CN111625607A - Oil-gas knowledge graph construction method and device, electronic equipment and storage medium - Google Patents
Oil-gas knowledge graph construction method and device, electronic equipment and storage medium Download PDFInfo
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The application relates to the technical field of oil and gas data processing, in particular to a method and a device for constructing an oil and gas knowledge graph, computer equipment and a storage medium. The method in one embodiment comprises: acquiring entity nodes of an oil-gas knowledge graph to be constructed, entity relations corresponding to the entity nodes, oil-gas production data and preset oil-gas production nodes; performing node data extraction on the oil and gas production data based on the oil and gas production nodes to obtain oil and gas production node data; filling the oil-gas production node data to the corresponding entity node to obtain oil-gas entity node data; and obtaining an oil-gas knowledge graph based on the oil-gas entity node data and the entity relationship. The oil and gas production data are sorted in the oil and gas knowledge map building mode, the incidence relation among all oil and gas knowledge is built, the management degree of the oil and gas production data can be improved, and the subsequent data retrieval difficulty is reduced.
Description
Technical Field
The application relates to the technical field of oil and gas data processing, in particular to a method and a device for constructing an oil and gas knowledge graph, electronic equipment and a storage medium.
Background
In the process of petroleum geological exploration, oil-gas field development and production, mass oil-gas data such as achievement reports, scientific and technical literatures, multimedia data and the like are accumulated along with the passage of time. The historical knowledge data can represent the correlation between geology such as basins, traps, oil and gas reservoirs and achievement knowledge such as source rocks, cover layers, reservoirs, fluids, reserves, production characteristics, production increasing measures, development schemes and the like.
The induction and the arrangement of the historical oil and gas data are very important for oil and gas exploration and development. The traditional oil gas data storage method generally collects, arranges and stores the oil gas data in a database. However, the oil and gas data storage method has the problems of low data management degree and difficult data retrieval due to large data volume of historical oil and gas data.
Disclosure of Invention
In view of the above, it is necessary to provide a method, an apparatus, a computer device and a storage medium for constructing an oil-gas knowledge graph, which can improve the data management degree and reduce the data retrieval difficulty.
A method of constructing a hydrocarbon knowledge map, the method comprising:
acquiring entity nodes of an oil-gas knowledge graph to be constructed, entity relations corresponding to the entity nodes, oil-gas production data and preset oil-gas production nodes;
performing node data extraction on the oil and gas production data based on the oil and gas production nodes to obtain oil and gas production node data;
filling the oil-gas production node data to corresponding entity nodes to obtain oil-gas entity node data;
and obtaining an oil-gas knowledge graph based on the oil-gas entity node data and the entity relationship.
In one embodiment, the obtaining of the entity nodes of the oil-gas knowledge graph to be constructed and the entity relationships corresponding to the entity nodes comprises:
acquiring a preset oil-gas knowledge system, and extracting oil-gas data items in the oil-gas knowledge system;
creating a time node of the oil and gas data item, and obtaining an entity node of the oil and gas knowledge graph to be constructed according to the oil and gas data item and the time node;
and acquiring business relations among the oil and gas data items according to the oil and gas knowledge system, and acquiring entity relations of the oil and gas knowledge graph to be constructed according to the business relations.
In one embodiment, the hydrocarbon production data comprises structured hydrocarbon production data;
the node data extraction of the oil and gas production data based on the oil and gas production node to obtain the oil and gas production node data comprises:
constructing a data table query statement based on the oil and gas production node;
and searching in the structured oil and gas production data through the data table query statement to obtain oil and gas production node data.
In one embodiment, the hydrocarbon production data comprises unstructured hydrocarbon production data;
the node data extraction of the oil and gas production data based on the oil and gas production node to obtain the oil and gas production node data comprises:
labeling the unstructured oil and gas production data based on the oil and gas production node to obtain labeled data;
and performing node data extraction on the unstructured oil and gas production data according to the labeled data to obtain oil and gas production node data.
In one embodiment, before the populating the oil and gas production node data to the corresponding entity node and obtaining the oil and gas entity node data, the method further includes:
when the corresponding entity node does not exist in the oil and gas production node data, a new entity node is created according to the oil and gas production node corresponding to the oil and gas production node data;
updating the entity nodes of the oil-gas knowledge graph to be constructed and the corresponding entity relations according to the created entity nodes;
the step of filling the oil and gas production node data into corresponding entity nodes to obtain oil and gas entity node data, and the step of obtaining an oil and gas knowledge graph based on the oil and gas entity node data and the entity relationship comprises the following steps:
and correspondingly filling the oil and gas production node data to the updated entity node to obtain oil and gas entity node data, and obtaining an oil and gas knowledge graph based on the oil and gas entity node data and the updated entity relationship.
In one embodiment, obtaining oil and gas production data comprises:
acquiring initial oil gas production data;
and performing knowledge fusion processing on the initial oil and gas production data, and eliminating repeated data and abnormal data in the initial oil and gas production data to obtain the oil and gas production data.
In one embodiment, the method further comprises:
acquiring an oil gas production data analysis request;
analyzing the oil gas production data analysis request to obtain a target oil gas production data item;
searching in the oil gas knowledge graph according to the target oil gas production data item, and acquiring target oil gas production data corresponding to the target oil gas production data item;
and analyzing and processing the target oil and gas production data to obtain analysis result data corresponding to the oil and gas production data analysis request.
An apparatus for constructing a hydrocarbon knowledge map, the apparatus comprising:
the data acquisition module is used for acquiring entity nodes of the oil-gas knowledge graph to be constructed, entity relations corresponding to the entity nodes, oil-gas production data and preset oil-gas production nodes;
the first processing module is used for carrying out node data extraction on the oil and gas production data based on the oil and gas production nodes to obtain oil and gas production node data;
the second processing module is used for filling the oil and gas production node data to the corresponding entity node to obtain oil and gas entity node data;
and the map generation module is used for obtaining an oil-gas knowledge map based on the oil-gas entity node data and the entity relationship.
A storage medium comprises a stored program, wherein when the program runs, equipment where the storage medium is located is controlled to execute a construction method of an oil-gas knowledge graph.
An electronic device comprising at least one processor, at least one memory connected with the processor, and a bus;
the processor and the memory complete mutual communication through the bus;
the processor is used for calling the program instructions in the memory so as to execute the oil and gas knowledge graph construction method.
According to the oil-gas knowledge graph construction method, the oil-gas knowledge graph construction device, the computer equipment and the storage medium, oil-gas production data and preset oil-gas production nodes are obtained by obtaining the entity nodes of the oil-gas knowledge graph to be constructed and the corresponding entity relations, and node data extraction is carried out on the oil-gas production data based on the oil-gas production nodes to obtain oil-gas production node data; the oil and gas production node data are filled into the corresponding entity nodes to obtain oil and gas entity node data, an oil and gas knowledge graph is obtained based on the oil and gas entity node data and the entity relationship, the oil and gas production data are sorted in the oil and gas knowledge graph building mode, the incidence relation among various oil and gas knowledge is built, the management degree of the oil and gas production data can be improved, and the subsequent data retrieval difficulty is reduced.
Drawings
FIG. 1 is an application environment diagram of a method for constructing a hydrocarbon knowledge-graph in one embodiment;
FIG. 2 is a schematic flow diagram of a method for constructing a hydrocarbon knowledge map in one embodiment;
FIG. 3 is a schematic illustration of an ontology library in an oil and gas knowledge-graph in one embodiment;
FIG. 4 is a schematic illustration of manual tagging of oil and gas production data in one embodiment;
FIG. 5 is a diagram illustrating the construction of a knowledge-graph prior to the knowledge fusion process in one embodiment;
FIG. 6 is a schematic diagram of the construction of a knowledge-graph prior to the knowledge fusion process in another embodiment;
FIG. 7 is a diagram illustrating the construction of a knowledge-graph after a knowledge fusion process in one embodiment;
FIG. 8 is a schematic representation of the King water flooding curve for a waterflood oilfield in one embodiment;
FIG. 9 is a schematic illustration of a daily production operating curve for an oil field in one embodiment;
FIG. 10 is a block diagram of a hydrocarbon knowledge map building apparatus in one embodiment;
FIG. 11 is a diagram illustrating the internal architecture of an electronic device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The method for constructing the oil-gas knowledge graph can be applied to the application environment shown in figure 1. A user inputs entity nodes of an oil-gas knowledge graph to be constructed, entity relations corresponding to the entity nodes, oil-gas production data and preset oil-gas production nodes to a data processing terminal, and the data processing terminal acquires the entity nodes of the oil-gas knowledge graph to be constructed, the entity relations corresponding to the entity nodes, the oil-gas production data and the preset oil-gas production nodes; performing node data extraction on the oil and gas production data based on the oil and gas production nodes to obtain oil and gas production node data; filling the oil-gas production node data to the corresponding entity node to obtain oil-gas entity node data; and obtaining an oil-gas knowledge graph based on the oil-gas entity node data and the entity relationship. The data processing terminal may be, but is not limited to, various personal computers, notebook computers, smart phones, and tablet computers.
In one embodiment, as shown in fig. 2, a method for constructing a hydrocarbon knowledge graph is provided, which is described by taking the method as an example of being applied to the data processing terminal in fig. 1, and includes the following steps:
step 202, acquiring entity nodes of the oil-gas knowledge graph to be constructed, entity relations corresponding to the entity nodes, oil-gas production data and preset oil-gas production nodes.
The knowledge graph refers to a structured semantic knowledge base for describing entities and relationships among the entities, and the basic composition units of the knowledge graph are entity-relationship-entity triples, and the entities are connected with one another through the relationships. The knowledge graph can be constructed in a bottom-up mode, and information extraction, knowledge fusion and knowledge processing are included. The information extraction refers to extracting entities, attributes and relationships among the entities from different data sources, and forming knowledge expression on the basis. Knowledge fusion refers to integrating acquired knowledge to eliminate contradictions or ambiguities, for example, some entities correspond to multiple expressions. The knowledge processing means that the quality of knowledge subjected to knowledge fusion processing is evaluated, and qualified parts are added into a knowledge base to ensure the quality of the knowledge base.
The oil and gas knowledge graph refers to a knowledge graph established based on oil and gas production data, the entity refers to something which is distinguishable and independent, and the entity node specifically can be a basin, an oil and gas field, a well, a core and the like, and more specifically, can be a Sichuan basin, an apricot tree oil field, a Weiji 1 well Jurassic core and the like. The oil and gas knowledge data comprise oil and gas static data and oil and gas dynamic data, wherein the static data refer to the oil and gas knowledge data which do not change along with time, such as the area of a basin, the production position of an oil field, the reserve volume of the oil field, the author, the unit and the research subject of oil and gas knowledge achievement and the like. The oil gas dynamic data refers to oil gas production data which changes every year, month and day, and the oil gas production data comprises dynamic data of annual oil production, annual water production, annual gas production, annual water content, annual rate of decline, annual well opening number and the like of an oil field.
The oil and gas production nodes refer to a body library constructed according to actual production requirements of an oil field, for example, the oil field, a block, an oil reservoir, a small layer, a single well and the like are used as nodes, each node comprises time nodes such as annual dynamic, monthly dynamic, daily dynamic and the like, and each node comprises a plurality of attributes such as dynamic attributes such as annual oil production, annual water production, annual gas production, annual water content, annual decrement rate and the like. In particular, an ontology of oil and gas knowledge maps may be as shown in fig. 3.
And 204, extracting node data of the oil and gas production data based on the oil and gas production node to obtain the oil and gas production node data.
The oil and gas production node data refers to data corresponding to oil and gas production nodes, for example, oil fields, annual oil production, cumulative oil production, annual liquid production and cumulative liquid production are used as the oil and gas production nodes, 1979 is used as the time node, specifically, 1979 of the oil field of the happy ridge of the Liaohe produces 137.12 ten thousand tons of oil, 161.80 ten thousand tons of cumulative oil production, 125.87 thousand tons of annual liquid production and 125.87 thousand tons of cumulative liquid production. Therefore, the oil and gas production node data comprises that the oil field is a Liaohe Happy ridge oil field, the annual oil production data is 137.12 ten thousand tons, the cumulative oil production data is 161.80 ten thousand tons, the annual liquid production data is 125.87 ten thousand tons, and the cumulative liquid production data is 125.87 ten thousand tons.
And step 206, filling the oil and gas production node data to the corresponding entity node to obtain the oil and gas entity node data.
The oil gas entity node data comprises entity nodes and data corresponding to the entity nodes, the oil gas knowledge graph to be constructed is only the entity nodes, and the data corresponding to each entity node are blank. And filling the obtained oil and gas production node data to the corresponding entity node to obtain oil and gas entity node data.
And step 208, obtaining an oil-gas knowledge graph based on the oil-gas entity node data and the entity relationship.
A knowledge graph is a graph-based data structure consisting of nodes, i.e. entities, represented by a globally unique identity and edges, and relationships connecting two nodes. Knowledge maps link all of the different kinds of information together to form a relational network, providing the ability to analyze problems from a relational perspective. An oil and gas knowledge graph can be constructed through Neo4j, and Neo4j is a graph database which belongs to one of NoSQL (Not Only SQL, non-relational database) and can be used for persisting data. For example, Cypher commands can be written, and the nodes and the relationships among the nodes are created in the browser through Neo4 j.
The method for constructing the oil-gas knowledge graph comprises the steps of obtaining oil-gas production data and preset oil-gas production nodes by obtaining entity nodes and corresponding entity relations of the oil-gas knowledge graph to be constructed, and extracting the node data of the oil-gas production data based on the oil-gas production nodes to obtain oil-gas production node data; the oil and gas production node data are filled into the corresponding entity nodes to obtain oil and gas entity node data, an oil and gas knowledge graph is obtained based on the oil and gas entity node data and the entity relationship, the oil and gas production data are sorted in the oil and gas knowledge graph building mode, the incidence relation among various oil and gas knowledge is built, the management degree of the oil and gas production data can be improved, and the subsequent data retrieval difficulty is reduced.
In one embodiment, the obtaining of the entity nodes of the oil-gas knowledge graph to be constructed and the entity relationships corresponding to the entity nodes comprises: acquiring a preset oil-gas knowledge system, and extracting oil-gas data items in the oil-gas knowledge system; creating a time node of an oil-gas data item, and obtaining an entity node of an oil-gas knowledge graph to be constructed according to the oil-gas data item and the time node; and acquiring business relations among oil and gas data items according to an oil and gas knowledge system, and acquiring entity relations of the oil and gas knowledge graph to be constructed according to the business relations. Time nodes can be specifically established on different oil and gas field units, the knowledge graph generally only stores static data, and the dynamic data storage function of the knowledge graph can be realized by establishing the time nodes on the different oil and gas field units. Therefore, the dynamic data storage structure based on the relational database list is changed, and the data model for storing time series dynamic data based on the knowledge map and the graph data structure is realized. In addition, a concept of time nodes is introduced, oil and gas production data are connected to the time nodes of the oil and gas knowledge graph in a hanging mode, an exploration and development knowledge base integrating dynamic exploration and development data and static exploration and development data is formed, and a solid foundation is laid for cognitive calculation of oil and gas exploration and development. The application range of the knowledge graph is expanded, the dynamic data management based on the time sequence is extended, and the diversity and the flexibility of data types in the knowledge graph are improved. The oil and gas production data are managed by using the time nodes of the knowledge graph, and the efficiency of inquiring and analyzing dynamic data is greatly improved.
In one embodiment, the oil and gas production data comprises structured oil and gas production data, and the node data extraction of the oil and gas production data based on the oil and gas production nodes comprises: constructing a data table query statement based on the oil and gas production node; and searching in the structured oil and gas production data through a data table query statement to obtain oil and gas production node data. The structured oil and gas production data refers to oil and gas production data stored in a structured database, such as oil and gas production dynamic data stored in structured databases of Oracle, MySQL, SQL Server, and the like. Dynamic data in a whole table, a partial table and different tables are extracted by constructing different SQL (structured query Language) statements, and the extracted data is converted into an entity-relationship-entity triple form in a knowledge graph by a preset program. For example, for the oil FIELD of the happy ridge of the Liaohe, the dynamic production data of the oil FIELD can be inquired FROM the Oracle database through the SQL statement of SELECT FROM FIELD _ PROD _ YEARLY, and the inquiry result is shown in the following table, wherein the unit of annual oil production, cumulative oil production, annual liquid production and cumulative liquid production is ten thousand tons, and the comprehensive water content and oil extraction speed are percentage.
TABLE 1 dynamic production data of an oil field obtained by a certain query statement
In one embodiment, the oil and gas production data comprises unstructured oil and gas production data, and the node data extraction of the oil and gas production data based on the oil and gas production nodes to obtain the oil and gas production node data comprises: labeling the unstructured oil gas production data based on the oil gas production node to obtain labeled data; and extracting node data of the unstructured oil and gas production data according to the labeled data to obtain oil and gas production node data. Unstructured oil and gas production data refers to oil and gas production data stored in unstructured oil and gas production data, such as Word documents, ppt files, and PDF files. Extracting the unstructured oil gas production data through technical means such as knowledge labeling, knowledge extraction and the like, and accessing the unstructured oil gas production data into a knowledge map. The unstructured data is an important source of oil and gas exploration and development knowledge, and can supplement and expand data in a structured database, so that the data scale and coverage range are enlarged, and the data management and integration level is improved. Specifically, for example, a section of text of the "happy ridge oil field log" is extracted from the book of "chinese oil and gas field development log", the business expert may perform artificial knowledge labeling on the dynamic data therein, and the labeling example is shown in fig. 4. By supplementing the knowledge in the existing structured database with the labeled knowledge, the document in fig. 4 can expand the number of production days, the number of production blocks, the well spacing, the well pattern type and the like in 1979 of the happy ridge oil field. In addition, according to the manually marked linguistic data, the preset knowledge extraction system can train algorithms such as natural language processing, deep learning and the like, and the trained algorithms can automatically extract the triple knowledge of a new subsequent document.
In one embodiment, before the oil and gas production node data is filled into the corresponding entity node and the oil and gas entity node data is obtained, the method further includes: when the corresponding entity node does not exist in the oil-gas production node data, a new entity node is created according to the oil-gas production node corresponding to the oil-gas production node data; updating the entity nodes of the oil-gas knowledge graph to be constructed and the corresponding entity relations according to the created entity nodes; filling oil and gas production node data to corresponding entity nodes to obtain oil and gas entity node data, and obtaining an oil and gas knowledge graph based on the oil and gas entity node data and the entity relationship, wherein the oil and gas knowledge graph comprises the following steps: and correspondingly filling the oil and gas production node data to the updated entity node to obtain oil and gas entity node data, and obtaining an oil and gas knowledge graph based on the oil and gas entity node data and the updated entity relationship. If the oil and gas production node does not exist in the pre-constructed knowledge graph ontology base, a new entity node needs to be created in the ontology base according to the oil and gas production node, a new time node is updated or created in the pre-constructed knowledge graph, and the node is connected to the corresponding entity node of the knowledge graph. For example, the production dynamic data of the Happy ridge oil field in 1979 has two sources, one is from a database, and the other is from the book of development of the Chinese oil and gas field. Creating nodes and relationships between nodes for the oil and gas dynamic production data from the database through Neo4j, as shown in fig. 5; the relation between nodes is created for oil and gas dynamic production data from China oil and gas field development log through Neo4j, and is shown in figure 6. And carrying out knowledge fusion processing on the oil and gas production data from the two sources, and connecting the time nodes subjected to the fusion processing to related oil field entities in the knowledge graph, as shown in fig. 7.
In one embodiment, obtaining oil and gas production data comprises: acquiring initial oil gas production data; and carrying out knowledge fusion processing on the initial oil gas production data, and eliminating repeated data and abnormal data in the initial oil gas production data to obtain the oil gas production data. Knowledge fusion is carried out on the structured data and the unstructured data, the fused data are accessed into a knowledge map library, knowledge fusion is carried out on repeated data and inconsistent oil and gas production dynamic data, and the knowledge fusion is realized through the existing open source tool and technology. And connecting the oil gas production data subjected to knowledge fusion processing to specific oil gas production entity nodes in a knowledge map library to obtain an oil gas knowledge map.
In one embodiment, the method for constructing the oil and gas knowledge graph further comprises the following steps: acquiring an oil gas production data analysis request, and analyzing the oil gas production data analysis request to obtain a target oil gas production data item; searching in an oil gas knowledge graph according to the target oil gas production data item, and acquiring target oil gas production data corresponding to the target oil gas production data item; and analyzing and processing the target oil and gas production data to obtain analysis result data corresponding to the oil and gas production data analysis request. The oil-gas dynamic data query, analysis, statistics, data mining and the like are carried out on the basis of oil-gas dynamic data stored in the oil-gas knowledge graph, the oil-gas dynamic data query, analysis, statistics and data mining performance on the basis of the oil-gas knowledge graph is high, and when a large number of data tables are mutually connected in the oil-gas data, the performance advantages of the oil-gas knowledge graph are particularly obvious. The oil-gas knowledge graph not only realizes the mixed storage of various dynamic data on an oil-gas field, a block, a small layer and a single well, such as the mixed storage of daily output data, monthly output data, annual output, recoverable reserves and other data, but also realizes the mixed storage of structured data and unstructured data. For example, based on the oil and gas production data stored in the oil and gas knowledge graph, the extraction degree is used as an abscissa, the water content is used as an ordinate, and the obtained waterflood oilfield boy's water flooding curve is shown in fig. 8. For another example, based on the oil and gas production data stored in the oil and gas knowledge map, the time is used as an abscissa, the production operation index is used as an ordinate, and for example, the daily oil production, the daily fluid production, the daily water injection, and the comprehensive water content are used as ordinates, and the obtained daily oil production operation curve of the oil field is shown in fig. 9.
It should be understood that, although the steps in the flowchart of fig. 2 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in fig. 2 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 10, there is provided a hydrocarbon knowledge map construction apparatus, including: a data acquisition module 1002, a first processing module 1004, a second processing module 1006, and a map generation module 1008. The data acquisition module 1002 is configured to acquire an entity node of the oil-gas knowledge graph to be constructed, an entity relationship corresponding to the entity node, oil-gas production data, and a preset oil-gas production node. The first processing module 1004 is configured to perform node data extraction on the oil and gas production data based on the oil and gas production node to obtain oil and gas production node data. The second processing module 1006 is configured to fill the oil and gas production node data into the corresponding entity node, so as to obtain oil and gas entity node data. And the map generation module 1008 is used for obtaining an oil-gas knowledge map based on the oil-gas entity node data and the entity relationship.
In one embodiment, the data acquisition module is further configured to acquire a preset oil and gas knowledge system and extract oil and gas data items in the oil and gas knowledge system; creating a time node of an oil-gas data item, and obtaining an entity node of an oil-gas knowledge graph to be constructed according to the oil-gas data item and the time node; and acquiring business relations among oil and gas data items according to an oil and gas knowledge system, and acquiring entity relations of the oil and gas knowledge graph to be constructed according to the business relations.
In one embodiment, the first processing module is further configured to construct a data table query statement based on the oil and gas production node; and searching in the structured oil and gas production data through a data table query statement to obtain oil and gas production node data.
In one embodiment, the first processing module is further configured to label the unstructured oil and gas production data based on the oil and gas production node to obtain labeled data; and extracting node data of the unstructured oil and gas production data according to the labeled data to obtain oil and gas production node data.
In one embodiment, the device for constructing the oil and gas knowledge graph further comprises a node creating module, configured to create a new entity node according to the oil and gas production node corresponding to the oil and gas production node data when the corresponding entity node does not exist in the oil and gas production node data; updating the entity nodes of the oil-gas knowledge graph to be constructed and the corresponding entity relations according to the created entity nodes; the second processing module is also used for correspondingly filling the oil and gas production node data to the updated entity node to obtain oil and gas entity node data; the map generation module is also used for obtaining an oil-gas knowledge map based on the oil-gas entity node data and the updated entity relationship.
In one embodiment, the first processing module is further configured to obtain initial oil and gas production data; and carrying out knowledge fusion processing on the initial oil gas production data, and eliminating repeated data and abnormal data in the initial oil gas production data to obtain the oil gas production data.
In one embodiment, the device for constructing the oil and gas knowledge graph further comprises a data analysis module, which is used for acquiring an oil and gas production data analysis request, analyzing the oil and gas production data analysis request and obtaining a target oil and gas production data item; searching in an oil gas knowledge graph according to the target oil gas production data item, and acquiring target oil gas production data corresponding to the target oil gas production data item; and analyzing and processing the target oil and gas production data to obtain analysis result data corresponding to the oil and gas production data analysis request.
The oil-gas knowledge graph constructing device comprises a processor and a memory, wherein the data acquiring module, the first processing module, the second processing module, the graph generating module, the node creating module, the data analyzing module and the like are stored in the memory as program modules, and the processor executes the program modules stored in the memory to realize corresponding functions.
The processor comprises a kernel, and the kernel calls the corresponding program module from the memory. The kernel can be set to be one or more than one, the management degree of oil and gas production data is improved by adjusting kernel parameters, and the subsequent data retrieval difficulty is reduced.
The embodiment of the invention provides a storage medium, wherein a program is stored on the storage medium, and the program realizes the construction method of the oil-gas knowledge graph when being executed by a processor.
The embodiment of the invention provides a processor, which is used for running a program, wherein the method for constructing the oil-gas knowledge graph is executed when the program runs.
The embodiment of the invention provides equipment, which comprises at least one processor, at least one memory and a bus, wherein the memory and the bus are connected with the processor; the processor and the memory complete mutual communication through a bus; the processor is used for calling the program instructions in the memory so as to execute the oil-gas knowledge map construction method. The device herein may be a server, a PC, a PAD, a mobile phone, etc.
The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device: acquiring entity nodes of an oil-gas knowledge graph to be constructed, entity relations corresponding to the entity nodes, oil-gas production data and preset oil-gas production nodes; performing node data extraction on the oil and gas production data based on the oil and gas production nodes to obtain oil and gas production node data; filling the oil-gas production node data to the corresponding entity node to obtain oil-gas entity node data; and obtaining an oil-gas knowledge graph based on the oil-gas entity node data and the entity relationship.
The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device: acquiring a preset oil-gas knowledge system, and extracting oil-gas data items in the oil-gas knowledge system; creating a time node of an oil-gas data item, and obtaining an entity node of an oil-gas knowledge graph to be constructed according to the oil-gas data item and the time node; and acquiring business relations among oil and gas data items according to an oil and gas knowledge system, and acquiring entity relations of the oil and gas knowledge graph to be constructed according to the business relations.
The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device: constructing a data table query statement based on the oil and gas production node; and searching in the structured oil and gas production data through a data table query statement to obtain oil and gas production node data.
The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device: labeling the unstructured oil gas production data based on the oil gas production node to obtain labeled data; and extracting node data of the unstructured oil and gas production data according to the labeled data to obtain oil and gas production node data.
The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device: when the corresponding entity node does not exist in the oil-gas production node data, a new entity node is created according to the oil-gas production node corresponding to the oil-gas production node data; updating the entity nodes of the oil-gas knowledge graph to be constructed and the corresponding entity relations according to the created entity nodes; and correspondingly filling the oil and gas production node data to the updated entity node to obtain oil and gas entity node data, and obtaining an oil and gas knowledge graph based on the oil and gas entity node data and the updated entity relationship.
The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device: acquiring initial oil gas production data; and carrying out knowledge fusion processing on the initial oil gas production data, and eliminating repeated data and abnormal data in the initial oil gas production data to obtain the oil gas production data.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, as shown in FIG. 11, a device includes one or more processors (CPUs), memory, and a bus. The device may also include input/output interfaces, network interfaces, and the like.
The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip. The memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method of constructing a hydrocarbon knowledge map, the method comprising:
acquiring entity nodes of an oil-gas knowledge graph to be constructed, entity relations corresponding to the entity nodes, oil-gas production data and preset oil-gas production nodes;
performing node data extraction on the oil and gas production data based on the oil and gas production nodes to obtain oil and gas production node data;
filling the oil-gas production node data to corresponding entity nodes to obtain oil-gas entity node data;
and obtaining an oil-gas knowledge graph based on the oil-gas entity node data and the entity relationship.
2. The method of claim 1, wherein obtaining entity nodes of the hydrocarbon knowledge-graph to be constructed and entity relationships corresponding to the entity nodes comprises:
acquiring a preset oil-gas knowledge system, and extracting oil-gas data items in the oil-gas knowledge system;
creating a time node of the oil and gas data item, and obtaining an entity node of the oil and gas knowledge graph to be constructed according to the oil and gas data item and the time node;
and acquiring business relations among the oil and gas data items according to the oil and gas knowledge system, and acquiring entity relations of the oil and gas knowledge graph to be constructed according to the business relations.
3. The method of claim 1, wherein the oil and gas production data comprises structured oil and gas production data;
the node data extraction of the oil and gas production data based on the oil and gas production node to obtain the oil and gas production node data comprises:
constructing a data table query statement based on the oil and gas production node;
and searching in the structured oil and gas production data through the data table query statement to obtain oil and gas production node data.
4. The method of claim 1, wherein the oil and gas production data comprises unstructured oil and gas production data;
the node data extraction of the oil and gas production data based on the oil and gas production node to obtain the oil and gas production node data comprises:
labeling the unstructured oil and gas production data based on the oil and gas production node to obtain labeled data;
and performing node data extraction on the unstructured oil and gas production data according to the labeled data to obtain oil and gas production node data.
5. The method of claim 1, wherein prior to populating the hydrocarbon production node data to corresponding entity nodes to obtain hydrocarbon entity node data, further comprising:
when the corresponding entity node does not exist in the oil and gas production node data, a new entity node is created according to the oil and gas production node corresponding to the oil and gas production node data;
updating the entity nodes of the oil-gas knowledge graph to be constructed and the corresponding entity relations according to the created entity nodes;
the step of filling the oil and gas production node data into corresponding entity nodes to obtain oil and gas entity node data, and the step of obtaining an oil and gas knowledge graph based on the oil and gas entity node data and the entity relationship comprises the following steps:
and correspondingly filling the oil and gas production node data to the updated entity node to obtain oil and gas entity node data, and obtaining an oil and gas knowledge graph based on the oil and gas entity node data and the updated entity relationship.
6. The method of claim 1, wherein obtaining oil and gas production data comprises:
acquiring initial oil gas production data;
and performing knowledge fusion processing on the initial oil and gas production data, and eliminating repeated data and abnormal data in the initial oil and gas production data to obtain the oil and gas production data.
7. The method of claim 1, further comprising:
acquiring an oil gas production data analysis request;
analyzing the oil gas production data analysis request to obtain a target oil gas production data item;
searching in the oil gas knowledge graph according to the target oil gas production data item, and acquiring target oil gas production data corresponding to the target oil gas production data item;
and analyzing and processing the target oil and gas production data to obtain analysis result data corresponding to the oil and gas production data analysis request.
8. An oil and gas knowledge map construction device, which is characterized by comprising:
the data acquisition module is used for acquiring entity nodes of the oil-gas knowledge graph to be constructed, entity relations corresponding to the entity nodes, oil-gas production data and preset oil-gas production nodes;
the first processing module is used for carrying out node data extraction on the oil and gas production data based on the oil and gas production nodes to obtain oil and gas production node data;
the second processing module is used for filling the oil and gas production node data to the corresponding entity node to obtain oil and gas entity node data;
and the map generation module is used for obtaining an oil-gas knowledge map based on the oil-gas entity node data and the entity relationship.
9. A storage medium comprising a stored program, wherein the program, when executed, controls a device in which the storage medium is located to perform the method of constructing a hydrocarbon knowledge map of any one of claims 1 to 7.
10. An electronic device comprising at least one processor, at least one memory connected to the processor, and a bus;
the processor and the memory complete mutual communication through the bus;
the processor is used for calling the program instructions in the memory to execute the oil and gas knowledge graph construction method of any one of claims 1 to 7.
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