353 results about "Reservoir capacity" patented technology

The invention discloses a grating dam safety evaluation and design method and structure based on debris flow blocking degree. Wherein the safety assessment method comprises the following steps: S100, calculating the safety of the debris flow on the basis of the solid matter concentration of a debris flow susceptible area, the particle size value corresponding to the accumulated content of 95% in a full particle size grading curve, the channel average gradient, the channel average width and the primary debris flow scale in the section range of the grating dam, the minimum particle size value of the maximum boulder in the drainage basin and the opening width of the grating dam; calculating a critical blocking judgment coefficient according to the correlation value of the height of the grating dam, the angle of the wedge-shaped structure and 60 degrees and the correlation value of the total amount of debris flow solid substances and the reservoir capacity of the wedge-shaped beam type grating dam; and S200, evaluating the safety of the grating dam based on the critical blocking discrimination coefficient. The evaluation and design method and structure incorporate the relative relation between the debris flow scale and the dam body storage capacity, meanwhile, the influence on active structure parameters such as wedge-shaped flow guide is quantified, and the blocking state prediction accuracy of the grating dam in actual operation is improved to a certain degree.

A method for reducing the danger of a dammed lake formed by a debris flow blocking a river, comprising: first predicting the accumulation range of a river-blocking debris dam during occurrence of a debris flow, dividing a river boundary into multiple areas on the basis of the elevation, and then performing roughness reduction treatment on the areas of the river boundary during a dry season. The present method reduces the roughness of a river boundary within the accumulation range of a river-blocking debris dam, so as to reduce the opposite bank dam height of the river-blocking debris dam and the storage capacity of the dammed lake, thereby achieving the purpose of reducing the danger of dammed lakes formed by debris flows and reducing the impact of debris flow disasters.

A cascade reservoir optimization dynamic control method based on different scheduling objectives of flood season staging comprises the following steps: step 1, performing flood season staging on a cascade reservoir based on rainstorm flood characteristics, and establishing a pre / main flood season'flood control-power generation 'and post flood season'flood control-water storage' optimization scheduling model; step 2, constructing a cascade reservoir dynamic control domain; step 3, based on the flood season staging result in the step 1 and the cascade reservoir dynamic control domain constructed in the step 2, constructing an optimization model taking the maximum cascade generating capacity and the minimum flood control risk as targets; setting constraint conditions of the optimization model; and solving the optimization model through a multi-target intelligent optimization algorithm to obtain a dynamic scheduling scheme. According to the method, optimal scheduling methods such as flood season staging and'aggregation-decomposition 'are adopted, flood control risks of drainage basin reservoir group scheduling are fully considered, and efficient utilization of cascade reservoir water resources is realized by utilizing a cascade reservoir flood control capacity complementation mechanism.

The embodiment of the invention provides a reservoir capacity dynamic monitoring method and system based on an unmanned aerial vehicle, and the method comprises the steps: obtaining a reservoir surface feature data set through the unmanned aerial vehicle, determining the boundary of a water area, scanning the bottom of the reservoir, obtaining the underwater terrain elevation and sediment distribution data, and constructing a three-dimensional terrain model; and determining terrain and deposit change data based on the three-dimensional terrain model dynamic change data of the continuous time sequence. Sedimentation space distribution characteristics are obtained through change rate analysis, and the sediment transportation amount and the sedimentation and deposition space rule are determined in combination with the water flow speed. Key driving factors are screened through correlation analysis, a sedimentation high-risk area is determined according to the key driving factors, and the change of sediments in the area is monitored, so that the change of the reservoir capacity is mastered. The reservoir siltation can be accurately and dynamically monitored, the high-risk area and the change mode are defined, the dynamic database is constructed to update the capacity change in real time, and important technical support is provided for reservoir management and flood control and disaster reduction.

The invention relates to the field of multi-energy coupling complementary scheduling, and discloses a successive approximation random dynamic planning method for a watershed water-wind-light integrated system, and the method comprises the steps: 1, inputting the description of uncertainty; a plurality of characteristic discrete values are sampled from theoretical probability distribution functions of runoff, photovoltaic output and wind power output to represent known continuous probability distribution, and uncertainty of input of the watershed water-wind-light integrated system is described; 2, solving a transition probability matrix; describing the continuity of an input variable time sequence by adopting a simple discrete time Markov chain; 3, considering an objective function and constraint conditions of the watershed water-wind-light integrated system, and constructing a complementary optimization scheduling model; 4, solving by adopting a successive approximation-random dynamic programming method (SDP-SA), and deducing a scheduling rule, namely a scheduling decision table, of the watershed water-wind-light integrated system by taking the time period initial storage capacity, runoff, photovoltaic output and wind power output scenes of the adjustable reservoir in each stage of sub-complementary system as multi-dimensional state variables and the time period final storage capacity as a decision variable; and 5, when an actual inflow condition occurs, looking up the scheduling decision table to perform interpolation calculation according to the reservoir capacity and the inflow condition of the current sub-complementary system and the wind power output and the photovoltaic output which are obtained by forecasting in the period of time, obtaining the reservoir capacity at the end of the period of time, and completing an optimal scheduling decision.

The invention provides a productivity evaluation method for a tight gas reservoir horizontal well, and relates to the technical field of tight gas reservoirs, and the method comprises the following steps: obtaining well logging sensitive parameters and rock mechanical parameters of the tight gas reservoir horizontal well; based on the logging sensitive parameters and a comprehensive index model, comprehensive indexes corresponding to different reservoirs in the horizontal well are calculated; based on the comprehensive index, the logging sensitive parameter and the rock mechanical parameter, determining a geological dessert level and an engineering dessert level corresponding to the reservoir; and carrying out productivity evaluation on the horizontal well based on the geological dessert level and the engineering dessert level corresponding to the reservoir. Therefore, the geological sweet spots can be accurately identified based on different data dimensions through the comprehensive indexes determined by the logging sensitive parameters having great influence on lithology and the logging sensitive parameters, collaborative evaluation is performed through the geological sweet spots and the engineering sweet spots, the reservoir capacity and the transformation capacity of the reservoir capacity are considered at the same time, and the accuracy of capacity prediction is remarkably improved.

The invention discloses a reservoir level prediction method based on reservoir capacity curve decoupling. The reservoir level prediction method comprises the following steps: 1, forming a sample set by a historical water level and a reservoir capacity sequence; 2, fitting a water level-reservoir capacity curve by using a polynomial; 3, solving an optimal fitting coefficient through a least square method, and establishing a relation curve; 4, calculating the reservoir capacity change in the rainfall period; 5, obtaining a rainfall net contribution amount; 6, calculating a theoretical response water level; 7, collecting historical data and selecting a core predictive factor; and 8, constructing and calibrating a water level prediction model. According to the method, the model which is clear in physical significance, easy and convenient to calculate and high in prediction precision is constructed, reliable technical support is provided for refined scheduling and flood prevention decision making of the reservoir, and therefore the problems that in an existing reservoir water level prediction model, a physical mechanism model is complex in structure, high in data dependence and low in calculation efficiency are solved; and a data-driven model is poor in interpretability, easy to be interfered by data noise and uncertain in generalization ability.

The invention relates to a cascade reservoir flood control capacity collaborative optimization method and system based on a dynamic game, and belongs to the technical field of hydropower station group flood control regulation and storage. Comprising the following steps: collecting a historical water level sequence, upstream flood discharge flow, drainage basin rainfall confluence data, radar flow measurement data, dam body stress indexes and dynamic correlation parameters of a cascade reservoir group, inputting the collected data into a space-time risk field model, and constructing a space-time risk field; constructing a game model based on the space-time risk field, taking an upstream reservoir as a leader to formulate a reservoir capacity allocation strategy, taking a downstream reservoir as a follower to dynamically adjust a flood discharge scheme according to the leader strategy, and coordinating a flood control target and an economic target through a time-varying game weight; solving the game model by adopting an improved distributed ADMM optimization algorithm to generate a scheduling instruction, and verifying the legality of the scheduling instruction through a block chain smart contract; and pre-executing the scheduling instruction in the digital twin simulation platform, dynamically calibrating the mapping parameters of the physical reservoir and the virtual mirror image through reinforcement learning, generating a final scheduling instruction, and issuing and executing the scheduling instruction.

The invention discloses an analysis method and system for reservoir group sediment collaborative scheduling and space-time simulation. The method is based on a water-sediment coupling simulation model integrated based on collaborative desilting schemes: setting a simulation scene, and setting a collaborative scheduling scheme combination; executing long-series dynamic simulation, and simulating the dynamic response of the reservoir group under the combined action of the water and sediment input and the scheduling scheme; outputting a time sequence result, a spatial distribution result and a morphological evolution animation; defining a multi-objective optimization function, automatically adjusting key parameters in the scheduling scheme by adopting a multi-objective optimization algorithm, and searching a Pareto optimal solution set; and based on the Pareto optimal solution set, selecting a final scheduling scheme according to a preset decision, and outputting a specific scheduling instruction. According to the method, the space-time evolution and the desilting benefit of the siltation form under different scheduling schemes are accurately quantified, the method has engineering feasibility and can be suitable for collaborative desilting, reservoir capacity maintenance and comprehensive benefit improvement of cascade reservoirs, the engineering life is prolonged, and regulation and control of water and sediment in a drainage basin are optimized.

The invention provides an automatic operation control method for a low-dam hydropower station. The method comprises the following steps: preprocessing collected water level and incoming water flow data; a reservoir capacity dynamic calculation model is constructed in combination with the reservoir capacity curve graph and the water level flow data, and dynamic updating of reservoir capacity data is achieved; historical hydrological data, current water level flow and reservoir capacity data are fused to train a machine learning model, and the reliability of short-term inflow prediction is improved; based on the safe operation threshold value, the reservoir capacity data and the incoming water prediction result are input into a multi-objective optimization algorithm, a generator set power adjustment strategy and a flood discharge gate opening degree regulation strategy are automatically generated, and the generator set operation power and the flood discharge gate opening degree are automatically controlled, so that the problems that in the prior art, a low-dam hydropower station is low in automation degree and high in efficiency are solved. And manual adjustment is relied on.

The invention discloses a double-layer optimization method and system for real-time flood control scheduling of a series reservoir group. The method comprises the steps that the maximum feasible impounding boundary of each time period is calculated based on the discharge capacity and storage capacity constraint of each reservoir; constructing a space-time risk response kernel matrix, encoding lag response and attenuation intensity of flood routing, constructing a dynamic risk potential energy index in combination with real-time reservoir capacity, and solving space distribution water quantity of each reservoir by taking minimization of the index as a target under physical boundary constraint; the space distribution water quantity is used as a guide target, an evolutionary algorithm embedded with a physical consistent projection operator is adopted, and iterative optimization is carried out on hourly output flow of each reservoir. According to the method, through matrix coding of the space-time risk and introduction of manifold projection solution, the problem that upstream and downstream hydraulic space-time coupling and strong physical constraint are difficult to solve is effectively solved, and the physical consistency and peak clipping efficiency of a scheduling scheme are improved.

The invention discloses a river and lake regulation and storage system flood routing intelligent forecasting method based on a dynamic storage and discharge relation, and the method comprises the steps: constructing a space-time dynamic association diagram structure which reflects the waterpower relation of a drainage basin, and mapping multi-source hydrological data to generate a model input set with a unified space-time scale; establishing an aggregation reservoir parameterized structure model which comprises a dynamic water level-reservoir capacity relation driven by inflow change characteristics and a composite water level-flow relation integrating a time lag effect and backwater jacking feedback; constructing a flood regulation calculation equation set, and according to the real-time delay state in the composite relationship, adopting an adaptive solution mechanism to switch among different algorithm channels so as to solve the equation set; and correcting the model state by using the real-time observation data and executing rolling prediction. The method effectively solves the problems that in a complex river and lake system, dynamic characteristics of the storage and discharge relation are difficult to depict, the non-in-phase evolution process is unstable to solve, and high-dimensional parameters are difficult to calibrate, and the continuity and physical consistency of flood forecasting are improved.

The invention provides a reservoir water level real-time monitoring and early warning system and method based on the Internet of Things, and the method comprises the steps: extracting credible water level time sequence information from the water level monitoring data of a target reservoir dam body, and determining the potential risk intensity of the target reservoir dam body under the water level change according to a preset sliding time window in combination with the credible water level time sequence information; the potential risk intensity is input to a preset water level early warning unit, the water level early warning unit is synchronously connected into a reservoir capacity-pressure distribution diagram deduced by the hydrological model in real time, and a safe bearing boundary of the target reservoir dam body structure under the current water level is determined according to the reservoir capacity-pressure distribution diagram; determining a water level grading early warning value of the target reservoir dam body under the current water level according to the safety bearing boundary in combination with the potential risk intensity; and sending a water level grading early warning signal of the target reservoir dam body to a reservoir management terminal based on the water level grading early warning value. According to the technical scheme provided by the invention, water level grading early warning can be carried out under the time-varying risk caused by accumulative damage of the dam body structure of the reservoir.

The present invention relates to the technical field of sediment or sludge treatment of a water body, and provides a solidification material and a use thereof. The solidification material consists of the following components in percentage by mass: 30% of a sediment flocculant, 20% of a high-strength and high-water-resistant earth consolidator, 30%-40% of calcium bentonite, 5%-15% of a clay mineral, and 5% of an engineering admixture. When the solidification material is used in the sediment or sludge treatment of the water body, pollutants in sediments can be well immobilized, and as tested, no leaching of the pollutants occurs after immersion in the water body. Moreover, the usage amount of the solidification material is significantly reduced compared to that of a conventional solidification material, so that the impact on the storage capacity of the water body can be effectively reduced, and the construction cost is also saved.

The invention relates to the technical field of underground hydrology monitoring, and discloses an underground reservoir capacity prediction system capable of monitoring the water level of a drill hole in real time, which is suitable for dynamic capacity prediction and over-mining early warning management of a layered pore type underground reservoir. The data acquisition module is used for acquiring underground water level, water quality parameters, replenishment amount environment temperature and humidity, water pressure and geological vibration data in real time through multiple types of sensors; the Internet of Things platform is in communication connection with the data acquisition unit and is used for preprocessing and transmitting the data acquired in real time; the visualization unit is connected with the data acquisition unit and the Internet of Things platform and is used for constructing and rendering a three-dimensional twinborn body of the underground reservoir; and the system function unit is connected with the data acquisition unit, the visualization unit and the Internet of Things platform, and is used for performing intelligent analysis, water level prediction model generation, user side interaction control and system resource management on the preprocessed real-time acquired data. The hysteresis problem of traditional manual monitoring is solved, and the timeliness of monitoring is improved.

The invention discloses a reservoir capacity prediction method considering underlying surface change conditions, and aims to solve the problems that the prediction value of an existing scheme is too large, deviation exists between the estimated reservoir capacity and the actual reservoir capacity, the functions of flood control, water supply, irrigation and the like of a reservoir are affected, and the economic benefits of the reservoir are directly affected. The method comprises the following steps: acquiring actually measured water and sediment series data of a reservoir in historical periods, analyzing the reservoir water and sediment change trend, determining reservoir runoff and reservoir sediment abrupt change points in combination with underlying surface factor changes, dividing different stages of reservoir sediment change, and calculating soil erosion amounts of drainage basins above the reservoir in different stages. And converting the reservoir sand amount in the early stage into the reservoir sand amount under the current underlying surface condition by using the conversion coefficient, estimating the reservoir sand amount in the planning level year or the design level year, and analyzing the reservoir capacity curve in the future. The reservoir capacity prediction method achieves the effects of more accurately predicting the reservoir capacity, exerting the reservoir function, improving the reservoir benefit and avoiding the waste of engineering investment.

The invention relates to the technical field of flood control dispatching, and discloses a reservoir flood control water level dynamic control and flood recycling method and system, and the method comprises the steps: obtaining a surface rainfall forecast value of a reservoir basin based on real-time rainwater condition data and numerical weather forecast; a hydrodynamics and hydrology coupled drainage basin runoff model is driven, and an in-reservoir flood hydrograph in a predicted period is generated; judging the flood scale and grade based on the hydrograph, and when the flood is medium and small flood, calculating the dynamic flood control storage capacity of a downstream flood control object by adopting an equivalent flood control effect algorithm taking into account the pre-discharge scheduling capability; according to the dynamic flood control storage capacity, a dynamic flood control water level control value is obtained through backstepping of a water level-storage capacity relation curve of the reservoir; and finally, generating and executing a reservoir dispatching instruction based on the control value, and storing the water level of the reservoir to not exceed the dynamic value. The problems that a fixed flood control water level method is low in water resource utilization rate and inflexible in dispatching are solved, and flood resource efficient utilization on the premise of flood control safety is achieved.

The embodiment of the invention provides a site selection method of a pumped storage power station and related equipment, and belongs to the technical field of information processing. The method comprises the following steps: acquiring and identifying a river system and a contour line through topographic data; traversing all river systems, identifying a source node, a confluence node and an outflow node according to the beginning and end of the water system and the intersection condition of the water system, and generating discrete nodes according to a communication path so as to mark each water system node in the river system; calculating a reservoir area range and an optimal dam line of a reservoir at each water system node according to the water system nodes and the contour lines; generating a closed image according to the optimal dam line and the contour line, and calculating the limit storage capacity, the water level area curve and the water level storage capacity curve of the reservoir at the water system node; and screening to obtain a target reservoir through preset dam characteristic parameters according to the limit reservoir capacity, the water level area curve and the water level reservoir capacity curve of the reservoir at each water system node. According to the embodiment of the invention, omission of a high-quality dam site can be effectively avoided.

A calculation method of karst underground reservoir capacity curve based on hydrogeological parameters, including the following steps: hydrogeological exploration, determination of karst underground water reservoirs scope, determination of water storage space, determination of relevant hydrogeological parameters based on hydrogeological tests, and underground reservoir capacity analysis. The invention uses the unit water permeability and the borehole line karst rate that are very easily obtained through the borehole pressure (injection) water test and combines it with a small amount of water pumping test, thereby obtaining a correlation function relationship through regression analysis between the specific yield and the karst rate that are difficult to obtain and the unit water permeability or the permeability coefficient; the underground storage capacity at the corresponding elevation is calculated according to the specific yield or the karst rate and the underground storage capacity curve is obtained, which can improve accuracy and reduce errors.

The invention discloses a cascade reservoir short-term scheduling method considering the influence of dynamic reservoir capacity and backwater jacking. The method comprises the following steps: constructing a target function; setting constraint conditions; initial water levels of upstream and downstream power stations, upstream power station reservoir flow, downstream representative station water levels of downstream power stations, cascade power station interval runoff and power load plans are obtained, and initial reservoir capacities of all hydropower stations are obtained according to the reservoir capacity curve; assuming the end water level of the upstream power station in the time period, and calculating the corresponding ex-reservoir flow, the end water level, the power generation water head and the power station output; if the output of the upstream power station meets the load plan requirement in the period, adjusting and calculating the output of the downstream power station in the period; according to the upstream reservoir outlet flow and the interval runoff, the downstream reservoir inlet flow is calculated; if the load plan requirement of the downstream power station in the time period is met, adjusting calculation in the next time period is carried out; according to the method, the influence of the dynamic reservoir capacity and the backwater jacking is fully considered, and real-time optimal scheduling of the cascade reservoir is realized.

The invention belongs to the technical field of water resource optimal scheduling, and discloses a reservoir optimal scheduling method based on hybrid swarm intelligent optimization, which comprises the following steps: S1, collecting data required by reservoir historical inflow, a reservoir capacity curve, a water supply demand and a scheduling constraint condition; s2, setting a constraint condition and a scheduling target, and establishing a reservoir scheduling optimization model; s3, constructing a candidate solution group on the basis of combining reservoir scheduling decision variables, performing initial fitness calculation by utilizing an objective function of the reservoir scheduling optimization model, introducing a hybrid group intelligent optimization algorithm, performing multi-objective optimization scheduling calculation on the reservoir scheduling optimization model, and performing iterative updating; s4, completing all set iterations, and outputting a reservoir optimization scheduling scheme meeting constraint conditions; according to the method, the premature convergence problem of a traditional swarm intelligence optimization algorithm is effectively avoided, the convergence speed and the solution stability are improved, and the method is suitable for optimization solution of single-library and multi-library systems in single-target or multi-target scheduling problems of water supply, flood control, power generation and the like.

The invention is suitable for the technical field of electric power transaction, and provides a multi-target transaction strategy and system for water-wind-light power generation based on an improved hybrid algorithm, and the strategy comprises the following steps: collecting system parameters of a hydropower station, a photovoltaic power station, a wind power station and a pumped storage power station, and determining boundary values of constraint conditions; constructing a multi-objective optimization scheduling model, wherein the multi-objective optimization scheduling model comprises an objective function and a constraint condition; an improved fast non-dominated genetic algorithm and a time-varying multi-objective particle swarm optimization algorithm are adopted, and global optimization is carried out on the multi-objective optimization scheduling model through a double-population strategy; and displaying an optimization result at a client through a graphical interface, wherein the optimization result comprises the power generation plan of each power station, the change of the reservoir capacity and the economic benefit of the system. By combining the genetic algorithm of fast non-dominated sorting and the time-varying multi-objective particle swarm optimization algorithm, global optimization is carried out by adopting a double-population strategy, the advantages of the two algorithms are effectively combined, and the search efficiency is improved by dynamically adjusting the strategy and parameters.

The invention belongs to the technical field of reservoir related data correlation analysis, and discloses a reservoir capacity distribution characteristic coefficient and flood control capacity correlation data analysis method. The method comprises the following steps: S1, based on a sensor network, collecting reservoir related data in real time to obtain a reservoir data set; s2, quantifying reservoir capacity characteristics based on the reservoir data set; s3, correlating reservoir capacity characteristic data with flood control capability data through calculation; s4, a hydrodynamic equation is introduced to correct the calculation deviation; s5, quantitatively evaluating the influence intensity of the storage capacity feature data; s6, real-time risk early warning diagnosis is carried out according to the flood control evaluation value; in general, the flood risk prediction method has the remarkable advantages of being high in flood risk prediction accuracy, high in auxiliary decision-making capacity, good in sustainable use economical efficiency and the like.

The invention relates to the technical field of hydraulic engineering, and discloses a reservoir capacity curve high-precision calculation method and system based on a three-dimensional model, and the method comprises the steps: carrying out the self-adaptive sampling and optimization of original terrain data, constructing a three-dimensional terrain surface model, carrying out the self-adaptive discretization grid division, and carrying out the volume analysis error correction. And high-precision reservoir capacity estimation is realized. A data integrity detection and repair mechanism is introduced, the calculation efficiency is improved by combining a parallel processing technology, and the result reliability is ensured by adopting cross validation. Meanwhile, a three-dimensional visual model is generated, layered display of topographic features is realized, a topographic change adaptability analysis function is realized, and a capacity calculation result can be dynamically updated. According to the method, the accuracy and efficiency of reservoir capacity calculation are remarkably improved, and reliable data support and a visual visualization tool are provided for hydraulic engineering planning and management.

The invention discloses a reservoir capacity calculation method and system based on hydrodynamic simulation and non-uniform coefficient correction, and belongs to the technical field of water resource management, and the method comprises the steps: carrying out the grid division of a research region; constructing a hydrodynamic model based on topographic data, hydrological data and atmospheric data of a research area, and calculating a real-time water level; introducing a ratio between the actually measured water level and the simulated water level, and calculating a non-uniform coefficient; correcting the hydrodynamic model by using the non-uniform coefficient on the basis of hydrodynamic model calculation to obtain a corrected water level; and calculating the water volume of each grid based on the corrected water level, and accumulating the water volumes of all the grids to obtain the storage capacity. According to the method, the area of the regional grid is extracted through Arcgis software, and dynamic correction of the non-uniform coefficient is introduced, so that the storage capacity calculation precision is effectively improved.

The present application relates to a kind of carbonate buried hill oil reservoir reconstruction gas storage evaluation method and device, the method comprises: the cap rock sealing property and fault sealing property of carbonate buried hill oil reservoir are evaluated, and the trapping sealing property evaluation result is obtained;Attribute data body is obtained by multi-window dip scanning to time domain seismic data, and based on attribute data body, coherent attribute body, curvature attribute body and ant body attribute body are generated, and coherent attribute body, curvature attribute body are respectively fused with ant body attribute body, and the favorable reservoir characterization result is obtained;Reservoir space in the oil-gas-water three-phase saturation under the condition of reconstruction gas storage is calculated, and the capacity parameter evaluation result is obtained;Based on the trapping sealing property evaluation result, favorable reservoir characterization result and capacity parameter evaluation result, buried hill oil reservoir reconstruction gas storage evaluation result is generated.The present application method is suitable for the evaluation of reservoir type reconstruction gas storage, and provides good technical support for the design of gas storage scheme.

The invention discloses a reservoir damming branch blocking information extraction method and device based on a digital elevation model, and the method comprises the steps: obtaining a reservoir digital elevation model and key parameters, and extracting a corresponding water level isoline data set, a range boundary and slope data; after contour line data sets are classified, different types of pattern spot data sets are formed through surface construction and space relation operation; performing spatial inclusion relation query and judgment processing on the pattern spot data set to form a damming water area pattern spot object set; the object set is traversed, the nearest point and the minimum distance between the object set and the main flood prevention limited water level pattern spots or the object set are calculated, a damming and blocking branch object is formed, and the dam crest plane area, the average elevation, the loss reservoir capacity of the damming and blocking branch and the influence reservoir capacity are calculated. According to the method, the technical problems of limited precision, incomplete information extraction and the like due to the fact that the current damming and blocking branch information depends on manual identification are solved, and a basis is provided for reservoir flood control capacity analysis and damming and blocking branch rectification decision making.

The invention relates to the technical field of gas reservoir engineering and development, in particular to a dynamic correction method for the storage capacity of a gas storage of a condensate gas reservoir. Comprising the following specific steps: S1, based on a gas reservoir engineering method and geological data, calculating an original gas-bearing pore volume of a gas storage, and constructing an initial material balance model and various key parameters related to the initial material balance model; according to the method, through basic data collection and model construction, experimental determination and multi-path pore volume change calculation, and then model correction, parameter review, experimental simulation and final prediction and optimization, the storage capacity related parameters can be accurately calculated and corrected, the influence of various factors on the pore volume is effectively quantified, and the calculation efficiency is improved. Accurate prediction of the storage capacity change of the gas storage under future multi-cycle injection and production is achieved, injection and production parameters are optimized to remarkably improve the working gas amount and the storage capacity utilization rate, and good economic benefits and gas storage operation benefits are brought.

The invention relates to a reservoir optimization scheduling system and scheduling method for generating multiple objectives based on AI, the reservoir optimization scheduling system comprises a data input module, a multi-objective optimization module, a constraint processing module, a result output module and a visualization module, the data input module is configured to obtain basic data of a reservoir; the multi-objective optimization module is configured to construct an optimization model based on a particle swarm optimization algorithm, minimize the maximum discharged flow, minimize the flood exceeding storage capacity and minimize the discharged flow change rate as objective functions, and search the optimal discharged flow process through particle iteration; the constraint processing module is configured to perform constraint check on the discharged flow and the water level of the reservoir and apply punishment to solutions violating constraints so as to ensure the feasibility of the scheduling scheme; the result output module is configured to output the optimized discharge flow process, the optimized water level process and the optimized flood limit exceeding storage capacity process; the visualization module is configured to draw a water level-flow process chart and optimize a target convergence curve.

The invention aims to provide a coal mine water inrush body deep ex-situ dredging and restoring method and system, and belongs to the technical field of coal mine water disaster prevention and control. The system comprises a water inrush body recognition module, a drainage depressurization system, a closed pipeline collection system, a storage stratum screening and well design module, a high-pressure storage ectopic dredging system and a safety monitoring system. According to the method, the water inrush body is identified by finely evaluating the hydrogeological conditions, the optimal hydrogeological parameters are obtained by using the parameter inversion model and the particle swarm optimization, and drainage and pressure reduction are guided; a reservoir capacity grade dynamic evaluation system is established, a deep suitable stratum is screened, collected mine water is stored back to the deep part by using high-pressure equipment, and full-period safety monitoring is performed in combination with a multi-source data fusion early warning model. The strategic reserve of the mine water depth is achieved, the underground water ecology is effectively maintained, and the treatment cost and the safety risk are remarkably reduced.