57533 results about "Petroleum engineering" patented technology

The invention relates to the technical field of geological exploration, and discloses an advanced geological forecasting method and system based on tunnel geological exploration. The method comprises the following steps: performing data denoising on a multi-source data set pre-collected in a tunnel construction area to obtain an original data set; performing preprocessing and multi-stage data fusion on the original data set to obtain a fused data set; performing three-dimensional space modeling and feature extraction on the fused data set to obtain an intelligent geological prediction result; performing multi-factor risk assessment on the intelligent geological prediction result to obtain a geological risk distribution map in front of the tunnel; performing construction scheme optimization on the geological risk distribution map to obtain a construction guidance scheme; and carrying out comprehensive analysis and dynamic updating on the real-time monitoring data, the construction guidance scheme, the intelligent geological prediction result and the geological risk distribution map to obtain an advanced geological prediction result. According to the method and the system, the defects of insufficient prediction precision, reliability and accuracy of a traditional geological prediction method are overcome, and the safety risk is reduced.

The invention relates to the technical field of prediction algorithms, in particular to an oil and gas well digital twinborn modeling and prediction analysis system which comprises an underground dynamic data analysis module for extracting variables based on pressure, flow velocity and temperature data, performing data association calculation, analyzing the pressure change rate and the flow velocity trend, calculating the temperature fluctuation range and establishing time period variable analysis; and generating a dynamic parameter mode. According to the invention, through an autoregressive integral moving average model, the dynamic data of each time period is integrated and smoothed, the long-term trend of the data is captured, the subtle change in the production fluctuation is identified, the accurate future yield fluctuation trend is generated, a density clustering algorithm is adopted, key variables are analyzed, and the change mode of abnormal fluctuation is extracted. According to the method, potential fault types are screened, similar data points are classified through the density relation between data, dependence on parameter setting is reduced, abnormity is recognized more accurately under the unsupervised condition, and the fault recognition capability is improved.

A method and system for early prediction and warning of mine disasters through on-site monitoring is provided. [Solution] The method involves installing sensors at the mine site to monitor surface water, groundwater data and underground rock data in real time, so that mine safety management personnel can obtain timely and comprehensive data to better understand the state of the mine environment. The predictive analysis module uses deep drilling and computational learning technology to analyze the surface water, groundwater data and underground rock data to predict the risk assessment index Fpzs, which is helpful in predicting potential disaster risks, and comprehensively takes into account various factors such as the number of past disasters Lzs, the water level fluctuation coefficient Sbxs, and the rock stability coefficient Ywxs, which is helpful in quantifying the risk level, providing a more accurate disaster risk assessment, and reducing the casualties caused by mine disasters.

The invention discloses a petroleum drilling and production equipment management method and system based on big data analysis, and relates to the technical field of equipment management.The method comprises the steps that operation parameters and environment parameters of equipment are collected in real time by installing various sensors; based on the historical operation data of the equipment, calculating a dynamic baseline value of the operation parameters of the equipment, and setting a normal fluctuation range; the method comprises the following steps: analyzing operation parameters of a plurality of devices in the same operation area, calculating a correlation degree among the devices, and identifying a correlation mode among the devices; when the operation parameters of the equipment exceed the dynamic baseline range and the relevance between the equipment is abnormally changed, judging that the equipment is abnormal, and triggering early warning; and according to an abnormal detection result, the importance of the equipment and the operation condition, evaluating the maintenance priority, and making an optimized maintenance plan. According to the method, by introducing calculation of the dynamic baseline value and recognition of the association mode between the devices, early warning can be given out in time when the parameters are abnormal and the association changes, and the accuracy of anomaly detection is improved.

The invention provides a complex geothermal system digital twinning online experiment method based on multi-source data deep fusion, and solves the problems of precise construction of geothermal system digital twinning and low-delay visualization of virtual-real interaction. The method comprises the following steps: firstly, building a typical geothermal reservoir multi-source heterogeneous data parallel acquisition system, and carrying out fine inversion, high-precision identification and continuous correction on geothermal reservoir parameters by using a large amount of field experiment test data; then, a complete physical model of the geothermal system is established, online simulation is conducted on an actual system through high-performance scientific calculation, and mutual calibration is conducted on the actual system and test data; and finally, building a geothermal system digital twinning on-line experiment platform based on real-time acquired test data, a reliable mechanism model and an artificial intelligence method, and realizing accurate measurement and on-line monitoring of a geothermal exploitation process and iterative evolution of a geothermal reservoir exploitation scheme. According to the method, multi-source data of the geothermal system are deeply fused, high-precision online simulation and low-time-delay virtual-real interaction in the geothermal experiment process are achieved, and geothermal storage and exploitation details can be comprehensively transparentized. And furthermore, intelligent and rapid inversion is performed on the multi-scale seepage and heat transfer process of the geothermal reservoir by carrying out a virtual online experiment, so that the scientificity and efficiency of full-life-cycle geothermal exploitation are greatly improved. Meanwhile, a multi-agent collaborative optimization regulation and control framework provided by the method has relatively high expandability and flexibility, and an optimal well spacing design scheme and an optimal experiment scheme of the geothermal well group can be automatically excavated through adaptive optimization and iterative evolution of a system regulation and control strategy; and the method has a very strong application prospect in the distributed optimization field of the geothermal storage virtual experiment.

A cable trough for installing cables alongside a railway line or other right of way is described. The cable trough is constructed using longitudinally oriented reinforcing fibers coated with polymeric resin that generally aligns the reinforcing fibers with the length of the cable trough. One or more connector clips may be used to secure respective portions of the cable trough to one another. The cable trough is provided with a cover that may be removably secured to an elongate channel to protect the cables housed within the cable trough. Elbows, corners, tees, and other connectors may be provided to run the cable trough in any desired direction. A method of installing cables in a cable trough is also described.

The invention relates to the technical field of drill rod monitoring, in particular to a residual life prediction method for high-strength drill rod steel corrosion fatigue monitoring, which comprises the following steps: acquiring working data of a drill rod, including stress and corrosion environment data; quantifying the influence of the stress and the corrosion environment on the fatigue life, and establishing a stress-corrosion environment-fatigue life quantitative relationship; constructing an improved damage accumulation model considering corrosion rate and crack propagation to obtain a preliminary drill rod residual life prediction result; fusing real-time monitoring data and historical operation data by using a deep learning algorithm, introducing an attention mechanism to dynamically adjust the weight of the model, and correcting and updating the prediction result of the remaining life of the drill rod; and setting multi-stage safety thresholds, and carrying out graded early warning on the failure time of the drill rod. By means of the method, intelligent management of the whole life cycle of the drill rod can be achieved, and the safety, reliability and economical efficiency of drilling operation are improved.

The invention relates to the field of shale oil and gas, and discloses a method for identifying a shale oil and gas reservoir dessert, which comprises the following steps: acquiring a core CT image, three-dimensional seismic data and production dynamic data, and carrying out cross-scale preprocessing; constructing a fractional-order non-local seepage field model to represent nano-to-kilometer-level flow characteristics; predicting seepage field parameters through a Lie group symmetry constrained neural network; establishing a cross-scale coupling model of the quantum adsorption effect and the macroscopic seepage law; dynamically updating model parameters based on real-time monitoring data; and executing multi-target collaborative optimization to generate a sweet spot three-dimensional distribution and development scheme. According to the method, a fractal dimension dynamic constraint cross-scale data fusion technology is adopted, the effect of accurate mapping of nanopore and macroscopic fracture network parameters is achieved, and the problem of misalignment of CT scanning and seismic inversion data space registration is solved through pore communication fractal analysis.

The invention discloses a management system for real-time monitoring and early warning of mine coal and gas outburst parameters, and belongs to the field of safety production, and the management system specifically comprises the steps: collecting gas and ground stress data in a mine in real time through a gas sensor and a microseismic sensor, and carrying out the real-time monitoring and early warning of the mine coal and gas outburst parameters through a time sequence analysis and spatial data mining technology and a multi-scale coupling strategy; identifying the change rule and potential correlation of the crustal stress and the gas parameters; a comprehensive outburst analysis and prediction model is established, the coal and gas outburst risk level is evaluated, and a three-level early warning mechanism and an emergency plan are designed; the method can be flexibly adjusted according to actual conditions of a mine, coal and gas outburst accidents are effectively prevented and controlled, and the safety of the mine is improved.

The invention belongs to the technical field of petroleum pipeline inner wall defect detection, and particularly relates to a petroleum pipeline inner wall defect detection system which comprises a pipe section division module, a wall thickness analysis module, a straight pipe section detection module and a bent pipe section detection module. Ultrasonic incident detection and eddy current scanning are synchronously carried out in areas with different wall thicknesses, eddy current and ultrasonic dual-mode detection are fused to generate a three-dimensional map containing defect boundary and depth information, a deposition risk area is divided on the basis of stress distribution of flow field simulation of a bent pipe section, an adaptive defect detection mode is adopted in different areas, and the defect detection accuracy of the bent pipe section is improved. Therefore, targeted detection of the defects of the inner wall of the petroleum pipeline is realized, missed identification is avoided to a great extent, and the completeness and reliability of defect detection can be greatly improved.

The invention provides a three-dimensional geological modeling method fusing different geological data formats and different exploration analysis source data. Batch rapid extraction of drilling data, three-dimensional modeling of geological structures, data fusion of geophysical interpretation results and three-dimensional model construction of geological anomalous bodies (water-rich abnormal areas, collapse columns, karst caves, goaf areas or underground building facilities) can be conveniently and rapidly achieved, and integration and visual display of various exploration and analysis results can be achieved. The method can be applied to engineering design and development of subway tunnel shields, mine roadway tunneling, mineral resource mining, mine geological guarantee systems and the like, visual analysis decision assistance is provided for deployment and scheme formulation of development engineering, and a foundation is laid for construction of transparent mines and intelligent mines.

The invention relates to the technical field of mineral resource reserve simulation, in particular to a geological mineral resource reserve simulation method. The method comprises the following steps: carrying out multi-source heterogeneous data acquisition on a target geological area, and carrying out comprehensive feature extraction to obtain a comprehensive data set; constructing an initial static geologic model according to the comprehensive data set to obtain the initial static geologic model; building a multi-physics field coupling model according to the initial static geologic model to obtain a multi-physics field coupling model grid; performing metallogenic fluid migration and enrichment simulation according to the multi-physics field coupling model grid to obtain a metallogenic fluid migration simulation result; carrying out geologic body geometrical morphology updating on the initial static geologic model according to a metallogenic fluid migration simulation result to obtain a dynamic geologic model; and performing reserve prediction model training according to the dynamic geologic model to obtain a reserve prediction model. According to the method, the mineral resource reserves are evaluated more accurately and dynamically through a mineral resource reserve simulation technology.

The invention relates to the technical field of gas pipeline safety assessment, in particular to a gas pipeline safety assessment early warning system and method based on data analysis. The method comprises the following steps: collecting gas pressure data of a gas pipeline at multiple points at the same time, carrying out time-space synchronization processing to obtain aligned gas pressure data so as to construct a continuous gas pressure field of the pipeline, based on the gas pressure field, identifying the pressure distribution difference of the pipeline, estimating the transient flow velocity of the gas, continuously recording the transient flow velocity of the gas, and deducing the change of the flow velocity. Judging the deformation condition of the inner wall of the pipeline in combination with air pressure field data, positioning a deformation area, reconstructing a pipeline frame, analyzing deformation response, identifying a deformation type, identifying a corrosion evolution trend, performing safety evaluation, judging the gas circulation degree and performing physical safety evaluation. According to the invention, dynamic monitoring of the gas pipeline is realized, a data-driven safety management mode is promoted, the early warning capability of potential risks is improved, and a more intelligent safety assessment and early warning mechanism is formed.

The invention belongs to the technical field of marine corrosion monitoring, and particularly relates to a marine corrosion real-time monitoring method and system, a terminal and a storage medium, and the method comprises the steps: obtaining real-time original data based on sensing equipment arranged on a marine structure, the original data including electrochemical data, environmental data, physical state data and corrosion state data; mapping the original data to a high-dimensional space based on a kernel function, and obtaining enhanced features most related to a corrosion state in the original data mapped to the high-dimensional space based on an attention mechanism; an LSTM model is established based on the time dependency relationship of the corrosion state, and the LSTM model inputs reinforcement features and outputs local time sequence features; and performing weighted fusion on the strengthening features and the local time sequence features to obtain a corrosion state prediction model, inputting the strengthening features and the local time sequence features, and outputting a corrosion rate prediction value, a corrosion depth prediction value and a corrosion risk score value. The change of the corrosion process is reflected in real time, and the decision timeliness is improved.

The invention relates to an oil bearing carrying capacity evaluation method based on virtual simulation, and the method comprises the steps: obtaining working condition data samples of an oil bearing in a plurality of typical operation states under a complex working condition of a composite load, and carrying out the marking of bearing structure partitions, so as to build a working condition partition mapping table; establishing a multi-physics field sensitive area identification model for each partition, and performing dynamic parameter adjustment on the global finite element model and the local high-precision infinitesimal sub-model by using a multi-physics field coupling calibration factor; and performing time sequence feature extraction on a multi-physical field joint simulation result after dynamic parameter adjustment to obtain a multi-dimensional parameter sequence related to the typical failure mechanism of the oil bearing.

The invention discloses a coal and rock mass fracture instability multivariate signal fusion analysis method, and belongs to coal and rock mass analysis. The method comprises the following steps: carrying out time-frequency domain processing on an acoustic emission signal to obtain an accumulated ringing characteristic value # imgabs0 # and an accumulated b characteristic value # imgabs1 #; a main control frequency characteristic value # imgabs2 # and an amplitude characteristic value # imgabs3 # are accumulated; a spatial characteristic value # imgabs4 # of acoustic emission; fitting a fitting function # imgabs7 # from the characteristic value # imgabs5 # to the characteristic value # imgabs6 # respectively; according to the fitting function # imgabs8 #, calculating a correlation coefficient matrix R between the characteristic values # imgabs9 # to # imgabs10 #; according to the matrix R, determining a weight coefficient # imgabs11 # of each characteristic value; a first-order derivative function # imgabs13 # and a second-order derivative function # imgabs14 # of the fitting function # imgabs12 # are obtained, and according to the first-order derivative function # imgabs15 # and the second-order derivative function # imgabs16 #, a demarcation time point # imgabs17 # in the coal and rock mass damage process is determined; and the boundary time point # imgabs19 # is corrected by using the weight coefficient # imgabs18 #, and a corrected boundary time point # imgabs20 # is obtained. In order to solve the problems that an existing coal and rock mass fracture instability judgment index is single, and coal and rock mass fracture instability early warning is low in single index precision, the early warning precision is improved through multi-element signal fusion.

The invention provides a method for evaluating the grouting water control effect of an underground water-sealed cave depot project. The method comprises the steps that firstly, grouting and geological parameters and hydrological monitoring data of a project area are obtained; establishing a three-dimensional seepage-grouting coupling model, and simulating the dynamic state of a seepage field by using a finite element analysis algorithm; then calculating the equivalent permeability change rate of the grouting affected zone based on a simulation result; constructing an evaluation index system, and performing quantitative evaluation by using a fuzzy comprehensive evaluation algorithm; and finally, generating a grouting parameter dynamic adjustment scheme according to an evaluation result. According to the method, scientific and accurate evaluation and engineering optimization of the grouting water control effect can be achieved, and the safety and economical efficiency of engineering are improved.

The invention provides a water conservancy data acquisition supervision method and system based on big data analysis. The method comprises the following steps: firstly, obtaining dam body surface temperature field data, reservoir water level time sequence monitoring data and a dam body three-dimensional structure, and carrying out environmental radiation interference elimination processing on the temperature field data; secondly, extracting temperature fluctuation amplitude time sequence characteristics and water level change rate in the corrected temperature field data, and constructing a matrix reflecting correlation strength of the temperature fluctuation amplitude time sequence characteristics and the water level change rate through dynamic correlation analysis; and identifying temperature fluctuation abnormal points by using the matrix, and generating a seepage correlation map in combination with the water level change rate. And dividing seepage state categories according to the water level change rate, and generating a leakage risk probability distribution diagram by combining periodic trend prediction. And finally, fusing the graph with a dam body three-dimensional structure to generate positioning supervision information with a seepage abnormal identifier. The technical scheme provided by the invention can improve the efficiency and accuracy of water conservancy data acquisition supervision.

A method and device for optimizing comprehensive production of an oil reservoir. The method comprises: on the basis of historical production data, performing regional level recognition, single-well level recognition, and production optimization model recognition, and updating oil reservoir dynamic recognition; on the basis of the historical production data, using the following steps to perform cyclic historical fitting on model parameters of a plurality of production optimization models: performing historical fitting on the model parameters, and performing well-to-well communication relationship calibration on the plurality of production optimization models; determining, on the basis of the updated oil reservoir dynamic recognition, a constraint condition corresponding to each production optimization model, solving an objective function corresponding to each production optimization model, obtaining an optimal decision variable corresponding to each production optimization model, and obtaining a development regulation scheme corresponding to each production optimization model; obtaining a comprehensive development regulation scheme of an oil reservoir; and updating the oil reservoir dynamic recognition on the basis of a regulation effect obtained by real-time monitoring of a development operation.

A lubrication system for a gearbox assembly for a turbine engine. The gearbox assembly includes a gear assembly including one or more gears and one or more bearings. The lubrication system includes a sump. The sump is a primary reservoir that has a first lubricant level. The lubrication system also includes a secondary reservoir in the gearbox assembly. The secondary reservoir has a second lubricant level that is greater than the first lubricant level. A plurality of drain ports includes a first drain port and a second drain port. The lubrication system fills the secondary reservoir with lubricant between the first lubricant level and the second lubricant level and a portion of the lubricant drains though the second drain port. The one or more gears collects the lubricant to supply the lubricant from the secondary reservoir to the one or more gears or to the one or more bearings.

The invention belongs to the technical field of sewage treatment, and particularly discloses an oil-containing sewage treatment air flotation machine which comprises an air flotation machine box body, and a front partition plate, a front oil collecting plate and a rear oil collecting plate are sequentially arranged in the air flotation machine box body from left to right. The front partition plate, the front oil collecting plate and the rear oil collecting plate sequentially divide the air flotation machine box into a mixing pool, an air flotation pool, an oil collecting pool and a slag collecting pool from left to right, a slag scraping assembly is arranged on the upper side of the air flotation pool of the air flotation machine box, a rotary filter plate is arranged on the upper portion in the oil collecting pool, and operation rails are arranged on the upper walls of the two symmetrical side walls of the air flotation machine box. The inner side wall of the air floatation machine box body and the inner side wall of the running track are provided with multi-stage track grooves, and the multi-stage track grooves comprise a slag scraping track groove, a slag salvaging track groove and an oil filtering track groove. The adjusting baffle moves along the slag scraping track groove, the slag salvaging track groove and the oil filtering track groove, the walking path of the adjusting baffle is divided into a slag scraping stage, a slag salvaging stage and an oil filtering stage, and classified collection of scum and oil is automatically achieved.

The present invention belongs to the technical field of coal mine drilling rigs, and relates to an intelligent directional coal mine drilling rig and a drilling method thereof. The intelligent directional coal mine drilling rig comprises a moving platform, a frame, a clamping device, a main manipulator, a power head, a drill pipe storage system, a control system and a hydraulic system. The present invention improves the structure of a power head by providing an angle adjuster having accurate angle adjusting and anti-rotation locking functions on the side of a transmission away from a main motor, a driving shaft in the transmission connecting the main motor and the angle adjuster; in addition, the control system comprises a tool face angle measurement and initialization system. Therefore, by means of cooperation between the tool face angle measurement and initialization system and the angle adjuster, the present invention solves the problems that drilling rigs in the prior art lack special tool face angle adjusting devices and thus have low precision and efficiency in trajectory adjustment and have difficulty in achieving automatic directional drilling.

The invention relates to the field of oil exploitation, and discloses a polymer with a heavy oil cold recovery function as well as a preparation method and application thereof. After the polymer disclosed by the invention enters a stratum, hydrophobic groups on a polymer chain can be adsorbed on an oil-water interface, the aggregation state of micelles is destroyed, the size of the micelles is greatly reduced, and released energy can provide energy required by emulsification. And meanwhile, after the amphiphilic groups are adsorbed to an oil-water interface, the tension of the oil-water interface is reduced, a low-surface-tension oil phase is automatically diffused to a high-surface-tension water phase, and spontaneous permeation emulsification viscosity reduction of the thick oil is realized without external force or under the low-power condition by virtue of the Malangori effect.

A hydrocarbon recovery system is integrated with a fluff transfer system. The hydrocarbon recovery system is configured for contacting a wet polymer fluff with a purge gas to provide a purged polymer fluff and an overhead stream, and separating a solids stream, a recovered hydrocarbon stream, and a recovered purge gas from the overhead stream. The polymer fluff transfer system is configured to receive the purged polymer fluff from the hydrocarbon recovery system and transport the purged polymer fluff in the fluff transfer system via circulation of a fluff transfer gas. The hydrocarbon recovery system and the fluff transfer system are integrated by utilizing at least a portion of the recovered purge gas from the hydrocarbon recovery system in the fluff transfer system as the fluff transfer gas and optionally utilizing fluff transfer gas from the fluff transfer system as the purge gas in the hydrocarbon recovery system.

The invention relates to the technical field of petroleum pipelines, in particular to a petroleum pipeline leakage detection method and system, and the method comprises the following steps: S1, data collection and preprocessing: collecting the detection data of a petroleum pipeline in real time through a plurality of sensors and geographic information collection equipment; s2, feature extraction: performing feature extraction on the preprocessed detection data by adopting a multi-scale feature extraction algorithm; s3, model construction: constructing a petroleum pipeline state recognition model; s4, real-time detection: inputting detection data acquired in real time into the petroleum pipeline state recognition model; s5, leakage path prediction: predicting the diffusion path and range after petroleum leakage in real time; and S6, leakage alarm: when leakage of the petroleum pipeline is detected, an alarm mechanism is triggered, and related personnel are notified to take emergency measures. According to the method, the diffusion path and range after leakage are accurately predicted, and a reliable basis is provided for emergency response.

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 present invention relates to the technical field of oil and gas exploration and development. Provided are a digital core-based shale pore type recognition method and a quantitative characterization method. The digital core-based shale pore type recognition method comprises: on the basis of a gray image of a shale sample to be recognized, recognizing an organic matter and a transition zone to obtain an organic matter recognition result; and on the basis of the organic matter recognition result and the gray image, obtaining an organic pore image and an inorganic pore image as a shale pore type recognition result. The present invention can be used to quantitatively recognize organic pores, inorganic pores and micro-cracks of shale, quantitatively characterize shale pore structures, and analyze structural parameters of the organic pores, the inorganic pores and the micro-cracks, so as to perform statistical analysis of distribution of different types of reservoir spaces of shale, thereby being of great significance for shale reservoir quality evaluation and effective shale oil and gas development method optimization.

The invention relates to the technical field of coal mine safety monitoring, in particular to an underground coal mine dust concentration monitoring method and system based on multi-modal data fusion, and the method comprises the steps: synchronously collecting dust concentration time sequence data, dust image data, sound wave signal data and environmental parameters through a multi-modal sensor array deployed in an underground coal mine; carrying out preprocessing and feature extraction on the collected data; predicting the decomposed high-frequency and low-frequency component signals by adopting a long short-term memory neural network and a grey Markov model; when the environment humidity is greater than 80%, carrying out light scattering compensation on the predicted value; inputting various predicted values into an improved D-S evidence theory fusion device, and outputting a fusion dust concentration monitoring value; and when the threshold value is exceeded or the temperature and humidity composite condition is reached, an acousto-optic alarm is triggered and a spraying dust-settling device is started. According to the method, the problems of low precision of a single sensor, multi-source data conflict, high-humidity environment measurement deviation and insufficient time sequence and fusion precision in underground coal mine dust concentration monitoring can be solved.

The invention provides a while-drilling formation pressure early warning method and device based on model prediction, equipment and a medium, and relates to the technical field of low-carbon mining, and the method comprises the steps: in a pre-drilling stage, based on seismic data, adjacent well historical data and design data, analyzing and generating prediction risk data of a target monitoring well; in the drilling process, actual formation pressure data are calculated in real time by using drilling data collected for a target monitoring well in real time, and the actual formation pressure data are compared with the predicted risk data; in the drilling stage, a pressure safety window is depicted based on the predicted risk data, the cycle equivalent density of the target monitoring well calculated in real time is compared with the safety window, and the drilling safety risk is recognized and analyzed; and after drilling is finished, summarizing the predicted risk data, the actual formation pressure data and the drilling safety risk, and updating and iterating the model algorithm through the summarized data. The method has the effect of improving the accuracy of formation pressure early warning while drilling in the petroleum drilling process.

A fuzzy cloud-based risk assessment method for reservoir operation schemes, including: collecting basic data of target reservoirs; constructing optimal operation model of conventional reservoirs to obtain model calculation results; acquiring change process of operation characteristics during whole operating period according to model calculation results, and constructing multi-level reservoir multi-dimensional risk assessment index system; dividing different risk level intervals according to multi-level reservoir multi-dimensional risk assessment index system; obtaining large number of sample data xij of reservoir risk index under corresponding working conditions by multiple parallel calculations to conduct risk assessment; calculating cloud digital features of different indexes by inverse cloud generator; and weighting indexes in index layer and criterion layer by Analytic Hierarchy Process to obtain multi-dimensional risk assessment results. In order to promote sustainable development and utilization of water resources and enhance level of reservoir risk management, scientific evaluation of reservoir risk is conducted by comprehensively considering various uncertainties.