Design method and device for rock slope survey based on digitalized geological drilling machine

Abstract

The present application provides a rock slope survey design method and device based on a digital geological drilling rig, comprising: acquiring the while-drilling parameters collected by the digital geological drilling rig during drilling of multiple exploration holes; determining the total drilling power according to the while-drilling parameters to obtain effective rock breaking specific energy; adjusting the fluctuation weight of each while-drilling parameter according to the spatial mutation of the drilling rig control mode and the effective rock breaking specific energy to obtain a while-drilling discreteness index; determining the rock mass mechanical parameters distributed along the hole depth according to the effective rock breaking specific energy and the while-drilling discreteness index; determining the rock layer occurrence according to the corresponding mutation positions of the effective rock breaking specific energy in the multiple exploration holes, adjusting the interpolation weight of the known data points according to the rock layer occurrence and the effective rock breaking specific energy of the known data points, and performing spatial interpolation on the rock mass mechanical parameters based on the adjusted interpolation weight to obtain a three-dimensional rock mass mechanical parameter model, and determining the slope support parameters according to the spatial residual sliding force field and the burial depth of the potential sliding surface to generate a slope support design scheme.

Description

Technical Field

[0001] This invention relates to the field of geotechnical engineering investigation and design technology, and in particular to a method and apparatus for rock slope investigation and design based on a digital geological drilling rig. Background Technology

[0002] Rock slopes typically exhibit complex strata attitudes, significant spatial variations in rock mass mechanical properties, and concealed distributions of weak interlayers and fractured zones. The reliability of slope stability analysis and support design largely depends on the accurate acquisition of rock mass mechanical parameters and the spatial distribution of potential sliding structures. Traditional rock slope investigation primarily relies on core drilling, field logging, and laboratory testing to obtain rock and rock mass parameters. However, limitations in the number of boreholes, sampling integrity, and testing costs result in parameters that are usually discretely distributed, failing to continuously reflect changes in the rock mass with borehole depth and spatial location. With the development of digital geological drilling rigs, parameters generated during drilling, such as feed thrust, rotational torque, drill bit speed, and drilling velocity, can be continuously acquired, providing a data foundation for in-situ inversion of rock mass mechanical parameters, 3D geological modeling, and slope support design.

[0003] Current technologies typically estimate rock strength directly based on drilling parameters or drilling energy calculated from these parameters, evaluate rock mass integrity based on the fluctuation of these parameters, and then extend the rock mass parameters obtained from each exploration borehole to the three-dimensional region of the slope through spatial interpolation for stability analysis and support design. However, the drilling parameters collected during drilling are affected not only by rock mass properties but also by factors such as rig idle wear, drill pipe-hole wall friction, drilling depth, and rig control mode. This results in the inverted rock mechanics parameters not accurately reflecting the actual properties of the rock mass. Furthermore, conventional spatial interpolation primarily determines interpolation weights based on the spatial distance between data points, easily averaging data from different rock strata, weakening weak interlayers or stratum boundaries in the three-dimensional model. In addition, existing support designs often use zonal average parameters or empirical parameters, making it difficult to fully utilize the spatial distribution information of the rock mechanics parameters obtained from the drilling inversion. Therefore, how to obtain reliable rock mechanics parameters based on the drilling parameters collected by digital geological drilling rigs, construct a three-dimensional rock mechanics parameter model that maintains the rock strata interface and the heterogeneous characteristics of the rock mass, and determine the rock slope support design scheme accordingly has become an urgent technical problem to be solved. Summary of the Invention

[0004] This invention provides a method and apparatus for rock slope investigation and design based on a digital geological drilling rig, which solves the problem in the prior art that it is difficult to accurately construct a three-dimensional rock mass mechanical parameter model that reflects the rock strata interface and the heterogeneous characteristics of the rock mass based on drilling data, and to determine the slope support design scheme accordingly.

[0005] This invention provides a rock slope exploration and design method based on a digital geological drilling rig, comprising: acquiring drilling parameters collected by the digital geological drilling rig during drilling of multiple exploration holes; determining the total drilling power based on the drilling parameters and deducting the frictional power loss along the drilling path to obtain the effective rock breaking energy; adjusting the fluctuation weights of each drilling parameter according to the drilling rig control mode and the spatial abrupt change of the effective rock breaking energy to obtain the drilling dispersion index; determining the rock mass mechanical parameters distributed along the hole depth based on the effective rock breaking energy and the drilling dispersion index; determining the rock strata attitude based on the corresponding abrupt change locations of the effective rock breaking energy in multiple exploration holes; adjusting the interpolation weights of the known data points based on the rock strata attitude and the effective rock breaking energy of the known data points; and performing spatial interpolation on the rock mass mechanical parameters based on the adjusted interpolation weights to obtain a three-dimensional rock mass mechanical parameter model; determining the potential sliding surface and the spatial residual sliding force field based on the three-dimensional rock mass mechanical parameter model; and determining the slope support parameters based on the spatial residual sliding force field and the burial depth of the potential sliding surface to generate a slope support design scheme.

[0006] According to the rock slope exploration and design method based on digital geological drilling rig provided by the present invention, the rock mass mechanical parameters include rock mass cohesion and internal friction angle. The step of determining the potential sliding surface based on the three-dimensional rock mass mechanical parameter model includes: normalizing the rock mass cohesion and internal friction angle in the three-dimensional rock mass mechanical parameter model, and calculating the gradient modulus of the normalized rock mass cohesion and internal friction angle in three-dimensional space; determining the spatial comprehensive mutation rate field based on the gradient modulus corresponding to the rock mass cohesion and internal friction angle; extracting local maxima points in the spatial comprehensive mutation rate field to form an initial sliding surface point cloud, and performing clustering and spatial surface fitting on the initial sliding surface point cloud to obtain the potential sliding surface.

[0007] According to the rock slope exploration and design method based on a digital geological drilling rig provided by the present invention, the drilling parameters include the feed thrust, slewing torque, drill bit speed, and drilling speed of the geological drilling rig; the step of determining the total drilling power based on the drilling parameters and deducting the friction power loss along the drilling path to obtain the effective rock breaking energy includes: determining the total drilling power based on the feed thrust, the slewing torque, the drill bit speed, and the drilling speed; determining the basic no-load power loss based on the no-load feed thrust and no-load slewing torque when the drill bit is not in contact with the rock mass; determining the friction power loss along the drilling path based on the drilling depth and a pre-established depth-friction relationship; determining the effective net power based on the total drilling power, the basic no-load power loss, and the friction power loss along the drilling path; and determining the effective rock breaking energy based on the effective net power and the rock breaking volume per unit time.

[0008] According to the rock slope exploration and design method based on a digital geological drilling rig provided by the present invention, the step of adjusting the fluctuation weights of each of the drilling parameters according to the drilling rig control mode and the spatial abrupt change of the effective rock breaking specific energy to obtain the drilling dispersion index includes: determining the coefficient of variation of each of the drilling parameters within a preset depth window; reducing the fluctuation weights corresponding to the controlled drilling parameters according to the drilling rig control mode; normalizing the adjusted fluctuation weights and weighting the coefficients of variation according to the normalized fluctuation weights to obtain the drilling dispersion index.

[0009] According to the rock slope exploration and design method based on digital geological drilling rig provided by the present invention, the step of determining the rock mass mechanical parameters distributed along the borehole depth based on the effective rock breaking specific energy and the drilling dispersion index includes: determining the uniaxial compressive strength of the rock distributed along the borehole depth based on the effective rock breaking specific energy; determining the rock mass geological strength index distributed along the borehole depth based on the drilling dispersion index; and determining the rock mass mechanical parameters based on the rock uniaxial compressive strength and the rock mass geological strength index, according to the rock mass strength criterion.

[0010] According to the rock slope exploration and design method based on a digital geological drilling rig provided by the present invention, the step of spatially interpolating the rock mass mechanical parameters based on adjusted interpolation weights to obtain a three-dimensional rock mass mechanical parameter model includes: determining the rock strata attitude based on the corresponding abrupt change locations of the effective rock breaking energy in at least three exploration boreholes; constructing an anisotropic search neighborhood extending along the rock strata direction based on the rock strata attitude; the anisotropic search neighborhood is used to limit the selection range of known exploration borehole data points participating in spatial interpolation; projecting the node to be interpolated onto the known exploration boreholes based on the rock strata attitude, and adjusting the interpolation weights of the known data points based on the difference between the effective rock breaking energy at the projected location and the effective rock breaking energy of the known data points; and spatially interpolating the rock mass mechanical parameters corresponding to each of the exploration boreholes based on the adjusted interpolation weights to obtain the three-dimensional rock mass mechanical parameter model.

[0011] According to the rock slope exploration and design method based on digital geological drilling rig provided by the present invention, the method further includes: determining weak and abnormal regions based on the degree of rock mass strength attenuation between adjacent exploration boreholes in the three-dimensional rock mass mechanics parameter model; extracting abnormal data points with rock mass strength lower than a preset strength threshold from the weak and abnormal regions, and spatially clustering the abnormal data points to obtain weak and abnormal clusters; determining the locations of additional exploration boreholes based on the spatial location of the weak and abnormal clusters; obtaining the rock mass mechanics parameters corresponding to the additional exploration boreholes, and updating the three-dimensional rock mass mechanics parameter model based on the rock mass mechanics parameters corresponding to the additional exploration boreholes.

[0012] According to the rock slope investigation and design method based on digital geological drilling rig provided by the present invention, the step of determining the potential sliding surface and the spatial residual sliding force field based on the three-dimensional rock mass mechanics parameter model includes: performing slope stability analysis based on the spatial morphology of the potential sliding surface and the rock mass mechanics parameters corresponding to the potential sliding surface to obtain the spatial residual sliding force field; mapping the spatial residual sliding force field to multiple support nodes on the slope surface; and determining the anchor length and anchor hole density based on the residual sliding force corresponding to each support node and the burial depth of the potential sliding surface to obtain the slope support parameters.

[0013] According to the rock slope investigation and design method based on digital geological drilling rig provided by the present invention, the step of determining the anchor length based on the potential sliding surface burial depth corresponding to each of the support nodes and determining the anchor hole density based on the remaining sliding force corresponding to each of the support nodes includes: determining the maximum potential sliding surface burial depth corresponding to each support node in each of the preset slope zones according to preset slope zones; determining the theoretical anchor length corresponding to the preset slope zone based on the maximum potential sliding surface burial depth and the preset effective anchoring section length; and merging the theoretical anchor length upwards to the preset anchor mark. The anchor bolt length corresponding to the preset slope zone is obtained by determining the standard length; the remaining sliding force within the spatial control range corresponding to each support node is determined as the support resistance requirement of the corresponding support node, and the support resistance requirement is compared with the design resistance of a single anchor bolt; support nodes are added in areas where the support resistance requirement is greater than the design resistance, and the spatial control range is re-divided and the support resistance requirement is determined according to each added support node, until the support resistance requirement corresponding to each support node is not greater than the design resistance, so as to determine the anchor bolt hole density.

[0014] This invention also provides a rock slope exploration and design device based on a digital geological drilling rig, comprising: a data acquisition module for acquiring drilling parameters collected by the digital geological drilling rig during drilling of multiple exploration holes; a rock breaking energy calculation module for determining the total drilling power based on the drilling parameters and deducting the friction power loss along the drilling path to obtain the effective rock breaking energy; a dispersion index calculation module for adjusting the fluctuation weight of each drilling parameter according to the drilling rig control mode and the spatial abrupt change of the effective rock breaking energy to obtain the drilling dispersion index; and a rock mechanics parameter calculation module for determining the drilling power along the drilling path based on the effective rock breaking energy and the drilling dispersion index. The system includes: a rock mass mechanical parameters based on borehole depth distribution; an interpolation module for determining the rock strata attitude based on the corresponding abrupt changes in effective rock breaking energy in multiple exploration boreholes; adjusting the interpolation weights of the known data points based on the rock strata attitude and the effective rock breaking energy of the known data points; and spatially interpolating the rock mass mechanical parameters based on the adjusted interpolation weights to obtain a three-dimensional rock mass mechanical parameter model; and a design scheme generation module for determining the potential sliding surface and the spatial residual sliding force field based on the three-dimensional rock mass mechanical parameter model, and determining the slope support parameters based on the spatial residual sliding force field and the burial depth of the potential sliding surface, and generating a slope support design scheme.

[0015] The rock slope exploration and design method and device based on digital geological drilling rig provided by this invention separates the basic no-load power loss and frictional power loss along the drilling from the total drilling power, which are unrelated to rock mass fracturing. This allows the obtained effective rock breaking energy to characterize the actual resistance of the rock to drilling fracturing. At the same time, by adjusting the fluctuation weight of the drilling parameters in combination with the drilling rig control mode, the interference of mechanical adjustment fluctuations of the controlled parameters on the judgment of rock mass integrity is reduced. Furthermore, the spatial abrupt change of the effective rock breaking energy enhances the response corresponding to the actual stratum changes. Thus, drilling-while-drilling characterization quantities that can reflect rock strength and rock mass integrity respectively are obtained, reducing the influence of the drilling rig's own operating conditions and drilling depth on the rock mass mechanical parameters obtained by inversion along the borehole depth. Based on this, the direction of rock strata extension is determined by the corresponding abrupt changes in the effective rock breaking energy in multiple exploration boreholes. During spatial interpolation, the correlation between data within the same rock stratum is preserved, and the mutual influence between data from different rock strata is reduced. This expands the borehole discrete parameters to three-dimensional space while minimizing the average weakening of weak interlayers and rock strata interfaces, resulting in a three-dimensional rock mass mechanical parameter model that reflects the heterogeneous distribution of the rock mass. Furthermore, the spatial differences in shear strength within the three-dimensional rock mass mechanical parameter model are used to determine the potential sliding surface and the residual sliding force at different locations. The residual sliding force and the burial depth of the potential sliding surface are then converted into support requirements for the corresponding locations. This allows the generated slope support design scheme to configure support parameters according to the instability risk of different areas within the rock slope, reducing the possibility of insufficient or excessive support caused by using average rock mass parameters for uniform support design. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 A flowchart of a rock slope investigation and design method based on a digital geological drilling rig is shown. Figure 2 This is a flowchart illustrating how the total drilling power is determined based on drilling parameters, and the power loss due to friction along the drilling path is deducted to obtain the effective rock-breaking energy. Figure 3 This is a flowchart illustrating an example of the present invention, which describes how to adjust the fluctuation weights of various drilling parameters based on the spatial abrupt changes in the drilling rig control mode and the effective rock breaking energy to obtain the drilling dispersion index. Figure 4 This is a flowchart illustrating an example of the present invention for determining rock mass mechanical parameters distributed along the borehole depth based on effective rock breaking specific energy and drilling dispersion index; Figure 5 This is a flowchart illustrating an example of the present invention of spatial interpolation of rock mass mechanical parameters based on adjusted interpolation weights to obtain a three-dimensional rock mass mechanical parameter model; Figure 6 This is a structural block diagram of the rock slope exploration and design device based on a digital geological drilling rig according to the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0019] The embodiments of the present invention provide a rock slope exploration and design method based on a digital geological drilling rig.

[0020] Figure 1 A flowchart of a rock slope exploration and design method based on a digital geological drilling rig is shown.

[0021] like Figure 1 As shown, the method includes operations S110~S160.

[0022] The S110 is used to acquire drilling parameters collected by the digital geological drilling rig during the drilling of multiple exploration holes.

[0023] Drilling parameters are parameters collected while the drill bit is drilling into the rock mass, reflecting the working status of the drilling rig and the interaction between the drill bit and the rock mass. Drilling parameters can include feed thrust, rotational torque, drill bit speed, and drilling rate.

[0024] According to an embodiment of the present invention, multiple exploration boreholes can be laid out based on the topographic conditions and preliminary geological data of the rock slope to be analyzed, and a digital geological drilling rig can be controlled to drill sequentially at each exploration borehole location and collect drilling parameters.

[0025] When operating S120, the total drilling power is determined based on the drilling parameters, and the power loss due to friction along the drilling path is deducted to obtain the effective rock breaking energy.

[0026] Effective rock-breaking energy is used to characterize the actual energy consumed in breaking a unit volume of rock. Because it eliminates the influence of drill pipe-hole wall friction that varies with drilling depth, effective rock-breaking energy can more accurately reflect the degree of resistance of the rock at the current hole depth to drilling breaking action compared to total drilling power.

[0027] According to an embodiment of the present invention, the axial power of the drilling rig can be determined based on the feed thrust and drilling speed, and the rotary power of the drilling rig can be determined based on the slewing torque and drill bit speed. The axial power and the rotary power are combined to obtain the total drilling power.

[0028] Further, the frictional power loss between the drill pipe and the borehole wall is determined based on the current drilling depth, and this loss is subtracted from the total drilling power to obtain the actual rock-breaking power acting on the bottom of the borehole. Then, the rock-breaking power is converted based on the volume of rock broken by the drill bit per unit time to obtain the effective rock-breaking specific energy.

[0029] When operating S130, the fluctuation weights of each drilling parameter are adjusted according to the drilling rig control mode and the spatial abrupt change of the effective rock breaking energy to obtain the drilling dispersion index.

[0030] According to an embodiment of the present invention, each drilling parameter can be read sequentially according to a preset depth window, and the change of effective rock breaking energy along the hole depth direction can be analyzed to identify the spatial abrupt change position between adjacent depth windows, so as to determine the section where the lithology or structure changes.

[0031] Subsequently, the control mode currently used by the digital geological drilling rig is identified, and the fluctuation weight of the drilling parameters actively adjusted by the drilling rig control system is reduced. For example, when a certain drilling parameter is maintained within a preset range by the control system, the change in this drilling parameter originates more from the control process and cannot be directly used to characterize the rock mass condition, thus reducing the impact of this drilling parameter on the overall results.

[0032] Simultaneously, the variation of effective rock-breaking ratio along the borehole depth is analyzed. When the effective rock-breaking ratio undergoes a significant abrupt change within the current depth window, it indicates that the drill bit may have entered a region of lithological change, weak interlayers, or fractured areas. In this case, the fluctuation weight corresponding to the drilling parameters that reflect the passive response of the rock mass is increased.

[0033] Finally, the fluctuation levels of each drilling parameter are synthesized based on the adjusted fluctuation weights to obtain the drilling dispersion index. This reduces the interference of the active control process of the drilling rig on the drilling fluctuation analysis and makes the drilling dispersion index more accurately reflect the integrity and structural changes of the rock mass.

[0034] When operating S140, the rock mechanics parameters distributed along the borehole depth are determined based on the effective rock breaking energy and the drilling dispersion index.

[0035] According to embodiments of the present invention, the rock strength characteristics and rock mass integrity characteristics at each hole depth can be determined based on the exploration hole location and drilling depth corresponding to each effective rock breaking energy and drilling dispersion index.

[0036] In one example, the uniaxial compressive strength of the rock at each borehole depth can be determined using a pre-established mapping relationship between effective rock breaking energy and rock strength; the geological strength index of the rock mass at each borehole depth can be determined using a mapping relationship between the drilling dispersion index and the rock mass integrity index. Then, based on the uniaxial compressive strength and the geological strength index of the rock mass, the corresponding rock mass compressive strength, rock mass cohesion, internal friction angle, and deformation modulus, etc., are calculated using rock mass strength criteria.

[0037] By sequentially performing the above processing on each sampling depth, the rock mechanics parameters of each exploration borehole, distributed continuously or discretely along the borehole depth direction, can be obtained. This step converts the drilling parameters collected during drilling operations into engineering parameters that can be directly used for slope stability analysis and support design.

[0038] In operation S150, the rock strata attitude is determined based on the corresponding abrupt change locations of the effective rock breaking energy in multiple exploration holes. The interpolation weights of the known data points are adjusted based on the rock strata attitude and the effective rock breaking energy of the known data points. Based on the adjusted interpolation weights, the rock mass mechanical parameters are spatially interpolated to obtain a three-dimensional rock mass mechanical parameter model.

[0039] According to embodiments of the present invention, the locations where the effective rock-breaking energy abruptly changes along the depth direction in each exploration borehole can be detected, and the variation characteristics of the effective rock-breaking energy on both sides above and below each abrupt change location in different exploration boreholes can be compared. The abrupt change locations with corresponding variation characteristics are associated as control points of the same rock stratum interface in different exploration boreholes, and the spatial extension direction and dip state of the rock stratum are determined based on the spatial coordinates of multiple control points to obtain the rock stratum attitude.

[0040] When determining the rock mechanics parameters of the node to be interpolated, the basic interpolation weights are first determined based on the spatial relationship between the node to be interpolated and each known data point. Then, the bedding or cross-bedding relationship of each known data point relative to the node to be interpolated is determined based on the stratum attitude, and the effective rock breaking energy of the known data points is compared with the effective rock breaking energy characteristics of the strata corresponding to the node to be interpolated. When a known data point and the node to be interpolated have similar stratum properties, the corresponding basic interpolation weights are retained; when the difference in effective rock breaking energy indicates that they may be located in different strata, the interpolation weight of the known data point is reduced.

[0041] Based on the adjusted interpolation weights, spatial interpolation is performed on the rock mass mechanics parameters with known spatial coordinates in each exploration borehole to obtain the rock mass mechanics parameters corresponding to each spatial node between boreholes. The positions of each spatial node are combined with the corresponding rock mass mechanics parameters to form a three-dimensional rock mass mechanics parameter model.

[0042] Through the above processing, the rock mechanics parameters can be transmitted mainly along the extension direction of the same rock stratum, and the mutual influence of different rock stratum data on the interpolation results can be reduced. Thus, while expanding the borehole data to three-dimensional space, the spatial differences of rock stratum interfaces and weak areas can be preserved.

[0043] In operation S160, the potential sliding surface and the remaining spatial sliding force field are determined based on the three-dimensional rock mechanics parameter model. The slope support parameters are then determined based on the remaining spatial sliding force field and the burial depth of the potential sliding surface, and a slope support design scheme is generated.

[0044] According to embodiments of the present invention, rock mechanics parameters related to the shear capacity of the rock mass can be extracted from a three-dimensional rock mechanics parameter model, and the variations of these parameters in three-dimensional space can be analyzed. Regions with low shear capacity and continuous spatial distribution are identified as potential sliding regions, and potential sliding surfaces are obtained by fitting spatial nodes within these potential sliding regions.

[0045] After obtaining the potential sliding surface, slope stability calculations are performed based on the spatial morphology of the potential sliding surface, the rock mechanics parameters corresponding to each location on the potential sliding surface, and the gravity effect of the potential sliding body. The sliding force and resisting force at different locations on the potential sliding surface are determined, and a spatial residual sliding force field is formed based on the difference between the sliding force and the resisting force. The spatial residual sliding force field is used to characterize the sliding force that still needs to be borne by the support structure at different locations on the potential sliding surface.

[0046] Subsequently, the remaining sliding force field in space is mapped to each support area on the slope surface, and the required support capacity is determined according to the magnitude of the remaining sliding force corresponding to each support area. The required working depth of the support components is determined according to the burial depth of the potential sliding surface in each support area, thereby determining the slope support parameters such as anchor length, layout density, prestressing or slope protection parameters.

[0047] Finally, based on the location of each support area and the corresponding slope support parameters, the layout and parameter configuration of the support components are determined, generating a slope support design scheme. Thus, the drilling parameters from each exploration borehole are sequentially transformed into rock mechanics parameters, a three-dimensional rock mechanics parameter model, potential sliding surfaces, and spatial support requirements, ultimately forming the slope support design result.

[0048] In one illustrative embodiment, the drilling parameters include the feed thrust, slewing torque, drill bit speed, and drilling rate of the geological drilling rig.

[0049] Figure 2 This is a flowchart illustrating how the total drilling power is determined based on drilling parameters, and the power loss due to friction along the drilling path is deducted to obtain the effective rock-breaking energy.

[0050] like Figure 2 As shown, operation S120 includes operations S210~S240.

[0051] When operating S210, the total drilling power is determined based on the feed thrust, slewing torque, drill bit speed, and drilling speed.

[0052] According to embodiments of the present invention, the real-time feed thrust, slewing torque, drill bit speed and drilling speed of a digital geological drilling rig at the current drilling depth can be obtained, and the total drilling power applied by the drilling rig to the drill bit and drill rod system can be calculated.

[0053] During normal drilling operations, the drilling parameters, including feed thrust, are collected in real time by the drilling monitoring system of the digital geological drilling rig. F (Unit: kN) Rotational torque T (Unit: kN) m), drill bit speed N (Unit: r / min) and drilling speed V(Unit: m / s); Calculate the total drilling power applied to the drill string by the drilling rig's hydraulic system. P total The calculation formula is:

[0054] When operating S220, the basic no-load power loss is determined based on the no-load feed thrust and no-load rotation torque when the drill bit is not in contact with the rock mass.

[0055] According to embodiments of the present invention, the no-load feed thrust and no-load rotation torque of a digital geological drilling rig when it is not in contact with the rock mass can be obtained, and the basic no-load power loss for overcoming sliding friction of the feed mechanism, internal mechanical resistance, and fluid viscous resistance can be calculated. With the drill bit suspended in the rock mass at the bottom of the hole, the digital geological drilling rig is subjected to a no-load operation test, and the no-load feed thrust at this time is collected. F 0 and no-load rotational torque T 0. Calculate the basic no-load power loss to overcome the friction of the feed mechanism and the viscous resistance of the system. P base :

[0056] During operation S230, the frictional power loss along the drilling path is determined based on the drilling depth and the pre-established depth-friction relationship.

[0057] According to an embodiment of the present invention, the frictional power loss along the drilling path can be calculated using a pre-established dynamic frictional attenuation model that includes the effects of borehole wall frictional resistance and drill pipe gravity. Specifically: With drilling depth L As the depth increases, the contact area between the drill pipe and the borehole wall also increases. A friction loss model along the drilling path is constructed to calculate the current depth in real time. L Additional friction feeds thrust With additional frictional rotational torque Calculate the frictional power loss along the path due to increased depth. P fric :

[0058] In one example, additional friction provides thrust. With additional frictional rotational torque The depth-friction empirical coefficient can be obtained through dynamic interpolation using depth-friction empirical curves measured under drilling or non-cutting hole cleaning conditions. By determining the depth-friction relationship curves pre-determined under drilling or hole cleaning conditions, and then measuring the frictional force and frictional torque generated between the drill rod and the hole wall at different depths under non-drilling cutting conditions, and connecting these measured data points to form a curve, the coefficient can be fitted. F f (L )and T f ( L The functional relationship between ).

[0059] When operating S240, the effective net power is determined based on the total drilling power, the power loss of the foundation under no-load and the power loss of friction along the drilling path, and the effective rock breaking specific energy is determined based on the effective net power and the rock breaking volume per unit time.

[0060] According to an embodiment of the present invention, the effective net power for bottom rock breaking is obtained by subtracting the base no-load power loss and frictional power loss from the total drilling power; the effective net power is then divided by the product of the drill bit's rock-breaking cross-sectional area and the drilling speed to obtain the effective rock-breaking specific energy corresponding to the rock breaking per unit volume. For example, the total work power... P total Subtract the base no-load power loss in sequence P base Power loss due to friction along the path P fric To obtain the effective net power used solely for cutting and crushing rock at the bottom of the hole; divide the effective net power by the rock-breaking volume rate of the drill bit per unit time (i.e., the cross-sectional area of ​​the drill bit). A With drilling speed V The product of these factors yields the effective rock-breaking energy consumed per unit volume of rock mass. SE eff :

[0061] In the formula, F , T , N , V These are the real-time data collected: feed thrust, slewing torque, drill bit speed, and drilling speed. F 0 and T 0 represents the no-load thrust and torque at the same rotational speed and feed rate when the drill bit is suspended in the air. F f ( L )and T f ( L ) is based on depth L Additional frictional thrust and torque obtained by interpolation from a pre-determined depth-friction curve; A This represents the cross-sectional area of ​​the drill bit.

[0062] Understandably, in traditional drilling parameter analysis techniques, rock strength is typically assessed directly using the hydraulic output power of the drilling rig or the apparent feed thrust and rotation torque. However, through long-term engineering practice, the inventors have discovered that digital geological drilling rigs experience significant non-rock-breaking energy dissipation when applying drilling energy. This energy dissipation primarily stems from three aspects: sliding friction of the feed mechanism (mechanical friction generated when the drill head moves up and down along the mast), internal impedance of the rotation system (internal dissipation caused by gearbox meshing and hydraulic fluid viscosity), and friction between the drill rod and the borehole wall (the dynamic friction between the drill rod and the borehole wall increases linearly or non-linearly with increasing drilling depth due to the drill rod's own weight and skew). If apparent drilling energy consumption is directly used for rock strength inversion, the aforementioned mechanical and frictional losses will be incorrectly attributed to the rock's resistance to breakage, resulting in a severely overestimated rock strength and distortion with increasing borehole depth. Therefore, this invention proposes an effective rock-breaking specific energy extraction method that removes mechanical losses from total work performed. SE eff The first term of the formula represents the effective axial compression rock-breaking energy, and the second term represents the effective tangential shear rock-breaking energy. This aims to filter out mechanical and frictional noise, obtaining pure, true rock-breaking energy at the bottom of the borehole, thus laying the data foundation for the subsequent accurate inversion of the Hoek-Brown criterion. This step completely eliminates the depth effect commonly found in traditional logging-while-drilling (i.e., the phenomenon of a false increase in predicted intensity with increasing borehole depth), giving the inversion parameters genuine physical and mechanical meaning.

[0063] Figure 3 This is a flowchart illustrating an example of the present invention, which describes how to adjust the fluctuation weights of various drilling parameters based on the drilling rig control mode and the spatial abrupt change in effective rock breaking energy to obtain the drilling dispersion index.

[0064] like Figure 3 As shown, operation S130 includes operations S310~S340.

[0065] In operation S310, determine the coefficient of variation of each drilling parameter within the preset depth window.

[0066] According to an embodiment of the present invention, the coefficients of variation of the feed thrust, slewing torque, drill bit rotation speed, and drilling speed within a preset depth window are calculated. CV i And assign the same initial base weight to each coefficient of variation. w i0 For example, since this embodiment simultaneously collects four parameters—feed thrust, slewing torque, drill bit speed, and drilling speed—in a preferred embodiment, the initial basic weights of each parameter are determined as follows: w i0All values ​​are assigned an equal value of 0.25. For example, the preset depth window is typically the depth of a single drilling pass.

[0067] When operating S320, the fluctuation weight corresponding to the controlled drilling parameters is reduced according to the drilling rig control mode.

[0068] Identify the drilling rig control mode and assign a suppressive working condition weighting coefficient to the controlled active quantity under constant pressure or constant speed mode. P i In constant pressure drilling mode, the coefficients of variation of feed thrust and drill bit speed are assigned a working condition weighting factor of less than 1, while the coefficients of other uncontrolled parameters remain at 1; in constant speed drilling mode, the coefficients of variation of drilling speed and drill bit speed are assigned a working condition weighting factor of less than 1, while the coefficients of other uncontrolled parameters remain at 1.

[0069] In operation S330, the adjusted fluctuation weights are normalized, and the coefficients of variation are weighted according to the normalized fluctuation weights to obtain the drilling dispersion index.

[0070] According to an embodiment of the present invention, the spatial gradient abrupt change rate of effective rock-breaking specific energy within a depth window can be extracted. If the abrupt change rate is greater than a preset threshold, a geological feature weighting coefficient that enhances the passive response of the formation is assigned to the uncontrolled parameter characterizing the formation. η i ; Will w i0 , P i and η i The final fluctuation weight is determined after normalizing the product. ,pass The drilling dispersion index is obtained.

[0071] It is understandable that in actual engineering exploration, simply using the statistical coefficient of variation to assess rock mass fragmentation is highly susceptible to severe interference from internal hydraulic vibrations (mechanical noise) or manual unsteady pushing and pulling (operational noise). Therefore, this invention proposes a dynamic synthetic weighted model with engineering applicability: In this embodiment, the specific meanings of each coefficient in the model are as follows: Working condition weighting factor P i When a drilling rig forcibly stabilizes the controlled parameters through its internal PID control loop, the minute fluctuations are mechanical vibrations and do not indicate formation characteristics. Because the rotation system of mainstream digital drilling rigs is typically independently controlled, the drill bit speed... N It is treated as a controlled active variable under all operating conditions, therefore the system constantly reduces the weighting coefficient of the operating condition corresponding to the speed. P NAdjust to between 0.05 and 0.1 (preferably 0.1). Other parameters are dynamically adjusted according to the control mode: (a) When the digital geological drilling rig is in constant pressure drilling mode, the feed thrust F This is a controlled active variable. The weighting factor corresponding to the feed thrust is used to reduce the load. P F The value is lowered to between 0.05 and 0.1 (preferably 0.1) to reduce its weight in the composite calculation; while the gyratory torque, as a passive response quantity of the formation, is... T and drilling speed V Its coefficient P T , P V All remain at the baseline value of 1.0.

[0072] (b) Drilling speed when the digital geological drilling rig is in constant speed drilling mode V This is a controlled active variable. The weighting factor corresponding to the drilling speed is used... P V The value is lowered to between 0.05 and 0.1 (preferably 0.1) to reduce its weight in the composite calculation; while the feed thrust, as a passive response quantity of the formation, is... F and rotational torque T Its coefficient P F , P T All remain at the baseline value of 1.0.

[0073] Geological feature weighting coefficient η i If abnormal pushing or pulling by humans causes drastic fluctuations in parameters, the effective rock-breaking specific energy will decrease because the work done changes synchronously with the rock-breaking volume. SE eff It will remain relatively stable; when encountering real rock mass joints or fracture zones, the effective rock breaking energy will remain relatively stable. SE eff This will result in a dramatic drop in spatial gradient. Digital geological drilling rigs monitor effective rock-breaking energy in real time. SE eff The spatial gradient mutation rate was determined, and a baseline geological mutation threshold was set. S 0, S 0 can preferably be within a preset window above the current drilling depth. SE eff 15%~20% of the spatial moving average: (a) when SE eff mutation rate < S At time 0, it is determined that the fluctuation did not penetrate a significant geological interface or was caused by human activity; at this time, all parameters... ηi All values ​​are set to the baseline value of 1.0.

[0074] (b) When SE eff mutation rate ≥ S At time 0, it is determined that the drill bit is cutting a real weak or fractured structural surface. At this time, the drilling rig will use the passive response parameters under the current model (e.g., the rotational torque in constant pressure mode). T and drilling speed V Rotational torque in constant speed mode T and feed thrust F Geological feature weighting coefficients η Scale up to between 1.5 and 3.0 (preferably 2.0) to achieve the final synthesized fluctuation weight. w i At that time, it accurately and greatly amplifies the characterization signals of real geological defects.

[0075] Normalized fluctuation weights are Using the weighted summation formula The drilling dispersion index, excluding mechanical and operational disturbances, can be obtained through calculation. DI .

[0076] Figure 4 This is a flowchart illustrating an example of the present invention for determining rock mechanics parameters distributed along the borehole depth based on effective rock breaking energy and drilling dispersion index.

[0077] like Figure 4 As shown, operation S140 includes operations S410 to S430.

[0078] When operating S410, the uniaxial compressive strength of the rock distributed along the borehole depth is determined based on the effective rock breaking specific energy.

[0079] According to embodiments of the present invention, an effective rock-breaking specific energy and the uniaxial compressive strength of rock can be established. σ c The linear mapping relationship is used to calculate the uniaxial compressive strength of rock along the borehole depth direction through effective rock breaking energy calculation. σ c Effective rock-breaking energy SE eff In its physical essence, it represents the energy of a unit volume of rock resisting damage from drill bit cutting, and its dimensions are consistent with the uniaxial compressive strength of rock. This invention establishes the following linear mapping calibration model:

[0080] In the formula: σ c For the uniaxial compressive strength of rock, kThis is the drill bit cutting efficiency conversion factor. Preferably, the drill bit cutting efficiency conversion factor is... k The measured values ​​were obtained by conducting an indoor uniaxial compression test on representative rock cores obtained from digital coring drilling in step S1. σ c The value is obtained by fitting and calibrating it with the average effective rock breaking ratio of the borehole section corresponding to the test rock mass. k After the value is obtained, the digital geological drilling rig can output the inversion value of the uniaxial compressive strength of the rock, which is continuously distributed along the drilling depth direction.

[0081] When operating S420, the rock mass geological strength index distributed along the hole depth is determined based on the drilling dispersion index.

[0082] According to an embodiment of the present invention, a drilling dispersion index can be established. DI Geological strength index GSI The negative exponential mapping model between them is used to invert and obtain continuous rock geological strength indicators along the borehole depth direction. GSI In traditional geological exploration, geological intensity indicators GSI Typically, geological engineers subjectively score the rock mass by visually observing the development and weathering degree of its structural surfaces. Field experiments have shown that drilling is smoother when the rock mass is extremely intact. DI If it approaches 0, then it is calculated as follows: GSI The value tends to 100; when the rock mass has extremely well-developed joints and fractures or contains fracture zones, DI Significantly increased, calculated GSI This will exhibit exponential decay. This invention addresses this by establishing a discrete exponential type during drilling. DI and GSI The negative exponential model between these two methods achieves objective quantification of this indicator.

[0083] In the formula: a This refers to the formation attenuation characteristic coefficient. Preferably, the formation attenuation characteristic coefficient... a The measured values ​​were obtained by statistical analysis of representative core samples obtained from digital coring drilling in step S1. GSI The value is then fitted and calibrated with the average effective rock breaking ratio of the measured rock mass in that section.

[0084] In operation S430, rock mass mechanical parameters are determined based on the rock uniaxial compressive strength and rock mass geological strength index, according to the rock mass strength criterion.

[0085] For example, the perturbation factor D Set it to 0, and determine the rock material constants by referring to the table. m i Combined with the inversion obtained GSICalculate rock mass material parameters in the generalized Hoek-Brown criterion m b , s , a ;

[0086] Furthermore, the uniaxial compressive strength of the combined rock σ c Rock mass material parameters m b , s , a Substituting these values ​​into the Hoek-Brown strength criterion equation and the equivalent Mohr-Coulomb transformation equation, continuous rock mechanics parameters (including rock cohesion) along the borehole depth direction are calculated and obtained. c m Friction angle within the rock mass φ m Rock mass compressive strength σ cm Rock mass tensile strength σ tm and rock mass deformation modulus E m );

[0087] In the formula: ,in This is the upper limit of the minimum principal stress. For rock masses in slope engineering, Calculate using the following formula:

[0088] In the formula: γ The weight of the rock mass; H The slope is high; The overall strength of the jointed rock mass. When hour, It can be determined by the following formula:

[0089] In slope engineering, rock mechanics parameters are a crucial foundation for assessing slope stability. Furthermore, these parameters can be used to establish numerical models to analyze the evolution of slope displacement, stress, and plastic zones, thus providing a basis for slope support design. However, currently, obtaining rock mechanics parameters mainly relies on in-situ tests and estimation methods based on empirical strength criteria. Due to time and cost constraints, conducting numerous in-situ tests is often difficult; therefore, empirical methods for effectively estimating rock mechanics parameters are of great significance in practical engineering. The Hoek-Brown strength criterion, an empirical criterion established based on extensive experimental data, can effectively describe the nonlinear failure behavior of rock masses and has been widely used in rock mechanics analysis. This invention innovatively proposes a quantitative relationship between drilling parameters and rock mechanics parameters, enabling real-time continuous inversion of rock mechanics parameters during the drilling process of a digital geological drilling rig.

[0090] Figure 5 This is a flowchart illustrating an example of the present invention of spatial interpolation of rock mass mechanical parameters based on adjusted interpolation weights to obtain a three-dimensional rock mass mechanical parameter model.

[0091] like Figure 5 As shown, operation S150 includes operations S510 to S540.

[0092] In operation S510, the attitude of the rock strata is determined based on the corresponding abrupt change locations of the effective rock breaking energy in at least three exploration holes.

[0093] According to an embodiment of the present invention, the corresponding depth nodes in which the effective rock breaking energy of the three adjacent initial exploration holes in the neighborhood of the node to be interpolated are extracted. The statistical mean of the effective rock breaking energy of the rock segment above and below each depth node is calculated. The statistical mean between adjacent holes is compared. If the difference in the statistical mean of the upper rock segment and the difference in the statistical mean of the lower rock segment between adjacent holes are both less than the preset same-layer correlation threshold, then the corresponding depth nodes are determined to belong to the same geological interface. Their three-dimensional spatial coordinates are extracted, and the strike and dip angle of the rock strata in the local area enclosed by the three initial exploration holes are obtained by using the three-point plane algorithm.

[0094] For example, for any node to be interpolated i The system automatically matched the initial exploration boreholes ZK1, ZK2, and ZK3 in its neighborhood, and detected that ZK1 had an effective rock-breaking energy of 45 MJ / m at a depth of 15.2 m. 3 The sudden drop to 12 MJ / m 3Simultaneously, ZK2 and ZK3 experienced synchronous abrupt changes at 16.5m and 17.8m, respectively. Calculations revealed that the average specific energy difference in the rock segments above the three abrupt change points was within 5%, and the difference in the rock segments below was within 8%, both less than the preset threshold for co-strata association (e.g., 15%), indicating they belong to the same bedding plane. The coordinates of three points (x1, y1, z1), (x2, y2, z2), and (x3, y3, z3) were extracted, and the strike of the rock strata in this local area was calculated to be N45°E with a dip angle of 20°.

[0095] In operation S520, an anisotropic search neighborhood extending along the direction of the rock strata is constructed based on the rock strata attitude; the anisotropic search neighborhood is used to limit the selection range of known exploration well data points participating in spatial interpolation.

[0096] For example, with the node to be interpolated as the geometric center, an anisotropic search ellipsoid is constructed with its principal axis parallel to the strike and dip angle of the rock strata in the local area and its minor axis perpendicular to the rock strata. Only known data points falling within this anisotropic search ellipsoid are extracted for calculation. In this embodiment, known data points refer to discrete sampling points distributed along the axes of each exploration borehole, containing measured effective rock breaking energy values ​​and three-dimensional spatial coordinates. For example, with the node to be interpolated as the geometric center, an anisotropic search ellipsoid is constructed with its principal axis parallel to the strike and dip angle of the rock strata in the local area and its minor axis perpendicular to the rock strata. i Centered on a central ellipsoid, an anisotropic search ellipsoid with a triaxial ratio of 5:5:1 is constructed, and its principal axis plane (the plane formed by the major and middle axes) is adjusted to be parallel to the orientation at N45°E / 20°. The system only retrieves known borehole data points falling within this ellipsoid, such as data points on the adjacent borehole ZK1. j .

[0097] In operation S530, the node to be interpolated is projected onto the known exploration hole according to the rock stratum attitude, and the interpolation weight of the known data point is adjusted according to the difference between the effective rock breaking energy of the projected location and the effective rock breaking energy of the known data point.

[0098] For example, the node to be interpolated is projected along the dip direction onto the axis of the initial exploration borehole containing the aforementioned known exploration borehole. The value corresponding to the projected location is directly read as the reference specific energy on the effective rock-breaking energy curve continuously distributed with depth of the initial exploration borehole. For instance, the node to be interpolated... i Projecting obliquely along a 20° angle onto the axis of borehole ZK1, we obtain the projection point. i' Read directly from the continuous energy specific curve of ZK1. i' The specific energy at a depth (e.g., 16.0 m) is 13.5 MJ / m. 3 Use it as the bedding reference specific energy SE ref .

[0099] A specific adjustment method for interpolation weights is as follows: for each known data point inside an ellipsoid, first calculate its actual measured specific energy of effective rock breaking SE j and the bedding reference specific energy SE ref absolute difference , preset the same-stratum threshold T1 and the cross-stratum mutation threshold T2 (T1<T2) that can be generated based on regional exploration data, then determine the corresponding weight correction coefficient λ according to the interval where ΔSE is located: when ΔSE is not greater than T1, it is determined that the node to be interpolated and the known data point belong to the same rock stratum, λ is 1.0, and the interpolation weight has no attenuation; when ΔSE is between T1 and T2, it is determined to be in a thin layer transition zone, the correction coefficient decreases linearly with the difference according to λ=1-(ΔSE-T1) / (T2-T1); when ΔSE is not less than T2, it is determined to cross the lithology interface, weak interlayer or fault, λ is set as a fixed low weight reduction coefficient of 0.1~0.3 to weaken the interpolation contribution of this known point; on this basis, the spatial directions of the anisotropic ellipsoid are distinguished, and the basic interpolation weight w which is consistent with traditional interpolation methods such as inverse distance weight and Kriging weight 0j is coupled to obtain the final interpolation weight w j , in the principal axis plane extending along the strike and inclination of the rock stratum, w j = w 0j ·λ, which ensures smooth transition of parameters inside the same rock stratum; in the short-axis normal direction perpendicular to the rock layer plane, a normal attenuation factor η less than 1 is superimposed, and the final weight is w j =w 0j ·λ·η. The larger the rock dip angle and the greater the interlayer property difference, the smaller the value of η ( , θ is the rock dip angle, a and b are fitting coefficients), which further suppresses the interference of cross-stratum measurement points.

[0100] For example, the actual measured effective rock breaking specific energy of the known data point j is 14.1MJ / m³, the same-stratum threshold T1 is set to correspond to a relative deviation of 15%, and the cross-stratum mutation threshold T2 is set to correspond to a relative deviation of 40%. The calculated relative deviation of the specific energy at this point is about 4.4%, which is less than the same-stratum threshold, the correction coefficient λ is 1.0, and the measurement point is located in the main extension plane of the rock stratum, the normal attenuation factor η is 1, so its final interpolation weight is consistent with the basic weight, and can fully participate in the parameter calculation of the node to be interpolated; if there is another depth measurement point in the ellipsoid with a specific energy of 38MJ / m³, whose relative deviation far exceeds the cross-stratum mutation threshold, λ=0.2 is taken, and when the measurement point is in the normal direction perpendicular to the rock layer plane, η=0.4 is superimposed, the final weight is only 0.08 of the basic weight, which hardly affects the parameters of the node to be interpolated, so as to realize the parameter change at the rock stratum interface.

[0101] By adopting the above technical solution, this invention achieves intelligent anisotropic interpolation at the mathematical level. Specifically, interpolation weights are preserved along the extension direction of the rock strata dip angle, ensuring reasonable smoothing of data within the same rock stratum. However, in the normal direction perpendicular to the rock strata, if a sudden change in specific energy occurs, a smaller reduction coefficient can be used to avoid mutual influence and over-smoothing of parameters between different rock strata (especially weak interlayers and hard rock strata). This allows the final constructed three-dimensional rock mass mechanical parameter model to realistically reproduce the geometric boundaries and mechanical properties under complex inclined strata. Preferably, the preset rock strata boundary threshold is dynamically generated based on previous data.

[0102] In the S540 operation, spatial interpolation is performed on the rock mass mechanical parameters corresponding to each exploration hole according to the adjusted interpolation weights to obtain a three-dimensional rock mass mechanical parameter model.

[0103] The parameter value of the node to be interpolated is the sum of the products of the measured values ​​of the rock mechanics parameters corresponding to the aforementioned known data points and their final interpolation weights, divided by the sum of the final interpolation weights of all known data points involved in the calculation. After traversing all regular grid nodes to be interpolated within the 3D modeling area and completing the parameter calculation, a continuously distributed 3D rock mechanics parameter model is obtained. Through the above setting method, in constructing the 3D rock mechanics parameter model, it is possible to allow parameters to smoothly transition within the same rock layer, and to induce a cliff-like abrupt change in parameters when crossing weak interlayers or fault interfaces, thereby faithfully reproducing the real heterogeneous geological structure inside the slope. For example, after screening by anisotropic ellipsoids, three valid known data points were retained. The basic weights calculated based on spatial distance were 0.9, 0.8, and 0.7, respectively. After correction for same-layer properties and directional attenuation, the final interpolation weights were 0.9, 0.78, and 0.65, respectively. The measured values ​​of the uniaxial compressive strength of the rock mass at the three points were 32 MPa, 30 MPa, and 35 MPa, respectively. The weighted average calculation showed that the uniaxial compressive strength of the rock mass at node i to be interpolated was approximately 32.2 MPa.

[0104] In one illustrative embodiment, the rock slope exploration and design method based on a digital geological drilling rig further includes: determining weak and anomalous areas based on the degree of rock mass strength attenuation between adjacent exploration boreholes in the three-dimensional rock mass mechanics parameter model; extracting anomalous data points whose rock mass strength is lower than a preset strength threshold from the weak and anomalous areas, and spatially clustering these anomalous data points to obtain weak and anomalous clusters; determining the locations of additional exploration boreholes based on the spatial location of the weak and anomalous clusters; obtaining the rock mass mechanics parameters corresponding to the additional exploration boreholes, and updating the three-dimensional rock mass mechanics parameter model based on these parameters.

[0105] In traditional slope investigation, exploration boreholes are usually arranged with a fixed grid spacing. If the spacing between adjacent boreholes is too large, it is easy to miss hidden faults or weak interlayers between the boreholes. To address this, this invention proposes a denser exploration decision-making method based on the strength attenuation characteristics of the initial model, aiming to capture hidden weak zones to the maximum extent with minimal additional drilling.

[0106] For example, by analyzing the relative attenuation rate of rock compressive strength along the dip direction of rock strata in the initial three-dimensional rock mass mechanics parameter model; for the inter-hole region where the attenuation rate exceeds a preset abrupt change threshold, the corresponding elevation range where the strength abrupt change occurs is extracted, and a local three-dimensional search space is constructed in the initial three-dimensional rock mass mechanics parameter model with the inter-hole region and the elevation range as the boundary; the model data points inside the local three-dimensional search space are traversed, and model data points with compressive strength lower than a preset extreme value threshold are extracted to form an abnormal point cloud set; a spatial clustering algorithm is used to divide the abnormal point cloud set into clusters to identify single or multiple spatially independent weak anomaly clusters; for each spatially independent weak anomaly cluster, its spatial geometric centroid is extracted, and the plane projection coordinates of each spatial geometric centroid are used as a set of densified exploration borehole locations; supplementary drilling is carried out at each location of the densified exploration borehole location set, and rock mass mechanics parameters are obtained by inversion, constraining and updating the initial three-dimensional rock mass mechanics parameter model to obtain the second three-dimensional rock mass mechanics parameter model.

[0107] In one example, the relative attenuation rate of rock mass compressive strength between adjacent exploration boreholes can be analyzed along the rock stratum dip direction. If the relative attenuation rate is greater than a preset abrupt change threshold, it is determined that a hidden weak zone exists between the boreholes. Specifically, along the rock stratum dip direction obtained from S510, the rock mass compressive strength values ​​of two adjacent initial exploration boreholes at the corresponding dip extension depth can be read, and the relative attenuation rate of the rock mass compressive strength values ​​between the two boreholes can be calculated. If the relative attenuation rate is greater than a preset abrupt change threshold, it is determined that a hidden weak zone exists between the adjacent exploration boreholes. For example, the strength difference between adjacent initial exploration boreholes in the initial three-dimensional geological model of the initial rock slope is first analyzed. Unlike the traditional horizontal elevation comparison, this invention reads the rock mass compressive strength values ​​of two adjacent boreholes at the corresponding dip extension depth along the rock stratum dip direction obtained from step S3. σ cm And calculate the relative attenuation rate:

[0108] If the relative attenuation rate exceeds a preset abrupt change threshold (preferably 30%~45%), it is determined that a concealed weak zone exists between adjacent exploration boreholes. Assuming the initial exploration boreholes ZK1 and ZK2 are 20m apart, and the rock strata dip angle calculated in step S3 is 20°, data extracted along the 20° dip direction reveals that ZK1 has a compressive strength of 40MPa at an elevation of 50m, while ZK2 has a compressive strength of only 10MPa at an elevation of 42.7m in the corresponding diagonal stratum. Calculations show a relative attenuation rate as high as 75%, far exceeding the preset 40% threshold, thus indicating the presence of a concealed weak zone between the boreholes.

[0109] Then, a local 3D search space for strength abrupt changes is defined within the initial 3D rock mass mechanical parameter model. Model data points with compressive strength below a preset extreme threshold are selected to form an anomalous point cloud set. Specifically, for borehole areas where concealed weak zones are identified, the upper and lower elevation boundaries corresponding to the strength abrupt changes are extracted. Combined with the planar connection of two adjacent initial exploration boreholes, a closed local 3D search space is defined within the initial 3D geological model of the rock slope. All model data points containing 3D coordinates and strength attributes within this local 3D search space are traversed, and model data points with rock mass compressive strength below a preset extreme threshold are selected to construct an anomalous point cloud set. For example, for areas identified as anomalous, the system extracts the upper and lower elevation boundaries corresponding to the strength abrupt changes. Combined with the planar connection of adjacent initial exploration boreholes, a closed local 3D search space is defined within the model, and model data points with rock mass compressive strength below a preset extreme threshold (such as 50% of the average strength of the stratum) are selected to construct an anomalous point cloud set.

[0110] Finally, a spatial clustering algorithm is used to identify spatially independent weak anomaly clusters, and the planar projection coordinates of their spatial geometric centroids are extracted as the locations for intensified exploration boreholes. Specifically, based on the spatial Euclidean distance between model data points, a spatial clustering algorithm is used to perform cluster analysis on the anomaly point cloud set, grouping spatially connected model data points into the same cluster, thereby identifying one or more spatially independent weak anomaly clusters. For each weak anomaly cluster, the average three-dimensional spatial coordinates of all model data points within it are calculated to obtain the spatial geometric centroid representing the volume center of the cluster. Only the horizontal projection coordinates of each spatial geometric centroid are extracted, and the output constitutes the set of intensified exploration borehole locations. For example, a spatial clustering algorithm (such as the DBSCAN algorithm) is used to divide the anomaly point cloud into clusters based on spatial Euclidean distance, identifying spatially independent weak anomaly clusters. For each anomaly cluster, the system calculates the average three-dimensional spatial coordinates of all model data points within it, thereby obtaining the spatial geometric centroid representing the volume center of the cluster. Finally, only the horizontal projection coordinates of each spatial geometric centroid are extracted. X 0, Y0) As the output of the intensified exploration borehole. Within the local search space between ZK1 and ZK2, the system screened out 500 anomalous data points with compressive strength below 15 MPa. Through spatial clustering, a lenticular cluster of weak points was identified, and its geometric centroid coordinates were calculated to be (125.5, 230.8, 45.2). The system automatically locked the planar coordinates (125.5, 230.8) as the output of the intensified borehole ZK. add The specific location should be determined, rather than blindly filling in the hole at the midpoint between the two holes.

[0111] Drilling personnel based on the plane coordinates determined by the system ( X 0, Y 0) Conduct additional drilling on-site and repeatedly use digital drilling parameters to obtain continuous rock mechanics parameter values ​​for the intensified exploration borehole in real time. Re-input these inverted values ​​as hard data (measured control points) with absolute constraint weights into the model, and force the surrounding grid parameters to converge to the measured values ​​through interpolation algorithms, thereby realizing the reconstruction from the initial geological model to a high-resolution second-dimensional rock mechanics parameter model.

[0112] In one illustrative embodiment, the rock mass mechanical parameters include rock mass cohesion and internal friction angle.

[0113] The process of determining potential sliding surfaces based on a three-dimensional rock mechanics parameter model includes: The rock mass cohesion and internal friction angle in the three-dimensional rock mass mechanical parameter model are normalized respectively, and the gradient modulus of the normalized rock mass cohesion and internal friction angle in three-dimensional space is calculated. The spatial comprehensive mutation rate field is determined based on the gradient modulus corresponding to the rock mass cohesion and internal friction angle. Local maxima points in the spatial comprehensive mutation rate field are extracted to form the initial slip surface point cloud, and the initial slip surface point cloud is clustered and fitted with a spatial surface to obtain the potential slip surface.

[0114] Specifically, the cohesion and internal friction angle of the rock mass can be normalized, and their gradient modulus in three-dimensional space can be calculated to obtain the spatial comprehensive mutation rate field.

[0115] The rock mass cohesion in the second three-dimensional rock mass mechanics parameter model c m Friction angle within the rock mass φ m Normalize by both maximum and minimum values ​​to obtain the normalized parameter field. c norm and φ norm :

[0116]

[0117] Calculate the three-dimensional spatial gradient modulus of the two normalized parameter fields respectively. and :

[0118]

[0119] Then according to the preset cohesion weight w c and internal friction angle weight w φ Linear weighted fusion is performed to obtain a three-dimensional spatial comprehensive mutation rate field. ,in ,and It is understandable that, in weak interlayers and fractured rock zones, the loss of cohesion is often more severe than the attenuation of the internal friction angle and is more sensitive to early sliding. Therefore, this embodiment sets... w c The value range is 0.6 to 0.8. w φ The value range is 0.2 to 0.4 (for example, taking...). w c = 0.7, w φ = 0.3).

[0120] Finally, the local maxima point cloud of the spatial comprehensive mutation rate is extracted to form the initial sliding surface point cloud. This point cloud is then used for clustering and 3D spatial surface fitting to generate a set of potential sliding surfaces. Preferably, in the 3D spatial comprehensive mutation rate field, spatial data points whose mutation rate values ​​reach local maxima are extracted to form the initial sliding surface point cloud. A spatial clustering algorithm is used to divide the initial sliding surface point cloud into clusters, grouping spatially continuous data points into the same feature cluster. This identifies and separates one or more spatially independent sliding surface feature clusters. For each independent sliding surface feature cluster, a 3D spatial surface fitting algorithm is used to reconstruct its continuous geometric shape, outputting a set of potential sliding surfaces containing one or more independent spatial surfaces.

[0121] In one illustrative embodiment, the process of determining the potential sliding surface and the remaining spatial sliding force field based on a three-dimensional rock mass mechanics parameter model includes: Based on the spatial morphology of the potential sliding surface and the corresponding rock mechanics parameters, slope stability analysis is performed to obtain the spatial residual sliding force field.

[0122] According to an embodiment of the present invention, the three-dimensional stability coefficient and the spatial residual sliding force field of the slope are calculated using the three-dimensional limit equilibrium method. Preferably, the three-dimensional geometric morphology of each independent potential sliding surface generated in the aforementioned steps and the rock mass shear strength parameters (cohesion and internal friction angle) of the model data points distributed on it are extracted, and imported into a three-dimensional limit equilibrium algorithm (such as the GIS-based three-dimensional Spencer method or the Morgenstern-Price method) to calculate the overall three-dimensional stability coefficient of the slope and solve the spatial residual sliding force field applied to each surface of the potential sliding surface. In this process, the engineering design concept of prioritizing shallow unloading is introduced: a relative burial depth threshold (e.g., 5 meters) and a local sliding force threshold are set. When it is determined that the relative burial depth of the sliding surface in a certain area is less than the relative burial depth threshold and the residual sliding force is greater than the local sliding force threshold (because blindly installing high-strength anchors in this area would lead to extremely high costs and low cost-effectiveness), slope reduction calculation is directly performed. On the three-dimensional rock mass mechanics parameter model, the shallow high-risk area is subjected to top reduction or slope rate adjustment to update the slope surface morphology, and the spatial residual sliding force field is updated synchronously based on the new terrain.

[0123] The remaining sliding force field in space is mapped onto multiple support nodes on the slope surface.

[0124] The anchor length and anchor hole density are determined based on the remaining sliding force and potential sliding surface burial depth corresponding to each support node, thus obtaining the slope support parameters.

[0125] According to an embodiment of the present invention, the remaining sliding force field is mapped to the hole nodes on the slope, and the design length of the anchor and the hole density pattern are adaptively determined by combining the relative burial depth of the potential sliding surface at the node. Preferably, an initial slope hole array is established on the slope design surface. Each hole node of the slope hole array is projected onto the corresponding potential sliding surface along the vertical slope direction. The relative burial depth of the potential sliding surface at each hole node is extracted, and combined with the spatial control area of ​​the hole node, the remaining sliding force equivalent that the node needs to bear is calculated. Using a preset slope step or elevation zone as a design unit, the maximum relative burial depth of all hole nodes in the unit is extracted and used as the safe penetration baseline length of the unit. The safe penetration baseline length is added to the preset effective anchorage section length and rounded up to the preset standard anchor length specification as the unified design anchor length of the design unit. The remaining sliding force equivalent at each hole node is used as the support resistance requirement of the node. The over-limit hole node area where the support resistance requirement is greater than the design pull-out resistance of a single anchor is identified. A spatial interpolation algorithm is used to adaptively add densified holes in the initial array gaps of the over-limit hole node area until the support resistance requirements of all nodes in the area are met, and the final differentiated anchor hole pattern is output.

[0126] It should be noted that traditional slope design is often based on two-dimensional profiles, employing a uniform slope ratio and evenly distributed anchor bolts. This crude design either leads to a large amount of unnecessary earthwork excavation or causes a significant waste of support materials. In this embodiment, the three-dimensional limit equilibrium method is used to verify the overall stability of the slope. Unlike the traditional two-dimensional slice method, this embodiment discretizes the sliding surface into several vertical spatial columnar elements. It is particularly important to point out that the core advantage of this invention lies not in improving the mechanical equilibrium equations of the three-dimensional limit equilibrium method itself, but in providing it with three-dimensional model input parameters with extremely high fidelity. In conventional calculations, the shear strength parameter at the bottom of the sliding surface is often simplified to an average value; however, in this invention, the rock mass cohesion of the grid node where the bottom surface of each spatial column is located is accurately extracted. c m Friction angle with rock mass φ m (This parameter has been obtained through in-situ drilling and dynamic interpolation). By directly substituting these spatially non-uniformly distributed shear strength parameters into the matrix equations of the three-dimensional limit equilibrium method (such as the 3D Spencer method or the 3D Morgenstern-Price method), and iteratively solving the force balance between the columns, the three-dimensional overall safety factor and the three-dimensional residual sliding force distribution that accurately reflect the heterogeneity of the rock mass are finally obtained.

[0127] In this embodiment, for each independent potential sliding surface in the potential sliding surface set, its three-dimensional geometric shape and the rock mass shear strength parameters of the model data points distributed on it are extracted. The three-dimensional stability coefficient and spatial residual sliding force field of the slope are calculated using the three-dimensional limit equilibrium method. Shallow high-risk areas with a relative burial depth less than a preset depth threshold and a local residual sliding force greater than a preset sliding force threshold are extracted. For these areas, slope cutting and sloping are performed to update the slope surface morphology, and the spatial residual sliding force field is updated simultaneously. For the spatial residual sliding force field that still exists after slope cutting, the design length and hole density of the anchor bolts are adaptively and differentially calculated based on the local relative burial depth of the potential sliding surface and the distribution value of the residual sliding force at the node, and finally, the rock slope investigation and design scheme is output.

[0128] In this invention, for areas where potential instability risks remain after slope trimming, an adaptive differentiated design stage for anchor bolts is initiated. This process abandons the traditional manual "one-size-fits-all" uniform distribution design mode and specifically includes the following three aspects: I. Slope Hole Array Mapping and Resistance Equivalent Conversion. An initial slope hole array is established on the updated slope design surface (e.g., a matrix network with initial horizontal and vertical spacing of 2m × 2m). Then, each hole node in the array is projected downwards onto its corresponding potential sliding surface along a direction perpendicular to the slope. To convert the continuous sliding surface thrust into discrete anchor bolt forces, the principle of area equivalence is used: the relative burial depth of the potential sliding surface at each hole node is extracted, and combined with the corresponding spatial control area of ​​the hole node (for a 2m × 2m array, the single-hole spatial control area is 4 square meters), the integral of the sliding force on the corresponding sliding surface is extracted as the "residual sliding force equivalent" that the hole node must bear, thus achieving accurate mapping of macroscopic sliding force to microscopic support nodes.

[0129] II. Adaptive Merging of Anchor Bolt Lengths. In practical engineering, the anchor bolt lengths for single-stage slope steps are usually required to remain uniform to facilitate material preparation and construction. A pre-defined slope step (e.g., the first step at an elevation of 100m to 110m) is used as an independent design unit. All hole nodes within this unit are traversed, and the maximum relative burial depth (e.g., 7.3 meters) is extracted. This is used as the safe penetration baseline length for that step, ensuring that every anchor bolt on that step can penetrate the deepest sliding surface. Subsequently, this safe penetration baseline length (7.3 meters) is added to the pre-defined effective anchoring section length (e.g., 4 meters, penetrating deep into stable rock mass), resulting in a theoretically calculated length of 11.3 meters. To comply with engineering material processing specifications, the length is rounded up and merged with the pre-defined standard anchor bolt length specifications (e.g., rounded up to 12 meters using a 3-meter module), ultimately outputting a uniform design anchor bolt length of 12 meters for that step. This approach balances geological safety under extreme conditions with the standardization requirements of on-site construction.

[0130] III. Resistance-Driven Anchor Densification. The remaining sliding force equivalent of each anchor node calculated in the previous steps is used as the support resistance requirement at that location. The support resistance requirement is compared with the ultimate pull-out force of a single designed anchor bolt (e.g., a single bolt provides 200kN of resistance). If it is identified that the support resistance requirement of the anchor nodes in a certain local area exceeds the limit (e.g., due to severe geological conditions, the requirement is as high as 350kN, exceeding the limit of a single anchor bolt), then densified anchor holes are adaptively added to the original 2m×2m initial array gap (e.g., at the intersection of diagonal lines in a quincunx pattern). The addition of densified anchor holes will redistribute and distribute the spatial control area of ​​the region, thereby reducing the resistance requirement of each node until the resistance requirement of all nodes in the region drops below the safety threshold (200kN), ultimately outputting a differentiated anchor bolt layout.

[0131] Through the adaptive calculation of support using the above-described methods, the final output rock slope design scheme can achieve "long anchors for deep sections, slope reduction and load reduction for shallow sections; denser hole locations for high stress, and sparser hole locations for low stress." Compared to the traditional design scheme with equal length and spacing across the entire slope, the differentiated support pattern output by this method can allocate support materials most efficiently while ensuring the overall three-dimensional stability of the slope, thereby saving engineering costs to the greatest extent.

[0132] In one illustrative embodiment, the process of determining the anchor bolt length based on the potential sliding surface burial depth corresponding to each support node, and determining the anchor bolt hole density based on the remaining sliding force corresponding to each support node, includes: According to the preset slope zoning, determine the maximum potential sliding surface depth of each support node in each preset slope zoning. Based on the maximum potential sliding surface depth and the preset effective anchoring section length, determine the theoretical anchor length of the corresponding preset slope zoning. Then, merge the theoretical anchor length upwards to the preset standard anchor length to obtain the anchor length of the corresponding preset slope zoning.

[0133] The remaining sliding force within the spatial control range corresponding to each support node is determined as the support resistance requirement of the corresponding support node, and the support resistance requirement is compared with the design resistance of a single anchor bolt.

[0134] In areas where the support resistance requirement exceeds the design resistance, additional support nodes are added. The spatial control range is then redefined and the support resistance requirement is determined based on the added support nodes, until the support resistance requirement corresponding to each support node is no greater than the design resistance, in order to determine the anchor bolt hole density.

[0135] Specifically, if the overall safety factor of the slope does not meet the requirements and the average strength of the sliding zone is lower than the extreme limit of soft rock, the local slope rate is reduced. Preferably, if the overall safety factor of the slope does not meet the preset safety threshold, a three-dimensional sliding zone where plastic strain occurs is extracted in the three-dimensional plastic strain field; the average rock mass compressive strength in the area where the three-dimensional sliding zone is located is calculated; if the average rock mass compressive strength is lower than the preset extreme limit of soft rock, it is determined that the current geological conditions are insufficient to provide effective anchoring reaction force, and the local slope rate is reduced. If the slope crest displacement exceeds the limit, the hole density or prestress of the anchor bolt clusters penetrating the shallow dominant sliding surface is increased. Preferably, if the maximum slope crest displacement does not meet the preset safety threshold and the overall safety factor meets the requirements, a three-dimensional envelope surface with a displacement gradient exceeding the preset threshold is extracted from the nodal displacement field as the shallow dominant sliding surface; for the target anchor bolt clusters whose spatial trajectories penetrate the shallow dominant sliding surface, the hole density of the target anchor bolt clusters is increased or its prestress design value is increased; If the axial force of the anchor bolt exceeds the limit, the boundary of the hard rock layer is searched along the axis of the failed anchor bolt, and the design depth of the anchoring section is dynamically extended. Preferably, if the extracted axial force of the anchor bolt exceeds the ultimate pull-out bearing capacity of a single anchor bolt, the three-dimensional spatial coordinates of the anchor bolt that has failed in pull-out are extracted; the second rock slope geological model is called, and a one-dimensional spatial data search is performed along the deep axis of the failed anchor bolt to locate the boundary of the hard rock layer where the shear strength parameter of the rock mass changes abruptly; the design depth of the anchoring section of the failed anchor bolt is dynamically extended until it penetrates the boundary of the hard rock layer and meets the preset rock-embedded anchoring length.

[0136] Furthermore, to address the issue of unanchorable soft rock, an overall stability correction rule is employed. If the calculation reveals that the overall safety factor of the slope is only 1.05 (below the threshold of 1.20), a three-dimensional sliding zone where plastic strain has occurred is extracted from the model. In this case, the system calculates the average compressive strength of the rock mass in the area where the sliding zone is located. Assuming this is strongly weathered mudstone with an average compressive strength of only 5 MPa, below the preset extreme limit for soft rock (e.g., 10 MPa), even increasing the number of anchor bolts in such extremely soft rock or soil-like rock masses is ineffective because the weak rock mass itself will undergo shear failure and cannot provide effective anchoring force. Therefore, anchoring failure is determined, and the local slope ratio is adjusted from 1:0.75 to 1:1.0 or 1:1.25, using large-volume slope reduction to completely eliminate the sliding potential energy.

[0137] To address the issue of shallow surface slippage, a local deformation control correction rule is employed. If the overall safety factor meets the standard (e.g., 1.25), but the maximum displacement at the top of the slope reaches 80mm (exceeding the limit), a three-dimensional envelope surface with drastic changes in displacement gradient is extracted from the nodal displacement field (e.g., identifying a shallow dominant slip surface at a depth of 3 meters). This situation indicates that the deep slope is stable, but the surface exhibits traction-induced slippage deformation. In this case, the system maintains the predetermined slope ratio (to avoid unnecessary earthwork excavation costs). For the target anchor bolt cluster whose spatial trajectory precisely penetrates the 3-meter-deep slip surface, the hole density is increased or its prestress design value is increased. For example, the anchor bolt hole spacing of this cluster is increased from 2m×2m to 1.5m×1.5m, or its design prestress is increased from 100kN to 150kN, thereby forcibly locking the displacement of the shallow slip surface.

[0138] To address the issue of anchor failure at deep weak surfaces, a targeted tracking and correction rule for anchorage failure is employed. If calculations reveal that the axial force of a certain anchor reaches 250kN, exceeding its ultimate pull-out bearing capacity (200kN), it faces pull-out failure. In this case, the three-dimensional spatial coordinates of the failed anchor and the current design depth (e.g., 10 meters) are extracted. If the anchor is pulled out, it indicates that its anchoring section has not penetrated into a sufficiently hard rock layer. This method reverse-engineers the previous second rock slope geological model and performs a one-dimensional spatial data search along the axis of the anchor to the deeper part of the slope (below 10 meters). If a sharp positive change in the rock mass shear strength parameters (cohesion, friction angle) is detected at a depth of 13 meters (indicating entry into a slightly weathered hard rock layer), the system dynamically extends the design depth of the anchor from 10 meters to 16 meters (13-meter boundary + 3-meter embedment length). This mechanism achieves targeted optimization of a single anchor in complex three-dimensional geological bodies.

[0139] After each execution of the above correction rules (overall stability correction, local deformation control correction, or anchorage failure targeted tracking correction), the system will automatically reconstruct the numerical model using the updated local slope ratio or support parameters, and re-solve the problem using finite difference or finite element mechanics. This iterative process will continue until the overall slope safety factor, maximum displacement at the top of the slope, and anchor pull-out bearing capacity all meet the preset safety thresholds, at which point the iteration will automatically terminate and the final rock slope investigation and design scheme will be output.

[0140] The beneficial effects of this step are: it abandons the extensive mode of "experience trial and error + global uniform margin" in traditional slope design, and realizes differentiated targeted support of "long anchors in deep areas, slope cutting and load reduction in shallow areas; dense hole positions in areas with high stress, and sparse hole positions in areas with low stress". Under the premise of ensuring the absolute safety of the slope throughout its entire life cycle, it avoids ineffective support and excessive excavation to the greatest extent, and achieves the optimization of engineering economy.

[0141] In constructing and dynamically updating a three-dimensional rock mass mechanics parameter model, this invention creatively employs rock mass mechanics parameters that match the physical mechanisms of different geological design stages and algorithmic actions. Its core logic is as follows: When establishing the initial model and calculating interpolation weights, the primary problem the system addresses is accurately identifying stratigraphic lithological boundaries (i.e., inter-strata barriers). This invention utilizes effective rock-breaking specific energy obtained from drilling measurements (…). SE eff The core indicator is the effective rock-breaking energy. Its mechanical basis lies in the fact that effective rock-breaking energy is a direct physical mapping of the mechanical work done by the drilling rig in cutting rock, and it is extremely sensitive to the mineral hardness, density, and micro-cementation state of the rock. Compared to macroscopic strength parameters obtained through multiple inversion steps, rock-breaking energy data can capture the physical abrupt changes at the interface between soft and hard rock layers with high resolution. Therefore, utilizing... SE effConstructing anisotropic search neighborhoods and calculating interpolation weighting coefficients can maximize the preservation of spatial clarity and geological authenticity of physical interfaces.

[0142] When conducting anomaly detection and densification of borehole locations, the detection target shifts from the stratification boundary to volumetric defects within the strata (such as tectonic fracture zones and weak karst interlayers). In this case, the invention utilizes the uniaxial compressive strength of the rock mass (…). σ cm () is used as an analytical indicator. Its physical basis lies in: σ cm It integrates the intrinsic strength characteristics of the rock block itself with the macroscopic integrity characteristics of the rock mass (such as geological strength indicators). GSI This is the most intuitive volumetric scalar evaluation of the overall bearing capacity of a rock mass. It is measured along the dip angle of the rock strata. σ cm The occurrence of localized, rapid attenuation is a macroscopic mechanical manifestation of subsequent damage (weathering, fault compression) within the same strata. Based on... σ cm The extreme points or centroids are used to guide the densification drilling, ensuring that each densification borehole can accurately penetrate the weakest soft core of the slope's internal bearing capacity.

[0143] In the final stage of extracting potential sliding surfaces, this invention strictly adheres to the mechanical nature of rock slope instability. It follows the Mohr-Coulomb failure criterion (…). The failure of the slope is not compressive failure, but rather a strict shear slip failure. Therefore, simply evaluating compressive strength cannot accurately delineate the slip channel. This invention utilizes rock mass cohesion (… c m ) and internal friction angle ( φ m Using these parameters as the target parameters, and extracting the maximum value of the spatially integrated mutation rate based on their weights in shear control, this approach directly targets the weak points in the rock mass's shear capacity. The reconstructed potential sliding surface is no longer a simple numerical geometric surface, but a shear failure surface with mechanical significance, thus providing the most accurate physical boundary for subsequent slope numerical analysis (finite element method or limit equilibrium method).

[0144] The rock slope exploration and design device based on digital geological drilling rig provided by the present invention will be described below. The rock slope exploration and design device based on digital geological drilling rig described below can be referred to in correspondence with the rock slope exploration and design method based on digital geological drilling rig described above.

[0145] Figure 6 This is a structural block diagram of the rock slope exploration and design device based on a digital geological drilling rig according to the present invention.

[0146] like Figure 6As shown, the rock slope exploration and design device 600 based on digital geological drilling rig includes a data acquisition module 610, a rock breaking energy calculation module 620, a discreteness index calculation module 630, a rock mass mechanical parameter calculation module 640, an interpolation module 650, and a design scheme generation module 660.

[0147] The acquisition module 610 is used to acquire drilling parameters collected by the digital geological drilling rig during the drilling process of multiple exploration holes.

[0148] The rock-breaking energy calculation module 620 is used to determine the total drilling power based on the drilling parameters and deduct the power loss due to friction along the drilling path to obtain the effective rock-breaking energy.

[0149] The dispersion index calculation module 630 is used to adjust the fluctuation weight of each drilling parameter according to the drilling rig control mode and the spatial abrupt change of the effective rock breaking energy, so as to obtain the drilling dispersion index.

[0150] The rock mass mechanics parameter calculation module 640 is used to determine the rock mass mechanics parameters distributed along the borehole depth based on the effective rock breaking specific energy and the drilling dispersion index.

[0151] The interpolation module 650 is used to determine the rock stratum attitude based on the corresponding abrupt change location of the effective rock breaking energy in multiple exploration holes, adjust the interpolation weight of the known data points based on the rock stratum attitude and the effective rock breaking energy of the known data points, and perform spatial interpolation of the rock mass mechanical parameters based on the adjusted interpolation weights to obtain a three-dimensional rock mass mechanical parameter model. The design scheme generation module 660 is used to determine the potential sliding surface and the remaining spatial sliding force field based on the three-dimensional rock mechanics parameter model, and to determine the slope support parameters based on the remaining spatial sliding force field and the burial depth of the potential sliding surface, thereby generating a slope support design scheme.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for rock slope investigation and design based on a digital geological drilling rig, characterized in that, include: Acquire drilling parameters collected by a digital geological drilling rig during drilling of multiple exploration holes; The total drilling power is determined based on the drilling parameters, and the power loss due to friction along the drilling path is deducted to obtain the effective rock breaking energy. Based on the drilling rig control mode and the spatial abrupt change of the effective rock breaking specific energy, the fluctuation weights of each of the drilling parameters are adjusted to obtain the drilling dispersion index. The rock mass mechanical parameters distributed along the borehole depth are determined based on the effective rock breaking specific energy and the drilling dispersion index. The rock strata attitude is determined by the corresponding abrupt change locations of the effective rock breaking energy in multiple exploration boreholes. The interpolation weights of the known data points are adjusted based on the rock strata attitude and the effective rock breaking energy of the known data points. The rock mass mechanical parameters are then spatially interpolated based on the adjusted interpolation weights to obtain a three-dimensional rock mass mechanical parameter model. Based on the three-dimensional rock mechanics parameter model, the potential sliding surface and the spatial residual sliding force field are determined, and the slope support parameters are determined based on the spatial residual sliding force field and the burial depth of the potential sliding surface, thereby generating a slope support design scheme.

2. The rock slope investigation and design method based on a digital geological drilling rig according to claim 1, characterized in that, The rock mass mechanical parameters include rock mass cohesion and internal friction angle. The step of determining the potential sliding surface based on the three-dimensional rock mass mechanical parameter model includes: The rock mass cohesion and internal friction angle in the three-dimensional rock mass mechanical parameter model are normalized respectively, and the gradient modulus of the normalized rock mass cohesion and internal friction angle in three-dimensional space is calculated. The spatial comprehensive mutation rate field is determined based on the gradient modulus corresponding to the cohesion of the rock mass and the internal friction angle of the rock mass. Local maxima points are extracted from the spatial integrated mutation rate field to form an initial sliding surface point cloud. The initial sliding surface point cloud is then clustered and fitted with a spatial surface to obtain the potential sliding surface.

3. The rock slope investigation and design method based on a digital geological drilling rig according to claim 1, characterized in that, The drilling parameters include the feed thrust, slewing torque, drill bit speed, and drilling speed of the geological drilling rig; The step of determining the total drilling power based on the drilling parameters and deducting the power loss due to friction along the drilling path to obtain the effective rock-breaking specific energy includes: The total drilling power is determined based on the feed thrust, the slewing torque, the drill bit speed, and the drilling speed. The no-load power loss of the foundation is determined based on the no-load feed thrust and no-load rotation torque when the drill bit is not in contact with the rock mass. The frictional power loss along the drilling path is determined based on the drilling depth and the pre-established depth-friction relationship. The effective net power is determined based on the total drilling power, the power loss under no-load conditions, and the power loss due to friction along the drilling path. The effective rock-breaking specific energy is then determined based on the effective net power and the volume of rock broken per unit time.

4. The rock slope investigation and design method based on a digital geological drilling rig according to claim 1, characterized in that, The step of adjusting the fluctuation weights of each of the drilling parameters based on the drilling rig control mode and the spatial abrupt change in the effective rock-breaking specific energy to obtain the drilling dispersion index includes: Determine the coefficient of variation of each of the drilling parameters within the preset depth window; Reduce the fluctuation weight of the controlled drilling parameters according to the drilling rig control mode; The adjusted fluctuation weights are normalized, and the variation coefficients are weighted according to the normalized fluctuation weights to obtain the drilling dispersion index.

5. The rock slope investigation and design method based on a digital geological drilling rig according to claim 1, characterized in that, The determination of rock mass mechanical parameters distributed along the borehole depth based on the effective rock-breaking specific energy and the drilling dispersion index includes: The uniaxial compressive strength of the rock distributed along the hole depth is determined based on the effective rock breaking ratio. The geological strength index of the rock mass distributed along the borehole depth is determined based on the drilling dispersion index. Based on the uniaxial compressive strength of the rock and the geological strength index of the rock mass, the mechanical parameters of the rock mass are determined according to the rock mass strength criterion.

6. The rock slope investigation and design method based on a digital geological drilling rig according to claim 1, characterized in that, The step of spatially interpolating the rock mass mechanical parameters based on the adjusted interpolation weights to obtain a three-dimensional rock mass mechanical parameter model includes: The attitude of the rock strata is determined based on the corresponding abrupt change locations of the effective rock breaking energy in at least three exploration boreholes; An anisotropic search neighborhood is constructed along the direction of the rock strata based on the rock strata's attitude; the anisotropic search neighborhood is used to limit the selection range of known borehole data points participating in spatial interpolation; Based on the rock strata attitude, the node to be interpolated is projected onto the known exploration borehole, and the interpolation weight of the known data point is adjusted according to the difference between the effective rock breaking energy of the projected location and the effective rock breaking energy of the known data point. Based on the adjusted interpolation weights, the rock mass mechanical parameters corresponding to each exploration hole are spatially interpolated to obtain the three-dimensional rock mass mechanical parameter model.

7. The rock slope investigation and design method based on a digital geological drilling rig according to claim 1, characterized in that, The method further includes: The weak and abnormal areas are determined based on the degree of rock mass strength attenuation between adjacent exploration holes in the three-dimensional rock mass mechanics parameter model. Extract abnormal data points where the rock mass strength is lower than a preset strength threshold from the weak and abnormal regions, and perform spatial clustering on the abnormal data points to obtain weak and abnormal clusters. The location of the encrypted exploration boreholes is determined based on the spatial location of the weak and anomalous clusters. Obtain the rock mass mechanics parameters corresponding to the densified exploration borehole locations, and update the three-dimensional rock mass mechanics parameter model based on the rock mass mechanics parameters corresponding to the densified exploration borehole locations.

8. The rock slope investigation and design method based on a digital geological drilling rig according to claim 1, characterized in that, The determination of the potential sliding surface and the remaining spatial sliding force field based on the three-dimensional rock mass mechanics parameter model includes: Based on the spatial morphology of the potential sliding surface and the corresponding rock mechanics parameters of the potential sliding surface, slope stability analysis is performed to obtain the spatial residual sliding force field. The remaining sliding force field in space is mapped to multiple support nodes on the slope surface; The anchor length and anchor hole density are determined based on the remaining sliding force and potential sliding surface burial depth corresponding to each support node, thus obtaining the slope support parameters.

9. The rock slope investigation and design method based on a digital geological drilling rig according to claim 8, characterized in that, The step of determining the anchor bolt length based on the potential sliding surface burial depth corresponding to each of the support nodes, and determining the anchor bolt hole density based on the remaining sliding force corresponding to each of the support nodes, includes: According to the preset slope zoning, determine the maximum potential sliding surface burial depth corresponding to each support node in each preset slope zoning. Based on the maximum potential sliding surface burial depth and the preset effective anchoring section length, determine the theoretical anchor length of the corresponding preset slope zoning. Then, merge the theoretical anchor length upwards to the preset standard anchor length to obtain the anchor length of the corresponding preset slope zoning. The remaining sliding force within the spatial control range corresponding to each support node is determined as the support resistance requirement of the corresponding support node, and the support resistance requirement is compared with the design resistance of a single anchor bolt. In areas where the required support resistance is greater than the design resistance, additional support nodes are added, and the spatial control range is redefined and the required support resistance is determined based on the added support nodes, until the required support resistance for each support node is not greater than the design resistance, so as to determine the anchor bolt hole density.

10. A rock slope exploration and design device based on a digital geological drilling rig, characterized in that, include: The data acquisition module is used to acquire drilling parameters collected by the digital geological drilling rig during the drilling process of multiple exploration holes; The rock-breaking energy calculation module is used to determine the total drilling power based on the drilling parameters and deduct the friction power loss along the drilling path to obtain the effective rock-breaking energy. The dispersion index calculation module is used to adjust the fluctuation weight of each of the drilling parameters according to the drilling rig control mode and the spatial abrupt change of the effective rock breaking specific energy, so as to obtain the drilling dispersion index. The rock mass mechanics parameter calculation module is used to determine the rock mass mechanics parameters distributed along the borehole depth based on the effective rock breaking specific energy and the drilling dispersion index. The interpolation module is used to determine the rock strata attitude based on the corresponding abrupt change locations of the effective rock breaking energy in multiple exploration holes, adjust the interpolation weights of the known data points based on the rock strata attitude and the effective rock breaking energy of the known data points, and perform spatial interpolation on the rock mass mechanical parameters based on the adjusted interpolation weights to obtain a three-dimensional rock mass mechanical parameter model. The design scheme generation module is used to determine the potential sliding surface and the spatial residual sliding force field based on the three-dimensional rock mechanics parameter model, and to determine the slope support parameters based on the spatial residual sliding force field and the burial depth of the potential sliding surface, thereby generating a slope support design scheme.

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