Mountainous area geophysical prospecting construction difficulty determination method, device, equipment and storage medium

Abstract

The embodiment of the application provides a mountain area geophysical prospecting construction difficulty determination method, device, equipment and storage medium, the method comprises the following steps: determining the relief, slope, cliff, gully and traffic target difficulty weight of the work area; obtain the construction difficulty coefficient of the relief, slope, cliff, gully and traffic of the target work area; according to the construction difficulty coefficient of the relief, slope, cliff, gully and traffic of the target work area and the target difficulty weight, the construction difficulty coefficient of the target work area is determined, the key factors influencing the construction difficulty in the mountain area are preferably determined, the weight of each key factor is determined, and the construction difficulty coefficient of the whole target work area is obtained, which provides more objective support for the economic and technical integrated evaluation work of seismic exploration acquisition project.

Description

Technical Field

[0001] This application relates to the field of petroleum geophysical exploration technology, specifically to a method, apparatus, computer equipment, and storage medium for determining the difficulty of geophysical exploration operations in mountainous areas. Background Technology

[0002] Currently, in order to complete seismic exploration work more efficiently and accurately, many seismic acquisition projects conduct cost calculations before they officially begin. In the past, most of them used field reconnaissance to estimate the difficulty of the work area. However, seismic acquisition is now characterized by a large workload, short cycle, fast pace, and increasing complexity. Simply estimating the difficulty coefficient through field reconnaissance can no longer meet the needs of the fast-paced and scientific development of oilfield production.

[0003] In characterizing the difficulty of field geophysical exploration in the southwestern mountainous region, most current methods involve qualitative evaluation followed by the determination of a difficulty coefficient for calculation. A few quantitative evaluation methods only refer to the dimensions of undulation and slope.

[0004] Therefore, there is an urgent need to explore a scientific, reasonable, objective, economical, efficient, and repeatable method for calculating the construction difficulty coefficient, so as to better meet the needs of cost estimation for seismic acquisition projects. Summary of the Invention

[0005] This application provides a method, apparatus, computer equipment, and storage medium for determining the difficulty of geophysical exploration operations in mountainous areas.

[0006] The first aspect of this application provides a method for determining the difficulty of geophysical exploration operations in mountainous areas, including:

[0007] Determine the target difficulty weights for the work area's undulation, slope, steep cliffs, gullies, and transportation;

[0008] Obtain the construction difficulty coefficients of the target work area, including its undulation, slope, steep cliffs, gullies, and transportation.

[0009] The construction difficulty coefficient of the target work area is determined based on the construction difficulty coefficient and target difficulty weight of the undulation, slope, steep cliff, gully and traffic of the target work area.

[0010] In an optional embodiment of this application, determining the target difficulty weights for the undulation, slope, cliffs, gullies, and transportation of the work area includes:

[0011] Based on the multivariate linear regression algorithm, the first difficulty weights of the undulation, slope, cliff, gully and traffic of the known work area are determined according to the construction difficulty coefficients of the known work area.

[0012] Based on the geometric mean method, the target difficulty weights of the undulation, slope, cliff, gully, and transportation of the known work area are determined according to the first difficulty weights of the known work area.

[0013] In an optional embodiment of this application, based on a multivariate linear regression algorithm, the first difficulty weights of the undulation, slope, cliff, gully, and traffic of the known work area are determined according to the construction difficulty coefficients of the known work area, including:

[0014] Using the first difficulty weights of the known work area's undulation, slope, cliffs, gullies, and transportation as independent variables, and the known construction difficulty coefficient of the work area as the dependent variable, an expression for solving the first difficulty weight is constructed.

[0015] Based on the expression for solving the first difficulty weight, the first difficulty weight of the undulation, slope, cliff, gully and traffic of the known work area is solved according to the construction difficulty coefficients of the known work area.

[0016] In an optional embodiment of this application, the first difficulty weight of the undulation, slope, cliff, gully, and traffic of the known work area is solved based on the expression for solving the first difficulty weight, according to the construction difficulty coefficients of the known work area's undulation, slope, cliff, gully, and traffic, including:

[0017] For the following expression for solving the weight of the first difficulty level:

[0018] y = b0 + b1x1 + b2x2 + ... + b5x5 + c

[0019] Where y is the construction difficulty coefficient of the known work area, x1,x2,...,x n Let b0 be the construction difficulty coefficient for the known work area's undulation, slope, cliffs, gullies, and traffic conditions, respectively; b1, b2, b3, ..., b5 be the first difficulty weights for the known work area's undulation, slope, cliffs, gullies, and traffic conditions, respectively; and c be the error term.

[0020] The first difficulty weights for the undulation, slope, steep cliffs, gullies, and transportation in the known work area are determined by minimizing the following loss function:

[0021]

[0022] Where m is the number of samples, n is the number of indicators, and y i For the actual value of the i-th sample, Let β be the predicted value of the i-th sample, and β0 be the sum of the intercept and error terms. j Let x be the first difficulty weight of the j-th indicator. ijLet be the construction difficulty coefficient of the j-th indicator for the i-th sample.

[0023] In an optional embodiment of this application, based on the geometric mean method, the target difficulty weights for the undulation, slope, cliffs, gullies, and traffic of the known work area are determined according to the first difficulty weights of the known work area, including:

[0024] The weights of the undulation, slope, cliff, gully, and transportation difficulty of each known work area are used as column vectors to generate an index weight matrix for multiple known work areas.

[0025] Multiply the elements of the index weight matrix by row to obtain the first column vector;

[0026] Take the α-th root of each element of the first column vector to obtain the second column vector; where α is the number of known work areas.

[0027] Normalize the second column vector to obtain the third column vector, where the elements of the third column vector are the target difficulty weights for the undulation, slope, cliff, gully, and traffic of the known work area.

[0028] In an optional embodiment of this application, obtaining the construction difficulty coefficients of the target work area's undulation, slope, cliffs, gullies, and traffic includes:

[0029] The target work area is divided into multiple grids according to the preset specifications;

[0030] The construction difficulty coefficients of the current grid point are determined based on the relative elevation difference, slope value, presence of steep cliffs, presence of gullies, and the number of kilometers of non-highway rural roads.

[0031] Based on the preset time windows for undulation, slope, cliff, gully, and traffic, the construction difficulty coefficients of the target work area are determined according to the construction difficulty coefficients of all grid points in the target work area for undulation, slope, cliff, gully, and traffic.

[0032] In an optional embodiment of this application, the construction difficulty coefficient of the target work area is determined by the following expression, based on the construction difficulty coefficients of the undulation, slope, cliff, gully, and traffic of the target work area, and the target difficulty weight:

[0033] γ=a1z1+a2z2+...a5z5

[0034] Where z1, z2, ..., z nThese are the construction difficulty coefficients for the undulation, slope, cliff, gully, and transportation of the target work area, respectively, and a1, a2, a3, ..., a5 are the target difficulty weights for the undulation, slope, cliff, gully, and transportation of the target work area, respectively.

[0035] A second aspect of this application provides a device for determining the difficulty of geophysical exploration operations in mountainous areas, comprising:

[0036] The first determination module is used to determine the target difficulty weights for the undulation, slope, steep cliffs, gullies, and transportation in the work area;

[0037] The acquisition module is used to acquire the construction difficulty coefficients of the target work area, including its undulation, slope, steep cliffs, gullies, and transportation.

[0038] The second determination module is used to determine the construction difficulty coefficient of the target work area based on the construction difficulty coefficient and target difficulty weight of the target work area's undulation, slope, steep cliff, gully and traffic.

[0039] A third aspect of this application provides a computer device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of any of the above methods for determining the difficulty of geophysical exploration operations in mountainous areas.

[0040] A fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when executed by a processor, the computer program implements the steps of the method for determining the difficulty of geophysical exploration construction in mountainous areas as described above.

[0041] Compared with the prior art, the technical solutions provided in this application have at least some or all of the following advantages:

[0042] The method for determining the difficulty of geophysical exploration construction in mountainous areas described in this application determines the target difficulty weights for the undulation, slope, steep cliffs, gullies, and transportation of the work area; obtains the construction difficulty coefficients for the undulation, slope, steep cliffs, gullies, and transportation of the target work area; determines the construction difficulty coefficient of the target work area based on the construction difficulty coefficients and target difficulty weights for the undulation, slope, steep cliffs, gullies, and transportation of the target work area; selects the key factors affecting the construction difficulty in mountainous areas; determines the weight of each key factor; and obtains the construction difficulty coefficient of the entire target work area, providing more objective support for the integrated economic and technical evaluation of seismic exploration and acquisition projects. Attached Figure Description

[0043] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0044] Figure 1 A flowchart illustrating a method for determining the difficulty of geophysical exploration operations in mountainous areas, provided in one embodiment of this application;

[0045] Figure 2 A flowchart illustrating a method for determining the difficulty of geophysical exploration operations in mountainous areas, provided in another embodiment of this application;

[0046] Figure 3 A schematic diagram of a device for determining the difficulty of geophysical exploration in mountainous areas, provided in one embodiment of this application;

[0047] Figure 4 This is a schematic diagram of a computer device structure provided in one embodiment of this application. Detailed Implementation

[0048] To make the technical solutions and advantages of the embodiments of this application clearer, the exemplary embodiments of this application will be described in further detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not an exhaustive list of all embodiments. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other.

[0049] Please see Figure 1 The method for determining the difficulty of geophysical exploration in mountainous areas provided in this application includes the following steps 100 to 300:

[0050] Step 100: Determine the target difficulty weights for the undulation, slope, steep cliffs, gullies, and transportation in the work area;

[0051] Step 200: Obtain the construction difficulty coefficients of the target work area, including its undulation, slope, steep cliffs, gullies, and transportation.

[0052] Step 300: Determine the construction difficulty coefficient of the target work area based on the construction difficulty coefficient and target difficulty weight of the undulation, slope, steep cliff, gully and traffic of the target work area.

[0053] In an optional embodiment of this application, since the factors affecting the construction difficulty of seismic acquisition projects in mountainous areas include the height of the mountains, the development characteristics of steep cliffs and gullies, transportation conditions, surface lithology, and the distribution of dense forests, among which surface lithology mainly affects drilling construction, and this part has a clear compensation coefficient in the project cost, it is not considered in the construction difficulty coefficient for the time being. The distribution of dense forests and transportation conditions are strongly correlated, so they are also not considered for the time being. Therefore, the undulation, slope, steep cliffs, gullies, and transportation difficulty are preferred as the five important indicators for calculating the construction difficulty coefficient.

[0054] In an optional embodiment of this application, step 100, determining the target difficulty weights for the undulation, slope, cliffs, gullies, and traffic in the work area, includes:

[0055] Based on the multivariate linear regression algorithm, the first difficulty weights of the undulation, slope, cliff, gully and traffic of the known work area are determined according to the construction difficulty coefficients of the known work area.

[0056] Based on the geometric mean method, the target difficulty weights of the undulation, slope, cliff, gully, and transportation of the known work area are determined according to the first difficulty weights of the known work area.

[0057] In an optional embodiment of this application, based on a multivariate linear regression algorithm, the first difficulty weights of the undulation, slope, cliff, gully, and traffic of the known work area are determined according to the construction difficulty coefficients of the known work area, including:

[0058] Using the first difficulty weights of the known work area's undulation, slope, cliffs, gullies, and transportation as independent variables, and the known construction difficulty coefficient of the work area as the dependent variable, an expression for solving the first difficulty weight is constructed.

[0059] Based on the expression for solving the first difficulty weight, the first difficulty weight of the undulation, slope, cliff, gully and traffic of the known work area is solved according to the construction difficulty coefficients of the known work area.

[0060] In an optional embodiment of this application, the first difficulty weight of the undulation, slope, cliff, gully, and traffic of the known work area is solved based on the expression for solving the first difficulty weight, according to the construction difficulty coefficients of the known work area's undulation, slope, cliff, gully, and traffic, including:

[0061] For the following expression for solving the weight of the first difficulty level:

[0062] y = b0 + b1x1 + b2x2 + ... + b5x5 + c

[0063] Where y is the construction difficulty coefficient of the known work area, x1,x2,...,x n Let b0 be the construction difficulty coefficient for the known work area's undulation, slope, cliffs, gullies, and traffic conditions, respectively; b1, b2, b3, ..., b5 be the first difficulty weights for the known work area's undulation, slope, cliffs, gullies, and traffic conditions, respectively; and c be the error term.

[0064] The first difficulty weights for the undulation, slope, steep cliffs, gullies, and transportation in the known work area are determined by minimizing the following loss function:

[0065]

[0066] Where m is the number of samples, n is the number of indicators, and y i For the actual value of the i-th sample, Let β be the predicted value of the i-th sample, and β0 be the sum of the intercept and error terms. j Let x be the first difficulty weight of the j-th indicator. ij Let be the construction difficulty coefficient of the j-th indicator for the i-th sample.

[0067] In an optional embodiment of this application, based on the geometric mean method, the target difficulty weights for the undulation, slope, cliffs, gullies, and traffic of the known work area are determined according to the first difficulty weights of the known work area, including:

[0068] By using the weights of the undulation, slope, steep cliffs, gullies, and transportation difficulty of each known work area as column vectors, the following index weight matrices for multiple known work areas are generated:

[0069]

[0070] Multiply the elements of the index weight matrix by row to obtain the first column vector;

[0071] Take the α-th root of each element of the first column vector to obtain the second column vector; where α is the number of known work areas.

[0072] Normalize the second column vector to obtain the third column vector, where the elements of the third column vector are the target difficulty weights for the undulation, slope, cliff, gully, and traffic of the known work area.

[0073] In an optional embodiment of this application, step 200, obtaining the construction difficulty coefficients of the target work area's undulation, slope, cliffs, gullies, and traffic, includes:

[0074] The target work area is divided into multiple grids according to the preset specifications;

[0075] The construction difficulty coefficients of the current grid point are determined based on the relative elevation difference, slope value, presence of steep cliffs, presence of gullies, and the number of kilometers of non-highway rural roads.

[0076] Based on the preset time windows for undulation, slope, cliff, gully, and traffic, the construction difficulty coefficients of the target work area are determined according to the construction difficulty coefficients of all grid points in the target work area for undulation, slope, cliff, gully, and traffic.

[0077] See Figure 2Surface relief refers to the elevation difference between the highest and lowest points within a defined area. The greater the elevation difference within a region, the greater the construction difficulty. The time window for surface relief is determined based on the area of ​​the work area, generally within 5 square kilometers. It is calculated using 10m precision DEM (Digital Elevation Model) data. Grid points with a relative elevation difference of less than 200 meters within the time window are assigned a difficulty coefficient of 0.7; grid points with a relative elevation difference greater than or equal to 200 meters and less than 400 meters are assigned a difficulty coefficient of 0.8; grid points with a relative elevation difference greater than or equal to 400 meters and less than 600 meters are assigned a difficulty coefficient of 0.9; and grid points with a relative elevation difference greater than or equal to 600 meters are assigned a difficulty coefficient of 1.0. The difficulty coefficient of the current region's relief index is obtained by calculating the average of the difficulty coefficients of all grid points within each time window in the region.

[0078] See Figure 2 Slope and other geographical features are correlated. The slope time window is determined based on the area of ​​the work area, generally within 500m*500m, and is calculated from a grid point and its surrounding 8 grids. The steeper the slope, the greater the construction difficulty. A grid point with a slope value less than 10 is assigned a difficulty coefficient of 0.7; a grid point with a slope value greater than or equal to 10 but less than 20 is assigned a difficulty coefficient of 0.8; a grid point with a slope value greater than or equal to 20 but less than 30 is assigned a difficulty coefficient of 0.9; and a grid point with a slope value greater than or equal to 30 is assigned a difficulty coefficient of 1.0. The slope difficulty coefficient of the current area is obtained by averaging the difficulty coefficients of all grid points in each time window within the area.

[0079] See Figure 2 Steep cliffs, resembling vertical slopes, significantly hinder personnel access and equipment relocation, regardless of size. The difficulty coefficient can be calculated by statistically analyzing the presence or absence of steep cliffs within a defined area. The time window for steep cliffs is determined by the area of ​​the work zone, typically within 1 square kilometer. If a grid point containing a steep cliff exists within the time window, its difficulty coefficient is assigned as 1; otherwise, it is assigned as 0.5. The steep cliff difficulty coefficient for the current area is obtained by averaging the difficulty coefficients of all grid points across all time windows within the region.

[0080] See Figure 2Gullies are channels formed by intermittent water erosion on the ground, and are common in hilly and mountainous areas. Gullies can also have a certain impact on construction. The time window for gully identification depends on the area of ​​the work zone, generally within 1 square kilometer. If a grid point with a gully exists within the time window, the difficulty coefficient of the current point is assigned as 1; if no grid point with a gully exists within the time window, the difficulty coefficient of the current point is assigned as 0.5. The gully index difficulty coefficient of the current area is obtained by calculating the average of the difficulty coefficients of all grid points in each time window within the area.

[0081] See Figure 2 Regarding transportation, since highways are mostly enclosed with few exits, the focus is primarily on non-highway national roads, provincial roads, county roads, and township roads. When calculating traffic difficulty, not only the total mileage but also the uniformity of road distribution must be considered. A block-based calculation method is used, with each grid point as the center, and each block having an area of ​​10 square kilometers. Because road widths vary, the convenience of different roads also differs; therefore, township roads are multiplied by a coefficient of 0.8 when calculating road mileage. If the weighted road length of each block is less than 1.0 km, the traffic difficulty coefficient for that block is 1.0; if it is greater than or equal to 1.0 km but less than 3.0 km, the coefficient is 0.9; if it is greater than or equal to 3.0 km but less than 6.0 km, the coefficient is 0.8; if it is greater than or equal to 6.0 km but less than 10.0 km, the coefficient is 0.7; and if it is greater than or equal to 10.0 km, the coefficient is 0.6. The traffic difficulty coefficient for the current area is obtained by averaging the difficulty coefficients of all blocks within the area.

[0082] In an optional embodiment of this application, in step 300, the construction difficulty coefficient of the target work area is determined based on the construction difficulty coefficients and target difficulty weights of the undulation, slope, steep cliffs, gullies, and traffic of the target work area using the following expression:

[0083] γ=a1z1+a2z2+...a5z5

[0084] Where z1, z2, ..., z n These are the construction difficulty coefficients for the undulation, slope, cliff, gully, and transportation of the target work area, respectively, and a1, a2, a3, ..., a5 are the target difficulty weights for the undulation, slope, cliff, gully, and transportation of the target work area, respectively.

[0085] In an optional embodiment of this application, a weight matrix of sub-process indicators is constructed for multiple work areas, and then the final indicator weights can be obtained by using the geometric mean method. Taking a work area in Southwest China as an example, the final indicator weight allocation calculation result is (undulation 0.38, slope 0.23, steep cliff 0.16, traffic difficulty 0.13, gully 0.10). After calculating the difficulty coefficient of each indicator, the overall construction difficulty coefficient can be calculated by combining it with the weight value.

[0086] Overall construction difficulty coefficient = undulation index difficulty coefficient × 0.38 + slope index difficulty coefficient × 0.23 + steep cliff index difficulty coefficient × 0.16 + traffic difficulty index difficulty coefficient × 0.13 + gully index difficulty coefficient × 0.10.

[0087] In the cost calculation of a construction site in Southwest China, the application of this method improved the efficiency of cost calculation, reducing the calculation time from one week to two days. At the same time, during the construction process, by calculating costs by region and rationally dividing the subcontracted construction areas, reasonable prices were set according to the different construction difficulties, and personnel and equipment allocation were optimized, which mobilized production enthusiasm and improved overall production efficiency by 10%.

[0088] In an optional embodiment of this application, since each indicator has a different impact on construction difficulty, the final difficulty coefficient cannot be calculated simply by taking the average value. To allocate weights more scientifically, a statistical analysis method is chosen. To ensure the scientific validity and effectiveness of the indicator weight calculation, statistical analysis is performed on multiple work areas with similar characteristics to form multiple judgment matrices. Then, the geometric mean method is used to obtain the indicator weights. This method is less affected by extreme values ​​in the data, can eliminate data with large dispersion, and ensures the scientific rationality of the indicator weights.

[0089] This application employs a universally applicable research methodology. Through a dynamic, multi-weighted calculation method, it achieves quantitative calculation of the diverse difficulties in geophysical exploration operations in the complex mountainous regions of Southwest China. This provides a reference for various stages of seismic acquisition project deployment, technical scheme demonstration, engineering cost estimation, and production organization of each process. It can further improve the efficiency and scientific rigor of integrated economic and technical evaluation, facilitate the rational division of subcontracted construction areas and the formulation of reasonable prices based on varying construction difficulties, significantly impacting production enthusiasm and efficiency. It also promotes the safe, high-quality, and efficient completion of seismic acquisition projects and the implementation of green and environmentally friendly exploration.

[0090] This application presents a method for determining the difficulty of geophysical exploration construction in mountainous areas. Different seismic acquisition project areas have different characteristics. In some areas, the terrain has a large elevation difference, which is the biggest factor affecting construction. In other areas, the elevation difference is not large, but steep cliffs and gullies are very developed due to geological activity. In some areas, there are basically no roads and pedestrian walkways need to be built. Some areas have a combination of different characteristics. A dynamic calculation method is used to flexibly deal with different actual situations. First, the difficulty characteristics are calculated by index. Then, the weights of each index are constructed by statistically analyzing data from similar past projects. Finally, the construction difficulty is calculated using the established calculation model. This method can be applied to the integrated economic and technical evaluation of seismic exploration and acquisition projects.

[0091] The method for determining the difficulty of geophysical exploration in mountainous areas proposed in this application optimizes the influencing factors of geophysical exploration difficulty in mountainous regions, and then dynamically selects different weight combinations based on the actual characteristics of different work areas. This achieves a dynamic, multi-weighted method for calculating the difficulty coefficient of geophysical exploration in mountainous areas. It can dynamically calculate the construction difficulty coefficient based on the actual characteristics of each work area, thus providing a more accurate representation of the difficulty coefficient of geophysical exploration in the southwestern mountains.

[0092] It should be understood that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order constraint on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the diagram may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0093] Please see Figure 3 One embodiment of this application provides a device 300 for determining the difficulty of geophysical exploration operations in mountainous areas, comprising:

[0094] The first determining module 310 is used to determine the target difficulty weights of the undulation, slope, steep cliffs, gullies, and transportation in the work area;

[0095] The acquisition module 320 is used to acquire the construction difficulty coefficients of the target work area, including undulation, slope, steep cliffs, gullies, and transportation.

[0096] The second determining module 330 is used to determine the construction difficulty coefficient of the target work area based on the construction difficulty coefficient and target difficulty weight of the target work area's undulation, slope, cliff, gully and traffic.

[0097] Specific limitations regarding the aforementioned device 300 can be found in the above description of the limitations on the method for determining the difficulty of geophysical exploration in mountainous areas, and will not be repeated here. Each module in the aforementioned device 300 can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0098] In one embodiment, a computer device is provided, the internal structure of which can be as follows: Figure 4 As shown. The computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and the database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores data. The network interface communicates with external terminals via a network connection. When the processor executes the computer program, it implements the method for determining the difficulty of geophysical exploration operations in mountainous areas as described above. It includes: memory and a processor; the memory stores the computer program; and the processor executes the computer program to implement any step in the method for determining the difficulty of geophysical exploration operations in mountainous areas as described above.

[0099] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, can perform any step of a method for determining the difficulty of geophysical exploration operations in mountainous areas.

[0100] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0101] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0102] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0103] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0104] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0105] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for determining the difficulty of geophysical exploration operations in mountainous areas, characterized in that, include: Determine the target difficulty weights for the work area's undulation, slope, steep cliffs, gullies, and transportation; Obtain the construction difficulty coefficients of the target work area, including its undulation, slope, steep cliffs, gullies, and transportation. The construction difficulty coefficient of the target work area is determined based on the construction difficulty coefficient and target difficulty weight of the undulation, slope, steep cliff, gully and traffic of the target work area.

2. The method according to claim 1, characterized in that, The determination of the target difficulty weights for the undulation, slope, steep cliffs, gullies, and transportation in the work area includes: Based on the multivariate linear regression algorithm, the first difficulty weights of the undulation, slope, cliff, gully and traffic of the known work area are determined according to the construction difficulty coefficients of the known work area. Based on the geometric mean method, the target difficulty weights of the undulation, slope, cliff, gully, and transportation of the known work area are determined according to the first difficulty weights of the known work area.

3. The method according to claim 2, characterized in that, Based on a multivariate linear regression algorithm, the first difficulty weights for the undulation, slope, cliffs, gullies, and traffic of the known work area are determined according to the construction difficulty coefficients. These weights include: Using the first difficulty weights of the known work area's undulation, slope, cliffs, gullies, and transportation as independent variables, and the known construction difficulty coefficient of the work area as the dependent variable, an expression for solving the first difficulty weight is constructed. Based on the expression for solving the first difficulty weight, the first difficulty weight of the undulation, slope, cliff, gully and traffic of the known work area is solved according to the construction difficulty coefficients of the known work area.

4. The method according to claim 3, characterized in that, Based on the expression for solving the first difficulty weight, the first difficulty weight of the undulation, slope, cliff, gully, and traffic of the known work area is calculated according to the construction difficulty coefficients of the known work area, including: For the following expression for solving the weight of the first difficulty level: y = b0 + b1x1 + b2x2 + ... + b5x5 + c Where y is the construction difficulty coefficient of the known work area, x1,x2,...,x n Let b0 be the construction difficulty coefficient for the known work area's undulation, slope, cliffs, gullies, and traffic conditions, respectively; b1, b2, b3, ..., b5 be the first difficulty weights for the known work area's undulation, slope, cliffs, gullies, and traffic conditions, respectively; and c be the error term. The first difficulty weights for the undulation, slope, steep cliffs, gullies, and transportation in the known work area are determined by minimizing the following loss function: Where m is the number of samples, n is the number of indicators, and y i Let i be the actual value of the i-th sample. Let β be the predicted value of the i-th sample, and β0 be the sum of the intercept and error terms. j Let x be the first difficulty weight of the j-th indicator. ij Let be the construction difficulty coefficient of the j-th indicator for the i-th sample.

5. The method according to claim 2, characterized in that, Based on the geometric mean method, the target difficulty weights for the undulation, slope, cliffs, gullies, and transportation of the known work area are determined according to the first difficulty weights of these factors, including: The weights of the undulation, slope, cliff, gully, and transportation difficulty of each known work area are used as column vectors to generate an index weight matrix for multiple known work areas. Multiply the elements of the index weight matrix by row to obtain the first column vector; Take the α-th root of each element of the first column vector to obtain the second column vector; where α is the number of known work areas. Normalize the second column vector to obtain the third column vector, where the elements of the third column vector are the target difficulty weights for the undulation, slope, cliff, gully, and traffic of the known work area.

6. The method according to claim 1, characterized in that, Obtain the construction difficulty coefficients for the target work area, including its undulation, slope, steep cliffs, gullies, and transportation. The target work area is divided into multiple grids according to the preset specifications; The construction difficulty coefficients of the current grid point are determined based on the relative elevation difference, slope value, presence of steep cliffs, presence of gullies, and the number of kilometers of non-highway rural roads. Based on the preset time windows for undulation, slope, cliff, gully, and traffic, the construction difficulty coefficients of the target work area are determined according to the construction difficulty coefficients of all grid points in the target work area for undulation, slope, cliff, gully, and traffic.

7. The method according to claim 1, characterized in that, The construction difficulty coefficient of the target work area is determined using the following expression, based on the construction difficulty coefficients and target difficulty weights of the target work area's undulation, slope, steep cliffs, gullies, and transportation: γ=a1z1+a2z2+...a5z5 Where z1, z2, ..., z n These are the construction difficulty coefficients for the undulation, slope, cliff, gully, and transportation of the target work area, respectively, and a1, a2, a3, ..., a5 are the target difficulty weights for the undulation, slope, cliff, gully, and transportation of the target work area, respectively.

8. A device for determining the difficulty of geophysical exploration operations in mountainous areas, characterized in that, include: The first determination module is used to determine the target difficulty weights for the undulation, slope, steep cliffs, gullies, and transportation in the work area; The acquisition module is used to acquire the construction difficulty coefficients of the target work area, including its undulation, slope, steep cliffs, gullies, and transportation. The second determination module is used to determine the construction difficulty coefficient of the target work area based on the construction difficulty coefficient and target difficulty weight of the target work area's undulation, slope, steep cliff, gully and traffic.

9. A computer device, comprising: A memory and a processor, the memory storing a computer program, characterized in that, when the processor executes the computer program, it implements the steps of the method for determining the difficulty of geophysical exploration construction in mountainous areas as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for determining the difficulty of geophysical exploration in mountainous areas as described in any one of claims 1 to 7.

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