Reservoir porosity permeability calculation method based on multi-element thermal fluid displacement

Abstract

The invention provides a reservoir porosity and permeability calculation method based on multi-element thermal fluid displacement, which comprises the following steps: preprocessing a target stratum core, and measuring the original porosity and permeability; mounting the rock core in a rock core holder; opening a multi-element thermal fluid generator, and injecting the multi-element thermal fluid with a preset volume into the holder after the proportional metering of each component of the multi-element thermal fluid is completed; sampling and metering the product at the outlet of the core holder, metering the pressure difference between the two ends of the core holder, and detecting the current porosity through nuclear magnetic resonance equipment; repeating the displacement process, performing an experiment under different experiment conditions, and recording experiment data; summarizing experimental data, carrying out sensitivity analysis, and respectively screening out key factors which have the greatest influence on the porosity and permeability change; and based on the key factors which have the greatest influence on the porosity change, respectively establishing calculation models of the porosity and permeability of the reservoir subjected to multi-element thermal fluid displacement. According to the method, the calculation precision of the model is improved.

Description

Technical Field

[0001] The invention relates to the technical field of reservoir evaluation, and in particular to a reservoir porosity and permeability calculation method based on multi-element thermal fluid displacement. Background Art

[0002] The physical properties of reservoir rocks are affected by the formation environment and diagenesis. Under the action of diagenesis, the pore structure in the reservoir is heterogeneous. The porosity of the reservoir can reflect the ability of the rock to store fluids, and the permeability reflects the ability of the fluid to pass through the rock. The rock permeability is related to factors such as porosity and pore structure. When multiple fluids are injected into the formation, different fluids react chemically with rock minerals, which will cause the porosity and permeability of the rock to change to varying degrees. Studies on the effects of existing fluids on reservoir physical properties have shown that reaction temperature, pressure and fluid injection volume are the main influencing factors. However, existing studies on the effects of fluids on reservoir porosity and permeability changes mainly explore the effects of single-component fluids, and the research results are difficult to apply to the study of reservoir porosity and permeability changes under the action of multiple thermal fluids. Therefore, in the existing research on the changes in porosity and permeability after reservoir development, there are problems such as a single working medium component, incomplete experimental data acquisition, and low efficiency. Summary of the invention

[0003] In view of this, the present invention provides a reservoir porosity and permeability calculation method based on multi-element thermal fluid displacement to solve the above problems.

[0004] The present invention provides a reservoir porosity and permeability calculation method based on multi-component thermal fluid displacement, comprising: pre-treating a target formation core, and detecting the original porosity and original permeability of the target formation core by a nuclear magnetic resonance device, wherein the pre-treatment comprises vacuuming, water saturation, centrifugal drying and oil saturation treatment; installing the pre-treated target formation core in a core holder; opening a multi-component thermal fluid generator, and sampling and analyzing the proportion of each component in the multi-component thermal fluid through a bypass venting pipeline; when the proportion of each component of the multi-component thermal fluid is measured, opening the inlet of the core holder, closing the outlet of the bypass venting pipeline, and injecting a preset volume of the core holder into the core holder. The method comprises the steps of: sampling and metering the product at the outlet of the core holder, measuring the pressure difference at both ends of the core holder, and detecting the current porosity by the nuclear magnetic resonance device; repeating the displacement process, conducting experiments under different experimental conditions, and recording the experimental data; summarizing the experimental data and conducting sensitivity analysis, and respectively screening out the key factors that have the greatest impact on the changes in porosity and permeability; establishing a calculation model for the reservoir porosity of multi-element thermal fluid displacement based on the key factors that have the greatest impact on the changes in porosity; and establishing a calculation model for the reservoir permeability of multi-element thermal fluid displacement based on the key factors that have the greatest impact on the changes in permeability and the calculation model for porosity.

[0005] In another implementation of the present invention, the experimental conditions in the displacement process include multi-component thermal fluid component ratio, cumulative injection volume multiple, fluid flow rate and injection temperature.

[0006] In another implementation of the present invention, the calculation model of porosity change rate and the calculation model of permeability change rate are respectively established based on the key factors that have the greatest impact on the changes in porosity and permeability, including: the influence of the experimental conditions on the changes in porosity and permeability are, from large to small, injection temperature, cumulative injection volume multiples, fluid flow rate, and multi-component thermal fluid component ratio, and the injection temperature and cumulative injection volume multiples are the key factors with the greatest impact; nonlinear curve fitting analysis is performed on different injection temperatures, different cumulative injection volume multiples, and the porosity change rate and permeability change rate, and a calculation model of the two and the porosity change rate and permeability change rate is established.

[0007] In another implementation of the present invention, the porosity calculation model is expressed as:

[0008] φ=ae (bT+cPV) φ0

[0009] Among them, φ0 is the original porosity of the target formation core, %; T is the injection temperature, °C; PV is the cumulative injection volume multiple; a, b, c are the coefficients to be measured.

[0010] In another implementation of the present invention, the permeability calculation model is expressed as:

[0011]

[0012] Among them, K o is the original permeability of the target formation core, mD; n is the coefficient to be tested; φ is the porosity after the experiment, %; φ o is the original porosity of the target formation core, %.

[0013] The reservoir porosity and permeability calculation method based on multi-component thermal fluid displacement of the present invention uses the principle of nuclear magnetic resonance to track and measure the porosity data of the core, can evaluate the core porosity change online, guide the time to stop injecting the multi-component thermal fluid, and shorten the experimental period; at the same time, by determining the main controlling factors of the reservoir physical property changes under the influence of the multi-component thermal fluid, the model structure is optimized while the model calculation accuracy is improved, and a reliable reservoir porosity and permeability calculation method is derived. The method provides a means of standardized calculation and repeatable evaluation for accurately evaluating the change law of porosity and permeability after multi-component thermal fluid displacement with different component proportions, and provides technical support for subsequent production capacity evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. By reading the detailed description of the following implementations, the advantages and benefits of the solutions become clear to those skilled in the art. The drawings are only used to illustrate the preferred implementations and are not to be considered as limiting the present invention.

[0016] In the attached picture:

[0017] Figure 1 The figure is a schematic flow chart of a method for calculating reservoir porosity and permeability based on multi-component thermal fluid displacement according to an embodiment of the present invention.

[0018] Figure 2 Schematic diagram of the relationship between the injection temperature of the multi-element thermal fluid and the porosity change rate according to an embodiment of the present invention.

[0019] Figure 3 Schematic diagram of the relationship between the injection temperature and the permeability change rate of the multi-component thermal fluid according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be described clearly and in detail below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in the field based on the embodiments in the embodiments of the present invention should fall within the scope of protection of the embodiments of the present invention.

[0021] Figure 1 A schematic flow chart of a reservoir porosity and permeability calculation method based on multi-component thermal fluid displacement provided in an embodiment of the present invention. The multi-component thermal fluid nuclear magnetic online displacement experiment is carried out in accordance with the process specified in the "Rock Sample Nuclear Magnetic Resonance Parameter Laboratory Measurement Specification SY / T6490-2023" standard. Figure 1 As shown, this embodiment mainly includes:

[0022] S101, pre-treating the target formation core, and detecting the original porosity and original permeability of the target formation core by nuclear magnetic resonance equipment, wherein the pre-treatment includes vacuuming, water saturation, centrifugal drying and oil saturation treatment.

[0023] For example, the rock samples of the target formation core are pretreated before the experiment, and the rock samples are placed in a vacuum pressurized saturation device (saturated with water) for pure water saturation. After saturation, the rock samples are placed in a nuclear magnetic detection device for testing, and the porosity and permeability of the rock samples in the original state are analyzed. After the test, the rock samples are placed in a constant temperature drying oven, and after drying, the rock samples are placed in a vacuum pressurized saturation device (saturated with oil) for oil saturation operation, and taken out before the experiment. The samples that have not been tested are stored in oil.

[0024] S102, installing the pre-treated target formation core in a core holder.

[0025] S103, opening the multi-component thermal fluid generator, and taking samples through the bypass vent line to analyze the proportion of each component in the multi-component thermal fluid.

[0026] Exemplarily, the valves of the multi-component thermal fluid delivery pipeline and the multi-component thermal fluid venting pipeline are opened, the clamp inlet is closed, the injection rate of each component of the multi-component thermal fluid is adjusted, and samples are taken in the venting pipeline to analyze the proportion of the multi-component thermal fluid components.

[0027] S104, when the proportions of the components of the multi-component thermal fluid are measured, the inlet of the core holder is opened, the outlet of the bypass vent line is closed, and a preset volume of the multi-component thermal fluid is injected into the core holder.

[0028] Exemplarily, when the proportions of the fluid components are measured to be stable, the inlet of the holder is opened and the bypass vent line valve is closed.

[0029] S105, sampling and metering the product at the core holder outlet, measuring the pressure difference at both ends of the core holder, and detecting the current porosity by the nuclear magnetic resonance device.

[0030] S106. Repeat the above displacement process, conduct experiments under different experimental conditions, and record the experimental data.

[0031] For example, 16 groups of orthogonal experiments were designed with injection temperature, injection rate, fluid component ratio and cumulative injection volume multiples as the main influencing factors to study their effects on reservoir properties. The injection ratio was converted into fluid flow rate for experimental research. The experimental factors are shown in Table 1.

[0032] Table 1 Design of 16 orthogonal experimental schemes

[0033]

[0034] The rock samples of the target formation core after the experiment were processed, washed repeatedly with distilled water for 3 times, and then placed in a constant temperature drying oven for 2 hours. After drying, the rock samples were placed in a vacuum pressurized saturation device (saturated water) for pure water saturation and pressurization to 13MPa for 2 hours. After saturation, the rock samples were placed in a nuclear magnetic detection device for a test, and then the rock samples were centrifuged twice and tested, and compared with the data before displacement, to analyze the changes in porosity and permeability of the rock samples after multi-component thermal fluid displacement.

[0035] S107. Summarize the experimental data and conduct sensitivity analysis to screen out the key factors that have the greatest impact on the changes in porosity and permeability.

[0036] For example, the sensitivity analysis of the experimental data results is performed by the range analysis method to select the most important factors affecting the reservoir porosity change. Among them, in order to study the influence of different injection factors on the reservoir porosity after the multi-component thermal fluid is injected into the formation, the present invention selects 4 multi-component thermal fluid injection factors and 4 levels for orthogonal experiments. The injection factors and the number of levels of this experiment are shown in Table 2. The purpose is to select the key factors affecting the reservoir porosity change by analyzing the orthogonal experimental results, where the fluid flow rate represents the component ratio of the injected multi-component thermal fluid.

[0037] Table 2 Factors and levels affecting porosity change

[0038]

[0039] The porosity and porosity change rate after the reaction corresponding to each group of experiments after the orthogonal experiment are shown in Table 3, where the blank column is used as the error column in the orthogonal experiment analysis. It can be seen from Table 3 that the porosity change rate under different experiments is in the range of 0.8% to 15%.

[0040] Table 3 Porosity change rate corresponding to different experiments

[0041]

[0042]

[0043] S108. Based on the key factors that have the greatest impact on porosity changes, a calculation model for reservoir porosity driven by multi-component thermal fluids is established.

[0044] S109. Combining the key factors that have the greatest impact on permeability changes with the porosity calculation model, a calculation model for reservoir permeability driven by multi-element thermal fluids is established.

[0045] The reservoir porosity and permeability calculation method based on multi-component thermal fluid displacement of the present invention uses the principle of nuclear magnetic resonance to track and measure the porosity data of the core, can evaluate the core porosity change online, guide the time to stop injecting the multi-component thermal fluid, and shorten the experimental period; at the same time, by determining the main controlling factors of the reservoir physical property changes under the influence of the multi-component thermal fluid, the model structure is optimized while the model calculation accuracy is improved, and a reliable reservoir porosity and permeability calculation method is derived. The method provides a means of standardized calculation and repeatable evaluation for accurately evaluating the change law of porosity and permeability after multi-component thermal fluid displacement with different component proportions, and provides technical support for subsequent production capacity evaluation.

[0046] In another implementation of the present invention, the experimental conditions in the displacement process include multi-component thermal fluid component ratio, cumulative injection volume multiple, fluid flow rate and injection temperature.

[0047] In another implementation of the present invention, the calculation model of porosity change rate and the calculation model of permeability change rate are respectively established based on the key factors that have the greatest impact on the changes in porosity and permeability, including: the influence of the experimental conditions on the changes in porosity and permeability are, from large to small, injection temperature, cumulative injection volume multiples, fluid flow rate, and multi-component thermal fluid component ratio, and the injection temperature and cumulative injection volume multiples are the key factors with the greatest impact; nonlinear curve fitting analysis is performed on different injection temperatures, different cumulative injection volume multiples, and the porosity change rate and permeability change rate, and a calculation model of the two and the porosity change rate and permeability change rate is established.

[0048] For example, the porosity change rate under different injection factors in Table 3 is subjected to a range analysis, and Table 4 is the range analysis result of the orthogonal test result of the porosity change rate, where K i Sum the experimental data of the i-th level of a factor, k i The corresponding K i The range R is the range value of a factor, which is calculated as the difference between the maximum and minimum values ​​of k of the corresponding factor and can be used to compare the advantages and disadvantages of each factor.

[0049] From the range analysis of the orthogonal experimental results in Table 4, it can be seen that the influence of the four factors on the porosity change during the multi-component thermal fluid displacement process is in the following order: injection temperature (6.83) > cumulative injection volume multiple (5.54) > injection rate (1.95) > injected multi-component thermal fluid component ratio (1.9235), among which the positive difference between the injection temperature and the cumulative injection volume is much higher than the blank column error value (2.255), and the range R between the injected multi-component thermal fluid component ratio and the injection rate is close to the blank column error extreme value. Therefore, the injection temperature and the cumulative injection volume multiple are the key factors affecting the rock porosity change, that is, the porosity change after multi-component thermal fluid displacement is mainly related to the injection temperature and the cumulative injection volume.

[0050] Table 4 Range analysis of orthogonal test results of porosity change rate

[0051]

[0052]

[0053] In order to study the effect of different injection factors on reservoir permeability in multi-element thermal fluid displacement reservoirs, four influencing factors and four levels were selected for L 16 The orthogonal experiment uses the same method as the above method. Finally, it can be known that the influence of multi-component thermal fluid displacement on permeability change is in the following order: injection temperature (16.9125) > cumulative injection volume multiple (15.5825) > multi-component thermal fluid component ratio (3.5025) > injection rate (2.8025). The positive difference between injection temperature and cumulative injection volume is much higher than the blank column error value (3.81). These two factors are the key factors, that is, the porosity change after multi-component thermal fluid displacement is mainly related to the injection temperature and cumulative injection volume.

[0054] After analyzing the results of orthogonal experiments, it was found that the effects of multi-element thermal fluid displacement on reservoir porosity and permeability are related to the injection temperature and cumulative injection volume of the fluid. Therefore, the porosity and permeability were studied based on these two key factors. The selected data are shown in Table 5.

[0055] Table 5 Core permeability and porosity test data before and after multi-component thermal fluid displacement

[0056]

[0057]

[0058] By using the data analysis module in Origin software to perform nonlinear curve fitting analysis on the relationship between different injection temperatures and the porosity change rate and permeability change rate, it is found that the relationship between the temperature and the porosity change rate and permeability change rate conforms to the ExpDecl model, such as Figure 2 and Figure 3 As shown in the figure, the fitting relationship between the cumulative injection volume multiple and the porosity change rate and the permeability change rate also conforms to the ExpDecl model, and will not be further described here.

[0059] In another implementation of the present invention, the porosity calculation model is expressed as:

[0060] φ=ae (bT+cPV) φ0

[0061] Among them, φ0 is the original porosity of the target formation core, %; T is the injection temperature, °C; PV is the cumulative injection volume multiple; a, b, c are the coefficients to be measured.

[0062] For example, in the process of CO2 displacement, the temperature and pressure have an exponential relationship on the change rate of rock porosity and permeability. The relationship is established after mathematical regression of the experimental data:

[0063] Y=ae bX (1-1)

[0064] The above formula is linearized and the logarithmic power of both ends is reduced. The equation after processing is expressed as:

[0065] lgY=lga+bX (1-2)

[0066] Expanding the above formula and taking the average, we get:

[0067]

[0068] Among them, Q is a function related to a and b, X is the independent variable, and Y is the degree of dissolution. The partial derivatives of a and b are obtained for Q, and the equations to be solved are:

[0069]

[0070] After regression using the above method, the mathematical characterization equation of the influence of key parameters on porosity under CO2 displacement was obtained:

[0071] φ1=6.695×10 -7 e (0.0214T+0.728p) (1-5)

[0072] The error value of this equation is very small and the accuracy is high. Among them, φ1 is the porosity change value, %; T is the temperature, ℃; p is the pressure, MPa.

[0073] The porosity change caused by displacement is:

[0074] φ2=6.695×10 -7 e (0.0214T+0.728p) φ0 (1-6)

[0075] Among them, φ2 is the porosity change value under the influence of CO2 displacement, %; φ0 is the original porosity of the target formation core, %.

[0076] Since the injection temperature and cumulative injection volume multiples in displacement are key factors and the injection temperature and cumulative injection volume multiples under the influence of a single factor are exponentially related to the rock porosity change rate, they satisfy the ExpDecl model and are similar to the porosity change caused by CO2 displacement, so the relationship is constructed:

[0077] φ3=ae (bT+cPV) φ0 (1-7)

[0078] Among them, φ3 is the porosity change value under the influence of multi-element thermal fluid displacement, T is the injection temperature, °C; PV is the cumulative injection volume multiple, and a, b, and c are the coefficients to be determined.

[0079] Formula (1-1) is curve-fitted with the experimental data in step S106 to obtain the fitted formula. The change rate obtained from the experimental data is matched with the fitted formula to calculate the coefficients a, b, and c to be measured. The calculated porosity change rate and related parameters are shown in Table 6.

[0080] Table 6. Table of relevant parameters for permeability change rate curve fitting

[0081]

[0082]

[0083] Fitting result R 2 The fitting effect is good. The coefficients to be measured are a, b, and c, respectively. Substituting them into formula (1-7), the formula for porosity change under the influence of multi-element thermal fluid displacement is obtained:

[0084] φ3=9.058×10 -3 e (0.0049T+0.0455PV) φ0 (1-8)

[0085] In another implementation of the present invention, the permeability calculation model is expressed as:

[0086]

[0087] Among them, K o is the original permeability of the target formation core, mD; n is the coefficient to be tested; φ is the porosity after the experiment, %; φ o is the original porosity of the target formation core, %.

[0088] Exemplarily, the porosity-permeability relationship refers to the Kozeny-Carman equation, and the formula (1-3) is curve-fitted with the experiment in step S106 to obtain the fitted formula. The change rate obtained by the experimental data is matched with the fitted formula to calculate the coefficient n to be measured. The calculated permeability and related parameters are shown in Table 7.

[0089] Table 7. Related parameters of permeability curve fitting after displacement

[0090]

[0091]

[0092] The square error of the correlation coefficient of the fitting result is 0.981, and the fitting effect is good. The coefficient n to be measured is 0.37. Substitute formula (1-8) into the permeability calculation formula under the influence of multi-element thermal fluid displacement:

[0093]

[0094] Among them, K is the permeability of the reservoir after multi-component thermal fluid displacement, mD; K0 is the initial permeability of the reservoir, mD; T is the injection temperature, °C; PV is the cumulative injection volume multiple; φ0 is the original porosity of the target formation core, %.

[0095] In another aspect of the present invention, an electronic device includes: a processor, a memory, a communication bus, and a communication interface.

[0096] in:

[0097] The processor, memory and communication interface communicate with each other through a communication bus.

[0098] Communication interface, used to communicate with other electronic devices or servers.

[0099] The processor is used to execute the program, and specifically can execute the steps of any one of the reservoir porosity and permeability calculation methods based on multi-element thermal fluid displacement in the above embodiments.

[0100] Specifically, the program may include program codes including computer operation instructions.

[0101] The processor may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The one or more processors included in the smart device may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0102] The memory is used to store programs. The memory may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory.

[0103] The program can be specifically used to enable the processor to execute the steps of any one of the reservoir porosity and permeability calculation methods based on multi-element thermal fluid displacement described in the embodiment. The specific implementation of each step in the program can refer to the corresponding descriptions in the steps and units executed by any one of the reservoir porosity and permeability calculation methods based on multi-element thermal fluid displacement in the above steps, which will not be repeated here. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described equipment and modules can refer to the corresponding process description in the aforementioned method embodiment.

[0104] The exemplary embodiments of the present application also provide a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the methods of the various embodiments of the present application.

[0105] The above-described method according to an embodiment of the present invention may be implemented in hardware, firmware, or as software or computer code that may be stored in a recording medium (such as a CD ROM, RAM, floppy disk, hard disk, or magneto-optical disk), or as computer code that is originally stored in a remote recording medium or a non-temporary machine-readable medium downloaded over a network and will be stored in a local recording medium, so that the method described herein may be stored in such software processing on a recording medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware (such as an ASIC or FPGA). It is understood that a computer, processor, microprocessor controller, or programmable hardware includes a storage component (e.g., RAM, ROM, flash memory, etc.) that can store or receive software or computer code, and when the software or computer code is accessed and executed by a computer, processor, or hardware, the method described herein is implemented. In addition, when a general-purpose computer accesses the code for implementing the method shown herein, the execution of the code converts the general-purpose computer into a dedicated computer for executing the method shown herein.

[0106] Thus far, specific embodiments of the present invention have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims may be performed in a different order and still achieve the desired results. Additionally, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing may be advantageous.

[0107] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0108] In the description of the present invention, the terms "first" and "second" are only used to facilitate the description of different components or names, and cannot be understood as indicating or implying a sequential relationship, relative importance, or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features.

[0109] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0110] It should be noted that although the specific embodiments of the present invention are described in detail in conjunction with the accompanying drawings, it should not be understood as limiting the scope of protection of the present invention. Within the scope described in the claims, various modifications and variations that can be made by those skilled in the art without creative work still belong to the scope of protection of the present invention.

[0111] The examples of the embodiments of the present invention are intended to concisely illustrate the technical features of the embodiments of the present invention so that those skilled in the art can intuitively understand the technical features of the embodiments of the present invention, and are not intended to be improper limitations of the embodiments of the present invention.

[0112] 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 reservoir porosity and permeability calculation method based on multi-component thermal fluid displacement, characterized in that: include: Pre-treating the target formation core and detecting the original porosity and original permeability of the target formation core by nuclear magnetic resonance equipment, wherein the pre-treatment includes vacuuming, water saturation, centrifugal drying and oil saturation treatment; Installing the pre-treated target formation core in a core holder; Opening the multi-component thermal fluid generator, and sampling and analyzing the proportion of each component in the multi-component thermal fluid through a bypass vent line; When the proportions of the components of the multi-component thermal fluid are measured, the inlet of the core holder is opened, the outlet of the bypass vent line is closed, and a preset volume of the multi-component thermal fluid is injected into the core holder; Sampling and metering the product at the core holder outlet, measuring the pressure difference at both ends of the core holder, and detecting the current porosity by the nuclear magnetic resonance device; Repeat the above displacement process, conduct experiments under different experimental conditions, and record the experimental data; The experimental data are summarized and sensitivity analysis is performed to screen out the key factors that have the greatest impact on the changes in porosity and permeability; Based on the key factors that have the greatest impact on porosity changes, a calculation model for reservoir porosity under multi-component thermal fluid displacement is established; By combining the key factors that have the greatest impact on permeability changes and the porosity calculation model, a calculation model for reservoir permeability driven by multi-component thermal fluids is established.

2. The method according to claim 1, characterized in that The experimental conditions in the displacement process include multi-component thermal fluid component ratio, cumulative injection volume multiple, fluid flow rate and injection temperature.

3. The method according to claim 2, characterized in that The calculation model of porosity change rate and the calculation model of permeability change rate are established based on the key factors that have the greatest impact on the porosity and permeability changes, respectively, including: The influence of the experimental conditions on the porosity and permeability changes is, from greatest to least, injection temperature, cumulative injection volume multiple, fluid flow rate, and multi-component thermal fluid component ratio, wherein the injection temperature and cumulative injection volume multiple are the most influential key factors; Nonlinear curve fitting analysis was performed on different injection temperatures, different cumulative injection volume multiples and the porosity change rate and permeability change rate, and a calculation model of the two and the porosity change rate and permeability change rate was established.

4. The method according to claim 3, characterized in that The porosity calculation model is expressed as: φ=ae (bT+cPV) φ0 Among them, φ0 is the original porosity of the target formation core, %; T is the injection temperature, °C; PV is the cumulative injection volume multiple; a, b, c are the coefficients to be measured.

5. The method according to claim 4, characterized in that The permeability calculation model is expressed as: Among them, K o is the original permeability of the target formation core, mD; n is the coefficient to be tested; φ is the porosity after the experiment, %; φ o is the original porosity of the target formation core, %.

Images