Intelligent evaluation method for nanometer space shale oil in-situ phase state and shale oil reservoir type

Abstract

The invention relates to the technical field of shale oil phase state evaluation, in particular to a nanometer space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method which comprises the steps that a pressure maintaining rock core is obtained from a shale target layer series; the method comprises the following steps: taking out a blocky frozen-state pressure-maintaining rock core, quickly crushing, putting into a pyrolysis device sample boat, feeding into a pyrolysis furnace, acquiring pyrolysis data at each acquisition moment in a pyrolysis process, determining a comparison interval coefficient at the current moment, and constructing an accumulated comparison coefficient for adjusting control parameters so as to adjust the pyrolysis temperature; the method comprises the following steps: preparing a pressure-maintaining rock core, rapidly heating a heat release sample, separating the sample into various monomeric compounds to obtain a pressure-maintaining rock core pyrolysis gas chromatography spectrogram, calculating the content of each component, using simulation software and combining thermodynamic parameters of oil and gas components to obtain a shale oil P-T phase diagram, and further determining a nano space shale oil in-situ phase state and a shale oil reservoir type. The accuracy, efficiency and convenience of shale oil phase state and oil reservoir type evaluation are improved.

Description

Technical Field

[0001] The present application relates to the technical field of shale oil phase state evaluation, and specifically to a method for intelligently evaluating the in-situ phase state of nano-space shale oil and shale oil reservoir types. Background Art

[0002] Crude oil and natural gas are both mixtures of various hydrocarbon and non-hydrocarbon substances, typically found in high-temperature, high-pressure reservoirs. Crude oil, in particular, contains a significant amount of dissolved hydrocarbon gas, resulting in significant differences between the physical and chemical properties of the fluids in the reservoir and those at the surface. To rationally develop oil and gas reservoirs, particularly continental shale oil, which resides in micro- and nano-pores, it is essential to understand the in situ properties of oil and gas underground and their temperature and pressure variations. This requires clarifying the phase behavior of oil and gas at the nano-pore scale, allowing for the assessment of shale oil reservoir types, crude oil and natural gas reserves, mobility, recovery levels, optimal production rates, and optimal measures to reduce production decline and enhance recovery. Therefore, accurate assessment of reservoir fluid properties and reservoir types is essential for establishing and simulating the production processes of crude oil and natural gas throughout the hydrocarbon reservoir production cycle. Intelligent sensor systems can play a role in these experiments and data processing processes, improving accuracy and efficiency.

[0003] Generally, the composition of reservoir fluids is considered the most important factor influencing their pressure-volume-temperature (PVT) characteristics. Reservoir fluid phase characteristics and formation temperature are two important influencing factors, and the determination of reservoir fluid type is also based on these two factors. Currently, the best way to describe these properties is to conduct laboratory tests on real reservoir oil and gas fluid samples, combining equations of state (EOS) and phase diagram calculations and analysis to predict oil and gas phase characteristics. Examples include SYT 5542-2009, "Method for Physical Property Analysis of Oil and Gas Reservoir Fluids," CN201811386775.1, "High-Pressure Physical Property Experimental Method for Openhole Well Samples," CN201811186578.5, "Method for Analyzing Heavy Oil Well Flow," CN201610621336.9, "Method and Apparatus for Black Oil Reservoir Simulation," and CN202110498443.8, "Method and Apparatus for Determining Thermodynamic Parameters of Reservoir Fluid PVT Phase Characteristics."

[0004] The above methods usually require the use of dehydrated surface oil samples, separator gas samples and gas-oil ratio data to prepare formation fluids. However, the pore diameter of shale oil reservoirs is small, mainly at the nanometer level, and the natural seepage capacity is extremely weak. It is necessary to use fracturing measures to artificially create fractures and transform the reservoir. After the transformation, shale oil enters the fractures and wellbore from the matrix pores. In this process, the composition and properties of the shale oil will change. The oil and gas samples obtained at the bottom of the well or the wellhead do not represent the original underground oil and gas composition characteristics. During the fracturing process of shale oil reservoirs, due to the addition of "thousands of cubic meters of sand and tens of thousands of cubic meters of liquid", a large amount of fracturing fluid is often produced at the same time during shale oil extraction. It is difficult to meet the sampling requirements of a water production rate of less than 5%. The success rate of obtaining well fluids that meet the standards and represent the properties of the original reservoir is extremely low. During phase analysis, it is difficult to obtain the high-pressure physical properties of shale oil and to determine the gas-oil ratio of surface crude oil. At the same time, During the dehydration, flash evaporation and other testing processes of the samples, the light oil and gas components are volatilized and lost, causing the obtained oil and gas component parameters to deviate from the oil and gas components in the formation, affecting the accuracy of the reservoir numerical simulation results; on the other hand, reservoir numerical simulation requires prior PVT phase state experiments such as differential degassing, isocomponent expansion, isochoric depletion, separator experiments and expansion experiments to obtain phase characteristic thermodynamic parameters such as differential degassing, isocomponent expansion, isochoric depletion, separator experiments and expansion experiments, and then use numerical simulation software to fit the experimental data to obtain the fluid PVT phase characteristic thermodynamic parameters, which is difficult to experiment with. Furthermore, because highly mature shale oil is generally light in quality and gas and light hydrocarbon components evaporate rapidly, it is difficult to determine the gas-to-oil ratio by compounding wellhead samples with crude oil. This significantly reduces the credibility of shale oil phase states obtained through high-pressure physical property experiments. Finally, unlike the oil and gas phase states in conventional reservoirs, shale oil reservoirs have small pore diameters, primarily at the nanoscale. These nanopores increase fluid retention in the pores, promote the formation of adsorbed gas, reduce the amount of free-phase oil and gas available for flow, and increase the difficulty of extraction. The influence of factors such as capillary forces, pore structure, fluid-solid interactions, and intermolecular forces on shale oil phase states cannot be ignored. Therefore, in-depth research on shale oil phase states, shale oil reservoir types, and their dynamic evolution during development under in-situ confined underground conditions is crucial for evaluating shale oil productivity, reducing production decline rates, and improving oil recovery, and is of both theoretical and practical significance. Summary of the Invention

[0005] In order to solve the above technical problems, this application provides an intelligent evaluation method for the in-situ phase state of nano-space shale oil and the type of shale oil reservoir. By establishing a full-process liquid nitrogen freezing, cutting, transportation, preparation and analysis of pressure-maintained cores, a relatively complete original hydrocarbon composition of shale oil is obtained, and confined nano-space shale oil phase state and shale oil reservoir type analysis is carried out to solve existing problems.

[0006] The nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method of this application adopts the following technical solutions:

[0007] One embodiment of the present application provides a method for intelligently evaluating the in-situ phase state and reservoir type of shale oil in nanospace, including the following steps:

[0008] S1, obtain pressure-maintained cores from the shale target formation;

[0009] S2, through the pressure-maintained core pyrolysis gas chromatography quantitative analysis, obtain the pressure-maintained core molecular composition and component content, the specific acquisition steps are:

[0010] S201: Take out the frozen block pressure-maintained core, quickly crush it in a mortar after liquid nitrogen cooling, then select the crushed particles that meet the requirements and put them into the sample boat of the pyrolysis device, and send them into the pyrolysis furnace. After pyrolysis, obtain the pyrolysis sample. The pyrolysis temperature is adjusted by the pyrolysis device. The pyrolysis temperature adjustment process includes:

[0011] Obtain pyrolysis data at each acquisition moment during the pyrolysis process;

[0012] Determine a comparison interval coefficient at the current moment based on changes in the pyrolysis data at all acquisition moments before the current moment and the time intervals between peak values ​​of the pyrolysis data, and determine a judgment threshold based on the comparison interval coefficient;

[0013] When the comparison interval coefficient at the current moment is lower than the judgment threshold, a sliding window is constructed using the comparison interval coefficient, and a cumulative comparison coefficient of each sliding window is determined based on the correlation between the pyrolysis data in each sliding window and the pyrolysis data in other sliding windows; the control parameters of the PLC programmable controller are adjusted based on the cumulative comparison coefficients of all sliding windows, and the pyrolysis temperature is controlled by the PLC controller;

[0014] When the comparison interval coefficient at the current moment is higher than the judgment threshold, the pyrolysis temperature is not adjusted;

[0015] S202, rapidly heating and releasing the sample, and separating it into various monomer compounds through a capillary chromatographic column under the influence of inert gas, and detecting it with a hydrogen flame ionization detector to obtain a pressure-maintained core pyrolysis gas chromatogram;

[0016] S203, combining the pyrolysis gas chromatogram of the pressure-maintained core and calculating the content of each component;

[0017] S3, determine the thermodynamic parameters of oil and gas components;

[0018] S4, using simulation software, fitting the nanospace thermodynamic state equation model to obtain the PT phase diagram of shale oil under different nanospace conditions;

[0019] S5. Combined with the formation temperature, pressure, shale reservoir pore size distribution data and PT phase diagram of the study area, the in-situ phase state of nano-space shale oil and the type of shale oil reservoir in the study area are determined.

[0020] Preferably, during the pressure-maintained core pyrolysis gas chromatography quantitative analysis, the capture trap uses liquid nitrogen cooling.

[0021] Preferably, the crushed particles meeting the conditions are 0.01 g of particles with a diameter of 2 mm and placed in a sample boat of a pyrolysis device.

[0022] Preferably, the calculation method of the comparison interval coefficient at the current moment is:

[0023] A pyrolysis monitoring matrix is ​​constructed based on the pyrolysis data, and the weight and cumulative influence corresponding to each row vector in the pyrolysis monitoring matrix are calculated to obtain the comparison interval coefficient: Among them, k represents the comparison interval coefficient at the current moment; a i and b i They represent the weight and cumulative influence corresponding to the i-th row vector in the pyrolysis monitoring matrix respectively; n represents the number of rows in the pyrolysis monitoring matrix; δ is a constant to avoid the denominator being zero.

[0024] Preferably, the construction of the pyrolysis monitoring matrix includes: arranging the same type of pyrolysis data into a sequence according to the collection time, each serving as a row vector, and all row vectors forming the pyrolysis monitoring matrix.

[0025] Preferably, the acquisition of the weight and cumulative influence further includes:

[0026] The entropy weight method is used to obtain the weight of each row vector in the pyrolysis monitoring matrix;

[0027] The peak value of each row vector in the pyrolysis monitoring matrix is ​​extracted, and the acquisition time corresponding to all peak values ​​in each row vector is sorted in ascending time order. Then, the cumulative sum of the time intervals of all adjacent acquisition times after sorting is calculated as the cumulative influence of each row vector.

[0028] Preferably, the judgment threshold is the average of all comparison interval coefficients at the current moment and all previous acquisition moments.

[0029] Preferably, the side length of the sliding window is the comparison interval coefficient, and the sliding step length is the result of rounding off half of the sliding window length.

[0030] Preferably, the cumulative contrast coefficient of each sliding window is calculated as follows:

[0031] Among them, h x represents the cumulative contrast coefficient of the x-th sliding window; g x and g rThey represent the submatrices corresponding to the elements of the x-th and r-th sliding windows in the pyrolysis monitoring matrix, m is the number of sliding windows, and z() represents the consistency ratio.

[0032] Preferably, the parameter value calculation method of the control parameter of the PLC programmable controller after adjustment is: ′ =ρ+Δε; wherein, ρ′ is the parameter value of the control parameter of the PLC programmable controller after adjustment, ρ is the initial control parameter value preset by the PLC programmable controller, and Δε is the compensation amount of the control parameter adjustment, which is obtained through the cumulative comparison coefficient.

[0033] Preferably, the compensation amount is calculated as follows: Δε=ρ×(1-w); wherein w is the average value of the normalized results of the cumulative contrast coefficients of all sliding windows.

[0034] Preferably, the calculation method of the content of each component is:

[0035] The molar mass of each alkane molecular component in the pressure-retaining core is statistically analyzed through the pyrolysis gas chromatography spectrum of the pressure-retaining core, and the mass fraction of each alkane molecular component in the pressure-retaining core is divided by the molar mass of the corresponding alkane component to obtain the molar number of each alkane component; the cumulative result of the molar number of all alkane components is the total molar number of alkanes in the pressure-retaining core, and the molar number of each alkane component is divided by the total molar number to obtain the mole fraction of each alkane component.

[0036] Preferably, the thermodynamic parameters of the oil and gas components are determined by using either a table lookup method or a correlation formula.

[0037] Preferably, the thermodynamic parameters include the specific gravity, normal pressure boiling point, critical temperature, critical pressure, vapor pressure, eccentricity factor, binary interaction coefficient between the added component and the hydrocarbon component, and volume offset term of the added component, wherein the added component is other components other than the hydrocarbon component.

[0038] This application has at least the following beneficial effects:

[0039] This application takes into account the difficulties faced by traditional methods in the evaluation of shale oil phase and reservoir types, such as the difficulty in sampling shale oil high-pressure physical properties and the difficulty in determining the gas-oil ratio of surface crude oil. This application only requires pyrolysis gas chromatography measurement of pressure-maintained cores to effectively carry out the evaluation of shale oil phase and reservoir types.

[0040] The pyrolysis gas chromatography analysis method has high-precision measurement characteristics and can perform fine separation and precise quantitative analysis of hydrocarbon components in core samples. Combined with temperature monitoring and compensation adjustment during the pyrolysis process, it further improves measurement accuracy and enhances the accuracy of simulation results.

[0041] Due to the high precision of the pyrolysis gas chromatography analysis method, the shale oil phase evaluation model constructed based on it can accurately simulate the phase change process of shale oil under reservoir conditions, and the simulation results are accurate and reliable. At the same time, the in-situ phase state of nano-space shale oil and shale oil reservoir type evaluation can be carried out only through pressure-maintained core pyrolysis gas chromatography measurement, and the experimental process is simple and easy. Compared with traditional shale oil phase and shale oil reservoir type evaluation methods, the amount of experimental data required is significantly reduced, and there is no need for complex high-pressure physical property sampling and tedious surface crude oil ratio determination. This greatly improves the efficiency and convenience of shale oil phase evaluation work, providing an efficient, accurate and practical evaluation method for phase and reservoir type research during shale oil exploration and development. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0043] Figure 1 Flowchart of the method for intelligent evaluation of in-situ phase state and reservoir type of nano-space shale oil provided in this application;

[0044] Figure 2 Schematic diagram of the pyrolysis gas chromatography spectrum of the pressure-maintained core of Zhaoye 1H Well provided in this application;

[0045] Figure 3 Schematic diagram of the pyrolysis gas chromatogram of the Guye 8HC pressure-maintained core provided in this application;

[0046] Figure 4 Schematic diagram of the pyrolysis gas chromatogram of the Guye 3HC pressure-maintained core provided in this application;

[0047] Figure 5 Schematic diagram of the gas chromatography spectrum of the pyrolysis of the pressure-maintained core of Guye 1 provided in this application;

[0048] Figure 6 A flow chart of the temperature regulation process for pressure-maintained core pyrolysis provided for this application;

[0049] Figure 7 Schematic diagram of the PT phase diagram of shale oil from Zhaoye 1H well provided for this application;

[0050] Figure 8 Schematic diagram of the PT phase diagram of shale oil from the Guye 36 well provided for this application;

[0051] Figure 9Schematic diagram of the PT phase diagram of shale oil from the Guye 4HC well provided for this application;

[0052] Figure 10 Schematic diagram of the PT phase diagram of shale oil from the Guye 1 well provided for this application;

[0053] Figure 11 Schematic diagram of the PT phase diagram of shale oil in the Guye 1 well under different nanospace conditions provided for this application. DETAILED DESCRIPTION

[0054] To further illustrate the technical means and effectiveness of this application to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of the nano-spatial shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method proposed in this application. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0055] Unless otherwise defined, terms such as "comprises," "comprising," or any other variants thereof are intended to encompass non-exclusive inclusion, such that a circuit structure, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such article or device. In the absence of further restrictions, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the article or device comprising the element. In addition, the term "and\or" as used herein includes any and all combinations of one or more related listed items. All technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application pertains.

[0056] The specific scheme of the nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method provided by this application is described in detail below with reference to the accompanying drawings.

[0057] An embodiment of the present application provides a method for intelligently evaluating the in-situ phase state and reservoir type of nano-space shale oil. For details, please refer to Figure 1 , including the following steps:

[0058] S1, obtain pressure-maintained core from the shale target formation.

[0059] Obtain pressure-maintained cores from the target shale formation. The pressure-maintained core barrel is kept in a liquid nitrogen environment after being taken to the surface. Liquid nitrogen is also used for protection during the process of removing the core from the pressure-maintained core barrel. The specific acquisition steps include:

[0060] S101 uses a pressure-maintaining cylinder with a built-in pressure metering device to maintain pressure and coring. After the pressure-maintaining cylinder reaches the surface, the formation pressure and surface pressure are compared. If the surface pressure reading is more than 80% of the formation pressure reading, the pressure maintenance effect is achieved.

[0061] S102, placing the pressure-maintaining cylinder that has achieved the pressure-maintaining effect into a liquid nitrogen tank and fully freezing it;

[0062] S103, cutting the pressure-maintaining cylinder into small sections under liquid nitrogen protection, and placing the sections in a liquid nitrogen tank for storage and transportation;

[0063] S104: Use a pressure-maintained core inner barrel milling device with liquid nitrogen protection to mill and split the frozen core barrel, cut out samples at the center of the core, and store them in a liquid nitrogen barrel for later use.

[0064] S2, obtain the molecular composition and component content of the pressure-maintained core through quantitative analysis of pressure-maintained core pyrolysis gas chromatography.

[0065] The quantitative analysis results of the molecular composition and component content of the pressure-maintained core were obtained through quantitative analysis of pyrolysis gas chromatography of the pressure-maintained core. During the quantitative analysis of pyrolysis gas chromatography of the pressure-maintained core, the trap was cooled by liquid nitrogen. The specific acquisition process is as follows:

[0066] S201: Take out the frozen block pressure-maintained core, quickly crush it in a mortar after liquid nitrogen cooling, select 0.01g of particles with a diameter of 2mm and put them into the sample boat of the pyrolysis device, and send it into the pyrolysis furnace to pyrolyze the free oil in the source rock. After pyrolysis, obtain the pyrolysis sample.

[0067] During the pyrolysis process, the free oil in the source rock is extracted by precisely controlling the temperature and time in the pyrolysis device, which is then enriched using a liquid nitrogen cold trap. When obtaining pyrolysis gas chromatograms, different samples and pyrolysis temperatures produce different cracking products and degrees of pyrolysis. Abnormal temperatures can lead to cracking problems and side reactions, affecting the accuracy of the results. For example, if the pyrolysis temperature of a shale oil sample fluctuates due to heating and environmental factors, this can cause abnormal cracking of hydrocarbon components, affecting the determination of their compositional properties. Therefore, it is necessary to integrate an intelligent sensor system to collect pyrolysis data from core samples and monitor and adjust the pyrolysis status.

[0068] Given that the stability of pyrolysis temperature affects the determination of sample composition and that control offset has the effect of continuous cumulative changes, this application adopts a stage-by-stage judgment compensation strategy for temperature control during the insulation stage. That is, based on the changes in the temperature gradient and pressure distribution characteristics caused by the changes in the balance in the furnace due to pyrolysis changes, the control offset caused by the cumulative changes is judged and the temperature of the pyrolysis process is adjusted accordingly. The specific process is as follows:

[0069] (1) Data collection: Obtain the pyrolysis data at each collection moment during the pyrolysis process.

[0070] Temperature and pressure sensors are placed within the pyrolysis apparatus. Considering the size of the actual apparatus and the characteristic gradient variations of parameters within the furnace, this embodiment uses these sensors to collect pyrolysis data at each acquisition point during the pyrolysis process. In this embodiment, the pyrolysis data includes both temperature and pressure data. However, during the data acquisition process, environmental factors and changes in the instrument's own state may introduce noise interference, affecting data quality. To address this issue, this embodiment employs a median filter to reduce noise from the collected data, obtaining noise-reduced data during the control process.

[0071] (2) Data analysis: Determine the comparison interval coefficient at the current moment based on the changes in the pyrolysis data at all acquisition moments before the current moment and the time interval between the peak values ​​of the pyrolysis data, and determine the judgment threshold based on the comparison interval coefficient; when the comparison interval coefficient at the current moment is lower than the judgment threshold, construct a sliding window using the comparison interval coefficient, and determine the cumulative comparison coefficient of each sliding window based on the correlation between each sliding window and the pyrolysis data in other sliding windows.

[0072] The pyrolysis of core samples involves heating and holding stages. During the heating stage, the temperature is raised to the pyrolysis temperature at a set rate. During the holding stage, the pyrolysis temperature must be precisely controlled to prevent unstable pyrolysis from interfering with sample composition determination. When the heating element or environmental changes cause temperature fluctuations, the pressure within the furnace changes accordingly, affecting the retention and diffusion of pyrolysis products within the furnace. Increased pressure accelerates diffusion, and products may be carried out before they are fully reacted. Lowered pressure slows diffusion, which can easily trigger secondary reactions. Furthermore, unstable pyrolysis temperatures disrupt the previously stable temperature gradient within the furnace from the heating source to the center of the sample. Once the temperature rises sharply locally, pyrolysis of samples in the corresponding area accelerates, increasing the number of products and affecting the overall distribution. This can also lead to significant differences in the degree of pyrolysis of samples at different locations within the furnace, resulting in pyrolysis products that fail to accurately reflect the actual pyrolysis conditions of shale oil.

[0073] Based on the above analysis, in order to effectively integrate the continuous influence relationship between pressure and temperature, and thus accurately analyze the cumulative change comparison characteristics during the control process, the same type of pyrolysis data is arranged into sequences according to the collection time, and each row vector is used as a row vector. All row vectors constitute a pyrolysis monitoring matrix. Specifically, in this embodiment, each type of data is arranged into sequences according to the collection time sequence, and each row vector is used as a row vector of the pyrolysis monitoring matrix. Therefore, in this embodiment, the matrix composed of temperature and pressure data serves as the pyrolysis monitoring matrix. In this embodiment, by analyzing the pyrolysis monitoring matrix, the changing patterns of pressure and temperature in the time dimension and their mutual influence relationship can be obtained, thereby providing a key basis for optimizing the control strategy.

[0074] Furthermore, in order to effectively compare the comparative characteristics of the cumulative changes between different data in different time series intervals during the pyrolysis process, in this embodiment, the entropy weight method is used to obtain the weight of each row vector in the pyrolysis monitoring matrix, denoted as a. The weight represents the difference in stability change between the data corresponding to each row vector and other data. The larger the weight, the more significant the stability change characteristic. An adaptive multi-scale peak search algorithm is used to obtain the peak value of each row vector in the pyrolysis monitoring matrix, and the acquisition time corresponding to all peak values ​​in each row vector is arranged in ascending time order. Then, the cumulative sum of the time intervals of all adjacent acquisition times after sorting is calculated as the cumulative influence of each row vector, denoted as b. The larger the absolute value, the smaller the cumulative influence of the stability change of the data corresponding to the current row. The comparison interval coefficient at each moment is further analyzed, and the calculation relationship is as follows:

[0075] Among them, k represents the comparison interval coefficient at the current moment; a i and b i They respectively represent the weight and cumulative influence corresponding to the i-th row vector in the pyrolysis monitoring matrix; n represents the number of rows in the pyrolysis monitoring matrix; δ is a constant to avoid the denominator being zero, and its value range is 0 to 0.1. In this embodiment, it is 0.001; if the stability change characteristics of different types of data are greater and the cumulative influence range is larger, that is, the weight and the cumulative influence are greater, then the comparison interval coefficient of the data corresponding to the row vector at the current moment is smaller, indicating that the continuous cumulative influence of the stability difference is greater, and there is a significant cumulative change feature.

[0076] Furthermore, the characteristics of the continuous cumulative effect of the control during the pyrolysis process are used to judge the influence of the control response of the current pyrolysis process. Specifically, the mean of all comparison interval coefficients at the current moment and all previous acquisition moments is calculated, and the mean is set as the judgment threshold at the current moment; if the comparison interval coefficient at the current moment is lower than the judgment threshold, it indicates that as of the current moment, its control process is affected by the cumulative effect of continuous stable changes, and the control response deviation is larger; if the comparison interval coefficient is higher than the judgment threshold, it indicates that as of the current moment, the control process is weakly affected by the cumulative effect of continuous stable changes, and the control response difference is smaller. Therefore, if the comparison interval coefficient at the current moment is higher than the judgment threshold, then in this embodiment, there is no need to regulate the pyrolysis temperature.

[0077] Furthermore, based on the above judgment results, if the comparison interval coefficient at the current moment is lower than the judgment threshold, then it is necessary to carry out continuity comparison analysis in different time series intervals for the control response difference at the current moment. Specifically, a sliding window is set for continuous stable change comparison, and the length of the sliding window is equal to the comparison interval coefficient. By setting the sliding window according to the comparison interval coefficient, the data accumulation characteristics can be accurately compared in the process of continuous stable change. Among them, the sliding step length of the sliding window is taken as half of the sliding window length and rounded to the integer. Since the continuity parameters of the pyrolysis process in different time periods are less affected by the cumulative influence when the fixed point is judged, and have significant consistency characteristics, the cumulative comparison coefficient of the pyrolysis fixed point judgment is obtained based on the data in different sliding windows. The specific calculation relationship is as follows:

[0078] Among them, h x represents the cumulative contrast coefficient of the x-th sliding window; g x and g r They represent the submatrices composed of the corresponding elements in the pyrolysis monitoring matrix within the time range of the xth and rth sliding windows, respectively. m is the number of sliding windows, and z(g x ,g r ) represents g x and g r The smaller the calculated cumulative contrast coefficient, the greater the influence of the cumulative change on the control of the pyrolysis temperature at the current control moment; a large control offset may occur, resulting in a large deviation in the pyrolysis temperature, affecting the gas chromatography measurement results. It should be noted that the calculation of the consistency ratio between matrices is a well-known technique, and the specific process will not be repeated in this embodiment.

[0079] (3) Control adjustment: The control parameters of the PLC programmable controller are adjusted based on the cumulative contrast coefficients of all sliding windows, and the pyrolysis temperature is controlled by the PLC controller; when the contrast interval coefficient at the current moment is higher than the judgment threshold, the pyrolysis temperature is not adjusted.

[0080] Through the above analysis, combined with the analysis of the contrast difference characteristics caused by the cumulative influence of continuity during the control process, the control deviation of the pyrolysis temperature can be accurately judged and analyzed. Furthermore, the cumulative contrast coefficients of all sliding windows obtained up to the current moment are used as input, and the Softmax function is used to obtain the normalization result of all cumulative contrast coefficients. It should be noted that the specific normalization process is existing technology and will not be repeated in this embodiment. The implementer may also use other existing normalization methods for processing, and this embodiment does not limit this.

[0081] If the cumulative comparison coefficient obtained based on the above judgment as of the current moment is smaller, it means that the continuous cumulative changes in the control process have caused a larger delayed response, resulting in a larger control offset. Therefore, the control response at the current moment is adjusted based on the cumulative comparison coefficient. Specifically, in this embodiment, a PLC programmable controller is used for control, and the mean of the normalized results of all cumulative comparison coefficients is calculated, and the control parameters of the PLC programmable controller are adjusted based on this.

[0082] Preferably, in this embodiment, the compensation amount for the control parameter adjustment is Δε=ρ×(1-w), where w is the average value of the normalized results of the cumulative contrast coefficients of all sliding windows, and ρ is the initial control parameter value preset by the PLC programmable controller. In this embodiment, the initial control parameter value is the proportional parameter in the PID algorithm, and the value range is 0 to 1. In this embodiment, it is set to 0.1. The implementer can set it according to the actual application scenario. There is no special restriction on this in this embodiment. It can be understood that the larger the cumulative contrast coefficient, the greater the compensation amount for the control parameter adjustment, and timely response adjustment should be made to the impact of cumulative changes.

[0083] Furthermore, the control parameters of the PLC programmable controller are adjusted in combination with the compensation amount and the initial control parameter value preset by the PLC programmable controller. The parameter value calculation formula of the control parameter of the PLC programmable controller after adjustment is: ′ =ρ+Δε; where ρ′ is the parameter value of the control parameter of the PLC programmable controller after adjustment, ρ is the initial control parameter value preset by the PLC programmable controller, and Δε is the compensation amount of the control parameter adjustment.

[0084] At this point, according to the above process of this embodiment, the pyrolysis temperature can be adjusted by the pyrolysis device in combination with the PLC programmable controller, and a pyrolysis sample can be obtained after pyrolysis.

[0085] S202, the sample is rapidly heated and released, and separated into various monomer compounds by a capillary chromatographic column under the influence of inert gas. The sample is detected by a hydrogen flame ionization detector, and a schematic diagram of the pyrolysis gas chromatogram of the pressure-maintained core is obtained, as shown in FIG. Figure 2 、 3 , 4, and 5, Figures 2 to 5 C1, C 17 、C 29 All represent components, among which, Figure 2 This is a schematic diagram of the gas chromatography spectrum of the pyrolysis core of the Zhaoye 1H well. Figure 3 This is a schematic diagram of the gas chromatography spectrum of the pyrolysis of the Guye 8HC pressure-maintained core. Figure 4 This is a schematic diagram of the gas chromatography spectrum of the pyrolysis of the Guye 3HC pressure-maintained core. Figure 5 Schematic diagram of the gas chromatography spectrum of pyrolysis of the pressure-maintained core of Guye 1.

[0086] S203, combining the pyrolysis gas chromatography spectrum of the pressure-maintained core and calculating the content of each component.

[0087] Specifically, the molar mass of each alkane molecular component in the pressure-retained core is calculated using the pyrolysis gas chromatogram of the pressure-retained core. The specific process is well known to those skilled in the art and will not be described in detail in this example. The mass fraction of each alkane molecular component in the pressure-retained core is divided by the molar mass of the corresponding alkane component to obtain the molar number of each alkane component. The molar numbers of all alkane components are added to obtain the total molar number of alkanes in the pressure-retained core. The molar number of each alkane component is then divided by the total molar number to obtain the mole fraction of each alkane component.

[0088] Specifically, the process flow chart of pressure-maintained core pyrolysis temperature adjustment is as follows: Figure 6 shown.

[0089] S3, determine the thermodynamic parameters of the oil and gas components.

[0090] The thermodynamic parameters of the oil and gas components are determined using a lookup table or correlation equations. The thermodynamic parameters include the specific gravity, atmospheric boiling point, critical temperature, critical pressure, vapor pressure, eccentricity factor, binary interaction coefficient between the added component and the hydrocarbon component, and volume offset term of the added component. The added component refers to components other than the hydrocarbon component.

[0091] Preferably, in this embodiment, the method for determining the thermodynamic parameters of oil and gas components using the correlation equation is:

[0092] According to the specific gravity and normal pressure boiling point of the added component, the critical temperature and critical pressure of the added component are determined. The specific relationship for determining the critical temperature is:

[0093] Among them, T c is the critical temperature of the added component; SG is the specific gravity of the added component; T b is the atmospheric boiling point of the added component.

[0094] The critical pressure of the added component is determined as follows:

[0095] Among them, P c is the critical pressure of the added component.

[0096] According to the vapor pressure of the added component, the eccentricity factor of the added component is determined. The specific relationship is:

[0097] ω=-1.46456×[lnP vp (T=0.85T b)-9.77882]; where ω is the eccentricity factor of the added component; P vp (T=0.85T b ) is a temperature of 0.85T b The vapor pressure of the added component.

[0098] Based on the result parameters of the saturation pressure experiment and the state equation, the binary interaction coefficient between the added component and the hydrocarbon component is determined through repeated contact calculations. The specific process is existing technology and will not be described in detail in this embodiment.

[0099] According to the density of the component, the volume offset term of the added component is determined. The specific determination method is:

[0100] c=V c -V EoS ; Where c is the volume offset term of the added component; V c V is the volume of the pure component obtained from the density of the added component obtained by density measurement, and the density measurement process is the existing technology; EoS The volume of the pure component is obtained by adding the component density calculated by two-phase flash evaporation according to the equation of state. The specific process is prior art and will not be repeated in this embodiment.

[0101] It should be noted that, in actual application scenarios, the implementer can select the determination method of each thermodynamic parameter of the oil and gas components at his / her own discretion. The specific determination process can be achieved through existing technologies, and there is no special limitation on this in this embodiment.

[0102] At this point, the thermodynamic parameters of the oil and gas components can be obtained according to the above process of this embodiment.

[0103] S4, using simulation software, fit the nanospace thermodynamic state equation model to obtain the shale oil PT phase diagram under different nanospace conditions.

[0104] Furthermore, PVTsim software was used to simulate and calculate the phase equilibrium of shale oil and gas components in the pressure-maintained sealed core under nanospace conditions using the confined space phase analysis method, forming a PT phase diagram of shale oil under nanospace conditions.

[0105] Specifically, in this embodiment, the molecular composition, component content, and thermodynamic parameters of the pressure-maintained core were input into the PVTsim software, and the confined space phase analysis method was used to simulate the phase equilibrium of the shale oil and gas components in the pressure-maintained confined core under 150 nanometer space conditions through flash calculation to form a shale oil PT phase diagram. Specifically, the schematic diagrams of the PT phase diagrams of the shale oil from Zhaoye 1H Well, Guye 36 Well, Guye 4HC Well, and Guye 1 Well are shown as follows: Figure 7 、 8 , 9, and 10. Figures 7 to 10In the figure, the horizontal axis is temperature in °C, the vertical axis is pressure in MPa, and Ro is the vitrinite reflectance, which is an important indicator of the maturity of the source rock. Figures 7 to 10 The Ro rates are 0.96%, 1.18%, 1.38% and 1.61% respectively. Figures 7 to 10 The diagram contains black oil, volatile oil, and condensate gas areas. At the same time, the coordinate information of the points where the formation temperature and pressure data are located in the PT phase diagram are (102.7, 28.9), (106.2, 32.7), (115.7, 36.6), and (135, 37.5), respectively. The square is the boundary between the volatile oil area and the condensate gas area, that is, the critical point.

[0106] In this embodiment, taking the Guye 1 well as an example, the phase equilibrium of the Guye 1 well in the 10nm, 20nm, 50nm, and 150nm spaces is calculated respectively, and a schematic diagram of the PT phase diagram of the Guye 1 well under different nano-space conditions is formed, as shown in FIG. Figure 11 As shown, the PT phase diagram of conventional pores in the BULK oil field is used for comparison. Figure 11 The envelope lines of the medium phase diagram belong from the inside to the outside: the PT phase diagram of the Guye 1 well at 10nm, 20nm, 50nm, 150nm and the conventional pores of the BULK oilfield. Figure 11 In the figure, the horizontal axis is pressure in MPa, the vertical axis is temperature in °C, GY1 well is Guye 1 well, the dot coordinates are (135, 37.5), and the schematic diagram of shale oil PT phase diagram under different nanospace conditions is as follows: Figure 11 shown.

[0107] S5. Combined with the formation temperature, pressure, shale reservoir pore size distribution data and PT phase diagram of the study area, the in-situ phase state of nano-space shale oil and the type of shale oil reservoir in the study area are determined.

[0108] In this embodiment, the in-situ phase of the nano-space Gulong shale oil is determined by using the formation temperature, pressure, shale reservoir pore size distribution data and PT phase diagram of the study area. In the medium-low maturity evolution stage (Ro<1.2%), its in-situ phase is mainly black oil; in the medium-high maturity evolution stage (Ro 1.2~1.4%), it is mainly black oil, with some condensate gas developed; in the high maturity evolution stage (Ro>1.4%), the shale oil phase is mainly condensate gas, and the smaller the pore size of the rock where the shale oil is located, the lower the critical temperature and critical pressure, and the reservoir type will change from black oil to condensate gas. When the pore size is below 10nm, most of the shale oil is condensate gas.

[0109] Among them, it should be noted that when the in-situ phase of nano-space shale oil is black oil, the corresponding reservoir type is black oil reservoir; when the in-situ phase of nano-space shale oil is volatile oil, it is in a gas-liquid transition state, and the corresponding reservoir type is volatile oil reservoir or light oil reservoir; when the in-situ phase is condensate gas, the corresponding reservoir type is condensate gas reservoir.

[0110] In this embodiment, the vitrinite reflectance of the core favorable exploration and development area of ​​Gulong shale oil is greater than 1.4%, and the main peak of the pore size of the nanospace is 2-30 nm, so the in-situ phase is mainly condensate gas, and the oil reservoir type is mainly condensate gas reservoir.

[0111] It is understood that references to "one embodiment" or "some embodiments" in the present specification mean that one or more embodiments of the present application include a particular feature, structure, or characteristic described in conjunction with that embodiment. Thus, if "in one embodiment," "in some embodiments," "in other embodiments," or "in other embodiments" appear in different places in this specification, they do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and their variations all mean "including but not limited to," unless otherwise specifically emphasized.

[0112] It should be noted that the above-mentioned sequence of the embodiments of the present application is for description only and does not represent the advantages and disadvantages of the embodiments. The above description is of a specific embodiment of this specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-tasking and parallel processing are also possible or may be advantageous. At the same time, the size of the sequence number of each step in the embodiment does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments in this specification.

[0113] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application 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. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. Nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method, characterized by: The following steps are involved: S1, obtain pressure-maintained cores from the shale target formation; S2, through the pressure-maintained core pyrolysis gas chromatography quantitative analysis, obtain the pressure-maintained core molecular composition and component content, the specific acquisition steps are: S201: Take out the frozen block pressure-maintained core, quickly crush it in a mortar after liquid nitrogen cooling, then select the crushed particles that meet the requirements and put them into the sample boat of the pyrolysis device, and send them into the pyrolysis furnace. After pyrolysis, obtain the pyrolysis sample. The pyrolysis temperature is adjusted by the pyrolysis device. The pyrolysis temperature adjustment process includes: Obtain pyrolysis data at each acquisition moment during the pyrolysis process; Determine a comparison interval coefficient at the current moment based on changes in the pyrolysis data at all acquisition moments before the current moment and the time intervals between peak values ​​of the pyrolysis data, and determine a judgment threshold based on the comparison interval coefficient; When the comparison interval coefficient at the current moment is lower than the judgment threshold, a sliding window is constructed using the comparison interval coefficient, and a cumulative comparison coefficient of each sliding window is determined based on the correlation between the pyrolysis data in each sliding window and the pyrolysis data in other sliding windows; the control parameters of the PLC programmable controller are adjusted based on the cumulative comparison coefficients of all sliding windows, and the pyrolysis temperature is controlled by the PLC controller; When the comparison interval coefficient at the current moment is higher than the judgment threshold, the pyrolysis temperature is not adjusted; S202, rapidly heating and releasing the sample, and separating it into various monomer compounds through a capillary chromatographic column under the influence of inert gas, and detecting it with a hydrogen flame ionization detector to obtain a pressure-maintained core pyrolysis gas chromatogram; S203, combining the pyrolysis gas chromatogram of the pressure-maintained core and calculating the content of each component; S3, determine the thermodynamic parameters of oil and gas components; S4, using simulation software, fitting the nanospace thermodynamic state equation model to obtain the PT phase diagram of shale oil under different nanospace conditions; S5. Combined with the formation temperature, pressure, shale reservoir pore size distribution data and PT phase diagram of the study area, the in-situ phase state of nano-space shale oil and the type of shale oil reservoir in the study area are determined.

2. The nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method according to claim 1, characterized in that: During the pressure-maintained core pyrolysis gas chromatography quantitative analysis, the trap is cooled by liquid nitrogen.

3. The nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method according to claim 1, characterized in that: The crushed particles that meet the conditions are 0.01 g of particles with a diameter of 2 mm and placed in a sample boat of a pyrolysis device.

4. The nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method according to claim 1, characterized in that: The calculation method of the comparison interval coefficient at the current moment is: A pyrolysis monitoring matrix is ​​constructed based on the pyrolysis data, and the weight and cumulative influence corresponding to each row vector in the pyrolysis monitoring matrix are calculated to obtain the comparison interval coefficient: Among them, k represents the comparison interval coefficient at the current moment; a i and b i They represent the weight and cumulative influence corresponding to the i-th row vector in the pyrolysis monitoring matrix respectively; n represents the number of rows in the pyrolysis monitoring matrix; δ is a constant to avoid the denominator being zero.

5. The nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method according to claim 3, characterized in that: The construction of the pyrolysis monitoring matrix includes: arranging the same type of pyrolysis data into a sequence according to the collection time, all of which are used as row vectors, and all row vectors form a pyrolysis monitoring matrix.

6. The nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method according to claim 3, characterized in that: The acquisition of the weight and cumulative influence further includes: The entropy weight method is used to obtain the weight of each row vector in the pyrolysis monitoring matrix; The peak value of each row vector in the pyrolysis monitoring matrix is ​​extracted, and the acquisition time corresponding to all peak values ​​in each row vector is sorted in ascending time order. Then, the cumulative sum of the time intervals of all adjacent acquisition times after sorting is calculated as the cumulative influence of each row vector.

7. The nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method according to claim 1, characterized in that: The judgment threshold is the mean value of all comparison interval coefficients at the current moment and all previous acquisition moments.

8. The nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method according to claim 1, characterized in that: The side length of the sliding window is the comparison interval coefficient, and the sliding step length is half of the sliding window length and is rounded up.

9. The nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method according to claim 1, characterized in that: The calculation method of the cumulative contrast coefficient of each sliding window is: Among them, h x represents the cumulative contrast coefficient of the x-th sliding window; g x and g r They represent the submatrices corresponding to the elements of the x-th and r-th sliding windows in the pyrolysis monitoring matrix, m is the number of sliding windows, and z() represents the consistency ratio.

10. The nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method according to claim 1, characterized in that: The calculation method of the control parameter value of the PLC programmable controller after adjustment is: ρ ′ =ρ+Δε; Wherein, ρ′ is the parameter value of the control parameter of the PLC programmable controller after adjustment, ρ is the initial control parameter value preset by the PLC programmable controller, and Δε is the compensation amount of the control parameter adjustment, which is obtained through the cumulative comparison coefficient.

11. The nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method according to claim 1, characterized in that: The compensation amount is calculated as follows: Δε=ρ×(1-w); wherein w is the average value of the normalized results of the cumulative contrast coefficients of all sliding windows.

12. The nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method according to claim 1, characterized in that: The calculation method of the content of each component is: The molar mass of each alkane molecular component in the pressure-retaining core is calculated by using the pyrolysis gas chromatography spectrum of the pressure-retaining core, and the mass fraction of each alkane molecular component in the pressure-retaining core is divided by the molar mass of the corresponding alkane component to obtain the molar number of each alkane component; The cumulative result of the molar numbers of all alkane components is the total molar number of alkanes in the pressure-retaining core, and the molar number of each alkane component is divided by the total molar number to obtain the mole fraction of each alkane component.

13. The nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method according to claim 1, characterized in that: The thermodynamic parameters of the oil and gas components are determined by using either a table lookup method or a correlation formula.

14. The nano-space shale oil in-situ phase state and shale oil reservoir type intelligent evaluation method according to claim 1, characterized in that: The thermodynamic parameters include the specific gravity, normal pressure boiling point, critical temperature, critical pressure, vapor pressure, eccentricity factor, binary interaction coefficient between the added component and the hydrocarbon component, and volume offset term of each oil and gas component, wherein the added component is other components other than the hydrocarbon component.

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