JP6261824B2 - Data correction system and data correction method - Google Patents

Description

  The present invention relates to a data correction system and a data correction method.

  When developing resources that extract and produce crude oil, natural gas, various minerals, etc., collect information on various events, such as monitoring the production volume of the target resources, the presence of abnormalities at the production site, or evaluating the economics of development projects. It is common to perform analysis.

  In addition, the collection and analysis of such information is carried out by various stakeholders involved in resource development for their respective purposes. Stakeholders in resource development are, for example, operators who own wells, service companies that excavate and construct wells, and administrative organizations that collect data for the purpose of protecting the environment in the development area.

  As described above, when the purpose of collecting and analyzing information varies from stakeholder to stakeholder, the accuracy and granularity of the data handled tend to be different. For example, public documents managed by administrative agencies are often composed of text written by hand on paper media. On the other hand, production data of each well managed by an operator is often composed of measured values obtained frequently from observation sensors or the like. When such various data are used for analysis or the like, it is necessary to perform processing for specifying each data related to the same event or time even if the format is different.

  The following techniques have been proposed as conventional techniques related to such processing. In other words, for each non-structural data such as a document related to oil drilling, information on the occurrence position and time of the event targeted by the non-structural data is given as a tag, and thereafter, it is related to a specific position and time. A technique (see Patent Document 1) that specifies unstructured data to be identified by search based on a tag and provides it to a drilling worker has been proposed.

US200906230

  However, since the accuracy and granularity of data in each information vary, there are many cases where consistency of data relating to the same event cannot be obtained between information even if such data is associated with position and time. For example, in the information handled by government agencies, the data regarding processes using specific chemical substances are detailed and accurate, while the information handled by operators does not include or simplify data regarding such processes. is there. On the other hand, in the case of well drilling and production volume data, operators handle detailed and accurate data, but there are cases where administrative agencies handle only simplified data. Therefore, even if data analysis is performed across each information, the analysis accuracy is limited, and the data collected in various ways cannot be used effectively.

  Accordingly, an object of the present invention is to provide a technique that ensures data consistency regarding the same event among information regarding resource development and enables analysis across each information.

Data correction system of the present invention to solve the above problems is the information each stakeholder held with the predetermined resource development, a storage device for storing the execution history of the resource development process, the storage device are stored, wherein a said execution history of each stakeholder, the execution history of the process, respectively the stakeholders to hold for a given step in the same development target collates it relates time implementation, implementation period A process for correcting the implementation time so as to conform to the constraints of the process order of the resource development with respect to the implementation history in which the inconsistency is identified, and the storage device stores The implementation history of the relevant process, which is held by the interested party regarding the predetermined process in the same development target, with respect to the implementation area and the implementation content. Collates relates granularity or sets whether over data to identify the differences in the particle size or the setting whether, those among granularity of data to which the difference has been identified having the smaller ones or data sets, target of the differences A predetermined calculation is performed on either the data having a larger granularity, or the data for the predetermined execution area or the content of the execution in the predetermined process, which is data for calculation of the data without the data setting, and the process an arithmetic unit for executing a reasoning process to interpolate an other data to be insufficient for a given range of, characterized in that it comprises a.

Further, the data correction method of the present invention is the information each stakeholder held with the predetermined resource development, information processing system comprising a storage device that stores execution history of the resource development process, the storage The implementation history of each stakeholder stored in the device, the relevant stakeholder holding for the predetermined process in the same development object, the execution history of the relevant process is collated, The storage device stores a process for identifying the implementation time inconsistency, correcting the implementation time so that the implementation history in which the inconsistency is identified conforms to the constraints of the process sequence of the resource development , and The implementation history of the process, which is the implementation history of each of the interested parties, and each of the interested parties holds for the predetermined process in the same development target Collates relates granularity or setting presence or absence of data regarding to identify differences in the particle size or the setting whether, those among granularity of data to which the difference has been identified having the smaller ones or data set, of the difference Perform a predetermined calculation on either the data with the larger granularity targeted, or the data of the predetermined implementation area or the content of the implementation in the predetermined process that is the data for calculation of the data without the data setting, And inference processing for interpolating other data that is insufficient with respect to a predetermined range of the process .

  According to the present invention, data consistency related to the same event is ensured between pieces of information, and analysis across each piece of information becomes possible.

It is a figure which shows the structural example of the data correction system in this embodiment. It is a figure which shows the example of a data structure of fracturing DB in this embodiment. It is a figure which shows the example of a data structure of work report DB in this embodiment. It is a figure which shows the example of a data structure of the well excavation track | orbit DB in this embodiment. It is a figure which shows the example of a data structure of document storage DB in this embodiment. It is a figure which shows the example of a data structure of business process constraint condition DB in this embodiment. It is a figure which shows the data structure of corrected work record DB in this embodiment. It is a flowchart which shows process sequence example 1 of the data correction method in this embodiment. It is a flowchart which shows process sequence example 2 of the data correction method in this embodiment. It is a figure which shows the example of a screen in this embodiment.

--- System configuration ---
Embodiments of the present invention will be described below in detail with reference to the drawings. FIG. 1 is a diagram illustrating a network configuration example including a data correction system 100 according to the present embodiment. A data correction system 100 shown in FIG. 1 is a computer system that ensures data consistency related to the same event among information related to resource development and enables analysis across each information.

  As information on resource development to be processed by the data correction system 100 of the present embodiment, information held by each stakeholder in association with shale oil development is assumed. In the development of shale oil, a well is drilled horizontally from a vertical shaft that reaches the shale layer in the ground, and a high water pressure is applied from there to generate cracks in the bedrock layer (fracturing: hydraulic fracturing method) A series of steps such as injecting chemicals into the crack and collecting shale oil are performed.

  Therefore, the data correction system 100 according to the present embodiment corrects inconsistencies relating to data such as the contents of each process and work date for each piece of information held by each stakeholder, and the corrected data and other data (no correction is required). Inferring fine-grained detailed information based on In addition, the data correction system 100 appropriately processes each piece of information including the data that has undergone such correction and inference, for example, with respect to the three-dimensional position of the oil field (the area where the well is drilled), Information associating the name, amount used, injection date and the like is displayed on an appropriate display device.

  The hardware configuration of such a data correction system 100 is as follows. The data correction system 100 reads out to the memory 103 a storage device 101 composed of a non-volatile storage element such as a hard disk drive, a memory 103 composed of a volatile storage element such as a RAM, and a program 102 held in the storage device 101. Connected to the network 104 and the CPU 104 (arithmetic unit) that performs various determinations, computations, and control processing, and performs input / output processing such as a keyboard and a display. Each hardware element of the communication device 106 responsible for communication processing with other devices such as the client terminal 150 is provided.

  The CPU 104 described above implements the functions of the conversion unit 121, the correction unit 122, the inference unit 123, and the display processing unit 124 by executing the program 102 stored in the storage device 101. In addition to the program 102 described above, the storage device 101 stores a fracturing DB 131, a work report DB 132, a document storage DB 133, a well excavation trajectory DB 134, a business process constraint DB 135, and a corrected work record DB 136. Yes.

  On the other hand, the client terminal 150 connected to the data correction system 100 described above via the network 10 is a PC used by an environmental monitor such as an administrative organization or a shale oil excavator. The client terminal 150 accepts an input operation by an environmental monitor such as an administrative organization or a shale oil driller using an input interface such as a keyboard or a mouse, and the processing target information obtained here is used as the data correction system 100. Send to. Further, the client terminal 150 receives the analysis result based on the above-mentioned information transmitted from the data correction system 100 and displays it on a display device such as a display.

In this embodiment, it is assumed that information is input / output by the client terminal 150 described above, but information may be input / output via the I / O 105 of the data correction system 100.
--- Functional structure ---
Subsequently, functions provided in the data correction system 100 of the present embodiment will be described. As described above, the functions described below can be said to be functions that are implemented when the CPU 104 of the data correction system 100 executes the program 102, for example. Details of the database in this description will be described later.

  The data correction system 100 of the present embodiment collates a plurality of types of information obtained from each stakeholder regarding shale oil development, and identifies inconsistencies in data related to the same event such as the same process related to the same well between the information. In addition, the data for which the inconsistency is specified is provided with a correction function for correcting the inconsistency based on the business process constraint condition DB 135 that defines constraints on the process order of shale oil development. This correction function is provided in the correction unit 122 described above.

  Moreover, when the data correction system 100 collates the above-mentioned plurality of types of information in the correction unit 122 and identifies inconsistencies in the execution timing of the same process among the information, The process execution time before and after the process conforms to the restriction rules in the business process constraint DB 135, and the execution time of the process in the specified information is changed to other information in which inconsistency is specified. It has a function to implement the process in

  In the data correction system 100, the correction unit 122 collates a series of execution times of each process indicated by the above-described plurality of types of information with a restriction rule in the business process restriction condition DB 135, and a series of executions indicated by each information. A function is included that identifies the process that violates the constraint and the timing of its implementation, and corrects the timing of the identified process to a timing that is consistent with the implementation timing of the process before and after the process and meets the constraint. ing.

  In addition, the data correction system 100 collates the above-described plurality of types of information, specifies the difference in data granularity or the presence / absence of setting between the information, and the granularity of the data in which the difference is specified is higher. A function is provided for interpolating other data that is insufficient with respect to a predetermined range of the same event using a predetermined algorithm based on a small one or a data setting. This function is provided in the inference unit 123 described above.

  Further, the data correction system 100 does not include the execution frequency value as the execution content based on the execution content data in which the inference unit 123 specifies the above-described difference in the execution content data including the execution frequency value of the predetermined work. For the data including the value of the execution area, between the function of calculating the position of each divided area obtained by dividing the execution area by the number of execution times described above, and the execution time of the process and the next process in the execution area Is provided with a function of calculating the execution time of each divided area obtained by dividing the period of time by the number of execution times described above.

  Further, the data correction system 100 does not include the execution frequency value as the execution content based on the execution content data in which the inference unit 123 specifies the above-described difference in the execution content data including the execution frequency value of the predetermined work. With respect to data including the usage amount of a predetermined substance in the process, a function of calculating a value obtained by dividing the usage amount of the predetermined substance by the above-mentioned execution count value as the usage amount of the predetermined substance at the execution time of each divided area is further provided. ing.

Further, the data correction system 100 extracts data included in each of a plurality of types of information regarding at least the inconsistency correction process or inference process described above, and performs a predetermined process using a predetermined algorithm on the extracted data. And a function for outputting the result of the predetermined processing to a display device such as the client terminal 150 or the I / O 105. This function is provided in the display processing unit 124.
---- Data structure ---
Next, databases used by the data correction system 100 of this embodiment will be described. FIG. 2 shows an example of the data structure of the fracturing DB 131 in this embodiment. The fracturing DB 131 in this embodiment holds detailed information on the amount of water injected into the shale layer in the ground for the purpose of rock crushing and the chemicals injected into it in the fracturing process associated with the development of shale oil. Database. The fracturing DB 131 is a database that stores information input from the client terminal 150 by an operator who owns a well in shale oil development or a service company that excavates or constructs a well.

  In the fracturing DB 131 exemplified here, the record structure is in charge of the work execution date 212 of the fracturing process, with the well ID 211 uniquely identifying each well drilled in the oil field of the predetermined area as a key. The operator name 213, the total amount 214 of injected water, the work purpose 215, the classification 216 of the injected chemical substance, the ID 217, the substance amount 218, and the concentration 219 are associated with each other.

  FIG. 3 is a diagram showing an example of the data structure of the work report DB 132 in the present embodiment. The work report DB 132 in this embodiment is a database that stores, for example, electronic data of application forms and work reports for obtaining approval for the state government by the above-described operator or service company, for example, regarding well drilling. In the present embodiment, it is assumed that data related to the implementation of fracturing is stored in the work report DB 132.

  Such application forms and work reports are generally written on paper. Therefore, the conversion unit 121 of the data correction system 100 executes the appropriate character recognition process on the scan data of the application form or work report transmitted from the client terminal 150 to obtain the structure data. Assume that it is stored in the work report DB 132. As a character recognition processing technique, for example, OCR (optical character recognition) software may be adopted.

  In the work report DB 132 illustrated here, the record structure is shale oil development with a well ID 221 (common to that of the fracturing DB 131) that uniquely identifies each well drilled in the oil field of a predetermined area as a key. This is a configuration in which values such as the work execution date 222 of each process, the work name 223, and the number of times 224 of crushing work performed on the corresponding well are associated with each other.

  FIG. 4 is a diagram showing an example of the data structure of the document storage DB 133 in this embodiment. The document storage DB 133 in the present embodiment is a document managed by the state government regarding well drilling associated with shale oil development, such as the above-mentioned reports and application forms, and details of injected chemical substances accumulated by NPOs for the purpose of environmental protection. Is a database in which electronic data of a document in which is recorded is stored.

  In the document storage DB 133 exemplified here, the record structure is injected using the document ID 225 that uniquely identifies the stored document as a key, the document type, the registrant, and the well ID 228 to which the corresponding document is described. This is a configuration in which chemical substance classification 229 and values such as the amount of injected substance are associated with each other.

  FIG. 5 is a diagram showing a data structure example of the well excavation trajectory DB 134 in the present embodiment. The well excavation trajectory DB 134 in the present embodiment is a database that holds information on trajectory coordinates of the well excavated in the oil field. The well excavation trajectory DB 134 is a database that stores information input from the client terminal 150 by an operator who owns a well in shale oil development or a service company that excavates and constructs a well.

  In the well excavation trajectory DB 134 illustrated here, the record structure thereof is a well ID 231 (fracturing DB 131, work report DB 132, and document storage DB 133) that uniquely identifies each well excavated in an oil field in a predetermined area. Each of them has a configuration in which values such as a drilling direction 232, a total drilling distance 233, a vertical drilling depth 234, a latitude 235, and a longitude 236 are associated with each other. Such a record is recorded at a certain time or a certain distance in the execution order of the well excavation work by the service company, and the work order and the record order are the same.

  FIG. 6 is a diagram showing an example of the data structure of the business process constraint DB 135 in this embodiment. The business process constraint DB 135 in the present embodiment is a database that defines constraint conditions related to business processes such as the order of each process in the shale oil development, the context, and repetition. In the example of FIG. 6, an example is shown in which the constraint conditions of the fracturing process related to shale oil development are stored, but of course, other process constraint conditions related to resource development may also be stored.

  In the business process restriction condition DB 135 exemplified here, information defining the order restriction of each process related to shale oil development includes drilling 241, casing 242, plug installation 243, drilling blast 244, hydraulic fracturing 245 (fracturing process), This is a configuration in which the sequence of processes such as crude oil production 246 is associated with a sequence of processes in the development of shale oil and a sequence of processes such as a constraint that repeats between hydraulic crushing 245 and plug installation 243 among the processes. Yes. The business process constraint DB 135 is a database that stores information on constraint conditions input from the client terminal 150 by an operator who owns a well in shale oil development or a service company that excavates or constructs a well.

  FIG. 7 is a diagram showing a data structure of the corrected work record DB 136 in the present embodiment. The corrected work record DB 136 in the present embodiment is a database that stores each data that has been corrected by the correction unit 122 and inferred by the inference unit 123.

In the corrected work record DB 136 in this embodiment, the record structure is a well ID 301 (fracturing DB 131, work report DB 132, and document storage DB 133) that uniquely identifies each well drilled in an oil field in a predetermined area. The operation execution date 302 for the well, the operation name 303, the latitude / longitude 304, the depth 305 in the vertical direction of the drilling, the amount of water 306 injected during the crushing operation, and the name of the chemical substance injected 307 , The amount 308 of the injected chemical substance, the concentration 309 of the injected chemical substance, and the like are associated with each other.
--- Flow example 1 ---
Hereinafter, the actual procedure of the data correction method in the present embodiment will be described with reference to the drawings. Various operations corresponding to the data correction method described below are realized by a program 102 that the CPU 104 of the data correction system 100 reads into the memory 103 and executes. These programs are composed of codes for performing various operations described below.

  FIG. 8 is a flowchart showing a processing procedure example 1 of the data correction method according to the present embodiment. Specifically, the processing flow is performed by the correction unit 122 of the data correction system 100. In this case, the correction unit 122 first searches the fracturing DB 131 and the work report DB 132 with respect to the document related to each well stored in the document storage DB 133 using the well ID indicated by the record of the document as a key. A record relating to a well to be identified is specified (401).

  As a result of the above identification, if there is a well whose record could not be identified (402: No), the correction unit 122 reads the document file (characters) from the document storage DB 133 regarding the well where the record, that is, the structural data does not exist. (Unstructured unrecognized data) is read out, and this is instructed to the conversion unit 121 to be converted into structural data (403). In this case, the conversion unit 121 performs the conversion using an existing technology such as an optical character recognition technology. The correction unit 122 that has obtained the structure data from the conversion unit 121 stores it in the fracturing DB 131 and the work report DB 132. By the processing so far, the corresponding records (structure data) are registered in the fracturing DB 131 and the work report DB 132 for each document stored in the document storage DB 133, that is, for each well.

  Subsequently, the correction unit 122 performs a record search using each well ID as a key in the fracturing DB 131 and the work report DB 132, and specifies a record group for each well (404). Further, the correction unit collates the execution time of the process, that is, the values of the work execution dates 212 and 222 between the records constituting the record group specified here, and detects the difference (405).

  As a result of the above-described detection, when there is a difference between the work execution dates 212 and 222 of the fracturing process (406: Yes), the correction unit 122 assigns each record of the above-described record group to the business process constraint condition. Collate with the restriction of the process order specified by DB135, and identify the record in which the work execution date of the fracturing process and the processes before and after it conforms to the above-mentioned restrictions. The work execution date in the other record is updated with the work execution date in (407).

  Further, the correction unit 122 records the record that has been updated, that is, corrected as described above, in the corrected work record DB 136 as a corrected record (408).

  Subsequently, in the fracturing DB 131 and the work report DB 132, the correction unit 122 checks a series of work execution dates of each process indicated by each record related to the same well with the above-described process order restrictions, and a series of data indicated by each record. A process that violates the above-mentioned restrictions on the work execution date and the execution time are specified (409). That is, a constraint condition violation is detected.

  As a result of the above detection, when a violation of the constraint condition is detected for the work execution date (410: Yes), the correction unit 122 matches the work execution date of the specified process with the work execution dates of the processes before and after the process. In addition, correction is made at a time that meets the above-mentioned constraints (411). At this time, the correction unit 122 records the corrected record in the corrected work record DB 136 as the corrected record for the record corrected for the work execution date (412).

  In the processing of step 411 described above, for example, it is assumed that the value of the work execution date 212 “2012/10/31” is included for the record of the well ID “00001” in the fracturing DB 131, that is, the fracturing process. In addition, regarding the well ID “00001”, in the work report DB 132, a record that the work execution date 222 is “2012/9/15” and the work name 223 is “hydraulic crushing” (that is, the fracturing process) and the work execution are performed. It is assumed that there is a record in which the date 222 is “2012/9/30” and the work name 223 is “crude oil production”.

  In this case, the correction unit 122 refers to the restriction on the process order defined by the business process restriction condition DB 135, and a situation in which the “hydraulic crushing” process is executed after the “crude oil production” process cannot occur. Among the records, the work execution date indicated by the record of the “hydraulic crushing” process, that is, the fracturing process, is determined that “2012/9/15” registered in the “hydraulic crushing” process record of the work report DB 132 is correct, The value of the work execution date 212 in the corresponding record of the fracturing DB 131 is updated with this work execution date.

Next, the correction unit 122 obtains the corrected record stored in the corrected work record DB 136 and the record that the fracturing DB 131 and the work report DB 132 do not need to be corrected in the process up to the above. A process such as reading, for example, generating screen data enumerated regarding each process and its contents for each work execution date is applied, and this is output to the client terminal 150 or the I / O 105 (413), and the process is terminated.
--- Flow example 2 ---
Next, a flow based on processing by the inference unit 123 of the data correction system 100 will be described. FIG. 9 is a flowchart showing a processing procedure example 2 of the data correction method according to this embodiment. This flow is triggered by a batch process planned by the client terminal 150, an execution request by a user input at the client terminal 150, or a predetermined access from the client terminal 150 to the data correction system 100. Shall be.

  In this flow, the inference unit 123 includes, for example, the number of times of crushing between records relating to the same well among the records of the fracturing DB 131, the work report DB 132, the well excavation trajectory DB 134, and the corrected work record DB 136. For the latitude and longitude of each end point in the horizontal portion of the well and the amount of chemical injection, the difference in the granularity or presence of the data is identified (500). As in the present embodiment, it is clear that the granularity or presence / absence of the above data is different among the fracturing DB 131, the work report DB 132, the well excavation trajectory DB 134, and the corrected work record DB 136. In this case, step 500 may be unnecessary.

  Subsequently, the inference unit 123 determines that the work name 223 is “hydraulic crushing” in the well ID record “00001” in the work report DB 132, the work execution date 222, and the number of times of crushing 224. In the record in which the value exists in the record, the record in which the work name 223 is “crude oil production”, and the fracturing DB 131, the well drilling trajectory DB 134, and the corrected work record DB 136, the same well, that is, the well ID “ It is confirmed whether there is a well record “00001” (501).

  As a result of the above confirmation, when the existence of the corresponding record can be confirmed (502: Yes), the inference unit 123 determines that the excavation direction 232 is related to the above-mentioned well “00001” in the corresponding record in the well excavation trajectory DB 134. The record immediately after the record that is “vertical” identifies the record in which the excavation direction 232 is “horizontal”, and the values of the latitude 235, longitude 236, and drilling vertical direction depth 234 of the record are determined. It is acquired as one end point coordinate of the horizontal portion in the well “00001” (503).

  Further, the inference unit 123 identifies the last record in which the excavation direction 232 is “horizontal” among the records of the well “00001” in the well excavation trajectory DB 134, and the latitude 235, longitude 236, Each value of the drilling vertical direction depth 234 is acquired as the other end point coordinate of the horizontal portion in the well “00001” (504). Further, the inference unit 123 calculates the distance between the end point coordinates acquired in the above-described steps 503 and 504 as the distance of the horizontal portion in the well “00001” (505).

  Subsequently, the inference unit 123 acquires the value of the number of crushing times 224 from the record related to the well “00001” that has been identified from the fracturing DB 131 in step 501, and uses the obtained crushing number value to determine the horizontal portion described above. Are equally divided, and the latitude, longitude, and depth of each division position are inferred as the positions of hydraulic fracturing points (506).

  In this case, the inference unit 123 generates a record having the same data structure as that in the fracturing DB 131 with respect to the latitude, longitude, and depth of each hydraulic crushing place inferred above, and uses this as a corrected record to correct the corrected work record It records in DB136 (507).

  For example, if the distance of the well “00001” is calculated as “521 m” based on the values of latitude 235, longitude 236, and drilling vertical direction depth 234 indicated by records 1342 and 1343 in the well excavation trajectory DB 134 of FIG. To do. Further, as indicated by the record 1321 of the work report DB 132 in FIG. 3, it is assumed that the value of the number of times of crushing 224 in the well “00001” is “3 times”.

  In this case, the inference unit 123 converts the one end point coordinate “latitude−103.54, longitude 47.56, depth 10756” to the other end point coordinate “latitude−103.54, longitude 47.58, depth 10756”. The distance “521m” of the horizontal part leading to “3” is divided into three, and the coordinates of the divided positions between the end point coordinates are “longitude 47.56, latitude −103.54, depth 10756”, “longitude 47.58, latitude− 103.54, depth 10756 "," longitude 47.57, latitude-103.54, depth 10756 ", and the like, the latitude, longitude, and depth of the hydraulic fracturing point are calculated. As such a coordinate calculation method, an existing technique may be adopted as appropriate.

  Subsequently, the inference unit 123 sets each of the records of the well “00001” in the corrected work record DB 136 (the work report DB 132 when the correction is unnecessary) as “work pressure crushing” and “crude oil production”. The value of the work execution date 302 is extracted from the record, the period between the work execution dates is equally distributed by the value of the number of times of crushing 224 (example: 3), and the work of the hydraulic crushing work related to each of the above-mentioned hydraulic crushing points The execution date 302 is inferred (508).

  For example, it is assumed that “2012/09/15” and “2012/09/30” are extracted as the work execution date 302 from the records of “water pressure crushing” and “crude oil production” of the well ID “00001”, respectively. Further, it is assumed that “3 times” is extracted as the value of the number of times of crushing 224 from the record of the well ID “00001”. In this case, the inference unit 123 equally divides the period between “2012/09/15” and “2012/09/29” (the hydraulic fracturing work end date immediately before “crude oil production”) into three equal parts, The work execution date 302 of the hydraulic fracturing work relating to each of the hydraulic fracturing locations is inferred as “2012/09/15”, “2012/09/22”, and “2012/09/29”.

  In addition, the inference unit 123 applies the corrected record that has been added to the corrected work record DB 136 in Step 507 described above, that is, the record that defines the latitude and longitude of each hydraulic crushing location in Step 508 described above. The work execution date 302 of the inferred corresponding hydraulic fracturing point is added and updated (509).

  Next, the inference unit 123 extracts the amount of the chemical substance injected into the well “00001” described above, that is, the value of the injected substance amount 218 from the corresponding record in the fracturing DB 131 or the corrected work record DB 136, and this injected substance The quantity value is evenly distributed with the value of the number of crushing times 224 described above, and the amount of injected substance is inferred for each hydraulic crushing run (510).

  For example, it is assumed that the value of the injected substance amount 218 related to the well “00001” is “466638” and the value of the number of times of crushing 224 is “3 times”. In this case, the inference unit 123 divides the injection substance amount value “466638” into three, and infers the injection substance amount for each hydraulic crushing as “155546”.

  In addition, the inference unit 123 defines the corrected record that has been added to the corrected work record DB 136 in step 507 and updated in step 509, that is, the latitude, longitude, and work execution date of each hydraulic crushing location. The record is updated by adding the value of the injected substance amount 308 at the relevant hydraulic fracturing site inferred in step 510 described above (511). However, since it is not necessary to distribute the substance name 307 and the substance concentration 309 equally, the substance name 307 has the substance classification 216 to the chemical substance ID 217, and the substance concentration has the same value as the injection substance concentration 219. It shall be copied and used.

  Next, the inference unit 123 instructs the display processing unit 124 to perform correction up to the above-described processing, the corrected record stored in the corrected work record DB 136, the fracturing DB 131, and the work report DB 132 are held without correction. Each record is read, and each data related to the drilling direction, total drilling distance, vertical drilling depth, latitude, longitude, hydraulic fracturing location, injected chemicals, etc. of each well is extracted from each read record For example, on the oil field based on the map of the shale oil development target area, screen data is created in which each information about the distribution of each well and its drilling trajectory, hydraulic fracturing location, injected chemicals, etc. is arranged. This is output to the client terminal 150 or the I / O 105 (512), and the process is terminated.

  An example of a screen generated by the display processing unit 124 by the output processing is shown in FIG. The screen 1000 includes a screen 610 for displaying wells and well trajectories for the oil field map, a slide bar and a drop for designating the time when the chemical is used, the amount of water injected, and the name of the injected chemical. A screen 620 having an interface such as a down menu and a check box, and a bird's eye view 1030 expressing information such as a well, a well trajectory, and an injection material in an area selected by the user together with the terrain of the oil field.

  Among these, the screen 610 is a screen for displaying an outline of a well, a well trajectory, and a substance injected into the ground with respect to the oil field map. The well and the well trajectory shown as the object 611 on the screen 610 are displayed on the trajectory coordinates (latitude 235, longitude 236, depth 234 as each end point coordinate in the well by the display processing unit 124 referring to the well excavation trajectory DB 134. ) Is extracted, and based on this, drawing data is generated and displayed with a solid line. The injected water amount 306, the chemical substance name 307, and the chemical substance amount 308 are shown as an object 612.

  The user operating the client terminal 150 uses the interface 621 on the screen 620 to specify the timing conditions of the work implementation date such as the drilling age of the well in the oil field, and the range of the injected water volume using the interfaces 622 and 623 The condition selection related to the well to be displayed such as designation and designation regarding the name of the injected chemical substance using the interface 624 is performed. These interfaces 621 to 624 correspond to a filtering function based on each data of the work execution date 302, the amount of injected water 306, the substance name 307, and the substance amount 308 for each record in the corrected work record DB 136, for example.

  Of these interfaces, the interface 621 is a slider bar on the time axis. In response to the pressing of the play button 6211 in the interface 621, the display processing unit 124 identifies the record of the work execution date 302 corresponding to the time in the range specified by the slider bar, and the injection that the record has Drawing data is generated based on each value such as the amount of water 306, the substance name 307, and the amount of substance 308, and displayed on the screen 610.

  On the other hand, the interface 622 is a drop-down menu, and the lower limit value of the injected water amount is received from the user for the well to be displayed on the screen 610, while the interface 623 is the injected water amount for the well to be displayed on the screen 610. The upper limit value is accepted from the user. The display processing unit 124 identifies a record in which the value of the injected water amount 306 corresponds to the conditions received from the user through the interfaces 622 and 623, generates drawing data only for information included in the record, and displays it on the screen 610.

  An interface 624 is a check box for specifying the name of a chemical substance injected into the ground at the time of hydraulic fracturing and limiting a well. The display processing unit 124 specifies a record including the chemical substance designated by the user in the interface 624 in the chemical substance name 308, generates drawing data regarding only the information of the record, and displays it on the screen 610. Note that the screen 620 may include a drop-down menu for setting the upper and lower limits of the amount and concentration of chemical substances as well as a form in which the types of chemical substances are limited by check boxes as in the interface 624.

  In this way, the display processing unit 124 identifies, for example, a well that has values of water volume 306, substance name 307, and substance quantity 308 in the record that meet the conditions specified by the user through the above-described interfaces 621 to 624, and the water volume. Drawing data on the screen 610 is generated by selectively changing visual effects such as color shades and object sizes according to the values of 306, substance name 307, and substance amount 308.

  An object 613 on the screen 610 represents a river existing in the oil field. The display processing unit 124 generates and displays drawing data using existing terrain data and the like for objects corresponding to terrain and the like other than wells and well trajectories.

  On the other hand, the screen 630 cuts out a part of the oil field of the screen 610, and the three-dimensional position including the vertical depth 234, the latitude 235, and the longitude 236 of the underground well trajectory, the injected water amount 306 and It is the screen which displayed the information of the chemical substance name 307 and the chemical substance quantity 309 as a bird's-eye view.

  Among these, the object 631 is a drawing in which an appropriate figure 6312 such as a circle for each hydraulic fracturing point is arranged and drawn with respect to the trajectory 6311 based on the latitude and longitude 304 and the depth 305 that are the hydraulic fracturing points inferred by the inference unit 123. It is. This figure 6312 is drawn by associating the injected water amount 306, the substance name 307, and the substance amount 308 inferred by the inference unit 123 with colors, their shades, or the figure area. By visually recognizing such an object 631, the user can intuitively grasp the trajectory of each well, the location of hydraulic fracturing, information on chemicals injected at that time, and the like. The display processing unit 124 also displays the hydraulic crushing operation date 302, the substance name 307, and the substance concentration 309 in the vicinity of the above-described graphic 6312.

  In addition, the object 632 on the screen 630 is a work report on the corresponding well in the document storage DB 133 that is the basis of the work execution date 302 inferred by the inference unit 123, the amount of water 306 injected into the ground, the amount of substance 308, and the like. The link regarding etc. is displayed.

  When the user operating the client terminal 150 performs an operation on the UI tool such as mouse over the well object 631 displayed on the above-described screen 630, the display processing unit 124 displays the work report for the corresponding well. Or the like object 632 is displayed. When the user clicks on this object 632, the display processing unit 124 reads the data of the corresponding document from the document storage DB 133 and returns it to the client terminal 150. The user can view this.

  According to the present embodiment, the inconsistent data is corrected based on the process order restriction defined in the business process restriction condition DB 135, and a plurality of data stored in each database such as the fracturing DB 131, the work report DB 132, and the well excavation trajectory DB 134 are stored. Analysis combining information is possible. Furthermore, interpolation of the deficient data is realized by inferring the three-dimensional position (perforated vertical depth 234, latitude 235, longitude 236), work execution date 302, water volume 306, and substance name 307 of the injected chemical substance based on business knowledge, Information on shale oil development can be drawn with appropriate accuracy and good visibility.

  Therefore, it is possible to ensure data consistency regarding the same event between information, and to perform analysis across each information.

  At least the following will be clarified by the description of the present specification. That is, in the data correction system of the present embodiment, when the arithmetic unit collates the plurality of types of information and specifies inconsistencies in the execution timing of the same process among the information when correcting the inconsistency. In the information, the process and the time before and after the process are identified as conforming to the restrictions, and the process time in the identified information is identified as the inconsistency. It is good also as making it the implementation time of the said process in other information.

  According to this, the validity of the order in which a certain process and the processes before and after that process are performed, that is, the deviation of the execution timing of a certain process between information (that is, between information of each stakeholder) is satisfied. It can be resolved and unified. As a result, the data consistency regarding the same event between information is ensured regarding process implementation time, and the analysis over each information is attained.

  Further, in the data correction system according to the present embodiment, the arithmetic device collates a series of execution times of each process indicated by the plurality of types of information with constraints on a process order of the resource development, and a series indicated by the information. Identify the process that violates the restriction and the execution time of the specified process, and correct the execution time of the specified process to be consistent with the execution time of the process before and after the process and meet the restriction It is also possible to further execute the processing.

  According to this, with respect to the flow of each process indicated by each information, the execution time is corrected so as to satisfy the above-mentioned restrictions, and as a result, the data consistency regarding the same event is secured among the information of each stakeholder, and the information is straddled. Analysis becomes possible.

  Further, in the data correction system according to the present embodiment, the arithmetic device collates the plurality of types of information, identifies a difference in data granularity or presence / absence of setting regarding the same event, and identifies the difference. Further, based on data having a smaller granularity or data setting, inference processing for further interpolating other data that is insufficient with respect to the predetermined range of the same event with a predetermined algorithm may be executed.

  According to this, there is data granularity and presence / absence of information, for example, one side shows only the start and end positions for a given process, and the other shows the details of the work in the construction area for the process. Corresponding to different situations, interpolation processing for data with low granularity (eg, processing to divide the construction area from the start to the end of construction by the number of constructions and estimate the construction content of each divided area) It is possible to make the data granularity uniform. As a result, the data consistency regarding the same event between information is further ensured, and a highly accurate analysis across each information is attained.

  Further, in the data correction system according to the present embodiment, the arithmetic device collates the plurality of types of information during the inference process, and data granularity or setting regarding the execution area and execution content of the same process between the information. The difference between the presence and absence is specified, and based on the content of the execution content in which the difference is specified, the execution count value of the predetermined work is included, but the execution count value is not included as the execution content, but the value of the execution area is For the data to be included, the process between calculating the position of each divided area obtained by dividing the execution area by the number of execution times and the period between the execution time of the process and the next process in the execution area It is also possible to execute processing for calculating the execution time of each divided area divided by the number of times.

  According to this, only the number of executions of the predetermined work in the predetermined process is shown between the information, and the other shows the value of the construction area with respect to the process. Thus, it is possible to estimate the position of the divided area divided by the number of executions and the execution time thereof, and to make the data granularity uniform among the information. As a result, the data consistency regarding the same event between information is further ensured, and a highly accurate analysis across each information is attained.

  Further, in the data correction system according to the present embodiment, the arithmetic unit, as the execution content, is based on the execution content data including the execution frequency value of the predetermined work among the execution content data in which the difference is specified in the inference process. With respect to data that does not include the number of times of execution but includes the amount of use of the predetermined substance in the process, a value obtained by dividing the amount of use of the predetermined substance by the number of times of execution of the predetermined substance The process of calculating the usage amount may be further executed.

  According to this, with respect to the amount of substance used, the amount of use in each of the above-described divided regions and the implementation thereof are estimated, and the data granularity can be made uniform between information. As a result, the data consistency regarding the same event between information is further ensured, and a highly accurate analysis across each information is attained.

  Further, in the data correction system according to the present embodiment, the arithmetic device extracts data included in each of the plurality of types of information regarding at least an event in which inconsistency correction has been made with respect to the data, and the extracted data is Then, a predetermined process by a predetermined algorithm may be performed, and a process of outputting the result of the predetermined process to the display device may be further executed.

  According to this, it is possible to appropriately analyze and display the result based on each information that ensures data consistency regarding the same event.

  Further, in the data correction system according to the present embodiment, the arithmetic device extracts data included in each of the plurality of types of information regarding at least an event that has been inferred with respect to the data, and performs predetermined processing on the extracted data. A predetermined process by an algorithm may be performed, and a process of outputting the result of the predetermined process to the display device may be further executed.

  According to this, it is possible to appropriately analyze and display the result based on each information that further ensures data consistency regarding the same event.

  Further, in the data correction method of the present embodiment, the information processing system collates the plurality of types of information when the inconsistency is corrected, and identifies inconsistencies in the execution timing of the same process among the information. In this case, among the information, the process and the execution time of the process before and after the process are identified as conforming to the restriction, and the inconsistency is specified as the execution time of the process in the specified information. It may be set as the implementation time of the process in other information.

  Further, in the data correction method according to the present embodiment, the information processing system collates a series of execution times of each process indicated by the plurality of types of information with restrictions on the process order of the resource development, and each information indicates Identify a process that violates the constraint and its implementation time in a series of implementation times, and align the implementation time of the identified process with the implementation time of the process before and after the process and meet the constraint. The correction process may be further executed.

  Further, in the data correction method according to the present embodiment, the information processing system collates the plurality of types of information to identify a difference in data granularity or presence / absence of setting regarding the same event between the information, and the difference is identified. An inference process for interpolating other data that is insufficient with respect to the predetermined range of the same event with a predetermined algorithm may be further executed based on data having a smaller granularity or data setting.

  Further, in the data correction method according to the present embodiment, the information processing system collates the plurality of types of information during the inference process, and the data granularity or the execution content of the same process between the information A difference in the presence / absence of setting is specified, and based on the data of the execution contents in which the difference is specified, the execution frequency value of the predetermined work is included, but the execution frequency value is not included as the execution contents, but the value of the execution area For the data to include, the process between calculating the position of each divided area obtained by dividing the execution area by the number of execution times, and the period between the execution time of the process and the next process in the execution area, A process of calculating the execution time of each divided area divided by the number of execution times may be executed.

  Further, in the data correction method according to the present embodiment, the information processing system is configured to execute the inference process based on the execution content data including the execution frequency value of the predetermined work among the data of the execution contents in which the difference is specified. As for the data that does not include the execution number value but includes the use amount of the predetermined substance in the step, the value obtained by dividing the use amount of the predetermined substance by the execution number value is the predetermined substance at the execution time of each divided region. It is also possible to further execute a process for calculating the usage amount.

  Further, in the data correction method according to the present embodiment, the information processing system extracts data included in each of the plurality of types of information regarding at least an event in which inconsistency correction has been performed on the data, and the extracted data is included in the extracted data. Alternatively, a predetermined process using a predetermined algorithm may be performed, and a process of outputting the result of the predetermined process to the display device may be further executed.

  Further, in the data correction method according to the present embodiment, the information processing system extracts data included in each of the plurality of types of information regarding at least an event that has been inferred with respect to the data, and applies to the extracted data A predetermined process by a predetermined algorithm may be performed, and a process of outputting the result of the predetermined process to the display device may be further executed.

10 Network 100 Data Correction System 101 Storage Device 102 Program 103 Memory 104 CPU (Calculation Device)
105 I / O (input / output device)
106 Communication Device 121 Conversion Unit 122 Correction Unit 123 Insufficient Data Inference Mechanism 124 Display Processing Unit 131 Fracturing DB
132 Work Report DB
133 Document storage DB
134 Well Drilling Trajectory DB
135 Business process constraint DB
136 Corrected work record DB
150 client terminals

Claims (14)

A storage device that stores the execution history of the resource development process, which is each information held by each interested party in accordance with predetermined resource development ,
The execution history of each stakeholder stored in the storage device, and the execution history of the process held by each stakeholder for a predetermined process in the same development target is collated with respect to the execution time. Te, identifying inconsistencies implementation period, with respect to execution history in which the mismatch is identified, the process of correcting the implementation period to meet the constraints of the process sequence of the resource development, the storage device stores The execution history of each stakeholder, the stakeholder holding the execution history of the process with respect to the predetermined process in the same development target, the granularity of data or the presence / absence of setting regarding the execution area and execution content by matching relates to specific differences in the particle size or the setting whether, the differences are out particle size of data specified in the smaller ones or data sets In shall, granularity is larger than the data that is the subject of the difference, or the data of a given implementation area or exemplary contents of the predetermined step of the calculation data of the data without the data set, with respect to either An inference process for performing predetermined calculation and interpolating other data that is insufficient with respect to the predetermined range of the process ;
Data correction system with The arithmetic unit is
Upon correction of the mismatch, the stakeholders respectively by collating relates implementation period of the execution history of the step of holding for a given step in the same development target, the implementation period of the same process between the execution history not When matching is specified, the inconsistency is specified, and among the execution histories , the step and the execution timing of the steps before and after the step are matched with the constraint, and the step of the step in the specified execution history is specified . The execution time is the execution time of the process in the other execution history in which the inconsistency is specified.
The data correction system according to claim 1. The arithmetic unit is
A series of exemplary timing of the steps indicated by the execution history to retain for each step respectively the stakeholder in the same development target, against the constraint of the process sequence of the resource development, said one of said series of exemplary timing The process that violates the constraint and the timing of its implementation are identified, and the process of performing the identified process is further executed to adjust to the timing of matching with the implementation timing of the process before and after the process and conforming to the constraint. Is,
The data correction system according to claim 1. The arithmetic unit is
Upon the inference process, the differences on the basis of what is included execution count value of a predetermined working of the data execution content specified, the data does not include the execution count value as the exemplary content including the value of the above-described area With respect to the process, the period between each process in which the execution area is divided by the number of the execution count values and the execution time of the process and the next process in the execution area is expressed as the execution count value. divided by the number, and executes processing for calculating the implementation period of the divided regions, and
The data correction system according to claim 1. The arithmetic unit is
In the inference process, based on the data of the execution contents in which the difference is specified, including the execution frequency value of the predetermined work, the usage amount of the predetermined substance in the process is not included as the execution contents. For the data to include, a process of calculating a value obtained by dividing the amount of use of the predetermined substance by the value of the number of executions as the amount of use of the predetermined substance at the execution time of each divided region is further executed.
The data correction system according to claim 4. The arithmetic unit is
At least, the terms execution history correction of misalignment is made to extract the data to which the execution history comprises, based on the extracted data, and generates screen data representing the implementation period and implementation details of the process for the development target , To further execute a process of outputting the screen data to the display device.
The data correction system according to claim 1. The arithmetic unit is
At least, with respect to execution history in which the inference processing has been performed, the extracts data execution history comprises, based on the data the extracted, process implementation period of for the development target, implementation details, and screen data indicating an exemplary region And further executing a process of outputting the screen data to the display device.
The data correction system according to claim 1. An information processing system including a storage device that stores the execution history of the resource development process, which is each piece of information held by each stakeholder in association with predetermined resource development ,
The execution history of each stakeholder stored in the storage device, and the execution history of the process held by each stakeholder for a predetermined process in the same development target is collated with respect to the execution time. Te, identifying inconsistencies implementation period, with respect to execution history in which the mismatch is identified, the process of correcting the implementation period to meet the constraints of the process sequence of the resource development,
The implementation history of each process, which is stored in the storage device, is the implementation history of each process, and each process is held for a predetermined process in the same development target. collates relates granularity or setting the presence or absence of data on to identify the differences in the particle size or the setting whether, those among granularity of data to which the difference has been identified having the smaller ones or data sets, target of the differences A predetermined calculation is performed on either the data having a larger granularity, or the data for the predetermined execution area or the content of the execution in the predetermined process, which is data for calculation of the data without the data setting, and the process An inference process for interpolating other deficient data with respect to a predetermined range of
The data correction method characterized by performing. The information processing system is
Upon correction of the mismatch, the stakeholders respectively by collating relates implementation period of the execution history of the step of holding for a given step in the same development target, the implementation period of the same process between the execution history not When matching is specified, the inconsistency is specified, and among the execution histories , the step and the execution timing of the steps before and after the step are matched with the constraint, and the step of the step in the specified execution history is specified . The execution time is the execution time of the process in the other execution history in which the inconsistency is specified,
The data correction method according to claim 8, wherein: The information processing system is
A series of exemplary timing of the steps indicated by the execution history to retain for each step respectively the stakeholder in the same development target, against the constraint of the process sequence of the resource development, said one of said series of exemplary timing The process that violates the constraint and the timing of its implementation are identified, and the process of performing the identified process is further executed to adjust to the timing of matching with the implementation timing of the process before and after the process and conforming to the constraint. ,
The data correction method according to claim 8, wherein: The information processing system is
Upon the inference process, the differences on the basis of what is included execution count value of a predetermined working of the data execution content specified, the data does not include the execution count value as the exemplary content including the value of the above-described area With respect to the process, the period between each process in which the execution area is divided by the number of the execution count values and the execution time of the process and the next process in the execution area is expressed as the execution count value. The data correction method according to claim 8, wherein the data is divided by the number of and the processing for calculating the execution time of each divided area is executed. The information processing system is
In the inference process, based on the data of the execution contents in which the difference is specified, including the execution frequency value of the predetermined work, the usage amount of the predetermined substance in the process is not included as the execution contents. For the data to include, further execute a process of calculating a value obtained by dividing the amount of use of the predetermined substance by the value of the number of executions as the amount of use of the predetermined substance at the execution time of each divided region.
The data correction method according to claim 11. The information processing system is
At least, the terms execution history correction of misalignment is made to extract the data to which the execution history comprises, based on the extracted data, and generates screen data representing the implementation period and implementation details of the process for the development target , Further executing a process of outputting the screen data to the display device;
The data correction method according to claim 8, wherein: The information processing system is
At least, with respect to execution history in which the inference processing has been performed, the extracts data execution history comprises, based on the data the extracted, process implementation period of for the development target, implementation details, and screen data indicating an exemplary region And further executing a process of outputting the screen data to the display device.
The data correction method according to claim 8, wherein:

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