A method for estimating oil spill weathering parameters based on experimental data

Abstract

The present invention discloses a method for estimating oil spill weathering parameters based on experimental data, and relates to the field of prediction of oil spill weathering process. The method comprises the following steps: (1) obtaining oil component data; (2) constructing a weathering parameter estimation mathematical model; based on the oil component data obtained in step (1), analyzing the mathematical relationship between the oil component and the weathering parameter, and establishing a weathering parameter estimation equation; (3) obtaining hydrological and meteorological forecast data of the sea area where the oil spill is located; (4) according to the weathering parameter estimation equation established in step (2), combined with the hydrological and meteorological forecast data obtained in step (3), the oil spill weathering parameters are estimated. The oil spill weathering parameter estimation method provided by the present invention can improve the prediction accuracy of the oil spill weathering process, and provide technical support for oil spill emergency responders to quickly make scientific and reasonable oil spill emergency disposal decisions.

Description

Technical Field

[0001] The invention relates to the field of oil spill weathering process prediction, and in particular to an oil spill weathering parameter estimation method based on experimental data. Background Art

[0002] The process of oil or hydrocarbons disappearing from the sea surface after their composition and properties change over time is called oil weathering. This is the result of the combined effects of physical action, chemical oxidation and biodegradation in the natural state, which includes evaporation, dissolution, emulsification, dispersion, sedimentation, photooxidation and biodegradation. In the short term, evaporation and emulsification are important weathering processes, which play a decisive role in the residual amount of oil spills and their composition, properties and state, and affect the decision-making of oil spill emergency response and economic damage assessment. In the long term, photooxidation and biodegradation are becoming more and more important, determining the final destination of oil spills at sea and are of great significance in the global marine environmental impact assessment. The independence of the weathering process of oil spills is well known. The deeper people's understanding of weathering mechanisms, the more accurate weathering prediction models can be established.

[0003] The research methods for the evaporation process of oil spills include field observation and laboratory simulation. Taking all experimental methods into consideration, the best way to study evaporation is to analyze the composition changes based on the overall investigation of the weight method, so as to explore the evaporation mechanism and characteristics, find the correlation between experimental data and distillation data, and establish an evaporation prediction model described by easily accessible distillation curve parameters. The study of evaporation is mainly to determine the composition changes and total changes of oil. The calculation methods of evaporation rate can be divided into two types, namely quasi-component method and analytical method. The quasi-component method is to divide the oil into many components, then calculate the evaporation rate of each component, and then mix them together to calculate the total evaporation rate. The analytical method is to average the elements of the oil on the hydrocarbon spectrum and regard it as a separate substance. This method is more accurate than the quasi-component method, but it requires decomposition data of oil spill hydrocarbons, which is not easy to obtain.

[0004] In the quasi-component method model, the oil is divided into many small particles according to different boiling points. The vapor pressure of each part is calculated by empirical formula or semi-empirical formula according to the molecular weight and density of each part, the volume content (which can be converted into weight content), the boiling point of the oil and the density of the oil. Because the quasi-component method has high data requirements and is very complicated to calculate, a relatively simple algorithm is needed to calculate the evaporation process. Stive and Mackay proposed such a simple method: analytical method. This method is simplified in many aspects, such as the linear relationship between the boiling point and the evaporation loss in the liquid state. These linear relationships are determined based on the comparison between the boiling point temperature in the initial liquid state and the boiling point and the evaporation loss. Jones compared the existing quasi-component method with the analytical model. He found that the evaporation loss predicted by the existing analytical model is generally much larger than that of the quasi-component method. He believes that this difference can be explained by the different algorithm principles for calculating vapor pressure in the two models. In addition, the high evaporation loss obtained by the analytical method can also be explained by the boiling point-evaporation loss linear curve. From this we can conclude that the analytical method proposed by Stive and Mackay does not have any special requirements for distillation data.

[0005] However, the method of obtaining the required data based on standard distillation data will greatly reduce the superiority of the analytical method, such as simplicity. At the same time, the analytical method is also based on suspicious speculation, which greatly reduces the credibility of the prediction of evaporation losses. The behavioral characteristics of oil spill weathering are first determined by its composition and properties, so the composition and properties of oil spills are the basis for studying the weathering process. Looking at the current development trend, all of them adopt the calculation model based on the three-dimensional "oil particle" theory, which is constantly improved in terms of simple and fast input, rapid and accurate calculation, detailed and intuitive results, and actual inspection. In addition, the simulation of oil spills is increasingly closely integrated with geographic information system technology, information technology, graphics technology, and communication technology, and gradually developed into a comprehensive oil spill pollution information management system. In summary, the quasi-component method is the most reliable model and the most flexible. However, this model has too high requirements for data and calculation, and a simpler method (empirical formula) or a simplified model should be found.

[0006] Internationally, the research and application of weathering models started early, including Norway's SINTEF weathering model and the United States' ADIOS model. In recent years, some research institutions have achieved certain results in the research of oil spill weathering models, and they have been initially applied in water pollution emergency plans in some regions.

[0007] In summary, most of the existing weathering models are based on empirical equations and are established in combination with oil property databases. The equations used are recognized equations adopted by most modelers, but these equations, such as evaporation and emulsification rate equations, do not reflect the latest research results, and the accuracy of the results of oil spill weathering parameter estimation needs to be further improved. Summary of the invention

[0008] Based on the above technical problems, the present invention proposes a method for estimating oil spill weathering parameters based on experimental data. The method can improve the prediction accuracy of the oil spill weathering process and provide technical support for oil spill responders to quickly make scientific and reasonable decisions on oil spill emergency disposal.

[0009] The technical solution adopted by the present invention is:

[0010] A method for estimating oil spill weathering parameters based on experimental data comprises the following steps:

[0011] (1) Obtain oil composition data;

[0012] (2) Construct a mathematical model for estimating weathering parameters;

[0013] Based on the oil component data obtained in step (1), the mathematical relationship between the oil component and the weathering parameter is analyzed to establish a weathering parameter estimation equation;

[0014] (3) Obtain hydrological and meteorological forecast data for the sea area where the oil spill occurred;

[0015] (4) Calculating the weathering parameters of the oil spill based on the weathering parameter calculation equation established in step (2) and the hydrological and meteorological forecast data obtained in step (3).

[0016] Preferably, in step (1): oil product component data is obtained by literature collection or oil product experiments; the oil product component data includes the colloid, saturated fraction, asphalt, and gasoline fraction of the oil product.

[0017] Preferably, the weathering parameter estimation equation established in step (2) includes:

[0018] (21) Evaporation rate E calculation equation:

[0019] E=α1ln(τ)+β1 (1)

[0020] In formula (1): τ is the weathering time, h;

[0021] α1=α2T+β2 (2)

[0022] β1=α3T+β3 (3)

[0023] In formula (2) and formula (3): T is the sea surface temperature, °C;

[0024] In formula (2):

[0025] α2 = -0.005G + 0.114, G is gasoline content, % (4)

[0026] β2 = 0.1395S - 4.2495, S is the saturation fraction, % (5)

[0027] In formula (3):

[0028] α3 = 0.0286G + 0.0066, G is gasoline content, % (6)

[0029] β3= 0.9634As - 10.385, As is the asphaltene content; (7)

[0030] (22) The effect of evaporation rate on oil viscosity:

[0031] ν=a2E+b2 (8)

[0032] In formula (8), E is the evaporation rate, %; ν is the oil viscosity;

[0033] lna2= 0.403R - 5.142 (9)

[0034] lnb2=0.2244R + 0.8771 (10)

[0035] In formula (9) and formula (10): R is the percentage of colloid, %;

[0036] (23) The effect of evaporation rate on density:

[0037] ρ=a4E+b4 (11)

[0038] In formula (11): E is the evaporation rate, %; ρ is the density;

[0039] a4=-0.0867S+7.412 (12)

[0040] b4= -2.0792S + 986.22 (13)

[0041] In formula (12) and formula (13), S is the saturation fraction, %;

[0042] (24) Emulsification kinetic equation:

[0043]

[0044] In formula (14), R is the percentage of colloid, %; As is the asphaltene content; t is the weathering time of the oil spill, h.

[0045] Preferably, in step (3): the hydrological and meteorological forecast data includes the wind speed at 10 m above the sea surface and the sea surface temperature of the sea area where the oil spill is predicted to be located.

[0046] The beneficial technical effects of the present invention are:

[0047] The existing method of estimating the evaporation process of oil spills is basically empirical, using empirical formulas to estimate the weathering process of oil spills. However, since the chemical characteristics of crude oil determine its behavior, it is found in actual application that the accuracy of the weathering process estimated using empirical formulas is not high. Evaporation and emulsification processes are important weathering processes that directly affect the changes of oil spills in the ocean. The method for estimating oil spill weathering parameters provided by the present invention can improve the accuracy of predicting the weathering process of oil spills, and provide technical support for oil spill responders to quickly make scientific and reasonable decisions on oil spill emergency disposal. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a schematic diagram of the flow of the method for estimating oil spill weathering parameters based on experimental data of the present invention;

[0049] Figure 2 The figures are comparison diagrams of the prediction of the evaporation rate of Bohai 19-6 oil product and the laboratory results for a specific application example of the present invention, wherein (a) is the time series of the experimental observation value and the predicted value of the evaporation rate of Bohai 19-6 oil product at 15°C, (b) is the time series of the experimental observation value and the predicted value of the evaporation rate of Bohai 19-6 oil product at 7°C, (c) is the time series of the experimental observation value and the predicted value of the evaporation rate of Bohai 19-6 oil product at 35°C, and (d) is the time series of the experimental observation value and the predicted value of the evaporation rate of Bohai 19-6 oil product at 25°C. DETAILED DESCRIPTION

[0050] At present, the method of estimating the evaporation process of oil spills is basically empirical, and the weathering process of oil spills is estimated using empirical formulas. However, since the chemical characteristics of crude oil determine its behavior, it is found in actual application that the accuracy of the weathering process estimated using empirical formulas is not high. Evaporation and emulsification processes are important weathering processes that directly affect the changes of oil spills in the ocean. The present invention provides a method for estimating oil spill weathering parameters based on experimental data, which can improve the accuracy of predicting the weathering process of oil spills and provide technical support for oil spill responders to quickly make scientific and reasonable decisions on oil spill emergency disposal.

[0051] Moreover, it has been verified through specific application examples that the oil spill weathering parameter estimation method based on experimental data provided by the present invention can effectively improve the prediction accuracy of the Bohai Sea oil spill weathering process.

[0052] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0053] like Figure 1 As shown, a method for estimating oil spill weathering parameters based on experimental data includes the following steps:

[0054] (1) Obtain oil composition data;

[0055] Obtain oil component data through literature collection or oil product experiments, etc. Oil component data mainly includes colloid, saturated fraction, asphalt, and gasoline fraction of oil products.

[0056] (2) Construct a mathematical model for estimating weathering parameters;

[0057] Based on the oil component data obtained in step (1), the mathematical relationship between the oil component and the weathering parameters (evaporation, emulsification, etc.) is analyzed, and an equation for estimating the weathering parameters is established.

[0058] Specifically, the weathering parameter calculation equations established include:

[0059] (21) Evaporation rate E calculation equation:

[0060] E=α1ln(τ)+β1 (1)

[0061] In formula (1): τ is the weathering time, h;

[0062] α1=α2T+β2 (2)

[0063] β1=α3T+β3 (3)

[0064] In formula (2) and formula (3): T is the sea surface temperature, °C;

[0065] In formula (2):

[0066] α2 = -0.005G + 0.114, G is gasoline content, % (4)

[0067] β2 = 0.1395S - 4.2495, S is the saturation fraction, % (5)

[0068] In formula (3):

[0069] α3 = 0.0286G + 0.0066, G is gasoline content, % (6)

[0070] β3= 0.9634As - 10.385, As is the asphaltene content. (7)

[0071] (22) Equation for the effect of evaporation rate on oil viscosity (effect of evaporation on kinematic viscosity):

[0072] ν=a2E+b2 (8)

[0073] In formula (8), E is the evaporation rate calculated by formula (1), %; ν is the oil viscosity;

[0074] lna2= 0.403R - 5.142 (9)

[0075] lnb2=0.2244R + 0.8771 (10)

[0076] In formula (9) and formula (10): R is the percentage of colloid, %.

[0077] (23) The effect of evaporation rate on density (the effect of evaporation on density):

[0078] ρ=a4E+b4 (11)

[0079] In formula (11): E is the evaporation rate, %; ρ is the density;

[0080] a4=-0.0867S+7.412 (12)

[0081] b4= -2.0792S + 986.22 (13)

[0082] In formula (12) and formula (13), S is the saturation fraction, %.

[0083] (24) Under the action of waves, oil and water are mixed, emulsified, or dispersed. Analyzing the relationship between the experimental oil dynamic fitting parameters and the colloid content, the emulsification dynamic process is as follows:

[0084]

[0085] In formula (14), R is the percentage of colloid, %; As is the asphaltene content; t is the weathering time of the oil spill, h.

[0086] (3) Obtain hydrological and meteorological forecast data for the sea area where the oil spill is located.

[0087] The hydrological and meteorological forecast data include the wind speed at 10 m above the sea surface and the sea surface temperature of the sea area where the oil spill is located predicted based on the numerical simulation method. The forecast time of the sea temperature and sea surface wind data is not shorter than the forecast time of the weathering parameter calculation.

[0088] (4) Calculating the weathering parameters of the oil spill based on the weathering parameter calculation equation established in step (2) and the hydrological and meteorological forecast data obtained in step (3).

[0089] The present invention will be further described below in conjunction with specific application examples.

[0090] Laboratory experiments were carried out on Bohai oil products. Based on the experimental results, a mathematical relationship between oil components and oil spill weathering parameters was constructed to estimate the weathering parameters of typical Bohai oil products.

[0091] Specifically, taking a typical oil product in Bohai as an example, the weathering parameters of the oil spill are estimated. Assuming that the oil spill in Bohai is 100 tons and the sea surface temperature is 25°C, the evaporation of the oil spill after 40 hours is estimated. The characteristics of a certain oil are shown in Table 1:

[0092] Table 1

[0093]

[0094] Assuming no wind and 0.5 mm oil spill, calculate the evaporation rate (E), oil spill density and viscosity after 40 hours (t=40) at T=25°C as follows:

[0095] First, calculate the evaporation rate according to the evaporation rate calculation formula, and calculate the parameters:

[0096] α2=-0.005G+0.114, G is the gasoline content, %.

[0097] β2=0.1395S-4.2495, S is the saturation fraction, %.

[0098] α3=0.0286G+0.0066, G is the gasoline content, %.

[0099] β3=0.9634As-10.385, As is the asphaltene content.

[0100] Calculate:

[0101] α2=-0.135

[0102] β2=8.9179

[0103] α3=1.4109

[0104] β3=-10.0574

[0105] Based on the obtained sea surface temperature, T = 25°C, calculate α1 and β1.

[0106] α1=α2T+β2

[0107] β1=α3T+β3

[0108] α1=5.5429

[0109] β1=25.2151

[0110] According to the time t = 40h, calculate the evaporation rate E = α1ln (τ / h) + β1

[0111] E t＝40 =44.95%

[0112] Evaporation of spilled oil (assuming 100 tons of spilled oil) = E t＝40 × oil spill amount = 100 tons × 44.95% = 44.95 tons

[0113] The laboratory data was used to verify the results of the oil spill evaporation rate estimation. From the following Table 2 and Figure 2 From the above data, the average relative error between the predicted and observed evaporation rate of Bozhong 19-6 is 2.09% to 18.74%, and the average deviation is -8.43 to 1.26. The predicted results are consistent with the actual situation.

[0114] Table 2 shows the error statistics between the prediction and observation of evaporation loss rate of Bozhong 19-6.

[0115] Table 2

[0116]

[0117] It can be seen that for typical oil products in the Bohai Sea area, the calculation method of weathering parameters is basically empirical, and the accuracy of using empirical formulas to calculate the weathering process of oil spills is low. The method for calculating weathering parameters of typical oil products in the Bohai Sea provided by the present invention is more accurate in predicting the weathering process of Bohai Sea oil products.

Claims

1. A method for estimating oil spill weathering parameters based on experimental data, characterized in that The following steps are involved: (1) Obtain oil composition data; (2) Construct a mathematical model for estimating weathering parameters; Based on the oil component data obtained in step (1), the mathematical relationship between the oil component and the weathering parameter is analyzed to establish a weathering parameter estimation equation; (3) Obtain hydrological and meteorological forecast data for the sea area where the oil spill occurred; (4) estimating the weathering parameters of the oil spill according to the weathering parameter estimation equation established in step (2) and in combination with the hydrological and meteorological forecast data obtained in step (3); The weathering parameter calculation equation established in step (2) includes: (21) Evaporation rate E calculation equation: E=α1ln(τ)+β1 (1) In formula (1): τ is the weathering time, h; α1＝α2T+β2 (2) β1＝α3T+β3 (3) In formula (2) and formula (3), T is the sea surface temperature, °C; in formula (2): α2 = -0.005G + 0.114, G is gasoline content, % (4) β2 = 0.1395S - 4.2495, S is the saturation fraction, % (5) In formula (3): α3 = 0.0286G + 0.0066, G is gasoline content, % (6) β3= 0.9634As - 10.385, As is the asphaltene content, %; (7) (22) The effect of evaporation rate on oil viscosity: ν=a2E+b2 (8) In formula (8), E is the evaporation rate calculated by formula (1), %; ν is the oil viscosity; lna2= 0.403R - 5.142 (9) lnb2=0.2244R + 0.8771 (10) In formula (9) and formula (10): R is the percentage of colloid, %; (23) The effect of evaporation rate on density: ρ=a4E+b4 (11) In formula (11): E is the evaporation rate, %; ρ is the density; a4=-0.0867S+7.412 (12) b4= -2.0792S + 986.22 (13) In formula (12) and formula (13), S is the saturation fraction, %.

2. The method for estimating oil spill weathering parameters based on experimental data according to claim 1, characterized in that: In step (1): oil product component data is obtained by literature collection or oil product experiment; the oil product component data includes the colloid, saturated fraction, asphalt, and gasoline fraction of the oil product.

3. The method for estimating oil spill weathering parameters based on experimental data according to claim 1, characterized in that: In step (3): the hydrological and meteorological forecast data includes the wind speed at 10 m above the sea surface and the sea surface temperature of the sea area where the oil spill is predicted to be located.

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