CN110599034B - Dynamic management tracking system of oil extraction plant and early warning method thereof - Google Patents

Dynamic management tracking system of oil extraction plant and early warning method thereof Download PDF

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CN110599034B
CN110599034B CN201910863527.XA CN201910863527A CN110599034B CN 110599034 B CN110599034 B CN 110599034B CN 201910863527 A CN201910863527 A CN 201910863527A CN 110599034 B CN110599034 B CN 110599034B
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明光春
崔文富
于英霞
徐艳
朱平伦
杨权一
孙建康
刘一璠
叶风生
刘海峰
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Abstract

The utility model provides a dynamic management tracking system of oil recovery factory, including the customer end, the proxy server, web server and database server, the show layer, the one deck that the user directly contacted, operate on the interface that the show layer provided, the show layer is mainly used for receiving user's input data and the data after the processing of show system backstage, the user communicates each other through this interface and application, the UI interface of show layer divide into business portion and management portion, business portion includes dynamic early warning module, productivity analysis module, dynamic adjustment module three modules, management portion includes effect analysis module, categorised summarization module, basic management module.

Description

Dynamic management tracking system of oil extraction plant and early warning method thereof
Technical Field
The present invention relates to tracking systems. In particular to a dynamic management tracking system and an early warning method for an oil extraction plant.
Background
The coverage range of the existing oil reservoir dynamic tracking management software is limited, the design circulation, real-time operation and effect tracking of daily dynamic adjustment workload are still in manual and paper working states, so that unit managers cannot monitor the whole process and track in real time in the current production service circulation process, the adjustment effect is difficult to share, and the execution efficiency of dynamic analysis work is affected.
Through the construction of the system, dynamic management work can be standardized, and off-line analysis, disposal and circulation are converted into on-line operation; the dynamic analysis efficiency can be improved, and index comparison statistics can be automatically completed by a computer; the informatization construction level can be improved, and a knowledge experience system is formed by fully utilizing data sharing and analysis.
At present, most of oil fields in China enter the middle and later stages of development, in order to ensure stable production of oil production plants and shorten the time lag of finding problems, production early warning is required, the production early warning is provided according to the complex internal and external environments facing the crude oil production, the production early warning is an important content of effective management of the crude oil production, post-processing is turned to pre-prevention or in-process monitoring, effective deviation correction measures are timely adopted to keep the stable and orderly production through effective early warning control, so that the satisfactory completion of crude oil production tasks is ensured, objective rules of deviation of production operation caused by error of crude oil production management are comprehensively analyzed according to enterprise early warning management theory, main factors of production management effectiveness indexes (production) and influence degree and control methods of the main factors are mastered, the problems and the deviation existing in the production management are found early, targeted measures are taken in advance or timely, the influence of the factors on the production is minimized, and benign operation is kept.
Disclosure of Invention
The invention provides a dynamic management tracking system and an early warning method thereof for an oil extraction plant, which can realize the real-time tracking of production operation dynamic state and the dynamic early warning of the productivity of the oil extraction plant in time.
In order to achieve the above purpose, the technical scheme of the invention is as follows:
a dynamic management tracking system for oil extraction plant comprises a client, a proxy server, a Web server and a database server,
the client is equipment used by a user to access the system, and is a computer or a mobile phone provided with a Windows or MacOS, andriod or IOS operating system; the proxy server achieves the effect of load balancing by erecting the proxy server between the client and the Web server, and reduces the request pressure of the Web server; the Web server is deployed with a WEB application server for running system applications; the database server is provided with an oracle for storing system related data;
the Web server comprises a display layer and a logic layer;
the database server comprises a data layer;
the display layer is operated on an interface provided by the display layer, the display layer is mainly used for receiving input data of a user and data processed by a background of the display system, the user communicates with an application program through the interface, a UI interface of the display layer is divided into a service part and a management part, the service part comprises a dynamic early warning module, a capacity analysis module and a dynamic adjustment module, and the management part comprises an effect analysis module, a classification summarization module and a basic management module;
The logic layer is positioned between the display layer and the data layer, and provides interface service for the display layer through the call of the data interface of the data layer, thereby playing the role of going up and down. In the logic layer, a workflow engine is integrated with a Spring framework, a workflow configuration file is added into the Spring framework configuration file, the workflow engine has a series of collaboration components to complete the defining, executing and monitoring processes of the flow, has corresponding interfaces, and sets inquiry filtering and sequencing modes; flow management related logic in the system is processed by the workflow engine;
the data layer is used for performing CRUD operation on data of the database, unifying access modes of different databases and providing an interface for the logic layer to access;
the dynamic early warning module tracks the important attention well of the oil extraction factory in real time, sets a single well early warning line according to the dynamic change trend, automatically analyzes and judges early warning factors, early warns the important index change of oil quantity and water quantity in real time, assists management personnel and analysts in timely and accurately mastering the occurrence of early warning conditions, provides well type homonymy, ring ratio and trend analysis in any time period, any comparison items, self-setting early warning time and early warning indexes, and provides unit oil and water well comprehensive query, early warning query, abnormal well detailed information, abnormal well standing account, influence factor summary list and unit summary list, and specifically comprises the following functions:
(1) The key change well can automatically give an early warning,
(2) The abnormal well platform is inquired,
(3) The method is divided into single-position summarization,
(4) The influence factors are summarized and the method comprises the steps of,
(5) The components are summarized in a unit way,
(6) Untreated well count query
The productivity analysis module is used for classifying and adjusting development and effect evaluation, comprehensively analyzing according to the well pattern condition, the injection condition, the extraction condition and the water quality condition of the adjustment measures, and searching for the reason causing low yield. The content comprises: algorithm management, yield classification management, single well monthly yield analysis, unit comprehensive yield comparison and yield change analysis (analysis according to units, units and development types), and specifically comprises the following functions:
(1) The month analysis of a single well of an oil well,
(2) The comprehensive productivity of the oil well,
(3) The same-purpose and same-layer productivity of the oil well,
(4) The oil well is collected in blocks,
(5) The oil wells are grouped into a summary,
(6) The comprehensive productivity of the oil well is calculated according to the factor statistical table,
(7) The monthly water injection capacity of the water well is analyzed,
(8) A water injection capacity factor statistics table of the water well,
the dynamic adjustment module is used for circulation and operation monitoring of oil-water well adjustment workload, integrating adjustment work implementation nodes, setting special personnel to be responsible, assisting management personnel to control flow node circulation in real time, facilitating unified assessment, and setting different operation nodes according to different workload types; counting the time required for separating out each node; displaying the running flow and time at any time, and displaying the node with overtime running; providing a report form of classified operation of a water well, adjusting parameters and adjusting flow tracking functions, and specifically comprising the following functions:
(1) The water well allocation is reported,
(2) The operation of the water well is reported,
(3) The dynamic monitoring and reporting of the water well,
(4) The water well is allocated and inquired,
(5) The operation of the water well is inquired,
(6) The water well is monitored and inquired,
the effect analysis module is used for dynamically adjusting the automatic tracking statistics of the effect, carrying out summarizing comparison of unit yield and single well yield, drawing curve trend and basic graph on the effect of operation, parameter adjustment and adjustment means according to adjustment time and adjustment type conditions from the angles of single wells, well groups and units respectively, assisting management personnel in analyzing the production condition of an oil extraction plant, realizing the aim of assisting decision, and setting hierarchical statistics query according to different requirements; automatically tracking the effect and comprehensively analyzing the development effect; automatically classifying, counting and summarizing treatment effects; providing a report of unit classification statistics, adjustment time statistics and adjustment type statistics, and specifically comprising the following functions:
(1) The water well allocation effect is analyzed,
(2) The operation effect of the water well is analyzed,
(3) A water well allocation effect statistical table,
(4) A water well operation effect statistical table,
the basic management module specifically comprises the following functions:
(1) The algorithm is managed such that,
(2) The list of appendices is managed and,
(3) The relationship of the units is managed,
(4) The capacity is classified and managed,
(5) The management of the factors is affected and,
(6) The water injection capacity is classified and managed,
(7) The relationship management of the unit personnel is carried out,
(8) And (5) managing the blending cost oil price coefficient.
An automatic early warning method for a key change well of a dynamic management tracking system of an oil extraction plant comprises the following specific steps:
step 1, a time sequence is established,
the time sequence of the ith index is X i ＝(X i (1)+X i (2)+...+X i (t)), wherein X i (t) is the historical value of the ith index at the ith time,a predicted value at time t+1 of the i-th index, then,
where m is the associated depth number, the greater the value of m, k m The smaller the value, the smaller the influence of the first m time values on the predicted value is on the overall trend;
step 2, calculating the average deviation influence coefficient,
d t-j representing observed value X i (t) departure from time series X i Mean>Deviation factor, wherein->The extent of (3);
mean deviation influence coefficient lambda i X represents i (t) and X i (t-i) a degree of closeness between the means,
the solution is carried out to obtain the product,
step 3, calculating the time deviation influence coefficient,
time deviation influence coefficient mu i X represents i (t) and X i (t-i) the degree of temporal tightness between them,
solving to obtain
Step 4, calculating a correlation coefficient to represent the dependence degree of the predicted value on the known time value,
step 5, calculating a predicted value,
the correlation coefficient k calculated in the step 4 is calculated i Carry over into the predictive value of step 1Is calculated to predict +.>
Step 6, calculating the predicted value of other time,
predicting a predicted value at time t+2 of the i-th indexWill->Adding the known predicted value as a historical value into the time sequence of the ith index, performing the operation of the steps 1-5, and so on to obtain
And 7, calculating all index predicted values according to the steps 1-6.
And 8, calculating predicted values of 10 days in the future by taking oil production of the oil well and water content of the water well as indexes through the steps 1-7, and carrying out early warning display on the well triggering the early warning rule.
The early warning rule is as follows:
oil yield in t+1 day-oil yield in t day is less than or equal to-1;
the water content of the day I t+1 is less than or equal to 50.
The beneficial effects are that: the invention provides efficient, convenient and accurate service management tools and analysis tools for oil reservoir management personnel and analysis personnel, realizes tracking and early warning of the production condition of key wells in each service node, rapidly responds, makes measures, effectively improves the timeliness, accuracy, pertinence and working efficiency of development decisions, and ensures benefit development; the production operation dynamics of different business objects are tracked, the whole process management from dynamic early warning to dynamic adjustment to effect tracking of dynamic analysis work is realized, data support is provided for capacity analysis, and production operation decision is assisted. The method realizes real-time sharing of single-well dynamic data information of the oil extraction plant, comprehensively improves dynamic analysis capability of unit managers, reduces analysis workload of technicians, and improves dynamic tracking management level of the oil extraction plant. And the software management mode is changed, and the information service level is improved. And the professional software application is opened, so that the professional software management and service mode oriented to the user is realized, and the working efficiency and management level of oilfield development management and comprehensive research are improved. And the data acquisition mode is changed, so that the research and production work efficiency is improved. The data preparation link is simplified, and a user does not need to know which library is placed in which data and where, and can obtain relevant data such as static data, dynamic data, experiments and the like required by research at one time. And the achievement sharing mode is changed, and the professional cooperation level is improved. The geological research quality is guaranteed, research results among different professions are shared in the research process, and cooperative work among geological research professions is realized. The method has the advantages that efficient, convenient and accurate service management tools and analysis tools are provided for management staff and analysts, the production conditions of key wells in each service node are tracked and early-warned in real time, the quick response is realized, measures are made, the timeliness, the accuracy, the pertinence and the working efficiency of development decisions are effectively improved, and the benefit development is ensured; tracking production operation dynamics of different business objects, realizing overall process management from dynamic early warning to dynamic adjustment to effect tracking of dynamic analysis, providing data support for capacity analysis and assisting production operation decision-making; the real-time sharing of single-well dynamic data information of the oil extraction plant is realized, the dynamic analysis capability of a unit manager is comprehensively improved, the analysis workload of technicians is reduced, and the dynamic tracking management level of the oil extraction plant is improved;
Drawings
FIG. 1 is a block diagram of a system configuration of the present invention;
FIG. 2 is a flow chart of a dynamic early warning method of the present invention;
FIG. 3 is a schematic diagram of an early warning query interface of the present invention;
FIG. 4 is a schematic diagram of a single well month analysis interface according to the present invention
FIG. 5 is a schematic diagram of a layout summary interface of the present invention;
FIG. 6 is a diagram of an integrated capacity factor statistics table interface according to the present invention;
FIG. 7 is a schematic diagram of a well allocation interface according to the present invention
FIG. 8 is a schematic diagram of a dynamic monitoring interface for a well according to the present invention;
FIG. 9 is a schematic diagram of a well allocation effect analysis interface according to the present invention;
FIG. 10 is a schematic diagram of a cell personnel relationship management interface of the present invention;
Detailed Description
The invention is further described below with reference to the drawings and examples.
A dynamic management tracking system comprises a client, a proxy server, a Web server and a database server,
the client is mainly equipment used by a user to access the system, and is a computer or a mobile phone provided with a Windows or MacOS, andriod or IOS operating system.
Proxy server: the proxy server is erected between the client and the Web server to achieve the effect of load balancing, so that the request pressure of the Web server is reduced;
The Web server is mainly deployed with a WEB application server for running system applications;
the database server is provided with an oracle for storing system related data.
The Web server comprises a display layer and a logic layer, wherein the display layer and the logic layer are developed in a native+HTML 5 mixed mode, and comprise an application framework and a basic service support system, the display layer provides a concise and practical user experience for a user, and the framework installation and updating functions, single sign-on functions and message reminding functions are realized;
the basic service provides stable and efficient concurrency support for the application and provides rapid and accurate data support for the user.
The database server comprises a data layer, the data layer realizes system data support through a unified restful standard interface specification, data security is ensured by adopting strict identity authentication, the flexibility and expansibility of the system are ensured by an interface specification mode facing data resources, and the data layer adopts an oracle storage process to develop a data processing process;
the storage process is a set of pre-compiled codes, the operation speed is high, and meanwhile, the centralized modification can be realized because the codes are put into a database, and the client does not need to be reinstalled and upgraded, so that the maintenance is simple.
The display layer is used for operating on an interface provided by the display layer, the display layer is mainly used for receiving input data of a user and data processed by a background of the display system, the user communicates with an application program through the interface, the display layer displays a page by using a rendering technology in an HTML5 technology, a front-end jQuery frame and a Spring frame MVC, and interaction of front-end data and back-end data is realized through an Ajax asynchronous technology. Meanwhile, the system adopts an easy UI plug-in to design a front end UI interface so as to provide a UI interface for user interaction; the UI-dividing interface of the display layer is a business part and a management part, wherein the business part comprises a dynamic early warning module, a capacity analysis module and a dynamic adjustment module, and the management part comprises an effect analysis module, a classification summarization module and a basic management module;
The logic layer is positioned between the display layer and the data layer, and provides interface service for the display layer through the call of the data interface of the data layer, thereby playing the role of going up and down. In the logic layer, a workflow engine is integrated with a Spring framework, a workflow configuration file is added into the Spring framework configuration file, the workflow engine has a series of collaboration components to complete the defining, executing and monitoring processes of the flow, has corresponding interfaces, and sets inquiry filtering and sequencing modes; flow management related logic in the system is handled by the workflow engine.
The data layer is used for performing CRUD operation on data of the database, unifying access modes of different databases, and providing an interface for the logic layer for access, and comprises a production service library, a source database and a flow management library.
The dynamic early warning module tracks important attention wells of the oil extraction plant in real time, sets single well early warning lines according to dynamic change trend, automatically analyzes and judges early warning factors, early warns important index changes of oil quantity and water quantity in real time, and assists management staff and analysts in timely and accurately mastering the occurrence of early warning conditions. The method comprises the steps of well type homonymy, ring ratio and trend analysis in any time period, any comparison items (liquid amount, oil amount, water content and the like), self-setting early warning time and early warning indexes, and providing unit oil well and water well comprehensive inquiry, early warning inquiry (including treatment function, daily and monthly production curves and reports), abnormal well detailed information, abnormal well accounts, influence factor summary tables and unit summary tables.
The method specifically comprises the following functions:
(1) The key change well can automatically give an early warning,
aiming at the production abnormal well, carrying out dynamic early warning when the production is changed in a special way, analyzing according to the date, and carrying out early warning display on the well triggering the early warning rule;
the operation is specifically as follows: selecting page unit conditions; the date defaults to the same day, clicking is carried out after the date is selected, and the system automatically displays single well information of the triggering rule according to the oil-water well early warning rule; clicking the well number, penetrating and displaying an early warning disposal page, and carrying out reason classification selection, reason detailed description, treatment countermeasure description and other information filling.
(2) Abnormal well table inquiry
And inquiring all abnormal well (oil and water well) data treated by early warning in the period.
The operation is specifically as follows: selecting unit conditions (all the unit conditions are selected by the air), and automatically counting abnormal well information of all the units subjected to early warning treatment in a time period by the system.
(3) Grouping unit summaries
And counting the overall production conditions of the abnormal wells of different blocks within a certain period of time, and grasping the change condition of the unit. And summarizing and counting the oil, water well and production data produced and treated in unit time according to the management area.
The operation is specifically as follows: selecting a date condition and clicking on the query.
(4) Influence factor summarization
And according to different reasons, carrying out statistics and summarization on the abnormal oil-water wells. And summarizing and counting the production information of the processed abnormal wells (oil and water separation wells) in the stage time according to the classification factors.
The operation is specifically as follows: selecting a date condition and clicking on the query.
(5) Summarizing the sub-units:
and carrying out statistics of abnormal wells of the oil-water well according to different development and production units. And the whole control is convenient for technical developers. And can penetrate to check the abnormal well condition of different units. And summarizing and counting production information of the processed abnormal wells (oil and water separation wells) within the stage time according to the units.
The operation is specifically as follows: selecting a date condition and clicking on the query.
(6) Untreated well count query
And carrying out statistical query on the abnormal wells of each unit every day, and prompting unit management personnel to treat the abnormal wells. The number of wellheads that generated an early warning within the month time but were not disposed of in time or were disposed of over time is counted.
The operation is specifically as follows: the month condition is selected and the query is clicked.
The productivity analysis module is used for classifying and adjusting development and effect evaluation, comprehensively analyzing according to the well pattern condition, the injection condition, the extraction condition and the water quality condition of the adjustment measures, and searching for the reason causing low yield. The content comprises: algorithm management, yield classification management, single well monthly yield analysis, unit comprehensive yield comparison and yield change analysis (analysis by unit, unit and development type).
The method specifically comprises the following functions:
(1) The month analysis of a single well of an oil well,
different units and different months of energy production comparison are realized. And classifying and describing the productivity change condition of the heavy point change well, and classifying and describing the same layer. And the penetration function of the well number is realized, and the change condition of a single well is checked. The capacity classified hanging and the same-class hanging are realized.
The operation is specifically as follows: a selection unit (i.e. all of the blank), front and back value month (the front value defaults to 12 months of the last year), click inquiry, sorting the system according to the change of the yield from large to small, and automatically setting the single well productivity classification of which the yield change is within +/-0.5 ton as rising (or falling);
(2) The comprehensive productivity of the oil well,
and carrying out productivity analysis on the unit as a basic unit in the month range of the front and back values.
The operation is specifically as follows: only when the query type is a unit, the user can fill in the capacity change reason; the query types are divided into units, groups, partitions and plates, and other query types except the units can penetrate to unit pages to maintain the capacity change reasons;
(3) The same-purpose and same-layer productivity of the oil well,
carrying out productivity analysis by taking units as basic units in the month ranges of the front value and the back value;
The operation is specifically as follows: when the query type is a unit, the user can fill in the change reason; the query types are divided into units, groups, partitions and plates, and other query types except the units penetrate through the monthly yield report and curve page of the same layer;
(4) The oil well is collected in blocks,
the comprehensive productivity and the homonymous layer productivity of different time periods of the whole oil extraction plant are classified and counted, so that the classified summarization of different sections such as water flooding, three-production, thick oil and the like is realized, and summarized data of the comprehensive productivity and the homonymous layer are classified and summarized according to the plates;
the operation is specifically as follows: inquiring the comprehensive capacity data according to conditions such as units, partitions, groups and the like, and summarizing and displaying the partitioned blocks;
(5) The oil wells are grouped into a summary,
according to different inquiry conditions, carrying out classification inquiry and summarizing functions of dividing new wells, measures and old wells on the capacity change condition of the whole oil extraction plant, and respectively counting front and rear values of the new wells, the old wells and the measure wells according to unit, partition, grouping and plate dividing conditions;
the operation is specifically as follows: and respectively selecting the conditions of the units, the partitions, the groups and the plate blocks, determining the month of the front and back values, and clicking and inquiring.
(6) The comprehensive productivity of the oil well is calculated according to the factor statistical table,
the production running state of the whole oil extraction plant is mastered by comparing the production change of any month of the whole oil extraction plant with statistics of dividing factors of different units, groups, partitions and sections, and the single-well month production analysis is counted by summarizing the dividing factors;
the operation is specifically as follows: and selecting units (i.e. all of the unit, the partition, the grouping, the plate and the front-back value month), and summarizing and counting the designated productivity classification during the single-well month productivity analysis.
(7) The monthly water injection capacity of the water well is analyzed,
analyzing the monthly water injection capacity of a single well to realize the hooking of water injection factors;
the operation is specifically as follows: the system is characterized in that a selection unit (the blank selection is all), the month of the previous value and the month of the next value (the previous value defaults to 12 months of the last year), click inquiry is carried out, the system is ordered from big to small according to daily note change, and Shan Jingzhu water capacity factors with the difference value and the previous value contrast change range within +/-10% are automatically set to be stable.
(8) A water injection capacity factor statistics table of the water well,
the statistics of water injection capacity conditions of all water injection wells of the whole oil extraction factory according to factors is realized, the inquiry functions of units, groups, partition blocks and partition plates are realized, and the analysis data of the monthly water wells are classified and counted according to the factors.
The operation is specifically as follows: the selection unit (all empty), the front and back values versus the month, click the query.
The dynamic adjustment module is used for circulation and operation monitoring of oil-water well adjustment workload, integrating adjustment work implementation nodes, setting special personnel to be responsible for assisting management personnel to control flow node circulation in real time, and setting different operation nodes according to different workload types; counting the time required for separating out each node; displaying the running flow and time at any time, and displaying the node with overtime running; providing a report form of the classified operation of the water well and a parameter adjusting and blending flow tracking function.
The method specifically comprises the following functions:
(1) The water well allocation is reported,
in the daily development of oil reservoirs, the informatization of the whole flow of water well allocation work is realized, aiming at the key change well of a unit, unit management staff carry out formulation and condition tracking of allocation measures of the water well, and data information acquisition for adjusting daily water injection quantity of the daily water well is carried out. Realizing informatization of water well adjustment injection allocation work;
the operation is specifically as follows: selecting a filling time range, selecting a unit, and clicking to inquire;
(2) The operation of the water well is reported,
in the development process of the daily oil reservoir, the whole process tracking of the work load of the water well operation is realized, and the daily water well operation condition is collected and reported;
The operation is specifically as follows: selecting a filling time range, selecting a unit, and clicking to inquire;
(3) The dynamic monitoring and reporting of the water well,
aiming at the dynamic monitoring workload of a water well in the oil reservoir development management process, informatization, networking of a process, tracking and statistics of effects are realized, the function of dynamic monitoring service of a daily oil-water well of the oil reservoir is realized, and the storage and query functions of the oil reservoir are classified;
the operation is specifically as follows: selecting a filled date interval, selecting a unit, and clicking to inquire.
(4) The water well is allocated and inquired,
analyzing the well effect after the water is prepared;
the operation is specifically as follows: selecting the open month, selecting the unit, partition and grouping type, selecting the well type, and clicking the query.
(5) The operation of the water well is inquired,
aiming at the well operation workflow in the oil reservoir development process, the inquiry of the whole process is realized, the effect is tracked, and the well effect after operation is analyzed;
the operation is specifically as follows: selecting a well opening time range, selecting a unit, a partition and a grouping type, selecting a well type, and clicking to inquire.
(6) The water well is monitored and inquired,
monitoring production conditions of each part of the water well in the oil reservoir development process;
the operation is specifically as follows: selecting a filing date range, selecting a unit, a partition and a grouping type, selecting a well type, and clicking to inquire.
The effect analysis module is used for dynamically adjusting the automatic tracking statistics of the effect, carrying out summarizing comparison of unit yield and single well yield, drawing curve trend and basic graph on the effect of operation, parameter adjustment and adjustment means according to adjustment time and adjustment type conditions from the angles of single wells, well groups and units respectively, assisting management personnel in analyzing the production condition of an oil extraction plant, realizing the aim of assisting decision, and setting hierarchical statistics query according to different requirements; automatically tracking the effect and comprehensively analyzing the development effect; automatically classifying, counting and summarizing treatment effects; providing a report of unit classification statistics, adjustment time statistics and adjustment type statistics;
the method specifically comprises the following functions:
(1) The water well allocation effect is analyzed,
tracking and counting the well effect after the water is allocated;
the operation is specifically as follows: selecting the open month, selecting units, partitions and grouping types, selecting the well types, and clicking to inquire;
(2) The operation effect of the water well is analyzed,
tracking and counting the well effect after operation;
the operation is specifically as follows: selecting a well opening month range, selecting units, partitions and grouping conditions, selecting well types (two, three and four types), selecting adjustment types, and clicking and inquiring.
The classifying and summarizing module specifically comprises the following functions:
(1) A water well allocation effect statistical table,
realizing the effect statistics of injection and production allocation effects of different units and different time phases, and carrying out tracking statistics on the allocated water well effect;
the operation is specifically as follows: selecting a well opening month, selecting a unit, a partition and a grouping type, and selecting a well type;
(2) A water well operation effect statistical table,
tracking and counting the well effect after operation;
the operation is specifically as follows: selecting a well opening month range, selecting unit, partition and grouping conditions, and selecting well types, wherein the method comprises the following steps of: 1. two, three and four types, selecting an adjustment type, and clicking to inquire;
the basic management module specifically comprises the following functions:
(1) The algorithm is managed such that,
dividing a single well into a horizontal algorithm and a capacity algorithm, uniformly adopting the horizontal algorithm for all wells entering the local surface, and adopting the capacity algorithm for wells not entering the local surface;
the operation is specifically as follows: after the page is loaded, the well numbers of all horizontal algorithms are automatically displayed, and the row increasing operation can be realized by clicking +in the operation column of any data row, and the row deleting operation can be realized by clicking; note that: whether the operation is deleting the line or adding the line, the save button is clicked to realize the warehousing of the final result, otherwise, the operation of deleting the line, adding the line and modifying is invalid.
(2) The list of appendices is managed and,
the information with low change frequency such as plate, partition, grouping, isolayer classification and the like is formed into an annex table, so that a user can maintain the annex table by himself;
the operation is specifically as follows: firstly, inquiring the category of the annex to be maintained according to the condition area, and then carrying out information maintenance (adding, modifying and deleting) under the corresponding category by utilizing +, -and paying attention to: whether the operation is deleting the line or adding the line, the save button is clicked to realize the warehousing of the final result, otherwise, the operation of deleting the line, adding the line and modifying is invalid.
(3) The relationship of the units is managed,
the combination units are hung on the plate, the partition and the grouping relation; II, hanging the combined unit and the basic unit or the well number;
the operation is specifically as follows: the conventional combination unit is connected with the basic unit in a hanging way, and the custom combination unit is connected with the well number in a hanging way;
(4) The capacity is classified and managed,
the productivity classification tree is maintained, and is hung with a single well at a single well month productivity analysis position;
the operation is specifically as follows: the root node does not allow operation, selects a father node or a child node, and clicks an add button;
(5) The management of the factors is affected and,
the method comprises the following steps of (1) maintaining influence factors, and using an oil well early warning treatment page;
the operation is specifically as follows: the root node does not allow editing, selects a father node or a child node, and clicks an add button;
(6) The water injection capacity is classified and managed,
maintaining water injection capacity classification, and using a water well early warning treatment and a water well month water injection capacity analysis place;
the operation is specifically as follows: the root node does not allow editing, selects the parent node or child node, and clicks the add button.
(7) The relationship management of the unit personnel is carried out,
maintaining the relationship between the unit owner and the unit manager, and maintaining the relationship between the unit manager and the unit;
the operation is specifically as follows: clicking +, -, and realizing data row increasing and deleting operations;
(8) The cost of the preparation is managed by the oil price coefficient,
maintaining the cost oil price coefficient within the year;
the operation is specifically as follows: clicking +, -numbers to realize the addition and deletion of data;
the method comprises the following specific steps of:
step 1, a time sequence is established,
the time sequence of the ith index is X i ＝(X i (1)+X i (2)+...+X i (t)), wherein X i (t) is the historical value of the ith index at the ith time,a predicted value at time t+1 of the i-th index, then,
/>
where m is the associated depth number, the greater the value of m, k m The smaller the value, the smaller the influence of the first m time values on the predicted value is on the overall trend;
step 2, calculating the average deviation influence coefficient,
d t-j representing observed value X i (t) departure from time series X i Mean>Deviation factor, wherein- >The extent of (3);
mean deviation influence coefficient lambda i X represents i (t) and X i (t-i) a degree of closeness between the means,
the solution is carried out to obtain the product,
step 3, calculating the time deviation influence coefficient,
time deviation influence coefficient mu i X represents i (t) and X i (t-i) the degree of temporal tightness between them,
solving to obtain
Step 4, calculating a correlation coefficient k i Represents the dependence of the predicted value on the known time value,
step 5, calculating a predicted value,
the correlation coefficient k calculated in the step 4 is calculated i Carry over into the predictive value of step 1Is calculated to predict +.>
Step 6, calculating the predicted value of other time,
predicting a predicted value at time t+2 of the i-th indexWill->Adding the known predicted value as a historical value into the time sequence of the ith index, performing the operation of the steps 1-5, and so on to obtain/>
And 7, calculating all index predicted values according to the steps 1-6.
And 8, calculating predicted values of 10 days in the future by taking oil production of the oil well and water content of the water well as indexes through the steps 1-7, and carrying out early warning display on the well triggering the early warning rule.
The early warning rule is that the oil yield change of the oil well exceeds 1 ton, namely the oil yield in t+1 day minus the oil yield before t day is less than or equal to-1; the absolute value of the water content of (t+1 day-minus the water content of t day)/the water content of t day is more than or equal to 0.2; the absolute value of the water content (t+1 day) is more than or equal to 50m.
Namely, the early warning rule is:
oil yield in t+1 day-oil yield in t day is less than or equal to-1;
the water content of the day I t+1 is less than or equal to 50.
The workflow engine generates 23 tables for storing flow examples so that services are separated from the flows, the tables are divided into 5 types in total, namely a flow definition and flow static resource table, a runtime example table, an identity information table, a historical data table and a general data table, all data of the whole life cycle of one flow are stored in the tables, the historical data is stored, the function of each table corresponds to seven service APIs of the corresponding workflow engine, and the data of the workflow engine is automatically generated by the workflow engine;
and by utilizing a workflow technology, the work is automatically pushed to the next node according to a preset flow after being initiated, and a proxy prompt is sent at the same time, so that the service processing speed is increased.
The workflow engine and the Spring framework are integrated through configuration of an XML file, a process engine is created through configuration of a processing engine, bean elements of the processing engine are configured into a Spring framework container, the engine is managed through the container, and then seven large services generated through the processing engine can process related operations on a process instance through the seven large services. At the same time, a database needs to be configured, and 23 tables are generated in the database through a workflow engine.
The workflow engine draws a business flow chart by installing a designer plug-in;
after generating a flow definition file, the workflow engine registers the flow by reading the definition file, and the part of work needs to call an API of the action to realize the generation of a flow instance through codes;
after the process definition is deployed, a process instance is acquired through the process definition, and a starting operation is performed through the input of the defined process instance;
after the process instance is started, each user's ID is used to query the instance that owns or reaches the user's node, and the user's task can be completed. The user ID, the flow definition ID, the flow instance ID and the execution object ID are used for inquiring, and meanwhile, a unique result set, the number of the result sets, paging inquiry, list and other forms can be selected for displaying the returned results. After inquiring the instance task belonging to a certain user, the instance task is operated.
The system management module has the function of managing the user, the authority and the roles by the system manager. The implementation of the module is realized by adopting a Spring framework. The security of Web applications includes two aspects: user authentication and user authorization. The main purpose of user authentication is to verify whether the user is a user that the system has authenticated, i.e. whether this user has rights to use the system. User authentication is generally to compare the account number and password of the user with the account number and password stored in the system database, if the comparison is successful, the user has permission to access the system, and if the comparison is failed, the user does not have permission to access the system. User authorization refers to checking whether a user whose authentication is successful has the ability to perform a certain system operation, which is often referred to as a right in a software system.
Each user in the system has one or more roles, which also correspond to one or more rights. The system management is mainly aimed at realizing the management of the relationship among the user role authorities aiming at the user authorization. The relationship between users and roles and resources is a many-to-many relationship. Each resource refers to an interface access path or a page presentation path, each role matches one or more resources, and each user matches one or more roles.
And adding, deleting and modifying the resources for each role by adding, deleting and modifying the resources for each resource by entering the functional page.
The system management module adopts an MVC three-layer architecture, and simultaneously adopts a Spring framework for authority management, wherein the Spring framework uses a filter mechanism. For each request for accessing the system, the Spring framework checks whether the user information sent by the request passes the identity authentication of the system, and meanwhile judges whether the user can access the resource, namely, has specific authority to access the corresponding resource, if the user's authority is judged to access the resource, the user's request can reach the service layer to perform corresponding processing, so that the real request is calculated to the server data, and interaction is performed with the server. And for unsafe or failed judgment requests, the browser page jumps to a system login page to enable a user to log in or jump to a preset failed request page, the authority of different URL modes is configured for the user information, and the interface and page which can be accessed by the user are judged by acquiring the user information.
And judging whether interception is needed or not by acquiring a resource path of the http interface to be accessed to compare the authority resource of the login role. Therefore, the effect of different access rights owned by different users is achieved, and the main effect is that different pages can be accessed and different operations can be performed.
The above-described embodiment represents only one embodiment of the present invention, and is not to be construed as limiting the scope of the present invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention.

Claims (4)

1. A dynamic management tracking system for oil extraction plant comprises a client, a proxy server, a Web server and a database server,
the client is equipment used by a user to access the system, and is a computer or a mobile phone provided with a Windows or MacOS, andriod or IOS operating system; the proxy server achieves the effect of load balancing by erecting the proxy server between the client and the Web server, and reduces the request pressure of the Web server; the Web server is deployed with a WEB application server for running system applications; the database server is provided with an oracle for storing system related data;
The Web server comprises a display layer and a logic layer;
the database server comprises a data layer;
the display layer is operated on an interface provided by the display layer, the display layer is mainly used for receiving input data of a user and data processed by a background of the display system, the user communicates with an application program through the interface, a UI interface of the display layer is divided into a service part and a management part, the service part comprises a dynamic early warning module, a capacity analysis module and a dynamic adjustment module, and the management part comprises an effect analysis module, a classification summarization module and a basic management module;
the business logic layer is positioned between the display layer and the data layer, provides interface service for the display layer through the call of a data interface of the data layer, plays a role in supporting the starting and stopping, integrates a workflow engine with a Spring framework, adds a workflow configuration file into the Spring framework configuration file, and has a series of collaboration components to complete the defining, executing and monitoring processes of the flow, corresponding interfaces and set query filtering and sequencing modes; flow management related logic in the system is processed by the workflow engine;
The data layer is used for performing CRUD operation on data of the database, unifying access modes of different databases and providing an interface for the logic layer to access;
the dynamic early warning module tracks the important attention well of the oil extraction factory in real time, sets a single well early warning line according to the dynamic change trend, automatically analyzes and judges early warning factors, early warns the important index change of oil quantity and water quantity in real time, assists management personnel and analysts in timely and accurately mastering the occurrence of early warning conditions, provides well type homonymy, ring ratio and trend analysis in any time period, any comparison items, self-setting early warning time and early warning indexes, and provides unit oil and water well comprehensive query, early warning query, abnormal well detailed information, abnormal well standing account, influence factor summary list and unit summary list, and specifically comprises the following functions:
(1) The key change well can automatically give an early warning,
(2) The abnormal well platform is inquired,
(3) The method is divided into single-position summarization,
(4) The influence factors are summarized and the method comprises the steps of,
(5) The components are summarized in a unit way,
(6) Untreated well count query
The productivity analysis module is used for classifying and adjusting development and effect evaluation, comprehensively analyzing according to the well pattern condition, the injection condition, the extraction condition and the water quality condition of the adjustment measures, searching for reasons causing low yield, wherein the content comprises: algorithm management, yield classification management, single well month yield analysis, unit comprehensive yield comparison and yield change analysis, and specifically comprises the following functions:
(1) The month analysis of a single well of an oil well,
(2) The comprehensive productivity of the oil well,
(3) The same-purpose and same-layer productivity of the oil well,
(4) The oil well is collected in blocks,
(5) The oil wells are grouped into a summary,
(6) The comprehensive productivity of the oil well is calculated according to the factor statistical table,
(7) The monthly water injection capacity of the water well is analyzed,
(8) A water injection capacity factor statistics table of the water well,
the dynamic adjustment module is used for circulation and operation monitoring of oil-water well adjustment workload, integrating adjustment work implementation nodes, setting special personnel to be responsible for assisting management personnel to control flow node circulation in real time, and setting different operation nodes according to different workload types; counting the time required for separating out each node; displaying the running flow and time at any time, and displaying the node with overtime running; providing a report form of classified operation of a water well, adjusting parameters and adjusting flow tracking functions, and specifically comprising the following functions:
(1) The water well allocation is reported,
(2) The operation of the water well is reported,
(3) The dynamic monitoring and reporting of the water well,
(4) The water well is allocated and inquired,
(5) The operation of the water well is inquired,
(6) The water well is monitored and inquired,
the effect analysis module is used for dynamically adjusting the automatic tracking statistics of the effects, respectively carrying out summarizing comparison of unit yield and single well yield, drawing curve trend and basic graph on the effects of operation, parameter adjustment and adjustment means according to adjustment time and adjustment type conditions from the angles of single wells, well groups and units, assisting management personnel in analyzing the production conditions of oil extraction plants, and setting hierarchical statistics query according to different requirements; automatically tracking the effect and comprehensively analyzing the development effect; automatically classifying, counting and summarizing treatment effects; providing a report of unit classification statistics, adjustment time statistics and adjustment type statistics, and specifically comprising the following functions:
(1) The water well allocation effect is analyzed,
(2) The operation effect of the water well is analyzed,
(3) A water well allocation effect statistical table,
(4) A water well operation effect statistical table,
the basic management module specifically comprises the following functions:
(1) The algorithm is managed such that,
(2) The list of appendices is managed and,
(3) The relationship of the units is managed,
(4) The capacity is classified and managed,
(5) The management of the factors is affected and,
(6) The water injection capacity is classified and managed,
(7) The relationship management of the unit personnel is carried out,
(8) Blending cost and oil price coefficient management;
the automatic early warning method for the key change well of the dynamic management tracking system of the oil extraction factory comprises the following specific steps:
step 1, a time sequence is established,
the time sequence of the ith index is X i ＝(X i (1)+X i (2)+...+X i (t)), wherein X i (t) is the historical value of the ith index at the ith time,a predicted value at time t+1 of the i-th index, then,
where m is the associated depth number, the greater the value of m, k m The smaller the value, the smaller the influence of the first m time values on the predicted value is on the overall trend;
step 2, calculating the average deviation influence coefficient,
d t-j representing observed value X i (t) departure from time series X i Mean value X of (2) i Deviation factor, wherein->The extent of (3);
mean deviation influence coefficient lambda i X represents i (t) and X i (t-i) a degree of closeness between the means,
the solution is carried out to obtain the product,
Step 3, calculating the time deviation influence coefficient,
time deviation influence coefficient mu i X represents i (t) and X i (t-i) the degree of temporal tightness between them,
the solution is carried out to obtain the product,
step 4, calculating a correlation coefficient k i Represents the dependence of the predicted value on the known time value,
step 5, calculating a predicted value,
the correlation coefficient k calculated in the step 4 is calculated i Carry over into the predictive value of step 1Is predicted by the calculation formula of (2)
Step 6, calculating the predicted value of other time,
predicting a predicted value at time t+2 of the i-th indexWill->Adding the known predicted value as a historical value into the time sequence of the ith index, performing the operation of the steps 1-5, and so on to obtain
Step 7, calculating all index predicted values according to the steps 1-6;
and 8, calculating predicted values of 10 days in the future by taking oil production of the oil well and water content of the water well as indexes through the steps 1-7, and carrying out early warning display on the well triggering the early warning rule.
2. The oil production plant dynamic management tracking system of claim 1, wherein:
the Web server is deployed with a WEB application server for running system applications;
the database server is provided with an oracle for storing system related data;
the display layer and the logic layer are developed in a native+HTML 5 mixed mode, and comprise an application framework and a basic service support system, so that framework installation and updating, single sign-on and message reminding functions are realized;
The data layer realizes system data support through a unified restful standard interface specification, ensures data security by adopting strict identity authentication, ensures flexibility and expansibility of the system by adopting an interface specification mode facing data resources, and develops a data processing process by adopting an oracle storage process;
the display layer displays the page by using the rendering technology in the HTML5 technology, the front-end jQuery frame and the Spring frame MVC, and then realizes the interaction of front-end data and back-end data by the Ajax asynchronous technology, and meanwhile, adopts an easy UI plug-in to design a front-end UI interface so as to provide a UI interface for user interaction.
3. The oil production plant dynamic management tracking system of claim 1, wherein: the specific functions of each module of the dynamic early warning module, the productivity analysis module, the dynamic adjustment module, the effect analysis module, the classification summarizing module and the basic management module are as follows:
the dynamic early warning module specifically comprises the following functions:
(1) The key change well can automatically give an early warning,
aiming at the production abnormal well, carrying out dynamic early warning when the production is changed in a special way, analyzing according to the date, and carrying out early warning display on the well triggering the early warning rule;
the operation is specifically as follows: selecting page unit conditions; the date defaults to the same day, clicking is carried out after the date is selected, and the system automatically displays single well information of the triggering rule according to the oil-water well early warning rule; clicking the well number, penetrating and displaying an early warning disposal page, and carrying out reason classification selection, reason detailed description and treatment countermeasure description filling;
(2) The abnormal well platform is inquired,
inquiring all abnormal well data subjected to early warning treatment in the period of time;
the operation is specifically as follows: selecting unit conditions and date spans, and automatically counting abnormal well information of all units subjected to early warning treatment in a time period by a system;
(3) The method is divided into single-position summarization,
counting the overall production conditions of abnormal wells in different blocks within a certain period of time, grasping the change condition of units, and summarizing the production data of the oil, the water well and the production data which are produced and pre-warned and treated in a unit time according to a management area;
the operation is specifically as follows: selecting a date condition, and clicking to inquire;
(4) The influence factors are summarized and the method comprises the steps of,
according to different reasons, carrying out statistics and summarization on the abnormal oil-water wells, and summarizing and counting the production information of the processed abnormal wells in the stage time according to the classification factors;
the operation is specifically as follows: selecting a date condition, and clicking to inquire;
(5) The components are summarized in a unit way,
according to different development and production units, statistics of abnormal wells of the oil and water wells is carried out, so that technical developers can conveniently carry out overall control, penetration can be carried out, the abnormal well conditions of different units are checked, and the production information of the abnormal wells is processed in the statistics stage time according to unit summary;
the operation is specifically as follows: selecting a date condition, and clicking to inquire;
(6) The number of wells query is not handled,
carrying out statistical query on the wells which are not processed every day of each unit, supervising the unit management personnel to process the abnormal wells, and counting the number of the wellheads which generate early warning in the month time but are not processed in time or are processed overtime;
the operation is specifically as follows: selecting a month condition, and clicking to inquire;
the capacity analysis module specifically comprises the following functions:
(1) The month analysis of a single well of an oil well,
different units and different months of production capacity comparison are realized, the productivity change conditions of the heavy point change well are classified and explained, the isofunctional layers are classified and explained, the penetrating function of the well number is realized, the change condition of a single well is checked, and the productivity classified hanging and the isofunctional layers are classified and hung;
the operation is specifically as follows: selecting units, front and back value months, clicking and inquiring, sequencing the systems from big to small according to the yield change, and automatically setting the single well productivity classification of which the yield change is within +/-0.5 ton as ascending or descending;
(2) The comprehensive productivity of the oil well,
carrying out productivity analysis by taking units as basic units in the month ranges of the front value and the back value;
the operation is specifically as follows: only when the query type is a unit, the user can fill in the capacity change reason; the query types are divided into units, groups, partitions and plates, and other query types except the units can penetrate to unit pages to maintain the capacity change reasons;
(3) The same-purpose and same-layer productivity of the oil well,
carrying out productivity analysis by taking units as basic units in the month ranges of the front value and the back value;
the operation is specifically as follows: when the query type is a unit, the user can fill in the change reason; the query types are divided into units, groups, partitions and plates, and other query types except the units penetrate through the monthly yield report and curve page of the same layer;
(4) The oil well is collected in blocks,
the comprehensive productivity and the homonymous layer productivity of different time periods of the whole oil extraction plant are classified and counted, so that the classification and summarization of water flooding, three-production and thick oil sections are realized, and summarized data of the comprehensive productivity and the homonymous layer are classified and summarized according to plates;
the operation is specifically as follows: inquiring the comprehensive capacity data according to the conditions of units, partitions and groups, and summarizing and displaying the partitioned blocks;
(5) The oil wells are grouped into a summary,
according to different inquiry conditions, carrying out classification inquiry and summarizing functions of dividing new wells, measures and old wells on the capacity change condition of the whole oil extraction plant, and respectively counting front and rear values of the new wells, the old wells and the measure wells according to unit, partition, grouping and plate dividing conditions;
the operation is specifically as follows: respectively selecting unit, partition, grouping and plate dividing conditions, determining front and back value month, and clicking to inquire;
(6) The comprehensive productivity of the oil well is calculated according to the factor statistical table,
the production running state of the whole oil extraction plant is mastered by comparing the production change of any month of the whole oil extraction plant with statistics of dividing factors of different units, groups, partitions and sections, and the single-well month production analysis is counted by summarizing the dividing factors;
the operation is specifically as follows: selecting units, partitions, groups, plates and front-back value month, and summarizing and counting the designated capacity classification during single-well month capacity analysis;
(7) The monthly water injection capacity of the water well is analyzed,
analyzing the monthly water injection capacity of a single well to realize the hooking of water injection factors;
the operation is specifically as follows: selecting a unit, a front value month and a rear value month, clicking and inquiring, sequencing the system from big to small according to daily injection change, and automatically setting Shan Jingzhu water capacity factors with the difference value and the front value comparison change range within +/-10% to be stable;
(8) A water injection capacity factor statistics table of the water well,
the statistics of water injection capacity conditions of all water injection wells of the whole oil extraction factory according to factors is realized, the inquiry functions of units, groups, partition blocks and sections are realized, and the analysis data of the monthly water wells are classified and counted according to the factors;
the operation is specifically as follows: selecting a unit, comparing front and rear values with month, and clicking to inquire;
The dynamic adjustment module specifically comprises the following functions:
(1) The water well allocation is reported,
in the daily development of oil reservoirs, the informatization of the whole flow of water well allocation work is realized, aiming at the key change well of a unit, unit management staff carries out formulation and condition tracking of allocation measures of the water well, data information acquisition for adjusting daily water injection quantity of the daily water well is carried out, and the informatization of water well adjustment injection allocation work is realized;
the operation is specifically as follows: selecting a filling time range, selecting a unit, and clicking to inquire;
(2) The operation of the water well is reported,
in the development process of the daily oil reservoir, the whole process tracking of the work load of the water well operation is realized, and the daily water well operation condition is collected and reported;
the operation is specifically as follows: selecting a filling time range, selecting a unit, and clicking to inquire;
(3) The dynamic monitoring and reporting of the water well,
aiming at the dynamic monitoring workload of a water well in the oil reservoir development management process, informatization, networking of a process, tracking and statistics of effects are realized, the function of dynamic monitoring service of a daily oil-water well of the oil reservoir is realized, and the storage and query functions of the oil reservoir are classified;
the operation is specifically as follows: selecting a filled date interval, selecting a unit, and clicking and inquiring;
(4) The water well is allocated and inquired,
Analyzing the well effect after the water is prepared;
the operation is specifically as follows: selecting the open month, selecting units, partitions and grouping types, selecting the well types, and clicking to inquire;
(5) The operation of the water well is inquired,
aiming at the well operation workflow in the oil reservoir development process, the inquiry of the whole process is realized, the effect is tracked, and the well effect after operation is analyzed;
the operation is specifically as follows: selecting a well opening time range, selecting units, partitions and grouping types, selecting well types, and clicking to inquire;
(6) The water well is monitored and inquired,
monitoring production conditions of each part of the water well in the oil reservoir development process;
the operation is specifically as follows: selecting a filing date range, selecting a unit, a partition and a grouping type, selecting a well type, and clicking to inquire;
the effect analysis module specifically comprises the following functions:
(1) The water well allocation effect is analyzed,
tracking and counting the well effect after the water is allocated;
the operation is specifically as follows: selecting the open month, selecting units, partitions and grouping types, selecting the well types, and clicking to inquire;
(2) The operation effect of the water well is analyzed,
tracking and counting the well effect after operation;
the operation is specifically as follows: selecting a well opening month range, selecting a unit, a partition and grouping conditions, selecting a well type, selecting an adjustment type, and clicking and inquiring;
The classifying and summarizing module specifically comprises the following functions:
(1) A water well allocation effect statistical table,
realizing the effect statistics of injection and production allocation effects of different units and different time phases, and carrying out tracking statistics on the allocated water well effect;
the operation is specifically as follows: selecting a well opening month, selecting a unit, a partition and a grouping type, and selecting a well type;
(2) A water well operation effect statistical table,
tracking and counting the well effect after operation;
the operation is specifically as follows: selecting a well opening month range, selecting unit, partition and grouping conditions, and selecting well types, wherein the method comprises the following steps of: 1. two, three and four types, selecting an adjustment type, and clicking to inquire;
the basic management module specifically comprises the following functions:
(1) The algorithm is managed such that,
dividing a single well into a horizontal algorithm and a capacity algorithm, uniformly adopting the horizontal algorithm for all wells entering the local surface, and adopting the capacity algorithm for wells not entering the local surface;
the operation is specifically as follows: after the page is loaded, the well numbers of all horizontal algorithms are automatically displayed, and the row increasing operation can be realized by clicking +in the operation column of any data row, and the row deleting operation can be realized by clicking; whether the operation is deleting the line or adding the line, the storage button is clicked to realize the storage of the final result, otherwise, the operation of deleting the line, adding the line and modifying is invalid;
(2) The list of appendices is managed and,
classifying the plates, the partitions, the groups and the isolayers, forming an annex table from information with low change frequency, and enabling a user to maintain the annex table by himself;
the operation is specifically as follows: firstly, inquiring the category of the annex to be maintained according to the condition area, and then, carrying out information maintenance under the corresponding category by utilizing + -and taking into account: whether the operation is deleting the line or adding the line, the storage button is clicked to realize the storage of the final result, otherwise, the operation of deleting the line, adding the line and modifying is invalid;
(3) The relationship of the units is managed,
the combination units are hung on the plate, the partition and the grouping relation; II, hanging the combined unit and the basic unit or the well number;
the operation is specifically as follows: the conventional combination unit is connected with the basic unit in a hanging way, and the custom combination unit is connected with the well number in a hanging way;
(4) The capacity is classified and managed,
the productivity classification tree is maintained, and is hung with a single well at a single well month productivity analysis position;
the operation is specifically as follows: the root node does not allow operation, selects a father node or a child node, and clicks an add button;
(5) The management of the factors is affected and,
the method comprises the following steps of (1) maintaining influence factors, and using an oil well early warning treatment page;
the operation is specifically as follows: the root node does not allow editing, selects a father node or a child node, and clicks an add button;
(6) The water injection capacity is classified and managed,
maintaining water injection capacity classification, and using a water well early warning treatment and a water well month water injection capacity analysis place;
the operation is specifically as follows: the root node does not allow editing, selects a father node or a child node, and clicks an add button;
(7) The relationship management of the unit personnel is carried out,
maintaining the relationship between the unit owner and the unit manager, and maintaining the relationship between the unit manager and the unit;
the operation is specifically as follows: clicking +, -, and realizing data row increasing and deleting operations;
(8) The cost of the preparation is managed by the oil price coefficient,
maintaining the cost oil price coefficient within the year;
the operation is specifically as follows: clicking +, -numbers to realize the addition and deletion of the data.
4. The dynamic management tracking system of oil extraction plant according to claim 1, wherein the pre-warning rules are: oil yield in t+1 day-oil yield in t day is less than or equal to-1;
the water content of the t+1 day is less than or equal to 50.
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