heterogeneous formations.

[0084] Optionally, after obtaining the target logging curve, the method further includes:

[0085] Target logging curves of the reservoir and the dense layer and an intersection diagram of the logging curves are constructed, and the reservoir and the dense layer are compared based on the intersection diagram.

[0086] In this program, Figure 3 It is a diagram of the acoustic time difference and compensated neutron intersection between the reservoir and the dense layer before the well logging curve is normalized provided in Example 1 of the present application; Figure 4 This is the intersection diagram of the acoustic time difference between the reservoir and the dense layer and the compensated neutron after the well logging curve is standardized as provided in Example 1 of the present application. Figure 3 and Figure 4 As shown, intersection diagrams of logging curves of reservoir and tight layer before and after standardization are respectively produced to compare the differentiation effects of logging curves before and after standardization on reservoir and tight layer.

[0087] The technical solution of the embodiment of the present invention obtains the logging curves and data of the target layer section in the study area, identifies the carbonate rock dense layer in the target layer section according to the data and the logging curves, determines the dense layer, and then uses multiple sets of dense layers in a single well as standard layers to determine the frequency distribution histogram of the standard layer, and determines the curve characteristic value of the standard layer based on the frequency distribution histogram, calculates the average of the curve characteristic value, obtains the standard value of the standard layer, and uses the translation method to standardize the logging curves of all wells according to the standard value to obtain the target logging curve. By executing this technical solution, the formation with strong heterogeneity and no stable and continuously distributed standard layer can be finely standardized to obtain high-quality logging curves that meet the requirements of reservoir inversion, improve the accuracy of reservoir prediction of multi-well logging curves, and is of great significance to the reservoir evaluation of heterogeneous formations.

[0088] Embodiment 2

[0089] Figure 5This is a schematic diagram of the structure of a logging curve standardization device provided in the second embodiment of the present invention. Figure 5 As shown, the device comprises:

[0090] The logging curve and data acquisition module 510 is used to obtain the logging curve and data of the target layer section in the study area; wherein the logging curve includes the acoustic time difference logging curve, the compensated neutron logging curve and the compensated density logging curve; the data includes the coring, logging lithology, geological stratification and oil testing data;

[0091] A dense layer identification module 520 is used to identify the dense carbonate layer in the target layer section according to the data and the well logging curve, and determine the dense layer;

[0092] The curve characteristic value determination module 530 is used to take multiple sets of dense layers in a single well as standard layers, determine the frequency distribution histogram of the standard layers, and determine the curve characteristic value of the standard layers based on the frequency distribution histogram;

[0093] A standard value obtaining module 540 is used to calculate the average of the curve characteristic values ​​to obtain the standard value of the standard layer;

[0094] The logging curve standardization module 550 is used to standardize the logging curves of all wells using a translation method according to the standard value to obtain a target logging curve.

[0095] Optionally, the dense layer identification module 520 includes:

[0096] A dense layer discrimination value determination unit, used to determine the dense layer discrimination value according to the data and the well logging curve;

[0097] The dense layer determination unit is used to identify the carbonate rock dense layer of the target layer segment based on the dense layer discrimination amount to determine the dense layer.

[0098] Optionally, a dense layer discriminant determination unit is specifically used to:

[0099] When the dense layer discrimination value is less than a preset layer segment identification threshold, the target layer segment is determined as a dense layer.

[0100] Optionally, a dense layer determination unit is specifically used to:

[0101] The dense layer discrimination amount is determined in the following manner;

[0102] A=CNLp-ACp;

[0103] Wherein, A represents the dense layer discrimination value, CNLp represents the normalized curve value of the compensated neutron logging curve, and ACp represents the anti-normalized curve value of the acoustic time difference logging curve.

[0104] Optionally, the curve characteristic value determination module 530 is specifically used to:

[0105] The main peak value of the frequency distribution histogram is used as the curve characteristic value of the standard layer.

[0106] Optionally, the logging curve normalization module 550 is specifically used for:

[0107] Subtracting the standard value from the curve characteristic value to obtain a correction amount for the standard layer;

[0108] The well logging curves of all wells are standardized according to the correction amount to obtain a target well logging curve.

[0109] Optionally, the device further comprises:

[0110] The comparison module is used to construct the target logging curve of the reservoir and the dense layer and the intersection diagram of the logging curve, and compare the reservoir and the dense layer based on the intersection diagram.

[0111] A logging curve standardization device provided in an embodiment of the present invention can execute a logging curve standardization method provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0112] Embodiment 3

[0113] Figure 6 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can 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.

[0114] like Figure 6As 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.

[0115] 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.

[0116] 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 dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a well logging curve normalization method.

[0117] In some embodiments, a well logging curve normalization method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of a well logging curve normalization method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform a well logging curve normalization method in any other appropriate manner (for example, by means of firmware).

[0118] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0119] 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.

[0120] 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.

[0121] 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).

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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 normalizing a well logging curve, characterized in that: include: Obtaining logging curves and data of drilling in the target layer section of the study area; wherein the logging curves include acoustic time difference logging curves, compensated neutron logging curves and compensated density logging curves; the data include coring, logging lithology, geological stratification and oil testing data; Identify the carbonate rock dense layer in the target layer section according to the data and the logging curve, and determine the dense layer; Taking multiple sets of dense layers in a single well as standard layers, determining a frequency distribution histogram of the standard layers, and determining a curve characteristic value of the standard layers based on the frequency distribution histogram; Calculating the average of the characteristic values ​​of the curve to obtain the standard value of the standard layer; According to the standard value, the well logging curves of all wells are standardized by using the translation method to obtain the target well logging curve.

2. The method according to claim 1, characterized in that The dense carbonate layer of the target layer is identified based on the data and the logging curve, and the dense layer is determined, including: Determine the dense layer discrimination value based on the data and the logging curve; The carbonate rock dense layer of the target layer section is identified based on the dense layer discrimination amount to determine the dense layer.

3. The method according to claim 2, characterized in that The method of identifying the carbonate rock dense layer of the target layer segment based on the dense layer discrimination amount and determining the dense layer includes: When the dense layer discrimination value is less than a preset layer segment identification threshold, the target layer segment is determined as a dense layer.

4. The method according to claim 2, characterized in that: According to the data and logging curves, the dense layer identification quantity is determined, including: The dense layer discrimination amount is determined in the following manner; A=CNLp-ACp; Wherein, A represents the dense layer discrimination value, CNLp represents the normalized curve value of the compensated neutron logging curve, and ACp represents the anti-normalized curve value of the acoustic time difference logging curve.

5. The method according to claim 1, characterized in that Determining the curve characteristic value of the standard layer based on the frequency distribution histogram includes: The main peak value of the frequency distribution histogram is used as the curve characteristic value of the standard layer.

6. The method according to claim 5, characterized in that According to the standard value, the well logging curves of all wells are standardized by using the translation method to obtain the target well logging curve, including: Subtracting the standard value from the curve characteristic value to obtain a correction amount for the standard layer; The well logging curves of all wells are standardized according to the correction amount to obtain a target well logging curve.

7. The method according to claim 1, characterized in that After obtaining the target logging curve, the method further includes: Target logging curves of the reservoir and the dense layer and an intersection diagram of the logging curves are constructed, and the reservoir and the dense layer are compared based on the intersection diagram.

8. A logging curve standardization device, characterized in that: include: The logging curve and data acquisition module is used to obtain the logging curve and data of the target layer section in the study area; wherein the logging curve includes the acoustic time difference logging curve, the compensated neutron logging curve and the compensated density logging curve; the data includes the coring, logging lithology, geological stratification and oil testing data; A dense layer identification module is used to identify the dense carbonate layer in the target layer section according to the data and the logging curve, and determine the dense layer; A curve characteristic value determination module is used to take multiple sets of dense layers in a single well as standard layers, determine a frequency distribution histogram of the standard layers, and determine the curve characteristic value of the standard layers based on the frequency distribution histogram; A standard value obtaining module is used to calculate the average of the characteristic values ​​of the curve to obtain the standard value of the standard layer; The logging curve standardization module is used to standardize the logging curves of all wells using a translation method according to the standard value to obtain a target logging curve.

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 perform a logging curve normalization method 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 a logging curve standardization method according to any one of claims 1 to 7 when executed.

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