67 results about "Rock types" patented technology

The invention belongs to the technical field of information, and discloses a cloud-English rock type ore body construction method and system based on drilling data, and the method comprises the steps: carrying out the boundary recognition processing according to the gradient change characteristics in an alteration intensity space distribution model, and if the alteration intensity gradient change rate of adjacent space points exceeds a preset boundary threshold value, carrying out the boundary recognition processing; if yes, determining that the position is an ore body boundary point, forming an ore body boundary surface by connecting all boundary points, and judging geometric morphology characteristics of the ore body; a three-dimensional reconstruction algorithm is adopted to carry out internal structure analysis on a space area inside the boundary surface of the ore body, mineral combination difference degrees of different positions inside are calculated through a heterogeneity analysis method, internal structure layers are divided according to difference degree distribution characteristics, and occurrence characteristics and spatial distribution rules inside the ore body are determined. According to the method, full-process automation from data preprocessing to three-dimensional space modeling is achieved, the depicting precision of the ore body space distribution characteristics is remarkably improved, and efficient and accurate technical support is provided for geological exploration and resource evaluation.

A computer-implemented method for augmented inversion and uncertainty quantification for characterizing geophysical bodies is disclosed. The method includes machine-learning-augmented inversion that also facilitates the characterization of uncertainties in geophysical bodies. The method may further estimate wavelets without a well-log calibration, thereby enabling a pre-discovery exploration phase when well log data is unavailable. The machine learning component incorporates a priori knowledge about the subsurface and physics, such as distributions of expected rock types and rock properties, geological structures, and wavelets, through learning from examples. The methodology also allows for conditioning the characterization with the information extracted a priori about the geobodies, such as probabilities of rock types, using other analysis tools. Thus, the conditioning strategy may make the inversion more robust even when a priori distributions are not well balanced. Using the method, a scenario testing workflow may evaluate different candidate subsurface models, facilitating the management of uncertainty in decision-making processes.

The invention discloses a comprehensive evaluation method for a deep coal bed gas reservoir, and the method comprises the following specific steps: S100, classifying gas wells according to the effects of produced wells in a research area, and dividing the gas wells into three types of gas wells I, II and III; s200, in combination with gas well classification standards, carrying out classification evaluation on three types of gas wells I, II and III, including coal rock type, coal rank, coal body structure, coal seam thickness, coal seam physical property, coal seam gas-bearing property, coal seam roof and floor research and the like; and S300, establishing a coal rock reservoir comprehensive evaluation classification standard table according to classification evaluation, evaluating the reservoir quality of the undeveloped target area of the research area, and guiding coal bed gas development. By establishing the comprehensive evaluation method for the deep coal-bed gas reservoir, the method has good guiding significance for efficient development of the deep coal-bed gas, the actual reservoir characteristics of the deep coal-bed gas can be reflected, the requirement for the quality of the geological comprehensive evaluation reservoir is met, a favorable area is preferably selected for comprehensive evaluation of the deep coal-bed gas reservoir, and efficient development is achieved.

The invention relates to a well pattern deployment method for improving the recovery degree of a fractured buried hill oil reservoir, and belongs to the technical field of oil exploitation. The method comprises the following specific steps: in combination with a rock core analysis result, formulating a logging curve combination to recognize a lithologic template, recognizing a rock type, and depicting a dominant rock distribution condition; carrying out fracture prediction by adopting an ant body analysis technology, and further predicting the distribution characteristics of the dominant reservoir; productivity evaluation, water injection evaluation, horizontal well development effect evaluation and adjustment potential evaluation are carried out according to the oil reservoir development effect, and a vertical well and horizontal well combined injection-production well network structure is established in combination with understanding of dominant lithology distribution and dominant reservoir prediction. An injection-production well pattern is perfected by establishing a fractured block buried hill oil reservoir well pattern structure, various types of enriched remaining oil are effectively used, the problems that the inner curtain of the fractured block buried hill oil reservoir is not clearly known, the remaining oil is difficult to dive, and gas-water combined three-dimensional energy complementing is feasible are solved, and the recovery degree of the oil reservoir is improved.

The invention discloses a multi-geophysical field joint inversion method based on physical subspace decoupling, and belongs to the field of geophysical exploration. According to the invention, the problem of poor inversion effect caused by difficult characterization of multivariate and nonlinear physical relations of different types of rocks under complex geological conditions in the existing structure coupling joint inversion method is solved; according to the method, K subspace clustering is utilized to dynamically divide underground model units into different low-rank subspaces according to physical property parameter characteristics in each inversion iteration, and then a low-rank constraint based on a Schatten-p norm is applied to a physical property parameter matrix in each subspace; the clustering-coupling process and the inversion iteration are alternately carried out, so that the division of the physical property subspace and the model updating in each subspace are mutually promoted, the self-adaptive optimization is realized, and the clustering-coupling process and the inversion iteration are carried out at the same time; and finally, high-precision and high-resolution reconstruction of multi-type rock physical property distribution in the complex underground structure is realized.

The invention relates to the technical field of TBM equipment, and discloses a pumped storage power station underground cavity TBM applicability evaluation method, which comprises the following steps: S1, firstly carding an existing framework of pumped storage power station underground cavity TBM applicability evaluation, and defining core technical elements and a protection range of the framework; an evaluation framework of non-AHP driving, dynamic multi-source data fusion and machine learning enabling is provided. According to the method, an evaluation framework of non-AHP driving, dynamic multi-source data fusion and machine learning enabling is provided, an index system is constructed, the index system is divided into static indexes (in a design stage, cavern burial depth, surrounding rock category and turning radius) and dynamic indexes (in a construction stage, TBM attitude error, cutter wear rate, surrounding rock deformation rate and ventilation efficiency), a real-time monitoring system is integrated, and the dynamic index is divided into a dynamic index and a dynamic index; and data such as TBM attitude, cutter wear and surrounding rock deformation are input into the model in real time, and the applicability score is dynamically updated, so that the method has the advantages of high pertinence, comprehensive index system and the like.

The present application belongs to the technical field of deep hole blasting parameter optimization, and discloses a hole site parameter optimization analysis method based on open pit deep hole blasting. The present application determines rock types through multi-index coordination, improves the accuracy of rock classification by combining a dynamic threshold adjustment mechanism, and ensures the accurate matching of hole site parameters and geological conditions. The present application determines through three-level correlation of geological parameters-rock types-mapping relationship, avoids the limitations of empirical formulas, and makes the parameter range more in line with actual geological characteristics. At the same time, historical blasting data sets are introduced for similar case matching, potential risk parameter sets are removed through experience screening, the deviation between theoretical simulation and actual engineering is reduced, and the parameter reliability is improved. The present application adopts a multi-objective optimization model, simultaneously considers fragmentation quality, safety control and economy, outputs a parameter set balancing each target through a Pareto optimal algorithm, and realizes the coordinated optimization of high quality, low risk and low cost.

The present invention belongs to the technical field of efficient fragmentation of hard rocks. Provided are a vehicle-mounted system and method for controlling high-energy laser-induced rock fracturing, the method comprising: by means of a second image acquisition and analysis unit, acquiring surrounding environment information of an electric flat car during movement; on the basis of a stored motion path of the electric flat car and the surrounding environment information, an electric flat car control unit generating a first control instruction; the electric flat car controlling the electric flat car to move to a designated position for rock fragmentation; by means of a first image acquisition and analysis unit, acquiring the type of a rock to be fragmented, and after a laser emission unit is started, acquiring real-time condition information of laser-induced rock fracturing; a laser control unit acquiring a laser emission parameter corresponding to the type of the current rock to be fragmented, and upon receiving the real-time condition information of laser-induced rock fracturing that is acquired by the first image acquisition and analysis unit, adjusting the laser emission parameter, and generating a second control instruction on the basis of the laser emission parameter; and the laser emission unit controlling the laser emission unit to start emitting a laser for rock fragmentation.

Disclosed are methods, systems, and computer programs for generating petrophysical analysis data. The methods include: accessing first porosity data and first well log data associated with an NMR well; randomly selecting data elements comprised in the first porosity data and the first well log data; developing, based on the randomly selected first porosity data and first well log data, a learning data structure; generating, based on the learning data structure, a machine learning model; receiving second well log data using sensor(s) deployed about a non-NMR well; adapting, based on the second well log data, variable input parameters of the machine learning model to generate second porosity data; and formatting the second porosity data to generate petrophysical analysis data. The petrophysical analysis data indicates one or more of: a petrophysical characterization of a rock type; flow dynamic data of a carbonate reservoir; well test or perforation zone data; and pore data.

The present application relates to a kind of carbonate lithology identification method based on well logging parameter, device and storage medium, belong to rock type identification technical field, the method includes: the multiple carbonate thin section of target formation is calibrated, obtains the well logging parameter and type of corresponding depth of carbonate thin section;Carbonate thin section includes dolomite thin section and limestone thin section;Based on the well logging parameter of corresponding depth of carbonate thin section plot crossplot, and determine target parameter according to crossplot and type;Target parameter includes uranium value, thorium value, acoustic time difference and compensation neutron;Based on target parameter, the lithology of dolomite and limestone in non-coring section is identified.The present application provides the carbonate lithology identification method based on well logging parameter, is analyzed with multiple parameters such as uranium, thorium, acoustic time difference and compensation neutron, realizes accurate identification to carbonate lithology.

The application provides a kind of geotechnical engineering investigation three-dimensional geological model automatic construction method and system based on machine learning and BIM, it is related to geotechnical engineering investigation technical field, wherein, the method comprises: after obtaining borehole investigation data, color correction is carried out on original core image based on color chart image, corrected core image is input into convolutional neural network model to identify rock type and demarcate first rock layer boundary line;Key area of resistivity gradient change is used to replace fuzzy area to obtain second rock layer boundary line;According to the inclination correction space position and fill the wave velocity value to generate target borehole columnar section;According to the degree of stratigraphic relief, the calculation weight of spatial interpolation algorithm is adaptively adjusted, and three-dimensional stratum data is generated;Three-dimensional stratum data is imported into BIM software interface to automatically assemble three-dimensional geological model.The application improves the degree of automation and spatial accuracy of geological model construction.

This invention relates to an intelligent prediction method for the safety risks of surrounding rock in underground powerhouses of pumped storage power stations, comprising the following steps: S1, firstly, multiple monitoring devices are installed in the surrounding rock of the underground powerhouse to monitor and collect data on surrounding rock displacement, stress change, fissure opening, and environmental parameters; S2, then, the collected data on surrounding rock displacement, stress change, fissure opening, and environmental parameters are preprocessed using a terminal to complete time synchronization, abnormal data removal, and data standardization, forming a time-series dataset required for surrounding rock safety analysis. This invention realizes real-time monitoring, intelligent prediction, automatic support, and feedback of safety risks in the surrounding rock of underground powerhouses, improves the efficiency of surrounding rock safety management, reduces the risks of manual inspection and emergency operations, and can adapt to the temporary support needs of different surrounding rock types and construction stages.

This invention belongs to the field of solid mineral exploration and evaluation technology, specifically disclosing a rapid field identification method for altered rock-type niobium-tantalum mineralization based on spectral measurements. The method collects spectral data of altered rocks, extracts Fe-OH and Mg-OH spectral absorption characteristic position data after envelope removal, and completes preprocessing through outlier identification and interpolation filling. After adaptive smoothing, weighted fusion, and standardization, multi-model parameter fitting is performed, and the optimal model is selected by combining goodness of fit and information criteria. After smoothing and inflection point analysis of the fitted values, the niobium-tantalum mineralization grade range is determined. This invention achieves in-situ, non-destructive, rapid, and intelligent field identification, determining the degree of mineralization without laboratory testing, significantly improving prospecting efficiency, reducing exploration costs and risks, filling the gap in rapid spectral identification technology for altered rock-type niobium-tantalum mineralization, and providing efficient technical support for the exploration of strategic rare metal resources.

The invention provides a carbon dioxide sequestration site selection method and system based on a deposition ratio. The method comprises the following steps: S1, acquiring carbon dioxide adsorption phase equilibrium data of a middle-deep rock core sample in a to-be-selected area; s2, determining medium-deep reservoir parameters of the area to be subjected to site selection based on the carbon dioxide adsorption phase equilibrium data; s3, determining the porosity lower limit of the rock in the to-be-selected area according to the rock type, the carbon dioxide adsorption phase equilibrium data, the porosity distribution and the buried pressure range of the to-be-selected area; and S4, determining the porosity of the rock of the to-be-selected area based on the medium-deep reservoir parameters of the to-be-selected area, and judging whether the porosity of the rock of the to-be-selected area is greater than the porosity lower limit, if so, taking the to-be-selected area as the carbon dioxide storage area, otherwise, re-obtaining the to-be-selected area and returning to the step S1. According to the technical scheme provided by the invention, the position with relatively high CO2 storage capacity can be effectively screened out, and the scientificity and accuracy of storage site selection are improved.

This invention relates to the field of oil and gas exploration technology and discloses an automatic identification method for drilling cuttings lithology. The method includes: acquiring drilling cuttings images collected from different well areas; preprocessing the drilling cuttings images to obtain target images that meet preset requirements; using a deep learning model to identify the target images and segment them into multiple individual cuttings images; extracting features from the individual cuttings images based on a neural network algorithm; classifying and labeling rock types in the feature space based on the extracted features using the KNN algorithm to establish an automatic identification model for drilling cuttings lithology; and using the automatic identification model to identify the target drilling cuttings. The automatic identification method for drilling cuttings lithology disclosed in this invention is simple to operate, has high identification efficiency, accurate lithology identification, and a wide range of applications.

The invention discloses a comprehensive prospecting method and system for tectonic altered rock type antimony ore based on multivariate information fusion. Relates to the technical field of mineral resource exploration and prediction. Comprising the following steps: acquiring hyperspectral remote sensing data of a working area, and delineating a preliminary prospecting prospective area; constructing a deep three-dimensional density structure and a tectonic framework, and identifying an ore control structure of the preliminary prospecting prospective area and the form and spatial distribution of a hidden rock mass to obtain a prospective working area; collecting and analyzing soil and rock geochemical samples in a long-range working area, and determining favorable metallogenic parts; carrying out short-wave infrared spectrum measurement on the drilled core at the favorable mineralization part to obtain mineral spectrum multivariate information; and establishing a prospecting prediction model according to mineral spectrum multivariate information, and guiding to delineate a deep prospecting target region. According to the method, through multi-information complementation and cross-scale data collaboration, precise positioning and deep prediction of the antimony ore body under the complex structure background are achieved, and the exploration efficiency and the prospecting success rate are effectively improved.

A method for calibrating a model of a subterranean formation includes capturing one or more measurements at a surface extending to a wellbore in the subterranean formation. The measurements include a surface torque (STOR) on a drill string extending into the wellbore and a surface bit pressure (SWOB) on the drill string. The method further includes determining a coefficient of friction based on the STOR when the drill bit is off-bottom in the wellbore. The drill bit is coupled to a lower end of the drill string. The method also includes determining a downhole torque (DTOR) on the drill bit and a downhole bit pressure (DWOB) on the drill bit when the drill bit is bottomed in the wellbore. The method further includes identifying a rock type in the subterranean formation based at least in part on the coefficient of friction, the DTOR, and the DWOB.

The present application belongs to the geological exploration technical field, disclose a kind of deep old microorganism dolomite reservoir space quantitative characterization method, comprising: the rock sample is analyzed, and the rock type and pore information of each rock sample are obtained, according to pore information, determine pore type, and according to pore type and rock type, determine reservoir space type;Dolomite physical property quantitative characterization and nuclear magnetic resonance pore structure quantitative characterization are carried out to the rock sample of different reservoir space types, and the rock physical property difference information and rock pore structure type information of different reservoir space types are obtained;According to rock type, pore type, reservoir space type, rock physical property difference information and rock pore structure type information, the rock sample of different reservoir space types is comprehensively quantitatively characterized and described.The present application combines reservoir multiscale qualitative observation technology and quantitative test technology, and is characterized for deep old microorganism dolomite reservoir, with strong feasibility and applicability.

This invention belongs to the field of rock type classification technology, and discloses a method, device, medium, and terminal for rock type classification based on fractal dimension. It includes establishing a fractal dimension-based model and parameter Dn, comparing the correlation between Dn and mercury intrusion porosimetry (MIP) curve characteristics, and using parameter Dn to reflect the differences in pore throat distribution curves based on the R35 classification method. The fractal dimension-based model and parameter Dn established in this invention are correlated with pore throat distribution images, and comparing the magnitude of this parameter can clarify the differences in image features. Based on the combination of the absolute pore throat diameter method and R35 for pre-classification of rock types, the Dn parameter is used for more detailed classification. When mercury intrusion porosimetry pore throat distribution curves are similar, higher peak values ​​and larger pore throat radii lead to larger Dn parameters; therefore, curve difference characteristics can be obtained by comparing Dn.

The invention relates to the technical field of rock structure roughness surveying and mapping, in particular to a rock structure surface roughness high-precision surveying and mapping method and system. Comprising the steps that firstly, a rock classification model is provided, the model classifies 3D point cloud data of a rock structural surface, and a rock feature weighting layer is added to perform weighting operation on geometric features, shape features and color features of rocks; secondly, a rock roughness surveying and mapping model is provided, and the model achieves surveying and mapping of local roughness and global roughness of a rock structural surface through a structural surface point cloud clustering algorithm; and finally, providing a rock structural surface roughness analysis method, according to the method, establishing a three-dimensional rock structural surface model according to the obtained 3D point cloud data of the rock structural surface, performing meshing division on the three-dimensional rock structural surface model, and performing reason analysis on the rock structural surface roughness obtained by surveying and mapping in combination with rock types and various related data.

The invention discloses a method and device for determining the sealing amount, a storage medium, an electronic device and a computer program product, and relates to the field of carbon dioxide sealing, and the method comprises the following steps: determining the injection amount of carbon dioxide to be sealed; the leakage rate is determined according to the injection rate and geological and topographic information of the storage well, and the leakage rate is the leakage rate of the carbon dioxide after the carbon dioxide with the injection rate is injected into the storage well; the geological and topographic information comprises at least one of the following information: a geological structure, a rock type, crack distribution, an underground water level, a hydrogeological condition and a crustal stress state; and according to the injection rate and the leakage rate, determining the carbon dioxide storage amount actually stored in the storage well. By adopting the technical scheme, the problem that the actual storage amount of CO2 cannot be efficiently determined is solved.

The invention belongs to the technical field of core analysis, and discloses a pressure-maintaining coring deep coal rock lost gas content determination method, which comprises the following steps: carrying out pressure-maintaining gas analysis on a pressure-maintaining inner cylinder with a core, and after the pressure-maintaining gas analysis is completed, obtaining the time when the pressure-maintaining inner cylinder is opened; segmenting the rock core subjected to pressure maintaining gas analysis according to rock types to obtain single rock type analysis rock samples; the analysis rock sample is loaded into an analysis tank to be analyzed, the relation between the accumulated analysis gas volume and the total time is obtained through the sampling result in the analysis process, and the linear increasing end point of the accumulated analysis gas volume is determined; after gas analysis of the analysis rock sample is finished, the mass of the analysis rock sample is weighed; obtaining the relation between the square root of the total time before the linear growth end point moment of the cumulative analytic gas volume and the cumulative analytic gas volume, and solving the lost gas volume of the analytic rock sample by adopting a USBM method; and calculating the content of the lost gas by utilizing the mass of the analyzed rock sample and the volume of the lost gas. According to the method, more accurate and reliable deep coal rock lost gas content data can be provided.

The invention discloses an artificial core as well as a preparation method and application thereof. The method comprises the following steps: determining ingredient components and ingredient specifications of the artificial core according to a rock type in a high-level radioactive repository site selection area; the preparation method comprises the following steps: pre-drying ingredients meeting the specification, weighing the ingredients according to a predetermined component proportion, adding at least one of a water reducing agent, a retarder and an early strength agent, uniformly mixing to obtain a solid material, and synchronously and uniformly mixing the solid material and water in batches to obtain mortar; the mortar is added into the mold in batches, and compaction treatment is carried out after each time of addition; and after the mortar is solidified, demolding and maintaining to obtain the artificial rock core. The method effectively solves the technical problems that in the prior art, original core materials are difficult to obtain and large in demand quantity.

The invention relates to the technical field of engineering blasting, and discloses a large-diameter deep hole presplitting blasting method which comprises the following steps: S1, rock mass analysis: analyzing the states of a rock mass, including the type, the structure, the strength and the stress of the rock mass, and calculating the stability coefficient of the rock mass according to the analysis result, so as to determine the proper position and scheme of presplitting blasting; s2, drilling is conducted, specifically, the diameters and intervals of the drill holes are calculated, the drill holes are arranged in a staggered mode, and a certain overlapping area exists between every two adjacent drill holes; by calculating the stability coefficient of the rock mass, engineers can be helped to better understand the stability condition of the rock mass, so that changes of cracks and joints of the rock mass are predicted, the pre-splitting position is helped to be determined, a more scientific and safer blasting scheme is formulated, meanwhile, according to the calculation result of the stability coefficient, the time interval of a blasting point can be adjusted, and the blasting efficiency is improved. And release of blasting impact force is controlled, accurate control over the blasting effect is achieved, and therefore the blasting efficiency and accuracy are improved.

This invention discloses a method and apparatus for exploring unformed strata based on the synergy of auger drilling and static cone penetration testing. The exploration method includes: acquiring drilling parameters, cuttings characteristics, and static cone penetration testing data; spatiotemporally registering the drilling parameters, cuttings characteristics, and static cone penetration testing data; constructing a fusion dataset of multi-dimensional feature vectors based on the spatiotemporally registered drilling parameters, cuttings characteristics, and static cone penetration testing data, and calculating derived features; predicting formation mechanical parameters based on the fusion dataset and an LSTM model; and identifying soil and rock types based on the derived features, formation mechanical parameters, and a random forest model. This invention achieves multi-source data fusion and analysis, improving exploration efficiency and accuracy.

The application provides a kind of based on composite terrain's graphite and rare earth alloy grounding body installation method and system, it is related to data processing technology, according to the grounding profile of target object and the coverage distance of grounding body, obtainable installation area is carried out to region type identification to obtainable installation area, when determining region type is soil layer type, vertical grounding body is selected;Determine region type is rock type, based on the installation area to determine the detection area;Receive the crack data of detection device at detection area, according to crack data and the reference specification of grounding body groove to obtain the groove parameters of grounding body groove;The groove parameters are sent to management end, based on management end to carry out shape customization to grounding body, obtain customized grounding body, the shape of grounding body groove and graphite, rare earth alloy material's grounding body in complex terrain can be customized planning, improve the conductive current spreading effect of current spreading area.

The invention belongs to the technical field of geological modeling, and provides a lithofacies model establishment method and device, a storage medium and electronic equipment, and the method comprises the steps: determining a plurality of target geological facies and a plurality of rock physical facies; the geological facies and the rock physical facies are coupled, and multiple rock types of the reservoir are determined; acquiring sampling data of multiple rock types of a reservoir in the target well; inputting the sampling data into the structural model, and outputting a static lithofacies model established in the structural model; and correcting and correcting the static lithofacies model to obtain a dynamic lithofacies model. Through the method, the static lithofacies model can be established based on the construction model, and the static lithofacies model is corrected to obtain the dynamic lithofacies model; the method for establishing the lithofacies model is wide in applicable reservoir range, and is particularly suitable for extremely thick and complex bioclastic limestone reservoirs.

The application discloses a method for constructing a three-dimensional geological body, which comprises the following steps: establishing a three-dimensional seismic attribute body about a work area to be studied; based on the three-dimensional seismic attribute body, combining conventional logging data and imaging logging data, respectively dividing rock types under geological scale, logging scale and imaging scale; according to the rock type division results under different scales, combining core data, establishing a multi-scale correlation model for sequentially performing scale coarsening and attribute prediction from core, imaging, logging to geology; and updating the original three-dimensional geological body according to the multi-scale correlation model. The application can apply fine scale data to the construction of a macroscopic geological body.

The present application relates to a kind of experimental methods for characterizing davyne enrichment conditions, which includes rock types, temperature ranges, pH value ranges, fluid types of davyne enrichment characterization, by carrying out a series of water-rock simulation experiments under the same experimental conditions on davyne samples, and using the corresponding davyne dissolution strength and stability of each water-rock simulation experiment, the relationship between davyne enrichment and environmental conditions such as rock types, temperature ranges, pH value ranges and fluid types is characterized.The present application also relates to a high-temperature and high-pressure reaction kettle device for the experimental method.The present application is an experimental method for characterizing davyne enrichment conditions, which obtains the environmental conditions for the stable existence of natural davyne by characterizing davyne enrichment conditions in rock types, temperature, pH value and fluid types, and further determines the high-quality site for CO2 geological storage.

The invention discloses a long-distance small-section diversion tunnel construction process, which belongs to the field of diversion engineering, and comprises the following steps of: carrying out advanced geological forecast to obtain geological information of surrounding rock type, underground water distribution and ground stress state in a tunnel so as to provide safety guidance for subsequent construction; surveying and setting out, and determining a tunnel center line of an excavation face and an excavation contour line; tunnel excavation is conducted, specifically, a drilling and blasting method is adopted for tunnel excavation, and corresponding blasting design is adopted according to the surrounding rock type determined through advanced geological forecast; ventilation and smoke exhaust are conducted, and after blasting is finished, blasting smoke and harmful gas are exhausted; slag is discharged, a trackless transportation mode is adopted, and broken stones and sundries generated by blasting are transferred to a designated slag disposal site to be stacked; and tunnel body supporting is conducted, specifically, according to the surrounding rock type of each tunnel section of the tunnel, the tunnel excavation step is matched, and a targeted supporting strategy is selected to be conducted in the tunnel after excavation is completed or in the excavation process. The process is scientific and reasonable, and the construction quality and the construction safety can be guaranteed.