Optimization method and system for shape-preserving cubic spline of crude oil distillation curve
By optimizing the crude oil distillation curve using the cubic spline method, the problems of discontinuity and roughness in the distillation curve were solved, the monotonicity and accuracy of the distillation curve were improved, and the reliability of the results was enhanced.
Patent Information
- Application Number
- CN202511103370.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-07
- Publication Date
- 2025-11-11
AI Technical Summary
In the existing technology, the methods for determining petroleum fractions have problems such as discontinuous and uneven distillation curves, poor reliability of results, and difficulty in ensuring that the distillation curve is monotonically increasing.
The cubic spline method is used to obtain crude oil distillation data, determine the cubic function, determine whether the objective function satisfies the preset formula, add new values to form a new curve that satisfies the preset formula, and continue until the objective function no longer satisfies the preset formula, thus completing the optimization of the crude oil distillation curve.
It improves the accuracy of crude oil distillation curves, solves the problem of monotonicity in distillation curves, and enhances the reliability of results.
Smart Images
Figure CN120930366A_ABST
Abstract
Description
Technical Field
[0001] The embodiments of this application belong to the field of chemical optimization technology, and in particular relate to a method and system for optimizing crude oil distillation curves using cubic splines that preserve the shape. Background Technology
[0002] Petroleum is a complex mixture of hydrocarbons containing thousands of components. Due to this characteristic, precise component analysis of petroleum fractions is not feasible in practice.
[0003] In existing technologies, the determination of petroleum fractions mainly employs a simplified method of virtual component processing. However, in actual operation, the data for the oil distillation curve is obtained experimentally, resulting in a limited number of data points. This necessitates data fitting using these limited points to predict points for which no experimental values are available, thus forming a complete distillation curve. To address the problem of discontinuous and uneven distillation curves and poor reliability often caused by insufficient distillation data, the traditional cubic spline interpolation method is commonly used. However, the distillation curve is a cumulative curve of the distillate during crude oil distillation, and it can only increase monotonically. This method has the problem of not being able to guarantee a monotonically increasing distillation curve.
[0004] Therefore, an optimization method for conformal cubic splines of crude oil distillation curves is needed. Summary of the Invention
[0005] This specification provides an optimization method and system for shape-preserving cubic splines of crude oil distillation curves to solve some or all of the problems: In the prior art, the determination of petroleum fractions mainly adopts the virtual component processing method for simplification. In actual operation, the data of oil distillation curves are obtained from experiments, and the data points are limited. It is necessary to use a limited number of points for data fitting to predict points without experimental values, thereby forming a complete distillation curve. To address the problem that the distillation curve is often discontinuous and not smooth due to insufficient distillation data, resulting in poor reliability of the results, the traditional cubic spline interpolation method is often used. However, the distillation curve is a cumulative curve of distillates during crude oil distillation, which can only increase monotonically. This method has the problem of difficulty in ensuring the monotonous increase of the distillation curve.
[0006] To solve the above-mentioned technical problems, the embodiments in this specification are implemented as follows: This specification provides an embodiment of a method for optimizing crude oil distillation curves using cubic splines that preserve the shape. The optimization method includes: Obtain the crude oil distillation data to be processed; The cubic spline method is used to determine the cubic functions of each curve corresponding to the crude oil distillation data to be processed; Determine whether the objective function corresponding to the cubic function satisfies the preset formula; If the objective function corresponding to the cubic function satisfies the preset formula, then according to the preset method, a new value is added to the curve corresponding to the cubic function to form a new curve corresponding to the cubic function; Determine whether the objective function corresponding to the new curve of the cubic function satisfies the preset formula, until the objective function of the new curve of the cubic function does not satisfy the preset formula, and complete the optimization of the cubic spline of the crude oil distillation curve corresponding to the crude oil distillation data to be processed.
[0007] This specification also provides an optimization system for conformal cubic splines of crude oil distillation curves, the optimization system comprising: The acquisition module retrieves the crude oil distillation data to be processed. The module is determined by using the cubic spline method to determine the cubic functions of each curve corresponding to the crude oil distillation data to be processed; The judgment module determines whether the objective function corresponding to the cubic function satisfies the preset formula. The interpolation module, if the objective function corresponding to the cubic function satisfies the preset formula, adds a new value to the curve corresponding to the cubic function according to a preset method to form a new curve corresponding to the cubic function; The optimization module determines whether the objective function corresponding to the new curve of the cubic function satisfies the preset formula, until the objective function of the new curve of the cubic function does not satisfy the preset formula, thus completing the optimization of the cubic spline of the crude oil distillation curve corresponding to the crude oil distillation data to be processed.
[0008] The above-mentioned at least one technical solution adopted in the embodiments of this specification can achieve the following beneficial effects: by acquiring crude oil distillation data to be processed; using the cubic spline method to determine the cubic function of each curve corresponding to the crude oil distillation data to be processed; determining whether the objective function corresponding to the cubic function satisfies the preset formula; if the objective function corresponding to the cubic function satisfies the preset formula, then according to the preset method, adding new values to the curve corresponding to the cubic function to form a new curve corresponding to the cubic function; judging whether the objective function corresponding to the new curve corresponding to the cubic function satisfies the preset formula, until the objective function corresponding to the new curve does not satisfy the preset formula, thus completing the optimization of the cubic spline of the crude oil distillation curve corresponding to the crude oil distillation data to be processed, which can solve the monotonicity problem of the crude oil distillation curve and improve the accuracy of the crude oil distillation curve. Attached Figure Description
[0009] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. Some specific embodiments of this application will be described in detail below with reference to the accompanying drawings in an exemplary and non-limiting manner. The same reference numerals in the drawings designate the same or similar parts or components. Those skilled in the art should understand that these drawings are not necessarily drawn to scale. In the drawings: Figure 1 A flowchart illustrating a method for optimizing a conformal cubic spline for crude oil distillation curves, provided in an embodiment of this specification. Figure 2 A schematic diagram illustrating the framework of a method for optimizing crude oil distillation curves using cubic splines, as provided in the embodiments of this specification. Figure 3 The initial fitting curve for the crude oil distillation curve provided in the embodiments of this specification; Figure 4 The optimized fitting curve for the crude oil distillation curve provided in the embodiments of this specification; Figure 5 This is a schematic diagram of an optimization system for conformal cubic splines of crude oil distillation curves provided in this embodiment. Detailed Implementation
[0010] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are merely some, not all, of the embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative effort should fall within the scope of protection of the present application.
[0011] In the existing technology, the petroleum refining industry generally uses a virtual component processing method to simplify the determination of petroleum components, which specifically includes the following steps: Input the Engel distillation curve data of the oil, the distillation curve conversion method, and data such as specific gravity or API specific gravity, and the software will generate the true boiling point distillation curve. Based on the actual boiling point distillation curve, the oil is cut into virtual components using the default cut point; Estimate the physical properties of the virtual components based on the corresponding correlation formulas; Select an appropriate equation of state and load virtual components into the component package; The corresponding oil product is introduced into the process through the oil feeder module, and the process simulation calculation of the oil product is performed.
[0012] The accuracy of the distillation curve directly affects the subsequent determination of petroleum components. Therefore, the accuracy of the crude oil distillation curve is of great significance in determining the accurate determination of petroleum components.
[0013] However, in actual operation, the data of oil distillation curves are obtained from experiments, and the data points are limited. It is necessary to use a limited number of points to fit the data and predict the points without experimental values to form a complete distillation curve. In order to address the problem that the distillation curve is discontinuous and not smooth due to insufficient distillation data, resulting in poor reliability, the traditional cubic spline interpolation method is often used. However, this method has the problem that it is difficult to guarantee that the distillation curve is monotonically increasing.
[0014] Based on this, the embodiments of this specification provide a solution to the non-monotonicity of the conformal cubic spline of crude oil distillation curve. Taking into account the limited amount of oil distillation data and the need to ensure the monotonicity of the fitted curve, the method of adding virtual data points is used to ensure the monotonicity of the fitted curve with minimal impact on the simulation results.
[0015] Figure 1 This is a flowchart illustrating a method for optimizing a shape-preserving cubic spline of a crude oil distillation curve, as provided in an embodiment of this specification. From a programming perspective, the execution entity of this optimization method is a program mounted on an application server or application terminal. It can be understood that this optimization method can be executed by any device, equipment, platform, or cluster of devices with computing and processing capabilities. Figure 1 As shown, the optimization method includes: Step S101: Obtain the crude oil distillation data to be processed.
[0016] In the embodiments of this specification, the crude oil distillation data to be processed is experimental data used for crude oil distillation curve fitting.
[0017] In this embodiment, the crude oil distillation data to be processed includes n test points, each test point being... And satisfy for any .
[0018] Step S103: Use the cubic spline method to determine the cubic function of each curve corresponding to the crude oil distillation data to be processed.
[0019] Cubic splines are interpolation functions in mathematics constructed using piecewise cubic polynomials. These functions require that the spline be a cubic polynomial in each subinterval of the defined interval and that the second derivative is continuous at the nodes (i.e., S(x)∈C²[a,b]). The construction process involves establishing a system of linear equations using 3n-3 continuity equations and two boundary conditions (such as endpoint derivative constraints or periodic conditions), ultimately obtaining a unique solution under the special structure of a tridiagonal matrix.
[0020] Continuing from the previous example, if the crude oil distillation data to be processed includes n test points, then there are (n-1) curves.
[0021] Step S105: Determine whether the objective function corresponding to the cubic function satisfies the preset formula.
[0022] In the embodiments described in this specification, the expression of the objective function is:
[0023] in, The first part represents the crude oil distillation data to be processed. A line segment; This represents the data detection point of the crude oil distillation data to be processed; Indicates the first The objective function for each line segment; , , , All are constants.
[0024] It should be noted that, , , , It is calculated using a cubic function of the curves corresponding to the crude oil distillation data to be processed. For different curves, , , , different.
[0025] because , , , Since it is a constant, it can be further used to form a preset formula to determine the monotonicity of the curve.
[0026] In the embodiments described in this specification, the preset formula is:
[0027] When the preset formula is satisfied, the objective function is not monotonic.
[0028] In the embodiments described in this specification, the first The first line segment represents the first line segment of the crude oil distillation data to be processed. The ( ) point and the ( ) The line segment formed by ) points; The objective function is based on the first... The equations that each line segment must satisfy are determined by calculation:
[0029]
[0030]
[0031]
[0032]
[0033]
[0034] in, and It is a constant.
[0035] Step S107: If the objective function corresponding to the cubic function satisfies the preset formula, then according to the preset method, add a new value to the curve corresponding to the cubic function to form a new curve corresponding to the cubic function.
[0036] In the embodiments described in this specification, the preset method is as follows: Use data logic to determine new points It is close to the first The first segment point Or closer to the first point .
[0037] In the embodiments described in this specification, the logical judgment method is based on The relationship is judged, specifically including: like Then the x-coordinate of the newly added point near ,but
[0038] like Then the x-coordinate of the newly added point near ,but
[0039] in,
[0040]
[0041] The first part represents the crude oil distillation data to be processed. The slope of each line segment; This represents the ( )th of the crude oil distillation data to be processed. +1) slope of line segments.
[0042] In the embodiments described in this specification, the constant coefficient is 9.
[0043] In the embodiments described in this specification, the method further includes: Based on the determined x-coordinates of the new points Determine the ordinate of the new point ;
[0044] in,
[0045]
[0046] Represents the ordinate of a virtual point; The ordinate of the objective function corresponding to the newly added point represents the ordinate.
[0047] Determine new points Then, with the original n test points A total of (n+1) points are used as new crude oil distillation data to be processed.
[0048] Step S109: Determine whether the objective function corresponding to the new curve of the cubic function satisfies the preset formula, until the objective function of the new curve of the cubic function does not satisfy the preset formula, and complete the optimization of the cubic spline of the crude oil distillation curve corresponding to the crude oil distillation data to be processed.
[0049] To further understand the optimization method of the crude oil distillation curve conformal cubic spline in the embodiments of this specification, Figure 2 This is a schematic diagram illustrating the framework of a method for optimizing crude oil distillation curves using cubic splines, as provided in the embodiments of this specification. Figure 2 As shown, the crude oil distillation data to be processed is obtained, and the cubic spline method is used to calculate the cubic function of each curve; it is then determined whether the objective function of each cubic function satisfies the preset formula, and if so, a new value is added. Repeat the above process to determine whether the preset formula is satisfied, until the preset formula is not satisfied, and then output the result.
[0050] To further understand the optimization method for conformal cubic splines of crude oil distillation curves provided in the embodiments of this specification, the following will be explained in conjunction with specific embodiments.
[0051] The distillation data of a certain factory's oil products are shown in Table 1.
[0052] Table 1 Oil distillation data
[0053] The image is obtained by fitting the data using cubic splines, such as... Figure 3 As shown.
[0054] The experimental data provides 12 data points, with 11 intervals requiring a fitting function. Analysis of the graph shows that the fitted curve for the 10th interval is not monotonic. The slope of the next curve... Slope compared to the previous interval Large, therefore Calculated using this method ,Right now , but =98-(98-80) / 9=96 =
[0055]
[0056]
[0057] so for Join point The data was then organized and is shown in Table 2.
[0058] Table 2. Distillation data of oil products after update
[0059] Refit the function, such as Figure 4 As shown, from Figure 4 It is evident that the fitted image satisfies monotonicity.
[0060] Meanwhile, the crude oil has a specific gravity and relative density of 0.88052, and light components account for 3% of the oil product (liquid phase volume), as shown in Table 3.
[0061] Table 3 Light Components of Oil Products
[0062] The cutting simulation data for the oil are shown in Table 4.
[0063] Table 4 Cutting Mode Data
[0064] Further simulations were conducted using the process simulation software Simulator, and the quantities of naphtha, kerosene, diesel, atmospheric gas oil, and residual oil in the simulation results were read and compared with actual production data.
[0065] The comparison between simulated data and experimental data is shown in Table 5.
[0066] Table 5 Comparison of Simulated Data and Experimental Data
[0067] As shown in Table 5, the simulated values obtained by this method are quite close to the actual production data. This method has high accuracy and high feasibility.
[0068] The method for optimizing crude oil distillation curves using conformal cubic splines provided in this specification involves: acquiring crude oil distillation data to be processed; using the cubic spline method to determine the cubic function of each curve corresponding to the crude oil distillation data; determining whether the objective function corresponding to the cubic function satisfies a preset formula; if the objective function satisfies the preset formula, adding new values to the curve corresponding to the cubic function according to a preset method to form a new curve corresponding to the cubic function; judging whether the objective function corresponding to the new curve satisfies the preset formula, until the objective function of the new curve does not satisfy the preset formula, thus completing the optimization of the cubic splines of the crude oil distillation curves corresponding to the crude oil distillation data to be processed. This method can solve the monotonicity problem of crude oil distillation curves and improve the accuracy of crude oil distillation curves.
[0069] The foregoing embodiments of this specification provide a method for optimizing a conformal cubic spline of crude oil distillation curve. Based on the same idea, the embodiments of this specification also provide an optimization system for a conformal cubic spline of crude oil distillation curve. Figure 5 This is a schematic diagram of an optimization system for conformal cubic splines of crude oil distillation curves provided in this embodiment. Figure 5 As shown, the optimization system includes: Module 501 acquires the crude oil distillation data to be processed; The module 503 uses the cubic spline method to determine the cubic functions of each curve corresponding to the crude oil distillation data to be processed; The judgment module 505 determines whether the objective function corresponding to the cubic function satisfies the preset formula. Interpolation module 507: If the objective function corresponding to the cubic function satisfies the preset formula, then according to the preset method, a new value is added to the curve corresponding to the cubic function to form a new curve corresponding to the cubic function; The optimization module 509 determines whether the objective function corresponding to the new curve of the cubic function satisfies the preset formula, until the objective function of the new curve of the cubic function does not satisfy the preset formula, thus completing the optimization of the cubic spline of the crude oil distillation curve corresponding to the crude oil distillation data to be processed.
[0070] In the embodiments described in this specification, the expression of the objective function is:
[0071] in, The first part represents the crude oil distillation data to be processed. A line segment; This represents the data detection point of the crude oil distillation data to be processed; Indicates the first The objective function for each line segment; , , , All are constants.
[0072] In the embodiments described in this specification, the preset formula is:
[0073] In the embodiments described in this specification, the preset method is as follows: Use data logic to determine new points It is close to the first The first segment point Or closer to the first point .
[0074] In the embodiments described in this specification, the logical judgment method is based on The relationship is judged, specifically including: like Then the x-coordinate of the newly added point near ,but
[0075] like Then the x-coordinate of the newly added point near ,but
[0076] in,
[0077]
[0078] The first part represents the crude oil distillation data to be processed. The slope of each line segment; This represents the ( )th of the crude oil distillation data to be processed. +1) slope of line segments.
[0079] In the embodiments described in this specification, the constant coefficient is 9.
[0080] In the embodiments described in this specification, the method further includes: Based on the determined x-coordinates of the new points Determine the ordinate of the new point ;
[0081] in,
[0082]
[0083] Represents the ordinate of a virtual point; The ordinate of the objective function corresponding to the newly added point represents the ordinate.
[0084] In the embodiments described in this specification, the first The first line segment represents the first line segment of the crude oil distillation data to be processed. The ( ) point and the ( ) The line segment formed by ) points; The objective function is based on the first... The equations that each line segment must satisfy are determined by calculation:
[0085]
[0086]
[0087]
[0088]
[0089]
[0090] in, and It is a constant.
[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.
Claims
1. A method for optimizing crude oil distillation curves using cubic splines while preserving the shape, characterized in that, The optimization method includes: Obtain the crude oil distillation data to be processed; The cubic spline method is used to determine the cubic functions of each curve corresponding to the crude oil distillation data to be processed; Determine whether the objective function corresponding to the cubic function satisfies the preset formula; If the objective function corresponding to the cubic function satisfies the preset formula, then according to the preset method, a new value is added to the curve corresponding to the cubic function to form a new curve corresponding to the cubic function; Determine whether the objective function corresponding to the new curve of the cubic function satisfies the preset formula, until the objective function of the new curve of the cubic function does not satisfy the preset formula, and complete the optimization of the cubic spline of the crude oil distillation curve corresponding to the crude oil distillation data to be processed.
2. The optimization method as described in claim 1, characterized in that, The expression for the objective function is: in, The first part represents the crude oil distillation data to be processed. A line segment; This represents the data detection point of the crude oil distillation data to be processed; Indicates the first The objective function for each line segment; , , , All are constants.
3. The optimization method as described in claim 2, characterized in that, The preset formula is: 。 4. The optimization method as described in claim 2, characterized in that, The preset method is as follows: Use data logic to determine new points It is close to the first The first segment point Or closer to the first point .
5. The optimization method as described in claim 4, characterized in that, The logical judgment method is based on The relationship is judged, specifically including: like Then the x-coordinate of the newly added point near ,but like Then the x-coordinate of the newly added point near ,but in, The first part represents the crude oil distillation data to be processed. The slope of each line segment; This represents the ( )th of the crude oil distillation data to be processed. +1) slopes of line segments.
6. The optimization method as described in claim 5, characterized in that, The constant coefficient is 9.
7. The optimization method as described in claim 5, characterized in that, The method further includes: Based on the determined x-coordinates of the new points Determine the ordinate of the new point ; in, Represents the ordinate of a virtual point; The ordinate of the objective function corresponding to the newly added point represents the ordinate.
8. The optimization method as described in claim 2, characterized in that, The first The first line segment represents the first line segment of the crude oil distillation data to be processed. The ( ) point and the ( ) The line segment formed by ) points; The objective function is based on the first... The equations that each line segment must satisfy are determined by calculation: in, and It is a constant.
9. An optimization system for conformal cubic splines of crude oil distillation curves, characterized in that, The optimization system includes: The acquisition module retrieves the crude oil distillation data to be processed. The module is determined by using the cubic spline method to determine the cubic functions of each curve corresponding to the crude oil distillation data to be processed; The judgment module determines whether the objective function corresponding to the cubic function satisfies the preset formula. The interpolation module, if the objective function corresponding to the cubic function satisfies the preset formula, adds a new value to the curve corresponding to the cubic function according to a preset method to form a new curve corresponding to the cubic function; The optimization module determines whether the objective function corresponding to the new curve of the cubic function satisfies the preset formula, until the objective function of the new curve of the cubic function does not satisfy the preset formula, thus completing the optimization of the cubic spline of the crude oil distillation curve corresponding to the crude oil distillation data to be processed.