Gas tracking calculation method for oil-gas pipe network
By establishing a tracking calculation model for associated gas and humid natural gas in the oil and gas pipeline network, and using the Gaussian model and partial differential equation model for calculation, the problem of flowmeter accuracy reduction caused by the difference in methane content of natural gas is solved, and the gas tracking calculation is improved Accuracy and accuracy.
Patent Information
- Application Number
- CN202411273682.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-12
- Publication Date
- 2025-02-14
AI Technical Summary
The difference in methane content of natural gas in the oil and gas pipeline network leads to a decrease in the accuracy of the flowmeter, affecting the density and specific heat capacity of the natural gas, thereby reducing the accuracy of gas tracking calculations.
The tracking calculation model established for associated gas and moisture natural gas is adopted, and the Gaussian model and partial differential equation model are used for calculation, and the input parameters are determined through feature index screening and statistical analysis to improve the calculation accuracy.
It improves the accuracy and accuracy of gas tracking calculations, reduces calculation errors, and enhances the monitoring ability of natural gas flow direction and flow in the oil and gas pipeline network.
Smart Images
Figure CN119446338A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of gas tracking, and in particular to a gas tracking calculation method for an oil and gas pipeline network. Background Art
[0002] The oil and gas pipeline network refers to the infrastructure network composed of crude oil, refined oil, natural gas transmission pipelines and related storage facilities, port loading and unloading facilities, etc.; the natural gas of the oil and gas pipeline network comes from various sources, mainly including natural gas fields, coalbed methane, mud volcano gas, and biogenic gas. The above natural gas needs to be purified before it can be transported to each household through the oil and gas pipeline network. Among them, the methane content in the natural gas mined from different strata in the natural gas fields has a certain difference, and the above natural gas needs to be purified before it can be transported to meet the transportation standards. The natural gas transported to the oil and gas pipeline network includes wet natural gas and associated natural gas according to the different methane content. The oil and gas pipeline network needs to effectively monitor multiple indicators of natural gas extraction, such as flow rate, flow direction, temperature, density, specific heat capacity, etc. Different methane contents will affect the accuracy of the flowmeter, resulting in inaccurate flow measurement, and will also affect the density and specific heat capacity of the natural gas, thereby affecting the flow direction and flow of the natural gas, resulting in reduced accuracy of tracking calculations, errors in calculations, and reduced calculation accuracy. Summary of the invention
[0003] In view of the deficiencies in the prior art, an object of the present invention is to provide a gas tracking calculation method for an oil and gas pipeline network.
[0004] In order to achieve the above object, the present invention provides the following technical solutions: A gas tracking calculation method for an oil and gas pipeline network specifically comprises the following steps: Step S1, collecting oil and gas pipeline network data set; Step S2, preprocessing the oil and gas pipeline network data set to obtain input data; Step S3, creating a tracking calculation model; Step S4, inputting the input data into the tracking calculation model to obtain the tracking calculation result; The tracking calculation model includes a first tracking calculation model and a second tracking calculation model. The first tracking calculation model is used to perform tracking calculation on associated gas, and the second tracking calculation model is used to perform tracking calculation on wet gas.
[0005] Furthermore, in step S2, the oil and gas pipeline network data set is preprocessed, specifically including the following steps: Step S2.1, filter out unqualified data in the oil and gas pipeline network data set and delete them; Step S2.2, select data related to natural gas and delete irrelevant and redundant data.
[0006] Furthermore, the oil and gas pipeline network data set preprocessed in step S2 includes an oil and gas pipeline data set and a natural gas data set.
[0007] Furthermore, the natural gas dataset includes a first natural gas dataset and a second natural gas dataset, the first natural gas dataset is a preprocessed associated gas natural gas dataset, and the second natural gas dataset is a preprocessed wet gas natural gas dataset.
[0008] Furthermore, the acquisition of input data specifically includes the following steps: Step S21, performing statistical processing on the first natural gas data set, the second natural gas data set, and the oil and gas pipeline data set; Step S22, arranging the correlations between the first natural gas dataset, the second natural gas dataset and the oil and gas pipeline dataset from high to low, and obtaining the influencing features of the wet gas natural gas dataset and the associated gas natural gas dataset; Step S23: taking the influencing features of the wet gas natural gas dataset and the associated gas natural gas dataset as input data.
[0009] Furthermore, in step S22, the number of influencing features of the associated gas natural gas data set is 4, and the number of influencing features of the wet gas natural gas data set is 7.
[0010] Furthermore, the first tracking calculation model is a Gaussian model, and the second tracking calculation model is a partial differential equation model.
[0011] Furthermore, the four influencing characteristics of the associated gas data set are: methane content, natural gas emission rate, diffusion coefficient of natural gas in the oil and gas pipeline network, and wind speed of natural gas in the oil and gas pipeline network.
[0012] Furthermore, the seven influencing features of the wet natural gas dataset are: methane content, ethane content, propane content, n-butane content, n-pentane content, natural gas concentration, and natural gas transportation time.
[0013] Furthermore, the calculation formula of the Gaussian model is: Where K is the natural gas distribution index, Q is the natural gas emission rate, and k is the natural gas emission coefficient, which is related to the methane content. is the diffusion coefficient of natural gas in the oil and gas pipeline network, x is the wind direction coordinate, x0 is the coordinate of natural gas at the node of the oil and gas pipeline network, and v is the wind speed of natural gas in the oil and gas pipeline network; The calculation formula of the partial differential equation model is: Where C is the natural gas concentration, t is the natural gas transportation time, c1 is the methane content, c2 is the ethane content, c3 is the propane content, c4 is the butane content, c5 is the n-pentane content, x is the spatial coordinate system, and D is the coefficient.
[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention establishes a first tracking calculation model and a second tracking calculation model according to two types of gases, associated natural gas and wet natural gas, respectively. Based on the characteristic indicators of associated natural gas and wet natural gas, different tracking calculation models are used for calculation, which improves the calculation precision, reduces the calculation error, and improves the calculation accuracy.
[0015] 2. When the present invention performs tracking calculations on associated gas, the Gaussian model is selected for calculation. In terms of input model parameters, four parameters are selected as input through statistical analysis. In the tracking calculation process of wet gas, the partial differential equation model is selected for calculation. In terms of input model parameters, seven parameters are selected as input through statistical analysis, thus taking into account both accuracy and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] Figure 1 A flow chart of a gas tracking calculation method for an oil and gas pipeline network provided in Example 1 of the present invention; Figure 2 A flowchart of preprocessing in a gas tracking calculation method for an oil and gas pipeline network provided in Example 1 of the present invention; Figure 3 A flowchart of obtaining input data in a gas tracking calculation method for an oil and gas pipeline network provided in Example 1 of the present invention; Figure 4 A structural diagram of a gas tracking calculation system for an oil and gas pipeline network provided by 1 in Example 2 of the present invention. DETAILED DESCRIPTION
[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0018] It should be noted that when a component is referred to as being "fixed to" another component, it may be directly on the other component or there may also be a component centered. When a component is considered to be "connected to" another component, it may be directly connected to the other component or there may also be a component centered. When a component is considered to be "set on" another component, it may be directly set on the other component or there may also be a component centered. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.
[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.
[0020] Embodiment 1, Figure 1 This is a flow chart of a gas tracking calculation method for an oil and gas pipeline network provided in Example 1 of the present invention. Figure 1 The present invention provides a gas tracking calculation method for an oil and gas pipeline network, which specifically includes the following steps: Step S1, collecting oil and gas pipeline network data set; The oil and gas pipeline network data set includes oil and gas pipeline data (such as pipeline diameter, pipeline length, pipeline pressure, pipeline temperature, pipeline flow, transmission speed, node information, etc.) and natural gas data (such as concentration, transmission time, gas components and content); the above information is collected at different locations and different time periods of the oil and gas pipeline network through sensors or oil and gas production management systems to obtain representative data.
[0021] Step S2, preprocessing the sample data set to obtain input data; Figure 2 This is a flow chart of preprocessing in a gas tracking calculation method for an oil and gas pipeline network provided in Example 1 of the present invention. Figure 2 , specifically including the following steps: Step S2.1, filter out unqualified samples in the oil and gas pipeline network data set and delete them; Unqualified samples include but are not limited to: outliers, missing values, and erroneous data; In this embodiment, in order to achieve the accuracy of natural gas tracking calculation, the parameters input into the tracking calculation model need to ensure the accuracy of the calculation results. For this purpose, unqualified data need to be deleted. Specifically, unqualified data includes incomplete or abnormal data. To ensure the consistency and accuracy of the data, this part of the data will be deleted; Step S2.2, selecting data related to natural gas and deleting irrelevant and redundant data; This embodiment tracks the gas in the oil and gas pipeline network. In addition to fluids, the gas in the oil and gas pipeline network is mainly natural gas. This embodiment takes natural gas as the research object. Relevant data refers to information that is directly related to the flow, properties, detection, and management of natural gas, which helps to understand the state, behavior, and performance of natural gas in the oil and gas pipeline network. Relevant data includes but is not limited to: flow, pressure, gas composition, gas operation data, temperature, humidity, location information, and equipment status information; irrelevant data refers to information that is irrelevant to the flow, detection, and management of natural gas in the oil and gas pipeline network, which is of no substantial help in analyzing the behavior or state of natural gas and may even increase the complexity of data processing. Irrelevant data includes but is not limited to: data related to oil or other fluids, historical documents unrelated to pipeline construction or maintenance, employee personal information or administrative data, and non-real-time historical data; redundant data refers to information that is repeatedly provided or replaced by other data. In this regard, data that is irrelevant or redundant to natural gas is screened out from the oil and gas pipeline network data set and deleted to reduce data dimension and complexity; Furthermore, after the processing from step S2.1 to step S2.2, it can be ensured that the screened data sets are all relatively accurate data sets; The oil and gas pipeline network data set preprocessed from step S2.1 to step S2.2 includes an oil and gas pipeline data set and a natural gas data set, the natural gas data set includes a first natural gas data set and a second natural gas data set, the first natural gas data set is an associated gas natural gas data set consisting of natural gas data with a methane content of less than 80%, and the second natural gas data set is a wet gas natural gas data set consisting of natural gas data with a methane content between 80% and 90%; Due to the different stratum depths and sources of natural gas extraction, the methane content in the purified natural gas will also be different. Specifically, the natural gas input into the oil and gas pipeline network after purification includes three types: dry gas, wet gas, and associated gas. The methane content in dry natural gas is relatively high and is not suitable for input into the oil and gas pipeline network. The study of dry natural gas is not considered in this embodiment. For wet natural gas and associated natural gas input into the oil and gas pipeline network, due to the difference in methane content, for example, the methane content of wet natural gas is 80%-90%, and the methane content of associated natural gas is below 80%. In this regard, this embodiment uses the methane content as a characteristic indicator of the tracking calculation model, and creates tracking calculation models for wet natural gas and associated natural gas respectively; For natural gas with different methane contents, directly inputting the natural gas data into the tracking calculation model for calculation, different characteristic indicators will show different calculation results, which is easy to get wrong calculation results. Therefore, in order to get more accurate calculation results, this embodiment sets two data sets accordingly, and calculates respectively through two models; Figure 3 This is a flow chart of obtaining input data in a gas tracking calculation method for an oil and gas pipeline network provided in Example 1 of the present invention. Figure 3 , the acquisition of input data includes the following steps: Step S21, performing statistical processing on the first natural gas data set, the second natural gas data set and the oil and gas pipeline data set; statistical processing refers to performing statistics on the data in the first natural gas data set and the second natural gas data set, and calculating the correlation between the first natural gas data set, the second natural gas data set and the oil and gas pipeline data set by using statistical methods (such as Pearson correlation coefficient, Spearman rank correlation coefficient, etc.), so as to quantify the degree of association between the first natural gas data set, the second natural gas data set and the oil and gas pipeline data set; Step S22, arranging the correlations between the first natural gas dataset and the second natural gas dataset and the oil and gas pipeline dataset from high to low, and obtaining the influencing features of the wet gas natural gas dataset and the associated gas natural gas dataset; Specifically, there are 4 influencing features for the associated gas data set, and 7 influencing features for the wet gas data set. The 4 influencing features for the associated gas data set are obtained by sorting the oil and gas pipeline network data information and natural gas data information from high to low according to the relevance to the tracking calculation, and taking the first 4 as the influencing features of the associated gas data set. The seven influencing features of the wet natural gas dataset are sorted from high to low according to the relevance of the oil and gas pipeline network data information and natural gas data information to the tracking calculation, and the first seven are taken as the influencing features of the wet natural gas dataset; Specifically, the four influencing characteristics of the associated gas dataset are: methane content, natural gas emission rate, diffusion coefficient of natural gas in the oil and gas pipeline network, and wind speed of natural gas in the oil and gas pipeline network; The seven influencing features of the wet natural gas dataset are: methane content, ethane content, propane content, n-butane content, n-pentane content, natural gas concentration, and natural gas transportation time.
[0022] Step S23: taking the influencing features of the wet gas natural gas dataset and the associated gas natural gas dataset as input data.
[0023] The influencing characteristics of the associated gas data set are used as the first input data; the influencing characteristics of the wet natural gas data set are used as the second input data; the first input data is input into the first tracking calculation model for tracking calculation, and the second input data is input into the second tracking calculation model for tracking calculation.
[0024] Step S3, creating a tracking calculation model; The tracking calculation model includes a first tracking calculation model and a second tracking calculation model, the first tracking calculation model calculates the object to be tracked with a methane content below 80%, and the second tracking calculation model calculates the object to be tracked with a methane content between 80% and 90%; Further, the first tracking calculation model is a Gaussian model; It is worth noting that since the Gaussian model is used to calculate the objects to be tracked with a methane content of less than 80%, it is relatively easy to calculate. In order to improve the calculation accuracy and reduce the calculation cost, this embodiment uses the Gaussian model for calculation, taking into account the influence of multiple factors, and can more accurately simulate the flow direction and flow rate of the gas. By using the simple Gaussian model for calculation, fewer parameters can be input, reducing the difficulty and cost of model application; Further, the second tracking calculation model is a partial differential equation model; It is worth noting that since the tracking calculation model will produce different calculation results, the partial differential equation model calculates the objects to be tracked with a methane content of 80%-90%. Moreover, the partial differential equation model is based on the basic principles of physics, chemistry, etc., and can comprehensively consider the impact of multiple coefficients on the system to ensure the accuracy of the calculation results.
[0025] Step S4, inputting the input data into the tracking calculation model to obtain the tracking calculation result.
[0026] According to the four influencing features of the associated gas data set input into the calculation formula of the first tracking model, the formula of the first calculation model is: Where K is the natural gas distribution index, Q is the natural gas emission rate, k is the natural gas emission coefficient, which is related to the methane content, φ is the diffusion coefficient of natural gas in the oil and gas pipeline network, x is the wind direction coordinate, x0 is the coordinate of the natural gas at the node of the oil and gas pipeline network, and v is the wind speed of natural gas in the oil and gas pipeline network; In this embodiment, in order to improve the calculation accuracy, when establishing the Gaussian model formula, this embodiment is based on the transportation state of natural gas in the oil and gas pipeline network and takes into account the methane content, and establishes the Gaussian model formula to describe the distribution of natural gas in the oil and gas pipeline network, which is used to calculate the diffusion of natural gas, and further obtain the gas distribution, so that the flow direction and flow rate of the gas can be observed; The calculation formula of the second tracking model is input according to the seven influencing features of the wet natural gas data set. The formula of the second tracking model is: In the formula, C is the natural gas concentration, t is the natural gas transportation time, c1 is the methane content, c2 is the ethane content, c3 is the propane content, c4 is the butane content, c5 is the n-pentane content, and x is the spatial coordinate system; In this embodiment, in order to improve the accuracy of calculation, when establishing the partial differential equation calculation model, this embodiment establishes a partial differential equation based on the content of natural gas and comprehensively considers the content of main components. The flow rate and flow direction distribution of the gas can be observed based on the obtained natural gas density.
[0027] Embodiment 2, Figure 4 A structural diagram of a gas tracking calculation system for an oil and gas pipeline network provided by 1 in Embodiment 2 of the present invention. Figure 4 The present invention provides a gas tracking calculation system for oil and gas pipeline network, which is used for the above-mentioned gas tracking calculation method for oil and gas pipeline network, and includes the following modules: Dataset acquisition module: used to acquire and track oil and gas pipeline network datasets; Preprocessing module: connected with the data set acquisition module, used to preprocess the oil and gas pipeline network data set; The first tracking calculation model module is connected to the data set acquisition module and is used to input the associated gas data set for tracking calculation; The second tracking calculation model module is connected to the data set acquisition module and is used to input the wet natural gas data set for tracking calculation. The first tracking calculation model output module is connected to the first tracking calculation model and is used to output a first gas tracking calculation method for oil and gas pipeline networks.
[0028] Embodiment 3, A storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a gas tracking calculation method for an oil and gas pipeline network as described in any one of Examples 1-2.
[0029] The medium in the present invention may adopt any combination of one or more computer-readable media. The medium may be a computer-readable signal medium or a computer-readable storage medium. The medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples of the medium (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, the medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device, or device.
[0030] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims
1. A gas tracking calculation method for oil and gas pipeline network, characterized in that: The specific steps include: Step S1, collecting oil and gas pipeline network data set; Step S2, preprocessing the oil and gas pipeline network data set to obtain input data; Step S3, creating a tracking calculation model; Step S4, inputting the input data into the tracking calculation model to obtain the tracking calculation result; The tracking calculation model includes a first tracking calculation model and a second tracking calculation model. The first tracking calculation model is used to perform tracking calculation on associated gas, and the second tracking calculation model is used to perform tracking calculation on wet gas.
2. A gas tracking calculation method for oil and gas pipeline network according to claim 1, characterized in that: In step S2, the oil and gas pipeline network data set is preprocessed, specifically comprising the following steps: Step S2.1, screening out and deleting unqualified data in the oil and gas pipeline network data set; Step S2.2, select data related to natural gas and delete irrelevant and redundant data.
3. A gas tracking calculation method for oil and gas pipeline network according to claim 2, characterized in that: The oil and gas pipeline network data set preprocessed in step S2 includes an oil and gas pipeline data set and a natural gas data set.
4. A gas tracking calculation method for oil and gas pipeline network according to claim 3, characterized in that: The natural gas dataset includes a first natural gas dataset and a second natural gas dataset, wherein the first natural gas dataset is a preprocessed associated gas natural gas dataset, and the second natural gas dataset is a preprocessed wet gas natural gas dataset.
5. A gas tracking calculation method for oil and gas pipeline network according to claim 4, characterized in that: The acquisition of the input data specifically includes the following steps: Step S21, performing statistical processing on the first natural gas data set, the second natural gas data set, and the oil and gas pipeline data set; Step S22, arranging the correlations between the first natural gas dataset, the second natural gas dataset and the oil and gas pipeline dataset from high to low, and obtaining the influencing features of the wet gas natural gas dataset and the associated gas natural gas dataset; Step S23: taking the influencing features of the wet gas natural gas dataset and the associated gas natural gas dataset as input data.
6. A gas tracking calculation method for oil and gas pipeline network according to claim 5, characterized in that: In step S22, the number of influencing features of the associated gas natural gas dataset is 4, and the number of influencing features of the wet gas natural gas dataset is 7.
7. The gas tracking calculation method for oil and gas pipeline network according to claim 1, characterized in that: The first tracking calculation model is a Gaussian model, and the second tracking calculation model is a partial differential equation model.
8. A gas tracking calculation method for oil and gas pipeline network according to claim 6, characterized in that: The four influencing characteristics of the associated gas data set are: methane content, natural gas emission rate, diffusion coefficient of natural gas in the oil and gas pipeline network, and wind speed of natural gas in the oil and gas pipeline network.
9. A gas tracking calculation method for oil and gas pipeline network according to claim 6, characterized in that: The seven influencing features of the wet natural gas dataset are: methane content, ethane content, propane content, n-butane content, n-pentane content, natural gas concentration, and natural gas transportation time.
10. A gas tracking calculation method for oil and gas pipeline network according to claim 7, characterized in that: The calculation formula of the Gaussian model is: Where K is the natural gas distribution index, Q is the natural gas emission rate, and k is the natural gas emission coefficient, which is related to the methane content. is the diffusion coefficient of natural gas in the oil and gas pipeline network, x is the wind direction coordinate, x0 is the coordinate of natural gas at the node of the oil and gas pipeline network, and v is the wind speed of natural gas in the oil and gas pipeline network; The calculation formula of the partial differential equation model is: Where C is the natural gas concentration, t is the natural gas transportation time, c1 is the methane content, c2 is the ethane content, c3 is the propane content, c4 is the butane content, c5 is the n-pentane content, x is the spatial coordinate system, and D is the coefficient.