CN113705030B

CN113705030B - Method, device, equipment and storage medium for determining lifting amount of oil and gas pipeline

Info

Publication number: CN113705030B
Application number: CN202010431819.9A
Authority: CN
Inventors: 王东源; 谭秋霞; 张振永; 赵子峰; 余志峰; 杨建�; 王洪波
Original assignee: China National Petroleum Corp; China Petroleum Pipeline Engineering Corp
Current assignee: China National Petroleum Corp; China Petroleum Pipeline Engineering Corp
Priority date: 2020-05-20
Filing date: 2020-05-20
Publication date: 2024-03-26
Anticipated expiration: 2040-05-20
Also published as: CN113705030A

Abstract

The application discloses a method, a device, equipment and a storage medium for determining lifting amount of an oil and gas pipeline, and belongs to the technical field of energy transmission. Through the technical scheme provided by the embodiment of the application, the terminal can quickly obtain the maximum strain amount corresponding to the reference lifting amount by inputting the reference lifting amount, the pipeline parameters and the soil parameters of the goaf soil into the maximum strain amount model, so that whether the reference lifting amount is safe lifting amount or not is determined according to the maximum strain amount and the allowable strain amount. If the reference lifting amount is a safe lifting amount, the terminal can determine the reference lifting amount as a target lifting amount, and then the oil and gas pipeline can be lifted according to the target lifting amount. And a designer can quickly and accurately calculate whether the designed reference lifting amount is safe lifting amount according to the related parameters of the pipeline and the goaf, and a finite element model does not need to be reconstructed, so that the working efficiency is improved, and the design period is shortened.

Description

Method, device, equipment and storage medium for determining lifting amount of oil and gas pipeline

Technical Field

The application relates to the technical field of energy transmission, in particular to a method, a device, equipment and a storage medium for determining lifting amount of an oil and gas pipeline.

Background

Goafs can appear in exploitation of underground mineral resources, and if surrounding rock instability occurs in the goafs, geological disasters such as surface cracking, sinking or collapse can be caused, so that great potential safety hazards are brought to surface building (construction). In some areas with rich coal resources and wider distribution, geological disasters such as surface cracking and ground subsidence are frequent due to excessive mining of coal mines, which threatens the safety of people in production and life, and also causes larger potential safety hazards and extremely easy safety accidents for oil and gas pipelines positioned in goaf, so how to control and treat the geological disasters in the goaf is an important issue in the current pipeline transmission field.

For the oil gas pipeline in the mining subsidence area, in order to ensure the safe operation of the pipeline, a treatment measure must be adopted, the current treatment measure with good treatment effect and economy is a lifting pipe, the stress and/or strain states of the pipeline in the treatment section are required to be evaluated and checked according to the preset lifting amount in the lifting pipe treatment process, and a reasonable lifting pipe treatment scheme is determined. At present, when a pipe lifting treatment scheme is determined, a finite element method and finite element general analysis software are generally adopted to calculate the strain quantity of the pipeline under the action of pipe lifting, so that on one hand, the sinking displacement of the pipeline caused by sinking can be eliminated, and on the other hand, the secondary damage of the pipeline caused by the overlarge lifting quantity can be prevented.

In the above formulation process, when the finite element method is adopted for analysis and calculation, the specific engineering problem needs to be abstracted into a mechanical model, and then the mechanical model is built in general software (such as ANSYS) and the calculation is solved. However, the finite element method has high pertinence, specific analysis is required according to specific working conditions and boundary conditions, the model is difficult to realize universality, the calculation period is long, and the finite element calculation is required to have solid mechanical knowledge, so that common designers are difficult to fully master related mechanical knowledge in a short design period and complete complex finite element modeling and calculation; in addition, because of the characteristics of the finite element method and software, statistical results are difficult to form in batch processing, so that the design method based on reliability cannot be applied to the determination process of the oil and gas pipeline pipe lifting treatment scheme in the mining subsidence area, which is a technical problem to be solved urgently in the design of the pipe lifting treatment scheme.

Disclosure of Invention

The embodiment of the application provides a method, a device, equipment and a storage medium for determining the lifting amount of an oil and gas pipeline, which can improve the working efficiency and shorten the design period. The technical scheme is as follows:

On the one hand, a method for determining the lifting amount of an oil and gas pipeline is provided, which comprises the following steps:

obtaining pipeline parameters of a target oil-gas pipeline, wherein the target oil-gas pipeline is an oil-gas pipeline positioned in a goaf;

determining a maximum strain amount model matched with the pipeline steel type from a plurality of maximum strain amount models according to the pipeline steel type of the target oil and gas pipeline;

invoking the maximum strain quantity model, and inputting pipeline parameters of the target oil and gas pipeline, a reference lifting quantity and soil parameters of the goaf soil into the maximum strain quantity model for prediction to obtain the maximum strain quantity of the target oil and gas pipeline under the reference lifting quantity;

and comparing the maximum strain amount with the allowable strain amount of the target oil and gas pipeline, and determining the reference lifting amount as the target lifting amount if the maximum strain amount is smaller than the allowable strain amount.

In one possible embodiment, after the comparing the maximum strain amount to the allowable strain amount of the target hydrocarbon pipe, the method further comprises:

and if the maximum strain amount is larger than the allowable strain amount, updating the reference lifting amount, and executing the processes of predicting the maximum strain amount and comparing the maximum strain amount and the allowable strain amount based on the updated reference lifting amount and the pipeline parameters.

In a possible implementation manner, the invoking the maximum strain amount model, inputting the pipeline parameter of the target oil and gas pipeline, the reference lifting amount and the soil parameter of the goaf soil body into the maximum strain amount model for prediction, and obtaining the maximum strain amount of the target oil and gas pipeline under the reference lifting amount includes:

invoking relation data I, and inputting pipeline parameters of the target oil and gas pipeline, the reference lifting amount and soil parameters of the goaf soil into the relation data I to obtain the maximum strain of the target oil and gas pipeline under the reference lifting amount;

relationship data one:

wherein epsilon is the maximum strain of the target oil and gas pipeline, and A is the lifting displacement of the target oil and gas pipeline; b is the wall thickness of the target oil and gas pipeline; c is the outer diameter of the target oil and gas pipeline; d is the internal pressure of the target oil and gas pipeline; e is the temperature difference between the operating temperature and the installation temperature of the target oil and gas pipeline; lambda is the model deviation; η (eta) ₁ ,η ₂ ,…η ₁₀ And m, n are coefficients determined based on different pipe steel types; t (T) _u An axial soil spring for the soil body; q (Q) _u A vertical upward soil spring for the soil body; q (Q) _d A vertical downward soil spring for the soil body;

wherein,

wherein: h is the distance from the surface of the earth to the center of the target oil and gas pipeline; k (K) ₀ A lateral pressure coefficient for the soil mass; alpha is the cohesive force coefficient of the soil body; c is the cohesive force of the soil body; gamma' is the effective weight of the soil body; tan delta is the friction coefficient of the soil body and the target oil and gas pipeline; i is the surface gradient;an effective internal friction angle for the soil body; n (N) _c 、N _q 、N _γ The viscosity-aggregation bearing capacity coefficient of the soil body; and gamma is the total volume weight of the soil body.

In one possible embodiment, the reference lifting amount is less than or equal to a maximum lifting amount, and the method for determining the maximum lifting amount includes:

and calling relation data II, and determining the maximum lifting amount of the target oil and gas pipeline:

relationship data two:

wherein epsilon is the maximum strain of the target oil and gas pipeline, and A is the lifting displacement of the target oil and gas pipeline; b is the wall thickness of the target oil and gas pipeline; c is the outer diameter of the target oil and gas pipeline; d is the internal pressure of the target oil and gas pipeline; e is the temperature difference between the operating temperature and the installation temperature of the target oil and gas pipeline; lambda is the model deviation; η (eta) ₁ ,η ₂ ,…η ₁₀ And m, n are coefficients determined based on different pipe steel types; t (T) _u Axial soil spring for the soil body；Q _u A vertical upward soil spring for the soil body; q (Q) _d A vertical downward soil spring for the soil body;

wherein,

In one possible embodiment, the training method of the maximum strain amount model includes:

constructing the finite element model corresponding to the sample oil gas pipeline according to the material parameters of the sample steel type and the pipeline parameters of the sample oil gas pipeline;

placing the finite element model in a virtual goaf, applying a virtual lifting effect on the finite element model in the virtual goaf, and obtaining the maximum virtual strain quantity of the finite element model at a plurality of lifting heights, wherein the soil parameters of the virtual soil body of the virtual goaf are the same as those of the goaf soil body;

And training the maximum strain model according to the pipeline parameters, the soil parameters of the virtual soil of the virtual goaf, the lifting height and the maximum virtual strain.

In one possible embodiment, the training the maximum strain amount model according to the pipe parameter, the soil parameter of the virtual soil of the virtual goaf, the lifting height, and the maximum virtual strain amount includes:

constructing an initial maximum strain model according to the relation between the maximum virtual strain and the pipeline parameters, the soil parameters of the virtual soil of the virtual goaf and the lifting height;

and adjusting model parameters of the initial maximum strain amount model according to the lifting heights and the maximum virtual strain amounts corresponding to the lifting heights, and taking the initial maximum strain amount model meeting the target iteration condition as the maximum strain amount model.

In a possible implementation manner, after the initial maximum strain amount model meeting the target iteration condition is taken as the maximum strain amount model, the method further includes:

inputting the lifting height into the maximum strain quantity model, and predicting according to the lifting height through the maximum strain quantity model to obtain a predicted maximum strain quantity corresponding to the lifting height;

And adjusting model parameters of the maximum strain quantity model according to difference information between the maximum virtual strain quantity corresponding to the lifting height and the predicted maximum strain quantity.

In one aspect, a device for determining a lifting amount of an oil and gas pipeline is provided, including:

the parameter acquisition module is used for acquiring pipeline parameters of a target oil-gas pipeline, wherein the target oil-gas pipeline is an oil-gas pipeline positioned in a goaf;

the model determining module is used for determining a target strain quantity model matched with the pipeline steel type from a plurality of maximum strain quantity models according to the pipeline steel type of the target oil and gas pipeline;

the prediction module is used for calling the target strain quantity model, inputting pipeline parameters of the target oil and gas pipeline, a reference lifting quantity and soil parameters of the goaf soil into the target strain quantity model for prediction, and obtaining the maximum strain quantity of the target oil and gas pipeline under the reference lifting quantity;

the lifting amount determining module is used for comparing the maximum strain amount with the allowable strain amount of the target oil and gas pipeline, and determining the reference lifting amount as the target lifting amount if the maximum strain amount is smaller than the allowable strain amount.

In one possible embodiment, the apparatus further comprises:

and the updating module is used for updating the reference lifting amount if the maximum strain amount is larger than the allowable strain amount, and executing the processes of predicting the maximum strain amount and comparing the maximum strain amount and the allowable strain amount based on the updated reference lifting amount and the pipeline parameters.

In a possible implementation manner, the prediction module is configured to invoke the first relational data, and input the pipeline parameter of the target oil and gas pipeline, the reference lifting amount and the soil parameter of the goaf soil body into the first relational data to obtain the maximum strain amount of the target oil and gas pipeline under the reference lifting amount;

relationship data one:

wherein epsilon is the maximum strain of the target oil and gas pipeline, and A is the lifting displacement of the target oil and gas pipeline; b is the wall thickness of the target oil and gas pipeline; c is the outer diameter of the target oil and gas pipeline; d is the internal pressure of the target oil and gas pipeline; e is the temperature difference between the operating temperature and the installation temperature of the target oil and gas pipeline; lambda is the model deviation; η (eta) ₁ ,η ₂ ,…η ₁₀ And m, n are coefficients determined based on different pipe steel types; t (T) _u An axial soil spring for the soil body; q (Q) _u For the vertical upward direction of the soil bodyA soil spring; q (Q) _d A vertical downward soil spring for the soil body;

wherein,

In one possible embodiment, the reference lift is less than or equal to the maximum lift, the device further comprising:

the maximum lifting amount determining module is used for calling the second relation data to determine the maximum lifting amount of the target oil and gas pipeline:

relationship data two:

wherein epsilon is the maximum strain of the target oil and gas pipeline, and A is the lifting displacement of the target oil and gas pipeline; b is the wall thickness of the target oil and gas pipeline; c is the outer diameter of the target oil and gas pipeline;d is the internal pressure of the target oil and gas pipeline; e is the temperature difference between the operating temperature and the installation temperature of the target oil and gas pipeline; lambda is the model deviation; η (eta) ₁ ,η ₂ ,…η ₁₀ And m, n are coefficients determined based on different pipe steel types; t (T) _u An axial soil spring for the soil body; q (Q) _u A vertical upward soil spring for the soil body; q (Q) _d A vertical downward soil spring for the soil body;

wherein,

In one possible embodiment, the training device of the maximum strain amount model includes:

the construction module is used for constructing the finite element model corresponding to the sample oil gas pipeline according to the material parameters of the sample steel type and the pipeline parameters of the sample oil gas pipeline;

the maximum strain quantity acquisition module is used for placing the finite element model in a virtual goaf, applying a virtual lifting effect on the finite element model in the virtual goaf, and acquiring the maximum virtual strain quantity of the finite element model at a plurality of lifting heights, wherein the soil parameters of the virtual soil body of the virtual goaf are the same as those of the soil body of the goaf;

And the training module is used for training the maximum strain quantity model according to the pipeline parameters, the soil parameters of the virtual soil of the virtual goaf, the lifting height and the maximum virtual strain quantity.

In one possible implementation manner, the training module is used for constructing an initial maximum strain amount model according to the relation between the maximum virtual strain amount and the pipeline parameter, the soil body parameter of the virtual soil body of the virtual goaf and the lifting height; and adjusting model parameters of the initial maximum strain amount model according to the lifting heights and the maximum virtual strain amounts corresponding to the lifting heights, and taking the initial maximum strain amount model meeting the target iteration condition as the maximum strain amount model.

In one possible embodiment, the apparatus further comprises:

the adjustment module is used for inputting the lifting height into the maximum strain quantity model, and predicting the lifting height according to the maximum strain quantity model to obtain a predicted maximum strain quantity corresponding to the lifting height; and adjusting model parameters of the maximum strain quantity model according to difference information between the maximum virtual strain quantity corresponding to the lifting height and the predicted maximum strain quantity.

In one aspect, a computer device is provided that includes a processor and a memory having at least one program code stored therein, the at least one program code loaded and executed by the processor to perform operations as performed in a method of determining an amount of lift of an oil and gas pipeline.

In one aspect, a computer readable storage medium having stored therein at least one program code loaded and executed by a processor to perform operations as performed in a method of determining an amount of lift of an oil and gas pipeline is provided.

Through the technical scheme that this application embodiment provided, the terminal just can obtain the maximum strain volume that the reference lifting volume corresponds through the soil body parameter input maximum strain volume model with reference lifting volume, pipeline parameter and goaf soil body to whether the lifting volume is safe lifting volume is confirmed according to maximum strain volume and allowable strain volume to safe lifting volume is the lifting volume that does not damage oil gas pipeline promptly. If the reference lifting amount is a safe lifting amount, the terminal can determine the reference lifting amount as a target lifting amount, and then the oil and gas pipeline can be lifted according to the target lifting amount. If the reference lift amount is not a safe lift amount, the terminal may update the reference lift amount until the newly determined reference lift amount is a safe lift amount. And a designer can quickly and accurately calculate whether the designed reference lifting amount is safe lifting amount according to the related parameters of the pipeline and the goaf, and a finite element model does not need to be reconstructed, so that the working efficiency is improved, and the design period is shortened.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flowchart of a method for determining an amount of lifting of an oil and gas pipeline according to an embodiment of the present disclosure;

FIG. 2 is a flowchart of a method for determining an amount of lift of an oil and gas pipeline according to an embodiment of the present disclosure;

FIG. 3 is a flowchart of a method for determining an amount of lift of an oil and gas pipeline according to an embodiment of the present disclosure;

FIG. 4 is a flowchart of a method for determining an amount of lift of an oil and gas pipeline according to an embodiment of the present disclosure;

FIG. 5 is a schematic structural diagram of a device for determining the lifting amount of an oil and gas pipeline according to an embodiment of the present application;

fig. 6 is a schematic structural diagram of a terminal according to an embodiment of the present application;

fig. 7 is a schematic structural diagram of a server according to an embodiment of the present application.

Detailed Description

To make the objects, technical solutions and advantages of the present application more apparent, the terms related to the embodiments of the present application are described first:

The constitutive model: also known as the mechanical constitutive equation of a material, or the stress-strain model of a material. Mathematical expressions describing the mechanical properties (stress-strain-strength-time relationship) of a material. The stress is external force applied to the material from outside, the strain is deformation of the material under the action of the stress, and the strength is the maximum stress which the material can bear before breaking.

Finite element analysis: the continuous geometrical mechanism is discretized into a finite number of cells, and a finite number of nodes are set in each cell, so that the continuum is regarded as an aggregate of a group of cells connected only at the nodes, while the node values of the field functions are selected as basic unknowns and an approximate interpolation function is assumed in each cell to represent the distribution law of the field functions in the cell, and a finite element equation set for solving the node unknowns is built, so that the infinite degree of freedom problem in one continuous domain is converted into a finite degree of freedom problem in a discrete domain.

After the node value is obtained by solving, the field functions on the unit and the aggregate can be determined by the set interpolation function. For each cell, an appropriate interpolation function is selected such that the function satisfies certain conditions within the subfields, at the subfield interfaces, and at the subfield and external interface. When the unit combination is in an equilibrium state under the known external load, a series of linear equation sets taking nodes and displacement as unknown quantities are listed, after the node displacement is solved by a computer, the stress and strain of each unit are calculated by using related formulas of elastic mechanics, and when each unit is small to a certain extent, the unit represents the real situation of each place of the continuous body.

Finite element model: the finite element model is a model established by applying a finite element analysis method, and is a group of unit assemblies which are connected at nodes only, transmit force only by the nodes and are constrained at the nodes only.

L450 steel: also known as X65 steel, is used primarily for the transport of natural gas, water and oil. The chemical composition of L450 is C: < 0.12%, si: < 0.4%, mn: < 1.65%, P: less than 0.02%, sulfur S: less than 0.01%. The yield strength is between 450 and 600MPa, and the tensile strength is between 535 and 755 MPa.

L485 steel: the device is mainly used for conveying natural gas, water and oil. The chemical composition of L485 is C: < 0.1%, si: < 0.4%, mn: < 1.8%, P: less than 0.02%, sulfur S: less than 0.01%. The yield strength is between 485 and 620MPa, and the tensile strength is between 570 and 755 MPa.

L555 steel: the device is mainly used for conveying natural gas, water and oil. The chemical composition of L555 is C: < 0.1%, si: < 0.4%, mn: < 1.8%, P: less than 0.02%, sulfur S: less than 0.01%. The yield strength is 555-690MPa, and the tensile strength is 625-825 MPa.

For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

FIG. 1 is a flowchart of a method for determining an oil and gas pipeline lifting amount according to an embodiment of the present application. Referring to fig. 1, this embodiment specifically includes:

101. and obtaining pipeline parameters of a target oil-gas pipeline, wherein the target oil-gas pipeline is an oil-gas pipeline positioned in a goaf.

102. And determining a target strain quantity model matched with the pipeline steel type from a plurality of maximum strain quantity models according to the pipeline steel type of the target oil and gas pipeline.

103. And (3) calling a maximum strain quantity model, and inputting pipeline parameters of the target oil and gas pipeline, the reference lifting quantity and soil parameters of goaf soil into the maximum strain quantity model for prediction to obtain the maximum strain quantity of the target oil and gas pipeline under the reference lifting quantity.

104. And comparing the maximum strain amount with the allowable strain amount of the target oil and gas pipeline, and if the maximum strain amount is smaller than the allowable strain amount, determining the reference lifting amount as the target lifting amount.

Through the technical scheme that this application embodiment provided, the terminal just can obtain the maximum strain volume that the reference lifting volume corresponds through the soil body parameter input maximum strain volume model with reference lifting volume, pipeline parameter and goaf soil body to whether the lifting volume is safe lifting volume is confirmed according to maximum strain volume and allowable strain volume to safe lifting volume is the lifting volume that does not damage oil gas pipeline promptly. If the reference lifting amount is a safe lifting amount, the terminal can determine the reference lifting amount as a target lifting amount, and then the oil and gas pipeline can be lifted according to the target lifting amount. And a designer can quickly and accurately calculate whether the designed reference lifting amount is safe lifting amount according to the related parameters of the pipeline and the goaf, and a finite element model does not need to be reconstructed, so that the working efficiency is improved, and the design period is shortened.

In the application, the terminal may execute the method for determining the lifting amount of the oil and gas pipeline provided by the application by training a plurality of maximum strain amount determining models, and for convenience of understanding, the training method of the maximum strain amount determining model related to the application is described first:

201. and the terminal constructs a finite element model corresponding to the sample oil gas pipeline according to the material parameters of the sample steel type and the pipeline parameters of the sample oil gas pipeline.

The steel type may be a type of steel used in actual production of oil and gas pipelines, such as L450 steel, L485 steel or L555 steel, and the embodiment of the application is not limited to the steel type. The steel type material parameters may include, but are not limited to, steel type yield strength, tensile strength, exercise strength, hardness, and the like. The parameters of the sample oil and gas pipeline may include, but are not limited to, parameters such as the outer diameter of the sample oil and gas pipeline, the pipe wall thickness, the internal pressure of the pipeline, the temperature difference between the operating temperature of the pipeline and the installation temperature, and the like. It should be noted that, the terminal may construct a plurality of finite element models according to material parameters of different sample steel types, and train to obtain a plurality of maximum strain amount models according to the plurality of finite element models, where each maximum strain amount model corresponds to one sample steel type, and for convenience of understanding, a description will be given below taking a terminal training one maximum strain amount model as an example.

In one possible embodiment, the terminal may construct a virtual oil and gas pipeline identical to the pipeline parameters of the sample oil and gas pipeline according to the pipeline parameters of the sample oil and gas pipeline, and the shape and structure of the virtual oil and gas pipeline are identical to those of the sample oil and gas pipeline. The terminal can divide a target number of square grids on the virtual oil and gas pipeline, and the vertex of each square grid is a node, and the node is an acting point when virtual stress is added. Each node in the square grid is connected with each other, that is, when any node is subjected to virtual stress, the other nodes are affected. The terminal can set the material parameters of the virtual material corresponding to the virtual oil and gas pipeline as the material parameters of the sample steel type, so that the finite element model corresponding to the sample oil and gas pipeline of the sample steel type can be obtained. For example, the terminal may use finite element simulation (ANSYS) software when constructing the finite element model, and of course, other software may also be used to construct the finite element model, which is not limited in this embodiment of the present application.

202. The terminal places the finite element model in a virtual goaf, applies a virtual lifting effect to the finite element model in the virtual goaf, and obtains the maximum virtual strain quantity of the finite element model at a plurality of lifting heights, wherein the soil parameters of the virtual soil of the virtual goaf are the same as those of the actual goaf.

The virtual goaf can be a model which is constructed by a terminal and used for simulating the real condition of the goaf, the virtual goaf can be composed of a virtual soil body, and soil parameters of the virtual soil body can be set according to soil parameters of the soil body in the actual goaf.

In one possible implementation manner, the terminal may prevent the finite element model from being in the virtual goaf, adjust the shape of the finite element model, and make the boundary of the finite element model and the boundary of the virtual goaf contact with each other, that is, by adjusting the shape of the finite element model, the finite element model and the virtual goaf after shape adjustment may simulate the actual goaf collapse condition. The terminal can apply a virtual lifting effect on the finite element model in the virtual goaf, control the finite element model to slowly lift from a collapsed shape to an uncollapsed shape, and record a plurality of virtual strain amounts of the finite element model at different lifting heights in the lifting process. After the lifting is finished, the terminal can determine the maximum virtual strain amount from the plurality of virtual strain amounts.

For example, the terminal may prevent the finite element model from being in the virtual goaf, determine a boundary function of an area left to the finite element model in the virtual goaf, adjust the shape of the finite element model according to the boundary function, ensure that the boundary of the finite element model after the shape adjustment and the boundary of the virtual goaf do not intersect with each other, and adjust the shape of the finite element model after the shape change so that the boundary of the finite element model may be tangent to the boundary of the virtual goaf. The terminal can apply virtual stress to the nodes on the collapse part of the finite element model in the virtual goaf, namely, apply virtual lifting action to the finite element model, and control the collapse part of the finite element model to slowly rise and recover to an uncollapsed shape. The terminal can determine a plurality of virtual strain amounts of the finite element model corresponding to different lifting heights in the lifting process according to the applied virtual stress, the virtual acting force of the virtual soil body of the virtual goaf on the finite element model and the model parameters of the finite element model. After the lifting is finished, the terminal can determine the maximum virtual strain amount from the plurality of virtual strain amounts.

It should be noted that, in the step 202 described above, taking a lifting process as an example, in order to obtain more corresponding relations between lifting heights and maximum virtual strain amounts, the terminal may adjust the collapse state of the virtual goaf, correspondingly adjust the shape of the finite element model, and repeat the step 202 multiple times, so as to obtain the corresponding relations between the plurality of lifting heights and the maximum virtual strain amounts.

In addition, the above-mentioned construction of the finite element model is described by taking the terminal as an example of self-generation according to the material parameter and the pipeline parameter, and in other possible embodiments, the terminal may obtain a constitutive model corresponding to the pipeline, and input the material parameter into the constitutive model to obtain the finite element model, which is not limited in this embodiment. The constitutive model may be, for example, the Osgood Ramberg-Osgood constitutive model of Orchidaceae Bei Ge.

203. And training a maximum strain model by the terminal according to the pipeline parameters, the soil parameters of the virtual soil of the virtual goaf, the lifting height and the maximum virtual strain.

In one possible implementation, the terminal may construct an initial maximum strain model based on the relationship between the maximum virtual strain and the pipeline parameters, the soil parameters of the virtual soil of the virtual goaf, and the elevation height. And the terminal adjusts model parameters of the initial maximum strain model according to the lifting heights and the maximum virtual strain corresponding to the lifting heights, and takes the initial maximum strain model meeting the target iteration condition as the maximum strain model.

For example, the terminal may construct a relationship data: epsilon=ax+bh+cm, wherein epsilon is the maximum virtual strain quantity, x is a pipeline parameter, h is a lifting height, m is a soil parameter, A, B, C is a coefficient to be determined, and the relation data epsilon=ax+bh+cm is an initial maximum strain quantity model. In an iterative process, the terminal may input a lifting height and a maximum strain amount corresponding to the lifting height obtained in step 202 into an initial maximum strain amount model, and determine initial values of the three undetermined coefficients A, B, C. In the subsequent iteration process, the terminal can continuously input other lifting heights and the maximum strain amount corresponding to the other lifting heights until the number of iterations exceeds a threshold number of times, and the initial maximum strain amount model at the moment is the maximum strain amount model.

It should be noted that the above is described by taking a linear first-order equation as an example, and in other possible embodiments, the relationship data may be a more complex nonlinear multiple-order equation, such as ε=x ^2A +Bh ⁴ +e ^Cm And the like, the embodiments of the present application are not limited thereto. The process of training the maximum strain model described above may also be referred to as fittingThe terminal may use fitting software, such as a matrix factory (MatLab), to implement the above process, and of course, other fitting software may also be used to implement the above process, which is not limited in this embodiment of the present application.

204. The terminal inputs the lifting height into a maximum strain quantity model, and predicts according to the lifting height through the maximum strain quantity model to obtain a predicted maximum strain quantity corresponding to the lifting height. And adjusting model parameters of the maximum strain model according to difference information between the maximum virtual strain corresponding to the lifting height and the predicted maximum strain.

For example, the terminal may sequentially input a plurality of lifting heights [ 1.2,1.3,1.4,1.5 … … ] into the maximum strain amount model, and determine a plurality of predicted maximum strain amounts [ 0.3,0.4,0.42,0.49 … … ] corresponding to the lifting heights through the maximum strain amount model. The terminal can adjust model parameters of the maximum strain amount model according to difference information [ 0.02,0.05,0.05,0.02 … … ] between a plurality of predicted maximum strain amounts [ 0.3,0.4,0.42,0.49 … … ] and a plurality of maximum virtual strain amounts [ 0.28,0.35,0.37,0.47 … … ] corresponding to lifting heights, so that the predicted maximum strain amount predicted by the maximum strain amount model is closer to the maximum virtual strain amount, and the prediction effect of the maximum strain amount model is improved.

It should be noted that, the above example is described by taking the terminal to train the maximum strain amount model by using the lifting height and the virtual maximum strain amount obtained in step 201 as an example, and in other possible embodiments, the terminal may train the maximum strain amount model by lifting the lifting height and the maximum strain amount of the actual oil and gas pipeline during the process of lifting the actual oil and gas pipeline. In the implementation mode, the result of maximum strain prediction by adopting the trained maximum strain model is closer to the actual situation. In addition, before the terminal trains the maximum strain amount model through the lifting height of the actual oil gas pipeline and the maximum strain amount of the actual oil gas pipeline, the terminal can conduct data screening on the lifting height of the actual oil gas pipeline and the maximum strain amount of the actual oil gas pipeline, the terminal can keep data with lower lifting heights and delete the data with higher lifting heights in response to the fact that one maximum strain amount corresponds to at least two lifting heights, and therefore the prediction result of the trained maximum strain amount model can be guaranteed to be more conservative, and the safety of subsequent actual operation is improved.

In addition, the foregoing steps 201-204 are described by taking the terminal training maximum strain amount model as an example, and in other possible embodiments, the maximum strain amount model may be trained by a server, or the maximum strain amount model may be trained by an interaction between the terminal and the server, which is not limited in this embodiment of the present application.

Through the steps 201-204, the terminal can train a general maximum strain amount model by constructing a finite element model, and the subsequent designer can directly determine the lifting amount of the oil and gas pipeline based on the maximum strain amount model obtained through training, and the method can see the steps 301-306.

FIG. 3 is a flowchart of a method for determining an amount of lifting of an oil and gas pipeline according to an embodiment of the present application.

Referring to fig. 3, the method includes:

301. and the terminal acquires pipeline parameters of a target oil-gas pipeline, wherein the target oil-gas pipeline is an oil-gas pipeline positioned in a goaf.

The pipeline parameters of the oil and gas pipeline can comprise the pipeline outer diameter, the pipeline wall thickness, the pipeline inner pressure and the temperature difference between the pipeline operation and the installation of the target oil and gas pipeline.

In one possible implementation, the terminal may obtain the pipeline parameters of the target oil and gas pipeline through the identification information of the target oil and gas pipeline, where the identification information may be used to identify the target oil and gas pipeline, and the identification information may include, but is not limited to, the model number and production lot number of the target oil and gas pipeline. For example, the terminal may input the identification information of the target oil and gas pipeline into the pipeline database for querying, to obtain the pipeline parameters corresponding to the pipeline information.

In one possible implementation manner, the terminal may obtain the pipeline parameters of the target oil and gas pipeline through the position information of the target oil and gas pipeline. For example, the terminal may determine the location information of the goaf, input the location information of the goaf into a pipeline database, query the information in the pipeline database, obtain the identification of the target oil and gas pipeline, and obtain the pipeline information of the target oil and gas pipeline according to the identification of the target oil and gas pipeline.

302. And determining a maximum strain amount model matched with the pipeline steel type from a plurality of maximum strain amount models by the terminal according to the pipeline steel type of the target oil and gas pipeline.

In one possible implementation manner, the terminal may obtain the type of the pipe steel to which the target oil and gas pipe belongs according to the identification information of the target oil and gas pipe. The terminal may determine a sample steel type corresponding to the plurality of maximum strain gauge models, and determine a maximum strain gauge model corresponding to a sample steel type identical to a pipe steel type to which the target oil and gas pipe belongs as a maximum strain gauge model matching the pipe steel type.

303. And the terminal calls a maximum strain quantity model, and inputs pipeline parameters of the target oil and gas pipeline, the reference lifting quantity and soil parameters of goaf soil into the maximum strain quantity model for prediction, so as to obtain the maximum strain quantity of the target oil and gas pipeline under the reference lifting quantity.

The reference lifting amount may be a lifting amount required for recovering the target oil and gas pipeline to the designed depth, for example, the designed depth of the target oil and gas pipeline is 3 meters below the ground surface, the target oil and gas pipeline is sunk by 2 meters due to goafs occurring during collapse, and then the target oil and gas pipeline needs to be lifted by 2 meters, namely the reference lifting amount, in order to recover the target oil and gas pipeline to the designed depth.

In one possible implementation manner, the terminal may call the first relation data, and input the pipeline parameter of the target oil and gas pipeline, the reference lifting amount and the soil body parameter of the goaf soil body into the first relation data to obtain the maximum strain amount of the target oil and gas pipeline under the reference lifting amount.

Relationship data one:

wherein epsilon is the maximum strain of the target oil and gas pipeline, A is the reference lifting amount of the target oil and gas pipeline, B is the pipeline wall thickness of the target oil and gas pipeline, C is the pipeline outer diameter of the target oil and gas pipeline, D is the pipeline inner pressure of the target oil and gas pipeline, E is the temperature difference between the operating temperature and the installation temperature of the target oil and gas pipeline, lambda is the model deviation, eta ₁ ,η ₂ ,…η ₁₀ And m, n are coefficients determined based on different pipe steel types, T _u An axial soil spring for soil mass, Q _u A vertical soil-up spring for soil mass, Q _d Is a vertical downward soil spring of soil body.

Wherein,

wherein: h is the distance from the surface of the earth to the center of the target oil and gas pipeline; k (K) ₀ Is the lateral pressure coefficient of the soil body; alpha is the cohesive force coefficient of the soil body; c is the cohesive force of the soil body; gamma ray ^‘ Is the effective weight of the soil body; tan delta is the friction coefficient of the soil body and the target oil and gas pipeline; i is the surface gradient;is the effective internal friction angle of the soil body; n (N) _c 、N _q 、N _γ Is the cohesive force bearing capacity coefficient of the soil body; gamma is the total volume weight of the soil body.

Under the implementation mode, the terminal can quickly obtain the maximum strain of the target oil gas pipeline under the reference lifting amount according to the pipeline parameters of the target oil gas pipeline, the reference lifting amount and the soil body parameters of the goaf soil body, a finite element model is not required to be built again according to the pipeline parameters of the target oil gas pipeline, the reference lifting amount and the soil body parameters of the goaf soil body, the finite element model is analyzed, the maximum strain of the target oil gas pipeline under the reference lifting amount is obtained, the efficiency of determining the maximum strain is improved, and the time is saved.

It should be noted that, the reference lifting amount in the step 303 may be smaller than the maximum lifting amount of the target oil and gas pipeline, so that stability of the target oil and gas pipeline when lifting the target oil and gas pipeline may be ensured, the probability of damage of the target oil and gas pipeline when lifting is reduced, and the method for determining the maximum lifting amount of the target oil and gas pipeline may include the following steps:

In one possible implementation manner, the terminal may call relationship data two to determine the maximum lifting amount of the target oil and gas pipeline:

relationship data two:

the A is the maximum lifting amount of the target oil and gas pipeline, and the meaning of other parameters in the relation data II is the same as that in the relation data I.

The above embodiments are described below by way of three specific examples:

in example 1, in response to the steel type of the target oil and gas pipeline being L450 steel, the target goaf is a coal mine goaf, the terminal can call the relation data III, and input pipeline parameters of the target oil and gas pipeline, the reference lifting amount and soil parameters of soil of the goaf into the relation data III to obtain the maximum lifting amount of the target oil and gas pipeline.

Relationship data three:

wherein: η (eta) ₁ ＝-1.05×10 ^-10 ，η ₂ ＝1.35，η ₃ ＝-1.33，η ₄ ＝0.5，η ₅ ＝0.67，η ₆ ＝-0.97，η ₇ ＝0.37，η ₈ ＝1.00，η ₉ ＝33.75，η ₁₀ ＝1.39×10 ³ The method comprises the steps of carrying out a first treatment on the surface of the The mean value μ=0.97 to 1.05 of λ, and the standard deviation σ=0.08 to 0.11.

In example 2, in response to the steel type of the target oil and gas pipeline being L485 steel, the target goaf is a coal mine goaf, and the terminal can call the relationship data IV, and input pipeline parameters of the target oil and gas pipeline, the reference lifting amount and soil parameters of the goaf soil body into the relationship data IV to obtain the maximum lifting amount of the target oil and gas pipeline.

Relationship data four:

Wherein: η (eta) ₁ ＝-1.85×10 ^-11 ，η ₂ ＝1.35，η ₃ ＝-1.37，η ₄ ＝0.56，η ₅ ＝0.73，η ₆ ＝-1.04，η ₇ ＝0.41，η ₈ ＝1.00，η ₉ ＝122.33，η ₁₀ ＝4.42×10 ³ Mean μ=0.98 to 1.05 and standard deviation σ=0.07 to 0.13 for λ.

In example 3, in response to the steel type of the target oil and gas pipeline being L555 steel, the target goaf is a coal mine goaf, the terminal can call the relation data five, and input pipeline parameters of the target oil and gas pipeline, the reference lifting amount and soil parameters of soil of the goaf into the relation data five to obtain the maximum lifting amount of the target oil and gas pipeline.

Relationship data five:

wherein: η (eta) ₁ ＝-6.10×10 ^-13 ，η ₂ ＝1.53，η ₃ ＝-1.53，η ₄ ＝1.39，η ₅ ＝0.5222，η ₆ ＝-1.17，η ₇ ＝0.47，η ₈ ＝1.00，η ₉ ＝13.78，η ₁₀ = 397.80; the mean value μ=0.97 to 1.01 of λ, and the standard deviation σ=0.11 to 0.16。

304. The terminal compares the maximum strain amount with the allowable strain amount of the target oil and gas pipeline, and if the maximum strain amount is smaller than the allowable strain amount, step 305 is executed; in response to the maximum strain amount being greater than the allowable strain amount, step 306 is performed.

305. If the maximum strain amount is less than the allowable strain amount, the terminal determines the reference lift amount as the target lift amount.

In one possible embodiment, after step 305, the terminal may control the target oil and gas pipeline to lift the target lift amount at the target speed.

Wherein, the target speed can be determined according to the type of the pipe steel to which the target oil and gas pipe belongs, for example, the type of the pipe steel of the target oil and gas pipe is L450, and then the terminal can determine the target speed to be 0.1m/min; if the pipe steel type of the target oil and gas pipe is L555, the terminal may determine the target speed to be 0.15m/min. It should be noted that the target speeds corresponding to the different types of pipe steel are set only for easy understanding, and different target speeds may be set for the different types of pipe steel according to actual situations, which is not limited in the embodiment of the present application.

306. If the maximum strain amount is greater than the allowable strain amount, the terminal updates the reference lifting amount, and executes the processes of predicting the maximum strain amount and comparing the maximum strain amount and the allowable strain amount based on the updated reference lifting amount and the pipeline parameters.

In one possible implementation manner, the terminal may reduce the reference lifting amount, input the reduced reference lifting amount into a maximum strain amount model, and predict the reduced reference lifting amount through the maximum strain amount model to obtain a maximum strain amount corresponding to the effective reference lifting amount. For example, the original reference lifting amount is 1.8 m, the maximum strain amount is 0.45% through the prediction of the maximum strain amount model, the allowable strain amount of the pipeline is 0.38%, and the terminal can reduce the reference lifting amount to 1.5 m because of 0.45% > 0.38%, and input 1.5 m into the maximum strain amount model for prediction, so that a new maximum strain amount is obtained. The terminal may compare the new maximum strain amount to the allowable strain amount until the maximum strain amount predicted by the maximum strain amount model is less than or equal to the allowable strain amount.

In one possible implementation, the terminal may determine the update step of the reference lift according to the soil parameters of the goaf soil. In each updating process, the terminal can update the current reference lifting amount according to an updating step length, and execute the processes of predicting the maximum strain amount and comparing the maximum strain amount and the allowable strain amount based on the updated reference lifting amount and the pipeline parameters. For example, the terminal may input soil parameters of the goaf soil at a plurality of change time points into a target neural network model, predict allowable lifting amount of the goaf in a lifting operation time period through the target neural network model, and determine a corresponding update step according to a numerical space where the allowable lifting amount is located, where the target neural network is obtained through training of the soil parameters and the allowable lifting amount, and has an ability of predicting the allowable lifting amount based on the soil parameters.

It should be noted that, the steps 301 to 306 are described by taking the terminal as an execution subject, and in other possible embodiments, the steps 301 to 306 may be executed by a server, or the maximum strain amount model may be trained by interaction between the terminal and the server, which is not limited in this embodiment of the present application.

The following describes a process of determining an oil gas pipeline lifting amount according to an embodiment of the present application by taking an example that an army wire length-remaining plateau section goaf pipeline passes through a coal mine goaf subsidence area, referring to fig. 4, the method includes:

401. and the terminal acquires the pipeline parameters of the An Yongxian sub-long-residual apron segment goaf pipeline.

The pipe steel of the An Yongxian long-residual apron goaf pipe is L450, the pipe outer diameter is 323.9mm, the pipe wall thickness is 6mm, the design pressure in the pipe is 4MPa, the pipe operation and installation temperature difference is 20 ℃, the pipe top burial depth is 1.0m, and the pipe parameters can be seen in Table 1.

TABLE 1

402. The terminal determines a maximum strain gauge model matching the pipe steel type from a plurality of maximum strain gauge models based on the pipe steel type.

The terminal may determine a maximum strain gauge model that matches L450 from a plurality of maximum strain gauge models.

403. The terminal can acquire soil parameters of the soil of the goaf of the AnYong line length-residual apron section.

For example, the soil body is medium density sand soil, the cohesive force c=0 of the soil body, and the effective gravity gamma' =18 kN/m of the soil body ³ Effective internal friction angle of soil bodyCoefficient of friction tan delta=0.6 between pipe and soil, axial soil spring T _u =5.66 kN/m, vertical earth up spring Q _u = 116.53kN/m, vertical earth spring Q _d ＝1420.55kN/m。

404. The terminal can determine the reference lifting amount according to the goaf parameters of the An Yongxian child long-residual apron goaf.

For example, at one location of the goaf, the terminal calculates the current depth of the oil and gas pipeline to be 3m according to the goaf parameters, and the initial design depth of the oil and gas pipeline, that is, the top of the pipe burial depth is 1m, then the terminal may determine the reference lifting amount to be 3m-1 m=2m. An example of goaf parameters for one goaf of An Yongxian child-metapad segments can be seen in table 2.

TABLE 2

405. And the terminal calls a maximum strain quantity model, and inputs the pipeline parameters, the reference lifting quantity and the soil parameters of the goaf soil into the maximum strain quantity model for prediction to obtain the maximum strain quantity of the An Yongxian-child long-residual plateau goaf pipeline under the reference lifting quantity.

And substituting the parameters into a maximum strain quantity model corresponding to the L450 by the terminal to obtain the maximum compressive strain quantity of the L450 pipeline under the lifting action, wherein the result is shown in the table 3.

TABLE 3 Table 3

Maximum strain	Maximum strain without internal pressure (%)	Design pressure maximum Strain (%)
			Numerical value	0.46	0.87

406. The terminal compares the maximum strain amount with the allowed strain amount, and in response to the maximum strain amount being less than the allowed strain amount, step 407 is performed; in response to the maximum strain amount being greater than the allowable strain amount, step 408 is performed.

407. If the maximum strain amount is less than the allowable strain amount, the terminal determines the reference lift amount as the target lift amount.

If the allowable strain amount of the non-internal pressure of the L450 is 0.55% and the maximum strain amount of the design pressure is 0.95%, the terminal needs to determine the reference lift amount as the target lift amount.

408. If the maximum strain amount is greater than the allowable strain amount, the terminal updates the reference lifting amount, and executes the processes of predicting the maximum strain amount and comparing the maximum strain amount and the allowable strain amount based on the updated reference lifting amount and the pipeline parameters.

If the allowable strain amount for the no internal pressure of L450 is 0.35% and the maximum strain amount for the design pressure is 0.75%, then the terminal needs to reduce the reference lift amount, and steps 405 and 406 are re-performed until the maximum strain amount for the no internal pressure is less than 0.35% and the maximum strain amount for the design pressure is less than 0.75%.

Fig. 5 is a schematic structural diagram of a device for determining an amount of lifting of an oil and gas pipeline according to an embodiment of the present application, referring to fig. 5, the device includes: a parameter acquisition module 501, a model determination module 502, a prediction module 503, and a lift determination module 504.

The parameter obtaining module 501 is configured to obtain a pipeline parameter of a target oil and gas pipeline, where the target oil and gas pipeline is an oil and gas pipeline located in a goaf.

The model determining module 502 is configured to determine, according to a pipe steel type to which the target oil and gas pipe belongs, a target strain amount model matched with the pipe steel type from a plurality of maximum strain amount models.

The prediction module 503 is configured to invoke the target strain capacity model, input the pipeline parameter of the target oil and gas pipeline, the reference lifting capacity, and the soil parameter of the goaf soil into the target strain capacity model, and predict the target oil and gas pipeline to obtain the maximum strain capacity of the target oil and gas pipeline under the reference lifting capacity.

The lifting amount determining module 504 is configured to compare the maximum strain amount with the allowable strain amount of the target oil and gas pipeline, and determine the reference lifting amount as the target lifting amount if the maximum strain amount is smaller than the allowable strain amount.

In one possible embodiment, the apparatus further comprises:

In one possible implementation manner, the prediction module is used for calling the first relation data, inputting the pipeline parameters of the target oil and gas pipeline, the reference lifting amount and the soil body parameters of the goaf soil body into the first relation data, and obtaining the maximum strain amount of the target oil and gas pipeline under the reference lifting amount.

Relationship data one:

and epsilon is the maximum strain of the target oil and gas pipeline, and A is the lifting displacement of the target oil and gas pipeline. And B is the wall thickness of the target oil and gas pipeline. C is the outer diameter of the target oil and gas pipeline. D is the internal pressure of the target oil and gas pipeline. E is the temperature difference between the operating temperature and the installation temperature of the target oil and gas pipeline. Lambda is the model deviation. η (eta) ₁ ,η ₂ ,…η ₁₀ And m, n are coefficients determined based on different pipe steel types. T (T) _u Is an axial soil spring of soil body. Q (Q) _u Is a vertical upward soil spring of soil body. Q (Q) _d Is a vertical downward soil spring of soil body.

Wherein,

wherein: h is the distance from the surface of the earth to the center of the target oil and gas pipeline; k (K) ₀ Is the lateral pressure coefficient of the soil body; alpha is the cohesive force coefficient of the soil body; c is the cohesive force of the soil body; gamma' is the effective weight of the soil body; tan delta is the friction coefficient of the soil body and the target oil and gas pipeline; i is the surface gradient;is the effective internal friction angle of the soil body; n (N) _c 、N _q 、N _γ Is the cohesive force bearing capacity coefficient of the soil body; gamma is the total volume weight of the soil body.

In one possible embodiment, the reference lift is less than or equal to the maximum lift, the apparatus further comprising:

Relationship data two:

Wherein,

/>

In one possible embodiment, the training device for the maximum strain amount model includes:

and the construction module is used for constructing a finite element model corresponding to the sample oil gas pipeline according to the material parameters of the sample steel type and the pipeline parameters of the sample oil gas pipeline.

The maximum strain quantity acquisition module is used for placing the finite element model in the virtual goaf, applying a virtual lifting effect on the finite element model in the virtual goaf, and acquiring the maximum virtual strain quantity of the finite element model at a plurality of lifting heights, wherein the soil parameters of the virtual soil body of the virtual goaf are the same as those of the soil body of the goaf.

The training module is used for training the maximum strain model according to the pipeline parameters, the soil parameters of the virtual soil of the virtual goaf, the lifting height and the maximum virtual strain.

In one possible implementation, the training module is configured to construct an initial maximum strain model according to a relationship between the maximum virtual strain and the pipeline parameters, the soil parameters of the virtual soil of the virtual goaf, and the lifting height. And adjusting model parameters of the initial maximum strain model according to the lifting heights and the maximum virtual strain corresponding to the lifting heights, and taking the initial maximum strain model meeting the target iteration condition as the maximum strain model.

In one possible embodiment, the apparatus further comprises:

the adjusting module is used for inputting the lifting height into the maximum strain quantity model, and predicting the lifting height according to the maximum strain quantity model to obtain the predicted maximum strain quantity corresponding to the lifting height. And adjusting model parameters of the maximum strain model according to difference information between the maximum virtual strain corresponding to the lifting height and the predicted maximum strain.

It should be noted that: when the device for determining the lifting amount of the oil and gas pipeline provided by the embodiment is used for determining the lifting amount of the oil and gas pipeline, only the division of the functional modules is used for illustration, in practical application, the function allocation can be completed by different functional modules according to needs, namely, the internal structure of the terminal is divided into different functional modules so as to complete all or part of the functions described above. In addition, the device for determining the lifting amount of the oil and gas pipeline provided in the foregoing embodiment belongs to the same concept as the embodiment of the method for determining the lifting amount of the oil and gas pipeline, and the detailed implementation process of the device is described in the embodiment of the method for determining the lifting amount of the oil and gas pipeline, which is not described herein again.

In the embodiment of the present application, the computer device may be implemented as a terminal, and first, a structure of the terminal is described: referring to fig. 6, fig. 6 illustrates a schematic structure of a terminal 600 according to an exemplary embodiment of the present application.

In general, the terminal 600 includes: a processor 601 and a memory 602.

Processor 601 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 601 may be implemented in at least one hardware form of DSP (Digital Signal Processing ), FPGA (Field-Programmable Gate Array, field programmable gate array), PLA (Programmable Logic Array ). The processor 601 may also include a main processor, which is a processor for processing data in an awake state, also called a CPU (Central Processing Unit ), and a coprocessor; a coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 601 may integrate a GPU (Graphics Processing Unit, image processing interactor) for rendering and rendering of content required to be displayed by the display screen. In some embodiments, the processor 601 may also include an AI (Artificial Intelligence ) processor for processing computing operations related to machine learning.

The memory 602 may include one or more computer-readable storage media, which may be non-transitory. The memory 602 may also include high-speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory computer readable storage medium in memory 602 is used to store at least one instruction for a determination method of lift amount of a hydrocarbon pipeline provided by a method embodiment in the present application that is possessed by processor 601.

In some embodiments, the terminal 600 may further optionally include: a peripheral interface 603, and at least one peripheral. The processor 601, memory 602, and peripheral interface 603 may be connected by a bus or signal line. The individual peripheral devices may be connected to the peripheral device interface 603 via buses, signal lines or a circuit board. Specifically, the peripheral device includes: at least one of radio frequency circuitry 604, a touch display 605, a camera 606, audio circuitry 607, a positioning component 608, and a power supply 609.

Peripheral interface 603 may be used to connect at least one Input/Output (I/O) related peripheral to processor 601 and memory 602. In some embodiments, the processor 601, memory 602, and peripheral interface 603 are integrated on the same chip or circuit board; in some other embodiments, either or both of the processor 601, memory 602, and peripheral interface 603 may be implemented on separate chips or circuit boards, which is not limited in this embodiment.

The Radio Frequency circuit 604 is configured to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 604 communicates with a communication network and other communication devices via electromagnetic signals. The radio frequency circuit 604 converts an electrical signal into an electromagnetic signal for transmission, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 604 includes: antenna systems, RF transceivers, one or more amplifiers, tuners, oscillators, digital signal processors, codec chipsets, subscriber identity module cards, and so forth. The radio frequency circuit 604 may communicate with other terminals via at least one wireless communication protocol. The wireless communication protocol includes, but is not limited to: metropolitan area networks, various generations of mobile communication networks (2G, 3G, 4G, and 8G), wireless local area networks, and/or WiFi (Wireless Fidelity ) networks. In some embodiments, the radio frequency circuitry 604 may also include NFC (Near Field Communication, short range wireless communication) related circuitry, which is not limited in this application.

The display screen 605 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display 605 is a touch display, the display 605 also has the ability to collect touch signals at or above the surface of the display 605. The touch signal may be input as a control signal to the processor 601 for processing. At this point, the display 605 may also be used to provide virtual buttons and/or virtual keyboards, also referred to as soft buttons and/or soft keyboards. In some embodiments, the display 605 may be one, providing a front panel of the terminal 600; in other embodiments, the display 605 may be at least two, respectively disposed on different surfaces of the terminal 600 or in a folded design; in still other embodiments, the display 605 may be a flexible display, disposed on a curved surface or a folded surface of the terminal 600. Even more, the display 605 may be arranged in a non-rectangular irregular pattern, i.e., a shaped screen. The display 605 may be made of LCD (Liquid Crystal Display ), OLED (Organic Light-Emitting Diode) or other materials.

The camera assembly 606 is used to capture images or video. Optionally, the camera assembly 606 includes a front camera and a rear camera. Typically, a front camera is provided at a front panel of the terminal 600, and a rear camera is provided at a rear surface of the terminal 600. In some embodiments, the at least two rear cameras are any one of a main camera, a depth camera, a wide-angle camera and a tele camera, so as to realize that the main camera and the depth camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize a panoramic shooting and Virtual Reality (VR) shooting function or other fusion shooting functions. In some embodiments, camera assembly 606 may also include a flash. The flash lamp can be a single-color temperature flash lamp or a double-color temperature flash lamp. The dual-color temperature flash lamp refers to a combination of a warm light flash lamp and a cold light flash lamp, and can be used for light compensation under different color temperatures.

The audio circuit 607 may include a microphone and a speaker. The microphone is used for collecting sound waves of users and environments, converting the sound waves into electric signals, and inputting the electric signals to the processor 601 for processing, or inputting the electric signals to the radio frequency circuit 604 for voice communication. For the purpose of stereo acquisition or noise reduction, a plurality of microphones may be respectively disposed at different portions of the terminal 600. The microphone may also be an array microphone or an omni-directional pickup microphone. The speaker is used to convert electrical signals from the processor 601 or the radio frequency circuit 604 into sound waves. The speaker may be a conventional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, not only the electric signal can be converted into a sound wave audible to humans, but also the electric signal can be converted into a sound wave inaudible to humans for ranging and other purposes. In some embodiments, the audio circuit 607 may also include a headphone jack.

The location component 608 is used to locate the current geographic location of the terminal 600 to enable navigation or LBS (Location Based Service, location based services). The positioning component 608 may be a positioning component based on the United states GPS (Global Positioning System ), the Beidou system of China, the Granati system of Russia, or the Galileo system of the European Union.

A power supply 609 is used to power the various components in the terminal 600. The power source 609 may be alternating current, direct current, disposable battery or rechargeable battery. When the power source 609 includes a rechargeable battery, the rechargeable battery may support wired or wireless charging. The rechargeable battery may also be used to support fast charge technology.

In some embodiments, the terminal 600 further includes one or more sensors 610. The one or more sensors 610 include, but are not limited to: acceleration sensor 611, gyroscope sensor 612, pressure sensor 613, fingerprint sensor 614, optical sensor 615, and proximity sensor 616.

The acceleration sensor 611 can detect the magnitudes of accelerations on three coordinate axes of the coordinate system established with the terminal 600. For example, the acceleration sensor 611 may be used to detect components of gravitational acceleration in three coordinate axes. The processor 601 may control the touch display screen 605 to display a user interface in a landscape view or a portrait view according to the gravitational acceleration signal acquired by the acceleration sensor 611. The acceleration sensor 611 may also be used for the acquisition of motion data of an application or user.

The gyro sensor 612 may detect a body direction and a rotation angle of the terminal 600, and the gyro sensor 612 may collect a 3D motion of the user on the terminal 600 in cooperation with the acceleration sensor 611. The processor 601 may implement the following functions based on the data collected by the gyro sensor 612: motion sensing (e.g., changing UI according to a tilting operation by a user), image stabilization at shooting, application control, and inertial navigation.

The pressure sensor 613 may be disposed at a side frame of the terminal 600 and/or at a lower layer of the touch screen 605. When the pressure sensor 613 is disposed at a side frame of the terminal 600, a grip signal of the terminal 600 by a user may be detected, and a left-right hand recognition or a shortcut operation may be performed by the processor 601 according to the grip signal collected by the pressure sensor 613. When the pressure sensor 613 is disposed at the lower layer of the touch display screen 605, the processor 601 controls the operability control on the UI interface according to the pressure operation of the user on the touch display screen 605. The operability controls include at least one of a button control, a scroll bar control, an icon control, and a menu control.

The fingerprint sensor 614 is used to collect a fingerprint of a user, and the processor 601 identifies the identity of the user based on the fingerprint collected by the fingerprint sensor 1414, or the fingerprint sensor 614 identifies the identity of the user based on the collected fingerprint. Upon recognizing that the user's identity is a trusted identity, the user is authorized by the processor 601 to have associated sensitive operations including unlocking the screen, viewing encrypted information, downloading software, paying for and changing settings, etc. The fingerprint sensor 614 may be provided on the front, back, or side of the terminal 600. When a physical key or vendor Logo is provided on the terminal 600, the fingerprint sensor 614 may be integrated with the physical key or vendor Logo.

The optical sensor 615 is used to collect ambient light intensity. In one embodiment, processor 601 may control the display brightness of touch display 605 based on the intensity of ambient light collected by optical sensor 615. Specifically, when the intensity of the ambient light is high, the display brightness of the touch display screen 605 is turned up; when the ambient light intensity is low, the display brightness of the touch display screen 605 is turned down. In another embodiment, the processor 601 may also dynamically adjust the shooting parameters of the camera assembly 606 based on the ambient light intensity collected by the optical sensor 615.

A proximity sensor 616, also referred to as a distance sensor, is typically provided on the front panel of the terminal 600. The proximity sensor 616 is used to collect the distance between the user and the front of the terminal 600. In one embodiment, when the proximity sensor 616 detects a gradual decrease in the distance between the user and the front face of the terminal 600, the processor 601 controls the touch display 605 to switch from the bright screen state to the off screen state; when the proximity sensor 616 detects that the distance between the user and the front surface of the terminal 600 gradually increases, the processor 601 controls the touch display screen 605 to switch from the off-screen state to the on-screen state.

Those skilled in the art will appreciate that the structure shown in fig. 6 is not limiting of the terminal 600 and may include more or fewer components than shown, or may combine certain components, or may employ a different arrangement of components.

In the embodiment of the present application, the computer device may be implemented as a server, and first, a structure of the server is described: referring to fig. 7, fig. 7 is a schematic structural diagram of a server provided in the embodiments of the present application, where the server 700 may have a relatively large difference due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) 701 and one or more memories 702, where at least one instruction is stored in the memories 702, and the at least one instruction is loaded and executed by the processors 701 to implement the methods provided in the above-mentioned method embodiments. Of course, the server may also have a wired or wireless network interface, a keyboard, an input/output interface, and other components for implementing the functions of the device, which are not described herein.

In an exemplary embodiment, a computer readable storage medium is also provided, for example a memory comprising at least one program code executable by a processor in a terminal to perform the methods provided by the various method embodiments described above. For example, the computer readable storage medium may be a ROM (Read-Only Memory), a RAM (Random-Access Memory), a CD-ROM (Compact Disc Read-Only Memory), a magnetic tape, a floppy disk, an optical data storage device, and the like.

It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program for instructing relevant hardware, where the program may be stored in a computer readable storage medium, and the above storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.

The foregoing description of the preferred embodiments of the present application is not intended to limit the invention to the particular embodiments of the present application, but to limit the scope of the invention to the particular embodiments of the present application.

Claims

1. A method of determining the lift of an oil and gas pipeline, comprising:

Comparing the maximum strain amount with the allowable strain amount of the target oil and gas pipeline, and determining the reference lifting amount as a target lifting amount if the maximum strain amount is smaller than the allowable strain amount;

the step of calling the maximum strain amount model, inputting the pipeline parameters of the target oil and gas pipeline, the reference lifting amount and the soil parameters of the goaf soil into the maximum strain amount model for prediction, and obtaining the maximum strain amount of the target oil and gas pipeline under the reference lifting amount comprises the following steps:

relationship data one:

wherein,

wherein: h is the distance from the surface of the earth to the center of the target oil and gas pipeline; k (K) ₀ Is saidSide pressure coefficient of soil mass; alpha is the cohesive force coefficient of the soil body; c is the cohesive force of the soil body; gamma ray ^‘ The effective weight of the soil body; tan delta is the friction coefficient of the soil body and the target oil and gas pipeline; i is the surface gradient;an effective internal friction angle for the soil body; n (N) _c 、N _q 、N _γ The viscosity-aggregation bearing capacity coefficient of the soil body; and gamma is the total volume weight of the soil body.

2. The method of claim 1, wherein after the comparing the maximum strain amount to the allowable strain amount for the target hydrocarbon conduit, the method further comprises:

3. The method of claim 1, wherein the reference lift is less than or equal to a maximum lift, the method of determining the maximum lift comprising:

relationship data two:

wherein epsilon is the maximum strain of the target oil and gas pipeline, and A is the lifting displacement of the target oil and gas pipeline; b is the wall thickness of the target oil and gas pipeline; c is the outer diameter of the target oil and gas pipeline; d is the internal pressure of the target oil and gas pipeline; e is the temperature difference between the operating temperature and the installation temperature of the target oil and gas pipeline; lambda is the model deviation；η ₁ ,η ₂ ,…η ₁₀ And m, n are coefficients determined based on different pipe steel types; t (T) _u An axial soil spring for the soil body; q (Q) _u A vertical upward soil spring for the soil body; q (Q) _d A vertical downward soil spring for the soil body;

wherein,

wherein: h is the distance from the surface of the earth to the center of the target oil and gas pipeline; k (K) ₀ A lateral pressure coefficient for the soil mass; alpha is the cohesive force coefficient of the soil body; c is the cohesive force of the soil body; gamma ray ^‘ The effective weight of the soil body; tan delta is the friction coefficient of the soil body and the target oil and gas pipeline; i is the surface gradient; An effective internal friction angle for the soil body; n (N) _c 、N _q 、N _γ The viscosity-aggregation bearing capacity coefficient of the soil body; and gamma is the total volume weight of the soil body.

4. The method of claim 1, wherein the training method of the maximum strain amount model comprises:

5. The method of claim 4, wherein the training the maximum strain amount model based on the pipe parameters, soil parameters of the virtual soil of the virtual goaf, the lift height, and the maximum virtual strain amount comprises:

6. The method of claim 5, wherein after said taking as said maximum strain amount model an initial maximum strain amount model that meets a target iteration condition, the method further comprises:

7. The device for determining the lifting amount of the oil and gas pipeline is characterized by comprising the following components:

the lifting amount determining module is used for comparing the maximum strain amount with the allowable strain amount of the target oil and gas pipeline, and determining the reference lifting amount as a target lifting amount if the maximum strain amount is smaller than the allowable strain amount;

relationship data one:

wherein epsilon is the maximum strain of the target oil and gas pipeline, and A is the lifting displacement of the target oil and gas pipeline; b is the wall thickness of the target oil and gas pipeline; c is the outer diameter of the target oil and gas pipeline; d is the internal pressure of the target oil and gas pipeline; e (E)A temperature difference between the target oil and gas pipeline operation temperature and the installation temperature; lambda is the model deviation; η (eta) ₁ ,η ₂ ,…η ₁₀ And m, n are coefficients determined based on different pipe steel types; t (T) _u An axial soil spring for the soil body; q (Q) _u A vertical upward soil spring for the soil body; q (Q) _d A vertical downward soil spring for the soil body;

wherein,

8. A computer device comprising a processor and a memory, wherein the memory has stored therein at least one program code that is loaded and executed by the processor to perform the operations performed in the method of determining the lift of an oil and gas pipeline as claimed in any one of claims 1 to 6.

9. A computer readable storage medium having stored therein at least one program code loaded and executed by a processor to perform the operations performed in the method of determining the lift of an oil and gas pipeline as claimed in any one of claims 1 to 6.