Crude oil processing and cutting method and device

Abstract

The invention provides a crude oil processing and cutting method and device. The method comprises the steps that prior distribution of cutting temperature is determined; under the prior distribution, the posterior probability distribution of the cutting temperature is determined by taking maximization of product benefits as a target; determining the temperature of a side line cutting point based on the posterior probability distribution; and on the basis of the side line cutting point temperature, to-be-cut crude oil is machined and cut. According to the crude oil processing and cutting method and device provided by the invention, the posterior probability distribution of the cutting temperature can be determined by taking maximization of product benefits as a target under the prior distribution, namely, the to-be-cut crude oil is processed and cut with high precision based on the side line cutting point temperature determined based on the posterior probability distribution; and the maximum product benefit obtained by cutting based on the side line cutting point temperature can be ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of crude oil cutting, and in particular to a crude oil processing and cutting method and device. Background Art

[0002] In the crude oil fractions, components with different carbon numbers have different uses. C1 to C4 are natural gas and liquefied gas, which are often used as fuel gas; C5 to C10 are mainly naphtha components, which are mainly used to produce motor gasoline; C10 to C13 are mainly kerosene components, which are used to produce aviation kerosene; C13 to C20 are diesel components, which can be used as vehicle fuel; C20 to C35 are wax oil components, which are used as raw materials for hydrocracking and catalytic cracking to produce low-carbon high-value-added products; C35 and above are mainly residual oil components, which can produce asphalt products or be processed to produce light distillate oil products. The atmospheric and vacuum distillation unit that separates different fractions directly processes crude oil and cuts the crude oil into various products of different fractions to provide raw materials for subsequent processes.

[0003] At present, most of the primary processing optimization problems are converted into linear problems by introducing a pendulum structure, but this method cannot determine the side line cutting point temperature and the inaccurate estimation of the physical properties of the distillate oil. Summary of the invention

[0004] The invention provides a crude oil processing and cutting method and device, which are used to solve the defect of low crude oil processing and cutting precision in the prior art.

[0005] The present invention provides a crude oil processing and cutting method, comprising:

[0006] Determine the prior distribution of cutting temperature;

[0007] Under the prior distribution, with the goal of maximizing product benefits, determining the posterior probability distribution of the cutting temperature;

[0008] Based on the posterior probability distribution, determining the temperature of the lateral cutting point;

[0009] The crude oil to be cut is processed and cut based on the temperature of the side line cutting point.

[0010] According to a crude oil processing and cutting method provided by the present invention, the product benefit is determined based on the product price corresponding to each cutting temperature and the product output corresponding to each cutting temperature, and the product output corresponding to each cutting temperature is determined based on the narrow fraction segment evaluation data of the crude oil to be cut.

[0011] According to a crude oil processing and cutting method provided by the present invention, the product benefit is determined based on the following formula:

[0012] θ=p i × i -δ;

[0013] Among them, θ represents the product benefit, p i represents the product price corresponding to the i-th cutting temperature, x i represents the product output corresponding to the i-th cutting temperature, and δ represents the penalty term.

[0014] According to a crude oil processing cutting method provided by the present invention, under the prior distribution, with the goal of maximizing product benefits, determining the posterior probability distribution of the cutting temperature includes:

[0015] Based on the Markov Chain Monte Carlo algorithm, the prior distribution and the formula for determining the product benefit are applied to determine the posterior probability distribution.

[0016] According to a crude oil processing and cutting method provided by the present invention, the narrow fraction segment evaluation data of the crude oil to be cut is obtained by weighted averaging the evaluation data of the crude oil in different temperature segments.

[0017] According to a crude oil processing and cutting method provided by the present invention, the prior distribution of the cutting temperature is:

[0018]

[0019] Wherein, f(t) represents the prior distribution of the cutting temperature, t represents the cutting temperature, μ represents the average value of the cutting temperature, and σ represents the standard deviation of the cutting temperature.

[0020] The present invention also provides a crude oil processing and cutting device, comprising:

[0021] A first determining unit, used to determine a priori distribution of cutting temperature;

[0022] A second determination unit is used to determine the posterior probability distribution of the cutting temperature under the prior distribution with the goal of maximizing product benefits;

[0023] A third determination unit is used to determine the temperature of the lateral cutting point based on the posterior probability distribution;

[0024] The processing and cutting unit is used to process and cut the crude oil to be cut based on the temperature of the side line cutting point.

[0025] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the crude oil processing and cutting method described above is implemented.

[0026] The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the crude oil processing and cutting method as described above is implemented.

[0027] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the crude oil processing and cutting method as described above is implemented.

[0028] The crude oil processing and cutting method and device provided by the present invention, under the prior distribution, aims to maximize the product benefit. It can not only determine the posterior probability distribution of the cutting temperature, that is, realize high-precision processing and cutting of the crude oil to be cut based on the side line cutting point temperature determined based on the posterior probability distribution, but also ensure that the product benefit obtained by cutting based on the side line cutting point temperature is maximized. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0030] Figure 1 It is a schematic flow chart of the crude oil processing and cutting method provided by the present invention;

[0031] Figure 2 It is a structural schematic diagram of the crude oil processing and cutting device provided by the present invention;

[0032] Figure 3 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are 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.

[0034] At present, the primary processing optimization problem is often converted into a linear problem by introducing a pendulum structure, but this method cannot determine the temperature of the side line cutting point and the inaccurate estimation of the physical properties of the distillate oil. Therefore, it is urgent to develop a new crude oil primary processing optimization method to improve the accuracy of the estimation of the physical properties of the distillate oil and provide reliable data reference for the operation of the atmospheric and vacuum unit.

[0035] To this end, the present invention provides a crude oil processing and cutting method. Figure 1 Schematic diagram of the crude oil processing and cutting method provided by the present invention. Figure 1 As shown, the method comprises the following steps:

[0036] Step 110: Determine the prior distribution of cutting temperature.

[0037] Here, the prior distribution of cutting temperature refers to the prior distribution of cutting temperature of the crude oil to be cut, which can be determined according to the Gaussian distribution of the temperature range of each side line of atmospheric and vacuum pressure, or it can be a prior distribution set according to the actual situation. The embodiment of the present invention does not specifically limit this. Among them, processing and cutting refers to separating the crude oil to be cut into components with multiple different boiling point ranges, so that various petroleum products can be obtained. The temperature ranges of each side line of atmospheric and vacuum pressure can include: naphtha and kerosene temperature cutting point (130℃-200℃), kerosene and diesel temperature cutting point (210℃-250℃), diesel and light wax oil temperature cutting point (320℃-370℃), wax oil and vacuum residue temperature cutting point (500℃-560℃).

[0038] Optionally, the prior distribution of cutting temperature can be understood as the number of temperature intervals that the crude oil to be cut needs to be divided into, and the number of temperature intervals can be determined according to actual needs of users.

[0039] Step 120: Under the prior distribution, with the goal of maximizing product benefits, determine the posterior probability distribution of the cutting temperature.

[0040] Specifically, the posterior probability distribution of the cutting temperature can be understood as the side cutting point temperature corresponding to each temperature interval under the prior distribution. Since the prior distribution is used to characterize the number of temperature intervals that the crude oil to be cut needs to be divided into, but the side cutting point temperature corresponding to each temperature interval cannot be determined. The product benefit can be understood as the fraction product benefit corresponding to the processing and cutting of the crude oil to be cut under the prior distribution, and the product benefit can be determined based on the product price and the output of each product.

[0041] Different side-line cutting point temperatures correspond to different temperature intervals, and different temperature intervals correspond to different fraction products, and thus different temperature intervals correspond to different product outputs and product prices, that is, different temperature intervals correspond to different product benefits.

[0042] In this regard, the embodiment of the present invention aims to maximize product benefits and solves the posterior probability distribution corresponding to the maximum product benefit under the prior distribution to ensure optimal product benefits.

[0043] Step 130: Determine the temperature of the side line cutting point based on the posterior probability distribution.

[0044] Specifically, the posterior probability distribution is used to characterize the side line cutting point temperature of each temperature interval corresponding to the prior distribution, and then the side line cutting point temperature can be determined based on the posterior probability distribution.

[0045] Step 140: Process and cut the crude oil to be cut based on the temperature of the side line cutting point.

[0046] Specifically, crude oil processing and cutting refers to a series of process steps such as separation, refining and treatment of crude oil to extract narrow fraction products of different components. Among them, crude oil processing and cutting processes can include distillation, cracking, reforming, hydrogenation, catalytic cracking, etc.

[0047] Since the posterior probability distribution is determined under the prior distribution with the goal of maximizing product benefits, the lateral cutting point temperature determined based on the posterior probability distribution can ensure the maximum product benefits after cutting the crude oil to be cut.

[0048] The crude oil processing and cutting method provided by the embodiment of the present invention aims to maximize product benefits under a priori distribution. It can not only determine the posterior probability distribution of the cutting temperature, that is, to achieve high-precision processing and cutting of the crude oil to be cut based on the side line cutting point temperature determined based on the posterior probability distribution, but also ensure that the product benefits obtained by cutting based on the side line cutting point temperature are maximized.

[0049] Based on the above embodiment, the product benefit is determined based on the product price corresponding to each cutting temperature and the product yield corresponding to each cutting temperature, and the product yield corresponding to each cutting temperature is determined based on the evaluation data of the narrow fraction of the crude oil to be cut.

[0050] Specifically, different cutting temperatures correspond to different fraction products, and thus different fraction products correspond to different product prices and product yields. The product yield corresponding to each cutting temperature is determined based on the evaluation data of the narrow fraction segment of the crude oil to be cut.

[0051] Among them, the narrow-cut segment evaluation data refers to the results of physical and chemical property testing and analysis of different narrow-cut segments (also called fraction intervals) obtained by distilling crude oil during the refining process. The narrow-cut segment evaluation data usually includes temperature, density, sulfur content, freezing point, flash point, vapor pressure, composition, yield and other characteristics.

[0052] Based on any of the above embodiments, the product benefit is determined based on the following formula:

[0053] θ=p i × i -δ;

[0054] Among them, θ represents the product benefit, p i represents the product price corresponding to the i-th cutting temperature, x irepresents the product output corresponding to the i-th cutting temperature, and δ represents the penalty term.

[0055] Based on any of the above embodiments, under the prior distribution, with the goal of maximizing product benefits, determining the posterior probability distribution of the cutting temperature includes:

[0056] Based on the Markov Chain Monte Carlo algorithm, the prior distribution and the formula for determining product benefits are applied to determine the posterior probability distribution.

[0057] Specifically, Markov Chain Monte Carlo is a commonly used method in statistics to obtain samples of high-dimensional distributions. Its theory involves the stationary distribution Markov chain transition process. The main idea is: for a given probability stationary distribution π, the state transfer matrix P of the non-periodic Markov chain and the probability distribution π(x) satisfy the following for all i, j: π(i)P(i, j) = π(j)P(j, i). However, in general, the target stationary distribution π(x) and any Markov chain state transfer matrix Q do not satisfy the detailed stationary condition, that is:

[0058] π(i)Q(i, j)≠π(j)Q(j, i)

[0059] In order to make the above equation satisfy the identity condition, a state transfer process α(i, j) is introduced to the above equation to make the detailed stability condition hold, that is:

[0060] π(i)Q(i,j)α(i,j)=π(j)Q(j,i)α(j,i)

[0061] Therefore, the Markov chain state transfer matrix P corresponding to the distribution π(x) satisfies:

[0062] P(i, j) = Q(i, j) α(i, j)

[0063] That is, the state transfer matrix P of the target distribution can be constructed by any Markov chain state transfer matrix Q and α, where α is generally called the acceptance rate and takes a value between [0, 1].

[0064] The embodiment of the present invention provides a calculation process of the Markov chain Monte Carlo method:

[0065] Select the Markov chain state transfer matrix Q, stationary distribution π(t), state transfer threshold n1, sample number n2, and determine the initial state value t0;

[0066] while i<n1+n2-1:

[0067] From the conditional probability distribution Q(x|t i ) to obtain sample t * ;

[0068] Pick a random number u from [0, 1];

[0069] If u<α(t i , t * )=π(t * )Q(t * |t i ), then t i+1 =t * , otherwise t i+1 =t i ;

[0070] Finally, the temperature of the side line cutting point is calculated by analyzing the posterior probability distribution of the cutting parameter t.

[0071] Based on any of the above embodiments, the narrow fraction evaluation data of the crude oil to be cut is obtained by weighted averaging the evaluation data of the crude oil in different temperature ranges.

[0072] Specifically, the narrow fraction evaluation data may include density, API (American Petroleum Institute), freezing point, sulfur content, nitrogen content, acid value, metal content, characteristic factor, yield, etc. Among them, the yield can be calculated by blending the physical properties of each narrow fraction within the temperature range, the density can be blended by a volume linear blending method, the sulfur content, nitrogen content, acid value, metal content, etc. can be blended by a mass linear weighted calculation method, and the indicators such as freezing point and flash point can be calculated by an exponential linear blending method.

[0073] Based on any of the above embodiments, the prior distribution of cutting temperature is:

[0074]

[0075] Wherein, f(t) represents the prior distribution of cutting temperature, t represents the cutting temperature, μ represents the mean value of the cutting temperature, and σ represents the standard deviation of the cutting temperature.

[0076] The crude oil processing and cutting method provided by the embodiment of the present invention uses the Bayesian-Monte Carlo method to estimate the atmospheric and vacuum side-line cutting temperature, which solves the problem that it is difficult to give a clear cutting temperature and the distillate oil physical property estimation in the past global resource optimization method, and provides technical support for realizing the global resource optimization of refining and the real-time optimization of atmospheric and vacuum units. The crude oil processing and cutting method provided by the embodiment of the present invention has the advantages of high parameter solution accuracy, fast calculation speed, and the ability to achieve complete nonlinear optimization.

[0077] The crude oil processing and cutting device provided by the present invention is described below. The crude oil processing and cutting device described below and the crude oil processing and cutting method described above can be referred to each other.

[0078] Based on any of the above embodiments, the present invention also provides a crude oil processing and cutting device, such as Figure 2 As shown, the device comprises:

[0079] A first determining unit 210, configured to determine a priori distribution of cutting temperature;

[0080] A second determination unit 220 is used to determine the posterior probability distribution of the cutting temperature under the prior distribution with the goal of maximizing product benefits;

[0081] A third determination unit 230 is used to determine the temperature of the side line cutting point based on the posterior probability distribution;

[0082] The processing and cutting unit 240 is used to process and cut the crude oil to be cut based on the temperature of the side line cutting point.

[0083] Based on any of the above embodiments, the product benefit is determined based on the product price corresponding to each cutting temperature and the product output corresponding to each cutting temperature, and the product output corresponding to each cutting temperature is determined based on the narrow fraction evaluation data of the crude oil to be cut.

[0084] Based on any of the above embodiments, the product benefit is determined based on the following formula:

[0085] θ=p i × i -δ;

[0086] Among them, θ represents the product benefit, p i represents the product price corresponding to the i-th cutting temperature, x i represents the product output corresponding to the i-th cutting temperature, and δ represents the penalty term.

[0087] Based on any of the above embodiments, the method of determining the posterior probability distribution of the cutting temperature under the prior distribution with the goal of maximizing product benefits includes:

[0088] Based on the Markov Chain Monte Carlo algorithm, the prior distribution and the formula for determining the product benefit are applied to determine the posterior probability distribution.

[0089] Based on any of the above embodiments, the narrow fraction evaluation data of the crude oil to be cut is obtained by weighted averaging the evaluation data of the crude oil in different temperature ranges.

[0090] Based on any of the above embodiments, the prior distribution of the cutting temperature is:

[0091]

[0092] Wherein, f(t) represents the prior distribution of the cutting temperature, t represents the cutting temperature, μ represents the average value of the cutting temperature, and σ represents the standard deviation of the cutting temperature.

[0093] Figure 3 is a schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 3 As shown, the electronic device may include: a processor 310, a memory 320, a communications interface 330 and a communications bus 340, wherein the processor 310, the memory 320 and the communications interface 330 communicate with each other through the communications bus 340. The processor 310 may call the logic instructions in the memory 320 to execute the crude oil processing and cutting method, which includes: determining the prior distribution of the cutting temperature; under the prior distribution, determining the posterior probability distribution of the cutting temperature with the goal of maximizing the product benefit; determining the side line cutting point temperature based on the posterior probability distribution; and processing and cutting the crude oil to be cut based on the side line cutting point temperature.

[0094] In addition, the logic instructions in the above-mentioned memory 320 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0095] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the crude oil processing and cutting method provided by the above methods, and the method includes: determining a priori distribution of cutting temperature; under the prior distribution, with the goal of maximizing product benefits, determining the posterior probability distribution of the cutting temperature; based on the posterior probability distribution, determining the side line cutting point temperature; based on the side line cutting point temperature, processing and cutting the crude oil to be cut.

[0096] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the above-mentioned crude oil processing and cutting methods, the methods comprising: determining a priori distribution of cutting temperature; under the priori distribution, determining a posterior probability distribution of the cutting temperature with the goal of maximizing product benefits; based on the posterior probability distribution, determining the side line cutting point temperature; based on the side line cutting point temperature, processing and cutting the crude oil to be cut.

[0097] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0098] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A crude oil processing and cutting method, characterized in that: include: Determine the prior distribution of cutting temperature; Under the prior distribution, with the goal of maximizing product benefits, determining the posterior probability distribution of the cutting temperature; Based on the posterior probability distribution, determining the temperature of the lateral cutting point; The crude oil to be cut is processed and cut based on the temperature of the side line cutting point.

2. The crude oil processing and cutting method according to claim 1, characterized in that: The product benefits are determined based on the product prices corresponding to each cutting temperature and the product yields corresponding to each cutting temperature, and the product yields corresponding to each cutting temperature are determined based on the evaluation data of the narrow fractions of the crude oil to be cut.

3. The crude oil processing and cutting method according to claim 2, characterized in that: The product benefits are determined based on the following formula: θ=p i ×x i -d; Among them, θ represents the product benefit, p i represents the product price corresponding to the i-th cutting temperature, x i represents the product output corresponding to the i-th cutting temperature, and δ represents the penalty term.

4. The crude oil processing and cutting method according to claim 3, characterized in that: The method of determining the posterior probability distribution of the cutting temperature under the prior distribution with the goal of maximizing product benefits includes: Based on the Markov Chain Monte Carlo algorithm, the prior distribution and the formula for determining the product benefit are applied to determine the posterior probability distribution.

5. The crude oil processing and cutting method according to claim 2, characterized in that: The narrow fraction evaluation data of the crude oil to be cut is obtained by weighted averaging the evaluation data of the crude oil in different temperature ranges.

6. The crude oil processing and cutting method according to any one of claims 1 to 5, characterized in that: The prior distribution of the cutting temperature is: Wherein, f(t) represents the prior distribution of the cutting temperature, t represents the cutting temperature, μ represents the average value of the cutting temperature, and σ represents the standard deviation of the cutting temperature.

7. A crude oil processing and cutting device, characterized in that: include: A first determining unit, used to determine a priori distribution of cutting temperature; A second determination unit is used to determine the posterior probability distribution of the cutting temperature under the prior distribution with the goal of maximizing product benefits; A third determination unit is used to determine the temperature of the lateral cutting point based on the posterior probability distribution; The processing and cutting unit is used to process and cut the crude oil to be cut based on the temperature of the side line cutting point.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the crude oil processing and cutting method as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the crude oil processing and cutting method as described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the crude oil processing and cutting method as described in any one of claims 1 to 6 is implemented.

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