A method for evaluating carbon utilization efficiency of a heavy oil thermal recovery technology

Abstract

The application discloses a kind of thick oil thermal recovery technology carbon utilization efficiency evaluation method, comprising the following steps: step one: data collection and pretreatment: the data of petroleum coke production, transportation, processing and utilization link are collected, pretreatment and verification are carried out;Step two: dynamic coupling modeling: a multi-physics field simultaneous model is constructed, and the reaction efficiency function is corrected in real time by reservoir numerical simulation;Step three: carbon flow analysis: according to carbon flow analysis matrix, calculate input carbon flow, effective carbon utilization and loss carbon flow, realize real-time monitoring in combination with digital twin system;Step four: index calculation: calculate total carbon utilization efficiency, primary conversion efficiency, secondary cycle efficiency, and introduce carbon negative value potential evaluation;Step five: dynamic correction: according to petroleum coke quality coefficient, system integration coefficient and biomass blending combustion coefficient, the total carbon utilization efficiency is dynamically corrected;Step six: evaluation benchmark comparison: compare the total carbon utilization efficiency calculated with the evaluation benchmark value.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of carbon utilization efficiency, in particular to a method for evaluating carbon utilization efficiency of heavy oil thermal recovery technology. BACKGROUND

[0002] Heavy oil thermal recovery technology is one of the main means of exploiting heavy oil resources at present, including steam huff and puff, steam flooding, steam assisted gravity drainage (SAGD) and fire flooding. However, these thermal recovery technologies are usually accompanied by high energy consumption and high carbon emissions. Improving the carbon utilization efficiency of heavy oil thermal recovery technology and reducing carbon emissions have become an important challenge faced by the petroleum and chemical industry. Petroleum coke, as an important carbon material in the process of heavy oil thermal recovery, its efficient utilization and low-carbon treatment are of great significance to the sustainable development of the entire industry. Petroleum coke is a byproduct of petroleum refining process, with high carbon content and low calorific value, its effective utilization and emission reduction treatment is directly related to the overall carbon utilization efficiency of heavy oil thermal recovery technology. By optimizing heavy oil thermal recovery technology, improving the utilization efficiency of carbon materials such as petroleum coke, reducing carbon emissions, and realizing green and low-carbon development.

[0003] In the traditional evaluation of carbon utilization efficiency of heavy oil thermal recovery technology, a relatively rough evaluation method is usually used. These methods often only focus on the total amount of carbon input and output, ignoring the conversion and utilization efficiency of carbon in different links and different forms. Therefore, a method for evaluating the carbon utilization efficiency of heavy oil thermal recovery technology is proposed. SUMMARY

[0004] The purpose of the present application is to solve the problems existing in the prior art, and a method for evaluating the carbon utilization efficiency of heavy oil thermal recovery technology is proposed.

[0005] In order to achieve the above purpose, the present application adopts the following technical scheme:

[0006] A method for evaluating the carbon utilization efficiency of heavy oil thermal recovery technology, comprising the following steps:

[0007] Step 1: Data collection and preprocessing: Collect data of petroleum coke production, transportation, processing and utilization, and combine with biomass raw material characteristics for preprocessing and verification;

[0008] Step 2: Dynamic coupling modeling: Construct a multi-physical field coupled model, and correct the reaction efficiency function in real time through reservoir numerical simulation;

[0009] Step 3: Carbon flow analysis: Calculate input carbon flow, effective carbon utilization and loss carbon flow according to carbon flow analysis matrix, and realize real-time monitoring combined with digital twin system;

[0010] Step 4: Index calculation: Calculate total carbon utilization efficiency (CUE), primary conversion efficiency and secondary cycle efficiency, and introduce carbon negative potential evaluation;

[0011] Step five: dynamic correction: dynamically correct the total carbon utilization efficiency according to the petroleum coke quality coefficient, system integration coefficient and biomass blending combustion coefficient;

[0012] Step six: evaluation benchmark comparison: compare the calculated total carbon utilization efficiency with the evaluation benchmark value, and evaluate the pros and cons of the technical route.

[0013] The above further comprises:

[0014] Further, in step two, the specific steps of the dynamic coupling modeling are:

[0015] Determine the basic framework of the model: determine the basic framework of the multi-physical field simultaneous model, including mass conservation, energy conservation and momentum conservation. For carbon flow analysis, mainly focus on the mass conservation equation, that is, the input, reaction consumption and output of carbon elements in the system;

[0016] Establish the carbon flow change rate equation: according to the principle of mass conservation, establish the carbon flow change rate equation, which describes the change rate of carbon elements in the system over time, including input carbon flow, reaction consumption carbon flow and diffusion loss carbon flow, the calculation formula is represented as Wherein, is the carbon concentration in the system, is the time, is the input carbon flow, is the input coefficient, is the change of input carbon flow over time, is the reaction consumption carbon flow, is the reaction coefficient, is the temperature-pressure associated reaction efficiency function, is the carbon concentration participating in the reaction, is the diffusion loss carbon flow, is the diffusion coefficient, is the carbon concentration gradient;

[0017] Determine the reaction efficiency function: the reaction efficiency function is a function of temperature and pressure , which is determined by reservoir numerical simulation. The reaction efficiency function describes the efficiency of carbon elements participating in the reaction under different temperature and pressure conditions. The following reaction efficiency function is obtained by reservoir numerical simulation, and the calculation formula is represented as Wherein, is the activation energy, set to 50 kJ / mol, is the gas constant, 8.314 J / (mol·K), is the temperature, unit: K, is the critical pressure, assumed to be 10 MPa, is the system pressure, in MPa;

[0018] Simultaneous solution of carbon flow rate change equation: Substitute the real-time corrected reaction efficiency function into the carbon flow rate change equation, combine the input carbon flow and diffusion loss carbon flow data, and simultaneously solve the equation to obtain the change of carbon concentration in the system with time.

[0019] Further, the input carbon flow calculation formula is represented as , wherein, is the carbon content of the i-th carbon source, is the amount of the i-th carbon source.

[0020] Further, the effective carbon utilization calculation formula is represented as , wherein, is the energy or carbon amount of the i-th effective carbon utilization mode, is the carbon utilization efficiency of the i-th mode.

[0021] Further, the loss carbon flow calculation formula is represented as , wherein, is the amount of the i-th loss carbon flow.

[0022] Further, the specific steps of realizing real-time monitoring by the digital twin system are:

[0023] Deploy monitoring equipment: deploy distributed fiber-optic temperature measurement + LIBS spectrum combined device in the well and on the ground to realize synchronous monitoring of carbon flow;

[0024] Establish a digital twin: use monitoring data to establish a carbon flow-heat flow-oil flow three-field coupled digital twin, with an error of <3%;

[0025] Real-time monitoring and data analysis: through the digital twin system, real-time monitoring of changes in input carbon flow, effective carbon utilization and loss carbon flow is realized, and real-time analysis of monitoring data is carried out to timely discover carbon flow abnormalities and provide basis for system optimization.

[0026] Further, the total carbon utilization efficiency calculation formula is represented as , wherein, is the input carbon flow, is the effective carbon utilization, and the primary conversion efficiency calculation formula is represented as Primary conversion efficiency target value: ≥95%, wherein, is the gasification carbon conversion rate, is the combustion efficiency, and the secondary circulation efficiency calculation formula is represented as Secondary circulation efficiency target value: >70%, wherein, is the CO2 capture rate, is the sealing utilization rate, the contribution rate of carbon emission reduction is calculated by evaluating the carbon negative potential, the actual effect in reducing carbon emission, the contribution rate of carbon emission reduction, the biomass blending ratio and the biomass directional negative carbon technology contribution rate are equal to the carbon negative potential.

[0027] Further, the petroleum coke quality coefficient calculation formula is represented as , wherein, is the S content of the petroleum coke, is the ash melting point, is the operating temperature, and the system integration coefficient is , the system integration coefficient is valued according to the system type, the gasification-power-oil driving tri-generation system takes 1.3, the microwave assisted in-situ catalytic upgrading system takes 1.2, and the single steam generation system takes 0.7, and the biomass blending coefficient calculation formula is represented as , wherein, is the biomass blending ratio, and the calculation formula for dynamically correcting the total carbon utilization efficiency is represented as .

[0028] The present application has the following beneficial effects:

[0029] In the present application, while calculating the total carbon utilization efficiency (CUE), the upgrading grading index is added, the first conversion efficiency, the secondary cycle efficiency and the system efficiency coefficient are added, so that the evaluation is more detailed and in-depth, through the multi-physical field simultaneous model and the digital twin carbon flow tracking system, the real-time monitoring and dynamic correction of the carbon flow are realized, the accuracy and timeliness of the evaluation are improved, the total carbon utilization efficiency is dynamically corrected according to the petroleum coke quality coefficient, the system integration coefficient and the biomass blending coefficient, and the biomass blending coefficient is helpful to evaluate the influence of biomass blending on the carbon utilization efficiency, and provides a scientific basis for optimizing the blending ratio. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 A step diagram of a heavy oil thermal recovery technology carbon utilization efficiency evaluation method is provided in the present application. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0032] Please refer to Figure 1 The present application is a heavy oil thermal recovery technology carbon utilization efficiency evaluation method, which comprises the following steps:

[0033] Step one: Data collection and preprocessing: Collect data on petroleum coke production, transportation, processing, and utilization, and combine with biomass feedstock characteristics for preprocessing and verification;

[0034] Step two: Dynamic coupling modeling: Construct a multi-physics coupled model and real-time correct the reaction efficiency function through reservoir numerical simulation;

[0035] Step three: Carbon flow analysis: Calculate input carbon flow, effective carbon utilization, and loss carbon flow based on carbon flow analysis matrix, and realize real-time monitoring combined with digital twin system;

[0036] Step four: Index calculation: Calculate total carbon utilization efficiency (CUE), primary conversion efficiency, and secondary cycle efficiency, and introduce carbon negative potential evaluation;

[0037] Step five: Dynamic correction: Dynamically correct the total carbon utilization efficiency based on petroleum coke quality coefficient, system integration coefficient, and biomass blending coefficient;

[0038] Step six: Evaluation benchmark comparison: Compare the calculated total carbon utilization efficiency with the evaluation benchmark value to evaluate the pros and cons of the technical route.

[0039] In one embodiment, in step two, the specific steps of the dynamic coupling modeling are:

[0040] Determine the basic framework of the model: Determine the basic framework of the multi-physics coupled model, including mass conservation, energy conservation, and momentum conservation. For carbon flow analysis, the main focus is on the mass conservation equation, i.e., the input, reaction consumption, and output of carbon elements in the system;

[0041] Establish the carbon flow change rate equation: According to the principle of mass conservation, establish the carbon flow change rate equation, which describes the change rate of carbon elements in the system over time, including input carbon flow, reaction consumption carbon flow, and diffusion loss carbon flow, the calculation formula is represented as where, is the carbon concentration in the system, is the time, is the input carbon flow, is the input coefficient, is the change of input carbon flow over time, is the reaction consumption carbon flow, is the reaction coefficient, is the temperature-pressure associated reaction efficiency function, is the carbon concentration involved in the reaction, is the diffusion loss carbon flow, is the diffusion coefficient, is the carbon concentration gradient;

[0042] Determine the reaction efficiency function: is a function of temperature and pressure , which is determined by reservoir numerical simulation, and the reaction efficiency function describes the efficiency of carbon elements participating in the reaction under different temperature and pressure conditions, and the following reaction efficiency function is obtained by reservoir numerical simulation, and the calculation formula is represented as , wherein, is the activation energy, which is set to 50 kJ / mol, is the gas constant, 8.314 J / (mol·K), is the temperature, in K, is the critical pressure, which is assumed to be 10 MPa, is the system pressure, in MPa;

[0043] Simultaneously solve the carbon flow change rate equation: substitute the real-time corrected reaction efficiency function into the carbon flow change rate equation, combine the input carbon flow and the diffusion loss carbon flow data, and simultaneously solve the equation to obtain the change of carbon concentration in the system with time.

[0044] In one embodiment, the input carbon flow calculation formula is represented as , wherein, is the carbon content of the i-th carbon source, is the amount of the i-th carbon source, assuming that the fixed carbon content of petroleum coke is 85% and the yield is 1000 tons, then the input carbon flow of petroleum coke is 85% x 1000 = 850 tons of carbon. The consumption of auxiliary fuel carbon (natural gas) is 50000 cubic meters, and the carbon content is assumed to be 75% (calculated according to methane), so the input carbon flow of natural gas is 50000 x 0.75 x 12 / 22.4 ≈ 20089.29 tons of carbon (here, cubic meters are converted to moles, and then multiplied by the molar mass of carbon). The fixed carbon content of biomass carbon (canna-based biochar) is 70%, and the yield is 200 tons, so the input carbon flow of biomass is 70% x 200 = 140 tons of carbon. The process consumables carbon (catalyst consumption) is assumed to be 10 tons, and the carbon content is 5%, so the input carbon flow of process consumables is 10 x 5% = 0.5 tons of carbon. The total input carbon flow is: = 850 + 20089.29 + 140 + 0.5 ≈ 21079.79 tons of carbon.

[0045] In one embodiment, the effective carbon utilization calculation formula is represented as , wherein, is the energy or carbon amount of the i-th effective carbon utilization mode, is the carbon utilization efficiency of the ith mode, the effective heat value carbon of the displaced heavy oil: assuming that 10,000 tons of crude oil are displaced, and the effective heat value carbon of each ton of crude oil is 0.8 tons of carbon (an assumed value), then the effective heat value carbon of the displaced heavy oil is 10,000 x 0.8 = 8,000 tons of carbon. Carbon equivalent of power output: assuming that the power output is 10,000 MWh, and the carbon equivalent of each MWh of power is 0.5 tons of carbon (an assumed value), then the carbon equivalent of the power output is 10,000 x 0.5 = 5,000 tons of carbon. Carbon sequestration: assuming that the CO2-EOR sequestration rate is 70%, and the amount of carbon that can be used for sequestration in the input carbon stream is 2,000 tons (an assumed value), then the amount of carbon sequestration is 2,000 x 70% = 1,400 tons of carbon. Carbon conversion rate for methanol synthesis: assuming that the carbon conversion rate for CO2 hydrogenation to methanol is 85%, and the amount of carbon that can be used for methanol synthesis in the input carbon stream is 1,000 tons (an assumed value), then the amount of carbon used for methanol synthesis is 1,000 x 85% = 850 tons of carbon. Total effective carbon utilization: = 8,000 + 5,000 + 1,400 + 850 = 15,250 tons of carbon.

[0046] In one embodiment, the loss carbon stream calculation formula is represented as wherein, is the amount of the ith loss carbon stream. Unconverted residual carbon: assuming that the carbon content of the ash is 5%, and the ash production is 100 tons, then the unconverted residual carbon is 100 x 5% = 5 tons of carbon. Escaped carbon emissions: assuming that the total amount of escaped carbon emissions such as CH4 and VOCs is 10 tons of carbon. System leakage carbon amount: assuming that the pipeline / equipment leakage carbon amount is 5 tons of carbon. Total loss carbon stream: = 5 + 10 + 5 = 20 tons of carbon.

[0047] In one embodiment, the specific steps for realizing real-time monitoring by the digital twin system are:

[0048] Deploying monitoring equipment: deploying distributed fiber-optic temperature measurement + LIBS spectral combination devices in the well and on the ground to realize synchronous monitoring of carbon flow;

[0049] Establishing a digital twin: using monitoring data, establishing a digital twin of the carbon flow-heat flow-oil flow three-field coupling, with an error control of <3%;

[0050] Real-time monitoring and data analysis: through the digital twin system, real-time monitoring of changes in input carbon flow, effective carbon utilization, and loss carbon flow is realized, and real-time analysis of monitoring data is carried out to timely discover carbon flow abnormalities and provide a basis for system optimization.

[0051] In one embodiment, the total carbon utilization efficiency calculation formula is represented as wherein, is the input carbon flow, is the effective carbon utilization, and the first conversion efficiency calculation formula is represented as The primary conversion efficiency target value is > 95%, wherein, is the gasification carbon conversion rate, is the combustion efficiency, and the secondary circulation efficiency calculation formula is represented as The secondary circulation efficiency target value is > 70%, wherein, is the CO2 capture rate, is the storage utilization rate, and the contribution rate of carbon emission reduction is calculated by evaluating the carbon negative potential, the actual effect in reducing carbon emissions, the contribution rate of carbon emission reduction, the biomass blending ratio, and the biomass directional negative carbon technology contribution rate are equal to the carbon negative potential.

[0052] In one embodiment, the petroleum coke quality coefficient calculation formula is represented as wherein, is the S content of the petroleum coke, is the ash melting point, is the operating temperature, and the system integration coefficient is The system integration coefficient is valued according to the system type, and the gasification-power-oil driving tri-generation system takes 1.3, the microwave-assisted in-situ catalytic upgrading system takes 1.2, and the single steam generation system takes 0.7, and the biomass blending coefficient calculation formula is represented as wherein, is the biomass blending ratio, and the calculation formula of the total carbon utilization efficiency after dynamic correction is represented as .

[0053] Although the embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and alterations can be made without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for evaluating the carbon utilization efficiency of heavy oil thermal recovery technology, characterized in that, The method comprises the following steps: Step one: data collection and pretreatment: collect data of petroleum coke production, transportation, processing and utilization links, combine with the characteristics of biomass raw materials, and perform pretreatment and verification; Step two: dynamic coupling modeling: build a multi-physical field coupled model, and correct the reaction efficiency function in real time through numerical simulation of the oil reservoir; Step three: carbon flow analysis: calculate the input carbon flow, effective carbon utilization and loss carbon flow according to the carbon flow analysis matrix, and realize real-time monitoring combined with the digital twin system; Step four: index calculation: calculate the total carbon utilization efficiency, primary conversion efficiency and secondary cycle efficiency, and introduce the carbon negative potential evaluation; Step five: dynamic correction: dynamically correct the total carbon utilization efficiency according to the petroleum coke quality coefficient, system integration coefficient and biomass blending combustion coefficient; Step six: evaluation benchmark comparison: compare the calculated total carbon utilization efficiency with the evaluation benchmark value, and evaluate the advantages and disadvantages of the technical route; In step two, the specific steps of the dynamic coupling modeling are: Determine the basic framework of the model: determine the basic framework of the multi-physical field coupled model, including mass conservation, energy conservation and momentum conservation. For carbon flow analysis, mainly focus on the mass conservation equation, that is, the input, reaction consumption and output of carbon elements in the system; Establishing carbon flow rate of change equation: according to the principle of conservation of mass, the carbon flow rate of change equation is established, which describes the rate of change of carbon elements in the system with time, including input carbon flow, reaction consumption carbon flow and diffusion loss carbon flow, and the calculation formula is represented as Wherein, C sys is the carbon concentration in the system, t is the time, α·F in (t) is the input carbon flow, α is the input coefficient, F in (t) is the change of input carbon flow with time, β·η(T,P)·C react is the reaction consumption carbon flow, β is the reaction coefficient, η(T,P) is the temperature-pressure associated reaction efficiency function, C react is the carbon concentration participating in the reaction, γ·▽C loss is the diffusion loss carbon flow, γ is the diffusion coefficient, and ▽C loss is the carbon concentration gradient; Determining the reaction efficiency function: the reaction efficiency function η (T, P) is a function of temperature T and pressure P, which is determined by reservoir numerical simulation, and describes the efficiency of carbon elements participating in the reaction under different temperature and pressure conditions. The following reaction efficiency function is obtained by reservoir numerical simulation, and the calculation formula is represented as Wherein, E a is the activation energy, R is the gas constant, T is the temperature, and the unit is K, P crit is the critical pressure, and P is the system pressure, with the unit of MPa; Solve the carbon flow change rate equation: substitute the real-time corrected reaction efficiency function into the carbon flow change rate equation, combine the input carbon flow and diffusion loss carbon flow data, and solve the equation to obtain the change of carbon concentration in the system over time; The total carbon utilization efficiency calculation formula is represented as Wherein, F in is the input carbon flow, F util is the effective carbon utilization, the primary conversion efficiency calculation formula is represented as η1=η q ×η r , wherein, η q is the gasification carbon conversion rate, η r is the combustion efficiency, the secondary cycle efficiency calculation formula is represented as η2=η co2 ×η f , wherein, η co2 is the CO2 capture rate, η f is the storage utilization rate, and the contribution rate of carbon emission reduction is calculated by evaluating the carbon negative potential power. The actual effect in reducing carbon emission, the contribution rate of carbon emission reduction, the biomass blending combustion ratio and the biomass directional negative carbon technology contribution rate are equal to the carbon negative potential. The petroleum coke quality coefficient calculation formula is expressed as K1=0.2×S -0.5 +0.8×(H / T c ), where S is the sulfur content of petroleum coke, H is the ash melting point, T c is the operating temperature, the system integration coefficient is K2, and the system integration coefficient is determined according to the system type. The system integration coefficient is 1.3 for the gasification-power generation-oil displacement trigeneration system, 1.2 for the microwave-assisted in-situ catalytic reforming system, and 0.7 for the single steam generation system. The biomass blending coefficient calculation formula is K3=1+0.5×μ s , where μ s is the biomass co-combustion ratio, and the calculation formula for the total carbon utilization efficiency after dynamic correction is expressed as CUE'=CUE×K1×K2×K3.

2. The method according to claim 1, characterized in that, The input carbon flow calculation formula is represented as F in =∑(C i ×Q i ), where C i is the carbon content of the i-th carbon source, and Q i is the quantity of the i-th carbon source.

3. The method according to claim 1, characterized in that, The calculation formula for effective carbon utilization is expressed as F util =∑(E i ×η i ), where E i is the energy or carbon content of the i-th effective carbon utilization mode, η i is the carbon utilization efficiency of the ith mode.

4. The method according to claim 1, characterized in that, The loss carbon flow calculation formula is expressed as F loss =∑(L i ), wherein L i is the amount of the ith loss carbon flow.

5. The method according to claim 1, wherein, The specific steps of realizing real-time monitoring combined with the digital twin system are: Deploy monitoring equipment: deploy distributed optical fiber temperature measurement + LIBS spectrum combined device in the well and on the ground to realize synchronous monitoring of carbon flow; Establish a digital twin: use the monitoring data to establish a carbon flow-heat flow-oil flow three-field coupled digital twin; Real-time monitoring and data analysis: through the digital twin system, real-time monitoring and data analysis of the change of input carbon flow, effective carbon utilization and loss carbon flow.

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