Method for characterizing organic matter maturity based on mechanical properties

Abstract

The present invention discloses a method for characterizing the maturity of organic matter based on mechanical properties, belonging to the field of characterizing the maturity of organic matter. It includes measuring the vitrinite reflectance of a source rock sample to obtain the maturity of the organic matter in the source rock sample and establishing a sequence of organic matter maturity; using an atomic force microscope to measure the Young's modulus of the source rock sample to obtain the Young's modulus of the organic matter in source rock samples with different maturities; combining the sequence of organic matter maturity and the Young's modulus, and using the regression analysis method to construct an S model of the organic matter maturity and the Young's modulus; using an atomic force microscope to measure the Young's modulus of an unknown source rock sample, and using the S model to obtain the maturity of the organic matter in the unknown source rock sample. The present invention is applied to the characterization of the maturity of organic matter, solves various limitations and problems existing in the traditional characterization method and the spectroscopic technology characterization method for characterizing the maturity of organic matter, and has the characteristics of wide application range, small limitation and accurate analysis results.

Description

Technical Field

[0001] The present invention belongs to the technical field of organic matter maturity characterization, and particularly relates to a method for characterizing organic matter maturity based on mechanical properties. Background Technique

[0002] Maturity refers to the degree of thermal reaction of organic matter converting into oil and gas, which can characterize the hydrocarbon generation effectiveness of organic matter and the properties of products, understand the evolution mechanism of the physical-chemical process of organic matter, and is an important parameter for evaluating the amount of oil and gas resources. How to accurately characterize the maturity of organic matter is an important issue in source rock geochemistry.

[0003] The characterization of organic matter maturity has always been a research hotspot in the field of petroleum geology. The characterization of organic matter maturity mainly goes through two stages. The first stage is the traditional characterization method, and the second stage is the spectroscopic technology characterization method. Among them, in the traditional characterization method, vitrinite reflectance (Ro) is the most commonly used method, but it is not applicable to formations lacking terrigenous higher plant input and older strata. Therefore, for strata where it is difficult to obtain vitrinite reflectance, predecessors have established alternative equivalent models of solid bitumen, graptolite, etc. for vitrinite reflectance. However, due to anisotropy, this method also faces some uncertainties; the Tmax peak corresponding to the rock pyrolysis parameter S2 is also a commonly used parameter for obtaining thermal maturity. Predecessors have established models of Tmax and Ro under different conditions, but for high-maturity and low-TOC content strata, the S2 peak often does not develop, resulting in inaccurate determination of maturity; the C29 sterane isomerization parameter is a commonly used maturity biomarker index, but after Ro is greater than 1.0%, there is an isomerization equilibrium interval, which is not applicable to high-maturity and microbially degraded strata. It can be seen that the traditional maturity characterization methods have various limitations.

[0004] The spectroscopic technology characterization methods include spectroscopic technologies such as Raman spectroscopy (Raman), Fourier transform infrared spectroscopy (FTIR), and nuclear magnetic resonance spectroscopy (NMR). However, the above methods for characterizing maturity based on chemical structure have some common limitations: the test has certain requirements for the specifications of organic matter; it is greatly affected by the type of organic matter. Taking Raman spectroscopy as an example, the peak spacing (G-D1) of the maturity parameter has different regression curves in different types of organic matter; and the spectroscopic method cannot be quantified; the relationship between the structural parameters and Ro is not clear. These problems are all the difficulties restricting the application of spectroscopic technologies. Summary of the Invention

[0005] Aiming at the deficiencies of the existing technologies, the technical problem to be solved by the present invention is to overcome the various limitations and problems existing in the existing traditional characterization methods and spectroscopic technology characterization methods for characterizing the maturity of organic matter, and to propose a method for characterizing the maturity of organic matter based on mechanical properties with a wide application range, small limitations, and accurate analysis results.

[0006] To solve the above technical problems, the technical solution adopted by the present invention is as follows:

[0007] The present invention provides a method for characterizing the maturity of organic matter based on mechanical properties, including:

[0008] Steps for establishing an organic matter maturity sequence, including measuring the vitrinite reflectance of source rock samples to obtain the maturity of the organic matter in the source rock samples and establishing an organic matter maturity sequence;

[0009] Steps for obtaining Young's modulus, including measuring the Young's modulus of the source rock samples using an atomic force microscope to obtain the Young's modulus of the organic matter in source rock samples with different maturities;

[0010] Steps for constructing an S model, including combining the organic matter maturity sequence and the Young's modulus and using the regression analysis method to construct an S model of the organic matter maturity and Young's modulus;

[0011] Steps for determining the maturity of the organic matter in unknown source rock samples, including measuring the Young's modulus of the unknown source rock samples using an atomic force microscope and obtaining the maturity of the organic matter in the unknown source rock samples using the S model.

[0012] Preferably, it further includes: steps for verifying the results of vitrinite reflectance measurement, including, after the steps for establishing the organic matter maturity sequence, verifying the results of the organic matter maturity obtained from the vitrinite reflectance measurement using traditional biomarker parameters.

[0013] Preferably, the steps for verifying the results of vitrinite reflectance measurement specifically include: performing gas chromatography-mass spectrometry analysis on the saturated hydrocarbons in the organic matter, obtaining Ts / Ts+Tm, C29ααα20S / (20R+20S), 20R C29αββ / (αββ+ααα), and maturity parameters of hopane / tricyclic terpane, comparing their correlations with the vitrinite reflectance, and verifying the results of vitrinite reflectance measurement.

[0014] Preferably, it further includes: steps for selecting source rock samples, including selecting source rock samples at different depths before the steps for establishing the organic matter maturity sequence.

[0015] Preferably, the source rock samples in the steps for selecting source rock samples are from the Fengcheng Formation in the Mahu Sag and the Lucaogou Formation in the Jimusar Sag, the organic matter types are all type II1, and they are taken from different depths.

[0016] Preferably, the fitting equation of the S model is:

[0017]

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0019] The present invention provides a method for characterizing the maturity of organic matter based on mechanical properties, which does not require the identification of microscopic components of organic matter, is also applicable to high-maturity, low-TOC, and microbially degraded formations, is not affected by the specifications of organic matter, can measure the mechanical properties of organic matter at the nanoscale, the mechanical properties of organic matter are mainly affected by the degree of evolution and less affected by the type of organic matter, and the established model can quantitatively characterize the maturity of unknown source rocks, has a large correlation with Ro, and has the characteristics of a wide application range, small limitations, and accurate analysis results. Description of the Drawings

[0020] Figure 1 Schematic diagram of the microscopic characteristics of transmitted light vitrinite of the sample at 4096.60m in Well Fengnan-1 in the Mahu Sag of the Junggar Basin provided by the embodiment of the present invention;

[0021] Figure 2 Schematic diagram of the microscopic characteristics of fluorescent vitrinite of the sample at 4096.60m in Well Fengnan-1 in the Mahu Sag of the Junggar Basin provided by the embodiment of the present invention;

[0022] Figure 3 Schematic diagram of the microscopic characteristics of reflected light (air immersion) vitrinite of the sample at 4096.60m in Well Fengnan-1 in the Mahu Sag of the Junggar Basin provided by the embodiment of the present invention;

[0023] Figure 4 Schematic diagram of the microscopic characteristics of reflected light (oil immersion) vitrinite of the sample at 4096.60m in Well Fengnan-1 in the Mahu Sag of the Junggar Basin provided by the embodiment of the present invention;

[0024] Figure 5 Schematic diagram of the correlation between the depth and vitrinite reflectance Ro of 16 source rock samples in the Junggar Basin provided by the embodiment of the present invention;

[0025] Figure 6 Schematic diagram of the correlation between the maturity parameter C29ααα20S / (20R + 20S) of saturated hydrocarbon GC-MS biomarkers and vitrinite reflectance Ro of 16 samples in the Junggar Basin provided by the embodiment of the present invention;

[0026] Figure 7 Schematic diagram of the correlation between the maturity parameter 20R C29αββ / (αββ + ααα) of saturated hydrocarbon GC-MS biomarkers and vitrinite reflectance Ro of 16 samples in the Junggar Basin provided by the embodiment of the present invention;

[0027] Figure 8 Schematic diagram of the correlation between the maturity parameter Ts / Ts + Tm of saturated hydrocarbon GC-MS biomarkers and vitrinite reflectance Ro of 16 samples in the Junggar Basin provided by the embodiment of the present invention;

[0028] Figure 9Schematic diagram of the correlation between the maturity parameter of hopane / tricyclic terpane and vitrinite reflectance Ro for 16 saturated hydrocarbon GC-MS biomarker samples in the Junggar Basin provided by the embodiments of the present invention;

[0029] Figure 10 Organic matter image under an optical microscope of F20 in the Junggar Basin provided by the embodiments of the present invention;

[0030] Figure 11 Organic matter image under an optical microscope of X40 in the Junggar Basin provided by the embodiments of the present invention;

[0031] Figure 12 Distribution map a of the DMT modulus of organic matter in F20 in the Junggar Basin provided by the embodiments of the present invention;

[0032] Figure 13 Channel map of Peak Force Error of organic matter in X40 in the Junggar Basin provided by the embodiments of the present invention;

[0033] Figure 14 Distribution map b of the DMT modulus of organic matter in F20 in the Junggar Basin provided by the embodiments of the present invention;

[0034] Figure 15 Distribution map c of the DMT modulus of organic matter in X40 in the Junggar Basin provided by the embodiments of the present invention;

[0035] Figure 16 Frequency map of the DMT modulus distribution of organic matter in F20 in the Junggar Basin after Gaussian fitting provided by the embodiments of the present invention;

[0036] Figure 17 Frequency map of the DMT modulus distribution of organic matter in X40 in the Junggar Basin provided by the embodiments of the present invention;

[0037] Figure 18 Distribution map of the DMT modulus of J66 in the Junggar Basin provided by the embodiments of the present invention;

[0038] Figure 19 Frequency map of the DMT modulus distribution of J66 in the Junggar Basin after Gaussian fitting provided by the embodiments of the present invention;

[0039] Figure 20 Distribution map of the DMT modulus of FN5 in the Junggar Basin provided by the embodiments of the present invention;

[0040] Figure 21 Frequency map of the DMT modulus distribution of FN5 in the Junggar Basin after Gaussian fitting provided by the embodiments of the present invention;

[0041] Figure 22 Distribution map of the DMT modulus of J44 in the Junggar Basin provided by the embodiments of the present invention;

[0042] Figure 23 It is the frequency diagram of the DMT modulus distribution after Gaussian fitting in the Junggar Basin J44 provided by the embodiment of the present invention;

[0043] Figure 24 It is the DMT modulus distribution diagram of X40 in the Junggar Basin provided by the embodiment of the present invention;

[0044] Figure 25 It is the frequency diagram of the DMT modulus distribution after Gaussian fitting in the Junggar Basin X40 provided by the embodiment of the present invention;

[0045] Figure 26 It is the S model of the maturity Ro of the source rock in the Junggar Basin and the Young's modulus provided by the embodiment of the present invention;

[0046] Figure 27 It is the Raman spectrogram at different positions in the organic matter provided by the embodiment of the present invention;

[0047] Figure 28 It is the schematic diagram of the maturity of the FN5 sample obtained by the Ro and RBS models established by Robust provided by the embodiment of the present invention;

[0048] Figure 29 It is the frequency distribution diagram of the DMT modulus after Gaussian function fitting for the unknown source rock sample provided by the embodiment of the present invention;

[0049] Figure 30 It is the schematic diagram of the maturity of the unknown source rock sample obtained by the established S model provided by the embodiment of the present invention. Detailed implementation manners

[0050] Next, the technical solutions in the specific embodiments of the present invention will be described in detail and completely with reference to the accompanying drawings. Obviously, the described embodiments are only partial specific implementation manners of the overall technical solution of the present invention, rather than all implementation manners. Based on the overall concept of the present invention, all other embodiments obtained by those of ordinary skill in the art fall within the protection scope of the present invention.

[0051] The present invention provides a method for characterizing the maturity of organic matter based on mechanical properties, including:

[0052] Steps for establishing the organic matter maturity sequence include measuring the vitrinite reflectance (Ro) of source rock samples to obtain the organic matter maturity of the source rock samples and establishing the organic matter maturity sequence. In this step, the maturity of source rock samples at different depths is measured, and the most commonly used vitrinite reflectance is used to calibrate the maturity, and a maturity sequence from low maturity to high maturity is established. It should be noted that the reason for establishing the maturity sequence from low maturity to high maturity is that it is beneficial to measure the Young's modulus of organic matter in samples with different maturities and explore the correlation between the Young's modulus of organic matter and maturity.

[0053] Steps for obtaining the Young's modulus include measuring the Young's modulus of the source rock samples using an atomic force microscope to obtain the Young's modulus of the organic matter in source rock samples with different maturities; steps for constructing the S model include combining the organic matter maturity sequence and the Young's modulus and using the regression analysis method to construct the S model of the organic matter maturity and the Young's modulus. The atomic force microscope (AFM) measurement technology realizes the characterization of the mechanical properties of organic matter at the nanoscale. In this step, the quantitative nano-imaging technology of the atomic force microscope AFM is used to measure the Young's modulus of organic matter, analyze the differences in the Young's modulus of organic matter at different maturities, and establish the S model of the organic matter maturity Ro and the Young's modulus. It should be noted that Emmanuel et al. found that there is a potential connection between the mechanical property parameter Young's modulus of organic matter and maturity, and this connection is related to the shedding of organic matter fatty groups and the enrichment of aromatic groups. However, they did not explore the correlation between the mechanical property parameter Young's modulus of organic matter and maturity. The technical solution of the present invention takes into account that the physical and chemical properties of organic matter will change during the maturation process and provides a new idea for using the mechanical properties of organic matter to characterize the organic matter maturity.

[0054] Steps for determining the organic matter maturity of unknown source rock samples include measuring the Young's modulus of the unknown source rock samples using an atomic force microscope and obtaining the organic matter maturity of the unknown source rock samples using the S model.

[0055] The method for characterizing the organic matter maturity provided by the present invention provides a new technical method for characterizing the organic matter maturity, provides a new window for studying and understanding the mechanical behavior of organic matter during the hydrocarbon generation and evolution process, provides a new method for characterizing the organic matter maturity based on mechanical properties, and has important significance for source rock evaluation. This method does not require the identification of organic matter macerals, is also applicable to high-maturity, low-TOC, and microbially degraded strata, is not affected by the specifications of organic matter, can measure the mechanical properties of organic matter at the nanoscale, the mechanical properties of organic matter are mainly affected by the degree of evolution and less affected by the type of organic matter, and the established model can quantitatively characterize the maturity of unknown source rocks, has a large correlation with Ro, and has the characteristics of a wide application range, small limitations, and accurate analysis results.

[0056] In a preferred embodiment, it further includes a step of verifying the determination result of vitrinite reflectance, including, after the step of establishing the organic matter maturity sequence, verifying the result of the organic matter maturity obtained by the determination of vitrinite reflectance by using traditional biomarker parameters. Optionally, the step of verifying the determination result of vitrinite reflectance specifically includes: performing gas chromatography-mass spectrometry (GC-MS) analysis on the saturated hydrocarbons in the organic matter to obtain Ts / Ts+Tm, C29ααα20S / (20R+20S), 20R C29αββ / (αββ+ααα), and hopane / tricyclic terpane maturity parameters, comparing their correlation with the vitrinite reflectance, and verifying the determination result of vitrinite reflectance.

[0057] In a preferred embodiment, it further includes: a step of selecting hydrocarbon source rock samples, including selecting hydrocarbon source rock samples at different depths before the step of establishing the organic matter maturity sequence. Optionally, the study area is the Junggar Basin, and the hydrocarbon source rock samples in the step of selecting hydrocarbon source rock samples are from the Fengcheng Formation in the Mahu Sag and the Lucaogou Formation in the Jimusar Sag, and the organic matter types are all type II1, taken from different depths, which is conducive to establishing the organic matter maturity sequence.

[0058] In a preferred embodiment, the fitting equation of the S model is:

[0059]

[0060] The correlation R of the above fitting equation 2 reaches 0.9667, indicating the strong potential of characterizing maturity based on AFM mechanical properties. The increase in the modulus value has obvious stages. During the organic matter maturation process, the turning points of its mechanical behavior correspond to the key stages of oil-gas conversion, namely the oil generation threshold (Ro = 0.7%), the peak oil generation stage (Ro = 1.0%), and the high-maturity oil-gas stage (Ro = 1.3%).

[0061] In order to introduce the method for characterizing the maturity of organic matter based on mechanical properties provided by the embodiments of the present invention more clearly and in detail, the following will be described in combination with specific embodiments.

[0062] Example 1

[0063] Taking the hydrocarbon source rock samples from the Fengcheng Formation in the Mahu Sag and the Lucaogou Formation in the Jimusar Sag of the Junggar Basin as examples, a new method for characterizing the maturity of organic matter provided by the present invention will be introduced in detail.

[0064] S1: Select hydrocarbon source rock samples at different depths

[0065] The Fengcheng Formation in the Mahu Sag and the Lucaogou Formation in the Jimusar Sag of the Junggar Basin are two important source rock series. The salt lake of the Lucaogou Formation to the alkaline lake of the Fengcheng Formation represents the saline-alkali sequence of salinized lakes, which is a typical source rock in salinized lake basin facies. The organic matter types are all type II1. The core sampling depths vary from 2576.00 m to 5662.00 m, which is conducive to establishing the maturity sequence of organic matter in the natural section.

[0066] S2: Measure the vitrinite reflectance (Ro) of source rock samples to establish the maturity sequence

[0067] The most commonly used vitrinite reflectance Ro is used to calibrate the maturity. The instruments for measuring Ro are Zeiss Axioskop 40 pol microscope and MSP210 photometer. The key to Ro measurement lies in the identification of vitrinite. Vitrinite is brownish-red under transmitted light (as Figure 1 shown), without fluorescence (as Figure 2 shown), different from sapropel group. Under reflected light air immersion, it has a higher relief compared with surrounding minerals (as Figure 3 shown), and is darker than inertinite group under oil immersion (as Figure 4 shown). The vitrinite reflectance of 16 source rock samples ranges from 0.52% to 1.45%, mainly in the oil generation window, and has a strong correlation with depth (as Figure 5 shown), which is consistent with the actual geological situation.

[0068] S3: Use traditional biomarker parameters to test the Ro measurement results

[0069] In this study, the vitrinite reflectance is a very important parameter, and the accuracy of the measurement needs to be tested. Perform GC-MS analysis on saturated hydrocarbons to obtain maturity parameters such as Ts / Ts+Tm, C 29 sterane isomerization parameter, hopane / terpane, etc., to see the correlation with vitrinite reflectance. The results show that the vitrinite reflectance has a high correlation with biomarker maturity parameters (as Figure 6 、 7 、8、9 shown), indicating the accuracy of the Ro measurement results.

[0070] S4: Use atomic force microscope (AFM) to measure the Young's modulus of organic matter with different maturities and establish the "S model" of maturity Ro and Young's modulus

[0071] Use atomic force microscope quantitative nanoimaging technology (AFM-QNM) to in-situ measure the Young's modulus of organic matter. When preparing samples for AFM experiments, first polish with diamond suspension, and then perform argon ion polishing on the samples with an acceleration voltage of 4 kv to make the sample surface as smooth as possible and reduce the influence of surface roughness during scanning. When measuring the elastic modulus of organic matter based on AFM, it is necessary to first find the organic matter to be measured under the microscope (asFigure 10 , 11 As shown in 11 . Organic matter is softer than inorganic minerals and can be quickly located in the DMT modulus distribution map and the Peak Force Error channel (as shown in Figure 12 Figure 12 , 13 ). Then, local scanning is performed (as shown in Figure 14 Figure 14 , 15 ), and Gaussian fitting is performed on the DMT modulus distribution frequency map to obtain the elastic modulus of the organic matter (as shown in Figure 16 Figure 16 , 17 ). The scale of the modulus map is uniformly adjusted to 0 - 15 GPa. Low-maturity organic matter is green (as shown in Figure 18 Figure 18 , 19 ), mature organic matter is blue and cyan (as shown in Figure 20 Figure 20 , 21 ), and high-maturity organic matter is pink (as shown in Figure 24 Figure 24 , 25 ). The maturity stage can be effectively characterized through the mechanical modulus map. The modulus distribution range of the scanned organic matter is 2.1 - 14.78 GPa, and as the maturity increases, the modulus value increases in an S shape. Fitting with the Slogistic model, the correlation coefficient R2 reaches 0.9667, indicating the great potential of characterizing maturity based on the AFM mechanical properties (as shown in Figure 26 Figure 26 ).

[0072] Fitting equation of the Slogistic1 model: R 2 = 0.9667.

[0073] The increase in the modulus value has obvious stages. During the maturation process of organic matter, the turning points of its mechanical behavior correspond to the key stages of oil - gas conversion, namely the oil - generation threshold (Ro = 0.7%), the peak of oil - generation (Ro = 1.0%), and high - maturity oil - gas (Ro = 1.3%).

[0074] S5: Determine the maturity of the unknown source rock sample

[0075] Sample number FN5 - 4065.50m:

[0076] (1) The measured result of vitrinite reflectance (Ro) is 1.13%.

[0077] (2) The Raman spectroscopy maturity parameter (RBS) is 240 cm -1 (as shown in Figure 27 Figure 27 ), and the maturity Ro obtained according to the Ro - RBS model established by Robust is 1.15% (as shown in Figure 28 Figure 28 ).

[0078] (3) The DMT modulus of the sample was obtained as 12.10 GPa using the AFM-QNM technique (as Figure 29 shown).

[0079] The Derjaguin-Muller-Toporov (DMT) modulus can be obtained from the force-distance curve, as shown in Equation 1. After calculating the DMT modulus, the Young's modulus value can be obtained through Equation 2.

[0080]

[0081] In the formula, Fapplied is the force applied by the tip, E* is the DMT modulus, R is the tip radius, δ is the depth of the pit caused by the tip indentation, and Fadhesion is the adhesion force between the tip and the surface of the scanned sample.

[0082]

[0083] In the formula, E* is the DMT modulus, Vs is the Poisson's ratio of the sample, Es is the Young's modulus of the sample, Vtip is the Poisson's ratio of the selected tip, and Etip is the Young's modulus of the selected tip.

[0084] According to the above formula, the Young's modulus of the sample was obtained as 11.90 GPa, and the Ro obtained from the "S model" of the maturity Ro and the Young's modulus established by the present invention was 1.14% (as Figure 30 shown).

[0085] The maturity results obtained by the above three methods are shown in Table 1.

[0086] Table 1 Maturity results obtained by different methods

[0087]

[0088]

[0089] As can be seen from the results in Table 1, the "S model" of the maturity Ro and the Young's modulus established based on the present invention can accurately characterize the organic matter maturity.

Claims

1. A method for characterizing the maturity of organic matter based on mechanical properties, characterized in that Including: Steps for establishing the organic matter maturity sequence, including measuring the vitrinite reflectance of the source rock sample to obtain the organic matter maturity of the source rock sample and establishing the organic matter maturity sequence; Steps for obtaining the Young's modulus, including measuring the Young's modulus of the source rock sample using an atomic force microscope to obtain the Young's modulus of the organic matter in source rock samples with different maturities; Steps for constructing the S model, including combining the organic matter maturity sequence and the Young's modulus and using the regression analysis method to construct the S model of the organic matter maturity and the Young's modulus; Steps for determining the organic matter maturity of an unknown source rock sample, including measuring the Young's modulus of the unknown source rock sample using an atomic force microscope and obtaining the organic matter maturity of the unknown source rock sample using the S model.

2. The method for characterizing the maturity of organic matter based on mechanical properties according to claim 1, wherein Also including: Steps for verifying the result of the vitrinite reflectance measurement, including, after the steps for establishing the organic matter maturity sequence, verifying the result of the organic matter maturity obtained from the vitrinite reflectance measurement using traditional biomarker parameters.

3. The method for characterizing the maturity of organic matter based on mechanical properties according to claim 2, wherein The steps for verifying the result of the vitrinite reflectance measurement specifically include: Performing gas chromatography-mass spectrometry analysis on the saturated hydrocarbons in the organic matter, obtaining Ts / Ts+Tm, C29ααα20S / (20R+20S), 20RC29αββ / (αββ+ααα), and hopane / tricyclic terpane maturity parameters, comparing their correlation with the vitrinite reflectance, and verifying the result of the vitrinite reflectance measurement.

4. The method for characterizing the maturity of organic matter based on mechanical properties according to claim 1, characterized in that, Also including: Steps for selecting the source rock sample, including selecting source rock samples at different depths before the steps for establishing the organic matter maturity sequence.

5. The method for characterizing the maturity of organic matter based on mechanical properties according to claim 4, wherein, The source rock samples in the steps for selecting the source rock sample are from the Fengcheng Formation in the Mahu Sag and the Lucaogou Formation in the Jimusar Sag, the organic matter types are both type Ⅱ1, and they are taken from different depths.

6. The method for characterizing the maturity of organic matter based on mechanical properties according to claim 1, wherein The fitting equation of the S model is:

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