1179 results about "Assise" patented technology

A stability assessment method of roadway surrounding rock includes: obtaining actual stratum rock parameters; establishing a two-dimensional geological model through numerical simulation based on a drill core columnar diagram and the actual stratum rock parameters; changing influencing factors, and recording amounts and acceleration values of deformation of roadway sidewalls, and whether failure occurs to obtain dynamic response characteristics of roadway surrounding rock, combining the changed influencing factors and the dynamic response characteristics as labels to obtain a dataset, and obtaining multiple datasets including the dataset; dividing the multiple datasets into a training set and a validation set, inputting the training set into a PSO-BP neural network and a GA-SVM deep learning model to obtain a preliminary stability assessment model, and adjusting and validating the preliminary stability assessment model by the validation set to obtain an optimized stability assessment model; and using the optimized stability assessment model to assess roadway stability.

The invention discloses a multi-source collaborative advanced geological exploration method based on TBM construction, and belongs to the technical field of tunnel engineering geological exploration. A three-dimensional geological model is constructed through multi-scale collaborative operation of directional long exploration drilling, branch short exploration drilling and in-hole transient electromagnetic detection; the directional long exploration adopts a secondary drilling structure and a screw motor directional drilling technology to realize accurate control of a deep stratum, the branch short exploration realizes dynamic and rapid verification through a TBM integrated drilling machine, meanwhile, in-hole transient electromagnetic exploration adopts three-component measurement and an intelligent inversion algorithm to fill the blank of geological information between drill holes, and by means of mutual data correction of the three methods, the detection accuracy is improved. A three-in-one detection system of drilling, geophysical prospecting and intelligent analysis is formed, and then accurate advanced prediction is achieved, so that the problems that a traditional single detection technology is low in precision and insufficient in coverage range are effectively solved, the water inrush risk is remarkably reduced, construction safety is guaranteed, and the method is effectively suitable for deep tunnel TBM safety construction.

The invention relates to the technical field of geological exploration, and discloses a water-rich sandy stratum tunnel base settlement prediction method and system, and the method comprises the steps: constructing a multi-source cooperative exploration system; deploying a sanding-seepage-stress coupling model at an edge computing node, and mining the relevance of data of different dimensions through a space-time attention fusion network; based on the prediction matrix and mineral exploitation working condition parameters; when the predicted settlement exceeds a safety threshold value or the sanding expansion rate is abnormal, a high-precision remeasurement mechanism is triggered, and a cross-hole radar and acoustic logging combined verification module is activated; and iteratively optimizing coupling model parameters by adopting a transfer learning algorithm through deviation analysis of measured data and a prediction result. According to the method, a scientific basis is provided for stratum stability evaluation and prevention and control measure formulation in the mineral exploitation process, and the probability of engineering risks caused by base settlement of the water-rich sandy stratum is effectively reduced.

The invention relates to the technical field of underground cavern construction, and discloses a layered rock mass cavern excavation parameter dynamic optimization decision system and method, and the system comprises a rock stratum database building module, an excavation simulation module and an excavation model optimization module. The method comprises the following steps: collecting basic data such as engineering geological conditions, rock mechanical properties and ground stress distribution; establishing an initial rock stratum parameter database through a three-dimensional ground stress test and rock mass permeability characteristic analysis; establishing a stratified rock mass excavation simulation model, simulating a failure mode of a stratified rock stratum under excavation disturbance, and analyzing stress redistribution and a potential failure area; determining a cavern axis direction, an excavation sequence and support parameters according to a simulation result; acquiring surrounding rock deformation, loosening circle expansion and seepage characteristic change; and utilizing a damage proximity index to predict the distribution of the loose circles, and optimizing the stratified rock mass excavation simulation model. The method can adapt to various complex working conditions from a sand shale interbed to an ultra-deep fractured stratum and the like.

The invention discloses a three-dimensional geologic model modeling method and device. The three-dimensional geological model modeling method comprises the following steps: acquiring to-be-established geological region data and actual geological boundary data; generating an initial stratum interface grid according to the to-be-established geological region data; correcting the initial stratigraphic interface grid to obtain a corrected stratigraphic interface grid; carrying out geological rule constraint on the corrected stratigraphic interface grid so as to form simple three-dimensional stratigraphic interface model data; correcting the simple three-dimensional stratigraphic interface model data according to the seismic profile information so as to obtain a composite geologic structure model; generating a three-dimensional fault plane model according to the composite geologic structure model; and generating a composite geological structure model including a fault network according to the three-dimensional fault plane model and the composite geological structure model. Through the three-dimensional geological model modeling method, the deviation between the model and an actual geological boundary can be remarkably reduced.

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 sandy stratum tunnel water burst risk prediction method. The method comprises the steps that a radar instantaneous energy spectrum in front of tunneling is obtained through a geological radar, a micro-seismic spectrum is obtained through a micro-seismic array, and a residual distance is obtained through laser ranging; aligning and coupling the two spectrums to obtain a water inrush risk index, inputting the water inrush risk index and the residual distance into a self-adaptive threshold comparator, and if the water inrush risk index and the residual distance exceed the limit, dynamically adjusting the rotating speed of a cutter head, propulsive force, the rotating speed of a screw conveyor and grouting pressure, and generating a risk avoidance path; and calling a water inrush risk model library constructed by LSTM-Attention, inputting a risk index sequence, a residual distance, cutterhead torque, a soil pressure gradient, a current change rate and other auxiliary variables, and outputting a future multi-step risk level. According to the method, accurate prediction and real-time avoidance of the water gushing risk of the sandy stratum tunnel can be realized, and the safety and efficiency of tunnel construction are improved.

The invention relates to the technical field of geotechnical engineering disaster monitoring and early warning, and discloses a stratum rainfall seepage deformation coupling numerical simulation method and system and a storage medium, and the method comprises the steps: building a three-dimensional geologic model reflecting soft and hard rock interbed characteristics; converting the on-site rainfall data into hydraulic boundary conditions in real time; calculating a rock mass shear expansion volume change rate, determining a chemical damage acceleration factor, and updating a total damage variable; reconstructing a permeation tensor representing the dominant flow channel according to the space gradient of the damage variable; solving a fluid-solid coupling equation based on the permeability tensor, obtaining pore water pressure and calculating a displacement field; building a likelihood function by using field monitoring data to perform inversion correction on model parameters; and evaluating the stability based on the corrected calculation result and outputting an early warning signal. By constructing a mechanical coupling mechanism and a dominant flow channel model, precise simulation of a landslide evolution process in a complex geological environment is realized.

A method can include rendering a graphical user interface to a display; receiving data; responsive to determining boundary locations for formations in the subsurface environment using the data, automatically rendering the boundary locations in the graphical user interface; responsive to determining extended boundary locations in the subsurface environment for a region beyond an end of the borehole using the boundary locations, automatically rendering the extended boundary locations in the graphical user interface; responsive to determining a target location in the region using the extended boundary locations, automatically rendering the target location in the graphical user interface; and, responsive to generation of a trajectory from an end of the borehole location to the target location, automatically rendering the trajectory in the graphical user interface.

The invention belongs to the technical field of geological engineering monitoring and multi-physics field intelligent sensing, and discloses a separation grouting slurry migration monitoring method and system, and the method comprises the steps: constructing an acoustics-optics-electricity-electromagnetism multi-physics field coupling monitoring system; a grouting hole and a monitoring drilling hole array are arranged in a target stratum, a distributed optical fiber sensor, a drilling hole ultrasonic imager, a resistivity measuring device and a transient electromagnetic detection device are installed, and a three-dimensional monitoring network is formed; synchronously acquiring sound field, light field, electric field and magnetic field data; four-field monitoring data and overlying strata multi-parameter observation data are fused, a coal seam mining three-dimensional overlying strata separation model is constructed, and a slurry diffusion three-dimensional visualization model is generated through numerical simulation; and based on the four-field monitoring response difference of the separation space before and after grouting, in combination with a monitoring frequency domain correction model of multiple indexes of grout diffusion, the diffusion range, compactness and filling effect of the grouting grout are evaluated, and abnormal early warning is triggered.

The invention relates to a deep stratum well hole and cave mining system and method, the system comprises a traffic well hole system, the traffic well hole system is provided with at least one well hole smaller than 1 m, an internal channel formed by the well hole is communicated with a cave formed by excavation, and the internal channel formed by the well hole is configured to be a flow-back channel and / or an injection channel; the well hole and cave mining device is provided with a crushing assembly and / or a cleaning and transporting assembly, the crushing assembly is used for carrying out form-controllable mining on the ore on the cave rock wall surface, and the cleaning and transporting assembly is used for cleaning ore particles in the cave or transporting the ore particles to the flowback channel; and the particle flow lifting system is used for lifting the extracted ore particles out of the well through the flow-back channel. The technical problems that when caves of deep stratums are mined, the supporting effect is poor, and the ore particle clearing and transporting efficiency is low are solved, and large-scale and high-efficiency mining operation can be conducted on the deep stratums or non-hard stratums.

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.

Systems and methods include obtaining well log data and core sample data of a subsurface formation; generating, based on the well log data and the core sample data, an unconfined compressive strength log for the subsurface formation; using an unsupervised machine learning model to form rock type clusters based on the unconfined compressive strength log and the well log data; forming a training dataset including the well log data, the training dataset labeled based on the rock type clusters; training a supervised machine learning model using the training dataset. While drilling a well in the subsurface formation, logging-while-drilling data is obtained from drilling equipment used to drill the well; and rock types in the subsurface formation are determined using the supervised machine learning model and the logging-while-drilling data.

The invention discloses a water-rich composite stratum tunnel surrounding rock deformation identification method, and relates to the technical field of tunnel engineering, and the method comprises the following steps: collecting stratum information and hydrological data in a geological exploration stage, and on-site monitoring data in a construction stage, carrying out the cleaning and normalization processing of the data, constructing a training set of a random forest model, and carrying out the recognition of the deformation of the tunnel surrounding rock. Training a random forest model by using the training set to obtain a trained surrounding rock deformation classification model; and by means of the trained surrounding rock deformation classification model, current to-be-identified surrounding rock data are analyzed, first deformation data are obtained, and the first deformation data represent the preliminary tendency of surrounding rock deformation. Through the strong classification capability of the random forest model, the preliminary judgment of the surrounding rock deformation tendency is realized, the judgment accuracy and efficiency are improved, the weighted scoring method and the Bayesian network algorithm are adopted to carry out preliminary judgment and detailed judgment, the multi-source data are effectively integrated, and the judgment precision is improved.

The invention discloses a soft rock TBM jamming risk intelligent prediction method based on numerical mechanism guidance, and the method comprises the following steps: S01, building an extrusion soft rock stratum TBM dynamic tunneling whole process refined numerical simulation model which comprises a TBM cutterhead, a front, middle and tail step shield, soft rock, a segmental lining and a backfill material behind a wall, and simulating an evolution process; s02, systematically calculating and analyzing surrounding rock geological parameters, TBM tunneling parameters, TBM construction parameters and TBM construction parameters, and constructing a machine blocking index numerical value sample library; s03, predicting the large deformation of the soft rock and the extrusion load of the shield, fusing TBM rock-machine interaction multi-source data in actual engineering, and establishing a soft rock TBM jamming risk intelligent prediction model; and S04, evaluating the TBM jamming risk, and verifying the effectiveness of the prevention and control measures. According to the technical scheme, the whole process of dynamic interaction between the TBM and the soft rock can be comprehensively considered; the TBM jamming disaster occurrence mechanism is explained, and the generalization ability of the machine learning method in practical application is improved.

The invention provides a method for preferably selecting a shale gas structure storage favorable area not based on formation pressure. The method comprises the steps that a target research area is selected, and a core exploration target layer series is determined; on the basis of a target stratum shale gas preservation mechanism, core parameters independent of stratum pressure data are screened, and a comprehensive evaluation index system containing target stratum self-sealing performance, regional cover stratum conditions and structural transformation action parameters is constructed; spatial distribution analysis is carried out on each parameter, grading is carried out according to geological laws and adjacent region experience, and weight coefficients are distributed according to the influence degree of the parameters on storage conditions; obtaining a comprehensive score of the structure storage condition of each evaluation unit through grade assignment and weighted stacking calculation; and delineating a shale gas structure storage favorable area according to the comprehensive score. The method is suitable for low-exploration-degree areas with complex structures, sparse drilling wells or lack of formation pressure data, and has the advantages of objective evaluation, high operability and high practical value.

The invention provides a three-dimensional surface matrix modeling method based on multi-source data, and the method comprises the steps: calculating a preset interval based on geological profile data, drilling density, terrain curvature and other information, and extracting and estimating virtual drilling data in an area with insufficient original drilling data; the generation of the virtual drill hole effectively fills up the data blank, enriches the drill hole data set, enables the model construction to more comprehensively and accurately reflect the stratum characteristics, and greatly improves the data integrity and the adaptability of the model to the complex geological area. The accuracy of the model is dynamically judged by setting a standard deviation threshold value, and when the standard deviation of the error matrix exceeds the threshold value, the optimization process of the model is triggered, including T IN grid reconstruction and GNN parameter updating; the self-adaptive optimization mechanism can enable the model to be continuously adjusted to adapt to the characteristics of actual geological data, and the precision and reliability of the model are improved.

Methods and systems are provided for predicting thermal properties of a subsurface rock formation. A training dataset is derived from petrophysical properties of a plurality of formation rock samples and thermal properties of the plurality of formation rock samples. The training dataset is used to train a machine learning model that predicts label data representing the predefined set of thermal properties given input data representing the predefined set of petrophysical properties of an arbitrary formation rock sample. The machine learning model can be validated and deployed for use in predicting thermal properties of subsurface rock formations.

The invention relates to a tunnel three-dimensional line selection design method based on geological intelligent evaluation, and the method comprises the steps: obtaining the geological exploration data of a tunnel line selection section, and constructing a drilling information database; based on the drilling information database, a pre-trained single stratum excavation benefit evaluation model is adopted for benefit evaluation, and the excavation benefit score of each single stratum is obtained; based on the drilling information database, virtual drilling data are introduced, and a three-dimensional geologic model is constructed; based on the three-dimensional geologic model, performing benefit evaluation on the adjacent GTP voxels by adopting a pre-trained adjacent stratum excavation benefit evaluation model to obtain excavation benefit scores of the adjacent stratums; and constructing an underground existing structure model, superposing the underground existing structure model to the three-dimensional geologic model, and performing comprehensive evaluation according to the excavation benefit score of each single stratum and the excavation benefit score of the adjacent stratum to obtain a final three-dimensional line selection scheme. Compared with the prior art, the method has the advantages that various factors are considered, and the path is optimal.

The invention provides an intelligent prediction method and system for settlement of a TBM penetrating through a pebble stratum, and belongs to the technical field of stratum settlement prediction. The method comprises the following steps: acquiring ground surface monitoring point position information, excavation surface position information and burial depth, inputting the information into a first deep neural network model, and acquiring and outputting tunnel vault displacement, haunch convergence and ground surface settlement; the second deep neural network model takes a position coordinate formed by earth surface monitoring point position information, excavation surface position information and burial depth and earth surface settlement as input, and outputs earth surface elastic modulus and Poisson ratio; obtaining stress-strain components of ground surface settlement, and constructing a control equation and boundary conditions based on the stress-strain components, the elastic modulus and the Poisson's ratio; obtaining prior geological information by using the residual error of the control equation; and by taking the control equation, the boundary condition and the prior geological information as constraint conditions, obtaining a settlement prediction value when the TBM passes through the pebble stratum based on the tunnel vault displacement, and realizing accurate prediction of the settlement of the pebble stratum.

The invention provides a method and a device for constructing a three-dimensional digital geological model. The construction method comprises the following steps: constructing a geologic model area range and discretizing the geologic model area range into n unit lattices; mapping the drilling data to n unit lattices to construct an initial geological model; constructing a neighborhood system of each unit lattice, and setting spatial constraints in seven directions; based on the label value of each unit lattice in the initial geologic model, obtaining a prediction result comprising M sampling label values of each unknown unit lattice according to a label probability prediction formula and an updating iteration formula of a granularity coefficient; based on the prediction result, obtaining the marginal probability of each unknown unit lattice and the prediction label value of each unknown unit lattice; and updating the initial geologic model based on the predicted label value of each unknown unit lattice, and constructing a three-dimensional digital geologic model. The three-dimensional digital geologic model constructed by adopting the construction method is accurate in simulation result and can represent the uncertainty of the stratum at the same time.

The invention discloses a method and system for evaluating rock drillability in real time, and the method comprises the steps: determining a well section with logging data and element logging data at the same time in a target area, and obtaining a rock drillability grade value through the logging data; selecting element types conforming to geological characteristics of a current target area from the element logging data to form optimal element combination data of a corresponding stratum matched with the optimal element types, and based on the optimal element combination data, performing data fitting on a preset multiple regression model in combination with rock drillability levels to obtain a drillability level calculation model; the current drillability grade value calculation model is corrected by utilizing a rock core taken from a target stratum to obtain an experimental rock drillability grade value; and optimal element combination data of a target stratum is obtained in real time in the drilling process, and a dynamic rock drillability grade value is obtained by using the corrected drillability grade value calculation model, so that a rock drillability real-time evaluation result is obtained. According to the invention, real-time evaluation of the drillability of the rock is realized.

The invention discloses a boulder dense stratum geological radar detection method based on horizontal directional drilling, which comprises the following steps of: firstly, drilling into a stratum from the earth surface at a smaller incidence angle by adopting the horizontal directional drilling, and drilling along the central axis of a shield tunnel to form a drill hole with the diameter of about 30cm; after drilling is completed, the geological radar is fixed to the rear portion of the drill bit through a rigid connecting device, and the geological radar synchronously advances and rotates along with the drill bit. Four rolling balls are arranged at the bottom of the geological radar to reduce motion resistance and are tightly attached to the inner wall of a drill hole to ensure detection stability. The geological radar is driven by rotation of a drill bit to rotate by 360 degrees for detection, so that stratum information around a drill hole is obtained; then, performing image recognition on drilling slag, and establishing a corresponding relation between a geological radar image and a stratum type so as to optimize interpretation precision of geological radar data; and finally, in combination with geological radar detection data and a drilling deslagging analysis result, generating a boulder distribution profile map, and predicting the boulder distribution condition on the tunneling path of the shield tunneling machine.

The invention discloses a real-time multi-objective optimization decision-making method for shield tunneling parameters based on multi-mode NSGA-II (Non-dominated Sorting Genetic Algorithm-II) and LSTM (Long Short Term Memory). Comprising the following steps: acquiring a plurality of data sets, training a constructed shield tunneling parameter prediction model and a tool abrasion loss model, acquiring a tunneling parameter time sequence to be measured and a geological parameter time sequence, and inputting the tunneling parameter time sequence and the geological parameter time sequence into the shield tunneling parameter prediction model to obtain a tunneling parameter prediction value, inputting the tunneling parameter prediction value into a tool wear loss model to obtain a wear loss prediction value of each tool; constructing and solving a tunneling parameter multi-objective optimization model to obtain an optimal solution set of tunneling parameters; and performing minimum similar distance processing according to the optimal solution set, the tunneling parameter prediction value and the wear loss prediction value of each cutter, and taking the to-be-set tunneling parameter corresponding to the minimum similar distance value as the finally-set tunneling parameter at the current moment. According to the method, self-adaption to the geological condition of the tunneling stratum is achieved, the comprehensive tunneling performance of the shield is improved, and the total tunneling time and the construction cost in engineering are saved.

Methods and systems are disclosed. The method may include obtaining a first plurality of hydrocarbon source rock samples from a first well and a second plurality of hydrocarbon source rock samples from a second well, each well penetrating a portion of a subterranean region. For each of the first and second plurality of samples obtaining a set of kinetic parameter values, including a discrete distribution of activation energy and a common frequency factor and determining a weighted average activation energy value from the distribution. The method may further include identifying a first chemostratigraphic segment of the first well and a second chemostratigraphic segment of the second well, each based on the weighted average activation values; determining a correlated stratigraphic unit and mapping organofacies based on the first the second chemostratigraphic segments; and predicting hydrocarbon generation, retention and expulsion and determining a drilling target within the correlated stratigraphic unit.

The invention discloses a stratigraphic water content layering inversion method based on a shallow seismic full waveform, and relates to the technical field of geophysical exploration data processing, and the method comprises the following steps: 1, under the same survey line condition, synchronously obtaining a seismic wave full waveform, complex impedance and an induced polarization frequency spectrum; 2, constructing a layered initial model containing a layer boundary line and an in-layer water content initial value; based on the layered initial model, executing dual-domain quantile alignment interface keeping iteration until convergence, and obtaining a final layer boundary line and an in-layer water content field; the double-domain quantile alignment interface maintaining iteration comprises the following steps: updating an in-layer moisture content field and a layer boundary line according to a seismic wave full waveform; and performing total variation regularization processing on the updated in-layer water content field to maintain the transition characteristic of the layer boundary line. According to the method, an efficient and reliable solution with actual guidance value is provided for mineral resource exploration, geological structure detection, groundwater survey and engineering geology evaluation.

The invention discloses a tunnel high-pressure gushing water comprehensive treatment method integrating probing, guiding, blocking, discharging and fixing, and belongs to the technical field of tunnel construction. The method comprises the following steps: exploring and dividing geological subsections; drainage: drilling a water diversion hole in the concentrated water gushing channel, and pre-burying a multi-stage drainage pipe for graded pressure reduction; blocking is conducted, specifically, the channel is closed through a layered pressure backfill grouting technology; a permanent drainage system is laid, and a deep drainage pipe is connected; reinforcement is carried out, and radial consolidation grouting and groove jumping type inverted arch dismounting and replacing are carried out; and the whole process is monitored in real time, and construction is dynamically optimized. According to the method, exploration, drainage, plugging, drainage, reinforcement and dynamic regulation and control are organically combined, the problems that water plugging, pressure reduction and cooperation are difficult in high-pressure water-rich karst stratum tunnel gushing water treatment are solved, and the method has the advantages of being prominent in systematicness, thorough in treatment, remarkable in pertinence, safe, controllable, novel in process, reliable in quality, dynamic in regulation and control, high in adaptability, obvious in comprehensive benefit and the like.

The invention relates to the technical field of grouting tests, in particular to a three-dimensional high-pressure splitting grouting test method, which comprises the following steps: laying a rock mass sample in a large cubic test box, and applying a stable three-dimensional stress field to the sample in three directions by using a multi-hydraulic cylinder array; grout is injected in a stress maintaining state, grouting pressure, grouting flow and hydraulic cylinder data are synchronously collected to generate a pressure-flow-time relation curve, and meanwhile the grout diffusion process is directly observed through a visual window. According to the method, boundary interference is effectively reduced through a large-size sample and uniform loading, so that slurry is naturally diffused in a stress environment close to a real stratum. The dynamic stress compensation technology maintains boundary stability, and ensures that splitting expansion is not influenced by artificial constraint. A pressure-flow-time curve is combined with visual observation, and the diffusion rule of slurry in a three-dimensional stress field is clearly presented. According to the method, a test means closer to reality is provided for the underground engineering grouting process, and the reliability of grouting parameter design is remarkably improved.

The invention belongs to the technical field of sandy ground grouting regulation and control, and relates to a dolomite sandy ground tunnel high-pressure curtain grouting regulation and control method and system. According to the method, the fuzziness and the uncertainty of single sensing information when complex geological conditions are judged and recognized are overcome by generating the sanding rate grade map and the splitting early warning signal, and the accuracy of stratum state sensing is improved; a dynamic linkage mechanism among stratum states, risk early warning, slurry parameters and grouting parameters is established, the slurry proportion and the grouting pressure are automatically and differentially regulated and controlled according to the sanding grade, and optimal matching of the slurry property and stratum requirements and dynamic balance of safety and efficiency are achieved; the formation condition of the curtain is mastered in real time through grouting effect real-time imaging and closed-loop feedback regulation and control, the construction scheme is continuously optimized according to objective data, the uniformity, continuity and overall quality of high-pressure curtain grouting of the sandy stratum tunnel are ensured, and meanwhile material waste and construction period delay are avoided.

The invention provides a tight sandstone gas reservoir formation water division method based on mercury intrusion and online nuclear magnetic resonance, and relates to the field of gas reservoir formation water production, and the method specifically comprises the following steps: obtaining a tight sandstone core standard rock sample; cutting the rock core into two sections, and performing a high-pressure mercury injection experiment on the first section of the rock core; and scanning the nuclear magnetic resonance signal T2 spectrum curve of the rock core in the completely saturated water state and the area of the nuclear magnetic resonance T2 spectrum curve. And carrying out gas drive and nuclear magnetic scanning experiments. And sequentially increasing the displacement pressure differences to obtain a nuclear magnetic resonance correction curve under different displacement pressure differences. And drawing a water saturation and displacement pressure difference relation curve, and defining the critical pressure difference of different types of formation water production according to the curve form and the slope change rule. And processing the data to obtain the formation water production rule of the tight sandstone gas reservoir in different states. According to the technical scheme, the problem that in the prior art, the critical output pressure difference and the dynamic output rule of various types of formation water in different pore diameter ranges cannot be quantitatively represented is solved.