4500 results about "Oil field" patented technology

The invention relates to the technical field of oil field databases, and discloses a dynamic data management method, device, equipment and medium for an oil and gas field database, and the method comprises the steps: docking multi-source data of the oil and gas field database, the multi-source data comprising a shaft sensor real-time monitoring data flow, geologic modeling gridding structure data and an equipment management tree coding table; the method comprises the following steps: performing abnormal value cleaning and timestamp alignment on real-time monitoring data flow of a shaft sensor, converting geologic modeling gridding structure data into a reservoir unit set with a coordinate system label, extracting a set membership chain of well IDs and equipment IDs in an equipment management tree-shaped coding table, generating an identifier system with a unified coding format, and storing the identifier system in a database; the identifier system comprises a well identifier, a reservoir unit identifier and a device identifier; generating a structured data pool based on the identifier system; and when the data pool is updated, sending a change instruction to a plurality of subsystems of the oil and gas field database, and updating each subsystem based on the change instruction.

The invention relates to the technical field of oil and gas field development, and discloses an oil and gas reservoir intelligent dynamic monitoring and optimized mining method based on big data. According to the method, through multi-source data real-time sensing and dynamic coupling modeling, the limitation of traditional static analysis is broken through, and minute-level accurate description of the state of the oil and gas reservoir is achieved; a machine learning prediction model based on physical constraints effectively fuses a data rule and a geomechanics principle, and the early warning reliability of water-driven dynamics and equipment faults is remarkably improved; a multi-objective optimization strategy of digital twin driving comprehensively plans the recovery ratio, the economy and the safety, and supports intelligent decision making under complex working conditions; the edge control and the block chain technology are combined to form a'sensing-optimizing-executing-auditing 'closed loop, so that the high efficiency, the self-adaptability and the data credibility of the mining process are ensured. According to the overall scheme, oil and gas exploitation is promoted to be transformed to intelligentization, refinement and transparency, and technical support is provided for cost reduction, efficiency improvement and sustainable development of an oil field.

The present invention belongs to the technical field of fracture network optimization in oilfield exploitation. Specifically disclosed are a method and system for optimizing complex fracture networks in shale reservoirs. The method comprises: S1, on the basis of geological-engineering bimodal data fusion, constructing a three-dimensional digital twin of heterogeneous reservoirs; S2, synchronously calculating the interactions among fluid flow, rock fracturing and proppant transport during a hydraulic fracturing process; and S3, automatically and iteratively optimizing a combination of fracturing operation parameters. By means of constructing a closed-loop system consisting of geological modeling, multi-field coupling simulation, intelligent optimization and dynamic correction, efficient design and real-time optimization of complex fracture networks in shale reservoirs are realized.

The invention discloses an oil field power distribution network operation safety violation behavior deep learning recognition system. The system comprises a video acquisition module, a data preprocessing module, an improved YOLO model module, a violation behavior judgment module and a result output module. The video acquisition equipment is distributed in a key area of an oil field site and transmits video data to the server through a wireless network; the data preprocessing module adopts histogram equalization and sharpening operation to enhance the image contrast. The improved YOLO algorithm model is subjected to customized training, and behavior actions of operators and equipment can be accurately recognized. And the illegal behavior judgment module performs matching judgment on the result output by the model in combination with the safety specification of the oil field operation. According to the method, the difficult case mining technology and the multi-stage training strategy are adopted, the judgment capability of the model on illegal behaviors under complex conditions is improved, the OpenCV technology is combined, the capability of the system for coping with light changes and severe weather conditions is enhanced, and the recognition accuracy under different illumination intensities is ensured.

The invention relates to the technical field of oil field geological prediction, in particular to an oil field geological parameter intelligent prediction system based on machine learning, which acquires static geological data and environmental data in real time through a data acquisition module, and performs noise reduction, normalization and cleaning on the acquired data through a data preprocessing module, so as to obtain an oil field geological parameter prediction result. The feature extraction module adopts an XGBoost model and a long-short-term memory network model to process static features and time sequence data respectively. And the model optimization and self-adaption module dynamically adjusts model parameters according to real-time feedback data by using a reinforcement learning algorithm so as to ensure the accuracy and adaptability of a prediction result. The visualization module provides visual display of a prediction trend, a geological data prediction value and a risk indicator, and helps an operator to make a decision based on data driving. According to the method, the prediction precision of the oil field geological data can be effectively improved, the adaptability to environmental changes is enhanced, and a scientific basis is provided for oil field management and production optimization.

The invention relates to a remote monitoring method and system for oil field operation equipment, and belongs to the technical field of oil field equipment monitoring, and the remote monitoring method comprises the steps: receiving the operation state data, collected in real time, of each key part of the oil field operation equipment; time sequence features related to the equipment state are extracted and subjected to normalization processing, and a time sequence feature set is generated; analyzing the time sequence feature set based on a health degree model, generating a health degree time sequence, performing dynamic segmentation analysis, and labeling abnormal features; performing long and short term trend analysis on the health degree time sequence based on a sliding window method, and calculating to obtain a trend analysis result; correlation analysis is carried out according to the trend analysis result and the abnormal features, and a comprehensive risk score is calculated; and matching a corresponding early warning level and a maintenance strategy according to the comprehensive risk score, and sending maintenance prompt information to a maintenance terminal. According to the invention, real-time remote monitoring of the operation state of the oil field equipment can be realized, and potential fault early warning can be carried out in advance.

The invention relates to the technical field of oilfield exploitation, and discloses a nanometer oil-displacing agent for oilfield oil extraction and a preparation method thereof.The nanometer oil-displacing agent takes modified nanometer silicon dioxide and a surfactant as main components, polymer macromolecules are modified on the surface of the nanometer silicon dioxide to serve as a main body of the nanometer oil-displacing agent, and the nanometer oil-displacing agent is prepared. Under the action of the surfactant, the nano silicon dioxide can flow into the fine throat and the micro throat, and the polymer macromolecules of the branched structure can generate a relatively strong interaction force with the rock, so that the polymer macromolecules are firmly adhered to the surface of the rock, the adhesion of crude oil on the surface of the rock is reduced, a smooth crude oil channel is constructed, and the flowing pressure of liquid is reduced; and crude oil fluidity is improved. The structure of the cross-linking agent contains quaternary ammonium cations, so that the electrostatic repulsion effect between nano silicon dioxide can be greatly enhanced, aggregation between nano silicon dioxide and nano silicon dioxide can be avoided, the interfacial tension can be efficiently maintained, the oil-water interfacial tension is greatly reduced, and the recovery rate of crude oil is effectively increased.

The invention discloses a multi-mode intelligent inspection system and device for an oil field gathering and transportation station yard, and belongs to the technical field of oil field gathering and transportation station yard inspection. The multi-mode intelligent inspection system comprises a data acquisition module, an abnormity judgment module, a station yard model simulation analysis module and a decision analysis and execution module; comprising a vibration camera sensor, a temperature camera sensor, a pressure camera sensor, a flow camera sensor, a liquid level camera sensor, a gas camera sensor, an ultraviolet flame camera sensor, an infrared thermal imaging camera sensor, a visible light camera sensor and a depth camera sensor and is used for collecting process equipment, environment states and personnel operation behavior data of a current oil field gathering and transportation station and recording the data collected by the sensors in a near-field edge server and a cloud server; the time difference of data acquisition is eliminated through a space-time alignment algorithm, and a time sequence health vector in a unified format is generated. According to the multi-mode intelligent inspection system and device for the oil field gathering and transportation station yard, multi-mode inspection can be carried out on the oil field gathering and transportation station yard based on the type of the oil field gathering and transportation station yard, and typical anomalies are recognized and processed.

The invention provides an efficient oil reservoir yield increasing fracturing method based on a micro-particle-size echelon proppant and application of the efficient oil reservoir yield increasing fracturing method, and belongs to the technical field of oil field yield increasing. According to the method, fracturing parameters are optimized by controlling the particle size and the filling sequence of the proppant and combining an intelligent algorithm, and efficient yield increase of the oil reservoir is achieved. The method comprises the specific steps that proppants with different particle sizes are selected according to stratum characteristics, fluid flowing rules and fracturing targets; designing a particle size gradient filling sequence of the proppant; fracturing parameters are optimized through an intelligent algorithm; fracturing operation is carried out, and the crack is filled with a propping agent; monitoring crack propagation, propping agent filling and fluid flowing conditions in real time, and adjusting fracturing parameters and a filling sequence; after the fracturing operation is completed, the fracturing effect is evaluated, and the propping agent selection, the filling sequence and the fracturing parameters are further optimized. According to the efficient oil reservoir yield increasing fracturing method based on the micro-particle-size echelon proppant and the application of the efficient oil reservoir yield increasing fracturing method, the yield increasing effect of an oil reservoir can be remarkably improved, and the method has wide application prospects.

The invention discloses an intelligent inspection fault diagnosis method and system adopting six-dimensional judgment, and belongs to the technical field of oil field gathering and transportation intelligent inspection. A data access module is used for collecting information of field sensors deployed in different site devices in the oil field gathering and transportation process; protocol analysis, time alignment and semantic mapping are carried out on collected data, data collected by a single-point sensor in the oil field gathering and transportation process are packaged into a unified measuring point object UPO, and a standard data structure containing equipment ID, design attributes, real-time values, historical sequences, alarm threshold values, mechanism parameters and upstream and downstream pointers is constructed. According to the intelligent inspection fault diagnosis method and system adopting six-dimensional judgment, the accuracy of abnormal recognition, the efficiency of root cause positioning and the scientificity of regulation and control decision are improved by fusing multi-dimensional judgment, intelligent reasoning and distributed cooperative fault diagnosis, and powerful support is provided for safe and stable operation of an oil field gathering and transportation system.

The invention relates to a rock mechanical parameter prediction method, device and equipment and a medium, and belongs to the field of oil field stratum analysis, and the method comprises the steps: obtaining to-be-predicted logging data; performing feature extraction on the to-be-predicted logging data through a graph convolution layer of a completely trained GNN prediction model to obtain stratum feature information; and performing calculation according to the stratum characteristic information to obtain rock mechanical parameters of the stratum. According to the scheme, the graph structure of the stratum logging data can be modeled by training the complete GNN prediction model, the nonlinear interaction between stratums is extracted, the complex relation between nodes and edges is automatically learned, the rock mechanics parameter prediction problem of the complex fault zone of the northern oil field is solved, and the prediction efficiency is improved. And even under the condition of data missing or non-uniformity, relatively high prediction precision is kept, and the adaptability and prediction capability to complex stratums of oil fields along the north are greatly improved.

The invention discloses an intelligent optimization decision-making method and system for an oilfield water injection system, and belongs to the technical field of oilfield development engineering. The method comprises the following steps: constructing a pipe network digital twinborn model and carrying out actual measurement verification; executing hydraulic-thermal simulation based on the model to generate a pressure-flow map; optimizing water distribution in combination with an injection allocation scheme and matching a pump set combination; generating a control instruction and executing a pressurization scheme; monitoring the state of the pipe network in real time and correcting model parameters. Through the digital twin technology and the differential evolution algorithm, global optimization decision of water distribution and pump set combination of the water injection system is achieved, and the problems that a traditional system is high in energy consumption and low in efficiency are solved.

The invention relates to the technical field of intelligent management of oilfield water injection systems, and particularly discloses a water injection pipe network operation situation analysis and energy consumption evaluation method and system. According to the method, real-time data and pipe network parameters of an oilfield water injection system are collected, and after anomaly detection and data cleaning treatment, a node pressure matrix and pipe section flow distribution are generated; performing residual analysis and time sequence modeling by combining real-time data and a simulation result to realize accurate positioning of operation abnormity; a fuzzy analytic hierarchy process for dynamic weight adjustment is adopted to construct a four-stage energy efficiency evaluation system of water injection station-pipe network-water injection well-overall system, and an energy consumption bottleneck thermodynamic diagram is generated; and finally outputting a strategy rehearsal report and a fusion cockpit. According to the method, the change of the water injection pipe network from'black box 'to'transparent' management is realized, the technical problems of single energy efficiency evaluation, scheduling dependence on experience and the like in a traditional method are solved, the system operation efficiency can be remarkably improved, and the energy consumption is reduced.

The invention discloses a shale oil exploitation method based on cooperation of multistage pulse gas fracturing and nano-catalysis, and belongs to the technical field of oilfield development, and the shale oil exploitation method comprises the following steps: S1, determining an optimal drilling position of a target shale layer, and carrying out drilling operation; s2, 0.1-10 Hz adjustable pulse pressure waves are formed through control of a high-frequency electromagnetic valve, a fracturing medium mixed with the functionalized nanoparticles is injected into the stratum through a fracturing pump, the pulse frequency of the high-frequency electromagnetic valve is adjusted, staged pulse fracturing operation is conducted, and a fracture network is formed; s3, after fracturing of each stage is completed, mixed fluid of a propping agent and fracturing fluid is injected into stratum fractures; and S4, after fracturing operation is completed, a microwave field is applied to the stratum, and the stratum temperature is kept within a set range. According to the method, the gas fracturing medium and the functionalized nanoparticles are mixed and then fractured, so that the influence on the environment is remarkably reduced, and the recovery ratio of shale oil is greatly increased under the combined action of multi-stage pulse fracturing, the composite proppant and the microwave field.

A method for estimating an elemental composition of a multiphase oilfield fluid includes obtaining a sample of a multiphase oilfield fluid; blending the sample with a viscosity modifying agent to transform the sample into a high viscosity paste; introducing the high viscosity paste into a chamber of an XRF apparatus; using the XRF apparatus to make an XRF measurement of the high viscosity paste; and evaluating the XRF measurement to estimate an elemental composition of the obtained multiphase oilfield fluid.

A molten salt heating direct-flow type wet saturated steam generation system, comprising an evaporation device, a molten salt conveying device, a preheating device, a softened water conveying device, and a dryness adjustment device. The evaporation device is provided with a first heat exchange pipeline and a second heat exchange pipeline; the molten salt conveying device comprises a molten salt conveying apparatus and a molten salt recovery apparatus; the preheating device is provided with a first preheating pipeline, and an outlet of the second heat exchange pipeline is connected to a steam output pipeline; and the dryness adjustment device comprises an adjustment member and a dryness measurement apparatus. According to the steam generation system provided by the present invention, the temperature of softened water and the temperature of molten salt can be adjusted to appropriate ranges, avoiding the crystallization of the molten salt; moreover, the dryness of wet saturated steam can be controlled by means of coarse adjustment and fine adjustment, and the direct-flow type evaporation device is suitable for softened water having poor quality so as to meet the steam injection requirements of oil fields.

The invention relates to the technical field of reservoir numerical simulation, and discloses a polymer flooding reservoir rapid simulation optimization method considering sedimentary facies constraints, which comprises the following steps: identifying sedimentary facies boundaries according to distribution characteristics of sedimentary facies, and establishing a connected network model considering the sedimentary facies constraints on the basis of the sedimentary facies boundaries, well positions and various sedimentary facies attributes; carrying out one-dimensional grid division on the connected network model, converting the connected network model into a grid connection format of a universal simulator, and solving the connected network model by adopting the universal simulator to obtain pressure and saturation solutions; establishing an automatic historical fitting mathematical model based on sedimentary facies and oil reservoir constraint conditions; the economic net present value is used as an index, the water injection rate, the liquid production rate and the polymer injection rate of each well are used as optimization variables, the differential evolution algorithm is used, the total polymer injection amount and the oil reservoir pressure are restrained, and an oil reservoir injection and production optimization mathematical model is established. According to the method, the oil reservoir is optimized by comprehensively considering the characteristics of the oil reservoir after water flooding is converted into polymer flooding, so that rapid decision-making of the oil field and guidance of oil field construction are realized.

The invention discloses an oil pumping unit transmission flexible connection fault diagnosis method based on big data and artificial intelligence. The oil pumping unit transmission flexible connection fault diagnosis method sequentially comprises the following steps of S1, collecting monitoring data related to oil pumping unit transmission flexible connection; s2, preprocessing the collected monitoring data; s3, a traditional machine learning method and a deep learning technology are fused, and an oil pumping unit transmission flexible connection fault early warning model is established; s4, analyzing the real-time monitoring data of the flexible connection by using the fault early-warning model, quickly judging abnormal conditions in the real-time monitoring data, making a fault early-warning and analysis report, and providing the fault early-warning and analysis report to a manager; and S5, continuously monitoring and optimizing the early warning model. According to the fault diagnosis method, through data management, an intelligent algorithm and model analysis, the transmission flexible connection state of the oil pumping unit is monitored in real time, potential faults are predicted and diagnosed in advance, and an alarm is given in time when a belt of the oil pumping unit or a steel wire rope of a beam hanger is broken, so that the production efficiency and safety of an oil well are improved, and construction of an intelligent oil field is assisted.

The invention discloses a rapid simulation and layered injection-production real-time optimization method suitable for a complex oil reservoir, and belongs to the field of unconventional oil reservoir numerical simulation, and the method comprises the following steps: 1, constructing a GMM-XGB hybrid model based on a Gaussian mixture model and an XGBoost algorithm; 2, constructing a layered connected network model based on a physical model; step 3, carrying out automatic history fitting by adopting an ES-MDA algorithm; and 4, establishing a layered injection and production real-time optimization objective function mathematical model, and performing layered injection and production real-time optimization based on an SHADE algorithm. According to the method, the recovery efficiency of the complex oil reservoir can be improved, the stable production period of an oil field is prolonged, and efficient utilization of resources and maximization of economic benefits are achieved.

The invention provides a combustion drive circulating gas-lift pressurizing all-in-one machine, and belongs to the technical field of natural gas production. Comprising a pressurization exhaust system, a gas lift pressurization system, a sewage discharge system, a pressure stabilizing system, a combustion drive multi-stage compression system and a base, and the pressurization exhaust system, the gas lift pressurization system, the sewage discharge system, the pressure stabilizing system and the combustion drive multi-stage compression system are all installed on the base. By arranging the pressurization exhaust system and the gas lift pressurization system, the device can perform gas lift and pressurization operation in an oil field, one machine has two purposes, by arranging the combustion drive multi-stage compression system, efficient dispatching of an oil and gas field circulation gas lift pressurization site is achieved, powerful guarantee is provided for development of the dual-carbon industry, and meanwhile, the device has good application prospects. By arranging the purification assembly, the natural gas in the well rises, so that the purity of the extracted natural gas is improved, and the problems that an existing gas lifting and pressurizing all-in-one machine is high in use cost and poor in effect are solved.

The invention provides an oil field information asset automatic discovery and management method and system, and the method comprises the steps: carrying out the flow reduction, carrying out the active detection, carrying out the asset identification label marking of all types of attribute information and components of assets according to the asset information and feature information obtained through the active detection and flow reduction, and carrying out the asset marking. And for unidentified assets found by active detection and flow reduction scanning, inputting corresponding information of the unidentified assets according to the asset identification tag, and carrying out security monitoring on the identified asset information. And the asset information is fed back to the security platform, and the found asset information is compared with alarm information in the security platform, so that non-asset alarm information and alarm information inconsistent with the asset category are removed, and the security platform is assisted to remove invalid information. Through flow reduction and active detection, docking of various network products and automatic identification of asset information in the existing network, asset management ecology of part of third-party products can be integrated, information islands can be broken through, and a clear asset ledger can be established.

The invention provides a rod-pumped well working condition monitoring knowledge base construction method based on theoretical electric power reconstruction, and belongs to the technical field of oil field informatization construction. Actually-measured electric power curves of all working conditions of a rod-pumped well and corresponding oil pumping unit parameters are obtained, and an electric power historical data set is formed; establishing a relational expression among the suspension center displacement, the suspension center load, the electric power and the crank angle; establishing an electric power to suspension point indicator diagram model, and calculating a suspension point indicator diagram corresponding to the actually measured electric power curve; a theoretical indicator diagram generation method is adopted, and the suspension point indicator diagram obtained through calculation is converted into a theoretical indicator diagram; establishing a suspension point indicator diagram to electric power conversion model, and calculating a theoretical electric power curve corresponding to the theoretical indicator diagram; and extracting shape features of the theoretical electric power curve and the actually measured electric power curve, and establishing a rod-pumped well working condition monitoring knowledge base by utilizing an electric power historical data set. The theoretical electric power curve can be automatically calculated according to the actually measured electric power curve, and expert participation is not needed.

The invention discloses an oil-electricity hybrid linkage power supply system and a control method for a network electric drill, and belongs to the technical field of oil field network electricity land drilling machine system optimization control. Aiming at the power supply and consumption characteristics of the grid electricity drilling machine, on the basis of the energy flow characteristics of the grid electricity drilling machine system, the power grid side, the diesel generating sets and the grid electricity drilling machine oil-electricity hybrid linkage power supply system are linked, a multi-source coordination control algorithm is adopted, the starting number of the diesel generating sets is selected according to the power consumption capacity gap, and flexible power adjustment is conducted; with the purpose of minimizing the power utilization cost during operation of the grid electricity drilling machine, stable power output of the diesel generating set is balanced, the optimal economic operation mode is achieved, and mutual impact of currents of a power grid side and the diesel generating set is prevented; the problems that an existing single power supply cannot meet the electricity demand of the grid electricity drilling machine, cost is high, and cooperative power supply production efficiency is low are solved.

The invention discloses an automatic control system and method for an oil field power distribution network, and relates to the technical field of power system automation, and the method comprises the steps: a monitoring equipment configuration and deployment module is responsible for configuring monitoring equipment, and collecting the state information and environment data of each node of the power distribution network; the feature analysis processing module analyzes the collected data by using the intelligent operation module to generate control parameters and abnormal parameters; the remote connection module establishes remote connection with power distribution network equipment through communication equipment, and performs remote control or management according to control and abnormal parameters; the visual interface display module visually displays the state information, the environment data, the control parameters, the abnormal parameters and other data, and helps operators to monitor the operation of the power grid in real time. The technical problem that in an existing oil field power distribution network control system, the power grid operation state cannot be flexibly adjusted to adapt to oil field electric power characteristic changes is solved, and the technical effect of dynamically adjusting the power grid operation state based on oil field electric power characteristics is achieved.

The invention discloses a parameter-controlled intelligent oil field shaft digital twinning modeling method, which belongs to the field of petroleum engineering and comprises the following steps of: generating well track data by adopting a multi-source data fusion mode, and optimizing a multi-source data fusion weight coefficient by adopting a genetic algorithm when a measurement depth is generated; well track curvature optimization is conducted based on the minimum curvature principle, a minimum curvature second derivative serves as a target function, and geological factors are introduced to dynamically adjust the smooth weight; a second-order Taylor expansion compensation item is provided for curvature factor dynamic correction, and three-dimensional coordinate data of the well track are generated; and based on the three-dimensional coordinate data of the wellbore track, parameterized-driven wellbore geometric modeling is carried out, and parameterized programmable control over the wellbore radius, the wellbore wall thickness and the section inclination angle is achieved. The invention provides an efficient and accurate wellbore three-dimensional modeling solution, and the wellbore modeling efficiency is greatly improved.

The invention relates to the technical field of oil field fracturing operation, and provides a horizontal well shaft completion pipe string and a reconstruction method.The horizontal well shaft completion pipe string comprises an original casing pipe, an inner casing pipe, a suspension packer, a shearing ball seat, a float collar, a float shoe and a plurality of composite metal pipe outer packers.The suspension packer is connected to one end of the inner casing pipe, and the shearing ball seat, the float collar and the float shoe are sequentially connected to the other end of the inner casing pipe; a plurality of composite metal pipe outer packers are sequentially arranged on the inner casing pipe at intervals and used for blocking an annular space between the original casing pipe and the inner casing pipe and forming a plurality of fracturing sections, the inner drift diameter of a reconstructed new shaft is large, large-displacement and high-pressure fracturing construction can be met, the construction cost is reduced, the repeated transformation efficiency of an old well reservoir is improved, and the construction period is shortened. And in the later period, the original gas production section can be ejected to implement commingling production, and the oil-gas output efficiency is further improved.

The invention discloses an intelligent agent-based oil field station unattended intelligent operation and maintenance centralized control method and system, and belongs to the technical field of oil field station intelligent operation and maintenance management. The system comprises a data acquisition module, a data summarization decision module, a station coordination execution module, an emergency intervention module and an output module; pressure sensors, temperature sensors, flow sensors, liquid level sensors and water content sensors are arranged at oil field inter-well stations, transfer stations and united stations, and crude oil conveying equipment data of the inter-well stations, the transfer stations and the united stations are collected in real time. According to the intelligent agent-based unattended intelligent operation and maintenance centralized control method and system for the oil field station, station correlation analysis, instant optimization adjustment strategy and target optimization adjustment strategy generation, station specific parameter execution, feedback and optimization adjustment strategy fine adjustment and decision process recording can be realized, and a large model and a small model are closely combined; and an up-and-down collaborative hierarchical control framework is formed, so that the practicability and functionality are enhanced.

The invention discloses a multidirectional earthquake river channel sand body prediction method. The problems that in the prior art, due to the fact that full-superposition earthquakes are adopted, signals are covered due to superposition, the distinguishing capacity is insufficient, and the prediction precision of narrow and small river channels is low are solved. The method comprises the following steps: S1, obtaining pre-stack seismic trace gather data and a sound wave impedance logging curve; s2, performing statistics to obtain the azimuth angle range of the pre-stack seismic gather as theta1-theta2; s3, acquiring a plurality of seismic bodies with different azimuth angles; s4, obtaining seismic bodies of a plurality of azimuth angles after normalization; s5, obtaining a synthetic seismic data volume; s6, acquiring a plurality of correlation coefficient data volumes; s7, obtaining a fusion seismic body; and S8, based on the obtained fused seismic body, extracting plane amplitude attributes of a target stratum, and realizing river channel sand body prediction. According to the multidirectional earthquake channel sand body prediction method, azimuth angle information of the pre-stack earthquake channel set is comprehensively utilized, the channel sand body prediction precision is improved, and the oil field exploration and development effects are improved.

The invention provides a load distribution method, device and system for numerical reservoir simulation. The method comprises the steps that a grid file is obtained, the grid file is a file representing the geological space structure of a target area, the target area is one or more of a coal mine, an oil field, a geothermal field and a gas field, and the grid file comprises a plurality of grids; loads are distributed according to the types of grids in the grid file, the types of the grids comprise structured grids or non-structured grids, the loads are equipment used for reservoir numerical simulation, and the distribution mode comprises average distribution according to the number of the grids and / or average distribution according to the calculation time of the grids, the calculation time is time for load calculation of oil-water distribution of the target area during numerical reservoir simulation; and controlling all loads, and carrying out reservoir numerical simulation based on the distributed grid file. According to the method, the problem that in the prior art, load balancing cannot be achieved during load distribution in numerical reservoir simulation grid calculation is solved.