Drilling data analysis method and system and computer storage medium

Abstract

The invention belongs to the technical field of drilling engineering, and discloses a drilling data analysis method and system and a computer storage medium, and the analysis method comprises the steps: building a universal target data set; determining a calculation formula of each data item in the general target data set, and establishing a drilling data calculation model according to the calculation formula of each data item; determining an operator of an atomic attribute in a calculation formula of each data item; drilling data dimension attributes of all operators are determined, an operator data set with the dimension attributes is obtained, and a parameter factor dimension data set is determined according to the operator data set with the dimension attributes and the drilling data calculation model; and according to the parameter factor dimension data set and the drilling data calculation model, performing self-defined drilling data statistics. According to the method, the self-defined combined statistics of the drilling data is realized, the method has relatively high statistical efficiency and self-defining capability, the workload of the drilling data statistics can be effectively reduced, and the statistical analysis work is more flexible.

Description

Technical Field

[0001] The present invention belongs to the technical field of drilling engineering, and in particular relates to a drilling data analysis method, system and computer storage medium. Background Art

[0002] In the work of drilling data statistics, "Daily Drilling Report", "Weekly Drilling Report" and "Monthly Drilling Report" are important sources of information for technicians to understand the drilling situation and conduct data analysis. The traditional method classifies and analyzes production data by group, bureau level, department level, branch company, project department, well team, block, well type, well type and market. The report data is displayed through the report software, and the report header can display multiple columns of data. By checking the data items to be displayed, the target report is obtained, so as to understand the complex working conditions underground and provide strong support for safe and efficient drilling.

[0003] With the development of big data technology, intelligent drilling decisions have received widespread attention. In terms of data processing, there are new requirements for report data statistics. In view of the different characteristics of each oil field block, more customized data is needed in the report as support. If new customized items are encountered, the traditional method is to add database tables or fields in the table to add the required data items to the database code. However, due to the change of database fields, the data storage in the original database may be affected, resulting in the loss or change of the original data. In addition, this modification process will consume a lot of manpower and material resources, which is not conducive to software maintenance and the improvement of drilling efficiency. Summary of the invention

[0004] In view of the above problems, the present invention provides a drilling data analysis method, system and computer storage medium, which adopt the following technical solutions:

[0005] A drilling data analysis method comprises the following steps: establishing a general target data set; determining a calculation formula for each data item in the general target data set, and establishing a drilling data calculation model according to the calculation formula for each data item; determining an operator with atomic properties in the calculation formula for each data item; determining the drilling data dimension attributes of all operators, and obtaining an operator data set with dimension attributes, and determining a parameter factor dimension data set according to the operator data set with dimension attributes and the drilling data calculation model; and performing customized drilling data statistics according to the parameter factor dimension data set and the drilling data calculation model.

[0006] Further, establishing the common target data set includes the following steps: establishing the common target data set according to the first drilling data item and the second drilling data item.

[0007] Furthermore, the first drilling data item includes drilling footage, drilling time, mechanical rotation speed, wellbore quality qualification rate and viscosity coefficient, and the second drilling data item is determined according to the requirements of each oil field and block.

[0008] Furthermore, establishing a drilling data calculation model according to the calculation formula of each data item includes the following steps:

[0009] Get the parameter factors and calculation symbols in the calculation formula of each data item;

[0010] The parameter factors and calculation symbols are used as the basic quantities for computational modeling, and the standardized encoding of the parameter factors and calculation symbols is used as the relationship representation of the data computational model to establish the data computational model.

[0011] Furthermore, determining the operator of the atomic attribute in the calculation formula of each data item includes the following steps:

[0012] Determining an operator of an atomic attribute according to a parameter factor in a calculation formula of a data item includes: determining the parameter factor attribute, and if the parameter factor is an atomic attribute, taking it as an operator.

[0013] Furthermore, the operator for determining the atomic property according to the parameter factor in the calculation formula of the data item also includes:

[0014] If the parameter factor is a derived attribute, repeat the following steps: determine the calculation formula of the data item, establish a drilling data calculation model based on the calculation formula of the data item, and determine the operator of the atomic attribute in the calculation formula of the data item until all parameter factors are determined to be operators.

[0015] Further, according to the operator data set with dimensional attributes and the drilling data calculation model, determining the parameter factor dimensional data set includes the following steps:

[0016] The operator data set with dimension attributes is input into the drilling data calculation model, and the parameter factor dimension data set is output.

[0017] Furthermore, according to the parameter factor dimension data set and the drilling data calculation model, performing customized drilling data statistics includes the following steps:

[0018] Through the parameter factors in the calculation formula of the target data item, the value of the corresponding operator under the specified dimension attribute is searched in the parameter factor dimension data set, the value under the specified dimension attribute is input into the drilling data calculation model, and the value under the current dimension attribute is output after calculation;

[0019] If there are multiple derived attributes of the operator, the dimension attribute calculation steps are repeated until the values ​​of all dimension attributes of the operator are output, and a statistical report of the customized drilling data is obtained.

[0020] Furthermore, the operator dimension attributes are the same as the parameter factor dimension attributes.

[0021] The present invention also provides a drilling data analysis system, comprising:

[0022] A data acquisition module, used to establish a common target data set;

[0023] A model building module, used to determine the calculation formula of each data item in the general target data set, and to build a drilling data calculation model according to the calculation formula of each data item;

[0024] A first data processing module, used to determine the operator of the atomic attribute in the calculation formula of each data item;

[0025] The second data processing module is used to determine the drilling data dimension attributes of all operators, obtain the operator data set with the dimension attributes, and determine the parameter factor dimension data set according to the operator data set with the dimension attributes and the drilling data calculation model;

[0026] The data calculation module is used to perform customized drilling data statistics based on the parameter factor dimension data set and the drilling data calculation model.

[0027] Furthermore, the model building module is specifically used for:

[0028] Get the parameter factors and calculation symbols in the calculation formula of each data item;

[0029] The parameter factors and calculation symbols are used as the basic quantities for computational modeling, and the standardized encoding of the parameter factors and calculation symbols is used as the relationship representation of the data computational model to establish the data computational model.

[0030] Furthermore, the first data processing module is specifically used for:

[0031] Determining an operator of an atomic attribute according to a parameter factor in a calculation formula of a data item includes: determining the parameter factor attribute, and if the parameter factor is an atomic attribute, taking it as an operator.

[0032] Furthermore, the data calculation module is specifically used for:

[0033] Through the parameter factors in the calculation formula of the target data item, the value of the corresponding operator under the specified dimension attribute is searched in the parameter factor dimension data set, the value under the specified dimension attribute is input into the drilling data calculation model, and the value under the current dimension attribute is output after calculation;

[0034] If there are multiple derived attributes of the operator, the dimension attribute calculation steps are repeated until the values ​​of all dimension attributes of the operator are output, and a statistical report of the customized drilling data is obtained.

[0035] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the drilling data analysis method is implemented.

[0036] Beneficial effects of the present invention:

[0037] 1. The present invention combs the drilling data items, uses the calculation formula of the data items, reversely combs the calculation factors, performs dimensional statistics on each calculation factor, and finally realizes the customized combination statistics of the drilling data. It has high statistical efficiency and customization ability, can effectively reduce the workload of drilling data statistics, and makes the statistical analysis work more flexible.

[0038] 2. Aiming at the problem that there are few commonly used drilling data items and many restrictions, the present invention takes common drilling data items and custom data items as common target data sets, performs computational modeling and data statistics on custom data items, and can obtain drilling data information more widely;

[0039] 3. The present invention proposes a parameter factor reverse combing method to obtain drilling data items of all original operator attributes;

[0040] 4. The present invention proposes to sort out the dimensions of the original operators related to the drilling data, and re-label the original operator features through different dimensional information to provide support for the subsequent output of data sets with dimensional attributes and customized drilling indicators.

[0041] Other features and advantages of the present invention will be described in the following description, and partly become obvious from the description, or be understood by implementing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 A schematic flow chart of a drilling data analysis method according to an embodiment of the present invention is shown;

[0044] Figure 2 A structural schematic diagram of a drilling data analysis system according to an embodiment of the present invention is shown.

[0045] In the figure: 1. Data acquisition module; 2. Model building module; 3. First data processing module; 4. Second data processing module; 5. Data calculation module. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] It should be noted that the terms "first", "second", etc. in the present application are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0048] First, let’s briefly introduce the current statistical analysis of drilling data:

[0049] Drilling production data is classified and statistically analyzed by group, bureau, department, branch, project department, well team, block, well type, well type, and market classification; starting from the most original source data, it is entered once, summarized and statistically analyzed at different levels, and various business and technical indicators are analyzed, and business indicators and technical data are compared and analyzed, as follows:

[0050] 1. Production statistics analysis: daily production statistics, weekly production statistics, monthly production statistics, production progress analysis, drill bit statistics analysis, drilling rig statistics analysis;

[0051] 2. Oil drilling time efficiency analysis: well division time efficiency analysis, drilling time efficiency analysis, organization shutdown time efficiency analysis, relocation and other time efficiency analysis;

[0052] 3. Engineering statistics analysis: well team work status, oil drilling analysis, unfinished drilling analysis, block drilling analysis, completed well work, quality inquiry;

[0053] 4. Drilling technology: statistics of technical indicators of underbalanced well drilling, statistics of technical indicators of branch well drilling, situation of window sidetracking in old wells, basic information of window sidetracking in old wells;

[0054] 5. Analogy analysis: single drilling record indicators, statistics of completed wells at different depths, analogy analysis of well team production, analogy analysis of oil drilling time efficiency, comparative analysis of special process application;

[0055] 6. Accident complexity statistics: drilling accident statistics, pipe sticking statistics, drilling complexity statistics;

[0056] 7. Statistics of drilling economic and technical indicators: statistics of drilling market conditions, engineering quality, coring conditions, drill sticking accidents, production efficiency, special cementing process wells, small hole drilling, completion of wells at different depths, well teams with a footage of more than 10,000 meters, and completion of deep wells.

[0057] In the above-mentioned various statistical analysis works, more customized data are needed in the report as support according to the different characteristics of each oil field block. The embodiment of the present invention provides a drilling data analysis method, system and computer storage medium, which have higher statistical efficiency and realize customized combination statistics of drilling data, which can effectively reduce the workload of drilling data statistics and make the statistical analysis work more flexible.

[0058] like Figure 1 As shown, a drilling data analysis method comprises the following steps:

[0059] S1. Establishing a general target data set, specifically as follows: establishing a general target data set according to the first drilling data item and the second drilling data item.

[0060] Among them, the first drilling data item includes drilling footage, drilling time, mechanical rotation speed, wellbore quality qualification rate and viscosity coefficient. The first drilling data item is a commonly used drilling data item and can be obtained by referring to drilling standard books, literature and other materials. The second drilling data item is determined according to the needs of each oil field and block.

[0061] In this step, in order to solve the problem that there are few commonly used drilling data items and many restrictions, common drilling data items and custom data items are used as common target data sets, and computational modeling and data statistics are performed on the custom data items, so that drilling data information can be obtained more widely.

[0062] S2. Determine the calculation formula for each data item in the general target data set, and establish a drilling data calculation model according to the calculation formula for each data item.

[0063] Among them, establishing a drilling data calculation model according to the calculation formula of each data item includes the following steps:

[0064] S21. Obtain parameter factors and calculation symbols in the calculation formula of each data item.

[0065] S22. Use parameter factors and calculation symbols as basic quantities for computational modeling, use the standardized encoding of parameter factors and calculation symbols as the relationship representation of the data computational model, and establish a data computational model.

[0066] The calculation formulas for data items include standard calculation formulas and user-defined calculation formulas.

[0067] In this step, the data calculation model can perform calculation modeling and combined statistics on common drilling data items and custom data items, and apply this data calculation model to the drilling data to form a drilling data calculation model, which includes both standard calculation methods and custom calculation methods.

[0068] For example, the standard calculation formula for the viscosity coefficient is as follows:

[0069]

[0070] Where PV is the viscosity coefficient, x is the shear rate, and y is the shear stress.

[0071] The parameter factors and calculation symbols in the standard calculation formula of the viscosity coefficient are used as the relationship representation of the data calculation model, as follows:

[0072] The addition, subtraction, multiplication and division operation rules in the standard calculation formula of viscosity coefficient and the encoding of viscosity coefficient, shear rate and shear stress are used as the representation of the data calculation model.

[0073] S3. Determine the operator of the atomic property in the calculation formula of each data item, specifically as follows: determine the operator of the atomic property according to the parameter factor in the calculation formula of the data item.

[0074] Among them, the operator of atomic properties is determined according to the parameter factor in the calculation formula of the data item, specifically: determine the parameter factor attribute, atomic property or derived property, if the parameter factor is an atomic property, it is used as an operator, if the parameter factor is a derived property, repeat the following steps: determine the calculation formula of the data item, establish a drilling data calculation model according to the calculation formula of the data item, determine the operator of atomic properties in the calculation formula of the data item, until it is determined that all parameter factors are reversely combed into operators.

[0075] For example, the parameter factors of the viscosity coefficient PV are x and y, x=φ*1.7023, y=n*0.5077, where the parameter factor of x is φ, and the parameter factor of y is n, φ is the rotation speed, and n is the reading, both of which are operators.

[0076] In this step, in order to realize the atomization of parameter factors and find the original operator more accurately, the present invention proposes a parameter factor reverse combing method to obtain the drilling data items of all original operator attributes, laying the foundation for subsequent dimensional labeling.

[0077] In order to meet the actual needs of data statistics, the embodiment of the present invention proposes to sort out the dimensions of the original operators related to the drilling data, re-label the original operator features through different dimensional information, and provide support for the subsequent output of data sets with dimensional attributes and customized drilling indicators.

[0078] S4. Determine the drilling data dimension attributes of all operators, obtain the operator data set with the dimension attributes, and determine the parameter factor dimension data set according to the operator data set with the dimension attributes and the drilling data calculation model.

[0079] According to the operator data set with dimensional attributes and the drilling data calculation model, the parameter factor dimensional data set is determined as follows: the operator data set with dimensional attributes is input into the drilling data calculation model, and the parameter factor dimensional data set is output.

[0080] For example, first define the operator dimension attributes, such as the mechanical speed and reading in the first drilling data item. They can have common dimensions such as time, well number, well type, well type, designed well depth, current well depth, wellbore size, drill bit size, drilling fluid density, etc., or custom dimensions such as block structure, drilling company, drilling company, drill bit steel grade, etc. According to the operator dimension and the drilling data calculation model, the parameter factor dimension can be finally obtained. Usually, the operator dimension attributes are the same as the parameter factor dimension attributes.

[0081] S5. Customize drilling data statistics based on the parameter factor dimension data set and the drilling data calculation model, as follows:

[0082] S51, dimension attribute calculation step: through the parameter factor in the calculation formula of the target data item, search the corresponding operator in the parameter factor dimension data set for the value under the specified dimension attribute, input the value under the specified dimension attribute into the drilling data calculation model, and output the value under the current dimension attribute after calculation.

[0083] S52. If there are multiple derived attributes of the operator, the dimension attribute calculation step S51 is repeated until the values ​​of all dimension attributes of the operator are output, and a statistical report of the customized drilling data is obtained.

[0084] In this step, customized drilling data statistics are completed by limiting the dimensional attributes of the drilling data.

[0085] For example, if you need to count the number of wells with a drilling fluid density of 1.27 g / cm 3 The viscosity coefficient under the dimension attribute is obtained according to the viscometer reading under the current dimension, as shown in Table 1:

[0086] Table 1 Statistics of operator dimensions of viscosity coefficient

[0087] Speed ​​φ(r / min) 3 4 100 200 300 600 Reading n 11 12 26 35 43 61

[0088] PV=0.0353

[0089] The drilling data dimension attribute statistics of the present invention can obtain the target data item value under a certain dimension as long as it is ensured that the dimension contains the target data item, and finally form a target report, thereby obtaining a drilling data report with the same dimension attribute.

[0090] Based on the above drilling data analysis method, such as Figure 2As shown, an embodiment of the present invention further provides a drilling data analysis system, including a data acquisition module 1, a model building module 2, a first data processing module 3, a second data processing module 4 and a data calculation module 5.

[0091] Among them, the data acquisition module 1 is used to establish a general target data set; the model building module 2 is used to determine the calculation formula of each data item in the general target data set, and establish a drilling data calculation model according to the calculation formula of each data item; the first data processing module 3 is used to determine the operator of the atomic property in the calculation formula of each data item; the second data processing module 4 is used to determine the drilling data dimensional attributes of all operators, obtain the operator data set with dimensional attributes, and determine the parameter factor dimensional data set according to the operator data set with dimensional attributes and the drilling data calculation model; the data calculation module 5 is used to perform customized drilling data statistics according to the parameter factor dimensional data set and the drilling data calculation model.

[0092] For example, the model building module 2 is specifically used to: obtain the parameter factors and calculation symbols in the calculation formula of each data item; use the parameter factors and calculation symbols as the basic quantities for calculation modeling, and use the standardized encoding of the parameter factors and calculation symbols as the relationship representation of the data calculation model to establish a data calculation model.

[0093] For example, the first data processing module 3 is specifically used to: determine the operator of the atomic attribute according to the parameter factor in the calculation formula of the data item, including: determining the parameter factor attribute, and if the parameter factor is an atomic attribute, it is used as an operator.

[0094] For example, the data calculation module 5 is specifically used for: searching the corresponding operator under the specified dimension attribute in the parameter factor dimension data set through the parameter factor in the calculation formula of the target data item, inputting the value under the specified dimension attribute into the drilling data calculation model, and outputting the value under the current dimension attribute after calculation; if there are multiple operator-derived attributes, repeating the dimension attribute calculation steps until the values ​​under all dimensional attributes of the operator are output, and obtaining a statistical report of the customized drilling data.

[0095] Based on the above-mentioned drilling data analysis method, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned drilling data analysis method is implemented.

[0096] The computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In an embodiment of the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0097] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A drilling data analysis method, characterized in that: The following steps are involved: Establishing common target datasets; Determine the calculation formula for each data item in the general target data set, and establish a drilling data calculation model based on the calculation formula for each data item; Determine the operators of atomic properties in the calculation formula of each data item; Determine the drilling data dimension attributes of all operators, obtain the operator data set with the dimension attributes, and determine the parameter factor dimension data set according to the operator data set with the dimension attributes and the drilling data calculation model; Customized drilling data statistics are performed based on parameter factor dimension data sets and drilling data calculation models.

2. The drilling data analysis method according to claim 1, characterized in that: Establishing a universal target data set includes the following steps: establishing a universal target data set according to the first drilling data item and the second drilling data item.

3. The drilling data analysis method according to claim 2, characterized in that: The first drilling data item includes drilling footage, drilling time, mechanical rotation speed, wellbore quality qualification rate and viscosity coefficient, and the second drilling data item is determined according to the requirements of each oil field and block.

4. The drilling data analysis method according to claim 1, characterized in that: Establishing a drilling data calculation model according to the calculation formula of each data item includes the following steps: Get the parameter factors and calculation symbols in the calculation formula of each data item; The parameter factors and calculation symbols are used as the basic quantities for computational modeling, and the standardized encoding of the parameter factors and calculation symbols is used as the relationship representation of the data computational model to establish the data computational model.

5. The drilling data analysis method according to claim 1, characterized in that: Determining the operators of the atomic properties in the calculation formula of each data item includes the following steps: Determining an operator of an atomic attribute according to a parameter factor in a calculation formula of a data item includes: determining the parameter factor attribute, and if the parameter factor is an atomic attribute, taking it as an operator.

6. The drilling data analysis method according to claim 5, characterized in that: Operators that determine atomic properties based on parameter factors in the calculation formula of data items also include: If the parameter factor is a derived attribute, repeat the following steps: determine the calculation formula of the data item, establish a drilling data calculation model based on the calculation formula of the data item, and determine the operator of the atomic attribute in the calculation formula of the data item until all parameter factors are determined to be operators.

7. The drilling data analysis method according to claim 1, characterized in that: According to the operator data set with dimension attributes and the drilling data calculation model, determining the parameter factor dimension data set includes the following steps: The operator data set with dimension attributes is input into the drilling data calculation model, and the parameter factor dimension data set is output.

8. The drilling data analysis method according to any one of claims 1 to 7, characterized in that: According to the parameter factor dimension data set and the drilling data calculation model, the customized drilling data statistics include the following steps: Through the parameter factors in the calculation formula of the target data item, the value of the corresponding operator under the specified dimension attribute is searched in the parameter factor dimension data set, the value under the specified dimension attribute is input into the drilling data calculation model, and the value under the current dimension attribute is output after calculation; If there are multiple derived attributes of the operator, the dimension attribute calculation steps are repeated until the values ​​of all dimension attributes of the operator are output, and a statistical report of the customized drilling data is obtained.

9. The drilling data analysis method according to claim 7, characterized in that: The operator dimension properties are the same as the parameter factor dimension properties.

10. A drilling data analysis system, characterized in that: include: A data acquisition module, used to establish a common target data set; A model building module, used to determine the calculation formula of each data item in the general target data set, and to build a drilling data calculation model according to the calculation formula of each data item; A first data processing module, used to determine the operator of the atomic attribute in the calculation formula of each data item; The second data processing module is used to determine the drilling data dimension attributes of all operators, obtain the operator data set with the dimension attributes, and determine the parameter factor dimension data set according to the operator data set with the dimension attributes and the drilling data calculation model; The data calculation module is used to perform customized drilling data statistics based on the parameter factor dimension data set and the drilling data calculation model.

11. The drilling data analysis system according to claim 10, characterized in that: The model building module is specifically used to: Get the parameter factors and calculation symbols in the calculation formula of each data item; The parameter factors and calculation symbols are used as the basic quantities for computational modeling, and the standardized encoding of the parameter factors and calculation symbols is used as the relationship representation of the data computational model to establish the data computational model.

12. The drilling data analysis system according to claim 10, characterized in that: The first data processing module is specifically used for: Determining an operator of an atomic attribute according to a parameter factor in a calculation formula of a data item includes: determining the parameter factor attribute, and if the parameter factor is an atomic attribute, taking it as an operator.

13. The drilling data analysis system according to any one of claims 10 to 12, characterized in that: The data calculation module is specifically used for: Through the parameter factors in the calculation formula of the target data item, the value of the corresponding operator under the specified dimension attribute is searched in the parameter factor dimension data set, the value under the specified dimension attribute is input into the drilling data calculation model, and the value under the current dimension attribute is output after calculation; If there are multiple derived attributes of the operator, the dimension attribute calculation steps are repeated until the values ​​of all dimension attributes of the operator are output, and a statistical report of the customized drilling data is obtained.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the drilling data analysis method according to any one of claims 1 to 9 is implemented.

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