546 results about "System" patented technology

The invention relates to the technical field of tunnel engineering, in particular to a tunnel surrounding rock grading method and system, comprising intelligent sensing and data acquisition, multi-source data fusion and modeling, hybrid model dynamic grading, real-time decision and support optimization, online learning and dynamic feedback, and risk early warning and emergency response. Compared with the prior art that a geological data acquisition mode combining manual drilling coring and low-resolution geophysical prospecting is adopted, efficiency is low, subjective errors are large, and a complex geological structure is difficult to cover, unmanned aerial vehicle LiDAR scanning, intelligent rock core image analysis and a high-density IoT sensor network work cooperatively, and the working efficiency is greatly improved. Real-time dynamic acquisition of full-section geological information is achieved, manual intervention errors are eliminated in combination with a multi-source data fusion algorithm, the automation level and three-dimensional space representation precision of data acquisition are remarkably improved, and a high-resolution holographic data base is provided for surrounding rock classification.

The invention discloses a tunnel blasting simulation method and system for a karst area, and relates to the field of tunnel blasting simulation, and the method comprises the steps: building a three-dimensional geologic model of the karst area, and generating an initial ground stress distribution rule through numerical simulation; generating refined initial crustal stress field data; calculating stress wave intensity and time sequence data generated by explosion; acquiring stress wave propagation data; calculating the surrounding rock damage degree and the crack initial position and direction; simulating the surrounding rock crack propagation process, and calculating the penetration probability and the propagation speed of the crack near the karst cave in combination with the karst cave characteristic parameters; analyzing the surrounding rock stability and damage evolution trend of the karst cave area; and optimizing explosive source item parameters and stress wave propagation boundary conditions, and generating a karst area tunnel blasting simulation result. According to the method, the influence of the karst cave on stress wave propagation is accurately simulated, powerful support is provided for optimizing a blasting scheme and improving construction safety and efficiency, and the method has important guiding significance on tunnel engineering under complex geological conditions.

The present disclosure relates to systems and / or methods for predicting the location of subsurface reservoirs of natural hydrogen. One or more embodiments described herein include a system that can comprise a memory to store computer executable instructions. The system can also comprise one or more processors, operatively coupled to the memory, that execute the computer executable instructions to implement a hydrogen exploration controller configured to generate a plurality of maps characterizing a geographical region. The respective maps from the plurality of maps can delineate a location of respective geological features within the geographical region that are associated with a presence of a subsurface reservoir of natural hydrogen. Additionally the hydrogen exploration controller can be further configured to identify an area in the geographical region that comprises a convergence of two or more of the respective geological features based on the plurality of maps.

The invention provides a tunnel disaster source multi-attribute joint inversion method and system based on physical property constraint, and relates to the technical field of tunnel engineering and joint inversion, and the method comprises the steps: constructing a tunnel face three-dimensional geologic model, applying controlled disturbance to surrounding rock physical property parameters, analyzing the change characteristics of earthquake and electromagnetic observation response, and obtaining a tunnel face three-dimensional geologic model; establishing a quantitative mapping relation between the surrounding rock physical property parameter disturbance quantity and the multi-field response signal variable quantity; constructing a multi-dimensional sensitivity evaluation index, and generating a joint sensitivity result; the surrounding rock units are identified and divided, differentiated partition rock physical relationship constraints are constructed, and a physical multi-attribute inversion target of joint inversion is determined based on the partition rock physical relationship constraints; and on the basis of a physical multi-attribute inversion target, a multi-source joint inversion target function is constructed in combination with the joint sensitivity result, joint solving and iterative updating are carried out, and a tunnel face advanced inversion result is output. According to the invention, calamity source fine identification and risk quantitative evaluation in front of the tunnel face during the tunnel construction period are realized.

The invention provides a deep geologic body occurrence characteristic quantitative representation modeling method and system, and the model focuses on the multi-physics field occurrence environment of rock mass material composition, structural characteristics, stress distribution and the like under the continuous mining condition of a deep underground metal mine. An information expression framework capable of crossing a'microcosmic-experimental-engineering 'multi-level spatial scale is constructed, microcosmic rock core mineral components and crack information, laboratory mechanical response parameters and structural surface shear characteristics and macroscopic fault system and stress disturbance data reflected by microseismic events are introduced, a heterogeneous data fusion method is comprehensively applied, and a microcosmic-experimental-engineering multi-level spatial scale is constructed. A three-dimensional tensor model with dynamic evolution capability and physical interpretation capability is established, high-precision, dynamic and multi-scale comprehensive modeling of a complex deep geologic body occurrence environment is realized, and the model has the characteristics of clear information hierarchy, high fusion precision, strong physical interpretability and the like. And dynamic perception and scientific research and judgment of geologic mass mechanics and structure states can be realized in a complex deep environment.

A pore pressure prediction method for fine-grained hybrid sedimentary rock based on variable P-wave velocity includes: carrying out a P-wave velocity test of rock under different effective stresses, determining a function form of the relationship between acoustic velocity and effective stress, fitting the parameters in the function by optimization, and establishing an evaluation model of effective stress influence term by lithology. According to the measured formation pressure data and the effective stress influence term model, the acoustic velocity background value is deduced, the logging curve is preferred, and the acoustic velocity background value logging evaluation model is established. According to the logging curves of DT and DEN, combined with the lithology identification results, the acoustic velocity background value is calculated, and then the effective stress of the formation is obtained, and then the pore pressure is determined according to the overburden pressure.

The invention relates to the technical field of layered surrounding rock inversion analysis, and discloses a layered surrounding rock three-dimensional crustal stress field inversion intelligent analysis system and method, and the system comprises a dimensional geological value module, an intelligent inversion analysis module and an inversion result verification module. The method comprises the steps of collecting geological data in target layered surrounding rock; carrying out normalization processing on the geological data, and carrying out sensitivity analysis; constructing a three-dimensional geologic model, and performing numerical simulation; a crustal stress field inversion intelligent analysis model is generated based on the three-dimensional geologic model; training the crustal stress field inversion intelligent analysis model by using the training sample; inputting the real-time geological data into the crustal stress field inversion intelligent analysis model to obtain a crustal stress inversion analysis result; carrying out visual output on the ground stress analysis result; and adjusting the crustal stress field inversion intelligent analysis model according to the actually measured data. Scientific ground stress field analysis basis can be provided for complex projects such as tunnel engineering, underground engineering and hydropower stations.

The invention provides an intelligent optimization method and system for tunnel smooth blasting blast holes in layered rock mass, and belongs to the technical field of tunnel engineering and blasting. The method comprises the steps of collecting stratified rock geological data, evaluating and extracting features, constructing a multi-objective optimization function, solving by an intelligent optimization algorithm, performing construction feedback and dynamic optimization and the like. The method comprises the following steps of: acquiring data by using various geological exploration equipment, performing evaluation processing on the data by using a support vector machine model, constructing an optimization function considering multiple indexes, solving an optimal blast hole parameter combination by combining a genetic algorithm and a particle swarm optimization algorithm, and finally feeding back a blasting effect to dynamically adjust an optimization scheme. According to the intelligent optimization method and system for the smooth blasting blast holes of the tunnel in the layered rock mass, the blasting effect can be improved, over-break and under-break and concrete consumption can be reduced, the construction cost can be reduced, the construction safety and efficiency can be enhanced, and remarkable economic and social benefits can be achieved for layered rock mass tunnel engineering construction.

The invention provides a tunnel surrounding rock grouting control method and system, and relates to the technical field of tunnel engineering.The tunnel surrounding rock grouting control method comprises the steps that grouting parameters are obtained, and the grouting parameters comprise grouting pressure and slurry viscosity; performing multi-dimensional real-time monitoring on the surrounding rock fracture, and constructing a dynamic three-dimensional geologic model through the multi-dimensional real-time monitored data; performing grout diffusion path prediction based on the three-dimensional geologic model, and generating an initial grouting scheme through the predicted grout diffusion path; the fractal dimension is optimized according to a genetic algorithm, the grouting parameters are dynamically corrected through the optimized fractal dimension, and a grout diffusion result is obtained; establishing a multi-field coupling equation based on the slurry diffusion result, and optimizing the initial grouting scheme through the multi-field coupling equation to obtain an optimal grouting scheme; and according to the optimal grouting scheme, power pressure compensation is conducted, and grouting control is conducted. The problem that slurry diffusion is difficult to accurately control is solved.

Systems and methods for identifying natural hydrogen sweet spots in a subsurface formation include obtaining rock samples from the subsurface formation; performing pyrolysis of the rock samples to determine an amount of hydrogen generated in the rock samples; determining kinetic parameters based on the performed pyrolysis and a thermal history of the subsurface formation; simulating hydrogen generation in the subsurface formation based on the determined kinetic parameters and the thermal history to predict target maturity data for hydrogen richness in the subsurface formation; measuring total organic content and rock sample maturity data for the rock samples; and identifying hydrogen sweet spots in the subsurface formation based on the target maturity data, the total organic content, and the measured rock sample maturity data.

The present invention belongs to the technical field of geological exploration deep Earth. The system of the present invention is configured to: collect seismic data, and preprocess original seismic data to obtain standardized gamma ray logging parameters; extract features from the standardized gamma ray logging parameters to obtain a variance attribute curve while drilling; obtaining a formation thickness prediction model of each set based on the variance attribute curve while drilling; acquire frequency-division seismic data based on the standardized seismic data by means of a frequency-division processing method based on wavelet transform; acquire optimal seismic frequency band information based on a predicted formation thickness value of each set; establish a geological prediction model of the current formation based on the frequency-division seismic data, the optimal seismic frequency band information, historical gamma ray logging parameters and the standardized gamma ray logging parameters.

The embodiment of the invention discloses a mineral resource exploration data analysis method and device based on three-dimensional space modeling. The method comprises the steps that back-flushing pushing-covering structure feature information is extracted through structure interface occurrence measurement, lithology combination analysis and structure movement trace recognition and converted into geologic structure feature parameters; stratigraphic age data and lithology distribution information are integrated, and a three-dimensional stratigraphic model is constructed with a stratigraphic superposition relation as a constraint; geophysical data are imported to extract geophysical response characteristics of stratums with different depths, and lithologic boundary correction is combined to obtain deep fracture characteristic parameters; sedimentary system division is carried out on lithofacies paleogeographic information, and deep fracture characteristic parameters are fused to establish a fracture system three-dimensional model; the multi-feature association relationship is identified, the ore body prediction model is established, the spatial data is input to obtain the three-dimensional visual prediction result of the hidden ore body spatial distribution, and the exploration efficiency and accuracy in the deep phosphorite exploration process are improved.

The invention provides a simulation method and system for mechanical parameter prediction of a rock mass structural plane of a base-covering interface, and relates to the technical field of geological survey, and the simulation method specifically comprises the following steps: collecting environmental parameters and material parameters, and calculating a physical influence index, an environmental adaptability index and a fracture stability index; performing a dynamic load test on the rock mass to obtain dynamic response data of the rock mass, constructing a structural anti-seismic prediction model according to a physical influence index, an environmental adaptability index, a fracture stability index and a dynamic response index, and generating a weight in the model through an analytic hierarchy process, and utilizing the structure anti-seismic prediction model to generate a structure anti-seismic index of the base-covering interface rock mass structure. According to the scheme, the mechanical characteristics of the rock mass can be comprehensively reflected, and the influence of environmental change on the rock mass performance is effectively considered, so that the scientificity of anti-seismic performance prediction is improved.

The invention discloses a geological attribute modeling method and system based on multi-source information joint constraint, and relates to the technical field of geological engineering, and the method comprises the steps: obtaining geological detection data, obtaining geological attribute data after preprocessing, and carrying out the continuous and discontinuous type division and quantification of the geological attribute data; based on the quantized geological attribute data, performing multi-source geological attribute correlation analysis to obtain correlation among different geological attributes; the method comprises the following steps: constructing a geologic structure model of a to-be-modeled region, performing unstructured network division on the model by combining correlation among different geologic attributes, and performing geologic unit grid attribute assignment based on 1D + 2D trend chart constraint for each grid region according to acquired different geologic attribute data, thereby constructing a geologic unit attribute model. According to the method, tunnel geological attribute modeling and geological attribute prediction with higher precision and reliability can be realized.

The invention relates to the technical field of geological data processing, in particular to a prospecting method and system based on geological text data, and the method comprises the following steps: obtaining exploration drilling data, extracting lithologic description, mineral composition and fracture filling conditions of a rock core, calculating the correlation index of drilling depth and mineralization thickness, screening the change trend of ore grade, and obtaining the geological text data. And obtaining mining area borehole lithology distribution data. According to the method, by deeply analyzing drilling data and lithologic characteristics, accurately recognizing a mineralized fluid accumulation area and improving the prediction precision of an ore body occurrence position, boundary control of a mineralized zone is optimized through measurement and calculation of spatial homogeneity, the extension precision of the mineralized zone is enhanced, scientific adjustment of a prospecting range is ensured through detailed analysis of altered mineral characteristics, and the method is suitable for large-scale popularization and application. The reasonability of demarcation of the prospecting target area is improved, multi-dimensional data and parameter analysis are integrated, a complete prospecting logic chain is constructed, and mineral product prediction precision and resource exploration efficiency are remarkably improved.

The invention relates to the technical field of oil and gas geological exploration, in particular to an over-mature hydrocarbon source rock parent material type distinguishing method and system.The method comprises the following steps that regional deposition characteristics are studied, an over-mature hydrocarbon source rock deposition environment is recognized, principal elements and microelements are extracted in combination with a geological background, and component relevance is judged; and sorting representative sedimentary environment elements, and establishing a sedimentary environment associated element set. According to the method, accurate recognition of the sedimentary environment is achieved by extracting major elements and trace elements, representative elements are screened, proportional analysis is combined with the macerals, distribution characteristics of saprolite groups, exinite groups and the like are determined, the ratio relation between the macerals and inorganic elements is recognized, a ratio operation set is constructed, and the relation between the macerals and the elements is analyzed in a multi-dimensional mode. The relationship between parent material types and maceral characteristics is disclosed, a maceral type index model is constructed, hydrocarbon source rock parent material type division precision and sedimentary environment analysis systematicness are improved, and a scientific basis is provided for oil and gas resource exploration.

The invention provides an operation control method, system and equipment of a coring drilling machine and a program product. The method comprises the steps that geological information of a construction area is obtained, and geological features are analyzed; constructing rock stratum partitions and predicting the rock stratum depth; configuring partition features and predicting a drilling scheme; constructing a prediction data transmission scheme; controlling the preset coring drilling machine to drill the construction area and obtain actual drilling data, and analyzing rock stratum data from the actual drilling data; and selecting a reference rock stratum partition, and performing operation and data transmission based on the prediction drilling scheme and the prediction data transmission scheme of the reference rock stratum partition. According to the method, accurate prediction of geological information is matched with dynamic adjustment of data transmission, the rock stratum condition is mastered dynamically and accurately, the stability and timeliness of data transmission in the operation process are improved while accurate and efficient operation of the coring drilling machine is guaranteed, most of data analysis and decision-making processes are completed intelligently, and the working efficiency of the coring drilling machine is improved. And the automation level of operation is improved.

The invention relates to the technical field of rock mass earthquake dynamic response, and discloses a layered rock mass earthquake dynamic response multi-scale monitoring system and method, and the system comprises a rock mass three-dimensional geological module, a simulation setting module and an earthquake simulation module. The method comprises the following steps: establishing a layered rock mass three-dimensional geologic model; the method comprises the following steps: identifying a dangerous rock mass structural surface, monitoring slope displacement, and installing sound emission monitoring equipment at a key position to form a three-dimensional monitoring network; a layered rock mass and a broken area in the layered rock mass three-dimensional geological model are divided into discrete element areas, and a continuous medium area is divided into finite difference areas; coupling the discrete element region and the finite difference region; inputting the seismic wave as a dynamic boundary condition into the finite difference region, transmitting a response to the discrete element region through a coupling interface, and simulating a rock stratum and rock mass dynamic fracture process; and the crack propagation particle size and the original stress propagation are transmitted to the cloud platform. The geometric morphology and the internal structure of the rock mass can be accurately reflected.

A method and a system for predicting physical properties of rock are disclosed. The method includes obtaining digital images of drill cuttings and data on drilling parameters and mud gas content and inputting of the obtained digital images of the drill cuttings to a first trained artificial intelligence model to determine the physical properties of a rock matrix and a lithological composition of the drill cuttings. The data on the lithological content of the drill cuttings, the drilling parameters, and the mud gas data are inputted to a second trained artificial intelligence model to determine a total porosity, an effective porosity, and a saturation of rocks. Additionally, the method includes inputting of the data on the total porosity, the effective porosity, and the saturation of the rocks, and the physical properties of the rock matrix to a rock-physics model to determine the physical properties of the rocks.

The invention discloses a surrounding rock structure deformation prediction system based on multi-source information characterization, relates to the field of geology, solves the problem of poor prediction effect of a surrounding rock structure deformation prediction system, and comprises a geological data module which is used for performing regional geological analysis on target surrounding rock and a plurality of sample monitoring surrounding rock to obtain surrounding rock geological data, the engineering data module is used for carrying out engineering quantity analysis on the target surrounding rock and the plurality of sample monitoring surrounding rocks according to the surrounding rock geological data to obtain surrounding rock engineering data, and the data analysis module is used for obtaining surrounding rock prediction analysis data by analyzing the surrounding rock engineering data and the surrounding rock geological data. And the deformation prediction module is used for establishing a surrounding rock deformation prediction model according to the surrounding rock prediction analysis data and performing deformation prediction on the target surrounding rock by using the surrounding rock deformation prediction model. The accuracy and pertinence of a surrounding rock structure deformation prediction result can be improved.

The invention relates to the technical field of data processing, in particular to an engineering geological survey data processing method and system, and the method comprises the following steps: obtaining hole site space positioning and lithologic boundary information, collecting a structure segment sequence, extracting resistance change direction classification disturbance behaviors, recognizing node sequence conflicts, and judging hydrological turning positions. Identifying the corresponding relation between the structural section and the water level track, and generating a structural section water level merging mapping table. According to the method, the spatial information, the lithology identification, the sampling level and the penetration resistance of the drilling structure sections are collected and serialized, disturbance identification and non-sampling section classification are performed based on the resistance change trend between the sections, and node conflicts are identified in combination with the numbering relation and the lithology combination; continuous modeling and classified merging of geological information on the spatial level are achieved, the linkage adaptability of data in a multi-dimensional analysis scene is enhanced, misjudgment interference caused by information isolation is avoided, and dynamic recognition and hydrological response analysis of a geological structure are supported.

Methods and systems are disclosed. The methods may include determining a first sequence of permeabilities by subjecting a rock sample to a first sequence of confining stress, axial stress, pore pressure (CSASPP) triplets and determining a first rock parameter using the first sequence of permeabilities, the first sequence of CSASPP triplets, and a first permeability model. The methods may further include determining a second sequence of permeabilities by subjecting the rock sample to a second sequence of CSASPP triplets and determining a second rock parameter using the second sequence of permeabilities, the second sequence of CSASPP triplets, and the first permeability model. The method may still further include determining an in situ permeability for an in situ rock based on an initial permeability, a second stress sensitivity parameter, a first stress sensitivity parameter, a confining stress value, axial stress values, a pore pressure value, and a second permeability model.

The invention discloses a skarn type deposit three-dimensional metallogenic prediction method, system and equipment and a medium, and relates to the technical field of mineral exploration. The method comprises the following steps: collecting and sorting geological information of a to-be-studied area and a surrounding area; according to the collected information, performing gravity-magnetic three-dimensional physical property inversion and lithology mapping; carrying out gravity-magnetic three-dimensional comprehensive geological modeling by adopting a discrete body inversion method; on the basis of the constructed model, performing three-dimensional metallogenic favorable contrast prediction; constructing a three-dimensional mineralization comprehensive prediction model based on the mineralization favorable degree value; and carrying out target region delineation and verification by using the three-dimensional metallogenic comprehensive prediction model to complete three-dimensional metallogenic prediction under the support of regional gravity and magnetic data. The method has the advantages of wider prediction range, high prediction reliability and the like.

The invention discloses a three-dimensional geological modeling method, system and equipment based on a Markov chain and improved Monte Carlo, and belongs to the technical field of engineering rock geological modeling. On the basis that three-dimensional point cloud data of a rock mass is obtained through three-dimensional laser scanning, Markov chain transition probability matrix calculation is carried out through existing actual drilling and virtual drilling technologies, and then the stratum state of virtual drilling is confirmed based on a superimposed Markov chain. And finally, performing correlation simulation on the stratum thickness corresponding to the stratum state based on an improved Monte Carlo method. Compared with a traditional artificial three-dimensional geologic modeling method, the method can be more comprehensively suitable for engineering rock three-dimensional geologic modeling scenes in various complex scenes; meanwhile, based on the automatically constructed three-dimensional geologic model, the later engineering rock mass stability can be efficiently evaluated, and important data support is provided for rock mass engineering stability evaluation; the method is easy to implement, flexible to operate and remarkable in effect, and the application requirement is met.

The invention provides a quality evaluation method for a geological three-dimensional model, and the method comprises the steps: S11, carrying out the analysis of a historical geological project document, extracting evaluation indexes and data demands, and determining related modeling source data according to the type and target of a geological project; s12, learning an evaluation scheme of a historical successful geological project document, and generating a three-dimensional geological model evaluation scheme containing a verification data range and method; s13, monitoring and analyzing the modeling process of the three-dimensional geologic model based on the three-dimensional geologic model evaluation scheme; s14, determining the weight of each evaluation index in the three-dimensional geologic model evaluation scheme so as to determine the quality grade of the three-dimensional geologic model, and continuously adjusting the weight distribution of the evaluation indexes; and S15, according to the quality grade of the three-dimensional geologic model, determining whether the three-dimensional geologic model meets the acceptance requirement or not. The invention provides a systematic evaluation method for the quality evaluation of the three-dimensional geologic model, thereby promoting the application and development of the three-dimensional geologic model in various fields.

The invention discloses a three-dimensional geological model dynamic updating system and method based on multi-modal data fusion, and belongs to the technical field of geological engineering and information. According to the method, multi-source data of geological radar, earthquake, drilling, remote sensing and the like are integrated, and after unified formatting and quality optimization preprocessing, geological features of a stratum interface, a fault zone and the like are automatically extracted by using a deep learning network; multi-source feature data fusion is realized through space-time registration and attention; constructing a three-dimensional geologic model by adopting a TIN and Octree mixed structure based on a fusion result; dynamic updating of the model is realized through incremental detection and a local reconstruction mechanism, and the boundary of the model is optimized by adopting a radial basis function interpolation. According to the method, the problems of single data, updating lag and the like of a traditional method are solved, the modeling precision and efficiency are remarkably improved, and reliable support is provided for geological engineering decision making.

The invention belongs to the technical field of geological research, and discloses a multi-scale lithofacies identification and sedimentary microfacies reconstruction method and system, and the method comprises the steps: data collection and preprocessing: collecting core data, slice data, logging data and seismic data of a research region; multi-scale lithofacies feature extraction, wherein the multi-scale lithofacies feature extraction comprises micro-scale feature extraction, medium-scale feature extraction and macro-scale feature extraction; constructing and training a multi-scale lithofacies recognition model, constructing the multi-scale lithofacies recognition model by adopting a deep learning algorithm, and taking the extracted microscopic, mesoscopic and macroscopic lithofacies features as input data; multi-scale lithofacies identification: extracting multi-scale lithofacies features from the preprocessed multi-source data; and sedimentary microfacies reconstruction: establishing a lithofacies-sedimentary microfacies conversion relation in combination with a sedimentology principle and a geological knowledge base. According to the method, multi-source data such as rock cores, slices, logging and earthquakes are integrated, lithofacies features are extracted from microcosmic, mesoscopic and macroscopic multiple scales, the features and changes of lithofacies can be comprehensively and accurately reflected, and compared with a traditional single-scale method, the accuracy and reliability of lithofacies recognition are improved.

The invention provides a prospecting method and system based on rock fragmentation degree characterization tectonic stress, relates to the technical field of geological exploration, and aims to solve the problem of low prediction precision of a mining area in the prior art. Comprising the following steps: acquiring image data and sample data of a to-be-predicted region; constructing a first inversion model based on the sample data, and performing inversion on the to-be-predicted region based on the first inversion model and the hyperspectral image to obtain a spectral index of a target geologic feature factor of the to-be-predicted region; the target geological characteristic factors comprise crystallinity, alteration component concentration and weathering degree; performing data fusion on the crack features extracted from the high spatial resolution image and the spectral index of the target geologic feature factor to obtain a feature matrix; inputting the feature matrix into a second inversion model, and determining a target mining area of the to-be-predicted area; the second inversion model is a tectonic stress field inversion model pre-constructed based on the graph convolutional neural network. Therefore, the prediction precision of the mining area can be improved.

The invention provides a large-scale three-dimensional tunnel surrounding rock parameter random field model construction method and system, and relates to the technical field of tunnel surrounding rock modeling, and the method comprises the steps: carrying out the fitting construction of a probability distribution model reflecting surrounding rock parameters; selecting a plurality of surrounding rock parameters as clustering features, quantitatively classifying global geologic structures in tunnel surrounding rocks, and performing global decomposition on a tunnel model into continuous sub-domains containing overlapped buffer areas; for a first sub-domain from any direction of the whole domain of the tunnel model, performing covariance matrix spectral decomposition by adopting a KL decomposition method to generate a first sub-domain random field, and extracting random field values of overlapped regions among the sub-domains as boundary condition data of a recursive generation process; on the basis of the boundary condition data, conditional random fields of subsequent sub-domains are generated layer by layer; and seamlessly splicing the conditional random fields generated by recursion of the sub-fields into a global parameter random field, converting the global parameter random field into probability distribution by adopting a probability mapping method, and performing instruction encapsulation by developing a cross-platform data interface engine to realize a construction process of a parameter random field model.