Fluvial facies reservoir three-dimensional space feature prediction method based on single well data

Abstract

The invention relates to a fluvial facies reservoir three-dimensional space feature prediction method based on single well data. The method comprises the steps that S1, charts of different types of fluvial facies reservoirs are constructed based on the sedimentology principle; s2, according to parameter changes of different types of fluvial facies reservoirs, determining a three-dimensional space characteristic change mode of a plate corresponding to each type of fluvial facies reservoir; s3, according to the charts and the three-dimensional space characteristic change modes of the fluvial facies reservoirs of different types, constructing an analogy index system; s4, new drilling well information is obtained, drilling well related indexes in the new drilling well information are extracted, and an evaluation index sample of a new drilling well is constructed; s5, compiling a fluvial facies reservoir feature sample table and a reservoir feature three-dimensional space change diagram according to the evaluation index sample of the new drilled well and the analogy index system of the different types of fluvial facies reservoirs in combination with the charts and the three-dimensional space feature change modes of the different types of fluvial facies reservoirs, and predicting the three-dimensional space feature change of the reservoir at the new drilled position.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oil and gas exploration, and particularly relates to a fluvial facies reservoir three-dimensional space feature prediction method based on single well data. BACKGROUND

[0002] Fluvial facies reservoirs have become one of the core fields of increasing reserves and production of oil and gas development.

[0003] Accurate characterization of the three-dimensional structure of fluvial facies reservoirs is crucial for oil and gas exploration and development, and the three-dimensional spatial distribution characteristics directly affect the reservoir capacity, seepage characteristics and ultimate recovery of oil and gas reservoirs. The formation of reservoirs is controlled by many geological factors such as sedimentary environment, tectonic movement, diagenesis and later reconstruction, resulting in obvious structural differences of reservoirs in the horizontal and vertical directions. Therefore, how to quantitatively analyze the three-dimensional structural differences of reservoirs based on existing logging data has become one of the key scientific problems in reservoir and oil and gas development.

[0004] Although logging data plays an important role in reservoir evaluation, existing methods still have the following shortcomings:

[0005] Single well analysis has limitations, and existing reservoir analysis is mostly based on single well logging interpretation, lacking overall evaluation of regional reservoir structure changes;

[0006] Lack of description of horizontal reservoir distribution: traditional methods mainly rely on single well or profile data for reservoir correlation, lacking systematic plane structure analysis methods, and it is difficult to accurately reveal the horizontal variation law of reservoirs;

[0007] Vertical evolution process is not fully considered: reservoirs may experience physical property changes, dissolution or fracture development during diagenetic evolution, while existing methods mostly remain in static description, lacking dynamic analysis of vertical evolution of reservoirs.

[0008] In addition, although reservoir three-dimensional modeling technology has developed in recent years, most models rely on seismic data or qualitative interpretation, lacking fine quantitative evaluation methods based on logging data, and it is difficult to effectively characterize the three-dimensional structural differences of reservoirs. SUMMARY

[0009] The present application provides a fluvial facies reservoir three-dimensional space feature prediction method based on single well data, which can quantitatively analyze the three-dimensional structural differences of reservoirs based on existing logging data, improve the accuracy and reliability of fluvial facies reservoir oil and gas prediction, and provide effective decision support for oil and gas development.

[0010] To achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0011] The first aspect provides a method for predicting three-dimensional spatial characteristics of fluvial facies reservoirs based on single-well data, comprising:

[0012] S1, constructing a chart for different types of fluvial facies reservoirs based on principles of sedimentology;

[0013] S2, determining a three-dimensional spatial characteristic variation mode of the chart corresponding to each type of fluvial facies reservoir according to parameter variations of different types of fluvial facies reservoirs;

[0014] S3, constructing an analogy index system according to the chart and the three-dimensional spatial characteristic variation mode of different types of fluvial facies reservoirs;

[0015] S4, obtaining new well information, extracting drilling-related indexes in the new well information, and constructing an evaluation index sample of the new well;

[0016] S5, preparing a fluvial facies reservoir characteristic sample table and a reservoir characteristic three-dimensional spatial variation map according to the evaluation index sample of the new well and the analogy index system of different types of fluvial facies reservoirs, combining the chart and the three-dimensional spatial characteristic variation mode of different types of fluvial facies reservoirs, and predicting three-dimensional spatial characteristic variations of the reservoir drilled.

[0017] In an implementation manner, in the S1, the method comprises:

[0018] determining a main control factor of the fluvial facies based on principles of sedimentology;

[0019] dividing the fluvial facies reservoir into different types according to the main control factor, and establishing a corresponding three-dimensional fluvial facies reservoir chart.

[0020] In an implementation manner, in the S3, the analogy index system comprises a decisive basis, a constraint basis, and a supplementary basis; wherein the decisive basis is used to determine the chart type, the constraint basis is used to determine the geographical location of the chart, and the supplementary basis is used to analyze the main parameter variations of the reservoir without changing the location of the chart.

[0021] In an implementation manner, the method comprises:

[0022] constructing a fluvial facies reservoir analogy parameter system according to three-dimensional chart parameters of different fluvial types, wherein the three-dimensional chart parameters comprise genetic domain parameters, entity domain parameters, and response domain parameters;

[0023] wherein the genetic domain parameters are used to describe condition parameters of sedimentary genesis; the entity domain parameters are used to quantify physical entity characteristics of the reservoir; and the attribute response domain parameters are used to describe measurement indexes.

[0024] In an implementation manner, the method further comprises:

[0025] Extracting lithology data in the three-dimensional template parameter information, and performing similarity statistics on the lithology data;

[0026] Determining maximum, minimum and median values according to the similarity statistics result, and dividing a segmented range according to the maximum, minimum and median values;

[0027] Constructing a river facies reservoir analogy parameter system based on the segmented ranges of different parameters.

[0028] In an implementation manner, in S4, the drilling-related indexes include logging facies, logging facies combination, core color, sand ratio, interlayer, rock composition and content, and partial analysis test data.

[0029] In an implementation manner, the method comprises:

[0030] Determining a candidate template type of the reservoir according to the decisive index of the new well;

[0031] Determining a plane position of the template according to the constraint index and the candidate template type of the new well.

[0032] In an implementation manner, the method further comprises:

[0033] When the plane position of the template cannot be determined according to the constraint index and the candidate template type, modifying a corresponding position value of the template according to the supplementary index of the new well.

[0034] In a second aspect, a computer readable storage medium is provided, which stores a computer program, and the computer program is executed by a processor to implement the method in the first aspect.

[0035] In a third aspect, an electronic device is provided, which comprises a processor and a memory, and the memory stores a computer program, and the computer program is executed by the processor to implement the method in the first aspect.

[0036] The present application has the following advantages:

[0037] (1) Different types of three-dimensional river facies reservoir templates are constructed by the principle of sedimentology, ensuring the scientificity and accuracy of reservoir feature prediction; according to the three-dimensional space feature change mode of different types of river facies reservoirs, the spatial distribution and characteristics of the reservoirs can be fully captured; the analogy index system including decisive basis, constraint basis and supplementary basis is helpful to accurately identify the reservoir type under different conditions, avoid the interference of single factor, efficiently integrate multi-party information, and improve the stability and reliability of the prediction.

[0038] (2) By extracting drilling-related indexes in new well information and constructing evaluation index samples, the prediction model can be corrected and optimized according to actual drilling data, so that the model is more in line with the actual situation, and the prediction accuracy is improved.

[0039] The application integrates various data and models, can improve the prediction accuracy of the three-dimensional feature change of the fluvial facies reservoir, provides more reliable theoretical support for oil and gas development, and has strong practical application value. BRIEF DESCRIPTION OF DRAWINGS

[0040] Figure 1 is a method flowchart of an embodiment of the application;

[0041] Figure 2 is a chart and three-dimensional feature change diagram in the embodiment of the application;

[0042] Figure 3 is a schematic diagram of an analog parameter system;

[0043] Figure 4 is a schematic diagram of a decisive parameter of a drilling well;

[0044] Figure 5 is a schematic diagram of a supplementary parameter of a drilling well;

[0045] Figure 6 is a schematic diagram of an electronic device provided by the embodiment of the application. DETAILED DESCRIPTION

[0046] To make the purpose, technical scheme and advantages of the embodiments of the application clearer, the technical scheme of the embodiments of the application will be described clearly and completely below with reference to the drawings of the embodiments of the application. Obviously, the described embodiments are part of the embodiments of the application, rather than all the embodiments of the application. Based on the described embodiments of the application, all other embodiments obtained by those skilled in the art belong to the scope of protection of the application.

[0047] In view of the defects and problems of the prior art, the application provides a fluvial facies reservoir three-dimensional space feature prediction method based on single-well data, comprising:

[0048] S1, constructing a chart of different types of fluvial facies reservoirs based on the principle of sedimentology;

[0049] S2, determining the three-dimensional space feature change mode of the chart corresponding to each type of fluvial facies reservoir according to the parameter change of different types of fluvial facies reservoirs;

[0050] S3, constructing an analog index system according to the chart and the three-dimensional space feature change mode of different types of fluvial facies reservoirs;

[0051] S4, obtaining new drilling well information, extracting drilling-related indexes in the new drilling well information, and constructing an evaluation index sample of the new drilling well;

[0052] S5. Based on the evaluation index sample of the new well and the analogy index system of different types of fluvial reservoirs, combined with the map and three-dimensional spatial characteristic change pattern of different types of fluvial reservoirs, compile the fluvial reservoir characteristic sample table and the three-dimensional spatial change map of reservoir characteristics, and predict the three-dimensional spatial characteristic change of the reservoir at the new well.

[0053] The above method is described below in a more detailed embodiment with reference to more accompanying drawings.

[0054] See Figure 1 , Figure 1 This embodiment illustrates a flowchart of a method for predicting the three-dimensional characteristics of fluvial reservoirs based on single-well data. The method includes:

[0055] Step S101: Construct three-dimensional fluvial reservoir maps of different types based on sedimentological principles;

[0056] Step S102: Based on the parameter variations of each type of fluvial reservoir, determine the three-dimensional spatial characteristic variation patterns of the corresponding maps for different fluvial reservoir types;

[0057] Step S103: Construct an analogy index system based on the map and spatial characteristic variation patterns of different types of fluvial reservoirs. The analogy index system includes decisive basis, binding basis, and supplementary basis. The decisive basis is used to determine the map type, the binding basis is used to determine the geographical location of the map, and the supplementary basis is used to analyze the changes in the main parameters of the reservoir without changing the map location.

[0058] Step S104: Obtain new drilling information, extract drilling-related indicators from the new drilling information, and construct a sample of new drilling evaluation indicators;

[0059] Step S105: Based on the analogy index system, determine the type and index value of the newly encountered fluvial reservoir, and combine the three-dimensional spatial feature change pattern of the map to compile a reservoir feature sample table and a three-dimensional spatial change map of the reservoir features, and predict the three-dimensional feature changes of the drilled reservoir.

[0060] This embodiment provides a method for predicting the three-dimensional characteristics of fluvial reservoirs based on single-well data. It constructs three-dimensional fluvial reservoir maps of different types based on sedimentological principles, and combines an analogical index system and new well information to comprehensively predict changes in the three-dimensional spatial characteristics of the reservoirs. This invention improves the accuracy and reliability of predictions through scientific sedimentological modeling and spatial characteristic analysis, providing effective decision support for oil and gas development.

[0061] In a preferred embodiment, step S101, which involves constructing different types of three-dimensional fluvial reservoir maps based on sedimentological principles, includes:

[0062] Determining the main controlling factors of fluvial facies based on sedimentological principles;

[0063] Based on the main controlling factors, fluvial reservoirs are classified into different types, and corresponding three-dimensional fluvial reservoir maps are established.

[0064] In some embodiments, slope and load type are selected as the two main controlling factors of fluvial facies. Slope is classified into four categories: extremely steep, steep, relatively gentle, and gentle; load type is classified into six categories: gravelly stable, gravelly unstable, sandy stable, sandy unstable, sandy-muddy stable, and suspended sediment stable. Therefore, based on these two main controlling factors, fluvial reservoirs are classified into a total of 14 types.

[0065] Because a large body of literature on fluvial reservoirs lacks a systematic overview of the overall genetic types of fluvial facies, often focusing only on single river types, we have established analogous maps of fluvial reservoirs controlled by two main factors, based on their sedimentary characteristics. Specifically, based on the source type, rivers are classified as gravelly, sandy, and muddy; based on the river loading pattern, they are divided into stable and unstable types. The source type and loading pattern are collectively referred to as the loading type parameter, used to control the river's sedimentary type and channel morphology. The other factor controlling river deposition is slope, which significantly influences river hydrodynamics and tortuosity, thus determining the river type. In summary, we have classified slope into four categories and loading type into six types, establishing an analogous map of the three-dimensional morphology of fluvial reservoirs covering different types such as braided rivers, meandering rivers, and reticulated rivers. Figure 2 As shown, Figure 2 A schematic diagram of a three-dimensional fluvial reservoir is shown.

[0066] Furthermore, in step S102, based on the parameter variations of different types of river facies reservoirs, the three-dimensional spatial characteristic variation patterns of the corresponding maps for different river facies reservoir types are determined. Specifically, based on previous research results, as the parameters of slope and load type change, the river morphology and internal sand body morphology also change. That is, as the slope decreases, the channel curvature increases, point bars develop significantly, and as the downcutting effect weakens, the riverbed boundary gradually disappears. The overall variation pattern of the map is braided river, meandering river, and network river. The effects of a gentle slope and stable sand load will allow for sufficient lateral migration of river facies. When the slope is extremely gentle, the river loses its downcutting force and turns to vertical accretion, in which case the riverbank vegetation fixes the channel, forming a network pattern.

[0067] In a preferred embodiment, in step S103, an analogy index system is constructed based on analog maps and spatial characteristic variation patterns of different types of fluvial reservoirs, including:

[0068] Based on the three-dimensional map parameters of different river types, a river facies reservoir analogy parameter system is constructed. The three-dimensional map parameters include genetic domain parameters, entity domain parameters, and response domain parameters.

[0069] Among them, the genetic domain parameters are used to describe the conditional parameters of sedimentary genesis; the entity domain parameters are used to quantify the physical entity characteristics of the reservoir; and the attribute response domain parameters are used to describe the measurement indicators.

[0070] As a specific example, the genetic domain parameters include sedimentary genetic condition parameters, the core function of which is to explain "why such fluvial reservoirs are formed", including provenance characteristics, topographic features, and hydrodynamic conditions. Specific parameters of provenance characteristics include provenance lithology and parent rock type, which can determine the composition (gravelly / sandy / muddy) and stability of the loaded material. Topographic features such as slope can control water flow energy and channel tortuosity. A decrease in slope and an increase in curvature can determine the evolution of channel morphology. Hydrodynamic conditions such as water depth, flow velocity, and flow rate can affect sediment sorting and sand body structure, and are used to explain the heterogeneity of the reservoir.

[0071] Physical domain parameters include sand body size data, interlayer data, and grain size data. Their core function is to quantify the physical characteristics of the reservoir and explain "what the reservoir actually looks like." For example, sand body size data includes the thickness, width, and continuous length of a single sand body, which can reflect reservoir connectivity; interlayer data includes thickness, frequency, and clay content, which can control vertical fluid flow; and grain size can indicate sedimentary energy.

[0072] Response domain parameters include logging facies parameters, seismic attribute parameters, reservoir quality and heterogeneity parameters, etc. Their core function is to provide measurable indicators, enabling the inversion of reservoir characteristics using engineering data. For example, lithology and fluids can be identified through logging facies parameters (natural gamma morphology, resistivity amplitude, sonic transit time, etc.).

[0073] Based on the parameter division of the three-dimensional maps of different river types in the above three domains, a three-level river facies map identification basis is constructed. Compared with traditional raw data or chart analogy, by establishing an analogy index system and constructing a comprehensive analogy map based on three-dimensional sedimentary models, it has a more intuitive and clearer analogy form. The comprehensive analogy map mainly uses the three-dimensional map and map parameters as the core. Based on drilling data, analogy parameter indicators are obtained, and the indicators are located in the analogy map according to their characteristics. The map parameter information is used to guide the exploration and development of similar reservoirs.

[0074] As a preferred embodiment, a fluvial reservoir analogy parameter system is constructed based on the parameters of three-dimensional maps of different river types, including:

[0075] Lithological data is extracted from the parameter information of the 3D map using preset software, and similarity statistics are performed on the lithological data.

[0076] The maximum, minimum, and median values ​​are determined based on the similarity statistics, and the segment ranges are divided based on the maximum, minimum, and median values.

[0077] A fluvial reservoir analog parameter system is constructed based on segmented ranges of different parameters.

[0078] As a specific implementation, based on the drilling data of the target reservoir, we extracted lithological data using RESFORM software, performed similarity statistics in an EXCEL spreadsheet, and extracted data such as gravel thickness, sand thickness, clay thickness, and sand-to-soil ratio. Based on the data, we located it on the map (according to sedimentological principles, a content greater than 50% indicates this type of reservoir; for example, a gravel content greater than 50% indicates a gravelly river; if the clay content is greater than 50%, it indicates a long transport distance, generally a late stage of river development, a meandering river or a network river, which can be further distinguished by seismic attributes and morphology) to find similar reservoir types.

[0079] It should be noted that the quantitative indicators in the analogy chart, such as reservoir size, interlayers, and reservoir physical properties, are derived through literature collection and statistics. The specific quantification process is as follows: the maximum, minimum, and median values ​​are identified from the statistical data to establish numerical ranges. For example, the values ​​are divided into three segments: the range above and below the median is considered medium-sized; values ​​greater than this range are considered large-scale, and values ​​less than this range are considered small-scale.

[0080] As a specific example, in the early stages of exploration with few wells, incomplete data, or poor seismic data quality, drilling data is limited. Therefore, we need to extract rock composition data for that stratum from the limited data. This rock composition data includes gravel content (gravel-to-soil ratio), orientation, and thickness; sand content (sand-to-soil ratio), thickness, and mud content, thickness, color, and purity data (these data can be extracted from the wells). Based on this data, we established a river facies type classification parameter table for the map information and located the corresponding positions based on the data obtained from the drilling. For example... Figure 3 As shown, Figure 3 A diagram illustrating analogous parameter data is shown.

[0081] In a preferred embodiment, step S104, determining the type and index value of the newly encountered fluvial reservoir based on the analogy index system, includes:

[0082] Based on the decisive indicators of new drilling, determine the candidate map types for the reservoir;

[0083] The planar position of the chart is determined based on the binding parameters of the new well and the candidate chart type.

[0084] As a preferred embodiment, determining the type and index values ​​of newly encountered fluvial reservoirs based on the analogy index system further includes:

[0085] When the planar position of a chart cannot be determined based on the binding indicators and candidate chart types, the corresponding position value of the chart is modified according to the supplementary indicators of the new drilling.

[0086] It should be noted that the decisive indicator determines the reservoir type (location chart) of our chart. When the positioning accuracy of the decisive indicator is insufficient, or when three or four candidate charts are obtained, we need to supplement the indicator to make the positioning more accurate.

[0087] Supplementary indices are fine-tunings of the determinant indices. While the determinant indices define the relative location of the target fluvial facies, supplementary indices are more granular parameters. For example, when determining load type parameters, the determinant indices are the content of gravelly, sandy, and muddy materials. If these cannot be differentiated based on content alone, we can incorporate differences in sedimentary structural indices from the core, grain size probability curves, and CM diagrams to distinguish the location on the fluvial facies map. Specifically, reservoir porosity and permeability are based on the current research scope. Please refer to [link to relevant documentation]. Figure 4 and Figure 5 , Figure 4 The key characteristic parameters of drilling were presented. Figure 5 The drilling supplementary characteristic parameters were presented.

[0088] If the map can be located solely based on the decisive parameters, no further supplementation is needed. If it cannot be located, some supplementary indicators need to be added. These indicators can be quantitative or qualitative, such as the external morphology of earthquake attributes.

[0089] As a specific embodiment, in step S105, a reservoir characteristic sample table and a three-dimensional spatial variation map of reservoir characteristics are compiled to predict the three-dimensional characteristic changes of the drilled reservoir, including: displaying the lateral distribution and vertical evolution of the reservoir through the three-dimensional spatial variation map, providing technical guidance for oil and gas exploration and development (such as predicting the distribution of remaining oil and gas).

[0090] The present invention also provides an electronic device 700, which can be a mobile terminal, desktop computer, laptop, handheld computer, server, or other computing device. The electronic device includes a processor 701, a memory 702, and a display 703.

[0091] In some embodiments, memory 702 may be an internal storage unit of a computer device, such as a hard disk or memory. In other embodiments, memory 702 may be an external storage device of a computer device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc. Further, memory 702 may include both internal and external storage units of the computer device. Memory 702 is used to store application software and various types of data installed on the computer device, such as program code for installing the computer device. Memory 702 may also be used to temporarily store data that has been output or will be output. In one embodiment, memory 702 stores a program 704 for predicting the three-dimensional characteristics of fluvial facies reservoirs based on single-well data. This program 704 can be executed by processor 701 to implement a method for predicting the three-dimensional characteristics of fluvial facies reservoirs based on single-well data according to various embodiments of the present invention.

[0092] In some embodiments, processor 701 may be a central processing unit (CPU), microprocessor, or other data processing chip, used to run program code stored in memory 702 or process data, such as executing a program for predicting the three-dimensional characteristics of fluvial reservoirs based on single-well data.

[0093] In some embodiments, display 703 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. Display 703 is used to display information on a computer device and to display a visual user interface. Components 701-703 of the computer device communicate with each other via a system bus.

[0094] This embodiment also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the method for predicting the three-dimensional characteristics of fluvial reservoirs based on single-well data as described in any of the above technical solutions.

[0095] In the several embodiments provided by this invention, it should be understood that the disclosed methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0096] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for predicting the three-dimensional spatial characteristics of fluvial reservoirs based on single-well data, characterized in that, include: S1, a map of different types of fluvial reservoirs constructed based on sedimentological principles; S2, Based on the parameter variations of different types of fluvial facies reservoirs, determine the three-dimensional spatial characteristic variation patterns of the corresponding maps for each type of fluvial facies reservoir; S3. Based on the map and three-dimensional spatial characteristic variation patterns of different types of fluvial reservoirs, an analogy index system is constructed. S4. Obtain new drilling information, extract drilling-related indicators from the new drilling information, and construct a sample of evaluation indicators for new drilling. S5. Based on the evaluation index sample of the new well and the analogy index system of different types of fluvial reservoirs, combined with the map and three-dimensional spatial characteristic change pattern of different types of fluvial reservoirs, compile the fluvial reservoir characteristic sample table and the three-dimensional spatial change map of reservoir characteristics, and predict the three-dimensional spatial characteristic change of the reservoir at the new well.

2. The method for predicting the three-dimensional spatial characteristics of fluvial reservoirs based on single-well data according to claim 1, characterized in that, S1 includes: Determining the main controlling factors of fluvial facies based on sedimentological principles; Based on the main controlling factors, fluvial reservoirs are classified into different types, and corresponding three-dimensional fluvial reservoir maps are established.

3. The method for predicting the three-dimensional spatial characteristics of fluvial reservoirs based on single-well data according to claim 2, characterized in that, In S3, the analogy index system includes decisive criteria, binding criteria, and supplementary criteria; wherein, the decisive criteria are used to determine the map type, the binding criteria are used to determine the geographical location of the map, and the supplementary criteria are used to analyze the changes in the main parameters of the reservoir without changing the location of the map.

4. The method for predicting the three-dimensional spatial characteristics of fluvial reservoirs based on single-well data according to claim 3, characterized in that, include: Based on the three-dimensional map parameters of different river types, a river facies reservoir analogy parameter system is constructed. The three-dimensional map parameters include genetic domain parameters, entity domain parameters, and response domain parameters. Among them, the genetic domain parameters are used to describe the conditional parameters of sedimentary genesis; the entity domain parameters are used to quantify the physical entity characteristics of the reservoir; and the attribute response domain parameters are used to describe the measurement indicators.

5. The method for predicting the three-dimensional spatial characteristics of fluvial reservoirs based on single-well data according to claim 4, characterized in that, Further includes: Extract lithological data from the parameter information of the 3D map and perform similarity statistics on the lithological data; The maximum, minimum, and median values ​​are determined based on the similarity statistics, and the segment ranges are divided based on the maximum, minimum, and median values. A fluvial reservoir analog parameter system is constructed based on segmented ranges of different parameters.

6. The method for predicting the three-dimensional spatial characteristics of fluvial reservoirs based on single-well data according to claim 1, its The key feature is that, in S4, drilling-related metrics include: Well logging facies, well logging facies combinations, core color, sand-to-soil ratio, interlayers, rock composition and content, and some analytical and test data.

7. The method for predicting the three-dimensional spatial characteristics of fluvial reservoirs based on single-well data according to claim 6, characterized in that, include: Based on the decisive indicators of new drilling, determine the candidate map types for the reservoir; The planar position of the chart is determined based on the binding parameters of the new well and the candidate chart type.

8. The method for predicting the three-dimensional spatial characteristics of fluvial reservoirs based on single-well data according to claim 7, characterized in that, Also includes: When the planar position of a chart cannot be determined based on the binding indicators and candidate chart types, the corresponding position value of the chart is modified according to the supplementary indicators of the new drilling.

9. A computer-readable storage medium, characterized in that, The device contains a computer program that, when executed by a processor, implements the method of any one of claims 1 to 8.

10. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, it implements the method of any one of claims 1 to 8.

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