Stratum and sand body distribution identification method and device based on unmanned aerial vehicle digital outcrop

Abstract

The invention discloses a formation and sand body distribution identification method and device based on unmanned aerial vehicle digital outcrop. The formation and sand body distribution identification method based on the unmanned aerial vehicle digital outcrop comprises the following steps: determining a plurality of to-be-identified point locations in a to-be-identified region, determining target formation characteristics of each to-be-identified point location, determining a formation remote sensing image corresponding to an original remote sensing image based on the target formation characteristics, and obtaining formation distribution characteristics of the to-be-identified region; determining a plurality of geological outcrop point locations based on the target stratum features, establishing a three-dimensional live-action model corresponding to each geological outcrop point location based on the stratum remote sensing image, determining the target lithologic features of each geological outcrop point location, and determining a lithologic live-action model corresponding to each three-dimensional live-action model; and determining sand body feature data of the geological outcrop point, and determining sand body distribution features of the to-be-identified region based on the sand body feature data. According to the method, the distribution identification accuracy of the stratum and the sand body is improved, and the distribution identification cost of the stratum and the sand body is reduced.

Description

Technical Field

[0001] The present invention relates to the field of remote sensing interpretation technology, and in particular to a method and a device for identifying the distribution of strata and sand bodies based on unmanned aerial vehicle digital outcrops. Background Art

[0002] In the application of oil and gas fine geology, the identification of the distribution characteristics of strata and sand bodies has a good application prospect in oil and gas exploration and development and geological applications. Effective distribution feature identification is conducive to oil and gas exploration and development and geological applications.

[0003] At present, the common method for identifying the distribution of strata and sand bodies is: through the analysis of seismic data and logging data by experienced personnel in relevant technical fields, the distribution characteristics of strata and sand bodies are obtained. However, the amount of relevant data is relatively large, so it involves poor efficiency and high labor consumption costs, and the technical problems of low universality of experienced personnel and poor identification accuracy. Summary of the invention

[0004] The present invention provides a method and device for identifying the distribution of strata and sand bodies based on unmanned aerial vehicle digital outcrops, so as to solve the technical problems of low efficiency, high cost and poor accuracy in the identification of the distribution of strata and sand bodies.

[0005] According to one aspect of the present invention, a method for identifying the distribution of strata and sand bodies based on UAV digital outcrops is provided, wherein the method comprises:

[0006] Determine a region to be identified, and obtain an original remote sensing image corresponding to the region to be identified;

[0007] Determine a plurality of points to be identified in the area to be identified, determine target stratigraphic features of each of the points to be identified, determine a stratigraphic remote sensing image corresponding to the original remote sensing image based on the target stratigraphic features, and obtain stratigraphic distribution features of the area to be identified;

[0008] Determine a plurality of geological outcrop points based on the target stratigraphic features, establish a three-dimensional real-scene modeling corresponding to each of the geological outcrop points based on the stratigraphic remote sensing image, determine the target lithological features of each of the geological outcrop points, and determine the lithological real-scene modeling corresponding to each of the three-dimensional real-scene modeling based on the target lithological features;

[0009] The sand body characteristic data of the geological outcrop point is determined based on the lithology real-scene modeling, and the sand body distribution characteristics of the area to be identified are determined based on the sand body characteristic data.

[0010] According to another aspect of the present invention, a device for identifying the distribution of strata and sand bodies based on UAV digital outcrops is provided, wherein the device comprises:

[0011] A remote sensing image acquisition module is used to determine the area to be identified and obtain the original remote sensing image corresponding to the area to be identified;

[0012] A stratigraphic distribution recognition module is used to determine a plurality of points to be identified in the area to be identified, and determine the target stratigraphic features of each of the points to be identified, and determine the stratigraphic remote sensing image corresponding to the original remote sensing image based on the target stratigraphic features to obtain the stratigraphic distribution features of the area to be identified;

[0013] A lithology real-scene modeling module is used to determine a plurality of geological outcrop points based on the target stratigraphic features, establish a three-dimensional real-scene modeling corresponding to each of the geological outcrop points based on the stratigraphic remote sensing image, determine the target lithology features of each of the geological outcrop points, and determine the lithology real-scene modeling corresponding to each of the three-dimensional real-scene modeling based on the target lithology features;

[0014] The sand body distribution identification module is used to determine the sand body characteristic data of the geological outcrop point based on the lithology real-scene modeling, and determine the sand body distribution characteristics of the area to be identified based on the sand body characteristic data.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for identifying the distribution of strata and sand bodies based on drone digital outcrops as described in any embodiment of the present invention.

[0019] 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 the method for identifying the distribution of strata and sand bodies based on drone digital outcrops as described in any embodiment of the present invention when executed.

[0020] The technical solution of the embodiment of the present invention is to obtain the original remote sensing image corresponding to the area to be identified by determining the area to be identified; determine multiple points to be identified in the area to be identified, and determine the target stratigraphic features of each point to be identified, determine the stratigraphic remote sensing image corresponding to the original remote sensing image based on the target stratigraphic features, and obtain the stratigraphic distribution features of the area to be identified; determine multiple geological outcrop points based on the target stratigraphic features, establish three-dimensional real-scene modeling corresponding to each geological outcrop point based on the stratigraphic remote sensing image, and determine the target lithological features of each geological outcrop point, and determine the lithological real-scene modeling corresponding to each three-dimensional real-scene modeling based on the target lithological features; determine the sand body characteristic data of the geological outcrop point based on the lithological real-scene modeling, and determine the sand body distribution features of the area to be identified based on the sand body characteristic data. The present invention uses remote sensing images and three-dimensional real-scene modeling to improve the accuracy of the distribution identification of strata and sand bodies and reduce the cost of the distribution identification of strata and sand bodies.

[0021] 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

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 This is a flow chart of a method for identifying the distribution of strata and sand bodies based on UAV digital outcrops provided in accordance with Embodiment 1 of the present invention;

[0024] Figure 2 A stratum remote sensing image provided according to an embodiment of the present invention;

[0025] Figure 3 A remote sensing image to be identified corresponding to the Kalaza Formation marked with stratigraphic interpretation marks provided according to an embodiment of the present invention;

[0026] Figure 4 A remote sensing image to be identified corresponding to the Qingshuihe Formation marked with stratigraphic interpretation marks provided according to an embodiment of the present invention;

[0027] Figure 5 A stratum thickness image representing the exposed thickness of a stratum provided according to an embodiment of the present invention;

[0028] Figure 6 A scene graph for three-dimensional real scene modeling provided according to an embodiment of the present invention;

[0029] Figure 7 A scene diagram of lithology real-scene modeling provided according to an embodiment of the present invention;

[0030] Figure 8 It is a kind of sand body characteristic data characterizing the sand body distribution characteristics provided by an embodiment of the present invention;

[0031] Fig. 9 This is a flow chart of a method for identifying the distribution of strata and sand bodies based on UAV digital outcrops provided in accordance with Embodiment 2 of the present invention;

[0032] Fig.10 A data graph representing data characteristics of remote sensing stratum occurrence provided according to an embodiment of the present invention;

[0033] Fig.11 A scene diagram of three-point method occurrence extraction provided by an embodiment of the present invention;

[0034] Fig.12 A scene diagram of the occurrence extraction using the moving three-point method provided by an embodiment of the present invention;

[0035] Fig.13 A scene diagram of occurrence extraction using the trend surface method provided by an embodiment of the present invention;

[0036] Fig.14 This is a scene diagram of occurrence extraction using the dominant average method provided by an embodiment of the present invention;

[0037] Fig.15 is a structural schematic diagram of a stratum and sand body distribution identification device based on drone digital outcrop provided according to Embodiment 3 of the present invention;

[0038] Fig.16 It is a structural schematic diagram of an electronic device for implementing the method for identifying the distribution of strata and sand bodies based on unmanned aerial vehicle digital outcrops according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] 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.

[0040] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0041] Embodiment 1

[0042] Figure 1 A flow chart of a method for identifying the distribution of strata and sand bodies based on UAV digital outcrops is provided for the first embodiment of the present invention. This embodiment is applicable to the case of remote sensing interpretation. The method can be executed by a strata and sand body distribution identification device based on UAV digital outcrops. The strata and sand body distribution identification device based on UAV digital outcrops can be implemented in the form of hardware and / or software. The strata and sand body distribution identification device based on UAV digital outcrops can be configured in computer software. Figure 1 As shown, the method includes:

[0043] S110: Determine a region to be identified, and obtain an original remote sensing image corresponding to the region to be identified.

[0044] The region to be identified can be understood as a region where the strata and sand bodies to be identified are distributed. In the embodiment of the present invention, the region to be identified can be preset according to the scene requirements and is not specifically limited here. Optionally, the region to be identified can be the southern edge of the Junggar Basin.

[0045] The original remote sensing image can be understood as the remote sensing image corresponding to the area to be identified. Optionally, the original remote sensing image can be a high-resolution remote sensing image. Exemplarily, the original remote sensing image can be a high-resolution remote sensing image corresponding to the southern edge of the Junggar Basin.

[0046] It should be understood that in the embodiment of the present invention, taking the Kalaza Formation-Qingshuihe Formation on the southern edge of the Junggar Basin as an example, the main lithologies of the Kalaza Formation-Qingshuihe Formation include conglomerate, sandstone, siltstone and mudstone. The original remote sensing image uses 0.5-meter Quickbird data, and the study area is 150 kilometers long from east to west and 5 kilometers wide. A total of 10 drone three-dimensional digital outcrop models were collected and established, and the image accuracy reached 5 cm.

[0047] S120, determining a plurality of points to be identified in the area to be identified, and determining target stratigraphic features of each of the points to be identified, and determining a stratigraphic remote sensing image corresponding to the original remote sensing image based on the target stratigraphic features, to obtain stratigraphic distribution features of the area to be identified.

[0048] Among them, the points to be identified can be understood as sample points in the area to be identified. In an embodiment of the present invention, the points to be identified can be preset according to the scene requirements, and are not specifically limited here. Exemplarily, in an embodiment of the present invention, when the stratigraphic distribution characteristics identified are the stratigraphic distribution characteristics between the Kalaza Formation and the Qingshuihe Formation on the southern edge of the Gar Basin, the points to be identified can be a first preset number of points corresponding to the Kalaza Formation and a second preset number of points corresponding to the Qingshuihe Formation. Among them, the first preset number and the second preset number can be preset according to the scene requirements, respectively, and are not specifically limited here. The first preset number and the second preset number may be the same or different. Exemplarily, the first preset number and the second preset number may be 5, 10 or 15, etc.

[0049] The target stratum feature can be understood as the stratum feature corresponding to each of the points to be identified. Optionally, the target stratum feature may include the boundary between each stratum, the stratum property of each stratum, and the stratum exposure thickness of each stratum.

[0050] The stratum remote sensing image can be understood as a remote sensing image that characterizes the characteristics of the target stratum (refer to Figure 2 ).

[0051] The stratigraphic distribution characteristics can be understood as the stratigraphic distribution characteristics of the region to be identified. For example, the stratigraphic distribution characteristics can be the stratigraphic distribution characteristics between the Kalaza Formation and the Qingshuihe Formation (refer to Figure 2 ).

[0052] Optionally, the determining the stratum remote sensing image corresponding to the original remote sensing image based on the target stratum feature to obtain the stratum distribution feature of the area to be identified includes:

[0053] For each of the points to be identified, a stratigraphic interpretation mark is established on the remote sensing image to be identified based on the target stratigraphic features;

[0054] A stratigraphic remote sensing image corresponding to the original remote sensing image is obtained based on the plurality of stratigraphic interpretation marks, and stratigraphic distribution characteristics of the area to be identified are obtained based on the stratigraphic remote sensing image.

[0055] Among them, the remote sensing image to be identified can be understood as the remote sensing image corresponding to each of the points to be identified. Optionally, the remote sensing image to be identified may include remote sensing images corresponding to a first preset number of points to be identified in the Kalaza group and remote sensing images corresponding to a second preset number of points to be identified in the Qingshuihe group. Exemplarily, the remote sensing image to be identified may include remote sensing images corresponding to 10 points to be identified in the Kalaza group (refer to Figure 3 ) and the remote sensing images corresponding to the 10 points to be identified in the Qingshuihe Formation (reference Figure 4 ).

[0056] The stratigraphic interpretation mark can be understood as a mark that can characterize the target stratigraphic features on the original remote sensing image. Specifically, in an embodiment of the present invention, the stratigraphic interpretation mark can be marked on the cross section of the original remote sensing image (refer to Figure 3 and Figure 4 ).

[0057] S130. Determine a plurality of geological outcrop points based on the target stratigraphic characteristics, establish a three-dimensional real-scene modeling corresponding to each of the geological outcrop points based on the stratigraphic remote sensing image, and determine the target lithological characteristics of each of the geological outcrop points, and determine the lithological real-scene modeling corresponding to each of the three-dimensional real-scene modeling based on the target lithological characteristics.

[0058] The geological outcrop point can be understood as a point for establishing the three-dimensional real scene modeling. In the embodiment of the present invention, the geological outcrop point can include one or more, which are not specifically limited here. It can be understood that the target stratum feature includes the stratum outcrop thickness of each stratum.

[0059] Optionally, the determining of a plurality of geological outcrop locations based on the target stratum characteristics includes:

[0060] The point to be identified corresponding to the stratum outcrop thickness that meets the preset conditions is determined as the geological outcrop point.

[0061] Among them, the preset conditions can be understood as the conditions for screening out the geological outcrop points. Optionally, the points to be identified whose stratum exposure thickness is greater than a preset thickness threshold are determined as the geological outcrop points. Among them, the stratum exposure thickness can be preset according to scene requirements and is not specifically limited here. Specifically, in an embodiment of the present invention, for each of the points to be identified, a thickness interpretation mark corresponding to the stratum exposure thickness can be marked on the stratum remote sensing image to obtain a stratum thickness image (reference Figure 5 ).

[0062] The three-dimensional real scene modeling can be understood as the three-dimensional real scene modeling corresponding to the geological outcrop point established based on the stratum remote sensing image (refer to Figure 6 ), where J3k represents the Kalaza Formation and K1q represents the Qingshuihe Formation.

[0063] It should be understood that in the embodiments of the present invention, for field geological outcrops with complex terrain, large scale and large range, that is, geological outcrop points, "UAV stereoscopic acquisition modeling technology" is adopted, that is, low-altitude micro or light UAVs are used to perform multi-angle, high-overlap oblique photography of geological outcrop points, and advanced intelligent modeling software is used to reconstruct high-definition image big data into a three-dimensional outcrop model.

[0064] It is important to understand that the multi-view images of geological outcrop points collected by oblique photography from drones have all-round information and geographic information, and are the basic data for 3D modeling. The key technologies for 3D modeling using drones include aerial triangulation, geometric correction, joint adjustment of multi-view images, dense pixel matching of multi-view images, Mesh models, digital surface models (DSM), and true orthogonal image correction (TDOM). Among them, the construction of the Mesh model (grid surface model, commonly known as the triangulated mesh model) is the key. The ultra-high-density image point cloud is a massive point collection used to represent the spatial distribution and surface characteristics of the objects. The TIN (irregular triangulated network) is constructed with the point cloud to obtain the Mesh mesh surface model, and finally the real 3D model is constructed through real image texture mapping.

[0065] It should be understood that the data processing and modeling process mainly includes three steps: first, a large number of high-definition digital photos collected by professional digital cameras carried by drones are imported, namely the stratigraphic remote sensing images. These photos with high overlap contain the spatial position, attitude parameters and photography parameters of the camera when shooting; then automatic aerial triangulation is performed, and the aerial triangulation results are corrected by adding control points and editing connection points to improve the geometric and geographic spatial accuracy; finally, after the aerial triangulation calculation is completed, the inclined three-dimensional model is constructed on the aerial triangulation results: the result data is cut into pieces, the dense point cloud is extracted to construct an irregular triangular mesh model, and the high-definition photos are pasted as real textures on the model surface, thus finally completing the three-dimensional real scene modeling of the geological outcrop. The image resolution of the drone model can reach the centimeter level.

[0066] The target lithological characteristics can be understood as the lithological characteristics corresponding to each of the geological outcrop points.

[0067] The lithology real scene modeling can be understood as the three-dimensional real scene modeling that characterizes the target lithology characteristics (refer to Figure 7 ).

[0068] Optionally, the determining of the target lithological characteristics of each geological outcrop point, and determining the lithological real scene modeling corresponding to each three-dimensional real scene modeling based on the target lithological characteristics, includes:

[0069] Determine the image lithology characteristics of the current geological outcrop point based on the stratum remote sensing image, and determine the real-time lithology characteristics of the current geological outcrop point;

[0070] Determining target lithological features according to the real-time lithological features and the image lithological features, wherein the target lithological features include at least one of the boundary between each rock layer, the lithology, profile shape, occurrence and thickness of each rock layer;

[0071] Based on the target lithological characteristics, lithological interpretation marks are established on the current three-dimensional real-scene modeling to obtain lithological real-scene modeling.

[0072] The image lithology feature can be understood as the lithology feature corresponding to the current geological outcrop point represented by the stratum remote sensing image. Optionally, the image lithology feature can include at least one of the boundary between each rock layer, the lithology of each rock layer, the cross-sectional shape, the occurrence and the thickness of the rock layer.

[0073] The real-time lithological features can be understood as the lithological features corresponding to the current geological outcrop points determined based on artificial real-time survey. Optionally, the real-time lithological features can correspond to the feature types included in the image lithological features. In an embodiment of the present invention, the image lithological features are the same as or different from the real-time lithological features.

[0074] The lithology interpretation mark is a mark that can represent the target lithology feature in the three-dimensional real-scene modeling.

[0075] S140, determining the sand body characteristic data of the geological outcrop point based on the lithology real-scene modeling, and determining the sand body distribution characteristics of the area to be identified based on the sand body characteristic data.

[0076] The sand body characteristic data can be understood as data characterizing the characteristics of the sand body. Optionally, the sand body characteristic data can be a bar graph characterizing the types of sand bodies contained in the current geological outcrop point and the deposition location of the sand bodies (refer to Figure 8 ).

[0077] The sand body distribution characteristics can be understood as the distribution characteristics of the sand body determined based on the sand body characteristic data of multiple geological outcrop points (refer to Figure 8 ).

[0078] Optionally, determining the sand body distribution characteristics of the area to be identified based on the sand body characteristic data includes:

[0079] Determine the geographical location information of each geological outcrop point, and based on the geographical location information, connect the sand body characteristic data corresponding to the multiple geological outcrop points to obtain the sand body distribution characteristics of the area to be identified, wherein the sand body characteristic data is a bar graph characterizing the type of sand body contained in the current geological outcrop point and the deposition position of the sand body.

[0080] The geographical location information may be understood as information characterizing the geographical location of the geological outcrop point.

[0081] The technical solution of the embodiment of the present invention is to obtain the original remote sensing image corresponding to the area to be identified by determining the area to be identified; determine multiple points to be identified in the area to be identified, and determine the target stratigraphic features of each point to be identified, determine the stratigraphic remote sensing image corresponding to the original remote sensing image based on the target stratigraphic features, and obtain the stratigraphic distribution features of the area to be identified; determine multiple geological outcrop points based on the target stratigraphic features, establish three-dimensional real-scene modeling corresponding to each geological outcrop point based on the stratigraphic remote sensing image, and determine the target lithological features of each geological outcrop point, and determine the lithological real-scene modeling corresponding to each three-dimensional real-scene modeling based on the target lithological features; determine the sand body characteristic data of the geological outcrop point based on the lithological real-scene modeling, and determine the sand body distribution features of the area to be identified based on the sand body characteristic data. The present invention uses remote sensing images and three-dimensional real-scene modeling to improve the accuracy of the distribution identification of strata and sand bodies and reduce the cost of the distribution identification of strata and sand bodies.

[0082] Embodiment 2

[0083] Fig. 9 The flowchart of a method for identifying the distribution of strata and sand bodies based on UAV digital outcrops provided in the second embodiment of the present invention is a refinement of the target stratum characteristics of each point to be identified as described in the above embodiment. Fig. 9 As shown, the method includes:

[0084] S210: Determine a region to be identified, obtain an original remote sensing image corresponding to the region to be identified, and determine a plurality of points to be identified in the region to be identified.

[0085] S220: Determine the remote sensing image to be identified corresponding to each of the points to be identified based on the original remote sensing image.

[0086] The remote sensing image to be identified can be understood as a remote sensing image corresponding to each point to be identified.

[0087] S230: Determine the image stratigraphic features of the current point to be identified based on the remote sensing image to be identified, and determine the real-time stratigraphic features of the current point to be identified.

[0088] The image stratigraphic features can be understood as stratigraphic features corresponding to the current point to be identified represented by the remote sensing image to be identified. Optionally, the image stratigraphic features can include the boundary between each stratum, the stratigraphic properties of each stratum, and the stratigraphic exposure thickness of each stratum.

[0089] The real-time stratigraphic features can be understood as stratigraphic features corresponding to the current point to be identified determined based on artificial real-time survey. Optionally, the real-time stratigraphic features can correspond to the feature types included in the image stratigraphic features. In an embodiment of the present invention, the image stratigraphic features are the same as or different from the real-time stratigraphic features.

[0090] S240. Determine target formation characteristics according to the image formation characteristics and the real-time formation characteristics, wherein the target formation characteristics include the boundary between each formation, the formation property of each formation, and the formation exposure thickness of each formation.

[0091] The target stratum feature may be understood as the stratum feature corresponding to the current point to be identified. The exposed stratum thickness may be understood as the exposed stratum thickness corresponding to the current point to be identified.

[0092] Optionally, the image formation feature includes image exposure thickness, the real-time formation feature includes real-time exposure thickness, and the step of determining the target formation feature of each point to be identified includes:

[0093] For each of the points to be identified, determining the image exposure distance and remote sensing stratum occurrence based on the remote sensing image to be identified, wherein the remote sensing stratum occurrence includes a dip and / or an inclination;

[0094] Determine the image exposure thickness based on the image exposure distance and the remote sensing stratum occurrence;

[0095] The real-time exposed thickness of the current point to be identified is determined, and the exposed thickness of the stratum is determined based on the image exposed thickness and the real-time exposed thickness.

[0096] The image exposure distance may be understood as the exposure distance of the stratum where the current point to be identified is located on the remote sensing image to be identified.

[0097] The remote sensing stratum occurrence can be understood as the stratum occurrence corresponding to the current point to be identified extracted based on the remote sensing image to be identified (refer to Fig.10). Optionally, the remotely sensed formation occurrence may include dip and / or inclination.

[0098] The image exposure thickness can be understood as the exposure thickness of the stratum where the current point to be identified is located on the remote sensing image to be identified.

[0099] The real-time exposed thickness can be understood as the exposed thickness corresponding to the current geological outcrop point determined based on artificial real-time survey.

[0100] S250. Determine the stratigraphic remote sensing image corresponding to the original remote sensing image based on the target stratigraphic features, and obtain stratigraphic distribution features of the area to be identified.

[0101] S260, determining a plurality of geological outcrop points based on the target stratigraphic characteristics, establishing a three-dimensional real-scene modeling corresponding to each of the geological outcrop points based on the stratigraphic remote sensing image, and determining the target lithological characteristics of each of the geological outcrop points, and determining the lithological real-scene modeling corresponding to each of the three-dimensional real-scene modeling based on the target lithological characteristics.

[0102] S270, determining the sand body characteristic data of the geological outcrop point based on the lithology real-scene modeling, and determining the sand body distribution characteristics of the area to be identified based on the sand body characteristic data.

[0103] The technical solution of the embodiment of the present invention is to determine the remote sensing image to be identified corresponding to each point to be identified based on the original remote sensing image; determine the image stratigraphic features of the current point to be identified based on the remote sensing image to be identified, and determine the real-time stratigraphic features of the current point to be identified; determine the target stratigraphic features according to the image stratigraphic features and the real-time stratigraphic features, wherein the target stratigraphic features include the boundary between each stratigraphic layer, the stratigraphic properties of each stratigraphic layer, and the stratigraphic exposed thickness of each stratigraphic layer. Based on multi-faceted data comparison, the accuracy of the determined target stratigraphic features is guaranteed.

[0104] Optionally, the overall process of the method for identifying the distribution of strata and sand bodies based on UAV digital outcrops may be:

[0105] The present invention provides a method for identifying the distribution of strata and sand bodies based on UAV digital outcrops. The technical scheme of the method includes: 1. determining the distribution of strata based on high-resolution remote sensing images; 2. finely depicting the sand layer based on the UAV digital outcrop model; 3. connecting the sand body characteristic data to obtain the sand body distribution characteristics.

[0106] 1. Determine the distribution of strata based on high-resolution remote sensing images.

[0107] It is important to understand that remote sensing geological interpretation refers to the entire process of extracting geological information and data from remote sensing images to solve geological problems and explain various geological phenomena. The interpretation methods include direct interpretation: for images with obvious geological features and clear signs, the properties of the geological body and its spatial characteristics can be directly determined. For example, some faults and some igneous intrusive bodies; comparative interpretation: the properties of certain geological bodies are determined by comparative analysis with known signs in adjacent areas or standard interpretation areas; inferred interpretation: for some geological phenomena that often occur together, once the properties of one geological phenomenon are determined, the properties of another geological phenomenon that is associated with it can be inferred. For example, anticlines and synclines in fold structures, etc.

[0108] 1) Interpret remote sensing strata (determine the characteristics of the target strata). Through field surveys, analyze the outcrop characteristics and image characteristics of the strata in the area to be identified on the high-resolution remote sensing image (original remote sensing image), establish stratum interpretation image identification marks (stratum interpretation marks), divide the stratum distribution range of the area to be identified, and clarify the plane distribution characteristics of the strata. The resolution of high-resolution remote sensing images is generally 0.4 meters to 1 meter.

[0109] 2) Extracting the strike of remotely sensed strata. At present, the strike (dip and inclination) of strata has been initially realized by using high-resolution ground elevation model (DEM) remote sensing data. According to different situations such as interpreted rock layers, stratigraphic lines and trend surfaces, three automatic strike extraction methods have been developed. (1) Three-point method: The three-point method is used to calculate the fixed strike of the plane normal direction as the center point on the rock layer (refer to Fig.11 ); (2) Moving three-point method: for a stratum line or a marker line, calculate the occurrence of three points on the line at a given interval (refer to Fig.12 ); (3) Trend surface method: using irregular triangulated network to calculate the occurrence of each triangular facet (refer to Fig.13 ); (4) Then use the dominant average method to calculate the dominant occurrence of multiple surfaces (refer to Fig.14 ).

[0110] 3) Calculate the thickness of the exposed strata. Measure the distance of the exposed strata on the plane on the remote sensing image, multiply it by the dip angle of the occurrence, calculate the true thickness of the exposed strata, and then analyze the characteristics of the strata distribution.

[0111] 2. Detailed characterization of sand layers based on UAV digital outcrop model.

[0112] 1) UAV digital outcrop acquisition and modeling. Based on remote sensing images, a three-dimensional real-scene model corresponding to each geological outcrop point is established.

[0113] 2) Detailed description of sand layers. Through the image recognition marks of four types of lithology, namely conglomerate, sandstone, siltstone and mudstone, established in the field, the boundaries of each rock layer are finely divided on the three-dimensional digital outcrop model of the drone, and the thickness of each rock layer is measured. Detailed digital rock layer profiles and columnar diagrams are established, including topography, profile morphology, boundaries of each rock layer, lithology, occurrence and thickness, etc.

[0114] 3. Connect the sand body characteristic data to obtain the sand body distribution characteristics.

[0115] Based on the established typical cross-section rock column, the strata in multiple cross-section columnar diagrams are connected according to the geographical location to analyze the distribution characteristics of the sand body.

[0116] For example, taking the Kalaza Formation-Qingshuihe Formation on the southern edge of the Junggar Basin as an example, the main lithologies of the Kalaza Formation-Qingshuihe Formation include conglomerate, sandstone, siltstone and mudstone. The high-resolution remote sensing image uses 0.5-meter Quickbird data. The study area is 150 kilometers long from east to west and 5 kilometers wide. A total of 10 drone three-dimensional digital outcrop models were collected and established, and the image accuracy reached 5. Specifically, the overall process of the method for identifying the distribution of strata and sand bodies based on drone digital outcrops can be:

[0117] 1. Determine the distribution of strata based on high-resolution remote sensing images.

[0118] 1) Interpret remote sensing stratigraphy. (1) Identify and mark the stratigraphic interpretation marks of the Kalaza Formation. Through field surveys of 10 sections, the stratigraphic interpretation marks of the Kalaza Formation were established, and the boundaries of the Kalaza Formation at 10 points were demarcated on remote sensing images (refer to Figure 3 ), the Kalaza Formation has three image recognition features in the range of 150 km from west to east: 1> The main lithology is coarse conglomerate; 2> There are dotted vegetation, and the lithology is mainly conglomerate; 3> The main lithology is medium-coarse sandstone. (2) Identify and mark the stratigraphic interpretation marks of the Qingshuihe Formation. Through field surveys of 10 sections, the stratigraphic interpretation marks of the Qingshuihe Formation were established, and the boundaries of the Qingshuihe Formation at 10 points were demarcated on remote sensing images (refer to Figure 4 The image characteristics of the Qingshuihe Formation are relatively stable within a range of 150 km from west to east, and the main lithology is interbedded sand and mud.

[0119] The stratigraphic interpretation marks of the Kalaza Formation and Qingshuihe Formation were established based on the stratigraphic boundaries of 10 sections, and the stratigraphic boundaries of the two formations were interpreted on remote sensing images (refer to Figure 2 ).

[0120] 2) Extract remote sensing formation occurrence. Fig.10 ): The strata in the west are oriented northeast, with dips of more than 40°; the strata in the middle are oriented approximately due north and northeast, with dips of about 30°; the strata in the east are oriented northwest, with dips of more than 50°.

[0121] 3) Calculate the thickness of the exposed strata. Measure the distance of the exposed strata on the plane on the remote sensing image, multiply it by the dip angle of the occurrence, calculate the true thickness of the exposed strata, and then analyze the characteristics of the strata distribution.

[0122] 2. Detailed characterization of sand layers based on UAV digital outcrop model.

[0123] First, 10 UAV digital outcrop models were established, and the boundaries and thickness of the rock layers were carefully depicted on the models, and digital rock layer profiles were drawn (refer to Figure 6 and Figure 7 ).

[0124] 3. Connect the sand body characteristic data to obtain the sand body distribution characteristics.

[0125] Based on the established typical cross-section rock column, the strata in multiple cross-section columnar diagrams are connected according to the geographical location to analyze the distribution characteristics of the sand body.

[0126] refer to Figure 8 The distribution characteristics of sand bodies are as follows: 1) The thickness of J3k is unstable and partially missing; it is conglomerate in the west and medium sandstone in the east; the sedimentary facies is alluvial fan and fan delta, gradually transitioning to braided river delta to the east; 2) A layer of bottom conglomerate is developed at the bottom of K1q, and the middle and upper parts are interbedded with sand and mudstone; the bottom is fan delta deposits, and the middle and upper parts are shallow lake deposits.

[0127] Based on the technical solution of the embodiment of the present invention, high-resolution remote sensing and unmanned aerial vehicle digital outcrops are used to improve the accuracy of stratum and sand body distribution identification and reduce the cost of stratum and sand body distribution identification.

[0128] Embodiment 3

[0129] Fig.15 This is a schematic diagram of the structure of a stratum and sand body distribution identification device based on drone digital outcrop provided in the third embodiment of the present invention. Fig.15 As shown, the device includes: a remote sensing image acquisition module 310, a stratum distribution recognition module 320, a lithology real scene modeling module 330 and a sand body distribution recognition module 340; wherein,

[0130] The remote sensing image acquisition module 310 is used to determine the area to be identified and obtain the original remote sensing image corresponding to the area to be identified; the stratigraphic distribution identification module 320 is used to determine multiple points to be identified in the area to be identified, and determine the target stratigraphic characteristics of each point to be identified, determine the stratigraphic remote sensing image corresponding to the original remote sensing image based on the target stratigraphic characteristics, and obtain the stratigraphic distribution characteristics of the area to be identified; the lithological real-scene modeling module 330 is used to determine multiple geological outcrop points based on the target stratigraphic characteristics, establish a three-dimensional real-scene modeling corresponding to each geological outcrop point based on the stratigraphic remote sensing image, and determine the target lithological characteristics of each geological outcrop point, and determine the lithological real-scene modeling corresponding to each three-dimensional real-scene modeling based on the target lithological characteristics; the sand body distribution identification module 340 is used to determine the sand body characteristic data of the geological outcrop point based on the lithological real-scene modeling, and determine the sand body distribution characteristics of the area to be identified based on the sand body characteristic data.

[0131] The technical solution of the embodiment of the present invention is to obtain the original remote sensing image corresponding to the area to be identified by determining the area to be identified; determine multiple points to be identified in the area to be identified, and determine the target stratigraphic features of each point to be identified, determine the stratigraphic remote sensing image corresponding to the original remote sensing image based on the target stratigraphic features, and obtain the stratigraphic distribution features of the area to be identified; determine multiple geological outcrop points based on the target stratigraphic features, establish three-dimensional real-scene modeling corresponding to each geological outcrop point based on the stratigraphic remote sensing image, and determine the target lithological features of each geological outcrop point, and determine the lithological real-scene modeling corresponding to each three-dimensional real-scene modeling based on the target lithological features; determine the sand body characteristic data of the geological outcrop point based on the lithological real-scene modeling, and determine the sand body distribution features of the area to be identified based on the sand body characteristic data. The present invention uses remote sensing images and three-dimensional real-scene modeling to improve the accuracy of the distribution identification of strata and sand bodies and reduce the cost of the distribution identification of strata and sand bodies.

[0132] Optionally, the formation distribution identification module 320 is used to:

[0133] Determine the remote sensing image to be identified corresponding to each of the points to be identified based on the original remote sensing image;

[0134] Determine the image stratigraphic features of the current point to be identified based on the remote sensing image to be identified, and determine the real-time stratigraphic features of the current point to be identified;

[0135] The target formation characteristics are determined according to the image formation characteristics and the real-time formation characteristics, wherein the target formation characteristics include the boundary between each formation, the formation property of each formation and the formation exposure thickness of each formation.

[0136] Optionally, the formation distribution identification module 320 is used to:

[0137] For each of the points to be identified, a stratigraphic interpretation mark is established on the remote sensing image to be identified based on the target stratigraphic features;

[0138] A stratigraphic remote sensing image corresponding to the original remote sensing image is obtained based on the plurality of stratigraphic interpretation marks, and stratigraphic distribution characteristics of the area to be identified are obtained based on the stratigraphic remote sensing image.

[0139] Optionally, the image stratum feature includes image exposure thickness, the real-time stratum feature includes real-time exposure thickness, and the stratum spread identification module 320 is used to:

[0140] For each of the points to be identified, determining the image exposure distance and remote sensing stratum occurrence based on the remote sensing image to be identified, wherein the remote sensing stratum occurrence includes a dip and / or an inclination;

[0141] Determine the image exposure thickness based on the image exposure distance and the remote sensing stratum occurrence;

[0142] The real-time exposed thickness of the current point to be identified is determined, and the exposed thickness of the stratum is determined based on the image exposed thickness and the real-time exposed thickness.

[0143] Optionally, the lithology reality modeling module 330 is used to:

[0144] The point to be identified corresponding to the stratum outcrop thickness that meets the preset conditions is determined as the geological outcrop point.

[0145] Optionally, the lithology reality modeling module 330 is used to:

[0146] Determine the image lithology characteristics of the current geological outcrop point based on the stratum remote sensing image, and determine the real-time lithology characteristics of the current geological outcrop point;

[0147] Determining target lithological features according to the real-time lithological features and the image lithological features, wherein the target lithological features include at least one of the boundary between each rock layer, the lithology, profile shape, occurrence and thickness of each rock layer;

[0148] Based on the target lithological characteristics, lithological interpretation marks are established on the current three-dimensional real-scene modeling to obtain lithological real-scene modeling.

[0149] Optionally, the sand body distribution identification module 340 is used to:

[0150] Determine the geographical location information of each geological outcrop point, and based on the geographical location information, connect the sand body characteristic data corresponding to the multiple geological outcrop points to obtain the sand body distribution characteristics of the area to be identified, wherein the sand body characteristic data is a bar graph characterizing the type of sand body contained in the current geological outcrop point and the deposition position of the sand body.

[0151] The device for identifying the distribution of strata and sand bodies based on drone digital outcrops provided in an embodiment of the present invention can execute the method for identifying the distribution of strata and sand bodies based on drone digital outcrops provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0152] Embodiment 4

[0153] Fig.16 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.

[0154] like Fig.16 As 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.

[0155] 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.

[0156] 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, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, such as a method for identifying the distribution of strata and sand bodies based on drone digital outcrops.

[0157] In some embodiments, the method for identifying the distribution of strata and sand bodies based on drone digital outcrops 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 the method for identifying the distribution of strata and sand bodies based on drone digital outcrops described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the method for identifying the distribution of strata and sand bodies based on drone digital outcrops in any other appropriate manner (for example, by means of firmware).

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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).

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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 identifying the distribution of strata and sand bodies based on UAV digital outcrops, characterized in that: include: Determine a region to be identified, and obtain an original remote sensing image corresponding to the region to be identified; Determine a plurality of points to be identified in the area to be identified, determine target stratigraphic features of each of the points to be identified, determine a stratigraphic remote sensing image corresponding to the original remote sensing image based on the target stratigraphic features, and obtain stratigraphic distribution features of the area to be identified; Determine a plurality of geological outcrop points based on the target stratigraphic features, establish a three-dimensional real-scene modeling corresponding to each of the geological outcrop points based on the stratigraphic remote sensing image, determine the target lithological features of each of the geological outcrop points, and determine the lithological real-scene modeling corresponding to each of the three-dimensional real-scene modeling based on the target lithological features; The sand body characteristic data of the geological outcrop point is determined based on the lithology real-scene modeling, and the sand body distribution characteristics of the area to be identified are determined based on the sand body characteristic data.

2. The method according to claim 1, characterized in that Determining the target stratum characteristics of each of the points to be identified includes: Determine the remote sensing image to be identified corresponding to each of the points to be identified based on the original remote sensing image; Determine the image stratigraphic features of the current point to be identified based on the remote sensing image to be identified, and determine the real-time stratigraphic features of the current point to be identified; The target formation characteristics are determined according to the image formation characteristics and the real-time formation characteristics, wherein the target formation characteristics include the boundary between each formation, the formation property of each formation and the formation exposure thickness of each formation.

3. The method according to claim 1, characterized in that The step of determining the stratum remote sensing image corresponding to the original remote sensing image based on the target stratum feature to obtain the stratum distribution feature of the area to be identified includes: For each of the points to be identified, a stratigraphic interpretation mark is established on the remote sensing image to be identified based on the target stratigraphic features; A stratigraphic remote sensing image corresponding to the original remote sensing image is obtained based on the plurality of stratigraphic interpretation marks, and stratigraphic distribution characteristics of the area to be identified are obtained based on the stratigraphic remote sensing image.

4. The method according to claim 2, characterized in that: The image formation feature includes the image exposure thickness, the real-time formation feature includes the real-time exposure thickness, and the determination of the target formation feature of each point to be identified includes: For each of the points to be identified, determining the image exposure distance and remote sensing stratum occurrence based on the remote sensing image to be identified, wherein the remote sensing stratum occurrence includes a dip and / or an inclination; Determine the image exposure thickness based on the image exposure distance and the remote sensing stratum occurrence; The real-time exposed thickness of the current point to be identified is determined, and the exposed thickness of the stratum is determined based on the image exposed thickness and the real-time exposed thickness.

5. The method according to claim 4, characterized in that The step of determining a plurality of geological outcrop locations based on the target stratum characteristics comprises: The point to be identified corresponding to the stratum outcrop thickness that meets the preset conditions is determined as the geological outcrop point.

6. The method according to claim 1, characterized in that The step of determining the target lithological characteristics of each geological outcrop point and determining the lithological real scene modeling corresponding to each three-dimensional real scene modeling based on the target lithological characteristics comprises: Determine the image lithology characteristics of the current geological outcrop point based on the stratum remote sensing image, and determine the real-time lithology characteristics of the current geological outcrop point; Determining target lithological features according to the real-time lithological features and the image lithological features, wherein the target lithological features include at least one of the boundary between each rock layer, the lithology, profile shape, occurrence and thickness of each rock layer; Based on the target lithological characteristics, lithological interpretation marks are established on the current three-dimensional real-scene modeling to obtain lithological real-scene modeling.

7. The method according to claim 1, characterized in that Determining the sand body distribution characteristics of the area to be identified based on the sand body characteristic data includes: Determine the geographical location information of each geological outcrop point, and based on the geographical location information, connect the sand body characteristic data corresponding to the multiple geological outcrop points to obtain the sand body distribution characteristics of the area to be identified, wherein the sand body characteristic data is a bar graph characterizing the type of sand body contained in the current geological outcrop point and the deposition position of the sand body.

8. A device for identifying the distribution of strata and sand bodies based on UAV digital outcrops, characterized in that: include: A remote sensing image acquisition module is used to determine the area to be identified and obtain the original remote sensing image corresponding to the area to be identified; A stratigraphic distribution recognition module is used to determine a plurality of points to be identified in the area to be identified, and determine the target stratigraphic features of each of the points to be identified, and determine the stratigraphic remote sensing image corresponding to the original remote sensing image based on the target stratigraphic features to obtain the stratigraphic distribution features of the area to be identified; A lithology real-scene modeling module is used to determine a plurality of geological outcrop points based on the target stratigraphic features, establish a three-dimensional real-scene modeling corresponding to each of the geological outcrop points based on the stratigraphic remote sensing image, determine the target lithology features of each of the geological outcrop points, and determine the lithology real-scene modeling corresponding to each of the three-dimensional real-scene modeling based on the target lithology features; The sand body distribution identification module is used to determine the sand body characteristic data of the geological outcrop point based on the lithology real-scene modeling, and determine the sand body distribution characteristics of the area to be identified based on the sand body characteristic data.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for identifying the distribution of strata and sand bodies based on drone digital outcrops as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for identifying the distribution of strata and sand bodies based on unmanned aerial vehicle digital outcrops according to any one of claims 1 to 7 when executed.

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