33 results about "Reservoir optimization" patented technology

A method of managing a fluid or gas reservoir is disclosed which assimilates diverse data having different acquisition time scales and spatial scales of coverage for iteratively producing a reservoir development plan that is used for optimizing an overall performance of a reservoir. The method includes: (a) generating an initial reservoir characterization, (b) from the initial reservoir characterization, generating an initial reservoir development plan, (c) when the reservoir development plan is generated, incrementally advancing and generating a capital spending program, (d) when the capital spending program is generated, monitoring a performance of the reservoir by acquiring high rate monitor data from a first set of data measurements taken in the reservoir and using the high rate monitor data to perform well-regional and field-reservoir evaluations, (e) further monitoring the performance of the reservoir by acquiring low rate monitor data from a second set of data measurements taken in the reservoir, (f) assimilating together the high rate monitor data and the low rate monitor data, (g) from the high rate monitor data and the low rate monitor data, determining when it is necessary to update the initial reservoir development plan to produce a newly updated reservoir development plan, (h) when necessary, updating the initial reservoir development plan to produce the newly updated reservoir development plan, and (i) when the newly updated reservoir development plan is produced, repeating steps (c) through (h). A detailed disclosure is provided herein relating to the step (a) for generating the initial reservoir characterization and the step (b) for generating the initial reservoir development plan.

The invention discloses a method drawing up a multi-goal reservoir optimization scheduling graph capable of being self-adaptive to climate change. The method for drawing up the multi-goal reservoir optimization scheduling graph comprises the steps of: step 1. establishing a coupling model of a global climate model (GCM) and a variable infiltration capacity (VIC) hydrological model so as to forecast a run-off process under a future climate change scene; step two. establishing a multi-goal reservoir optimization scheduling graph model; and step 3. taking the forecast run-off process data under the future climate change scene as the input of the optimization scheduling graph model, and drawing up the multi-goal optimization scheduling graph model by adapting a self-adaptive genetic algorithm. The method for drawing up the multi-goal reservoir optimization scheduling graph has the advantages of balancing the social economy goal and ecological goal of reservoir scheduling, improving the comprehensive benefits of reservoir scheduling to the maximum degree on the condition of ensuring the flood control safety of a reservoir and being capable of being self-adaptive to future climate change and being widely applied to the production practice of multi-goal reservoir optimization scheduling.

The invention discloses a firefly algorithm-based cascade reservoir group scheduling optimization method. The method comprises the following steps of 1: by taking maximum generated energy of cascade reservoirs in a scheduling period as an optimization target, and taking waterpower constraints and electricity constraints of the cascade reservoirs as constraint conditions, building a cascade reservoir optimization model; and 2: performing optimization calculation on the cascade reservoir optimization model obtained in the step 1 by adopting an improved firefly algorithm to obtain the maximum generated energy and an optimal reservoir water level corresponding to the maximum generated energy, and outputting the optimal reservoir water level. The firefly algorithm-based cascade reservoir groupscheduling optimization method has important practical significance and application values for enriching cascade reservoir group optimization scheduling methods, improving the joint operation level ofa cascade reservoir group and improving comprehensive utilization benefits of water resources and economic benefits of power generation enterprises.

The invention discloses a data mining-based optimal selection method for reservoir multi-target dispatching rule parameters. The method comprises the steps of obtaining a reservoir multi-target dispatching non-inferior solution set by adopting a multi-target optimization algorithm; establishing a relationship between all reservoir dispatching rule parameters and the non-inferior solution set by utilizing a random forest model; and optimally selecting a reservoir multi-target dispatching rule parameter with a maximum information quantity by evaluating a prediction effect of each parameter on the non-inferior solution set. According to the method, reservoir optimization dispatching information can be effectively utilized, so that the number of parameters in a reservoir dispatching rule is greatly reduced, the efficiency of solving a reservoir multi-target optimization dispatching model is improved, and a simpler and high-operability reference basis is provided for scientific decision-making of a reservoir.

The invention relates to the technical field of reservoir optimization scheduling, in particular to an automatic correction system for the reservoir entering flow of a cascade reservoir. The system comprises a historical data module, an interval control value analysis module, a data server, a water affairs real-time module and a correction module, wherein the historical data module is used for storing water affairs information input into each power station interval of the cascade reservoir over the years through the data server; the interval control value analysis module is used for calling the information in the data server and analyzing and calculating the control value; the water affairs real-time module is used for storing the water affairs calculation information input into each powerstation interval of the cascade reservoir in the current day through the data server; and the correction module is used for correcting the reservoir entering flow. By use of the automatic correctionsystem for the reservoir entering flow of the cascade reservoir, the reservoir entering flow of the reservoir can be effectively corrected, in addition, the system has an automatic correction effect,and a manual operation is reduced.

The invention discloses a reservoir scheduling multi-objective optimization method based on GCN and NSGA-II, and the method comprises the steps: collecting reservoir flood control scheduling related data, and building a flood control multi-objective optimization model; using NSGA-II to obtain a primary population, grouping individuals through coding operation, taking grouped categories as nodes of the GCN, and mapping a parent-child relationship obtained by crossover and mutation operation into edges between the nodes of the GCN; using NSGA-II to obtain a preliminary pareto leading edge, performing grouping labeling on the abscissa of the preliminary pareto leading edge, and training a GCN model by using the grouping label and the graph structure obtained in the step 2; classifying the nodes of the graph structure by using the trained GCN model, and then adjsuting the uniformity of the pareto leading edge by using NSGA-II; and according to the pareto leading edge adjusted by the NSGA-II, outputting a non-inferior scheme set of the reservoir scheduling multi-objective optimization problem. The method can be widely applied to multi-target reservoir optimization scheduling, and a reservoir optimization scheduling scheme meeting all targets can be rapidly given.

The invention discloses a surface water and underground water combined dispatching optimization method based on an improved pollen algorithm. The method comprises: firstly, taking the maximum comprehensive objective of power generation, irrigation and ecology of a reservoir as an optimization objective, establishing an objective function of the reservoir optimization objective, and constraint conditions of the objective function comprising a water balance constraint, a node water quantity constraint, an underground water period water taking constraint, a reservoir water level constraint, a reservoir discharge constraint and a power station output constraint which are taken as constraint conditions; secondly, introducing a computer parallel technology to improve a pollen algorithm, and carrying out optimization calculation on the objective function to obtain power generation quantity, warehouse entering and exiting runoff, underground water taking rate and optimal reservoir water level.The surface water and underground water combined dispatching optimization method based on the improved pollen algorithm has important practical significance and application value for enriching reservoir group optimization dispatching methods, improving surface water and underground water combined dispatching benefits of northwest arid regions and improving water resource comprehensive utilizationbenefits and regional ecological benefits.

The invention relates to a data-driven water injection reservoir optimization method and system. The method comprises the steps of establishing a preliminary reservoir model based on static data and dynamic data collected in real time; randomly selecting historical production parameters related to oil reservoir parameters to carry out oil reservoir model numerical simulation on the preliminary oil reservoir model; under the condition that the difference between the numerical simulation result of the oil reservoir model and the production history is smaller than a second threshold value, adopting the preliminary oil reservoir model as an oil reservoir model for optimizing a subsequent water injection scheme and a drainage and production scheme; under the condition that the difference between the numerical simulation result of the oil reservoir model and the production history is greater than a second threshold value, analyzing and selecting at least one first parameter of which the correlation degree is greater than a first threshold value based on the correlation degree between the dynamic data and the numerical simulation result, and adjusting the preliminary oil reservoir model by optimizing at least one first parameter so as to enable the difference between the numerical simulation result and the production history to be smaller than a second threshold value.

The invention relates to the technical field of reservoir scheduling, and discloses a reservoir ecological scheduling method based on coupling modeling optimization optimization. The method comprisesthe following steps: constructing a reservoir multi-target scheduling model; collecting reservoir characteristic parameters; correlation analysis of a plurality of scheduling targets; carrying out optimization solution on a double-target model by using an optimization algorithm; extracting scheduling targets of benefit conflicts according to a correlation result to form a target set; constructinga scheduling model, and constructing a reservoir optimization scheduling model according to the target set; solving the optimal scheduling model by using a multi-target optimization algorithm to obtain a Pareto scheduling scheme set; optimizing the scheduling scheme set according to a multi-attribute decision-making method to obtain a preferred scheduling scheme. According to the reservoir ecological dispatching method, the defects in a traditional modeling method are overcome, and then the most ideal dispatching scheme is obtained.

The invention discloses a reservoir scheduling forecast information effective precision identification method based on data mining. The reservoir scheduling forecast information effective precision identification method comprises steps of adopting a dynamic planning method to obtain an optimal scheduling locus of the reservoir, performing disturbance on forecast information according to a given error level to generate forecast information according with the given error level, adopting a random forest method to establish a mapping relation between the reservoir optimal scheduling locus and a decision variety and forecast information, which is a random forest decision three; counting the related decision variety according to the random forest decision three; and gradually increasing an error level and repeating the above-mentioned steps, wherein a previous error level is an effective precision when forecast information does not exist in the obtained related decision variety. The invention can effectively identify effective forecast precision beneficial for reservoir optimization scheduling, can fully excavate useful forecast information and provides a reference basis which is more simple and strong in operability to the reservoir scientific decision.

The invention relates to a reservoir scheduling method based on spiral local search. The method comprises the following steps: step 1, establishing a reservoir optimization scheduling generating capacity maximum model; 2, a spiral local search algorithm and a bat algorithm are combined, so that the objective function of the mathematical model established in the step 1 is maximum, namely the reservoir generating capacity is maximum. The method has the beneficial effects that a spiral local search algorithm and a bat calculation method are combined to solve the problem of complicated constraintof reservoir scheduling, the reservoir scheduling level is effectively improved, and a new method is provided for solving the problem of complicated constraint of reservoir scheduling.

The invention discloses a cascade reservoir power generation scheduling compensation electric quantity distribution method. The invention belongs to the technical field of reservoir scheduling, the method comprises the following steps: respectively inputting runoff data of a design representative year into a reservoir single-reservoir optimization scheduling model and a cascade reservoir joint scheduling model, calculating the generating capacity of each reservoir during single-reservoir scheduling and joint scheduling of all reservoirs and the total generating capacity when a certain reservoir is runoff and the rest reservoirs are subjected to joint scheduling, and calculating compensation electric quantity and a relative contribution coefficient; calculating a relative contribution coefficient of each reservoir according to the compensation electric quantity contribution value of each reservoir; and according to the compensation electric quantity, the relative contribution coefficient and the power generation quantity of each reservoir during single-reservoir scheduling, updating the power generation quantity of each reservoir during joint scheduling of all reservoirs. Accordingto the method, the problem of distribution of cascade compensation electric quantity can be effectively guided, and the feasibility of joint scheduling is improved.

The invention relates to a monitoring and early warning method and system for a coal mine underground reservoir coal pillar dam body structure, and relates to the technical field of coal mine underground reservoir safety monitoring. The invention provides a monitoring and early warning method. The method comprises the following steps: acquiring a monitoring signal of a coal pillar dam body; collecting and sorting the monitoring signals to obtain monitoring data and spatio-temporal information data; performing real-time inversion analysis on the monitoring data and the spatio-temporal information data; performing intelligent analysis on characteristics and rules of the monitoring data; and performing safety analysis on the coal pillar dam body structure according to the monitoring data, the spatio-temporal information data, the inversion analysis result and the intelligent analysis result. On the other hand, the invention provides a monitoring and early warning system. According to the monitoring and early warning method and system, data acquisition and analysis are carried out on the operation condition of the coal mine underground reservoir, real-time diagnosis and safety early warning of the coal pillar dam body are achieved, and a necessary decision basis is provided for reservoir optimization scheduling.

The invention discloses a fracturing parameter design method based on riverway distribution, and a riverway construction method in tight gas development. The method comprises the following steps of: setting a high-permeability zone containing a hydraulic fracture; implanting the high-permeability zone into an oil reservoir numerical model; inputting each parameter into the oil reservoir numerical model for simulation to obtain a simulation result; performing screening according to hydraulic fracture parameters in a simulation result to obtain optimal hydraulic fracture parameters; through pressure simulation software, comparing the optimal hydraulic fracture parameters corresponding to different river width parameters to obtain a combination of river widths and fracturing parameters. According to the method, a one-section-one-parameter differentiation design can be achieved, and a basis is provided for later effect evaluation and reservoir optimization; meanwhile, the problems that reservoir difference sections are excessively transformed, and high-quality sections of a reservoir are insufficiently transformed, can be avoided, so that it is ensured that the reservoir is fully used according to river channel distribution, and the economic benefit and a single-well cumulative production volume are greatly improved.

The invention provides a reservoir optimization scheduling decision-making method and device for aquatic community system stability, and the method comprises the steps: 1, determining a research scene, collecting basic data and historical scheduling data of a reservoir group system, and hydrological data and biomass data of a downstream station, and determining an impact factor and a decision variable of a reservoir scheduling behavior; 2, considering interaction among multiple populations, and constructing a random multi-population dynamic model; 3, calculating hydrological variation degree, describing disturbance of hydrological variation on the aquatic community through noise intensity, establishing a'flow-ecology 'relationship, and analyzing the stability of the aquatic community system under the influence of the hydrological variation; 4, identifying the resilience and the resistance of the multi-population system by adopting two ecological indexes, namely steady-state time ST and a variable coefficient CVST at the steady-state time; and 5, comprehensively considering reservoir water supply and power generation targets and ST and CVST ecological targets, optimizing a reservoir operation curve, and obtaining a reservoir optimization scheduling decision.

The reservoir optimization scheduling method based on the dynamic optimization algorithm comprises the following steps: acquiring reservoir operation parameters, and setting the reservoir operation parameters as an initialized population popt; mathematical modeling is carried out; setting constraint conditions of the reservoir; detecting an environmental change; performing non-dominated sorting and layering on the reservoir population, and selecting a first layer as a non-dominated solution set popNon; edge individuals and lines or planes formed by the edge individuals are found and stored in several B; calculating the distance from the point to a straight line or a plane; uniformly dividing the mth target value into k regions, and selecting a point with the maximum distance to the line or the plane in each region as a Knee point of the first target value; calculating a boundary reference point; the calculated boundary reference points are added into the KN and recorded as updated Knee points NKN, congestion degree distance calculation is carried out, sorting is carried out, and the point with the minimum congestion degree distance is deleted; predicting a new position of the Knee point after the environment changes; calculating the position of the Knee point in the decision space; predicting the non-dominated solution set after the environment change to obtain a predicted new population; using an optimization algorithm to optimize the overall; and ending iteration.

The invention discloses a reservoir optimization scheduling method considering relevance and randomness of a water resource supply and demand process, and the method specifically comprises the following steps: 1, building a reservoir optimization scheduling model, and determining an optimization target and a constraint condition; 2, analyzing a runoff or water demand one-dimensional random process from two aspects of randomness of variables in a fixed time period and relevance of variables between adjacent time periods, and representing relevance characteristics between different states of every two random variables by adopting a state transition probability matrix; 3, analyzing relevance and randomness of the runoff and water demand multidimensional process; and 4, realizing a random dynamic planning method oriented to multi-dimensional process relevance and randomness. According to the method, randomness and relevance of the water resource supply and demand two-dimensional process are considered, random reservoir optimization scheduling is carried out, and the relevance and randomness problems of the water resource supply and demand process in reservoir water supply scheduling can be effectively solved.