A comprehensive selection method for brackets used in marine oil and gas pipeline installation

Abstract

The present invention discloses a comprehensive method for selecting supports for installing marine oil and gas pipelines, comprising: calculating the distance from the nearest wall, the nearest ground, and the nearest ceiling to the location where the support is to be installed based on pipeline design engineering drawings; calculating the diameter of the pipeline where the support is to be installed; training a pipe support selection model for the marine oil and gas industry using an MLP neural network algorithm; obtaining pipe support selection results using the trained model in actual operations; and determining a pipe support size sequence that meets strength requirements based on the selection results. Compared to traditional methods, the present invention effectively improves the accuracy of pipe support selection, avoids possible selection errors that may occur in manual selection, simplifies the cumbersome manual pipe support selection method, and improves selection efficiency.

Description

Technical Field

[0001] The present invention relates to a method for selecting a pipe support, and in particular to a comprehensive method for selecting a support for installing an offshore oil and gas pipeline. Background Art

[0002] Offshore oil and gas pipelines are crucial transportation vehicles for the offshore oil and gas industry, and numerous of them are installed throughout oil and gas modules. The installation of offshore oil and gas pipelines requires the use of supports to ensure the pipelines can be positioned in various locations. Oil and gas pipelines are typically numerous and of varying lengths, and different installation environments require different types of pipe supports. Therefore, selecting different types of pipe supports for offshore oil and gas pipelines is a complex and cumbersome task. The current manual selection process for oil and gas pipeline supports is inefficient and cumbersome, resulting in an urgent need for an efficient and accurate method for selecting pipe supports in the offshore oil and gas industry. Summary of the Invention

[0003] The purpose of the present invention is to overcome the shortcomings of the existing technology and provide a comprehensive selection method for pipe supports in the marine oil and gas industry that can improve the speed of comprehensive selection of pipe supports, ensure the smooth installation process of pipelines in the marine oil and gas industry, adapt to complex operating environments, and have strong versatility.

[0004] A comprehensive method for selecting supports for installing marine oil and gas pipelines according to the present invention comprises the following steps:

[0005] Step 1: According to the pipeline design engineering drawing, calculate the distance between the pipeline support and the nearest wall surface, which is recorded as a. i , where i is the location where the pipeline support needs to be installed; if there is no wall around the location where the pipeline support is to be installed or the distance to the wall is greater than the set threshold A, then a i =0, otherwise a i =1;

[0006] Step 2: According to the pipeline design engineering drawing, calculate the distance between the pipeline support and the ground, which is recorded as b. i If the distance between the location of the pipeline support to be installed and the ground is greater than the set threshold B, then b i = 0, otherwise, b i =1;

[0007] Step 3: According to the pipeline design engineering drawing, calculate the distance between the place where the pipeline bracket needs to be installed and the nearest point of the ceiling, which is recorded as c i If the distance between the pipeline support to be installed and the ceiling is greater than the set threshold C or there is no ceiling, then c i =0, otherwise c i =1;

[0008] Step 4: According to the pipeline design engineering drawing, calculate the diameter of the pipeline where the pipeline support needs to be installed, and record it as d i , will (a i ,b i ,c i ,d i ) is recorded as the feature vector of the position where the pipeline support needs to be installed at the i-th location;

[0009] Step 5: Use the MLP neural network algorithm to train the pipe support selection model for the offshore oil and gas industry. The specific process is as follows:

[0010] In the first step, steps 1 to 4 are repeated multiple times to obtain a large number of feature vectors as a training set. At the same time, the pipeline support type that should be selected for each feature vector is manually determined;

[0011] The second step is to import the MPL neural network module in Python, extract any feature vector obtained in the first step and input it into the MPL neural network module, and output the pipeline support type selection result as data to obtain the pipeline support type selection result;

[0012] The third step is to determine whether the pipeline support type selection result matches the manual selection result. If the match fails, the algorithm returns to the second step and uses the MPL neural network algorithm to select the pipeline support type for the feature vector again. If the match succeeds, the algorithm returns to the second step to extract the next feature vector for identification. This process continues until all feature vectors are successfully identified, resulting in a pipeline support selection model for the offshore oil and gas industry.

[0013] Step 6: In actual operation, select an engineering drawing that requires pipe support selection, and go through steps 1 to 4 in sequence. Then, use Python to calculate the feature vector obtained in step 4 using the offshore oil and gas industry pipe support selection model obtained in step 5 to obtain the pipe support selection result.

[0014] Step 7: Based on the pipe support selection results in step 6, determine the pipe support size sequence that meets the strength requirements. The specific steps are as follows:

[0015] The first step is to select the smallest tube support size sequence;

[0016] The second step is to carry out ANSYS modeling of the pipe support according to the selected size series;

[0017] Step 3: Carry out ANSYS modeling of pipelines, walls, floors, and ceilings according to the engineering drawings, and import the pipe support model from step 2 to the corresponding position;

[0018] Step 4: Apply the actual working strength to the pipe support model in ANSYS and perform ANSYS strength simulation analysis to determine the relationship between the actual working strength and the yield strength of the pipeline support material. If P≤P f / n, indicating that the pipe support model has yielded and deformed, then a larger size sequence should be selected and the model should be re-modeled in the second step; if P>P f / n, it is determined that the size sequence at this time is the required pipe support size sequence, and the next step is executed;

[0019] Where: P—actual working strength of pipeline support; P f —yield strength of pipeline support material; n—safety factor;

[0020] Step 8: Output the pipe support size sequence determined in step 7 as the support structure at the relevant position.

[0021] The beneficial effects of the present invention are: effectively improving the accuracy of pipe support selection, avoiding selection errors that may occur in manual selection, simplifying the cumbersome manual pipe support selection method, improving selection efficiency, shortening working time, and saving labor costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The present invention is a flow chart of a comprehensive selection method for supports for installing marine oil and gas pipelines. DETAILED DESCRIPTION

[0023] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] like Figure 1 The comprehensive selection method for a bracket for installing a marine oil and gas pipeline of the present invention comprises the following steps:

[0025] Step 1: According to the pipeline design engineering drawing, calculate the distance between the pipeline support and the nearest wall surface, which is recorded as a. i , where i is the location where the pipeline support needs to be installed. If there is no wall around the location where the pipeline support is to be installed or the distance to the wall is greater than the set threshold A, then a i =0, otherwise a i =1, the principle for setting the threshold A is usually equal to twice the pipeline diameter.

[0026] Step 2: According to the pipeline design engineering drawing, calculate the distance between the pipeline support and the ground, which is recorded as b. i If the distance between the location of the pipeline support to be installed and the ground is greater than the set threshold B, then b i = 0, otherwise, b i=1, the principle for setting threshold B is usually equal to one times the pipeline diameter.

[0027] Step 3: According to the pipeline design engineering drawing, calculate the distance between the place where the pipeline bracket needs to be installed and the nearest point of the ceiling, which is recorded as c i If the distance between the pipeline support to be installed and the ceiling is greater than the set threshold C or there is no ceiling, then c i =0, otherwise c i =1, the principle for setting the threshold C is usually equal to twice the pipeline diameter.

[0028] Step 4: According to the pipeline design engineering drawing, calculate the diameter of the pipeline where the pipeline support needs to be installed, and record it as d i . Will (a i ,b i ,c i ,d i ) is recorded as the feature vector of the position where the pipeline support needs to be installed at the i-th location.

[0029] Step 5: Use the MLP neural network algorithm to train the pipe support selection model for the offshore oil and gas industry. The specific process is as follows:

[0030] In the first step, steps 1 to 4 are repeated multiple times to obtain a large number of feature vectors as training sets, and the pipeline support type that should be selected for each feature vector is manually determined.

[0031] The second step is to import the MPL neural network module in Python, extract any feature vector obtained in the first step and input it into the MPL neural network module, and output the pipeline support type selection result as data to obtain the pipeline support type selection result;

[0032] The third step is to determine whether the pipeline support type selection result matches the manual selection result. If the match fails, the algorithm returns to the second step and uses the MPL neural network algorithm to select the pipeline support type for the feature vector. If the match succeeds, the algorithm returns to the second step to extract the next feature vector for identification. This continues until all feature vectors are successfully identified, resulting in a pipeline support selection model for the offshore oil and gas industry.

[0033] Step 6. In actual operation, select an engineering drawing that requires pipe support selection, go through steps 1 to 4 in sequence, and then use Python to calculate the feature vector obtained in step 4 using the offshore oil and gas industry pipe support selection model obtained in step 5 to obtain the pipe support selection result.

[0034] Step 7: Based on the pipe support selection results in step 6, determine the pipe support size sequence that meets the strength requirements. The specific steps are as follows:

[0035] The first step is to select the smallest tube support size sequence;

[0036] The second step is to carry out ANSYS modeling of the pipe support according to the selected size series;

[0037] Step 3: Carry out ANSYS modeling of pipelines, walls, floors, and ceilings according to the engineering drawings, and import the pipe support model from step 2 to the corresponding position;

[0038] Step 4: Apply the actual working strength P to the pipe support model to determine the yield strength P of the pipeline support material under the actual working strength P. f The relationship is judged as follows:

[0039] P≤P f / n

[0040] Where: P—actual working strength of pipeline support;

[0041] P f —Yield strength of pipeline support material;

[0042] n—Safety factor.

[0043] P in the above formula f is the yield strength of the pipeline support material, which can be determined by the Handbook of Mechanical Properties of Metal Materials published by the Machinery Industry Press on January 1, 2011. The value of n can be determined by consulting the API specifications based on the typhoon level and sea state level.

[0044] Step 5: Perform ANSYS strength simulation analysis to verify whether the pipe support model has yielded. If so, select the next larger size sequence and return to step 2 to re-model. If no deformation occurs, the size sequence at this point is determined to be the required pipe support size sequence.

[0045] Step 8: Output the pipe support size sequence determined in step 7 as the support structure at the relevant position.

Claims

1. A comprehensive selection method for brackets for installing marine oil and gas pipelines, characterized in that The following steps are involved: Step 1: According to the pipeline design engineering drawing, calculate the distance between the pipeline support and the nearest wall surface, which is recorded as a. i , where i is the location where the pipeline support needs to be installed; if there is no wall around the location where the pipeline support is to be installed or the distance to the wall is greater than the set threshold A, then a i =0, otherwise a i =1; Step 2: According to the pipeline design engineering drawing, calculate the distance between the pipeline support and the ground, which is recorded as b. i If the distance between the location of the pipeline support to be installed and the ground is greater than the set threshold B, then b i = 0, otherwise, b i =1; Step 3: According to the pipeline design engineering drawing, calculate the distance between the place where the pipeline bracket needs to be installed and the nearest point of the ceiling, which is recorded as c i If the distance between the pipeline support to be installed and the ceiling is greater than the set threshold C or there is no ceiling, then c i =0, otherwise c i =1; Step 4: According to the pipeline design engineering drawing, calculate the diameter of the pipeline where the pipeline support needs to be installed, and record it as d i , will (a i ,b i ,c i ,d i ) is recorded as the feature vector of the position where the pipeline support needs to be installed at the i-th location; Step 5: Use the MLP neural network algorithm to train the pipe support selection model for the offshore oil and gas industry. The specific process is as follows: In the first step, steps 1 to 4 are repeated multiple times to obtain a large number of feature vectors as a training set. At the same time, the pipeline support type that should be selected for each feature vector is manually determined; The second step is to import the MPL neural network module in Python, extract any feature vector obtained in the first step and input it into the MPL neural network module, and output the pipeline support type selection result as data to obtain the pipeline support type selection result; The third step is to determine whether the pipeline support type selection result matches the manual selection result. If the match fails, the algorithm returns to the second step and uses the MPL neural network algorithm to select the pipeline support type for the feature vector again. If the match succeeds, the algorithm returns to the second step to extract the next feature vector for identification. This process continues until all feature vectors are successfully identified, resulting in a pipeline support selection model for the offshore oil and gas industry. Step 6: In actual operation, select an engineering drawing that requires pipe support selection, and go through steps 1 to 4 in sequence. Then, use Python to calculate the feature vector obtained in step 4 using the offshore oil and gas industry pipe support selection model obtained in step 5 to obtain the pipe support selection result. Step 7: Based on the pipe support selection results in step 6, determine the pipe support size sequence that meets the strength requirements. The specific steps are as follows: The first step is to select the smallest tube support size sequence; The second step is to carry out ANSYS modeling of the pipe support according to the selected size series; Step 3: Carry out ANSYS modeling of pipelines, walls, floors, and ceilings according to the engineering drawings, and import the pipe support model from step 2 to the corresponding position; Step 4: Apply the actual working strength to the pipe support model in ANSYS and perform ANSYS strength simulation analysis to determine the relationship between the actual working strength and the yield strength of the pipeline support material. If P≤P f / n, indicating that the pipe support model has yielded and deformed, then a larger size sequence should be selected and the model should be re-modeled in the second step; if P>P f / n, it is determined that the size sequence at this time is the required pipe support size sequence, and the next step is executed; Where: P—actual working strength of pipeline support; P f —yield strength of pipeline support material; n—safety factor; Step 8: Output the pipe support size sequence determined in step 7 as the support structure at the relevant position.

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