Rapid quantitative identification method for oiliness of thin interbed shale oil

Abstract

The invention belongs to the technical field of oil-gas exploration and development, and particularly relates to a thin interbed shale oil oiliness rapid quantitative identification method, which comprises the following steps: establishing a first fitting relationship between S2 actual measurement and Q fluorescence for pyrolytic analysis and three-dimensional quantitative fluorescence analysis data, performing correlation correction on the S2 actual measurement to obtain S2 fitting correction, and determining the oiliness of the thin interbed shale oil; establishing a second fitting relationship between (S1 + S2) actual measurement and V for pyrolysis analysis and laser confocal analysis data, and performing correlation correction on the (S1 + S2) actual measurement to obtain (S1 + S2) fitting correction; establishing a relational expression between S1 correction and (S1 + S2) actual measurement and S2 actual measurement; and performing pyrolysis analysis on the to-be-detected rock core sample, substituting the S1 actual measurement and the S2 actual measurement into the relational expression to obtain S1 correction, and judging the oiliness of the to-be-detected rock core sample by utilizing the S1 correction. According to the method, pyrolysis analysis parameters can be corrected, the oiliness of shale oil can be reflected more accurately, and the method has the advantages of being high in accuracy and short in identification time.

Description

Technical Field

[0001] The invention belongs to the technical field of oil and gas exploration and development, and particularly relates to a method for rapid quantitative identification of oil content in thin interlayer shale oil. Background Art

[0002] As one of the important parameters for identifying shale oil sweet spots, shale oil oil content is a key indicator for current shale oil research and evaluation. Crude oil in shale oil is mainly composed of liquid hydrocarbons, which can be divided into movable free oil S1 and immobile adsorbed oil S2 according to current development conditions. Movable free oil S1 is mainly light hydrocarbons and can be measured at 90-300°C. Immobile adsorbed oil S2 is mainly the organic matter content of the potential hydrocarbon-generating part, which has the characteristic of not being volatile and can be measured at a temperature of 300-600°C. Since the movable free oil S1 is volatile, it brings great uncertainty to the oil content analysis, which is also a difficult problem to be solved in the current shale oil exploration.

[0003] In the process of identifying the oil content of shale oil, three methods, namely rock pyrolysis analysis (S1+S2), three-dimensional quantitative fluorescence and laser confocal analysis, usually support and verify each other. The rock pyrolysis analysis method has the advantages of convenient field application and short analysis time, but due to the volatility of the light component S1, this method has the problem of low test accuracy and cannot effectively reflect the oil content characteristics of thin interlayer shale oil. Three-dimensional quantitative fluorescence and laser confocal have relatively high analysis accuracy, but these two analysis methods have long experimental cycles and high costs, making it difficult to quickly and effectively identify the oil content of thin interlayer shale oil.

[0004] In general, the existing quantitative identification methods for oil content of shale oil cannot have the characteristics of high accuracy and short identification time at the same time. Summary of the invention

[0005] The purpose of the present invention is to provide a method for rapid quantitative identification of the oil content of thin interlayer shale oil, so as to solve the problem that the existing method for quantitative identification of the oil content of thin interlayer shale oil cannot have both high accuracy and short identification time.

[0006] To achieve the above object, the technical solution of the present invention is:

[0007] A method for rapid quantitative identification of oil content in thin interlayer shale oil, comprising: quantitatively analyzing a core sample of an oil-bearing layer to obtain quantitative analysis data; wherein the quantitative analysis comprises pyrolysis analysis, three-dimensional quantitative fluorescence analysis, and laser confocal analysis;

[0008] The correlation analysis of thermal analysis data and three-dimensional quantitative fluorescence analysis data was carried out to establish S 2实测 and oiliness index Q 荧光 The first fitting relationship is higher than the S2实测 Perform correlation correction according to the first fitting relationship to obtain S 2拟合校正 , and obtain the first correction coefficient R = S 2拟合校正 / S 2实测 , calculate the average value R0 of the first correction coefficient, and obtain S according to the correction relationship 2校正 = R0 * S 2实测 ;

[0009] Perform correlation analysis on the pyrolysis analysis data and the laser confocal analysis data, and establish the second fitting relationship between (S1 + S2) 实测 and the oil-bearing volume V. For (S1 + S2) below the second fitting relationship 实测 Perform correlation correction according to the second fitting relationship to obtain (S1 + S2) 拟合校正 , and obtain the second correction coefficient K = (S1 + S2) 拟合校正 / (S1 + S2) 实测 , calculate the average value K0 of the second correction coefficient, and obtain (S1 + S2) according to the correction relationship 校正 = K0 * (S1 + S2) 实测 ;

[0010] Establish the relationship between S 1校正 and (S1 + S2) 实测 , S 2实测 : S 1校正 = K0 * (S1 + S2) 实测 - R0 * S 2实测 ;

[0011] Perform pyrolysis analysis on the core sample to be tested, and substitute the measured S 1实测 , S 2实测 into the above relationship to obtain S 1校正 , and use S 1校正 to judge the oil-bearing property of the core sample to be tested;

[0012] Among them, S 1实测 and S 2实测 are pyrolysis analysis data, and (S1 + S2) 实测 is the sum of S 1实测 and S 2实测 .

[0013] The beneficial effects of the above technical solution are as follows: Based on the correlation analysis of three-dimensional quantitative fluorescence analysis, laser confocal analysis and rock pyrolysis, the present invention establishes a relevant calculation formula to correct the pyrolysis analysis data with large errors. Using the corrected pyrolysis analysis data as the standard for judging the oil-bearing property of shale oil can more accurately reflect the oil-bearing property characteristics of thin interbedded shale oil, and has the advantage of high accuracy. Moreover, when using the method of the present invention to predict the core samples that have not been analyzed, only the pyrolysis analysis of the core samples that have not been analyzed is required, and the pyrolysis analysis data is substituted into the calculation formula of the present invention, and the corrected data can be obtained. The oil-bearing property of the core samples that have not been analyzed can be judged by using the corrected data. When using the method of the present invention for oil-bearing property prediction, only the pyrolysis analysis of the core samples needs to be carried out on site, and the operation is simple and convenient, avoiding the three-dimensional quantitative fluorescence analysis and laser confocal analysis with high cost and long cycle. Therefore, the method of the present invention also has the advantage of short judgment time.

[0014] It should be noted that S 1实测 and S 2实测 are pyrolysis analysis data, S 1实测 is the content of hydrocarbon pyrolysis of organic matter in the temperature range of 90 - 300 °C, and S 2实测 is the content of hydrocarbon pyrolysis of organic matter in the temperature range of 300 - 600 °C.

[0015] Furthermore, affected by the volatility of light hydrocarbon components, the test accuracy of pyrolysis analysis is not high. Especially in thin interbedded shale oil, due to strong heterogeneity, large changes in geochemical indicators, and fast loss of light hydrocarbons, the value of S 1实测 is on the low side, affecting the judgment of oil-bearing property. The present invention can correct the abnormal data higher than the first fitting relationship and the abnormal data lower than the second fitting relationship, and can correct the abnormal data. After derivation, the calculation formula of S 1校正 with S 1实测 , S 2实测 can be obtained. According to the above operation, the three-dimensional quantitative fluorescence analysis and laser confocal analysis data with high accuracy can be used to correct S 1实测 , S 2实测 with lower accuracy, which can further improve the accuracy of oil-bearing property judgment.

[0016] As a further improvement, the first fitting relationship is: S 2实测 = a * Q 荧光 + b, where a and b are fitting parameters.

[0017] The beneficial effects of the above technical solution are as follows: Three-dimensional quantitative fluorescence analysis has the advantage of high accuracy of detection results. The present invention analyzes the data of multiple groups of samples to establish the relationship between S 2实测 and Q 荧光 , which is convenient for the S of pyrolysis analysis2实测 Calibration can be performed. High-accuracy three-dimensional quantitative fluorescence analysis data can be used to calibrate the relatively low-accuracy S 2实测 Calibration can be performed to further improve the accuracy of oil-bearing identification. Moreover, when S 2实测 and Q 荧光 When the above linear relationship is used for fitting, it has a relatively high correlation coefficient and good consistency, which can further improve the accuracy of oil-bearing identification.

[0018] As a further improvement, the second fitting relationship is: (S1 + S2) 实测 = c*V + d, where c and d are fitting parameters.

[0019] The beneficial effects of the above technical solution are: Laser confocal analysis has the advantage of high accuracy of detection results. By analyzing the data of multiple groups of samples, the present invention establishes the relationship between (S1 + S2) 实测 and V, which is convenient for calibrating (S1 + S2) in pyrolysis analysis. High-accuracy laser confocal analysis data can be used to calibrate the relatively low-accuracy (S1 + S2) 实测 Calibration can be performed to further improve the accuracy of oil-bearing identification. Moreover, when (S1 + S2) 实测 and V are fitted with the above linear relationship, it has a relatively high correlation coefficient and good consistency, which can further improve the accuracy of oil-bearing identification. 实测 When (S1 + S2) and V are fitted with the above linear relationship, it has a relatively high correlation coefficient and good consistency, which can further improve the accuracy of oil-bearing identification.

[0020] As a further improvement, the oil-bearing interval is determined by gas logging anomaly analysis. The gas logging anomaly analysis includes the following steps: According to the ratio △C of the methane gas logging anomaly value △C1 to the total hydrocarbon gas logging anomaly value △C 全 to select the gas logging anomaly identification mark; when △C > 1, the methane gas logging anomaly value △C1 is used as the gas logging anomaly identification mark; when △C ≤ 1, the total hydrocarbon gas logging anomaly value △C 全 is used as the gas logging anomaly identification mark; the oil-bearing property is preliminarily judged according to the gas logging anomaly identification mark.

[0021] The beneficial effects of the above technical solution are: Through gas logging anomaly analysis, the oil-bearing property can be quickly and preliminarily judged to determine whether the interval contains oil. Samples containing oil are further analyzed, while samples without oil do not need to be further analyzed. The above operations can simplify the operation and further shorten the identification time.

[0022] Furthermore, the total hydrocarbon gas logging anomaly value and the methane gas logging anomaly value are the data monitored during the drilling process. Gas logging anomaly analysis has the advantage of simple operation.

[0023] As a further improvement, after the gas logging anomaly analysis, the method further includes: sampling the oil-bearing interval, observing the core and performing fluorescence display on the obtained core, determining the fluorescence level according to the result of the fluorescence display, where a higher fluorescence level represents better oil-bearing property, and selecting the core with a high fluorescence level as the core sample of the oil-bearing interval.

[0024] The beneficial effects of the above technical solution are as follows: Since the gas logging anomaly value is data of a section of depth range, the accuracy of gas logging anomaly analysis is poor. Therefore, further detection and analysis are required to accurately determine the oil-bearing interval. Sampling the oil-bearing interval to obtain a core. Since the appearance of an oil-bearing core is different from that of a non-oil-bearing core, the oil-bearing property of the core can be further judged by observing the appearance of the core after sampling. Performing fluorescence display on the core judged to be oil-bearing through core observation to further judge the oil-bearing situation of the core. Through the above operations, qualitative judgment of the core can be carried out, accurately judging whether the core contains oil or not. Taking the oil-bearing core as the core sample for the next quantitative analysis, avoiding quantitative analysis of non-oil-bearing samples. The above operations can simplify the operation and further shorten the identification time.

[0025] Further, the method further includes: performing TOC and pyrolysis analysis on the core sample of the oil-bearing interval, analyzing the correlation between TOC and S1+S2, and using the method of the present invention to further judge the samples with discrete points of the fitting curve with poor correlation. TOC is the content of residual total organic carbon in shale, obtained by using a total organic carbon analyzer in the laboratory, which belongs to solid organic matter and is not affected by external factors such as volatilization. If the measurement of S1+S2 is accurate, usually there is a certain correlation between TOC and S1+S2; if the measurement of S1+S2 is inaccurate, then its correlation with TOC is poor. Correcting the samples with discrete points of the fitting curve with poor correlation by using the method of the present invention can further improve the accuracy of oil-bearing property identification. Description of the Drawings

[0026] Figure 1 is the flowchart of the method for rapid quantitative identification of oil-bearing property of thin interbedded shale oil in Embodiment 1 of the present invention;

[0027] Figure 2 is the relationship diagram between pyrolysis analysis data (S1+S2) 实测 and TOC in Embodiment 1 of the present invention;

[0028] Figure 3 is the pyrolysis analysis data S 2实测 and the relationship diagram between the oiliness index Q of three-dimensional quantitative fluorescence analysis data 荧光 in Embodiment 1 of the present invention;

[0029] Figure 4It is the pyrolysis analysis data (S1 + S2) in Embodiment 1 of the present invention 实测 The relationship diagram between the pyrolysis analysis data and the oil-bearing volume V of the laser confocal analysis data;

[0030] Figure 5 It is the comprehensive evaluation map of the oil-bearing property of Well W318. Specific implementation manners

[0031] Existing quantitative identification methods for the oil-bearing property of thin interbedded shale oil have the problem that they cannot have both high accuracy and short identification time. To solve this technical problem, the present invention provides a rapid quantitative identification method for the oil-bearing property of thin interbedded shale oil, including: performing quantitative analysis on core samples of the oil-bearing interval to obtain quantitative analysis data; wherein, the quantitative analysis includes pyrolysis analysis, three-dimensional quantitative fluorescence analysis, and laser confocal analysis; performing correlation analysis on the pyrolysis analysis data and the three-dimensional quantitative fluorescence analysis data to establish the first fitting relationship between S 2实测 and the oiliness index Q 荧光 . Due to the influence of oil-based mud and foreign hydrocarbons, it is necessary to perform correlation correction on S 2实测 higher than the first fitting relationship according to the first fitting relationship to obtain S 2拟合校正 . Calculate the first correction coefficient R = S 2拟合校正 / S 2实测 , and calculate the arithmetic mean of the number of samples (N) to calculate the average value R0 of the first correction coefficient. Obtain S 2校正 = R0 * S 2实测 according to the correction relationship; perform correlation analysis on the pyrolysis analysis data and the laser confocal analysis data to establish the second fitting relationship between (S1 + S2) 实测 and the oil-bearing volume V. Due to factors such as the volatilization of light hydrocarbons in S1, the loss of S1 is large, which easily leads to a low value of S1 + S2. It is necessary to perform correlation correction on (S1 + S2) 实测 lower than the second fitting relationship according to the second fitting relationship to obtain (S1 + S2) 拟合校正 . Calculate the second correction coefficient K = (S1 + S2) 拟合校正 / (S1 + S2) 实测 , and calculate the arithmetic mean of the limited number of samples (N) to calculate the average value K0 of the second correction coefficient. Obtain (S1 + S2) 校正 = K0 * (S1 + S2) 实测 according to the correction relationship; establish the relationship between S 1校正 and (S1 + S2) 实测 , S 2实测 : S 1校正 = K0 * (S1 + S2) 实测 - R0 * S 2实测 ; perform pyrolysis analysis on the core sample to be tested, and measure S1实测 and S 2实测 Substitute into the above relational expression to obtain S 1校正 , and use S 1校正 to judge the oil-bearing property of the core sample to be detected.

[0032] In view of the unstable oil-bearing property of thin interbedded shale oil, the present invention conducts quantitative analysis on core samples, including pyrolysis analysis, three-dimensional quantitative fluorescence analysis, and laser confocal analysis, conducts correlation analysis on the obtained quantitative analysis data, and corrects the data obtained by pyrolysis analysis by using the data of three-dimensional quantitative fluorescence analysis and laser confocal analysis to obtain S 1校正 and S 1实测 , S 2实测 The relational expression can be used to accurately predict the oil-bearing property of samples without complex experimental analysis (three-dimensional quantitative fluorescence analysis, laser confocal analysis). Specifically, by conducting pyrolysis analysis on core samples on site and substituting the measured S 1实测 , S 2实测 into the relational expression of the present invention, a relatively accurate S 1校正 can be obtained. Using S 1校正 can judge the oil-bearing property of the core sample to be detected. The method of the present invention has the advantages of high accuracy and short identification time, and can be popularized and applied in other regions.

[0033] The following further illustrates the technical solution of the present invention by taking the core well samples in the shale oil development area of Dongpu Sag in combination with the attached drawings.

[0034] Example 1

[0035] This example provides a method for quickly and quantitatively identifying the oil-bearing property of thin interbedded shale oil.

[0036] Referring to Figure 1 , the method for quickly and quantitatively identifying the oil-bearing property of thin interbedded shale oil includes the following steps:

[0037] 1. Establish a geological model of thin interbedded shale oil, predict the oil-bearing property of the target area, and obtain the predicted oil-bearing interval.

[0038] According to the core data of adjacent wells of Well w318, establish a sedimentary pattern diagram of the shale combination in the target interval. This interval has the combination characteristics of massive sandstone and mudstone - laminated mudstone - laminated carbonate mud shale. Through seismic and logging data for well-seismic calibration, establish a geological model of the spatial distribution of the shale combination in this interval, and predict the oil-bearing characteristics of the target interval before the new well drilling starts.

[0039] 2. Drill the predicted oil-bearing interval, and qualitatively judge the oil-bearing property of the predicted oil-bearing interval according to gas logging anomaly values, core observation, and fluorescence display analysis.

[0040] 2.1. Determine the oil-bearing interval through gas logging anomaly analysis.

[0041] During the drilling process, when drilling to the target interval, continuously observe the total hydrocarbon gas logging anomaly value and the methane gas logging anomaly value.

[0042] The total hydrocarbon gas logging anomaly value ΔC 全 is calculated by the formula: ΔC 全 = C 全 peak / C 全 base value.

[0043] The calculation formula for the methane gas logging anomaly value ΔC1 is: ΔC1 = C1 peak / C1 base value.

[0044] Since oil-based drilling fluids are usually used to prevent wellbore collapse in some shale oil drilling, and oil-based drilling fluids have a greater impact on the total hydrocarbon due to their volatile components and a smaller impact on methane. According to the ratio ΔC (ΔC = ΔC1 / ΔC 全 ) of the methane gas logging anomaly value ΔC1 to the total hydrocarbon gas logging anomaly value ΔC 全 to select the gas logging anomaly identification criterion, and then more effectively reflect the gas logging anomaly value. When ΔC > 1, use the methane gas logging anomaly value ΔC1 as the gas logging anomaly identification criterion; when ΔC ≤ 1, use the total hydrocarbon gas logging anomaly value ΔC 全 as the gas logging anomaly identification criterion. Initially judge the oiliness according to the gas logging anomaly identification criterion.

[0045] According to the empirical values of the measured data, when the gas logging anomaly identification criterion > 10, it is considered that there is a gas logging anomaly, the oil and gas shows are active, and the qualitative evaluation is good oiliness; when the gas logging anomaly identification criterion is between 2 and 10, it is considered that there is a gas logging anomaly, and the qualitative evaluation of oiliness is medium; when the gas logging anomaly identification criterion < 2, it is considered that there is no gas logging anomaly, and the oiliness is poor or there is no oil.

[0046] Specifically, observe the gas logging value while drilling at any time before drilling to the target interval. Well w318 used a polysulfonate potassium salt drilling fluid when drilling to the target interval, and the density of the drilling fluid was 1.45 g / cm 3 . Under this condition, the gas logging anomaly value is not obvious. The peak value of the total hydrocarbon C 全 is 7.06%, and the base value is 0.938%. The total hydrocarbon gas logging anomaly value ΔC 全 is about 7; the peak value of C1 is 6.835%, and the base value is 0.513%. The methane gas logging anomaly value ΔC1 is about 13.32. ΔC = ΔC1 / ΔC 全 = 1.9. Using the methane gas logging anomaly as the identification criterion, ΔC1 = 13.32, which belongs to the active section of oil and gas shows and has good oiliness.

[0047] 2.2. Take samples from the oil-bearing interval to obtain cores and conduct core observation.

[0048] Take cores on-site, observe the appearance of the cores on-site, and preliminarily identify the oil-bearing property based on the oil and gas characteristics shown on the cores.

[0049] 2.3. Conduct fluorescence display on the cores, determine the fluorescence level according to the results of the fluorescence display. The higher the fluorescence level, the better the oil-bearing property. Select the cores with high fluorescence levels as the core samples of the oil-bearing intervals.

[0050] Place the cores on a fluorescence logging instrument, observe under a fluorescence lamp, describe the colors of dry illumination, wet illumination, and drop illumination, refer to Table 1 to determine the fluorescence level, and determine the oil-bearing property according to the fluorescence level. If the fluorescence level reaches above level three, it belongs to good oil-bearing property and the next-step analysis can be carried out.

[0051] Table 1 Relationship table between fluorescence characteristics and fluorescence levels

[0052]

[0053] 3. Conduct quantitative analysis on the core samples of the oil-bearing intervals to obtain quantitative analysis data; among them, the quantitative analysis includes pyrolysis analysis, three-dimensional quantitative fluorescence analysis, and laser confocal analysis.

[0054] Take samples from the cores with a fluorescence level higher than level three, take 4 samples at the same position, which are respectively used for three-dimensional quantitative fluorescence analysis, pyrolysis analysis, organic carbon analysis, and laser confocal analysis.

[0055] Conduct pyrolysis analysis on multiple groups of core samples of the oil-bearing intervals: Use a rock pyrolyzer on-site to conduct pyrolysis analysis on multiple samples to obtain the S1 (90 - 300 °C) and S2 (300 - 600 °C) values that can reflect the content of organic matter pyrolysis hydrocarbons at different temperature stages.

[0056] Send the samples back to the laboratory and use a total organic carbon analyzer to obtain the total organic carbon TOC content of the samples.

[0057] TOC analysis requires sending the samples back to the laboratory and undergoing complex pretreatment for a long time, and the experimental analysis cycle is long. However, TOC is an important indicator for evaluating the oil-bearing property. Under certain conditions, it has a good correlation with S1 + S2. The two are key parameters for evaluating the oil content and shale quality of shale oil, and to a certain extent, determine the quality of shale oil. During the test and analysis process of this well, correlation analysis was conducted between TOC and S1 and S1 + S2 respectively, and it was found that in thin interbedded shale oil, due to the strong heterogeneity of TOC and the easy volatilization of light hydrocarbons in thin layers, the correlation between TOC and S1 is not as good as that between TOC and S1 + S2. Refer to Figure 2 , establish a linear relationship between S1 + S2 and TOC through correlation analysis: S1 + S2 = 3 * TOC - 0.5, R 2= 0.8712, with a high degree of correlation. Pyrolysis data correction was only performed on the discrete point samples (19) on both sides of the regression curve.

[0058] Perform three-dimensional quantitative fluorescence analysis on core samples of multiple oil-bearing intervals: At the site, a total of multiple samples were processed using a three-dimensional quantitative fluorescence analyzer, ground into powder, soaked in n-hexane, and then tested and analyzed by the instrument. Quantitative fluorescence intensity data and three-dimensional fluorescence spectra were obtained, and the oiliness index Q was calculated. 荧光 。

[0059] Since three-dimensional quantitative fluorescence extracts the crude oil in the rock through the extraction of organic solvents, and the fluorescent substances in the crude oil are excited by a fluorescent lamp to emit fluorescence, the oil content is reflected according to the fluorescence intensity. At the same time, the oiliness index Q is obtained by the ratio of the maximum fluorescence intensity at the emission wavelength of 350 - 500 nm to the maximum fluorescence intensity at the emission wavelength of 200 - 3500 nm. 荧光 。During the sample processing, it is necessary to grind the sample into powder, which will cause a large amount of light hydrocarbons to volatilize, resulting in the distortion of the S1 value, while relatively difficult-to-volatilize heavy hydrocarbons remain. This index can reflect a part of the hydrocarbons S2 that are not easily volatilized in rock pyrolysis.

[0060] 4. Perform a correlation analysis on the pyrolysis analysis data and the three-dimensional quantitative fluorescence analysis data to establish the first fitting relationship between S 2实测 and the oiliness index Q 荧光 . Due to the influence of oil-based mud and foreign hydrocarbons, there will be some S2 values that are too high during the three-dimensional quantitative fluorescence test. It is necessary to perform correlation correction on the S 2实测 higher than the first fitting relationship according to the first fitting relationship to obtain S 2拟合校正 , calculate the first correction coefficient R = S 2拟合校正 / S 2实测 , and calculate the arithmetic mean R0 for 19 samples.

[0061] Reference Figure 3 , the first fitting relationship between the pyrolysis analysis data S 2实测 and the three-dimensional quantitative fluorescence analysis data Q 荧光 is: S2 = 3.0941 * Q 荧光 - 1.2342, R 2 = 0.9706, Figure 3 The straight line shown is the first fitting relationship. Fit and correct the sample S2 higher than the straight line to obtain S 2拟合校正 , calculate the first correction coefficient R = S 2拟合校正 / S 2实测 , and calculate the arithmetic mean R0 for 19 samples.

[0062] The average value R0 of the first correction coefficient is calculated by the following method: Among them, n is the number of core samples.

[0063] Using S 2实测 and the average value R0 of the first correction coefficient, S can be calculated 2校正 .

[0064] Perform laser confocal analysis on the core samples in the oil-bearing interval: Send the samples back to the laboratory, prepare the slides after pretreatment, perform laser scanning confocal analysis, obtain the oil state model diagram, and calculate the oil-bearing volumes of light hydrocarbons and heavy hydrocarbons.

[0065] 5. Conduct a correlation analysis on the pyrolysis analysis data and the laser confocal analysis data, and establish the second fitting relationship between (S1 + S2) 实测 and the oil-bearing volume V. Due to factors such as the volatilization of S1 light hydrocarbons, the loss of S1 is large, which easily leads to a low value of S1 + S2. It is necessary to correct (S1 + S2) 实测 lower than the second fitting relationship according to the second fitting relationship to obtain (S1 + S2) 拟合校正 , obtain the second correction coefficient K = (S1 + S2) 拟合校正 / (S1 + S2) 实测 , calculate the arithmetic mean value for 19 samples, calculate the average value K0 of the second correction coefficient, and obtain (S1 + S2) 校正 = K0 * (S1 + S2) 实测 .

[0066] During the laser confocal test, due to factors such as the volatilization of S1 light hydrocarbons, the loss of S1 is large, which easily leads to a low value of S1 + S2. Therefore, it is necessary to correct the low S1 + S2 value.

[0067] Refer to Figure 4 , the second fitting relationship between the pyrolysis analysis data (S1 + S2) 实测 and the laser confocal analysis data V is: S1 + S2 = 1.2723 * V + 0.0718, R 2 = 0.8034, Figure 4 The straight line shown is the second fitting relationship, and the discrete points below the straight line are fitted and corrected for (S1 + S2) 拟合校正 . Obtain the second correction coefficient K = (S1 + S2) 拟合校正 / (S1 + S2) 实测 , and calculate the arithmetic mean value for 19 samples to calculate the average value K0 of the second correction coefficient.

[0068] The average value K0 of the second correction coefficient is calculated by the following method: Among them, n is the number of core samples.

[0069] Using (S1 + S2) 实测The average value of the second correction coefficient K0 can be calculated as (S1 + S2) 校正 , (S1 + S2) 校正 = K0 * (S1 + S2)actual 测 .

[0070] 6. Establish the relationship between S 1校正 and (S1 + S2) 实测 , S 2实测 : S 1校正 = K0 * (S1 + S2) 实测 - R0 * S 2实测 .

[0071] Using the two barrels of cores from Well Wen 318, a total of 19 core samples were quantitatively analyzed. The specific test results are shown in Table 2. The test results in Table 2 were calculated according to the formula described above, and S 2拟合校正 = 3.0941 * Q - 1.2342, the average value of the first correction coefficient R0 = 0.976, and S 2校正 = R0 * S 2实测 = 0.976 * S 2实测 . The value of (S1 + S2) 拟合校正 = 1.2723 * V + 0.0718, the average value of the second correction coefficient K0 = 1.44, and (S1 + S2) 校正 = K0 * (S1 + S2) 实测 = 1.44(S1 + S2) 实测 .

[0072] Table 2 Test and analysis results of core samples

[0073]

[0074] 7. Conduct pyrolysis analysis on the core samples to be tested, substitute the measured S 1实测 , S 2实测 into the relationship formula to obtain S 1校正 , and use S 1校正 to judge the oil-bearing property of the core samples to be tested.

[0075] The corrected S 1校正 can more accurately reflect the oil-bearing characteristics. According to the evaluation parameters and standards for favorable areas of semi-brackish - brackish water type (non-interlayer salt) shale oil proposed in the Evaluation Specification for Continental Shale Oil Selection Areas of Sinopec, S 1校正 ≥ 3 is Class I, 2 ≤ S 1校正 < 3 is Class II, 1 ≤ S 1校正 < 2 is Class III.

[0076] Figure 5 is the comprehensive evaluation map of the oil-bearing property of Well W318, from Figure 5It can be seen that the corrected S1 value can be used to classify the oil-bearing types of the shale oil in the four sections of the core, distinguish the key oil-bearing intervals, and provide support for the subsequent fracturing.

[0077] The actual application results show that the present invention has good application effects in the identification of the oil-bearing properties of thin interbedded shale oil. The method is simple and practical, the calibration results are accurate and effective. The present invention can be used to guide the oil and gas exploration, development, production and research of the target basin, and has high practical value for the exploration and development of each oil and gas basin.

Claims

1. A method for rapidly and quantitatively identifying the oil-bearing property of thin interbedded shale oil, characterized in that, Including: Performing quantitative analysis on core samples of the oil-bearing interval to obtain quantitative analysis data; wherein, the quantitative analysis includes pyrolysis analysis, three-dimensional quantitative fluorescence analysis, and laser confocal analysis; The correlation analysis of thermal analysis data and three-dimensional quantitative fluorescence analysis data was carried out to establish S 2实测 and oiliness index Q 荧光 The first fitting relationship is higher than the S 2实测 According to the first fitting relationship, correlation correction is performed to obtain S 2拟合校正 , find the first correction coefficient R = S 2拟合校正 / S 2实测 , calculate the first correction coefficient average value R0, and obtain S according to the correction relationship 2校正 =R0*S 2实测 ; Perform a correlation analysis on the pyrolysis analysis data and the laser confocal analysis data to establish the second fitting relationship between (S1 + S2) 实测 and the oil volume V. For (S1 + S2) below the second fitting relationship 实测 perform correlation correction according to the second fitting relationship to obtain (S1 + S2) 拟合校正 , calculate the second correction coefficient K = (S1 + S2) 拟合校正 / (S1 + S2) 实测 , calculate the average value K0 of the second correction coefficient, and obtain (S1 + S2) 校正 = K0 * (S1 + S2) 实测 ; Establish S 1校正 The relationship with (S1 + S2) 实测 and S 2实测 is: S 1校正 = K0 * (S1 + S2) 实测 - R0 * S 2实测 ; Perform pyrolysis analysis on the core sample to be tested, and substitute the measured S 1实测 , S 2实测 into the above-mentioned relational expression to obtain S 1校正 , and use S 1校正 to judge the oil-bearing property of the core sample to be tested; Among them, S 1实测 and S 2实测 are pyrolysis analysis data, and (S1 + S2) 实测 is the sum of S 1实测 and S 2实测 .

2. The rapid quantitative identification method for oil-bearing property of thin interbedded shale oil according to claim 1, wherein, The first fitting relationship is: S 2实测 = a * Q 荧光 + b, where a and b are fitting parameters.

3. The rapid quantitative identification method for oil-bearing property of thin interbedded shale oil according to claim 1, characterized in that, The second fitting relationship is: (S1 + S2) 实测 = c * V + d, where c and d are fitting parameters.

4. The rapid quantitative identification method for oil-bearing property of thin interbedded shale oil according to claim 1, characterized in that The oil-bearing interval is determined by gas logging anomaly analysis, and the gas logging anomaly analysis includes the following steps: According to the ratio △C of the methane gas logging anomaly value △C1 to the total hydrocarbon gas logging anomaly value △C 全 to select a gas logging anomaly identification criterion; when △C > 1, the methane gas logging anomaly value △C1 is used as the gas logging anomaly identification criterion; when △C ≤ 1, the total hydrocarbon gas logging anomaly value △C 全 is used as the gas logging anomaly identification criterion; preliminarily judge the oiliness according to the gas logging anomaly identification criterion.

5. The rapid quantitative identification method for oil-bearing property of thin interbedded shale oil according to claim 4, wherein After the gas logging anomaly analysis, the method further includes: sampling the oil-bearing interval, observing the core and performing fluorescence display on the obtained core, determining the fluorescence level according to the result of the fluorescence display, the higher the fluorescence level represents better oiliness, and selecting the core with a high fluorescence level as the core sample of the oil-bearing interval.

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