CN115060620A - Natural gas reservoir diffusion and dispersion prediction method, storage medium and terminal - Google Patents
Natural gas reservoir diffusion and dispersion prediction method, storage medium and terminal Download PDFInfo
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Abstract
The invention belongs to the technical field of natural gas reservoir detection, and discloses a natural gas reservoir diffusion and dispersion amount prediction method, a storage medium and a terminal. Analyzing the obtained target inclusion slice under a polarizing microscope, determining the position of a hydrocarbon-containing saline inclusion, and calculating the gas-liquid ratio of the hydrocarbon-containing saline inclusion slice; carrying out microscopic temperature measurement by combining a cold and hot table, and measuring the uniform temperature of the hydrocarbon-containing brine inclusion; determining components in the hydrocarbon-containing brine inclusion by laser Raman detection; taking a gas sample to determine the molar content of the components of the natural gas reservoir; PVT numerical simulation restores the molar content of the components in the inclusion; recovering the mole content of the original components of the natural gas reservoir; and predicting the diffusion dispersion amount of the natural gas reservoir. The diffusion loss of the gas reservoir is predicted by recovering the original components of the gas reservoir, so that the problem of insufficient accuracy of a mathematical model prediction result caused by insufficient knowledge of technicians on a diffusion mode in the field is solved, and the problem of inaccurate prediction result caused by errors existing when an experimental instrument measures the diffusion coefficient is solved.
Description
Technical Field
The invention belongs to the technical field of natural gas reservoir detection, and particularly relates to a natural gas reservoir diffusion and dispersion amount prediction method, a storage medium and a terminal.
Background
The diffusion of a substance is a mass-molecular state transfer mode of the substance driven by a concentration gradient, and the diffusion of molecules is not performed at all times as long as there is a difference in the concentration of the substance. Similarly, after the natural gas is gathered in the trap, natural gas molecules are inevitably diffused and dissipated through the cover layer under the action of concentration difference.
Research shows that although the diffusion loss rate of natural gas is low, the accumulated diffusion loss of natural gas is still considerable after a long geological time. According to the research results of predecessors, the diffusion and dispersion amount of natural gas in large and medium-sized gas fields in China is 1.66 multiplied by 10 8 m 3 To 2286.81X 10 8 m 3 This data not only quantitatively confirms the above observations, but also suggests that the damaging effects of diffusion on gas reservoirs are not negligible.
At present, a common method for predicting diffusion dispersion is a mathematical model derived from fick's first law or fick's second law. But the prediction method firstly ignores the diversity of natural gas diffusion modes; secondly, the influence of the natural gas on the rock diffusion coefficient, concentration gradient and diffusion loss distance due to the change of the buried depth after the natural gas is buried in the trap is neglected; errors existing in the measurement of the diffusion coefficient are ignored, and the combined action of the factors necessarily causes the prediction result to be inaccurate.
In recent years, domestic scholars have studied various PVT numerical simulation methods for hydrocarbon-containing brine inclusions in order to study the paleofluid pressure in highly mature natural gas reservoirs, so as to recover the formation pressure during inclusion formation and simulate the real molar content of each component in the inclusions.
At present, no relevant research aiming at PVT numerical simulation prediction of gas reservoir diffusion and dispersion amount exists, so that the invention provides a novel method for predicting gas reservoir diffusion and dispersion amount based on PVT numerical simulation, and certain guiding significance is generated for research on gas reservoir secondary change and prediction of resource amount.
The following detailed description of the problems and deficiencies of the prior art:
(1) the prior art is mainly based on a mathematical model derived from fick diffusion. And (4) predicting the diffusion dispersion amount of the gas reservoir based on the mathematical model, namely defaulting that the natural gas mainly generates Fick diffusion. However, the diffusion of natural gas is divided into diffusion modes such as Knudsen diffusion, Fick diffusion and excess diffusion, and is a rather complicated and slow process, which is the root of the error in the prior art.
(2) The most important parameter in the mathematical model is the diffusion coefficient, which is significantly affected by temperature, pressure, rock properties and pore filling medium properties, and it is difficult for laboratory instruments to recover rock samples to the state of underground burial for diffusion coefficient measurement, which also brings certain errors.
(3) The diffusion coefficient values measured by different methods can also be greatly different in the same sample. The natural gas diffusion coefficient test generally adopts a free hydrocarbon concentration method, a water soluble hydrocarbon concentration method and a time lag method. The natural gas concentration meanings adopted when the natural gas diffusion coefficient is measured by the method are different, and the influence factors are different, so that the measurement results are different. When the diffusion amount is predicted, if the meaning of the natural gas concentration is inconsistent with the natural gas concentration measured by the diffusion coefficient, the prediction result will generate an order of magnitude error.
Disclosure of Invention
In order to overcome the problems in the related art, the disclosed embodiment of the invention provides a natural gas reservoir diffusion dispersion prediction method, a storage medium, a terminal and application. In particular to a natural gas reservoir diffusion and dispersion prediction method based on PVT numerical simulation.
The technical scheme is as follows: a method for predicting diffusion dispersion of a natural gas reservoir comprises the following steps: the molar content of each component of the hydrocarbon-containing brine inclusion is recovered through PVT numerical simulation, the molar content of the original component of the gas reservoir is recovered by combining Henry's law, the diffusion and dispersion quantity of the gas reservoir is predicted based on the molar content of the original component, and the analysis of the secondary change of the gas reservoir and the prediction of the resource quantity are realized.
Specifically, the method comprises the following steps:
step 1, obtaining a target inclusion slice, wherein the target inclusion slice is a stratum sample obtained from a target reservoir;
step 2, observing the slice under a polarizing microscope, determining the position of a hydrocarbon-containing saline inclusion, and calculating the gas-liquid ratio of the hydrocarbon-containing saline inclusion;
step 3, carrying out microscopic temperature measurement by combining a cold-hot table, and measuring the uniform temperature of the hydrocarbon-containing saline inclusion;
step 4, determining components in the hydrocarbon-containing brine inclusion through laser Raman detection;
step 5, taking a gas sample to determine the molar content of the components of the natural gas reservoir at present;
step 6, simulating and recovering the molar content of the components in the inclusion by using a PVT numerical value;
7, recovering the mole content of the original components of the natural gas reservoir;
and 8, predicting the natural gas reservoir loss amount.
In one embodiment, in the step 1, a target inclusion sheet is obtained, and a person skilled in the art can determine a sampling position of the sheet according to actual needs.
In one embodiment, the step 2 comprises the following steps:
step 2.1, firstly observing the slice to determine the position of the hydrocarbon-containing brine inclusion;
step 2.2, measuring the sizes of the inclusion and the bubbles;
and 2.3, finally calculating the inclusion gas-liquid ratio.
In one embodiment, in step 3, the uniform temperature of the hydrocarbon-containing brine inclusion is obtained by heating the sheet through a cold and hot stage.
In one embodiment, in the step 4, a laser raman spectrum of the inclusion is acquired by a laser raman detector, and the gas phase component in the inclusion is determined according to the characteristic peak.
Wherein the liquid phase component is generally considered to be pure water.
In one embodiment, the step 5 comprises the steps of:
and 5.1, collecting a gas sample on site.
Wherein, the gas sample collection position can be decided by the person skilled in the art according to the actual need.
And 5.2, detecting by using a gas chromatograph to determine the molar content of the components in the gas sample.
In one embodiment, the step 6 comprises the steps of:
step 6.1, setting PVT numerical simulation initial component molar content according to laser Raman spectrum and gas chromatograph detection result
And 6.2, during numerical simulation, inputting the total volume and the uniform temperature of the hydrocarbon-containing brine inclusion, and continuously adjusting the initial component molar content to ensure that the volume of bubbles in the inclusion is zero at the uniform temperature and the gas-liquid ratio of the inclusion at room temperature is equal to the actually measured gas-liquid ratio, wherein at the moment, the component molar content input by the numerical simulation can be considered as the component molar content in the actual hydrocarbon-containing brine inclusion.
Wherein the room temperature was 25 ℃ and the uniform temperature was measured in step 3.
In one embodiment, the step 7 comprises the steps of:
7.1, calculating the solubility of gas in the hydrocarbon-containing brine according to the molar content of the components;
step 7.2, calculating the partial pressure of each gas component according to Henry's law;
7.3, recovering the mole content of the original components of the gas reservoir according to the relation between the partial pressure and the total pressure;
wherein, the component partial pressure/total pressure is the component mole content.
In one embodiment, the step 8 comprises the steps of:
step 8.1, calculating the molar content of the diffusion part according to the following formula:
step 8.2, calculating diffusion coefficients of the components according to the Einstein-Toasks equation:
substituting into the molecular radius of gas molecules of different components to calculate the diffusion coefficient D of each component, and further calculating the molar content c of each component in the diffusion part of the gas reservoir i 。
Step 8.3, calculating the relation of the gas reservoir resource amount before and after the gas reservoir diffusion according to the following formula:
Q a ＝Q b +Q c
and 8.4, calculating the relationship among the components according to the following formula:
Q a *a i ＝Q b *b i +Q c *c i
and 8.5, predicting the diffusion and dispersion amount of the gas reservoir according to the following formula:
wherein K is Boltzmann constant, g-cm 2 /s 2 K; t is temperature, K; r is the gas molecular radius, cm; μ is the medium viscosity coefficient. Q a M is the amount of the original resource of the gas reservoir 3 ；Q b For the gas reservoir of the present resource amount, m 3 ；Q c M is the diffusion loss of gas reservoir 3 ；a i The molar content of the original gas reservoir components,%; b i Is the molar content of the components of the existing gas reservoir,%; c. C i Is the component molar content,%, of the diffusion fraction.
Another object of the present invention is to provide a program storage medium for receiving a user input, the stored computer program causing an electronic device to execute the natural gas reservoir diffusion dispersion amount prediction method.
Another object of the present invention is to provide an information data processing terminal including a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to execute the natural gas reservoir diffusion dispersion amount prediction method.
The method for predicting the diffusion and dispersion amount of the natural gas reservoir can be applied to evaluation of secondary change and resource amount of the natural gas reservoir in different land geology and different marine environments.
By combining all the technical schemes, the invention has the advantages and positive effects that:
first, regarding the technical solution as a whole or from the perspective of products, the technical effects and advantages of the technical solution to be protected by the present invention are specifically described as follows:
(1) the method is based on a PVT numerical simulation technology, and the diffusion loss of the gas reservoir is predicted by recovering the mole content of the original components of the gas reservoir. The PVT numerical simulation technique is well established in fluid inclusion analysis, so that the original components of the finally recovered gas reservoir have high reliability.
(2) The method predicts the diffusion dispersion amount of the gas reservoir by recovering the original components of the gas reservoir, avoids the problem of insufficient accuracy of a mathematical model prediction result caused by insufficient knowledge of technicians on a diffusion mode, and also avoids the problem of inaccurate prediction result caused by errors existing when an experimental instrument measures the diffusion coefficient.
(3) The invention also provides a method for recovering the molar content of the original components of the natural gas reservoir, which is of great significance for researching the secondary change of the formed gas reservoir.
(4) The method can effectively eliminate the influence of related variables, such as concentration gradient and diffusion area of natural gas in rock, when the diffusion loss of the gas reservoir is predicted in the prior art. These variables can change with the change of reservoir burial depth after the gas reservoir is formed, resulting in inaccurate prediction results.
Secondly, as an inventive supplementary proof of the claims of the present invention, there are also presented several important aspects:
(1) the invention predicts the diffusion loss of the gas reservoir by recovering the molar content of the original components of the gas reservoir, and technically fills the gap in the field at home and abroad.
(2) The method well solves the technical problem that the current method for predicting the diffusion and dispersion of the gas reservoir is single, and meets the strong demand of common technicians in the field on the diversity of the prediction method.
(3) The gas reservoir diffusion and dispersion amount is predicted by the method, and the sum of the gas reservoir diffusion and dispersion amount and the current resource amount is the predicted value of the original resource amount of the gas reservoir. If the predicted value is smaller than the estimated value of the original resource amount of the gas reservoir by the person skilled in the art, it indicates that the resource amount may be underestimated, and the resource amount should be further mined and exploited to convert into economic benefits.
(4) The method predicts the diffusion dispersion amount of the gas reservoir by recovering the original components of the gas reservoir, avoids the problem of insufficient accuracy of a mathematical model prediction result caused by insufficient knowledge of technicians on a diffusion mode, and also avoids the problem of inaccurate prediction result caused by errors existing when an experimental instrument measures the diffusion coefficient.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a flow chart of a natural gas reservoir diffusion dispersion prediction method based on PVT numerical simulation according to an embodiment of the present invention.
Figure 2 is a schematic representation of a hydrocarbon-containing brine inclusion provided by an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather should be construed as broadly as the present invention is capable of modification in various respects, all without departing from the spirit and scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a method for predicting a natural gas reservoir diffusion loss, including the following steps:
s101, obtaining a target inclusion sheet, wherein the target inclusion sheet is a stratum sample obtained from a target reservoir;
s102, observing the slice under a polarization microscope, determining the position of a hydrocarbon-containing saline inclusion, and calculating the gas-liquid ratio of the hydrocarbon-containing saline inclusion;
s103, carrying out microscopic temperature measurement by combining a cold and hot table, and measuring the uniform temperature of the hydrocarbon-containing saline inclusion;
s104, determining components in the hydrocarbon-containing brine inclusion through laser Raman detection;
s105, taking a gas sample to determine the mole content of the components of the natural gas reservoir at present;
s106, simulating and recovering the molar content of the components in the inclusion by using a PVT numerical value;
s107, recovering the mole content of the original components of the natural gas reservoir;
and S108, predicting the natural gas reservoir loss amount.
The technical solution of the present invention will be further described with reference to the illustrative examples.
Examples
The invention provides a natural gas reservoir diffusion and dispersion amount prediction method based on PVT numerical simulation, which comprises the following steps:
step 1, under the premise that a target inclusion slice is obtained, determining the position of an inclusion (as shown in figure 2) by combining the image of an actual hydrocarbon-containing saline inclusion.
Step 2, determining the position of the hydrocarbon-containing brine inclusion, and calculating the gas-liquid ratio of the inclusion: the hydrocarbon-containing saline inclusion does not fluoresce or shows weak fluorescence under the excitation of ultraviolet light, but shows gray or dark gray under projection of single polarization light, and the central part of the inclusion has stronger light transmittance and shines.
Common inclusion gas-liquid ratio calculation methods include: laser confocal scanning microscopy, inclusion slice function fitting method at different depths, inclusion two-dimensional morphological integration method, visual measurement method and the like. In the above method, laser confocal scanning microscopy is commonly used for calculating the gas-liquid ratio of the fluorescent inclusion under ultraviolet light, and the inclusion slice function fitting method with different depths, the inclusion two-dimensional morphological integration method and the visual measurement method can be used for calculating the gas-liquid ratio of the inclusion under transmission single polarization.
Step 3, measuring the uniform temperature of the hydrocarbon-containing brine inclusion: after the position of the hydrocarbon-containing brine container is determined, the area where the hydrocarbon-containing brine container is located is cut off and is conveniently placed on a cold and hot table.
Setting the upper limit and the heating rate of a heating value, observing the change of bubbles in the inclusion under a polarizing microscope, and recording the temperature when the bubbles just disappear, namely the uniform temperature of the inclusion.
Step 4, laser Raman spectroscopy: determining a main component of a gas phase in the inclusion according to a laser Raman spectrum of the hydrocarbon-containing brine inclusion, wherein the component in the hydrocarbon-containing brine inclusion is determined according to Raman shift and a liquid phase is generally regarded as pure water.
TABLE 1 Raman Shift Table of common Components
Step 5, taking a gas sample to detect the molar content of the components: sampling on site, packaging with steel cylinders, and sending to a laboratory to detect the molar content of each component in the sample.
Step 6, PVT numerical simulation: the setting of the initial components needs to be set by referring to the detection result of the laser Raman spectrum and the detection result of the gas sample. First, the solubility of methane in water (generally 0.21% to 0.86% in terms of molar content) is used as an initial value of the total molar percentage of the gas-phase components in the envelope. Then, multiplying the initial value (e.g. 0.25%) by the ratio of each component in the present gas reservoir, i.e. the gas sample detection result, to obtain the initial component to be set.
After the initial components are set, a 'PTaqueous' module is selected from 'flash' options of the PVTsim software, and the uniform temperature of the inclusion is input. By continuously adjusting the pressure P, the value of "Vapor" under the column "Volume%" displayed by the output result is exactly zero, and the uniformity of the inclusion occurs. The total volume of the inclusion at this point was recorded and the pressure at this point was the minimum capture pressure for the initially set composition.
The 'VT' module is selected, the total volume of the inclusion and the room temperature are input (25 ℃ is generally selected), and the gas-liquid ratio of the inclusion at the room temperature is calculated. If the ratio of the gas to the liquid is consistent with the actually measured gas-liquid ratio, the initial simulation component of the inclusion is considered to be equivalent to the real component; if the gas-liquid ratio does not accord with the measured gas-liquid ratio, continuously adjusting the initial simulation component, and repeatedly operating the steps until the gas-liquid ratio calculated by the software is consistent with the measured gas-liquid ratio, wherein the input initial component can be regarded as a real component.
After the real components of the inclusion are simulated, the total volume and uniform temperature of the inclusion are input in the 'VT' module, and the minimum trapping pressure of the inclusion can be accurately obtained.
The pressure at a uniform temperature (Th +0.1) slightly above the hydrocarbon-containing brine inclusion is predicted in the "VT" module and combined with the minimum trapping pressure of the inclusion, the isochoric equation for the hydrocarbon-containing brine inclusion can be solved.
According to the prior art, the trapping temperature of a hydrocarbon-containing brine inclusion is higher than the uniform temperature by about 2 ℃, and the trapping pressure when the inclusion is formed, namely the formation pressure at that time, can be obtained by combining an isochoric equation.
And 7, restoring the molar content of the original components of the gas reservoir: suppose that: the volume of the inclusion is V, the gas-phase components in the inclusion have ymol, and the molar contents of the real components in the PVT numerical simulation are respectively
… …, the trapping pressure is P.
The solubility of each component was determined according to the solubility definition:
……
according to henry's law, the solubility of each component in the dissolved gas mixture can be determined by the respective henry constant and its partial pressure in the gas phase, i.e.:
S＝p/k
wherein S is the solubility of the component (S), mol/m 3 (ii) a p is the partial pressure of the components in the free phase, Pa; k is the Henry constant of the component Pa.mol/m 3 。
The ratio of the partial pressures between the components is then:
and because the component partial pressure/total pressure is equal to the component mole content
Therefore, the molar content (in terms of CH) of the original gas reservoir component was calculated as follows 4 For example):
CH 4 the molar content is as follows:
wherein, according to the Henry constant calculation formula, the method comprises the following steps:
1/k＝K p +K 2 -K 3
wherein, K p Is the hydration constant of the gas component;
effective gap degree of gas component in water; p is system pressure, Pa; t is the system temperature, K; b m Van der Waals volume, m, of constituent molecules 3 (ii) a R is a molar gas constant, and 8.314J/mol · K is taken. The system pressure and system temperature are the capture pressure and capture temperature found in the PVT numerical simulation.
Determining CH 4 After corresponding Henry constant, the original gas reservoir CH can be calculated 4 The molar content of the components.
In the same way, the molar contents of the other components can be calculated, and the recovery of the original components of the gas reservoir is also finished.
Step 8, predicting the diffusion and dispersion amount of the gas reservoir: assuming conservation of system mass before and after diffusion, there are:
the diffusion part comprises the following components in molar content:
the diffusion coefficient of each component was calculated from the einstein-tosks equation:
substituting into the molecular radius of gas molecules of different components to calculate the diffusion coefficient D of each component, and further calculating the molar content c of each component in the diffusion part of the gas reservoir i 。
According to the conservation of system quality, the resource amount of the gas reservoir before and after diffusion of the gas reservoir meets the following formula:
Q a ＝Q b +Q c
similarly, the components before and after the diffusion of the gas reservoir satisfy the following formula:
Q a *a i ＝Q b *b i +Q c *c i
the molar content a of the original component of the gas reservoir i Present component molar content b i The molar content of the components c in the diffusion part i And the amount of resources Q of today b The diffusion loss of the gas reservoir can be predicted by substituting the formula:
wherein K is Boltzmann constant, g cm 2 /s 2 K; t is temperature, K; r is the gas molecular radius, cm; μ is the medium viscosity coefficient. Q a M is the amount of the original resource of the gas reservoir 3 ；Q b For the gas reservoir of the present resource amount, m 3 ；Q c M is the diffusion loss of gas reservoir 3 ；a i The molar content of the original gas reservoir components,%; b i Is the molar content of the components of the existing gas reservoir,%; c. C i Is the component molar content,%, of the diffusion fraction.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made by those skilled in the art within the technical scope of the present invention disclosed herein, which is within the spirit and principle of the present invention, should be covered by the present invention.
Claims (10)
1. A method for predicting diffusion and dispersion amount of a natural gas reservoir is characterized by comprising the following steps: the molar content of each component of the hydrocarbon-containing brine inclusion is recovered through PVT numerical simulation, the molar content of the original component of the gas reservoir is recovered by combining Henry's law, the diffusion and dispersion quantity of the gas reservoir is predicted based on the molar content of the original component, and the analysis of the secondary change of the gas reservoir and the prediction of the resource quantity are realized.
2. The method of predicting gas reservoir diffusion dispersion of claim 1, wherein the step of predicting gas reservoir diffusion dispersion comprises the steps of: PVT numerical simulation restores the molar content of the components in the inclusion; recovering the mole content of the original components of the natural gas reservoir; and predicting the diffusion dispersion amount of the natural gas reservoir.
3. The method for predicting the diffusion dispersion of the natural gas reservoir according to claim 2, wherein the PVT numerical simulation for the molar content of the components in the recovery inclusion comprises the following steps:
(1) setting PVT numerical simulation initial component molar content according to the laser Raman spectrum and the detection result of the gas sample gas chromatograph;
(2) during numerical simulation, the total volume and the uniform temperature of the hydrocarbon-containing brine inclusion are input, the initial component molar content is continuously adjusted, so that the volume of bubbles in the inclusion is zero at the uniform temperature, the gas-liquid ratio of the inclusion is equal to the actually measured gas-liquid ratio at room temperature of 25 ℃, and the component molar content input by numerical simulation is the component molar content in the actual hydrocarbon-containing brine inclusion.
4. The method for predicting the diffusion dispersion of the natural gas reservoir according to claim 2, wherein the recovery of the mole content of the original components of the natural gas reservoir comprises the following steps:
1) calculating the solubility of the gas in the hydrocarbon-containing brine according to the molar content of the components;
2) calculating the partial pressure of each gas component according to Henry's law;
3) recovering the mole content of the original components of the gas reservoir according to the relationship between the partial pressure and the total pressure;
wherein, the component partial pressure/total pressure is the component mole content.
5. The method of predicting natural gas reservoir diffusion dispersion of claim 2, wherein the predicting natural gas reservoir dispersion comprises the steps of:
(i) the molar content of each component in the diffusion part is calculated according to the following formula:
(ii) the diffusion coefficients of the components were calculated according to the einstein-tosx equation:
substituting into the molecular radius of gas molecules of different components to calculate the diffusion coefficient D of each component, and further calculating the molar content c of each component in the diffusion part of the gas reservoir i ；
(iii) Calculating the relationship between the gas reservoir resource amount before and after diffusion of the gas reservoir and the original resource amount according to the following formula:
Q a ＝Q b +Q c
(iv) the relationship between the components is calculated according to the following formula:
Q a *a i ＝Q b *b i +Q c *c i
(v) predicting the diffusion dispersion of the gas reservoir according to the following formula:
wherein K is Boltzmann constant, g cm 2 /s 2 K; t is temperature, K; r is the gas molecular radius, cm; mu is the medium viscosity coefficient; q a M is the amount of the original resource of the gas reservoir 3 ；Q b For the gas reservoir of the present resource amount, m 3 ；Q c M is the diffusion loss of the gas reservoir 3 ；a i The molar content of the original gas reservoir components,%; b i Is the molar content of the components of the existing gas reservoir,%; c. C i Is the component molar content,%, of the diffusion fraction.
6. The method for predicting the diffusion and dispersion amount of a natural gas reservoir according to claim 1, wherein the step of predicting the diffusion and dispersion amount of the natural gas reservoir by recovering the molar content of the original components of the natural gas reservoir through PVT numerical simulation is performed before:
the method comprises the steps of firstly, obtaining a target inclusion slice, wherein the target inclusion slice is a stratum sample obtained from a target reservoir;
secondly, analyzing the slice under a polarizing microscope, determining the position of the hydrocarbon-containing saline inclusion, and calculating the gas-liquid ratio of the hydrocarbon-containing saline inclusion;
thirdly, carrying out microscopic temperature measurement by combining a cold and hot table, and measuring the uniform temperature of the hydrocarbon-containing saline inclusion;
fourthly, determining components in the hydrocarbon-containing brine inclusion through laser Raman detection;
and fifthly, taking a gas sample to determine the molar content of the components of the natural gas reservoir.
7. The method of claim 6, wherein the step of calculating the hydrocarbon-bearing brine inclusion gas-liquid ratio in the second step comprises the steps of: measuring the sizes of the inclusion and the bubbles; calculating the gas-liquid ratio of the inclusion;
in a third step, the sheet is heated by a cold and hot stage to obtain a homogeneous temperature of the hydrocarbon-containing brine inclusion.
8. The method for predicting diffusion dispersion of a natural gas reservoir according to claim 6, wherein in the fourth step, a laser Raman spectrum of the inclusion is obtained by a laser Raman detector, and the gas phase component in the inclusion is determined according to the characteristic peak; the liquid phase component is pure water;
in the fifth step, gas chromatography is used for detection to determine the molar content of the components in the gas sample.
9. A program storage medium for receiving a user input, the stored computer program causing an electronic device to execute the natural gas reservoir diffusion dispersion amount prediction method according to any one of claims 1 to 8.
10. An information data processing terminal, characterized in that the information data processing terminal comprises a memory and a processor, the memory stores a computer program, and the computer program, when executed by the processor, causes the processor to execute the natural gas reservoir diffusion dispersion amount prediction method according to any one of claims 1 to 8.
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