An optimization method and device for determining a target crude oil blending ratio

Abstract

The application discloses an optimization method and device for determining a mixing ratio of target crude oil, and the method is as follows: macroscopic physical property data of the target crude oil is acquired; a plurality of crude oil samples similar to the target crude oil are searched in a crude oil database; a mixed integer nonlinear programming method is used to determine the mixing ratio of the plurality of crude oil samples; the plurality of crude oil samples are mixed into blending crude oil according to the mixing ratio, and molecular composition data of the blending crude oil is determined; the macroscopic physical property data of the blending crude oil is determined according to the mixing ratio and the molecular composition data of the blending crude oil; the mixing ratio is adjusted according to the difference between the macroscopic physical property data of the blending crude oil and the macroscopic physical property data of the target crude oil until the difference reaches the minimum; and the mixing ratio of the plurality of crude oil samples in the adjusted blending crude oil is acquired as the mixing ratio of the target crude oil. The method can quickly and accurately determine the mixing ratio of each molecule of the target crude oil, and provides technical support for subsequent production processes.

Description

Technical Field

[0001] This invention belongs to the field of crude oil processing technology, and specifically relates to an optimization method and apparatus for determining the blending ratio of a target crude oil. Background Technology

[0002] With the rapid development of the national economy, my country's demand for oil has been increasing year by year, and the requirements for oil quality have become increasingly stringent. Therefore, controlling the oil processing technology has become extremely important.

[0003] In the oil refining process, simulations are often conducted based on data such as the molecular composition of crude oil to determine the various oil products to be produced. The blending ratio of crude oil is a crucial data point in this process; only by knowing the accurate blending ratio can the accuracy of the simulation results be guaranteed. Therefore, providing a method for quickly and accurately determining the target crude oil blending ratio is extremely important for the oil refining industry. Summary of the Invention

[0004] To address the problems existing in the prior art, the present invention provides an optimization method and apparatus for determining the target crude oil blending ratio.

[0005] To achieve the above objectives, the present invention provides the following four technical solutions:

[0006] In a first aspect, the present invention provides an optimization method for determining the target crude oil blending ratio, comprising the following steps:

[0007] Obtain macroscopic physical property data of the target crude oil;

[0008] Based on the macroscopic physical property data of the target crude oil, search the crude oil database for several crude oil samples that are similar to the target crude oil.

[0009] The mixing ratio of the crude oil samples was determined using a mixed-integer nonlinear programming method.

[0010] The crude oil samples are mixed into blended crude oil according to the mixing ratio, and the molecular composition data of the blended crude oil is determined according to the mixing ratio and the molecular composition data of the crude oil samples.

[0011] The macroscopic physical properties of the blended crude oil are determined based on the mixing ratio and the molecular composition data of the blended crude oil.

[0012] The blending ratio is adjusted according to the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil, and the several crude oil samples are remixed into blended crude oil according to the adjusted blending ratio until the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil is minimized.

[0013] The mixing ratio of several crude oil samples in the adjusted blended crude oil is obtained as the mixing ratio of the target crude oil.

[0014] Preferably, before the step of searching for several crude oil samples similar to the target crude oil in a crude oil database based on the macroscopic physical property data of the target crude oil, the method further includes:

[0015] Based on the macroscopic physical property data of the target crude oil, search for crude oil samples that match the target crude oil in the crude oil database;

[0016] If a crude oil sample that matches the target crude oil is found in the crude oil database, then the target crude oil is 100% of the crude oil sample.

[0017] If no crude oil sample matching the target crude oil is found in the crude oil database, then the step of searching for several crude oil samples similar to the target crude oil in the crude oil database based on the macroscopic physical property data of the target crude oil is performed.

[0018] Preferably, the step of searching for several crude oil samples similar to the target crude oil in a crude oil database based on the macroscopic physical property data of the target crude oil includes:

[0019] For each crude oil sample in the crude oil database, calculate the physical property similarity between that crude oil sample and the target oil product;

[0020] The crude oil samples in the crude oil database are sorted according to the similarity of their physical properties to the target oil product.

[0021] Based on the ranking results, select several crude oil samples whose physical properties are closest to those of the target crude oil.

[0022] Preferably, the physical property similarity is equal to the sum of the squares of the differences between the macroscopic physical property data of the crude oil sample and the corresponding macroscopic physical property data of the target oil product, multiplied by their respective weights; the weights characterize the importance of their corresponding macroscopic physical properties.

[0023] Preferably, the step of determining the blending ratio of the plurality of crude oil samples using a mixed-integer nonlinear programming method includes:

[0024] The blending ratio of the crude oil samples is determined based on mixed-integer nonlinear programming and a penalty function, wherein the penalty function includes:

[0025] The penalty function for the number of crude oil types is used to limit the number of crude oil types selected from the sorted crude oil samples for modeling.

[0026] The penalty function for the minimum mixing ratio is used to limit the minimum mixing ratio value in the final mixing ratio.

[0027] Preferably, the penalty function for the number of crude oil types is an increasing function of the number of crude oil types; the more crude oil types there are, the larger the value of the penalty function.

[0028] The penalty function for the minimum mixing ratio is a decreasing function of the minimum mixing ratio; the smaller the minimum mixing ratio, the larger the penalty function.

[0029] Preferably, when the sum of the products of the squares of the differences between the macroscopic physical property data of the blended crude oil and the corresponding macroscopic physical property data of the target crude oil and their respective weights reaches the minimum value, it is determined that the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil has reached the minimum value.

[0030] Secondly, the present invention provides an optimization apparatus for determining a target crude oil blending ratio, comprising:

[0031] The first acquisition module is used to acquire the macroscopic physical property data of the target crude oil;

[0032] The first search module is used to search for several crude oil samples that are similar to the target crude oil in the crude oil database based on the macroscopic physical property data of the target crude oil.

[0033] An analysis module is used to determine the blending ratio of the crude oil samples using a mixed-integer nonlinear programming method.

[0034] A mixing module is used to mix the plurality of crude oil samples into blended crude oil according to the mixing ratio, and to determine the molecular composition data of the blended crude oil based on the mixing ratio and the molecular composition data of the plurality of crude oil samples.

[0035] The determination module is used to determine the macroscopic physical property data of the blended crude oil based on the mixing ratio and the molecular composition data of the blended crude oil;

[0036] The adjustment module is used to adjust the blending ratio based on the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil, and to remix the several crude oil samples into blended crude oil according to the adjusted blending ratio until the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil is minimized.

[0037] The second acquisition module is used to acquire the adjusted mixing ratio.

[0038] Preferably, the device further includes a second search module.

[0039] The second search module is used to search for crude oil samples that are consistent with the target crude oil in the crude oil database based on the macroscopic physical property data of the target crude oil. If a crude oil sample that is consistent with the target crude oil is found in the crude oil database, then the target crude oil is 100% the crude oil sample. If no crude oil sample that is consistent with the target crude oil is found in the crude oil database, the first search module is invoked to search for several crude oil samples that are similar to the target crude oil in the crude oil database based on the macroscopic physical property data of the target crude oil.

[0040] Preferably, the first search module includes:

[0041] The calculation unit calculates the physical property similarity between each crude oil sample in the crude oil database and the target oil product.

[0042] The sorting unit sorts the crude oil samples in the crude oil database according to the similarity of their physical properties to the target oil product.

[0043] Select a cell and choose several crude oil samples whose physical properties are closest to the target crude oil based on the sorting results.

[0044] Preferably, in the adjustment module, when the sum of the products of the squares of the differences between the macroscopic physical property data of the blended crude oil and the corresponding macroscopic physical property data of the target crude oil and their respective weights reaches the minimum value, it is determined that the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil has reached the minimum.

[0045] Thirdly, the present invention provides an optimization device for determining the target crude oil blending ratio, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0046] Memory, used to store computer programs;

[0047] The processor, when executing the program stored in memory, implements the above-mentioned optimization method for determining the target crude oil blending ratio.

[0048] Fourthly, the present invention provides a computer-readable storage medium storing one or more programs that can be executed by one or more processors to implement the above-described optimization method for determining the target crude oil blending ratio.

[0049] Preferably, the computer-readable storage medium is one of a magnetic medium, an optical medium, or a semiconductor medium.

[0050] Compared with the prior art, the above-mentioned technical solution of the present invention has the following advantages:

[0051] 1. This method can quickly and accurately determine the mixing ratio of each molecule in the target crude oil, providing technical support for subsequent production processes.

[0052] 2. In this embodiment of the invention, the mixing ratio of crude oil samples in blended crude oil is adjusted by verifying the physical properties, thereby determining the true mixing ratio and molecular composition of crude oil, and avoiding economic losses caused by incorrect molecular composition in subsequent processes.

[0053] 3. This invention sets a penalty function in the optimization objective, so that the minimum value of the initially selected crude oil quantity and the mixing ratio is within a more reasonable range, which is conducive to the accurate determination of the mixing ratio.

[0054] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0055] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 is a flowchart of the optimization method for determining the target crude oil blending ratio according to Embodiment 1 of the present invention;

[0057] Figure 2 is a flowchart of the optimization method for determining the target crude oil blending ratio provided in Embodiment 2 of the present invention;

[0058] Figure 3 is a schematic diagram of an optimization device for determining the target crude oil blending ratio according to Embodiment 3 of the present invention;

[0059] Figure 4 is a schematic diagram of the first search module provided according to Embodiment 3 of the present invention;

[0060] Figure 5 is a schematic diagram of an optimization device for determining the target crude oil blending ratio according to Embodiment 4 of the present invention. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] Example 1

[0063] As shown in Figure 1, the present invention provides an optimization method for determining the target crude oil blending ratio, which mainly includes the following steps:

[0064] S10 acquires macroscopic physical property data of the target crude oil;

[0065] S20 searches for several crude oil samples that are similar to the target crude oil in the crude oil database based on the macroscopic physical property data of the target crude oil.

[0066] S30 uses a mixed-integer nonlinear programming method to determine the blending ratio of the crude oil samples;

[0067] S40 mixes the several crude oil samples into blended crude oil according to the mixing ratio, and determines the molecular composition data of the blended crude oil based on the mixing ratio and the molecular composition data of the several crude oil samples.

[0068] S50 determines the macroscopic physical property data of the blended crude oil based on the mixing ratio and the molecular composition data of the blended crude oil.

[0069] S60 adjusts the blending ratio based on the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil, and remixes the several crude oil samples into blended crude oil according to the adjusted blending ratio until the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil is minimized.

[0070] S70 obtains the blending ratio of several crude oil samples in the adjusted blended crude oil as the blending ratio of the target crude oil.

[0071] Example 2

[0072] Figure 2 is a flowchart of the optimization method for determining the target crude oil blending ratio according to Embodiment 2 of the present invention. As shown in Figure 2, the optimization method for determining the target crude oil blending ratio in this embodiment mainly includes the following steps:

[0073] S10 acquires macroscopic physical property data of the target crude oil;

[0074] S100: Based on the known macroscopic physical property data of the target crude oil, search for crude oil samples in the crude oil database that are consistent with the target crude oil.

[0075] If a crude oil sample that matches the target crude oil is found in the crude oil database, the molecular composition data of the crude oil sample is used as the molecular composition data of the target crude oil, and the target crude oil is 100% the crude oil sample.

[0076] If no crude oil sample matching the target crude oil is found in the crude oil database, proceed to step S200.

[0077] S200 is the step of searching for several crude oil samples that are similar to the target crude oil in the crude oil database based on the macroscopic physical property data of the target crude oil.

[0078] In this embodiment, step S200 mainly involves first sorting the crude oil samples in the crude oil database according to the norm and weight related to the physical properties, and then selecting several crude oil samples whose physical properties are closest to the target crude oil based on the sorting results.

[0079] In specific applications, step S200 may include the following steps:

[0080] S210, For each crude oil sample in the crude oil database, calculate the physical property similarity between the crude oil sample and the target oil product, wherein the physical property similarity is equal to the sum of the squares of the differences between the macroscopic physical property data of the crude oil sample and the corresponding macroscopic physical property data of the target oil product and their respective weights; wherein the weights can be determined in advance according to the importance of each macroscopic physical property.

[0081] S220: Sort the crude oil samples in the crude oil database according to the physical property similarity between each crude oil sample in the crude oil database and the target oil product.

[0082] S230: Select several crude oil samples whose physical properties are closest to the target crude oil based on the sorting results.

[0083] For example, crude oil samples in a crude oil database are sorted in descending order of physical property similarity. Then, the top-ranked crude oil samples are selected as those with the closest physical properties to the target crude oil. The number of crude oil samples selected is not limited and is usually determined based on a trade-off between the accuracy of the calculation results and time constraints.

[0084] S300, using mixed integer nonlinear programming to determine the blending ratio of the crude oil samples.

[0085] In this embodiment, the blending ratio of the crude oil samples is determined using mixed-integer nonlinear programming, primarily based on mixed-integer nonlinear programming and a penalty function. The penalty function is defined as the penalty function for the number of crude oil types used in establishing the candidate mixed-integer nonlinear programming model, and the penalty function for the minimum blending ratio value obtained in the final blending ratio. Specifically, the objective function of the mixed-integer nonlinear programming model is to minimize the weighted distance between the vectors composed of the macroscopic properties of the target crude oil and the blended crude oil. The penalty function for the number of crude oil types limits the number of crude oil types selected for modeling from the sorted crude oil samples; it is an increasing function of the number of crude oil types, with a larger penalty function value for a larger number of types. The penalty function for the minimum blending ratio value is a decreasing penalty function for the minimum blending ratio; that is, the smaller the minimum value of the blending ratio determined in the final scheme, the larger the penalty function value.

[0086] By setting a penalty function in the optimization objective, the minimum values ​​of the initially selected crude oil quantity and mixing ratio are within a more reasonable range, which is beneficial to the implementation and application of the scheme.

[0087] S400, the plurality of crude oil samples are mixed into blended crude oil according to the mixing ratio, and the molecular composition data of the blended crude oil is determined based on the mixing ratio and the molecular composition data of the plurality of crude oil samples.

[0088] S500, determine the macroscopic physical property data of the blended crude oil based on the mixing ratio and the molecular composition data of the blended crude oil.

[0089] S600 analyzes the differences between the macroscopic properties of the blended crude oil and the macroscopic properties of the target crude oil.

[0090] S700, if the difference does not meet the preset threshold condition, the mixing ratio is adjusted, and the process returns to step S400. The several crude oil samples are remixed into blended crude oil according to the adjusted mixing ratio, so as to re-analyze the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil.

[0091] In this embodiment, the difference meeting the preset threshold condition means that the difference between the macroscopic property data of the blended crude oil and the macroscopic property data of the target crude oil can be minimized.

[0092] Therefore, a quality assessment parameter can be preferably used to measure the difference between the macroscopic properties of the blended crude oil and the macroscopic properties of the target crude oil. Specifically, this quality assessment parameter is equal to the weighted distance between the vectors formed by the macroscopic properties of the blended crude oil and the corresponding macroscopic properties of the target crude oil, for example, the sum of the squares of the differences and the products of their respective weights.

[0093] In this embodiment, when the value of the quality assessment parameter reaches its minimum value, it is determined that the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil is minimized.

[0094] S800, if the difference meets the preset threshold condition, then the molecular composition data and blending ratio of the blended crude oil are used as the molecular composition data and blending ratio of the target crude oil.

[0095] The method in this embodiment can quickly and accurately determine the molecular composition of crude oil and the blending ratio of the target crude oil, avoiding economic losses caused by incorrect molecular composition and blending ratio in subsequent processes.

[0096] Example 3

[0097] Based on the same inventive concept, as shown in Figure 3: This embodiment of the invention provides an optimization device for determining the target crude oil blending ratio, which includes:

[0098] The first acquisition module 1 is used to acquire macroscopic physical property data of the target crude oil;

[0099] The first search module 2 is used to search for several crude oil samples that are similar to the target crude oil in the crude oil database based on the macroscopic physical property data of the target crude oil.

[0100] Analysis module 3 is used to determine the blending ratio of the crude oil samples using a mixed integer nonlinear programming method;

[0101] The mixing module 4 is used to mix the plurality of crude oil samples into blended crude oil according to the mixing ratio, and to determine the molecular composition data of the blended crude oil based on the mixing ratio and the molecular composition data of the plurality of crude oil samples.

[0102] Module 5 is used to determine the macroscopic physical property data of the blended crude oil based on the mixing ratio and the molecular composition data of the blended crude oil.

[0103] Adjustment module 6 is used to adjust the blending ratio based on the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil, and to re-mix the several crude oil samples into blended crude oil according to the adjusted blending ratio until the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil reaches its minimum. In the adjustment module, when the sum of the products of the squares of the differences between the macroscopic physical property data of the blended crude oil and the corresponding macroscopic physical property data of the target crude oil and their respective weights reaches its minimum value, it is determined that the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil has reached its minimum.

[0104] The second acquisition module 7 is used to acquire the adjusted mixing ratio.

[0105] Preferably, the above-mentioned device further includes a second search module, used to search for crude oil samples consistent with the target crude oil in the crude oil database based on the macroscopic physical property data of the target crude oil; if a crude oil sample consistent with the target crude oil is found in the crude oil database, then the target crude oil is 100% the crude oil sample; if no crude oil sample consistent with the target crude oil is found in the crude oil database, then the first search module is invoked to search for several crude oil samples similar to the target crude oil in the crude oil database based on the macroscopic physical property data of the target crude oil.

[0106] Preferably, as shown in FIG4, the first search module 2 specifically includes:

[0107] The calculation unit 101 calculates the physical property similarity between each crude oil sample in the crude oil database and the target oil product.

[0108] The sorting unit 102 sorts the crude oil samples in the crude oil database according to the physical property similarity between each crude oil sample in the crude oil database and the target oil product.

[0109] Select unit 103 to select several crude oil samples whose physical properties are closest to the target crude oil based on the sorting results.

[0110] Example 4

[0111] Based on the same inventive concept, such as Figure 5 As shown, this embodiment of the invention provides an optimization device for determining the target crude oil blending ratio, including a processor 1110, a communication interface 1120, a memory 1130, and a communication bus 1140, wherein the processor 1110, the communication interface 1120, and the memory 1130 communicate with each other through the communication bus 1140;

[0112] Memory 1130 is used to store computer programs;

[0113] When the processor 1110 executes the program stored in the memory 1130, it implements the following optimization method for determining the target crude oil blending ratio:

[0114] Obtain macroscopic physical property data of the target crude oil;

[0115] Based on the macroscopic physical property data of the target crude oil, search the crude oil database for several crude oil samples that are similar to the target crude oil.

[0116] The mixing ratio of the crude oil samples was determined using a mixed-integer nonlinear programming method.

[0117] The crude oil samples are mixed into blended crude oil according to the mixing ratio, and the molecular composition data of the blended crude oil is determined according to the mixing ratio and the molecular composition data of the crude oil samples.

[0118] The macroscopic physical properties of the blended crude oil are determined based on the mixing ratio and the molecular composition data of the blended crude oil.

[0119] The blending ratio is adjusted according to the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil, and the several crude oil samples are remixed into blended crude oil according to the adjusted blending ratio until the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil is minimized.

[0120] The mixing ratio of several crude oil samples in the adjusted blended crude oil is obtained as the mixing ratio of the target crude oil.

[0121] The aforementioned communication bus 1140 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus 1140 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, it is shown in the figure with only one thick line, but this does not indicate that there is only one bus or one type of bus.

[0122] Communication interface 1120 is used for communication between the above-mentioned electronic device and other devices.

[0123] The memory 1130 may include random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Optionally, the memory 1130 may also be at least one storage device located remotely from the aforementioned processor 1110.

[0124] The processor 1110 mentioned above can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0125] Example 5

[0126] Based on the same inventive concept, embodiments of the present invention provide a computer-readable storage medium storing one or more programs, which can be executed by one or more processors to implement the steps of the optimization method for determining the target crude oil blending ratio in any of the above possible implementations.

[0127] Optionally, the storage medium may be a non-transitory computer-readable storage medium, such as a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device.

[0128] Based on the same inventive concept as Embodiment 1, this embodiment provides a computer-readable storage medium storing one or more programs, which can be executed by one or more processors to control the operation of the above-mentioned optimization device for determining the target crude oil blending ratio and to realize the above-mentioned optimization method for determining the target crude oil blending ratio.

[0129] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state disk (SSD)).

[0130] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention 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 of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. It should be noted that the terminology used herein is only for describing specific implementations and is not intended to limit the exemplary implementations according to this application. When the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0131] It should be noted that the terms "first," "second," etc., used in the specification, claims, and drawings of this application are used to distinguish similar objects and are not used to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that the embodiments of this application described herein can be implemented, for example, in sequences other than those illustrated or described herein.

[0132] It should be understood that the exemplary embodiments described herein can be implemented in many different forms and should not be construed as being limited to the embodiments set forth herein. These embodiments are provided so that the disclosure of this application is thorough and complete, and that the concept of these exemplary embodiments is fully conveyed to those skilled in the art, and should not be construed as limiting the invention.

Claims

1. An optimization method for determining the blending ratio of a target crude oil, characterized in that, Includes the following steps: Obtain macroscopic physical property data of the target crude oil; Based on the macroscopic physical property data of the target crude oil, search the crude oil database for several crude oil samples that are similar to the target crude oil. The mixing ratio of the crude oil samples was determined using a mixed-integer nonlinear programming method. The step of determining the blending ratio of the crude oil samples using the mixed integer nonlinear programming method includes: The blending ratio of the crude oil samples is determined based on a mixed-integer nonlinear programming method and a penalty function, wherein the penalty function includes: The penalty function for the number of crude oil types is used to limit the number of crude oil types selected for modeling from the sorted crude oil samples; The penalty function for the minimum mixing ratio is used to limit the minimum mixing ratio value in the final mixing ratio; The crude oil samples are mixed into blended crude oil according to the mixing ratio, and the molecular composition data of the blended crude oil is determined according to the mixing ratio and the molecular composition data of the crude oil samples. The macroscopic physical properties of the blended crude oil are determined based on the mixing ratio and the molecular composition data of the blended crude oil. The blending ratio is adjusted according to the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil, and the several crude oil samples are remixed into blended crude oil according to the adjusted blending ratio until the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil is minimized. The mixing ratio of several crude oil samples in the adjusted blended crude oil is obtained as the mixing ratio of the target crude oil.

2. The optimization method for determining the target crude oil blending ratio according to claim 1, characterized in that, Before the step of searching for several crude oil samples similar to the target crude oil in the crude oil database based on the macroscopic physical property data of the target crude oil, the method further includes: Based on the macroscopic physical property data of the target crude oil, search for crude oil samples that match the target crude oil in the crude oil database; If a crude oil sample that matches the target crude oil is found in the crude oil database, then the target crude oil is 100% of the crude oil sample. If no crude oil sample matching the target crude oil is found in the crude oil database, then the step of searching for several crude oil samples similar to the target crude oil in the crude oil database based on the macroscopic physical property data of the target crude oil is performed.

3. The optimization method for determining the target crude oil blending ratio according to claim 1, characterized in that, The step of searching for several crude oil samples similar to the target crude oil in a crude oil database based on the macroscopic physical property data of the target crude oil includes: For each crude oil sample in the crude oil database, calculate the physical property similarity between that crude oil sample and the target oil product; The crude oil samples in the crude oil database are sorted according to the similarity of their physical properties to the target oil product. Based on the ranking results, select several crude oil samples whose physical properties are closest to those of the target crude oil.

4. The optimization method for determining the target crude oil blending ratio according to claim 3, characterized in that, The physical property similarity is equal to the sum of the squares of the differences between the macroscopic physical property data of the crude oil sample and the corresponding macroscopic physical property data of the target oil product, multiplied by their respective weights; the weights characterize the importance of their corresponding macroscopic physical properties.

5. The optimization method for determining the target crude oil blending ratio according to claim 1, characterized in that, The penalty function for the number of crude oil types is an increasing function of the number of crude oil types; the more crude oil types there are, the larger the value of the penalty function. The penalty function for the minimum mixing ratio is a decreasing function of the minimum mixing ratio; the smaller the minimum mixing ratio, the larger the penalty function.

6. The optimization method for determining the target crude oil blending ratio according to claim 1, characterized in that, When the sum of the products of the squares of the differences between the macroscopic physical property data of the blended crude oil and the corresponding macroscopic physical property data of the target crude oil and their respective weights reaches the minimum value, it is determined that the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil has reached the minimum.

7. An optimization device for determining the blending ratio of a target crude oil, characterized in that, include: The first acquisition module is used to acquire the macroscopic physical property data of the target crude oil; The first search module is used to search for several crude oil samples that are similar to the target crude oil in the crude oil database based on the macroscopic physical property data of the target crude oil. An analysis module is used to determine the blending ratio of the crude oil samples using a mixed-integer nonlinear programming method. The analysis module is specifically used for: The blending ratio of the crude oil samples is determined based on a mixed-integer nonlinear programming method and a penalty function, wherein the penalty function includes: The penalty function for the number of crude oil types is used to limit the number of crude oil types selected for modeling from the sorted crude oil samples; The penalty function for the minimum mixing ratio is used to limit the minimum mixing ratio value in the final mixing ratio; A mixing module is used to mix the plurality of crude oil samples into blended crude oil according to the mixing ratio, and to determine the molecular composition data of the blended crude oil based on the mixing ratio and the molecular composition data of the plurality of crude oil samples. The determination module is used to determine the macroscopic physical property data of the blended crude oil based on the mixing ratio and the molecular composition data of the blended crude oil; The adjustment module is used to adjust the blending ratio based on the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil, and to remix the several crude oil samples into blended crude oil according to the adjusted blending ratio until the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil is minimized. The second acquisition module is used to acquire the adjusted mixing ratio.

8. The optimization device for determining the target crude oil blending ratio according to claim 7, characterized in that, The device further includes: a second search module, The second search module is used to search for crude oil samples that are consistent with the target crude oil in the crude oil database based on the macroscopic physical property data of the target crude oil. If a crude oil sample that is consistent with the target crude oil is found in the crude oil database, then the target crude oil is 100% the crude oil sample. If no crude oil sample that is consistent with the target crude oil is found in the crude oil database, the first search module is invoked to search for several crude oil samples that are similar to the target crude oil in the crude oil database based on the macroscopic physical property data of the target crude oil.

9. The optimization device for determining the target crude oil blending ratio according to claim 7, characterized in that, The first search module includes: The calculation unit calculates the physical property similarity between each crude oil sample in the crude oil database and the target oil product. The sorting unit sorts the crude oil samples in the crude oil database according to the similarity of their physical properties to the target oil product. Select a cell and choose several crude oil samples whose physical properties are closest to the target crude oil based on the sorting results.

10. The optimization device for determining the target crude oil blending ratio according to claim 9, characterized in that, In the adjustment module, when the sum of the squares of the differences between the macroscopic physical property data of the blended crude oil and the corresponding macroscopic physical property data of the target crude oil and the products of their respective weights reaches the minimum value, it is determined that the difference between the macroscopic physical property data of the blended crude oil and the macroscopic physical property data of the target crude oil has reached the minimum.

11. An optimization device for determining the blending ratio of a target crude oil, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the optimization method for determining the target crude oil blending ratio as described in any one of claims 1 to 6.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores one or more programs, which can be executed by one or more processors to implement the optimization method for determining the target crude oil blending ratio as described in any one of claims 1 to 6.

13. The computer-readable storage medium according to claim 12, characterized in that, The computer-readable storage medium is one of magnetic media, optical media, and semiconductor media.

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