Method for judging maturity of organic matter
By screening Raman spectral parameters and dividing the critical point of vitrinite reflectance, a correlation formula was established, which solved the problem of accurately quantifying the maturity of ultra-deep organic matter and improved the accuracy of oil and gas exploration.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHINA PETROLEUM & CHEMICAL CORP
- Filing Date
- 2022-08-03
- Publication Date
- 2026-06-02
AI Technical Summary
In the ultra-deep domain, existing technologies struggle to accurately quantify the maturity of highly mature organic matter, especially due to the limitations of vitrinite reflectance testing and the unclear application scope of laser Raman spectroscopy, leading to errors and erroneous judgments.
By obtaining the Raman spectral parameters of source rock samples, characteristic parameters with strong correlation to vitrinite reflectance were screened out. The fitting region was divided using the critical point of vitrinite reflectance, and a correlation formula was established. A suitable formula was selected to calculate vitrinite reflectance to determine the maturity of organic matter.
It enables accurate quantitative assessment of highly mature organic matter within an effective range, reduces errors, and provides technical support for oil and gas exploration in high-thermal-evolution basins.
Smart Images
Figure CN117554350B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of oil and gas exploration and development, and specifically relates to a method for judging the maturity of organic matter. Background Technology
[0002] For oil and gas exploration, source rocks that reached the hydrocarbon generation threshold and peak, or even a relatively high stage of maturity, during geological history are the ones that contribute to oil and gas reserves. Therefore, the study of source rock maturity is crucial for identifying favorable hydrocarbon-generating blocks and strata. In ultra-deep strata, the strata are generally quite old, and many lack materials of higher plant origin. Ancient strata are typically dominated by lower plankton, making it difficult to use traditional methods to measure the degree of thermal evolution. For example, vitrinite reflectance (Ro) is difficult to apply in ultra-deep strata. Vitrinite reflectance (Ro) is a universally accepted indicator of the thermal evolution of source rocks, but Devonian strata dating back 405 million years generally lack terrestrial plant vitrinite, making it impossible to determine the maturity of source rocks using conventional Ro testing techniques.
[0003] Prospectors primarily assess the maturity of organic matter through optical vitrinite reflectance testing. Generally, the measured data needs to specify whether "maximum reflectance" (Romax%), "average reflectance" (Romen%), or "random reflectance" (Roren%) is used. This results in discrepancies between the maturity of source rocks, especially during the high-temperature evolution stage, and the actual degree of thermal evolution. Consequently, it is impossible to accurately determine the maturity of source rocks using conventional vitrinite reflectance testing methods.
[0004] In existing technologies, for ultra-deep, high-thermal evolution fields, the first-order vibrational peak parameters of the Raman spectra of solid carbonaceous materials in sedimentary / metamorphic rocks are often analyzed to directly reflect the vibrational modes of molecules and crystals within the studied material, the molecular structure of carbonaceous materials, paleogeological temperature, and the maturity of organic matter evolution. With the continuous maturation of laser Raman spectroscopy, significant progress has been made in exploring the relationship between the Raman spectra of solid organic matter and the degree of thermal evolution. Different stages of metamorphism in the study area have been successfully delineated by measuring the Raman spectra of carbonaceous materials in sedimentary metamorphic rocks. However, while laser Raman spectroscopy can quantify the maturity of high-thermal-evolutionary organic matter, its applicable scope is not defined. The boundary between high-thermal-evolutionary organic matter and organic matter in medium- and low-thermal-evolutionary stages remains unclear. This may lead to an overgeneralization of its application when analyzing high-thermal-evolutionary organic matter, potentially resulting in errors or even misinterpretations. Summary of the Invention
[0005] The purpose of this invention is to provide a method for judging the maturity of organic matter, which solves the problem of accurately quantifying highly mature organic matter within an effective application range.
[0006] To achieve the above objectives, the present invention provides a technical solution for determining the maturity of organic matter, comprising the following steps:
[0007] 1) Obtain source rock samples within the calibration area, and select samples containing vitrinite for Raman spectroscopy determination;
[0008] 2) Perform significance analysis on each Raman spectral parameter, analyze the correlation between vitrin reflectance and each Raman spectral parameter, and select Raman spectral parameters whose correlation with vitrin reflectance is greater than the correlation threshold as characteristic parameters.
[0009] 3) By fitting the correlation between each feature parameter and vitrinite reflectance, determine the critical point of vitrinite reflectance and the corresponding critical point of each feature parameter; the critical point of vitrinite reflectance refers to the vitrinite reflectance threshold obtained during the fitting process of the correlation between feature parameters and vitrinite reflectance. When the vitrinite reflectance is greater than this threshold, the correlation between feature parameters and vitrinite reflectance becomes stronger.
[0010] 4) Establish correlation formulas between vitrinite reflectance and each characteristic parameter when the vitrinite reflectance value is less than the critical point of vitrinite reflectance, and obtain the corresponding correlation coefficients; establish correlation formulas between vitrinite reflectance and each characteristic parameter when the vitrinite reflectance value is greater than the critical point of vitrinite reflectance, and obtain the corresponding correlation coefficients.
[0011] 5) Obtain the characteristic parameter values of the source rock samples in the target area, and select the corresponding correlation formula as the judgment formula based on the relationship between each characteristic parameter value and the critical point of the corresponding characteristic parameter and the magnitude of the correlation coefficient.
[0012] 6) Substitute the characteristic parameter values into the judgment formula to calculate the vitrinite reflectance value, and judge the organic matter maturity of the target area based on the obtained vitrinite reflectance value.
[0013] This method calculates vitrinite reflectance by analyzing the Raman spectral characteristics of organic matter. First, it selects highly correlated characteristic parameters and fits them to the vitrinite reflectance. Then, based on the inflection points in the relationship between characteristic parameters and vitrinite reflectance at different thermal evolution stages—that is, the critical points of vitrinite reflectance—different fitting regions are defined. Fitting relationships with high correlation coefficients within these regions are used as the discrimination formula. Therefore, when judging the organic matter maturity of a target area, it can directly apply the more correlated judgment formula within each region based on the characteristic parameter values and critical points obtained from the target area, thus calculating a vitrinite reflectance that more closely matches the actual value, making the judgment of organic matter maturity in the target area more accurate.
[0014] Furthermore, in step 5), the conditions for selecting the judgment formula are as follows:
[0015] If all characteristic parameter values satisfy the first relationship condition between the characteristic parameter value and its critical point, then from the correlation formulas between vitrinite reflectance and each characteristic parameter when the vitrinite reflectance value is less than the critical point of vitrinite reflectance, the correlation formula with the largest correlation coefficient is selected as the judgment formula; the first relationship condition is the relationship between each characteristic parameter value and its critical point when the vitrinite reflectance value is less than the critical point of vitrinite reflectance.
[0016] If all characteristic parameter values satisfy the second relationship condition between the characteristic parameter value and its critical point, then from the correlation formulas between vitrinite reflectance and each characteristic parameter when the vitrinite reflectance value is greater than the critical point of vitrinite reflectance, the correlation formula with the largest correlation coefficient is selected as the judgment formula; the second relationship condition is the magnitude relationship between each characteristic parameter value and its critical point when the vitrinite reflectance value is greater than the critical point of vitrinite reflectance.
[0017] If a feature parameter value satisfies both the first relationship condition between the feature parameter value and its critical point and the second relationship condition between the feature parameter value and its critical point, then the feature parameter with the smallest absolute value of the difference between the feature parameter value and its critical point is selected. If the feature parameter satisfies the first relationship condition, then the correlation formula between vitrinite reflectance and the feature parameter when the vitrinite reflectance value is less than the vitrinite reflectance critical point is selected as the judgment formula. If the feature parameter satisfies the second relationship condition, then the correlation formula between vitrinite reflectance and the feature parameter when the vitrinite reflectance value is greater than the vitrinite reflectance critical point is selected as the judgment formula.
[0018] When obtaining the critical points corresponding to each characteristic parameter through the critical point of vitrinite reflectance, there is a certain error. Therefore, when selecting the judgment formula, inconsistencies may arise near the critical point depending on the value of the characteristic parameter. To resolve this overlap and obtain vitrinite reflectance calculations that are as close as possible to the actual values, since the fitting results of each correlation formula near the critical point are all applicable, in the event of the above situation, the judgment formula is directly determined according to the relationship condition satisfied by the characteristic parameter closest to the corresponding critical point and the correlation formula corresponding to that characteristic parameter. This ensures the uniqueness of the judgment formula and avoids significant errors.
[0019] Furthermore, the Raman spectral parameters mentioned in step 2) include at least the full width at half maximum (FWHM) of the G peak, the FWHM of the D peak, the height of the D peak, the height of the G peak, the peak position difference, and the peak intensity ratio.
[0020] Furthermore, the characteristic parameters are the peak position difference and the full width at half maximum (FWHM) of the G peak.
[0021] Furthermore, when the vitrinite reflectance value is less than the critical point for vitrinite reflectance, the correlation formula between vitrinite reflectance and various characteristic parameters is as follows:
[0022] The correlation formula between vitrinite reflectance and peak position difference is Ro = ae bRBS The corresponding correlation coefficient is X1; where Ro is the vitrinite reflectance, RBS is the peak position difference, and a and b are the fitted values.
[0023] The correlation formula between vitrinite reflectance and the full width at half maximum (FWHM) of the G peak is Ro = cln(G -FWHM The correlation coefficient is X², where Ro is the vitrinite reflectance and G is the vitrinite reflectance. -FWHM denoted as the full width at half maximum (FWHM) of peak G, and c and d are fitted values.
[0024] When the vitrinite reflectance value is greater than the critical point for vitrinite reflectance, the correlation formula between vitrinite reflectance and various characteristic parameters is as follows:
[0025] The correlation formula between vitrinite reflectance and peak position difference is Ro = fe gRBS The corresponding correlation coefficient is X3; where Ro is the vitrinite reflectance, RBS is the peak position difference, and f and g are the fitted values.
[0026] The correlation formula between vitrinite reflectance and the full width at half maximum (FWHM) of the G peak is Ro = hln(G -FWHM The correlation coefficient for )+i is X4, where Ro is the vitrinite reflectance and G... -FWHM Let G be the full width at half maximum (FWHM) of the peak, and h and i be the fitted values, respectively.
[0027] Furthermore, the correlation threshold mentioned in step 2) is 0.8.
[0028] Furthermore, the critical point for vitrinite reflectance is 2.0%.
[0029] Furthermore, the critical point for peak position difference is 260, and the critical point for the full width at half maximum (FWHM) of the G peak is 55. Attached Figure Description
[0030] Figure 1 This is a structural block diagram of the method for determining the maturity of organic matter according to the present invention;
[0031] Figure 2a This is a schematic diagram illustrating the correlation between the full width at half maximum (FWHM) of the D peak in the laser Raman spectrum of organic matter and the reflectance of vitrinite in an embodiment of the method for determining the maturity of organic matter according to the present invention.
[0032] Figure 2b This is a schematic diagram illustrating the correlation between the full width at half maximum (FWHM) of the G peak in the laser Raman spectrum of organic matter and the reflectance of vitrinite in an embodiment of the method for determining the maturity of organic matter according to the present invention.
[0033] Figure 2c This is a schematic diagram illustrating the correlation between the peak height of the D peak in the laser Raman spectrum of organic matter and the reflectance of vitrinite in an embodiment of the method for determining the maturity of organic matter according to the present invention.
[0034] Figure 2d This is a schematic diagram illustrating the correlation between the peak height of the G peak in the laser Raman spectrum of organic matter and the reflectance of vitrinite in an embodiment of the method for determining the maturity of organic matter according to the present invention.
[0035] Figure 2e This is a schematic diagram illustrating the correlation between the peak position difference of the organic matter laser Raman spectrum and the reflectance of vitrinite in the scale area of an embodiment of the method for judging the maturity of organic matter of the present invention.
[0036] Figure 2f This is a schematic diagram illustrating the correlation between the peak intensity ratio of the organic matter laser Raman spectrum and the reflectance of vitrinite in the scale area of an embodiment of the method for determining the maturity of organic matter of the present invention.
[0037] Figure 3a This is a correlation analysis diagram between peak position difference and vitrinite reflectance critical point when the vitrinite reflectance is less than the vitrinite reflectance critical point in an embodiment of the organic matter maturity determination method of the present invention.
[0038] Figure 3b This is a correlation analysis diagram of the half-width at half-maximum (FWHM) of the G peak and the critical point of vitrinite reflectance when the vitrinite reflectance is less than the critical point of vitrinite reflectance in an embodiment of the method for determining the maturity of organic matter of the present invention.
[0039] Figure 3c This is a correlation analysis diagram between peak position difference and vitrinite reflectance critical point when the vitrinite reflectance is greater than the vitrinite reflectance critical point in the embodiment of the organic matter maturity determination method of the present invention.
[0040] Figure 3d This is a correlation analysis diagram of the half-width at half-maximum (WHM) of the G peak and the critical point of vitrinite reflectance when the vitrinite reflectance is greater than the critical point of vitrinite reflectance in an embodiment of the method for determining the maturity of organic matter of the present invention. Detailed Implementation
[0041] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.
[0042] Example of a method for determining the maturity of organic matter
[0043] This embodiment provides a method for determining the maturity of organic matter, referring to... Figure 1 Based on examples from exploration areas A and B in the Sichuan Basin of China, the specific steps are as follows:
[0044] 1) Obtain source rock samples within the calibration area, and select samples containing vitrinite for Raman spectroscopy determination.
[0045] The maturity of organic matter is generally measured by the vitrinite reflectance, abbreviated as Ro (%). Both exploration areas A and B belong to the Sichuan Basin. Conventional vitrinite reflectance (Ro) tests on the maturity of marine high-to-overmature source rocks in exploration area A show that Ro does not increase with depth across different strata and depths. The reasons for this phenomenon are as follows: First, the vitrinite content is low. According to the national standard "Method for Determination of Vitrinite Reflectance in Sedimentary Rocks SY / T 5124—2012", when the average Ro > 2.0%, it is difficult to find more than 30 measurement points for optical Ro measurement, resulting in significant deviations in the test results. Second, in the high-maturity stage, organic matter micro-components such as vitrinite, inertinite, and chitinite evolve into amorphous forms, making accurate identification of vitrinite difficult. Third, during testing, when no vitrinite components are available, the asphaltene, graptol, and other components contained in the sample are usually tested, and the test results still deviate somewhat from the vitrinite Ro. The above three factors make it difficult to accurately calibrate the maturity of marine high-to-overmature source rocks in area A using Ro optical technology. Therefore, laser Raman spectroscopy is used to quantitatively calibrate the maturity of marine high-to-overmature source rocks in exploration area A.
[0046] For the source rock samples used in the calibration zone, the kerogen of the samples must contain vitrinite. Samples containing little or no vitrinite were discarded; only samples containing vitrinite were used for vitrinite reflectance (Ro) measurement. Before testing the samples, the laser Raman spectrometer was calibrated for spectral wavenumber using single-crystal silicon. The laser Raman spectrometer was a French Horiba Jobin Yvon model, with a sample micro-area of 2 μm, using an argon-ion laser with an excitation power of 10 mW, an excitation wavelength of 488 nm, a 600-line grating, and a laser power of approximately 0.45 mW illuminating the sample. A 50x objective lens was used, with an exposure time of 20 s, 6 cycles, and a scanning wavenumber range of 500–2500 cm⁻¹. -1 The testing time for each sample point is approximately 120 seconds.
[0047] Samples containing vitrinite were subjected to laser Raman spectroscopy. N points were selected for scanning and measurement of each standard sample. The original spectral parameters were calculated by the instrument's built-in spectral analysis software. In this embodiment, the selected laser Raman spectral parameters mainly included: D peak, G peak, RBS (peak position difference), and G... -FWHM (G peak half-width), D -FWHM (D peak half-width), I D (D peak height), I G (G peak height), where RBS (peak position difference) is W. D (D peak displacement) and W GThe difference in (G peak displacement); the specific test values of each parameter are shown in Table 1.
[0048] Table 1. Measured values of Ro and laser Raman spectral parameters for each sample in the calibration area.
[0049]
[0050]
[0051] 2) Perform significance analysis on each Raman spectral parameter, analyze the correlation between vitrinite reflectance and each Raman spectral parameter, and select Raman spectral parameters whose correlation with vitrinite reflectance is greater than the correlation threshold as characteristic parameters.
[0052] Reference Figures 2a-2f The significance of each Raman spectral parameter in Table 1 was analyzed using laser Raman spectroscopy, and the correlation between Ro and the six parameters in Table 1 was analyzed. Figure 2a This is a schematic diagram illustrating the correlation between the full width at half maximum (FWHM) of the D peak and the reflectance of vitrinite. Figure 2b This is a schematic diagram illustrating the correlation between the full width at half maximum (FWHM) of the G peak and the reflectance of vitrinite. Figure 2c This is a schematic diagram illustrating the correlation between the peak height of D and the reflectance of vitrinite. Figure 2d This is a schematic diagram illustrating the correlation between the peak height of G and the reflectance of vitrinite. Figure 2e This is a schematic diagram illustrating the correlation between peak position difference and vitrinite reflectance. Figure 2f This is a schematic diagram illustrating the correlation between peak intensity ratio and vitrinite reflectance.
[0053] In this embodiment, the correlation threshold is set to 0.8, which can be adjusted according to actual needs; through the above fitting, it was found that RBS (peak position difference) and G -FWHM The full width at half maximum (FWHM) of the G peak is strongly correlated with Ro, i.e., R 2 The correlation between R and the remaining Raman spectral parameters is greater than 0.8, and the correlation between R and the others is poor. 2 Both are less than 0.8. Therefore, in this embodiment, the peak position difference and the full width at half maximum (FWHM) of the G peak are selected as characteristic parameters.
[0054] 3) By fitting the correlation between each feature parameter and vitrinite reflectance, determine the critical point of vitrinite reflectance and the corresponding critical point of each feature parameter; the critical point of vitrinite reflectance refers to the vitrinite reflectance threshold obtained in the process of fitting the correlation between feature parameters and vitrinite reflectance. When the vitrinite reflectance is greater than this threshold, the correlation between feature parameters and vitrinite reflectance becomes stronger.
[0055] Through the characteristic parameters RBS (peak position difference) and G -FWHMFitting the correlation between (G peak half-width at half-maximum) and Ro revealed that after Ro exceeded a certain critical point, the characteristic parameters RBS and G... -FWHM When the correlation with Ro becomes stronger, meaning that each data point better fits the fitted function line, the Ro value corresponding to this critical point is defined as the critical point of vitrinite reflectance. The G value corresponding to the critical point of vitrinite reflectance is then... -FWHM The (G peak half-width at half-maximum) value is defined as the G-FWHM critical point, and the RBS (peak position difference) value corresponding to the vitrinite reflectance critical point is defined as the RBS critical point. According to... Figure 2b , Figure 2e Analysis shows that the Ro critical point is 2.0%, corresponding to an RBS critical point of 260, and G- FWHM The critical point is 55.
[0056] 4) Establish correlation formulas between vitrinite reflectance and each characteristic parameter when the vitrinite reflectance value is less than the critical point of vitrinite reflectance, and obtain the corresponding correlation coefficients; establish correlation formulas between vitrinite reflectance and each characteristic parameter when the vitrinite reflectance value is greater than the critical point of vitrinite reflectance, and obtain the corresponding correlation coefficients (i.e., R0). 2 ).
[0057] When the vitrinite reflectance value is less than the critical point for vitrinite reflectance, the correlation formula between vitrinite reflectance and various characteristic parameters is as follows:
[0058] The correlation formula between vitrinite reflectance and peak position difference is Ro = ae bRBS The corresponding correlation coefficient is X1; where Ro is the vitrinite reflectance, RBS is the peak position difference, and a and b are the fitted values.
[0059] The correlation formula between vitrinite reflectance and the full width at half maximum (FWHM) of the G peak is Ro = cln(G -FWHM The correlation coefficient is X², where Ro is the vitrinite reflectance and G is the vitrinite reflectance. -FWHM denoted as the full width at half maximum (FWHM) of peak G, and c and d are fitted values.
[0060] When the vitrinite reflectance value is greater than the critical point for vitrinite reflectance, the correlation formula between vitrinite reflectance and various characteristic parameters is as follows:
[0061] The correlation formula between vitrinite reflectance and peak position difference is Ro = fe gRBS The corresponding correlation coefficient is X3; where Ro is the vitrinite reflectance, RBS is the peak position difference, and f and g are the fitted values.
[0062] The correlation formula between vitrinite reflectance and the full width at half maximum (FWHM) of the G peak is Ro = hln(G -FWHM The correlation coefficient for )+i is X4, where Ro is the vitrinite reflectance and G... -FWHM Let G be the full width at half maximum (FWHM) of the peak, and h and i be the fitted values, respectively.
[0063] In this embodiment, the fitting result of the correlation formula is referenced. Figures 3a-3d :
[0064] When Ro < 2.0%, the correlation formula between vitrinite reflectance and peak position difference is Ro = 0.0001e 0.0371RBS This is denoted as Formula 1, and its corresponding correlation coefficient X1 = 0.8888; the correlation formula between vitrinite reflectance and the full width at half maximum (FWHM) of the G peak is Ro = -3.288ln(G -FWHM )+15.061, denoted as Formula 2, has a corresponding correlation coefficient X2=0.8418;
[0065] When Ro > 2.0%, the correlation formula between vitrinite reflectance and peak position difference is Ro = 0.00001e 0.04703RBS This is denoted as Formula 3, and its corresponding correlation coefficient X3 = 0.88793; the correlation formula between vitrinite reflectance and the full width at half maximum (FWHM) of the G peak is Ro = -7.609ln(G -FWHM )+32.434, denoted as Formula 4, has a corresponding correlation coefficient X4=0.945.
[0066] 5) Obtain the characteristic parameter values of source rock samples in the target area. Based on the relationship between each characteristic parameter value and the corresponding critical point of each characteristic parameter, as well as the magnitude of the correlation coefficient, select the corresponding correlation formula as the judgment formula.
[0067] According to step 4), the vitrinite reflectance critical point divides the data fitting into different fitting regions, namely, the fitting region where the vitrinite reflectance value is less than the vitrinite reflectance critical point and the fitting region where the vitrinite reflectance value is greater than the vitrinite reflectance critical point. For example, in this embodiment, the fitting regions are divided into Ro<2.0% and Ro>2.0%, so that the correlation formula that fits the region better is fitted in different regions. Therefore, in order to select the judgment formula that best fits the actual situation, it is first necessary to determine the fitting region that is relatively more in line with the actual situation.
[0068] Since the vitrinite reflectance value is known in step 4) when establishing the correlation formula, the fitting region can be directly determined through the vitrinite reflectance critical point. However, this step is actually a process of solving for the vitrinite reflectance value only when the characteristic parameter values are known. Therefore, it is necessary to determine the fitting region through the critical point of the characteristic parameter. For example, in this embodiment, according to the conclusion obtained in step 3), the Ro critical point is 2.0%, and the corresponding RBS critical point is 260. -FWHM The critical point is 55, combined with Figures 3a-3d It can be determined that the fitted region with Ro < 2.0% is related to RBS < 260 and G. -FWHM The cases with values >55 correspond to the fit regions where Ro > 2.0% and RBS > 260 and G.-FWHM The values <55 correspond to each other. Therefore, based on this correspondence, the fitting region can be determined by judging the relationship between the characteristic parameter values of the source rock samples in the target area and their critical points.
[0069] Ideally, the fitting regions corresponding to each feature parameter should be consistent. However, there is a certain error in obtaining the critical points for each feature parameter through the critical point of vitrinite reflectance. Therefore, when selecting the judgment formula, different feature parameters may have different fitting regions near the critical point, leading to inconsistent judgment formulas selected based on different feature parameters, such as the RBS and G of the sample. -FWHM The values are all near their corresponding critical points, with RBS < 260, corresponding to the fitting region of Ro < 2.0%, while G... -FWHM <55 corresponds to the fitting region where Ro>2.0%. Since this situation mainly occurs near the critical point, and the fitting results of various correlation formulas near the critical point all have a certain applicability, in order to resolve this contradictory situation and avoid excessively erroneous vitrinite reflectance calculation values, when the above situation occurs, the feature parameter with the smallest absolute value of the difference between its feature parameter value and its critical point is selected, and the correlation formula between the vitrinite reflectance in the fitting region corresponding to the feature parameter and the feature parameter is used as the judgment formula.
[0070] In this embodiment, the same sample simultaneously exhibits RBS < 260 and G -FWHM In the case where |RBS-260| < |G|, if |RBS-260| < |G|, the value is less than 55. -FWHM＜ If 55|, then select the fitting region where Ro < 2.0% corresponding to RBS < 260, and calculate the correlation between Ro and RBS in this fitting region using the formula Ro = 0.0001e. 0.0371RBS As a judgment formula; if |RBS-260|>|G -FWHM If <55|, then choose G. -FWHM <55 corresponds to the fitting region where Ro>2.0%, and Ro and G are used to fit this region. -FWHM The correlation formula is Ro = 0.0001e 0.0371RBS As a judgment formula, the above method of selecting the judgment formula can avoid large errors in the calculation value of vitrinite reflectance while ensuring the uniqueness of the judgment formula.
[0071] 6) Substitute the characteristic parameter values into the judgment formula to calculate the vitrinite reflectance value, and judge the organic matter maturity of the target area based on the obtained vitrinite reflectance value.
[0072] The distinction between high-mature organic matter and low-mature organic matter is usually expressed by vitrinite reflectance Ro (%). The choice of threshold for judging the size of the boundary varies in different situations. In some cases, Ro = 2.0% is considered to be the boundary between high, medium and low-mature organic matter, while in other cases, Ro = 1.3% is considered to be the boundary between high and medium and low-mature organic matter. This boundary may vary in different regions. In this embodiment, Ro = 1.3% is used as the boundary between high and medium and low-mature organic matter.
[0073] Based on the correlation formula fitted in step 5), different correlation formulas are applied as judgment formulas to different intervals of vitrin reflectance. Therefore, even when the vitrin reflectance Ro of the obtained sample has not been tested, G can be obtained through laser Raman analysis. -FWHM By substituting the half-width at half-maximum (FWHM) of the G peak and the RBS (peak position difference) into the selected judgment formula, the vitrinite reflectance of the sample in the target area can be directly and accurately calculated. This effectively determines the maturity of organic matter in the target area, solving the problem that the maturity of high-thermal evolution zones cannot be quantitatively determined using traditional methods.
[0074] In this embodiment, according to step 3), the RBS critical point is 260, G -FWHM The critical point is 55. Therefore, combining steps 4) and 5), the vitrinite reflectance value (Ro) of the target area is calculated to determine the maturity of the source rock. The calculated vitrinite reflectance value (Ro) is shown below. -ave The measured values are shown in Table 2.
[0075] Table 2. Calculation results of Ro value derived from the characteristic parameters of the target area samples.
[0076]
[0077]
[0078] This embodiment can accurately calculate the source rock maturity of corresponding areas in exploration zones A and B of the Sichuan Basin based on the precise vitrinite reflectance value. For samples with Ro values less than 1.0%, the determination of organic matter maturity using laser Raman spectroscopy may have some errors due to strong fluorescence interference. However, for samples with Ro values greater than 2.0%, the organic matter maturity determination method of this invention can provide detailed quantification, overcoming the influence of inaccurate high-temperature evolution tests and the absence of vitrinite in previous methods. This determination method can be widely applied to high-temperature evolution basins, providing important technical support for oil and gas exploration in high-temperature evolution basins.
[0079] The method of this invention calculates vitrinite reflectance by differentiating the Raman spectral characteristics of organic matter. First, it selects characteristic parameters with strong correlations and fits them with vitrinite reflectance. Then, based on the inflection points in the relationship between characteristic parameters and vitrinite reflectance at different thermal evolution stages, i.e., the critical points of vitrinite reflectance, it divides different fitting regions. The fitting relationship with the highest correlation coefficient within the region is used as the discrimination formula. Therefore, when judging the maturity of organic matter in the target area, it can directly apply the judgment formula with stronger correlation based on the characteristic parameter values and critical points of the characteristic parameters obtained from the target area, thereby calculating the vitrinite reflectance that is closer to the actual value, making the judgment of the maturity of organic matter in the target area more accurate.
[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.
Claims
1. A method for determining the maturity of organic matter, characterized in that, The steps are as follows: 1) Obtain source rock samples within the calibration area, and select samples containing vitrinite for Raman spectroscopy determination; 2) Perform significance analysis on each Raman spectral parameter, analyze the correlation between vitrin reflectance and each Raman spectral parameter, and select Raman spectral parameters whose correlation with vitrin reflectance is greater than the correlation threshold as characteristic parameters. 3) By fitting the correlation between each feature parameter and vitrinite reflectance, determine the critical point of vitrinite reflectance and the corresponding critical point of each feature parameter; the critical point of vitrinite reflectance refers to the vitrinite reflectance threshold obtained during the fitting process of the correlation between feature parameters and vitrinite reflectance. When the vitrinite reflectance is greater than this threshold, the correlation between feature parameters and vitrinite reflectance becomes stronger. 4) Establish correlation formulas between vitrinite reflectance and each characteristic parameter when the vitrinite reflectance value is less than the critical point of vitrinite reflectance, and obtain the corresponding correlation coefficients; establish correlation formulas between vitrinite reflectance and each characteristic parameter when the vitrinite reflectance value is greater than the critical point of vitrinite reflectance, and obtain the corresponding correlation coefficients. 5) Obtain the characteristic parameter values of the source rock samples in the target area, and select the corresponding correlation formula as the judgment formula based on the relationship between each characteristic parameter value and the critical point of the corresponding characteristic parameter and the magnitude of the correlation coefficient. 6) Substitute the characteristic parameter values into the judgment formula to calculate the vitrinite reflectance value, and judge the organic matter maturity of the target area based on the obtained vitrinite reflectance value.
2. The method for determining the maturity of organic matter according to claim 1, characterized in that, In step 5), the conditions for selecting the judgment formula are as follows: If all characteristic parameter values satisfy the first relationship condition between the characteristic parameter value and its critical point, then from the correlation formulas between vitrinite reflectance and each characteristic parameter when the vitrinite reflectance value is less than the critical point of vitrinite reflectance, the correlation formula with the largest correlation coefficient is selected as the judgment formula; the first relationship condition is the relationship between each characteristic parameter value and its critical point when the vitrinite reflectance value is less than the critical point of vitrinite reflectance. If all characteristic parameter values satisfy the second relationship condition between the characteristic parameter value and its critical point, then from the correlation formulas between vitrinite reflectance and each characteristic parameter when the vitrinite reflectance value is greater than the critical point of vitrinite reflectance, the correlation formula with the largest correlation coefficient is selected as the judgment formula; the second relationship condition is the magnitude relationship between each characteristic parameter value and its critical point when the vitrinite reflectance value is greater than the critical point of vitrinite reflectance. If a feature parameter value satisfies both the first relationship condition between the feature parameter value and its critical point and the second relationship condition between the feature parameter value and its critical point, then the feature parameter with the smallest absolute value of the difference between the feature parameter value and its critical point is selected. If the feature parameter satisfies the first relationship condition, then the correlation formula between vitrinite reflectance and the feature parameter when the vitrinite reflectance value is less than the vitrinite reflectance critical point is selected as the judgment formula. If the feature parameter satisfies the second relationship condition, then the correlation formula between vitrinite reflectance and the feature parameter when the vitrinite reflectance value is greater than the vitrinite reflectance critical point is selected as the judgment formula.
3. The method for determining the maturity of organic matter according to claim 1, characterized in that, The Raman spectral parameters mentioned in step 2) include at least the full width at half maximum (FWHM) of the G peak, the FWHM of the D peak, the height of the D peak, the height of the G peak, the peak position difference, and the peak intensity ratio.
4. The method for determining the maturity of organic matter according to claim 3, characterized in that, The characteristic parameters are peak position difference and G peak half width at half maximum (FWHM).
5. The method for determining the maturity of organic matter according to claim 4, characterized in that, When the vitrinite reflectance value is less than the critical point for vitrinite reflectance, the correlation formula between vitrinite reflectance and various characteristic parameters is as follows: The correlation formula between vitrinite reflectance and peak position difference is Ro = ae bRBS The corresponding correlation coefficient is X1; where Ro is the vitrinite reflectance, RBS is the peak position difference, and a and b are the fitted values. The correlation formula between vitrinite reflectance and the full width at half maximum (FWHM) of the G peak is Ro = cln(G -FWHM The correlation coefficient is X², where Ro is the vitrinite reflectance and G is the vitrinite reflectance. -FWHM denoted as the full width at half maximum (FWHM) of peak G, and c and d are fitted values. When the vitrinite reflectance value is greater than the critical point for vitrinite reflectance, the correlation formula between vitrinite reflectance and various characteristic parameters is as follows: The correlation formula between vitrinite reflectance and peak position difference is Ro = fe gRBS The corresponding correlation coefficient is X3; where Ro is the vitrinite reflectance, RBS is the peak position difference, and f and g are the fitted values. The correlation formula between vitrinite reflectance and the full width at half maximum (FWHM) of the G peak is Ro = hln(G -FWHM The correlation coefficient for )+i is X4, where Ro is the vitrinite reflectance and G... -FWHM Let G be the full width at half maximum (FWHM) of the peak, and h and i be the fitted values, respectively.
6. The method for determining the maturity of organic matter according to claim 1, characterized in that, The correlation threshold mentioned in step 2) is 0.
8.
7. The method for determining the maturity of organic matter according to claim 1, characterized in that, The critical point for vitrinite reflectance is 2.0%.
8. The method for determining the maturity of organic matter according to claim 7, characterized in that, The critical point for peak position difference is 260, and the critical point for the full width at half maximum (FWHM) of the G peak is 55.