CN117348075A - Method and device for judging low-burial rock burst of river valley stress field - Google Patents
Method and device for judging low-burial rock burst of river valley stress field Download PDFInfo
- Publication number
- CN117348075A CN117348075A CN202311202846.9A CN202311202846A CN117348075A CN 117348075 A CN117348075 A CN 117348075A CN 202311202846 A CN202311202846 A CN 202311202846A CN 117348075 A CN117348075 A CN 117348075A
- Authority
- CN
- China
- Prior art keywords
- rock
- rock burst
- burst
- rock mass
- mass
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 239000011435 rock Substances 0.000 title claims abstract description 176
- 238000000034 method Methods 0.000 title claims abstract description 37
- 238000009933 burial Methods 0.000 title claims abstract description 15
- 238000007619 statistical method Methods 0.000 claims abstract description 6
- 230000003068 static effect Effects 0.000 claims description 11
- 230000006870 function Effects 0.000 claims description 9
- 230000005641 tunneling Effects 0.000 claims description 5
- 239000003673 groundwater Substances 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 6
- 238000004880 explosion Methods 0.000 abstract description 5
- 238000010276 construction Methods 0.000 description 6
- 238000012544 monitoring process Methods 0.000 description 5
- 238000012876 topography Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 2
- 239000010438 granite Substances 0.000 description 2
- 238000011835 investigation Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005422 blasting Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000011065 in-situ storage Methods 0.000 description 1
- 238000011081 inoculation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/30—Analysis
- G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/62—Physical property of subsurface
Landscapes
- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Acoustics & Sound (AREA)
- Environmental & Geological Engineering (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Geophysics (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
The invention discloses a method and a device for judging low-burial rock burst of a river valley stress field, wherein the method comprises the following steps: s1, determining the geological condition of a rock mass in a tunnel address area; s2, data acquisition is carried out on the rock mass in the tunnel address area, and parameters, rock explosion occurrence positions and rock explosion grades of the rock mass which are subjected to rock explosion are determined; s3, carrying out statistical analysis on parameters of rock burst rock mass, and establishing an empirical formula function for judging the occurrence of rock burst; s4, acquiring parameters of the rock mass to be tested by using a tunnel seismic wave method, and judging whether rock burst occurs in the rock mass to be tested according to an empirical formula function; s5, when the rock burst of the rock mass to be detected is judged, determining the geological condition of the rock mass to be detected by using a geological sketch method, judging whether the geological condition is consistent with the geological condition of the rock mass to be detected, and if so, taking the rock burst occurrence position and the rock burst grade of the rock mass to be detected as the rock burst occurrence position and the rock burst grade of the rock mass to be detected. The problem of poor identification effect on the occurrence of rock burst is solved.
Description
Technical Field
The invention relates to the field of tunnel rock burst prediction, in particular to a method and a device for judging low-burial rock burst of a river valley stress field.
Background
With the large-scale construction of southwest mountain tunnel engineering, hard rock burst disasters are more prominent under high ground stress conditions, prediction and control are still worldwide difficult, and besides the rock burst disasters of deep buried tunnels, some low buried tunnels close to the topography of the river valley face the rock burst problem. The method plays a good role in on-site in-situ monitoring means such as microseismic monitoring of rock burst, but also has the problems of high cost, difficult operation and the like.
The rock burst inoculation environment is extremely complex, the local abnormal ground stress field and the rock mass structure are difficult to ascertain, and the rock burst risk and the rock burst grade are difficult to clearly judge only by surveying the original ground stress and the rock mass strength. Generally, the low buried rock burst of the gully stress field has small variation of the magnitude of the gully stress field, the rock burst grade is still slightly dominant, the microseism monitoring cost is high, and the effect is not necessarily obvious.
Disclosure of Invention
The invention aims to overcome the defect of poor rock burst occurrence judgment effect in the prior art and provides a method and a device for judging low-burial rock burst in a river valley stress field.
In order to achieve the above object, the present invention provides the following technical solutions:
s1, determining the geological condition of a rock mass in a tunneling site area by using a geological sketch method;
s2, acquiring data of rock mass in a tunnel site area by using a tunnel seismic wave method, and determining parameters of rock mass, rock burst occurrence positions and rock burst grades of the rock mass;
s3, carrying out statistical analysis on parameters of rock burst rock mass, and establishing an empirical formula function for judging the occurrence of rock burst;
s4, acquiring parameters of the rock mass to be tested by using a tunnel seismic wave method, and judging whether rock burst occurs in the rock mass to be tested according to an empirical formula function;
s5, when the rock burst of the rock mass to be detected is judged, determining the geological condition of the rock mass to be detected by using a geological sketch method, judging whether the geological condition is consistent with the geological condition of the rock mass to be detected, and if so, taking the rock burst occurrence position and the rock burst grade of the rock mass to be detected as the rock burst occurrence position and the rock burst grade of the rock mass to be detected.
The tunnel seismic method (tunnel seismic prediction is abbreviated as TSP) is based on the principle that seismic signals generated by small-dose blasting propagate in the form of spherical waves in the tunnel direction, seismic waves propagate at different speeds in different rock layers, are reflected at the interfaces thereof, and are received by high-precision receivers. The characteristics of surrounding rock, joint fracture distribution, weak rock stratum, water content and the like in front are analyzed through computer software, the angle which is presented by the intersection of various surrounding rock structural interfaces and tunnel axes and the distance from the tunnel face are displayed on a final display screen, and parameters such as the elastic modulus, density, poisson ratio and the like of the rock can be preliminarily measured for reference.
Preferably, in step S1, the geological conditions include structural face occurrence, face integrity distribution, depth of burial from valley level and groundwater.
Preferably, in step S2, the parameters of the rock mass where rock burst has occurred include longitudinal wave velocity, transverse wave velocity, poisson ' S ratio, density, dynamic young ' S modulus and static young ' S modulus.
Preferably, in step S3, the empirical formula function for determining the occurrence of a rock burst is: when the longitudinal wave velocity is more than or equal to 5200m/s, the transverse wave velocity is more than or equal to 3000m/s, the Poisson ratio is less than or equal to 0.3, and the density threshold is more than or equal to 2690kg/m 3 When the static Young's modulus is more than or equal to 55GPa and the dynamic Young's modulus is more than or equal to 66.9GPa, the rock burst is judged to occur; and when any parameter is not satisfied, judging that rock burst does not occur.
A device for determining a low-burial rock burst in a valley stress field, comprising at least one processor and at least one memory communicatively connected to the processor, the memory storing instructions for execution by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to perform any of the steps of the method.
Compared with the prior art, the invention has the beneficial effects that:
1. by carrying out statistical analysis on the parameters of the rock burst, the parameter ranges of longitudinal wave velocity, transverse wave velocity, poisson ratio, density, dynamic Young modulus and static Young modulus are determined as the judging conditions of the rock burst, so that the judging effect on the rock burst is improved;
2. and carrying out geological sketch on the rock mass with the rock burst, determining the geological condition of the rock mass, and taking the rock burst occurrence position and grade corresponding to the geological condition as the judgment standard of the rock burst occurrence position and grade of the rock mass to be tested, so that the rock burst occurrence position and grade are effectively defined.
Drawings
FIG. 1 is a block diagram of the method of the present invention;
FIG. 2 is a graph of two-dimensional reflection horizon and physical mechanical parameter results;
FIG. 3 is a graph of parametric results versus rock burst location;
fig. 4 is a view showing a rock burst occurrence position and a rank prediction.
Detailed Description
The present invention will be described in further detail with reference to test examples and specific embodiments. It should not be construed that the scope of the above subject matter of the present invention is limited to the following embodiments, and all techniques realized based on the present invention are within the scope of the present invention.
Example 1
As shown in fig. 1, the method for determining the low-burial rock burst of the river valley stress field comprises the following steps:
s1, determining the geological condition of a rock mass in a tunneling site area by using a geological sketch method;
s2, acquiring data of rock mass in a tunnel site area by using a tunnel seismic wave method, and determining parameters of rock mass, rock burst occurrence positions and rock burst grades of the rock mass;
s3, carrying out statistical analysis on parameters of rock burst rock mass, and establishing an empirical formula function for judging the occurrence of rock burst;
s4, acquiring parameters of the rock mass to be tested by using a tunnel seismic wave method, and judging whether rock burst occurs in the rock mass to be tested according to an empirical formula function;
s5, when the rock burst of the rock mass to be detected is judged, determining the geological condition of the rock mass to be detected by using a geological sketch method, judging whether the geological condition is consistent with the geological condition of the rock mass to be detected, and if so, taking the rock burst occurrence position and the rock burst grade of the rock mass to be detected as the rock burst occurrence position and the rock burst grade of the rock mass to be detected.
In step S1, the geological conditions include the occurrence of a structural face, the distribution of the degree of integrity of a face, the horizontal position of a depth of burial from a valley, and the condition of groundwater.
In step S2, parameters of the rock mass where the rock burst has occurred include longitudinal wave velocity, transverse wave velocity, poisson ' S ratio, density, dynamic young ' S modulus and static young ' S modulus.
In step S3, the empirical formula function for determining the occurrence of the rock burst is: when the longitudinal wave velocity is more than or equal to 5200m/s, the transverse wave velocity is more than or equal to 3000m/s, the Poisson ratio is less than or equal to 0.3, and the density threshold is more than or equal to 2690kg/m 3 When the static Young's modulus is more than or equal to 55GPa and the dynamic Young's modulus is more than or equal to 66.9GPa, the rock burst is judged to occur; and when any parameter is not satisfied, judging that rock burst does not occur.
A low-burial rock burst judging device for a river valley stress field adopts a Core i7-12700 processor and a memory adopts a solid state disk of three stars 480 PRO 1T.
Example 2
Taking the Baoling mountain tunnel No. 3 transverse tunnel as an example for carrying out a test experiment, wherein the Baoling mountain tunnel is a control engineering of a newly built Sichuan and Tibetan railway, the Baoling mountain tunnel No. 3 transverse tunnel has the total length of 3360m, belongs to a typical extremely high mountain canyon area, has the overall north and south heights of Gao Chachao to more than 3000 meters, develops a northern east deep river valley on the left side of the tunneling direction, and has the transverse height difference of more than 1000 meters. The surrounding rock is granites and granite, is complete and complete, has joints which are not developed, is in a closed shape and is positioned in a Y-shaped construction field region.
The method comprises the following steps of:
s1, geological investigation is carried out, the topography and topography of a tunnel address area are analyzed, geological sketch is carried out, the occurrence, development and integrity degree of rock mass structure of the face are recorded, investigation shows that the geological conditions of the current face and an excavated section are basically consistent, the H3DK2+197 face reveals that surrounding rock is granulized rock, weak weathering is carried out, a layer-like structure is formed, joints are relatively developed, the occurrence of the joints 1 is N75 DEG W/35 DEG NE, the joints intersect with a hole axis at a large angle, the joints 2 are inclined to the left rear side, the occurrence of the joints 2 is N15 DEG E/75 DEG NW, the joints intersect with the hole axis at a small angle, the joints are inclined to the right rear side, the joint spacing is 30-120cm, the joints extend for 2-6m, the crack is closed-slightly tensioned, the whole surrounding rock is relatively complete, the rock is hard, the face is anhydrous, the left inclined structure face is mainly developed (inclined to one side of a river), and the rock explosion occurrence part is mainly concentrated at the left vault and the waist position;
s2, carrying out data acquisition (seismic wave emission method) to obtain a two-dimensional reflection horizon and a physical mechanical parameter result diagram, wherein the section Vp of H3DK2+197-H3DK2+097 is 5488-5724 m/S, vs is 3101-3301 m/S, poisson ratio is 0.23-0.27, and density is 2782-2864 kg/m 3 Static Young's modulus of 55-70 GPa, dynamic Young's modulus of 67-78 GPa, as shown in Table 1 and FIG. 2;
table 1h3dk2+197 to h3dk2+097 section inversion related parameters
S3, according to the physical parameters of the rock mass corresponding to the positions where more than 60 slight rock burst occur: vp:41 times >5400m/s,58 times >5200m/s,2 times < 5200m/s; vs:51 times >3000m/s,60 times >2960m/s; poisson ratio: 59 times < 0.3, 40 times < 0.264, density: 32 times >2800Kg/m3, 50 times >2690Kg/m3; static Young's modulus: 46 times >55GPa; dynamic young's modulus: 42 times >66.9GPa.
Comprehensive analysis: meanwhile, the dynamic Young's modulus is more than 66.9GPa, the static Young's modulus is more than 55GPa, the density is more than 2690Kg/m3, the Poisson ratio is less than 0.3, the longitudinal wave velocity Vs is more than 3000m/s, and the transverse wave velocity Vp is more than 5200m/s.60 rock bursts 41 times meet all the conditions, and the ratio is 68.3 percent, as shown in figure 3, wherein the rock bursts at the arch part are concentrated, and the side walls and the tunnel face are relatively less;
s4: according to forecasting results, the forecasting is carried out by combining geological sketch analysis, the H3 DK2+197-H3 DK2+097 sections, the full-section longitudinal wave speed Vp is larger than 5200m/s, the transverse waves are larger than 3000m/s, the Poisson ratio is smaller than 0.3, the density is larger than 2690Kg/m3, the static Young modulus is larger than 55GPa, the dynamic Young modulus is larger than 66.9GPa, and therefore 100m sections all have the condition of rock burst occurrence, wherein the longitudinal waves, the transverse waves, the density and the Young modulus values of the H3DK2+168 sections are largest, the possibility of light rock burst occurrence is largest, the light rock burst occurrence mainly occurs at the left arch (on the side of a dip), construction protection is required to be enhanced, and the safety risk of tunnel construction is reduced, as shown in fig. 4.
By analyzing the spatial relationship among the rock mass structure, the topography and the tunneling direction, the comprehensive prediction of the rock burst mileage paragraphs and the positions is combined, the positions and the grades with high probability are mainly used as the prediction basis under the same geological condition of the rear section according to the statistical analysis of the rock burst paragraphs, and meanwhile, the following basic judgment principle can be referred to if the following data exists.
(1) Stress environment. The second principal stress direction is substantially consistent with the hole axis direction, namely, the first principal stress is intersected with the hole axis at a large angle, and the possibility of rock burst at the positions of the side walls (the third principal stress direction) at the two sides of the tunnel is high.
(2) Rock mass structure. When the structural surface inclination angle gamma is larger than 60 degrees, rock burst is easy to occur, and the strength is enhanced along with the increase of gamma; the included angle alpha between the trend of the structural surface and the axis of the tunnel is between 0 and 30 degrees, rock burst is easy to occur, and the strength of the structural surface is increased along with the decrease of alpha.
(3) And (5) construction rock explosion. The rock burst continuously occurs along the axial direction of the hole, particularly when the rock burst occurs again in the hole section, the rock burst prediction method has the advantages that the rock stress around the hole is high to a great extent, and the possibility of adjusting the stress to the deep part exists, so that the rock burst prediction method can be used as an appearance of rock burst prediction.
(4) And (5) microseismic monitoring. And predicting the rock burst risk by using the effective microseismic monitoring range, and predicting by combining the microseismic activity characteristics and rules in the construction process of the hole section where the rock burst is located and the current microseismic activity characteristics of the hole section.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (5)
1. A method for judging low-burial rock burst of a river valley stress field is characterized by comprising the following steps:
s1, determining the geological condition of a rock mass in a tunneling site area by using a geological sketch method;
s2, acquiring data of rock mass in a tunnel site area by using a tunnel seismic wave method, and determining parameters of rock mass, rock burst occurrence positions and rock burst grades of the rock mass;
s3, carrying out statistical analysis on parameters of rock burst rock mass, and establishing an empirical formula function for judging the occurrence of rock burst;
s4, acquiring parameters of the rock mass to be tested by using a tunnel seismic wave method, and judging whether rock burst occurs in the rock mass to be tested according to an empirical formula function;
s5, when the rock burst of the rock mass to be detected is judged, determining the geological condition of the rock mass to be detected by using a geological sketch method, judging whether the geological condition is consistent with the geological condition of the rock mass to be detected, and if so, taking the rock burst occurrence position and the rock burst grade of the rock mass to be detected as the rock burst occurrence position and the rock burst grade of the rock mass to be detected.
2. The method for determining the low-burial rock burst of the river valley stress field according to claim 1, wherein in the step S1, the geological conditions include the occurrence of structural face, the distribution of the degree of integrity of the face, the level position of the burial depth from the river valley and the condition of groundwater.
3. The method according to claim 1, wherein in step S2, the parameters of the rock mass in which the rock burst has occurred include longitudinal wave velocity, transverse wave velocity, poisson ' S ratio, density, dynamic young ' S modulus, and static young ' S modulus.
4. A method for determining a low-burial type rock burst in a river valley stress field according to claim 3, wherein in step S3, the empirical formula function for determining the occurrence of rock burst is: when the longitudinal wave velocity is more than or equal to 5200m/s, the transverse wave velocity is more than or equal to 3000m/s, the Poisson ratio is less than or equal to 0.3, and the density threshold is more than or equal to 2690kg/m 3 When the static Young's modulus is more than or equal to 55GPa and the dynamic Young's modulus is more than or equal to 66.9GPa, the rock burst is judged to occur; and when any parameter is not satisfied, judging that rock burst does not occur.
5. A device for determining a low-burial rock burst in a valley stress field for carrying out the method according to any one of claims 1 to 4, comprising at least one processor and at least one memory communicatively connected to the processor, said memory storing instructions for execution by the at least one processor, said instructions being executable by the at least one processor to enable the at least one processor to perform any step of said method.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202311202846.9A CN117348075B (en) | 2023-09-18 | 2023-09-18 | Method and device for judging low-burial rock burst of river valley stress field |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202311202846.9A CN117348075B (en) | 2023-09-18 | 2023-09-18 | Method and device for judging low-burial rock burst of river valley stress field |
Publications (2)
Publication Number | Publication Date |
---|---|
CN117348075A true CN117348075A (en) | 2024-01-05 |
CN117348075B CN117348075B (en) | 2024-09-13 |
Family
ID=89354856
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202311202846.9A Active CN117348075B (en) | 2023-09-18 | 2023-09-18 | Method and device for judging low-burial rock burst of river valley stress field |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN117348075B (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117890477A (en) * | 2024-03-13 | 2024-04-16 | 西南交通大学 | Method for calculating compressive strength of rock based on TSP data |
Citations (14)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US3662325A (en) * | 1969-08-27 | 1972-05-09 | Western Geophysical Co | Method of displaying seismic data |
US20070244647A1 (en) * | 2006-04-14 | 2007-10-18 | Dickson William C | Density and velocity based assessment method and apparatus |
CN101915104A (en) * | 2010-07-30 | 2010-12-15 | 中国水电顾问集团华东勘测设计研究院 | Rock burst control method for deep tunnel excavation by adopting TBM (Tunnel Boring Machine) |
CN102749660A (en) * | 2012-06-26 | 2012-10-24 | 中国人民解放军第二炮兵工程设计研究所 | Method for comprehensively forecasting approximately horizontal stratum rock burst in high geostress regions |
WO2014176952A1 (en) * | 2013-04-28 | 2014-11-06 | 中国矿业大学 | Method for partitioning, grading and forecasting rock bursts in underground coal mine |
CN104345339A (en) * | 2013-07-25 | 2015-02-11 | 中国石油天然气集团公司 | Method utilizing array sound wave logging information for determining rock brittleness coefficients |
CN109736886A (en) * | 2018-12-20 | 2019-05-10 | 武汉理工大学 | A kind of strength-stress ratio rock burst criterion method considering tunnel surrounding stress distribution |
CN110298503A (en) * | 2019-06-26 | 2019-10-01 | 东北大学 | Tunnel rock burst method for early warning based on microseism information and depth convolutional neural networks |
CN110648082A (en) * | 2019-10-08 | 2020-01-03 | 东北大学 | Rapid table look-up method for rock burst grade evaluation of deep-buried hard rock tunnel |
CN112394397A (en) * | 2019-08-13 | 2021-02-23 | 中国石油化工股份有限公司 | Shale gas reservoir three-dimensional rock mechanical parameter field modeling method |
CN113189647A (en) * | 2021-04-30 | 2021-07-30 | 西南石油大学 | Method for predicting formation brittleness index of transverse isotropic shale |
CN116402347A (en) * | 2023-04-06 | 2023-07-07 | 中建三局集团有限公司 | Rock burst dynamic risk assessment method and system for high-ground stress tunnel construction |
CN116595335A (en) * | 2023-05-25 | 2023-08-15 | 成都理工大学 | Rock burst microseismic parameter multi-element multi-time-step output prediction model |
CN116643307A (en) * | 2023-05-08 | 2023-08-25 | 大连理工大学 | Method for accurately predicting rock burst strength and position through rock mass wave velocity |
-
2023
- 2023-09-18 CN CN202311202846.9A patent/CN117348075B/en active Active
Patent Citations (14)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US3662325A (en) * | 1969-08-27 | 1972-05-09 | Western Geophysical Co | Method of displaying seismic data |
US20070244647A1 (en) * | 2006-04-14 | 2007-10-18 | Dickson William C | Density and velocity based assessment method and apparatus |
CN101915104A (en) * | 2010-07-30 | 2010-12-15 | 中国水电顾问集团华东勘测设计研究院 | Rock burst control method for deep tunnel excavation by adopting TBM (Tunnel Boring Machine) |
CN102749660A (en) * | 2012-06-26 | 2012-10-24 | 中国人民解放军第二炮兵工程设计研究所 | Method for comprehensively forecasting approximately horizontal stratum rock burst in high geostress regions |
WO2014176952A1 (en) * | 2013-04-28 | 2014-11-06 | 中国矿业大学 | Method for partitioning, grading and forecasting rock bursts in underground coal mine |
CN104345339A (en) * | 2013-07-25 | 2015-02-11 | 中国石油天然气集团公司 | Method utilizing array sound wave logging information for determining rock brittleness coefficients |
CN109736886A (en) * | 2018-12-20 | 2019-05-10 | 武汉理工大学 | A kind of strength-stress ratio rock burst criterion method considering tunnel surrounding stress distribution |
CN110298503A (en) * | 2019-06-26 | 2019-10-01 | 东北大学 | Tunnel rock burst method for early warning based on microseism information and depth convolutional neural networks |
CN112394397A (en) * | 2019-08-13 | 2021-02-23 | 中国石油化工股份有限公司 | Shale gas reservoir three-dimensional rock mechanical parameter field modeling method |
CN110648082A (en) * | 2019-10-08 | 2020-01-03 | 东北大学 | Rapid table look-up method for rock burst grade evaluation of deep-buried hard rock tunnel |
CN113189647A (en) * | 2021-04-30 | 2021-07-30 | 西南石油大学 | Method for predicting formation brittleness index of transverse isotropic shale |
CN116402347A (en) * | 2023-04-06 | 2023-07-07 | 中建三局集团有限公司 | Rock burst dynamic risk assessment method and system for high-ground stress tunnel construction |
CN116643307A (en) * | 2023-05-08 | 2023-08-25 | 大连理工大学 | Method for accurately predicting rock burst strength and position through rock mass wave velocity |
CN116595335A (en) * | 2023-05-25 | 2023-08-15 | 成都理工大学 | Rock burst microseismic parameter multi-element multi-time-step output prediction model |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN117890477A (en) * | 2024-03-13 | 2024-04-16 | 西南交通大学 | Method for calculating compressive strength of rock based on TSP data |
CN117890477B (en) * | 2024-03-13 | 2024-05-17 | 西南交通大学 | Method for calculating compressive strength of rock based on TSP data |
Also Published As
Publication number | Publication date |
---|---|
CN117348075B (en) | 2024-09-13 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Zhao et al. | Rock fracturing observation based on microseismic monitoring and borehole imaging: In situ investigation in a large underground cavern under high geostress | |
Zhang et al. | Determination of statistical discontinuity persistence for a rock mass characterized by non-persistent fractures | |
CN117348075B (en) | Method and device for judging low-burial rock burst of river valley stress field | |
CN112485823B (en) | High-efficiency comprehensive advanced geological prediction method | |
CN112965136B (en) | Multi-means advanced detection method for water-rich karst tunnel | |
Fan et al. | Advanced stability analysis of the tunnels in jointed rock mass based on TSP and DEM | |
CN110174463B (en) | Nondestructive quantitative testing method for three-dimensional mining stress field of working face | |
CN111708079B (en) | Tunnel harmful gas comprehensive advanced prediction method based on TSP | |
Yertutanol et al. | Displacement monitoring, displacement verification and stability assessment of the critical sections of the Konak tunnel, İzmir, Turkey | |
CN108918682B (en) | Entrenched valley Slope Rock Mass natural crustal stress indoor test analysis method now | |
WO2024169098A1 (en) | Geological determination method for delayed extremely-intense rockburst | |
Zhang et al. | Excavation-induced structural deterioration of rock masses at different depths | |
Novopashina et al. | Methodical approach to isolation of seismic activity migration episodes of the northeastern Baikal rift system (Russia) | |
CN112016201B (en) | DFOS strain-based deep stope advanced support pressure evolution model reconstruction method | |
CN113376695A (en) | Full waveform inversion method suitable for complex collapse column of coal seam floor | |
Han et al. | Application of borehole camera technology in fractured rock mass investigation of a submarine tunnel | |
Zhu et al. | Analyses of disking phenomenon and stress field in the region of an underground powerhouse | |
Yang et al. | Questioning the use of RQD in rock engineering and its implications for rock engineering design | |
Kashnikov et al. | Solving the problems of exploitation safety of potassium salt deposit based on joint application of geophysical and geomechanical studies | |
CN107169637A (en) | A kind of power station layer of sand soil property liquefaction evaluation method | |
CN111596377A (en) | Joint test method for loosening ring of high-ground-stress soft rock tunnel | |
Ming‐Zhou et al. | THE THREE‐DIMENSIONAL IMAGING TECHNOLOGY AND ITS IMPROVEMENT FOR GEOLOGICAL STRUCTURE BASED ON TRT SYSTEM | |
Deák et al. | In-situ Primary Stress Detection Based on Seismic Tomography Measurements and Numerical Back-analysis for an Underground Radwaste Repository | |
Chen et al. | Deformation patterns and failure mechanisms of soft-hard-interbedded anti-inclined layered rock slope in Wolong open-pit coal mine | |
CN117371111B (en) | TBM card machine prediction system and method based on deep neural network and numerical simulation |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant |