Well cementation data management and mining analysis method and integrated decision-making platform

Abstract

The invention belongs to the technical field of oil and gas well drilling and completion engineering well cementation, and provides a well cementation data management and mining analysis method and an integrated decision platform. The method comprises the steps that a multi-source data transmission interface is designed, and historical data of the whole well cementation process are collected; historical data of the whole well cementation process are processed, and a unified data bin is constructed; and carrying out data mining on the unified data warehouse by utilizing a multi-dimensional analysis tool, and carrying out fitting to generate a data association relationship under a multi-factor condition. The method has the effect of mining and analyzing the data relevance of the well cementation big data.

Description

Technical Field

[0001] The invention belongs to the technical field of cementing in oil and gas well drilling and completion engineering, and relates to a cementing data management and mining analysis method and an integrated decision-making platform. Background Art

[0002] In the complex oil and gas exploration and development process, cementing operations are the key link between the wellbore and the formation, and their quality directly affects the long-term stability and production efficiency of the oil and gas wells. With the development of data technology, big data technology is increasingly widely used in the field of petroleum engineering. As an indispensable part of oil exploration and development, cementing involves the collection and management of a large amount of data.

[0003] Although the existing technology can initially realize the digital management of data related to cementing design, construction process, and cementing quality, the implementation of digital management has not fully considered data correlation mining and analysis, and cannot effectively support the implementation of cementing big data optimization and prediction technology.

[0004] Based on the above problems, it is urgent to carry out data correlation mining and analysis of cementing big data, which can effectively support the implementation of cementing big data optimization prediction technology. Summary of the invention

[0005] In order to solve the above problems, the present invention provides a cementing data management and mining analysis method and an integrated decision-making platform.

[0006] In a first aspect, the present invention provides a cementing data management and mining analysis method, which adopts the following technical solutions:

[0007] Design a multi-source data transmission interface to collect historical data of the entire cementing process;

[0008] Process the historical data of the entire cementing process and build a unified data warehouse;

[0009] The unified data warehouse is mined using multidimensional analysis tools to fit and generate data association relationships under multi-factor conditions.

[0010] Preferably, the historical data collected during the whole cementing process includes: cementing design simulation input data, cementing operation data, logging interpretation sound amplitude diagram, cementing experiment measured data, and cementing consumables data;

[0011] The cementing design simulation input data includes basic data of the measured well diameter, drilling fluid performance parameters, well profile and geological data; simulation input data of casing running parameters, injection pressure and displacement efficiency; design input data of casing string strength, string centering analysis, slurry column structure design and rheological displacement calculation;

[0012] The measured data of cementing experiments include experimental data of cement slurry performance and experimental data of triaxial compressive strength of cement paste;

[0013] The cementing consumables data includes tool accessories, casing data, and slurry material data in cementing operations.

[0014] Preferably, the experimental data of the cement slurry performance include: thickening time, water loss, compressive strength, rheology and stability of the cement slurry.

[0015] Preferably, multidimensional analysis tools are used to perform data mining on the unified data warehouse, including: digital management of data in the unified data warehouse, cementing engineering design, cementing simulation, cementing operation parameter calculation, and logging interpretation analysis.

[0016] Preferably, the fitting generates data association relationships under multi-factor conditions, including: real-time comparative analysis of implicit relationships among cementing design parameters, cementing construction parameters and cementing quality, to provide decision-making guidance for the design and construction plan formulation of wells of the same type.

[0017] Preferably, the implicit relationship between cementing design parameters, cementing construction parameters and cementing quality is compared and analyzed in real time, including: using association rules and regression analysis methods to analyze the association relationship between a single well single factor, a single well multiple factors, multiple wells single factors, and multiple wells multiple factors.

[0018] Preferably, cementing simulation includes: casing lowering feasibility, hook load during casing lifting / lowering, annular pressure during casing lowering, wellbore pressure during the whole cementing process, and simulation analysis of cement slurry displacement efficiency process.

[0019] In a second aspect, the present invention provides an integrated decision-making platform, which adopts the following technical solutions:

[0020] The integrated decision-making platform is characterized by including a cementing multi-source data acquisition module, a cementing engineering calculation and data management module, and a cementing data analysis and optimization decision module;

[0021] The cementing multi-source data acquisition module is used to design a multi-source data transmission interface to collect historical data of the entire cementing process;

[0022] The cementing engineering calculation and data management module processes the historical data of the entire cementing process and builds a unified data warehouse;

[0023] The cementing data analysis and optimization decision module uses a multidimensional analysis tool to perform data mining on a unified data warehouse, and fits and generates data association relationships under multi-factor conditions.

[0024] Preferably, the cementing multi-source data acquisition module is a functional module, and the functions of the cementing multi-source data acquisition module include basic data, pipe string verification, centering analysis, slurry column structure design, rheological displacement design, casing running simulation, injection dynamic simulation and displacement efficiency simulation.

[0025] Preferably, the cementing engineering calculation and data management module is a functional module, and the functions of the cementing engineering calculation and data management module include cementing design simulation calculation and management, cementing construction operation parameter calculation and information management, logging interpretation analysis and result management, cementing experiment information management, and cementing consumables information management.

[0026] In summary, the present invention includes the following beneficial technical effects:

[0027] 1. Based on the research results of the present invention, cementing engineers can optimize the design of the operation plan according to historical data and expert experience before cementing operations; during the operation, they can monitor the equipment status and process parameters in real time, discover potential problems in time and issue early warnings; after the operation, they can collect and analyze the operation data;

[0028] 2. The present invention is of great significance for improving data analysis utilization, ensuring data accuracy, and realizing data resource sharing. It is an effective technology for optimizing engineering design, improving work efficiency, and promoting safe production. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a flowchart of a public cementing data management and mining analysis method.

[0030] Figure 2 It is a framework diagram of a public integrated decision-making platform.

[0031] Figure 3 The invention discloses a schematic diagram of the structure of an electronic device. DETAILED DESCRIPTION

[0032] 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. All other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0033] The following is combined with Figure 1-3 The present invention is further described in detail.

[0034] See attached Figure 1The present invention proposes a cementing data management and mining analysis method that integrates advanced data management technology and data mining algorithms. It uses deep mining, standardized collection, standardized processing, and correlation analysis to achieve comprehensive management and efficient utilization of cementing process data, providing data support and decision-making basis for the design, construction, and post-management of cementing projects.

[0035] The cementing data management and mining analysis method comprises the following steps:

[0036] S1. Multi-source data collection for cementing

[0037] Design a multi-source data transmission interface to collect cementing design simulation input data, cementing operation measured parameters, logging interpretation acoustic amplitude diagrams, cementing experiment measured data, and cementing consumables data. The collection of multi-dimensional process data involved in cementing operations includes the following steps:

[0038] S11, transmission interface and protocol, including:

[0039] Design a multi-source data transmission interface, predefine the interface protocol (data exchange format, communication rules) of the multi-source data transmission interface, and transmit process data of multiple dimensions to a unified data warehouse through the designed interface.

[0040] S12. The scope of data collection includes:

[0041] 1. Cementing design simulation input data, including basic data related to the measured wellbore diameter, drilling fluid performance parameters, well profile and geological data; simulation input data related to casing running parameters, injection pressure and displacement efficiency; design input data related to casing string strength, string centering analysis, slurry column structure design and rheological displacement calculation.

[0042] For example:

[0043] A1. Wellbore data

[0044] Well number: GC-001; Depth of inclination measurement points (m): 500, 1000, 1500, 2000;

[0045] Well diameter changes (mm): 215.9, 215.8, 215.7, 215.6 (simulating a slight reduction in diameter).

[0046] A2. Drilling fluid performance parameters

[0047] Well number: GC-001; Drilling fluid type: water-based drilling fluid; Density (g / cm 3 ):1.05;

[0048] Viscosity (s): 45; Water loss (mL / 30min): 8; Mud cake thickness (mm): less than 1.

[0049] 3. Well profile and geological data

[0050] Well number: GC-001; Target layer: sandstone layer; Formation pressure gradient (MPa / km): 22;

[0051] Formation temperature gradient (℃ / 100m): 3; expected drilling fluid loss layer: 1200-1300m.

[0052] 4.Casing running parameters

[0053] Well number: GC-001; casing specifications: Φ139.7mm×9.65mm (outer diameter×wall thickness);

[0054] Lowering depth (m): 2500; Lowering method: Rotary lowering;

[0055] Number and spacing of centralizers: 6, with a spacing of 500m.

[0056] 5. Input data for injection pressure and displacement efficiency simulation

[0057] Well number: GC-001; cement slurry density (g / cm 3 ): 1.8; Replacement efficiency: expected to be > 95%;

[0058] Cement slurry displacement (m 3 / min): 1.0;

[0059] Injection pressure (MPa): initial 10, peak 15, stable 12.

[0060] 6. Input data for casing string strength and casing string centering analysis and design

[0061] Well number: GC-001; casing material: J55; tensile strength (MPa): 450;

[0062] Yield strength (MPa): 370;

[0063] Analysis of pipe string centering: Through simulation calculation, the centering degree of each centralizer is >70%.

[0064] 7. Slurry column structure design, rheological displacement calculation design input data

[0065] Well number: GC-001; pulp column structure: collar pulp (1.90g / cm 3 , 10m 3 )+intermediate pulp (1.85g / cm 3 , 25m 3 )+ tail slurry (1.90g / cm 3 , 10m 3 );

[0066] Rheological parameters: plastic viscosity (PV, mPa·s) = 30, yield value (YP, Pa) = 10;

[0067] Displacement calculation: Based on the change in wellbore diameter and casing centering, the displacement process is simulated to ensure uniform distribution of cement slurry.

[0068] 2. Measured parameters of cementing operations, i.e. cementing operation data, including cementing design parameters and real-time acquisition parameters;

[0069] For example, see Appendix 1, cementing design parameters are obtained through pre-defined interface protocol transmission (data exchange format, communication rules); real-time collection parameters are automatically collected directly through automatic monitoring of cementing trucks, automatic monitoring of cementing gate valve systems, automated stable ash supply systems and other operating equipment.

[0070] Cementing operation data (Appendix 1)

[0071]

[0072] 3. Well logging interpretation sound amplitude diagram, including acquisition of different types of sound amplitude curves including CBL, VDL, SBT, AUI, and IBC;

[0073] 4. Cementing test measured data, including but not limited to experimental data of cement slurry properties (such as thickening time, compressive strength, rheology, stability, water loss) and experimental data of cement paste triaxial compressive strength;

[0074] 5. Cementing consumables data, including tool accessories, casing data, and slurry material data used in cementing operations.

[0075] S2. Mining and analysis of cementing multi-source data

[0076] S21, based on the data collected in step S12, carry out cementing engineering design, cementing construction operation parameter calculation, cementing simulation, and logging interpretation and analysis; digitally manage cementing engineering design results, cementing simulation experimental data, cementing construction information, logging interpretation and analysis results, and cementing consumables data;

[0077] Among them, cementing engineering design is used to calculate data such as casing triaxial safety factor, relationship between casing centering degree at and between the centralizers with well depth, cementing working fluid dosage and distribution, cementing working fluid rheological parameters, and wellhead pressure at the end of cementing construction.

[0078] Calculate cementing operation parameters, and conduct pressure simulation at the wellhead, well bottom, and focus point depth based on the parameters collected in real time in step S12;

[0079] Cementing simulation is used to simulate and analyze the feasibility of casing running, the hook load during casing lifting / lowering, the annular pressure during casing lowering, the wellbore pressure during the whole cementing process, and the cement slurry displacement efficiency.

[0080] Well logging interpretation and analysis uses image recognition and batch data analysis technology to perform one-click interpretation of well logging interpretation acoustic amplitude maps, quantitative interpretation of the entire well, and refined statistical analysis of the layers.

[0081] S22. Digitally manage cementing engineering design results, simulation experiment data, etc., and establish a complete data warehouse.

[0082] S3. Cleaning and preprocessing of cementing multi-source data

[0083] Convert the collected text and image unstructured data into structured data, and perform data cleaning, format conversion, and standardization to eliminate noise, outliers, and redundant data, including:

[0084] S31. Digitalization of unstructured data

[0085] 1. Structuring text data, cleaning the noise and irrelevant information in the text data, splitting the text into individual words or phrases, completing feature extraction, and finally converting the text into a vector set that can be calculated and analyzed in mathematical space.

[0086] 2. Image data structuring, including text information processing and image information processing;

[0087] Among them, text information processing uses OCR technology to identify and extract text in the text content of the image, converts the text in the image into an editable and searchable text format, and then uses text data preprocessing methods to complete the structuring of the text data;

[0088] Image information processing uses a template matching-based method to identify objects in the image by comparing the similarity between the image to be identified and the predefined template, and can complete the structuring of numbers and curves in the image.

[0089] S32, data cleaning, including missing value processing, outlier detection and processing, and data consistency testing;

[0090] Among them, missing value processing, according to the changing trends of different types of data, adopts methods including mean filling, approximate value filling, cubic spline interpolation, and random forest filling to complete the processing, improve the unified data warehouse and supplement the missing values ​​of the data;

[0091] Outlier detection and processing: by presetting conditions and combining cementing design and construction requirements, data points that exceed the reasonable range are identified and corrected, and redundant and erroneous data are removed;

[0092] Data consistency check, combined with the characteristics and rules of the data itself, uses methods including logic check, cross check, extreme value analysis, and distribution analysis to complete data consistency check.

[0093] S4. Deeply explore key information and optimize decision-making

[0094] Multidimensional analysis tools are used to mine the patterns of pre-processed historical data, and historical data of design simulation, experimental data, construction data, and cementing quality are comprehensively analyzed; then, an algorithm is used to fit the correlation between single-well single factor, single-well multiple factors, multiple-well single factor, and multiple-well multiple factors.

[0095] S41, mining of cementing multi-source data, performing classification extraction, precise matching query, and multi-factor statistical analysis on the cementing multi-source data cleaned and pre-processed in step S3.

[0096] Specifically, classification extraction can be used to classify and count the pre-processed cementing multi-source data according to organizational structures such as project departments and Party A units;

[0097] Precise matching query: precise matching query according to operation content, cementing method, well type, well category, oil and gas well type, etc.

[0098] Multi-factor statistical analysis: statistical analysis is performed based on multiple factors such as oil field, well number, block, geographical location, drill bit size, casing size, etc.

[0099] S42, analysis of cementing multi-source data, mining and analysis of relevant text information such as drilling depth, wellbore size, casing size, etc., using association rules and regression analysis methods to fit and generate the association relationship between single well single factor, single well multiple factors, multiple wells single factor, and multiple wells multiple factors;

[0100] The mining and analysis of text information related to oil fields, well numbers, blocks, geographical locations, etc. is completed using methods such as the proportion of continuous common substrings, common character ratio, and text vectorization. With the help of the analysis results of text relevance, it can lay the foundation for in-depth analysis of the correlation between the same type of wells in the same oil field and the same block.

[0101] S43. Optimize decision making, such as the implicit relationship between cementing design parameters, cementing construction parameters, and cementing quality, to provide decision-making guidance for the design and construction plan of similar wells, including:

[0102] 1. Cementing design parameters, including formation pore pressure, wellbore diameter, wellbore trajectory, casing size, formation fracture pressure, cement slurry type and properties (such as design density, thickening time, rheology, etc.), additive type and design dosage, other cementing fluid properties (such as design density and rheology, etc.) and design dosage;

[0103] Among them, geological parameters such as formation pore pressure and formation fracture pressure determine the safe pressure window range of cementing construction. By rationally designing parameters such as cementing working fluid dosage, density, and displacement, it is ensured that cement slurry is smoothly pumped into the well and solidified.

[0104] The density and thickening time of cement slurry directly affect the sealing ability of cement slurry and have a key impact on the quality of cementing. Too high density of cement slurry may cause formation fracturing, while too low density of cement slurry may not be able to seal the formation;

[0105] The displacement and displacement speed of cement slurry directly affect the quality of cementing, and affect the distribution of cement slurry in the annulus and the displacement effect.

[0106] 2. Cementing construction parameters, including measured density of cementing working fluid, measured injection volume, measured construction displacement and measured wellhead pump pressure; according to cementing design parameters, simulation analysis of wellhead pump pressure, bottom hole pressure, focus point pressure and displacement efficiency can be carried out to optimize the design of the best construction displacement at each stage of cementing operation;

[0107] Based on the cementing designs and cementing construction plans of a large number of wells of the same type as the original data, by comparing the design values ​​and measured values ​​of parameters such as cementing working fluid density, construction displacement, and usage, the difference between the simulated value and the measured value of the wellhead pump pressure is analyzed in real time, and the simulation calculation algorithms such as the wellhead pump pressure, bottom hole pressure, and focus point pressure are automatically corrected.

[0108] 3. Optimize decision-making, deeply explore the implicit relationship between cementing design parameters, construction parameters, and cementing quality, and provide decision-making guidance for the design and construction plan of similar wells.

[0109] See attached Figure 2 The present invention proposes a cementing integrated collaborative work platform. A cementing data management and mining analysis method can be executed by the cementing integrated collaborative work platform, which can be applied to the collection, digital management and in-depth analysis of cementing data. The work platform includes a cementing multi-source data acquisition module, a cementing engineering calculation and data management module, and a cementing data analysis and optimization decision module.

[0110] Module 1: Cementing multi-source data acquisition module

[0111] The cementing multi-source data acquisition module is used to collect cementing design simulation input data, cementing operation measured parameters, logging interpretation sound amplitude diagrams, cementing experiment measured data, and cementing consumables information data; the collected data is automatically transmitted to the unified data warehouse through the preset interface protocol, and then the preliminary data is cleaned and preprocessed;

[0112] Specific instructions:

[0113] B1. Input data for cementing design simulation, including the acquisition of relevant input data involved in seven functional modules including basic data, string verification, centering analysis, slurry column structure design, rheological displacement design, casing running simulation, injection and displacement dynamic simulation, and displacement efficiency simulation;

[0114] Among them, basic data, including geological stratification and formation pressure, wellbore structure, well inclination, well diameter and cementing working fluid parameter data collection; data is automatically transmitted to seven functional modules of pipe string verification, centering analysis, slurry column structure design, rheological displacement design, casing running simulation, injection displacement dynamic simulation, and displacement efficiency simulation, including:

[0115] 1. Data on geological stratification and formation pressure, including formation, collapse pressure coefficient, pore pressure coefficient, vertical depth, leakage pressure coefficient, and fracture pressure coefficient;

[0116] 2. Wellbore structure data, including drilling depth, drill bit size, casing layer, casing outer diameter, casing wall thickness, casing top depth, casing bottom depth, and cement return depth;

[0117] 3. Well inclination data, including depth, well inclination angle, and azimuth;

[0118] 4. Well diameter data, including top depth, bottom depth and well diameter;

[0119] 5. Cementing fluid parameters, including density and fluid rheological parameters.

[0120] B2. Measured parameters of cementing operation. Collect the measured density, displacement, density, wellhead pump pressure and other data of cementing working fluid that changes with operation time. The design parameters such as density, displacement, usage and so on of injection dynamic simulation module can be automatically transmitted to cementing multi-source data acquisition module for real-time benchmarking analysis and automatic optimization and adjustment.

[0121] B3. Well logging interpretation sound amplitude diagram, including different types of sound amplitude curves such as CBL, VDL, SBT, AUI and IBC.

[0122] B4. Cementing test measured data, including experimental data of cement slurry performance and experimental input parameters of cement paste triaxial compressive strength;

[0123] B5. Cementing consumables information data, including cementing tool accessories, casing information, and slurry material related information.

[0124] Module 2: Cementing Engineering Calculation and Data Management Module

[0125] The cementing engineering calculation and data management module is used to carry out cementing design simulation, cementing construction operations, logging interpretation sound amplitude diagrams, cementing experimental measured data, cementing consumables information and other input data preprocessing, simulation analysis, and result management; it realizes the coordinated linkage of automated cementing equipment and monitors key data in the cementing construction process in real time;

[0126] Cementing engineering calculation and data management module, including five functional modules: cementing design simulation calculation and management, cementing operation parameter calculation and information management, logging interpretation analysis and result management, cementing experiment information management, and cementing consumables information management;

[0127] The cementing design simulation calculation and management module simulates the wellhead pressure and flow rate, vacuum section length, annular focus point and bottom hole pressure, annular fluid return rate and cementing dynamic process during the slurry injection process based on the formation pressure, wellbore structure and cementing design. It intuitively observes the fluid flow conditions and downhole pressure change rules during the cementing process, judges the rationality of the cementing construction design and automatically monitors the cementing construction to provide a data basis.

[0128] The cementing construction operation parameter calculation and information management module coordinates and links with the automated cementing equipment. During the cementing construction process, key construction data such as cementing working fluid density, dosage, displacement, and pump pressure are monitored in real time, and control instructions are issued in real time according to the designed density, dosage, displacement and other parameters to realize the automated operation of automated cementing trucks, automated stable ash supply systems, automated cementing heads and other equipment. At the same time, the cementing engineering calculation and data management module can monitor key locations of cementing construction, such as construction sites, circulation outlets, metering tanks, and slurry mixing tanks through video.

[0129] The logging interpretation analysis and result management module includes two functional modules: logging curve management in the logging interpretation amplitude diagram and amplitude quality analysis. It realizes the digital management of various types of logging curves such as CBL, VDL, SBT, etc. It completes the precise analysis of each image segment by segment through feature extraction and image analysis, and assists in the analysis of cementing quality efficiently and quickly.

[0130] The cementing experiment information management module is composed of measured data of cementing experiments, such as cement slurry thickening time. It uses the Internet of Things technology to automatically read the experimental input and output data directly from the experimental instruments, realizes the digital management of cementing experiments and instrument equipment use information, and lays the foundation for the rapid optimization of experimental formulas.

[0131] The cementing consumables information management module includes cementing tool accessories, downhole pipe information, and slurry material information modules. It realizes digital management of cementing site construction information in various forms such as pictures, documents, texts, and compressed files.

[0132] Module 3: Cementing data analysis and optimization decision module

[0133] Cementing data analysis and optimization decision module, used to conduct comprehensive analysis of historical data, associated data mining analysis and optimization decision-making;

[0134] Among them, the comprehensive analysis module of historical data includes various data of cementing engineering design, cementing experiment, cementing construction, and cementing quality evaluation;

[0135] 1. Cementing engineering design module: Through the existing cementing design on the integrated platform, the rationality and effectiveness of design parameters (including casing selection, centralizer placement method, cementing working fluid dosage design, cement slurry formula, and pumping procedure) are analyzed; based on historical data, the possible risk points of the design are evaluated, and optimization directions are provided for the new well design;

[0136] 2. Cementing experiment module: Verify whether the performance of key materials such as cement slurry meets the design requirements through experimental data, including thickening time, compressive strength, water loss, stability, etc., conduct in-depth analysis of problems encountered in the experiment, find out the causes (such as improper additive ratio, ambient temperature influence) and feedback to the subsequent experimental plan design;

[0137] 3. Cementing construction module is used to conduct real-time benchmarking analysis of simulated pump pressure and measured pump pressure, and continuously adjust operation parameters such as construction displacement to ensure that there is no leakage or leakage during the cementing construction process; by timely summarizing emergencies and response measures during the construction process, improving emergency plans, and improving the response capabilities for the next cementing construction;

[0138] 4. Cementing quality evaluation module: Use logging data to evaluate cementing quality, including the integrity of cement sheath, the bonding of the first and second interfaces, diagnose problems found in logging, such as cement sheath loss, gas channeling, etc., analyze the causes and propose remedial measures.

[0139] Among them, the associated information mining and analysis function module in the associated data mining and analysis and optimization decision-making module conducts feature analysis, preprocessing and deep mining analysis on multiple data such as oil fields, wells, cementing methods, casing types, well types, well types, oil and gas well types, casing sizes, drill bit sizes, drilling depths, blocks, construction units, geographical locations, geological stratifications, cementing design parameters, construction operation parameters, construction complexity, cementing quality, etc. on the integrated platform to determine the correlation relationships under multiple factors, multiple wells with single factors, single well with single factors, and multiple factors.

[0140] The optimization decision function module in the associated data mining analysis and optimization decision module carries out cementing scheme optimization design and automatic optimization adjustment of cementing construction parameters;

[0141] 1. The cementing scheme optimization design module determines the basic design parameters of a single well, including casing size, drill bit size, drilling depth, cementing design parameters, the correlation between construction parameters, and the correlation between parameters between wells, based on the analysis results of the correlation information mining and analysis function module. By deeply mining key information such as the implicit relationship between cementing design parameters, cementing construction parameters and cementing quality, it provides decision-making guidance for the optimal formulation of cementing design and construction plans for wells of the same block and type;

[0142] 2. The automatic optimization and adjustment module for cementing construction parameters is based on the original data of cementing design, cementing construction plan, etc. of a large number of similar wells on the integrated platform. By comparing the design value and measured value of cementing working fluid density, construction displacement, dosage and other parameters, the module conducts real-time benchmarking and analysis of the difference between the simulated value and the measured value of the wellhead pump pressure, and automatically corrects the construction density, displacement and other parameters to ensure that the simulated values ​​of the bottom hole pressure and the pressure of the leakage-prone point are less than the formation leakage pressure, thus ensuring the safety of cementing construction.

[0143] The modules described above may be implemented in whole or in part through software, hardware, or a combination thereof, supporting processors embedded in or independent of a computer device in hardware form, and also supporting memories stored in a computer device in software form, so that the processor can call and execute operations corresponding to the modules described above.

[0144] An embodiment of the present invention provides a computer storage medium, which stores instructions that can be executed by at least one processor. The instructions are executed by at least one processor to enable the at least one processor to execute a computer program of a cementing data management and mining analysis method as described above.

[0145] The storage medium includes, for example, various media that can store program codes, such as a USB flash drive, a mobile hard disk, a magnetic disk, a read-only memory (ROM), a random access memory (RAM), or an optical disk.

[0146] The embodiment of the present invention provides a device, see the attached Figure 3 , used to execute the above-mentioned coding management platform, the computer device includes a processor, a memory, a network interface and a database connected through a system bus. The processor of the computer device is used to provide computing and control capabilities; the memory of the computer device includes a non-volatile storage medium and an internal memory; the processor of the computer device implements the steps of the above-mentioned coding management method when executing the computer program; the non-volatile storage medium stores an operating system, a computer program and a database; the internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium.

[0147] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention is 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 replacements for some of the technical features therein. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A cementing data management and mining analysis method, characterized in that: The method comprises: Design a multi-source data transmission interface to collect historical data of the entire cementing process; Process the historical data of the entire cementing process and build a unified data warehouse; The unified data warehouse is mined using multidimensional analysis tools to fit and generate data association relationships under multi-factor conditions.

2. A cementing data management and mining analysis method according to claim 1, characterized in that: The historical data of the whole cementing process is collected, including: Cementing design simulation input data, cementing operation data, logging interpretation sound amplitude diagram, cementing experiment measured data, cementing consumables data; The cementing design simulation input data includes basic data of the measured well diameter, drilling fluid performance parameters, well profile and geological data; simulation input data of casing running parameters, injection pressure and displacement efficiency; design input data of casing string strength, string centering analysis, slurry column structure design and rheological displacement calculation; The measured data of cementing experiments include experimental data of cement slurry performance and experimental data of triaxial compressive strength of cement paste; The cementing consumables data includes tool accessories, casing data, and slurry material data in cementing operations.

3. A cementing data management and mining analysis method according to claim 2, characterized in that: The experimental data of the cement slurry performance include: thickening time, water loss, compressive strength, rheology and stability of the cement slurry.

4. The cementing data management and mining analysis method according to claim 1, characterized in that: The method of using a multidimensional analysis tool to perform data mining on a unified data warehouse includes: In view of the digital management of data in the unified data warehouse, cementing engineering design, cementing simulation, cementing operation parameter calculation, and logging interpretation and analysis are carried out.

5. A cementing data management and mining analysis method according to claim 4, characterized in that: The fitting generates data association relationships under multi-factor conditions, including: Real-time comparative analysis of the implicit relationship between cementing design parameters, cementing construction parameters and cementing quality provides decision-making guidance for the design and construction plan of the same type of wells.

6. A cementing data management and mining analysis method according to claim 5, characterized in that: The real-time comparative analysis of the implicit relationship between cementing design parameters, cementing construction parameters and cementing quality includes: The association rules and regression analysis methods are used to analyze the association relationships between single-well single factor, single-well multiple factors, multiple-well single factor, and multiple-well multiple factors.

7. A cementing data management and mining analysis method according to claim 4, characterized in that: The cementing simulation includes: casing lowering feasibility, hook load during casing lifting / lowering, annular pressure during casing lowering, wellbore pressure during the whole cementing process, and simulation analysis of cement slurry displacement efficiency process.

8. Integrated decision-making platform, characterized by: It includes cementing multi-source data acquisition module, cementing engineering calculation and data management module, cementing data analysis and optimization decision module; The cementing multi-source data acquisition module is used to design a multi-source data transmission interface to collect historical data of the entire cementing process; The cementing engineering calculation and data management module processes the historical data of the entire cementing process and builds a unified data warehouse; The cementing data analysis and optimization decision module uses a multi-dimensional analysis tool to perform data mining on a unified data warehouse, and fits and generates data association relationships under multi-factor conditions.

9. The integrated decision-making platform according to claim 8, characterized in that: The cementing multi-source data acquisition module is a functional module, and the functions of the cementing multi-source data acquisition module include basic data, pipe string verification, centering analysis, slurry column structure design, rheological displacement design, casing running simulation, injection dynamic simulation and displacement efficiency simulation.

10. The integrated decision-making platform according to claim 8, characterized in that: The cementing engineering calculation and data management module is a functional module, and its functions include cementing design simulation calculation and management, cementing construction operation parameter calculation and information management, logging interpretation analysis and result management, cementing experiment information management, and cementing consumables information management.

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