Land facies faulted lake basin high-precision sequence division method, device, medium and equipment

Abstract

The present application relates to a method, device, medium and equipment for high-precision sequence division of a continental rift lake basin, comprising: determining a target well; obtaining a GR curve of the target well and preprocessing the GR curve to obtain a shale volume curve; performing multi-stage filtering on the shale volume curve; performing cross-point analysis and picking up sand-shale boundary based on trend data of the shale volume curve; discriminating sandstone cycle types based on sand-shale layering results; dividing cycle basic units for discrimination of mudstone segments, sandstone segments and sand body cycle types; calculating an A / S ratio according to cycle basic units; the A / S ratio is a ratio of a basic unit thickness to a sandstone thickness; and identifying key interfaces and system domain positions according to the A / S ratio. The present application can realize high-precision division of sand-shale layers, and quantitatively reflect stratigraphic stacking patterns according to A / S ratio variation characteristics, thereby completing high-precision sequence and system domain division.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration, and more specifically, to a method, apparatus, medium, and equipment for high-precision sequence stratigraphy of continental rift basins. Background Technology

[0002] In recent years, with the completion of drilling on shallow oil and gas targets, deep marine strata (burial depth exceeding 3500 meters) have gradually become an important area for future reserve replacement. Currently, the main targets of deep marine oil and gas exploration are continental rift basins and their internal infilling strata. Meanwhile, as exploration progresses, deep lithological traps are gradually replacing structural traps as the primary targets for deep marine exploration. Considering the thin sand bodies, rapid boundary changes, and complex sand-mud junction patterns of lithological targets, conducting systematic and high-precision sequence stratigraphic analysis is undoubtedly the core work for understanding the distribution patterns of deep lithological oil and gas reservoirs and characterizing the effectiveness of traps. Compared to marine basins, rift lacustrine basins have a greater variety of deep facies zones, ranging from alluvial fans, rivers, and deltas to lacustrine facies. Each facies zone is affected by lake level fluctuations in some cases, but more often it is simultaneously influenced by local active factors such as climate change, fault activity, and magmatic uplift. This results in rapid changes in sedimentary facies zones, short sequence development cycles, and small distribution areas. These characteristics make it difficult to perform high-precision sequence stratigraphy in rift lacustrine basins, which greatly restricts the effective development of deep-sea lithologic oil and gas exploration.

[0003] Currently, the mainstream sequence stratigraphic process for continental rift-laminar basins suffers from the following major problems: 1) Sequence stratigraphy is highly subjective, lacking objective markers for defining boundaries and superposition patterns—traditional sequence stratigraphic interpretation of rift-laminar basins relies heavily on researchers' subjective understanding of alignment sequences, progradational and retrogradational patterns, and key boundary locations. This is significantly influenced by individual experience, educational background, and differences in data scale, leading to different sequence boundaries, floodplains, and systems tract delineation results for the same dataset, thus affecting the consistency and reproducibility of interpretation; 2) The distinction between upstream and downstream control relationships is unclear—continental rift-laminar basins are often simultaneously influenced by upstream source regions and downstream... The combined control of lake level rise and fall is primarily driven by the stacking of fluvial sedimentary units in the former and by the advance and retreat of deltaic fronts in the latter. However, in actual delineation, the sequence stratigraphy patterns controlled by these two mechanisms are not distinguished, leading to confusion in interface identification and systems tract delineation. 3) Low level of quantitative characterization of stratigraphic patterns: Stratigraphic patterns are a core tool for describing and interpreting the internal structure of the stratigraphic record. Although existing sequence stratigraphy methods have identified the main types of stratigraphic patterns and their relationship with systems tract development, they remain at the qualitative stage and have not yet formed quantitative characterization methods, resulting in low efficiency, unstable results, and low framework accuracy in sequence stratigraphy. While some existing quantitative methods (such as INPEFA technology and wavelet transform) reveal some cyclicity, they lack intuitive indications of patterns such as progradation, regression, and aggradation. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method, apparatus, medium and equipment for high-precision stratigraphic division of terrestrial rift lacustrine basins, addressing the problems existing in the prior art.

[0005] The technical solution adopted by this invention to solve its technical problem is: constructing a high-precision sequence stratigraphy method for terrestrial rift basins, comprising: Step S10: Determine the target well; Step S20: Obtain the GR curve of the target well and perform preprocessing to obtain the shale volume curve; Step S30: Perform cascade filtering on the shale volume curve to obtain trend data of the shale volume curve; Step S40: Perform cross-point analysis and sandstone / mudstone boundary picking based on the trend data of the shale volume curve; Step S50: Based on the sandstone and mudstone stratification results of step S40, determine the sandstone cycle type; Step S60: Based on the identification of mudstone section, sandstone section, and sand body cycle type in steps S40 and S50, divide the cycle into basic units. Step S70: Calculate the A / S ratio based on the basic cyclic units divided in step S60; the A / S ratio is the ratio of the thickness of the basic unit to the thickness of the sandstone. Step S80: Identify and determine the location of key interfaces and system domains based on the A / S ratio.

[0006] In the high-precision sequence stratigraphy method for continental rift basins described in this invention, step S20, which involves obtaining the GR curve of the target well and performing preprocessing to obtain the shale volume curve, includes: Obtain the GR curve of the target well; Read the GR data of the GR curve; The GR data is normalized to obtain GR index data; The shale volume curve is obtained by performing calculations and conversions based on the GR index data.

[0007] In the high-precision sequence stratigraphy method for terrestrial rift basins described in this invention, step S30, which involves performing cascade filtering on the shale volume curve to obtain trend data of the shale volume curve, includes: The shale volume curve was filtered using Wiener filtering. SG filtering is performed based on the set two-level calculation time window to extract the trend data of the shale volume curve.

[0008] In the high-precision sequence stratigraphy method for terrestrial rift basins described in this invention, step S40, which involves crosspoint analysis and sandstone / mudstone boundary picking based on the trend data of the shale volume curve, includes: Cross-point analysis is performed based on the trend data of the shale volume curve to determine the type of cross-point; Boundary picking is performed based on the intersection type to complete the division of sandstone and mudstone layers and obtain sandstone layers.

[0009] In the high-precision sequence stratigraphy method for terrestrial rift basins described in this invention, step S50, which involves determining the sandstone cycle type based on the sandstone-mudstone stratification results from step S40, includes: Set a positive cycle threshold based on the identified sandstone layers; Sandstone cycle type is determined based on the positive cycle threshold.

[0010] In the high-precision sequence stratigraphy method for terrestrial rift basins described in this invention, step S60, which involves dividing the mudstone segment, sandstone segment, and sand body cycle type into basic cycle units, includes: The positive cyclic sand body and the overlying mudstone section are combined into a positive cyclic basic unit; The anticyclic sand body and the underlying mudstone section are combined to form the basic anticyclic unit.

[0011] In the high-precision sequence stratigraphy method for terrestrial rift basins described in this invention, step S80, which involves identifying and determining key interfaces and system tracts based on the A / S ratio, includes: Determine its changing trend based on the A / S ratio; If the A / S ratio changes from a very small value to a sharp increase, then the location of the sequence interface is determined. If the A / S ratio changes by a sharp increase followed by a decrease, then the location of the maximum flood level is determined. The system domain is divided based on the location of the sequence boundary and the location of the maximum flooding surface.

[0012] The present invention also provides a high-precision sequence stratigraphy device for terrestrial rift basins, comprising: The target well selection unit is used to determine the target well; The GR data preprocessing unit is used to acquire the GR curve of the target well and perform preprocessing to obtain the shale volume curve; A cascaded filtering unit is used to perform cascaded filtering on the shale volume curve to obtain trend data of the shale volume curve; Sandstone and mudstone stratification unit, used for cross-point analysis and sandstone and mudstone boundary picking based on the trend data of the shale volume curve; Cycle type discrimination unit, used to determine sandstone cycle type based on sandstone-mudstone stratification results; Basic unit division unit, used to divide the cycle basic unit for the identification of mudstone section, sandstone section, and sand body cycle type; A statistical calculation unit is used to statistically calculate the A / S ratio based on the divided basic cyclic units; the A / S ratio is the ratio of the thickness of the basic unit to the thickness of the sandstone. The hierarchical division unit is used to identify and determine the location of key interfaces and system domains based on the A / S ratio.

[0013] The present invention also provides a storage medium storing a computer program adapted for loading by a processor to execute the steps of the high-precision stratigraphic sequence division method for terrestrial rift basins as described above.

[0014] The present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the steps of the high-precision stratigraphic sequence division method for terrestrial rift basins as described above by calling the computer program stored in the memory.

[0015] The high-precision sequence stratigraphy method, apparatus, medium, and equipment for continental rift basins of the present invention have the following beneficial effects: including: identifying the target well; acquiring and preprocessing the GR curve of the target well to obtain a shale volume curve; performing cascade filtering on the shale volume curve; performing crosspoint analysis and sandstone-mudstone boundary picking based on the trend data of the shale volume curve; determining the sandstone cycle type based on the sandstone-mudstone stratification results; dividing the cycle into basic units for mudstone sections, sandstone sections, and sandstone body cycle types; statistically calculating the A / S ratio based on the basic unit; the A / S ratio is the ratio of the basic unit thickness to the sandstone thickness; and identifying and determining the location of key interfaces and systems tracts based on the A / S ratio. This invention can achieve high-precision stratigraphy of sandstone-mudstone layers and quantitatively represent the stratigraphic stacking pattern based on the A / S ratio variation characteristics, thus completing high-precision sequence stratigraphy and systems tract division. Attached Figure Description

[0016] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a flowchart illustrating the high-precision sequence stratigraphy method for terrestrial rift basins provided in this embodiment of the invention. Figure 2 This is a schematic diagram of GR curve import and preprocessing provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the intersection point determination and identification of sandstone and mudstone layers provided in an embodiment of the present invention; Figure 4This is a schematic diagram of the cyclicity determination and stratigraphic unit division provided in an embodiment of the present invention; Figure 5 This is a schematic diagram illustrating the A / S ratio calculation and statistics provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of interface type determination and system domain division provided in an embodiment of the present invention; Figure 7 This is a logic block diagram of the high-precision stratigraphic sequence division device for terrestrial rift basins provided in an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] This invention focuses on terrestrial rift basins and conducts research on quantitative characterization methods for stratigraphic superposition patterns. It establishes an objective and quantitative discrimination process for stratigraphic superposition patterns, forming a systematic method for high-precision sequence division of terrestrial rift basins. This lays the relevant geological theoretical foundation for lithologic oil and gas exploration in deep marine areas.

[0019] Specifically, with the goal of promoting deep-sea lithologic oil and gas exploration, this invention provides a high-precision sequence stratigraphy method for continental rift basins based on quantitative characterization of stratigraphic stacking patterns.

[0020] In a preferred embodiment, such as Figure 1 As shown, the high-precision sequence stratigraphy method for terrestrial rift basins includes steps S10, S20, S30, S40, S50, S60, S70, and S80.

[0021] Step S10: Determine the target well.

[0022] Specifically, for the selection of target wells, wells with high-quality GR logging curves (i.e., natural gamma-ray logs, or simply GR curves) and complete geological information should be chosen as target wells (also known as reference wells, such as...). Figure 2 (As shown). In addition, to better reflect the combined effect of upstream and downstream control, drilling should be carried out at the intersection of the two zones whenever possible.

[0023] Step S20: Obtain the GR curve of the target well and perform preprocessing to obtain the shale volume curve.

[0024] In some embodiments, step S20, obtaining the GR curve of the target well and preprocessing it to obtain the shale volume curve, includes: obtaining the GR curve of the target well; reading the GR data of the GR curve; normalizing the GR data to obtain GR index data; and performing calculation and transformation based on the GR index data to obtain the shale volume curve.

[0025] Specifically, the steps for this operation are as follows: First, the GR data from the GR curves is read and normalized. Normalization eliminates baseline shifts caused by differences in logging instruments, environmental factors, or historical calibration, ensuring comparability of multi-well data. The goal of normalization is to adjust GR values ​​to a unified benchmark, ensuring consistency in geological interpretation. The specific calculation method is as follows: a set of logging data is selected, and its mean and standard deviation are calculated based on formula ①, thus converting the original GR data into GR index data, i.e., GRI. The expression for formula ① is as follows: ①; Within the second term of the equation: The GR value of the target well. The minimum GR value of the target well. The maximum value of the target well's GR value; In the last term of the equation: The GR value represents any well logging curve. The GR value represents the purity of sandstone. The GR value represents the purity of the mudstone.

[0026] Secondly, calculate the shale volume curve (V-shale curve). Specifically, based on formula ①, convert the normalized GRI curve into a shale volume curve. By calculating the shale volume curve, it can be used as basic data reflecting lithological changes (specifically, as shown in...). Figure 2 (As shown).

[0027] Step S30: Perform cascade filtering on the shale volume curve to obtain trend data of the shale volume curve.

[0028] In some embodiments, step S30, which involves performing cascade filtering on the shale volume curve to obtain trend data, includes: applying Wiener filtering to the shale volume curve; and performing SG filtering based on a set two-stage calculation window to extract trend data from the shale volume curve. Specifically, in this step, cascade filtering (i.e., Wiener filtering + two-stage SG filtering) is performed based on the V-shale curve to identify sandstone and mudstone boundaries through the intersection relationships of curves at different scales. The specific cascade filtering process is as follows: First, Wiener filtering is used to remove spikes in the V-shale curve, eliminating noise while highlighting the curve's key details (such as...). Figure 2 (As shown); secondly, two-level calculation windows are set (the specific settings of the two-level calculation windows are adjusted according to actual applications, and this invention does not impose specific limitations), and SG filtering (Savitzky-Golay filtering) is performed in two stages to extract the overall trend of the V-shale curve (i.e., the trend data of the shale volume curve). By extracting the trend data of the shale volume curve, the cyclical change characteristics of the curve on a larger scale can be effectively reflected (e.g., Figure 2 ).

[0029] Step S40: Perform cross-point analysis and sandstone / mudstone boundary picking based on the trend data of the shale volume curve.

[0030] In some embodiments, step S40, which involves crosspoint analysis and sandstone-mudstone boundary picking based on the trend data of the shale volume curve, includes: performing crosspoint analysis based on the trend data of the shale volume curve to determine the crosspoint type; and picking the boundary based on the crosspoint type to complete the division of the sandstone-mudstone layers and obtain the sandstone layer.

[0031] The main purpose of this step is to analyze the intersection points of different filter curves and to pick up the boundaries between sandstone and mudstone. Specifically, after different filter curves intersect, multiple levels of intersection points appear. By comparing the values ​​of different filter curves within specific micro-element time windows above and below the intersection points, two main types of intersection points (Type A and Type B) are identified. The distinguishing characteristic of Type A intersection points is that the Savitzky-Golay filter curve value is greater than the Wiener filter curve value within the upper micro-element time window, while the Wiener filter curve value is greater than the Savitzky-Golay filter curve value within the lower micro-element time window. Similarly, the distinguishing characteristic of Type B intersection points is that the Wiener filter curve value is greater than the Savitzky-Golay filter curve value within the upper micro-element time window, while the Savitzky-Golay filter curve value is greater than the Wiener filter curve value within the lower micro-element time window. This invention analyzes from deep to shallow to determine the stratigraphic unit sandstone from A to B and the stratigraphic unit mudstone from B to A, thereby completing the fine division of sandstone and mudstone layers (e.g., Figure 3 (As shown).

[0032] Step S50: Based on the sandstone-mudstone stratification results of step S40, determine the sandstone cycle type.

[0033] In some embodiments, step S50, determining the sandstone cycle type based on the sandstone-mudstone stratification results of step S40, includes: setting a positive cycle threshold based on the identified sandstone layers; and determining the sandstone cycle type based on the positive cycle threshold.

[0034] Continental rift basins primarily develop two types of sand bodies with varying cycles: fluvial sandstones typically exhibit positive cycles, while deltaic front sandstones exhibit negative cycles. The specific steps for determining sandstone cycle types are as follows: First, a positive cycle threshold is set. Specifically, based on the sandstone layer identified in step S40, a positive cycle threshold is set. This positive cycle threshold is generally greater than 10 meters.

[0035] Secondly, determine the cyclic type. Specifically, in cases where the thickness is less than 10 meters, determine the distribution of minimum values ​​within the sandstone section. Using the depth at the center of the sandstone as the boundary, if the minimum value is distributed in the upper half of the sandstone section, it is determined to be a reverse cyclic sandstone body; if the minimum value is distributed in the lower half of the sandstone section, it is determined to be a positive cyclic sandstone body.

[0036] Next, further elimination of pseudo-reverse-cycle sand bodies is carried out. Specifically, for the previously identified reverse-cycle sand bodies, further elimination of pseudo-reverse-cycle sand bodies is conducted. The specific steps are as follows: First, compare the absolute values ​​of the slopes at the top and bottom interfaces. If the absolute value of the slope at the top is greater than that at the bottom, it is reclassified as a positive-cycle sand body; if the absolute value of the slope at the bottom is larger, it is maintained as a reverse-cycle sand body. Second, analyze the standard deviation of the V-shale values ​​within the sandstone section. If the standard deviation is less than a certain threshold, it is reclassified as a positive-cycle sand body; if the standard deviation is larger, it is maintained as a reverse-cycle sand body (e.g., ...). Figure 4 (As shown).

[0037] Step S60: Based on the identification of the cycle type of mudstone section, sandstone section, and sand body in steps S40 and S50, the basic cycle unit is divided.

[0038] In some embodiments, step S60, the division of basic cycle units for the determination of the cycle type of mudstone segment, sandstone segment, and sand body includes: combining the positive cycle sand body with the overlying mudstone segment into a positive cycle basic unit; and combining the negative cycle sand body with the underlying mudstone segment into a negative cycle basic unit.

[0039] Specifically, in this step, based on the identification results of steps S40 and S50, the positive-cycle sand body is combined with the overlying mudstone section to form a positive-cycle basic unit, and the negative-cycle sand body is combined with the underlying mudstone section to form a negative-cycle basic unit (e.g., ...). Figure 4 (As shown).

[0040] Step S70: Calculate the A / S ratio based on the basic cyclic units divided in step S60; the A / S ratio is the ratio of the thickness of the basic unit to the thickness of the sandstone.

[0041] Specifically, in this step, based on the two types of basic cyclic units previously defined, the A / S ratio is calculated. Here, A represents the thickness of the basic cyclic unit, and B represents the sandstone thickness. By statistically calculating the A / S ratio for each of the two basic cyclic units, a refined quantitative characterization of the stratigraphic stacking pattern can be achieved (e.g., Figure 5 (As shown).

[0042] Step S80: Identify and determine the location of key interfaces and system domains based on the A / S ratio.

[0043] In some embodiments, step S80, identifying and determining key interfaces and system domain divisions based on the A / S ratio, includes: determining the trend of the A / S ratio; if the trend of the A / S ratio is from very small to rapidly increasing, then the location of the sequence interface is determined; if the trend of the A / S ratio is rapidly increasing and then decreasing, then the location of the maximum flooding surface is determined; and the system domain division is completed based on the location of the sequence interface and the location of the maximum flooding surface.

[0044] Specifically, this step mainly aims to identify key interfaces (i.e., sequence boundaries and maximum flooding) and delineate system tracts. That is, it identifies the interfaces and system tract locations based on the changing characteristics of the A / S ratio. The specific method is as follows: when the A / S ratio increases sharply from a very small value, it corresponds to the location of the sequence boundary (SB); when the A / S ratio increases sharply and then decreases, it corresponds to the location of the maximum flooding (MFS). Based on the determination of the SB and MFS locations, the delineation of the low-sill-lacustrine transgressive system tract and the high-sill system tract is completed (e.g., ...). Figure 6 (As shown).

[0045] refer to Figure 7 The present invention also provides a high-precision stratigraphic sequence division device for terrestrial rift basins.

[0046] like Figure 7 As shown, this high-precision sequence stratigraphy device for terrestrial rift basins includes: The target well selection unit 701 is used to determine the target well.

[0047] The GR data preprocessing unit 702 is used to acquire the GR curve of the target well and perform preprocessing to obtain the shale volume curve.

[0048] The cascaded filtering unit 703 is used to perform cascaded filtering on the shale volume curve to obtain trend data of the shale volume curve.

[0049] Sandstone and mudstone stratification unit 704 is used for cross-point analysis and sandstone and mudstone boundary picking based on trend data from shale volume curves.

[0050] Cycle type discrimination unit 705 is used to discriminate the cycle type of sandstone based on the sandstone-mudstone stratification results.

[0051] Basic unit division unit 706 is used to divide the cycle basic unit for the identification of mudstone section, sandstone section, and sand body cycle type.

[0052] The statistical calculation unit 707 is used to statistically calculate the A / S ratio based on the divided basic cycle units; the A / S ratio is the ratio of the thickness of the basic unit to the thickness of the sandstone.

[0053] The sequence division unit 708 is used to identify and determine the location of key interfaces and system domains based on the A / S ratio.

[0054] Specifically, the specific operational process of the various units in the high-precision sequence stratigraphy device for terrestrial rift basins can be referred to the above-mentioned high-precision sequence stratigraphy method for terrestrial rift basins, and will not be repeated here.

[0055] The invention will now be illustrated with a specific example.

[0056] Select GR data from a well in a terrestrial rift basin within a certain sea area (e.g.) Figure 2 Given the advantages of high quality and complete geological information, this well logging data can be used to complete high-precision sequence stratigraphy of continental rift basins based on quantitative characterization of stratigraphic stacking patterns.

[0057] First, the GR curve is read and normalized, and then the normalized GR curve is converted into a shale volume (V-shale) curve (e.g., Figure 2 ), serving as fundamental data reflecting lithological changes; Secondly, Wiener filtering was used to denoise the V-shale curve and extract curve details. Then, Savitzky-Golay filtering with different window sizes was applied twice to extract the trend of the V-shale curve (e.g., ...). Figure 2 ); Next, by utilizing the intersection relationships under defined conditions, the stratification results of sandstone and mudstone can be obtained (e.g. Figure 3 ); Then, by using methods such as V-shale gradient variation, extreme point offset, and standard deviation calculation, positive and negative cyclic sandstones are distinguished (e.g., Figure 4 That is, by using methods such as the difference in the absolute value of the slope of the V-shale curve of the top and bottom parts of the sandstone layer, the offset of the extreme point and the standard deviation calculation, positive and negative cyclic sand bodies are comprehensively divided. Furthermore, by defining the mudstone layer distribution conditions under different combinations of two types of sandstone, the basic cyclic unit division of the stratigraphy was completed (e.g. Figure 4 That is, by combining the different combinations with the overlying mudstone and the underlying mudstone, the basic units of the two cycles, positive and negative, are divided, which serve as the basis for judging the stratigraphic stacking style. Then, the A / S ratio of each basic unit of the cycle is calculated statistically (e.g., Figure 5 ); Finally, based on the stratigraphic stacking patterns reflected by the A / S ratio variation characteristics, the locations of sequence boundaries and the maximum flooding surface are determined, thereby completing the division of the systems tract (e.g., Figure 6 ).

[0058] Furthermore, an electronic device of the present invention includes a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program to implement the high-precision sequence stratigraphy method for terrestrial rift basins as described above. Specifically, according to embodiments of the present invention, the processes described above with reference to the flowchart can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, when the computer program is downloaded, installed, and executed by an electronic device, it performs the functions defined in the methods of the embodiments of the present invention. The electronic device in the present invention can be a terminal such as a laptop, desktop computer, tablet computer, or smartphone, or it can be a server.

[0059] Furthermore, one type of storage medium of the present invention stores a computer program, which, when executed by a processor, implements the high-precision stratigraphic sequence division method for terrestrial rift basins described above. Specifically, it should be noted that the storage medium described above in the present invention can be a computer-readable signal medium, a computer-readable storage medium, or any combination thereof. 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 of a computer-readable storage medium may include, but are not limited to: 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 the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. The transmitted data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0060] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0061] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0062] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0063] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0064] The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it accordingly. They do not limit the scope of protection of the present invention. All equivalent changes and modifications made within the scope of the claims of the present invention should fall within the scope of the claims of the present invention.

Claims

1. A high-precision sequence stratigraphy method for terrestrial rift basins, characterized in that, include: Step S10: Determine the target well; Step S20: Obtain the GR curve of the target well and perform preprocessing to obtain the shale volume curve; Step S30: Perform cascade filtering on the shale volume curve to obtain trend data of the shale volume curve; Step S40: Perform cross-point analysis and sandstone / mudstone boundary picking based on the trend data of the shale volume curve; Step S50: Based on the sandstone and mudstone stratification results of step S40, determine the sandstone cycle type; Step S60: Based on the identification of mudstone section, sandstone section, and sand body cycle type in steps S40 and S50, divide the cycle into basic units. Step S70: Calculate the A / S ratio based on the basic cyclic units divided in step S60; the A / S ratio is the ratio of the thickness of the basic unit to the thickness of the sandstone. Step S80: Identify and determine the location of key interfaces and system domains based on the A / S ratio.

2. The high-precision sequence stratigraphy method for terrestrial rift basins according to claim 1, characterized in that, In step S20, the GR curve of the target well is obtained and preprocessed to obtain the shale volume curve, including: Obtain the GR curve of the target well; Read the GR data of the GR curve; The GR data is normalized to obtain GR index data; The shale volume curve is obtained by performing calculations and conversions based on the GR index data.

3. The high-precision sequence stratigraphy method for terrestrial rift basins according to claim 1, characterized in that, In step S30, the cascade filtering process performed on the shale volume curve to obtain the trend data of the shale volume curve includes: The shale volume curve was filtered using Wiener filtering. SG filtering is performed based on the set two-level calculation time window to extract the trend data of the shale volume curve.

4. The high-precision sequence stratigraphy method for terrestrial rift basins according to claim 1, characterized in that, In step S40, the cross-point analysis and sandstone / mudstone boundary picking based on the trend data of the shale volume curve include: Cross-point analysis is performed based on the trend data of the shale volume curve to determine the type of cross-point; Boundary picking is performed based on the intersection type to complete the division of sandstone and mudstone layers and obtain sandstone layers.

5. The high-precision sequence stratigraphy method for terrestrial rift basins according to claim 1, characterized in that, In step S50, the sandstone cycle type determination based on the sandstone-mudstone stratification results of step S40 includes: Set a positive cycle threshold based on the identified sandstone layers; Sandstone cycle type is determined based on the positive cycle threshold.

6. The high-precision sequence stratigraphy method for terrestrial rift basins according to claim 1, characterized in that, In step S60, the basic unit division of cycles for determining the cycle types of mudstone sections, sandstone sections, and sand bodies includes: The positive cyclic sand body and the overlying mudstone section are combined into a positive cyclic basic unit; The anticyclic sand body and the underlying mudstone section are combined to form the basic anticyclic unit.

7. The high-precision sequence stratigraphy method for terrestrial rift basins according to claim 1, characterized in that, In step S80, identifying and determining the key interface and system domain division based on the A / S ratio includes: Determine its changing trend based on the A / S ratio; If the A / S ratio changes from a very small value to a sharp increase, then the location of the sequence interface is determined. If the A / S ratio changes by a sharp increase followed by a decrease, then the location of the maximum flood level is determined. The system domain is divided based on the location of the sequence boundary and the location of the maximum flooding surface.

8. A high-precision sequence stratigraphy device for terrestrial rift basins, characterized in that, include: The target well selection unit is used to determine the target well; The GR data preprocessing unit is used to acquire the GR curve of the target well and perform preprocessing to obtain the shale volume curve; A cascaded filtering unit is used to perform cascaded filtering on the shale volume curve to obtain trend data of the shale volume curve; Sandstone and mudstone stratification unit, used for cross-point analysis and sandstone and mudstone boundary picking based on the trend data of the shale volume curve; Cycle type discrimination unit, used to determine sandstone cycle type based on sandstone-mudstone stratification results; Basic unit division unit, used to divide the cycle basic unit for the identification of mudstone section, sandstone section, and sand body cycle type; A statistical calculation unit is used to statistically calculate the A / S ratio based on the divided basic cyclic units; the A / S ratio is the ratio of the thickness of the basic unit to the thickness of the sandstone. The hierarchical division unit is used to identify and determine the location of key interfaces and system domains based on the A / S ratio.

9. A storage medium, characterized in that, The storage medium stores a computer program adapted for loading by a processor to perform the steps of the high-precision sequence stratigraphy method for terrestrial rift basins as described in any one of claims 1 to 7.

10. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the steps of the high-precision sequence stratigraphy method for terrestrial rift basins as described in any one of claims 1 to 7 by calling the computer program stored in the memory.

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