Monitoring method for simulation process of offshore drilling and production operation

Abstract

The invention discloses an offshore drilling and production operation simulation process monitoring method, which comprises the following steps: acquiring offshore drilling and production operation data in real time, and adding the data into different data sets according to the types of the data; preprocessing data contained in each data set, converting the data into data points with data characteristic values as coordinates, detecting abnormal value points in the data points, and taking the abnormal value points as abnormal value samples of the data set; calculating an outlier factor value of a sample point in each data set abnormal value sample, and judging whether the sample point is an outlier factor or not according to a calculation result; if the sample point is an outlier factor, rejecting the sample point from the data set to which the sample point belongs; after the outlier factors of all the data sets are removed, the data of all the data sets are imported into the corresponding offshore drilling and production operation unit models according to the data types, and simulation calculation of all the offshore drilling and production operation processes is carried out. According to the invention, the dynamic monitoring of the simulation process of the offshore drilling operation can be realized, and the decision scientificity of the offshore drilling operation is enhanced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ship electronic information, and particularly relates to a simulation process monitoring method for offshore drilling and production operation. BACKGROUND

[0002] The offshore drilling and production operation process is complex, the operation load state is changeable, and the operation action flow monitoring requirement is high, which brings great challenges to the traditional ship operation safety. The existing offshore drilling and production operation technology lacks simulation verification of important operation processes in the offshore work ship operation stage, and has the problem of difficult operation guarantee of complex offshore drilling and production operation. SUMMARY

[0003] The main purpose of the present application is to provide a simulation process monitoring method for offshore drilling and production operation, which realizes dynamic monitoring of the simulation process of the offshore drilling and production operation process, enhances the decision-making scientificity of the offshore drilling and production operation, and improves the guarantee level of the offshore work ship platform.

[0004] The technical scheme adopted by the present application is as follows: a simulation process monitoring method for offshore drilling and production operation, comprising: Real-time collection of offshore drilling and production operation data, and addition of the data to different data sets according to the types of the data; Preprocessing of the data of each data set, conversion into data points with data characteristic values as coordinates, detection of abnormal value points in the data points, and taking all abnormal value points as abnormal value samples of the data set; Calculation of the outlier factor values of the sample points in the abnormal value samples of each data set, judgment of whether the sample points are outliers according to the calculation results, rejection of the sample points from the data sets if the sample points are outliers, and retention of the sample points in the data sets if the sample points are not outliers; After the outliers are removed, the data of each data set is respectively imported into a corresponding offshore drilling and production operation unit model for simulation calculation of the offshore drilling and production operation; wherein the plurality of offshore drilling and production operation unit models are obtained by pre-establishment.

[0005] According to the above technical scheme, a plurality of data acquisition devices are used to obtain offshore drilling and production operation data through a plurality of data acquisition protocols; wherein the data acquisition devices include sensors, programmable logic controllers and industrial computers; the data acquisition protocols include field bus protocols, wired network protocols and industrial control protocols; and the offshore drilling and production operation data includes speed data, acceleration data, stress data and strain data of offshore drilling and production operation.

[0006] According to the above technical scheme, the preprocessing of the data of each data set includes data filtering and data cleaning.

[0007] According to the technical scheme, the method for detecting the outlier point in the data point comprises: dividing a hyperplane outside the data point in a multi-dimensional space by density, angle and distance, and taking the data point outside the hyperplane as the outlier point.

[0008] According to the technical scheme, the method for calculating the outlier factor value of the sample point in the outlier sample of each data set comprises: calculating the distance between any two sample points in the outlier sample; calculating the local reachable distance of the sample point to be detected according to the distance between the any two sample points; calculating the local reachable density of the sample point to be detected; calculating the outlier factor value of the sample point to be detected according to the local reachable distance and the local reachable density of the sample point to be detected.

[0009] According to the technical scheme, the method for calculating the distance between any two sample points in the outlier sample comprises Mahalanobis distance method, Euclidean distance method, Hamming distance method, Chebyshev distance method, Minkowski distance method and spherical distance method. The method for calculating the local reachable distance of the sample point to be detected comprises: calculating the maximum value of the distance between the sample point to be detected and a plurality of cluster points thereof.

[0010] According to the technical scheme, the method for calculating the local reachable density of the sample point to be detected comprises: calculating the near distance of the sample point to be detected with respect to the outlier sample to which the sample point to be detected belongs according to the local reachable distance of the sample point to be detected, and taking the reciprocal of the near distance as the local reachable density of the sample point to be detected.

[0011] According to the technical scheme, the method for calculating the outlier factor value of the sample point to be detected comprises: calculating the local reachable density of each neighborhood point of the sample point to be detected, then calculating the ratio of the local reachable density of each neighborhood point to the local reachable density of the sample point to be detected, respectively, and taking the average value of the plurality of ratios as the outlier factor value of the sample point to be detected.

[0012] According to the technical scheme, the method for determining whether the sample point is an outlier factor according to the calculation result of the outlier factor value comprises: if the outlier factor value of the sample point is greater than a preset value, determining that the sample point is an outlier factor; otherwise, determining that the sample point is not an outlier factor.

[0013] According to the technical scheme, the offshore drilling and production operation unit model established in advance comprises: an offshore drilling and production operation mechanics simulation unit model constructed based on a geometric model, an offshore drilling and production operation motion dynamics simulation unit model constructed based on a physical model, and an offshore drilling and production operation process simulation unit model constructed based on an offshore drilling and production operation process template.

[0014] The beneficial effects generated by the present application are: compared with the prior art of collecting and monitoring limited discrete data, the present application more comprehensively and completely monitors and simulates the offshore drilling and production operation process, and based on the monitoring and simulation results, significantly optimizes the decision efficiency of the offshore drilling and production operation process. At the same time, based on the outlier factor detection technology, the present application accurately removes the abnormal values in the data used for simulation operation, reduces the error rate of the offshore drilling and production operation process management, and improves the reliability of the offshore drilling and production platform.

[0015] Of course, implementing any product of the present application does not necessarily require achieving all the advantages described above at the same time. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0017] Figure 1 is a flow chart of the offshore drilling and production operation simulation process monitoring method of the present application embodiment; Figure 2 is a structural diagram of the offshore drilling and production operation simulation process monitoring system of the present application embodiment; Figure 3 is a flow chart of the offshore drilling and production operation mechanics simulation process monitoring method of the present application embodiment; Figure 4 is a flow chart of the offshore drilling and production operation kinematics dynamics simulation process monitoring method of the present application embodiment; Figure 5 is a flow chart of the offshore drilling and production operation process simulation process monitoring method of the present application embodiment. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of the present application more clear, the present application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not to limit the present application.

[0019] It should be noted that the diagrams provided in the present application embodiment only illustrate the basic concept of the present application in a schematic manner, and therefore only the components related to the present application are shown in the diagrams, not the number, shape and size of the components when actually implemented. The actual implementation of each component may be a random change in shape, number and proportion, and the layout pattern of the components may also be more complex.

[0020] In the present application, it also needs to be explained that, if the terms such as "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" and the like appear, the indicated orientation or positional relationship is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the indicated device or element must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application. In addition, if the terms "first", "second" appear, they are only for description and distinction purposes, and cannot be understood as indicating or implying relative importance.

[0021] Embodiment 1 The present embodiment provides a method for monitoring the simulation process of offshore drilling and production operations, and the flowchart is as shown in Figure 1 The method comprises the following steps: S1, real-time acquisition of offshore drilling and production operation data, and adding the data into different data sets according to the types of the data.

[0022] Specifically, a variety of offshore drilling and production operation data including speed, acceleration, stress and strain are obtained by using sensors, programmable logic controllers and industrial personal computers through field bus protocols, wired network protocols and industrial control protocols.

[0023] S2, pre-processing the data of each data set, converting it into a data point with data characteristic value as coordinates, detecting the outlier points in the data point, and taking all the outlier points as the outlier samples of the data set.

[0024] S201, pre-processing the data contained in each data set, such as data filtering and data cleaning, extracting the characteristic values of the data as the multi-dimensional space coordinates of the data points corresponding to the data.

[0025] S202, dividing the hyperplane in the multi-dimensional space where the data point is located by density, angle and distance, and taking the data points outside the hyperplane as outlier points.

[0026] S203, taking all the outlier points of the data set as the outlier samples of the data set.

[0027] S3, calculating the outlier factor value of the sample points in the outlier samples of each data set, and judging whether the sample point is an outlier factor according to the calculation result; if the sample point is an outlier factor, it is removed from the data set to which it belongs; otherwise, the sample point is retained in the data set to which it belongs.

[0028] S301, calculating the distance between any two sample points in the outlier samples.

[0029] Specifically, the distance between any two sample points in the outlier sample is calculated by the Mahalanobis distance method, the Euclidean distance method, the Hamming distance method, the Chebyshev distance method, the Minkowski distance method or the spherical distance method.

[0030] The outlier sample set D, the sample point A and the sample point B are defined, and in this embodiment, the Minkowski distance method and the Mahalanobis distance method are selected for calculation.

[0031] The calculation formula of the Minkowski distance method is as follows:

[0032] wherein, is the distance between the sample point A and the sample point B, is the ith element in is the ith element in is the ith element in is the ith element in

[0033] The calculation formula of the Mahalanobis distance method is as follows:

[0034] wherein, is the distance between the sample point A and the sample point B, is the ith element in is the ith element in is the ith element in is the ith element in

[0035] S302, for the to-be-tested sample point o which needs to calculate the outlier factor value, according to the distance between any two sample points , in this embodiment, the Mahalanobis distance obtained in step S301 is selected to calculate the local reachable distance of the to-be-tested sample point o.

[0036] Specifically, the maximum value of the distance between the to-be-tested sample point o and its k cluster points P is calculated, and the calculation formula is as follows:

[0037] wherein, is the distance from the k cluster points P of the to-be-tested sample point o to the point o, is the distance between the kth cluster point P and the to-be-tested sample point o. The reachable distance of the k cluster points P of the to-be-tested sample point o is obtained by taking the maximum value of the distance between each cluster point P and the to-be-tested sample point o.

[0038] S303, the local reachable density of the to-be-tested sample point o is calculated.

[0039] Specifically, first, the near distance sum of the sample point o to be tested relative to the abnormal value sample set D is calculated, and the calculation formula is as follows:

[0040] wherein, is the k-nearest neighbor distance sum of the sample point o to be tested relative to D, is the neighborhood point of the sample point o to be tested.

[0041] Next, the local reachable density of the sample point o to be tested is calculated according to the near distance sum , and the calculation formula is as follows:

[0042] wherein, is the number of k neighborhood points P of the sample point o to be tested, represents the reciprocal of the near distance sum of the sample point o to be tested and the k neighborhood points P.

[0043] S304, the outlier factor value of the sample point to be tested is calculated according to the local sample point reachable distance sum and the local reachable density of the sample point to be tested.

[0044] Specifically, the local reachable density of each neighborhood point of the sample point to be tested is calculated, the ratio of the local reachable density of each neighborhood point to the local reachable density of the sample point to be tested is calculated respectively, and the average value is taken, and the calculation formula is as follows:

[0045] S305, if the outlier factor value of the sample point is greater than 1, the sample point is judged to be an outlier factor; otherwise, the sample point is judged to be a non-outlier factor.

[0046] If approaches 1, it indicates that the local reachable density of the sample point o to be tested is similar to the local reachable density of its neighborhood point, and the sample point o to be tested is judged to belong to the cluster where the neighborhood point is located. If is less than 1, it indicates that the reachable density of the sample point o to be tested is greater than the density of its neighborhood point, and the sample point o to be tested is judged to be a dense point. If is greater than 1, it indicates that the reachable density of the sample point o to be tested is less than the density of its neighborhood point, and the sample point o to be tested is judged to be an abnormal point.

[0047] S4, after removing the outlier factor, the data of each data set is respectively imported into the corresponding offshore drilling and production unit model, and the simulation calculation of offshore drilling and production operation is performed.

[0048] Specifically, the offshore drilling and production operation unit model comprises an offshore drilling and production operation mechanics simulation unit model constructed based on a geometric model and a finite element modeling method. The offshore drilling and production operation mechanics simulation unit model is obtained by discretely processing the geometric model in a grid through the finite element modeling method. Then, constraint conditions of the geometric model are determined based on installation and fixing forms of offshore drilling and production operation equipment, and the establishment is completed.

[0049] The collected load data and the like in the offshore drilling and production operation process are substituted into the offshore drilling and production operation mechanics simulation unit model to perform simulation calculation of stress and strain data. The offshore drilling and production operation mechanics data obtained through the simulation calculation can be inquired by a user through a cloud chart.

[0050] An offshore drilling and production operation motion dynamics simulation unit model is constructed based on a rigid body kinematics and dynamics method and a physical model. The collected motion state parameters in the offshore drilling and production operation process are substituted into the offshore drilling and production operation motion dynamics simulation unit model. The offshore drilling and production operation motion dynamics simulation unit model is numerically simulated by using the Lagrange second kinematics principle to perform simulation calculation of kinematics and dynamics such as displacement, velocity, acceleration, and inertial force. The offshore drilling and production operation motion dynamics data obtained through the simulation calculation can be presented in a multi-dimensional visualized manner through three-dimensional virtual display.

[0051] An offshore drilling and production operation process simulation unit model is constructed based on an offshore drilling and production operation process template. The offshore drilling and production operation process simulation unit model is constructed by using a linked list according to basic process nodes of offshore drilling and production operation. The offshore drilling and production operation process simulation unit model establishes a mapping relationship between the basic process nodes and physical properties of offshore drilling and production operation equipment. Collected offshore drilling and production operation process data are substituted into the offshore drilling and production operation process simulation unit model to simulate and calculate a complete offshore drilling and production operation process, and the simulation state is corrected through real-time collected data.

[0052] The embodiment also provides an offshore drilling and production operation simulation process monitoring system, which has a structure as shown in Figure 2 The system comprises an operation bearing module, a data collection module, a data processing module, and a simulation operation module.

[0053] Specifically, the operation bearing module is connected to the data collection module and comprises drilling and production equipment such as a derrick, a lifting system, a pipe grabbing machine, and a pipe arranging machine, and is a source of offshore drilling and production data.

[0054] The data collection module is connected to the data processing module and is used to acquire various offshore drilling and production operation data from the operation bearing module through various data collection protocols by using various data collection devices.

[0055] The data processing module is connected to the simulation operation module and is used to pre-process data collected by the data collection module, and then remove abnormal values in the data based on an outlier factor detection technology.

[0056] The simulation operation module is configured to respectively import data of each data set into a corresponding offshore drilling and production unit model according to the data category, and perform simulation calculation on each offshore drilling and production operation process.

[0057] The application further provides a computer readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card memory (for example, an SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application store, etc., which stores a computer program, and the program is executed by a processor to realize corresponding functions. The computer readable storage medium of the embodiment is executed by the processor to realize the offshore drilling and production operation simulation process monitoring method of the method embodiment.

[0058] Embodiment 2 The embodiment provides an offshore drilling and production operation mechanics simulation monitoring method, which is different from the offshore drilling and production operation simulation process monitoring method in Embodiment 1 in that after data collection and outlier factor elimination are completed, the data of the offshore drilling and production operation collected by the embodiment are imported into an offshore drilling and production operation mechanics simulation unit model, and the process is as shown in Figure 3 and includes the following steps: P1, the geometric model is discretely processed by grid through a limited unit modeling method.

[0059] P2, based on the installation and fixing form of the offshore drilling and production operation equipment, the constraint condition of the geometric model is determined, and the establishment of the offshore drilling and production operation mechanics simulation unit model is completed.

[0060] P3, the collected load data and other data in the offshore drilling and production operation process are substituted into the offshore drilling and production operation mechanics simulation unit model, and simulation calculation of stress and strain data is performed.

[0061] Further, the offshore drilling and production operation mechanics data obtained by simulation calculation can be queried by a user in a cloud chart mode.

[0062] The collection method of the load data has been described in Embodiment 1 and will not be described here.

[0063] Embodiment 3 The embodiment provides an offshore drilling and production operation mechanics simulation monitoring method, which is different from the offshore drilling and production operation simulation process monitoring method in Embodiment 1 in that after data collection and outlier factor elimination are completed, the data of the offshore drilling and production operation collected by the embodiment are imported into an offshore drilling and production operation mechanics simulation unit model, and the process is as shown in Figure 4 and includes the following steps: T1, using rigid body kinematics and dynamics method to construct offshore drilling and production operation kinematics simulation unit model.

[0064] T2, substituting the collected motion state parameters in the offshore drilling and production operation process into the offshore drilling and production operation kinematics simulation unit model.

[0065] T3, using Lagrange's second kinematics principle, numerical simulation is carried out on the offshore drilling and production operation kinematics simulation unit model, and kinematics and dynamics simulation calculation such as displacement, velocity, acceleration and inertial force is carried out.

[0066] Further, the offshore drilling and production operation kinematics data obtained by simulation calculation can be presented in multi-dimension through three-dimensional virtual display.

[0067] The collection method of the motion state parameters has been described in embodiment 1 and will not be repeated here.

[0068] Embodiment 4 The embodiment provides a kind of offshore drilling and production operation process simulation monitoring method, and the difference between the offshore drilling and production operation simulation process monitoring method described in embodiment 1 is that after completing data collection, outlier factor is eliminated, the data of the offshore drilling and production operation collected in this embodiment is introduced into offshore drilling and production operation process simulation unit model, process is as shown in Figure 5 Including the following steps: Q1, according to the basic flow node of offshore drilling and production operation, chain table is used to build offshore drilling and production operation process template.

[0069] Q2, establish the mapping relationship between basic flow node and offshore drilling and production operation equipment physical attribute, and construct offshore drilling and production operation process simulation unit model.

[0070] Q3, the collected offshore drilling and production operation process data is substituted into offshore drilling and production operation process simulation unit model, and the complete offshore drilling and production operation process is simulated and calculated, and the simulation state is corrected by real-time data acquisition.

[0071] The collection method of the offshore drilling and production operation process data has been described in embodiment 1 and will not be repeated here.

[0072] In summary, the present application provides a kind of offshore drilling and production operation simulation process monitoring method and system, realize the dynamic monitoring of offshore drilling and production operation process simulation, enhance the decision scientificity of offshore drilling and production operation, improve the support level of offshore work ship platform.

[0073] It should be noted that, according to the needs of implementation, each step / component described in the present application can be split into more steps / components, or two or more steps / components or part operations of the steps / components can be combined into a new step / component, to achieve the purpose of the present application.

[0074] The size of the serial number of each step in the above embodiment does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0075] It should be understood that, for those skilled in the art, improvements or changes can be made according to the above description, and all these improvements and changes shall fall within the protection scope of the appended claims of the present application.

Claims

1. A method for monitoring an offshore drilling operation simulation process, characterized in that: include: Collect offshore drilling and production data in real time and add it to different data sets according to the data type; Preprocess the data of each data set, convert it into data points with data feature values ​​as coordinates, detect outlier points in the data points, and use all outlier points as outlier samples of the data set; Calculate the outlier factor value of the sample point in the outlier sample of each data set, and determine whether the sample point is an outlier factor based on the calculation result; if the sample point is an outlier factor, remove it from the data set to which it belongs; Otherwise, keep the sample point in the corresponding data set; After the outlier factors are eliminated, the data of each data set are respectively imported into the corresponding offshore drilling and production operation unit model to perform simulation and solution of the offshore drilling and production operation; wherein, the offshore drilling and production operation unit model is obtained by pre-establishment.

2. The offshore drilling operation simulation process monitoring method according to claim 1, characterized in that: The method for collecting offshore drilling operation data includes: Offshore drilling and production operation data are acquired using a variety of data acquisition devices and a variety of data acquisition protocols; wherein the data acquisition devices include sensors, programmable logic controllers, and industrial computers; the data acquisition protocols include fieldbus protocols, wired network protocols, and industrial control protocols; the offshore drilling and production operation data include speed data, acceleration data, stress data, and strain data of offshore drilling and production operations.

3. The offshore drilling operation simulation process monitoring method according to claim 1, characterized in that: The preprocessing of the data of each data set includes data filtering and data cleaning.

4. The offshore drilling operation simulation process monitoring method according to claim 1, characterized in that: The method for detecting outlier points in data points includes: dividing a hyperplane in the multidimensional space where the data points are located by density, angle and distance, and treating data points outside the hyperplane as outlier points.

5. The offshore drilling operation simulation process monitoring method according to claim 1, characterized in that: The method for calculating the outlier factor value of the sample point in the outlier sample of each data set includes: Calculate the distance between any two sample points in the outlier sample; For a sample point to be tested for which an outlier factor value needs to be calculated, the local reachable distance of the sample point to be tested is calculated based on the distance between any two sample points; Calculating the local reachability density of the sample point to be measured according to the local reachability distance of the sample point to be measured; The outlier factor value of the sample point to be tested is calculated according to the local reachable distance and the local reachable density of the sample point to be tested.

6. The offshore drilling operation simulation process monitoring method according to claim 5, characterized in that: The method for calculating the distance between any two sample points in the outlier sample includes Mahalanobis distance method, Euclidean distance method, Hamming distance method, Chebyshev distance method, Minkowski distance method and spherical distance method; The method for calculating the local reachable distance of a sample point to be measured includes: calculating the maximum value of the distance between the sample point to be measured and a plurality of cluster points thereof.

7. The offshore drilling operation simulation process monitoring method according to claim 5, characterized in that: The method for calculating the local reachable density of the sample point to be tested includes: calculating the sum of the short distances of the sample point to be tested relative to the outlier sample to which it belongs according to the local reachable distance of the sample point to be tested, and taking the reciprocal of the short distances as the local reachable density of the sample point to be tested.

8. The offshore drilling operation simulation process monitoring method according to claim 5, characterized in that: The method for calculating the outlier factor value of the sample point to be tested includes: Calculate the local reachability density of each neighborhood point of the sample point to be tested, then calculate the ratio of the local reachability density of each neighborhood point to the local reachability density of the sample point to be tested, and take the average of the multiple ratios obtained as the outlier factor value of the sample point to be tested.

9. The offshore drilling operation simulation process monitoring method according to claim 1, characterized in that: The method for determining whether a sample point is an outlier factor according to the calculation result of the outlier factor value includes: if the outlier factor value of the sample point is greater than a preset value, then judging that the sample point is an outlier factor; otherwise, judging that the sample point is not an outlier factor.

10. The offshore drilling operation simulation process monitoring method according to claim 1, characterized in that: The pre-established offshore drilling and production operation unit models include: an offshore drilling and production operation mechanics simulation unit model based on a geometric model, an offshore drilling and production operation motion dynamics simulation unit model based on a physical model, and an offshore drilling and production operation process simulation unit model based on an offshore drilling and production operation process template.

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