Method for evaluating shale oil geochemical index under oil-based mud system

Abstract

The application provides a shale oil geochemical index evaluation method, and relates to the field of oil and gas exploration, and comprises the following steps: establishing a mathematical model of geochemical indexes under an oil-based mud system; measuring the organic carbon TOC content under a water-based mud system and the organic carbon TOC content under the oil-based mud system of multiple same depths of the same reference well; establishing a linear regression equation of the geochemical indexes under the oil-based mud system according to the mathematical model of the geochemical indexes and the measurement results; determining the organic carbon TOC content under the water-based mud system of a to-be-predicted area based on the linear regression equation; and evaluating the geochemical indexes of the to-be-predicted area according to the organic carbon TOC content under the water-based mud system of the to-be-predicted area. The evaluation method only needs to measure the organic carbon TOC content under the oil-based mud system of the same well, and uses the organic carbon TOC content under the water-based mud system to evaluate the geochemical parameters according to the regression equation, thereby improving the accuracy of the evaluation of the geochemical indexes.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oil and gas exploration, and particularly relates to a method for evaluating geochemical indexes of shale oil under an oil-based mud system. BACKGROUND

[0002] Unconventional oil and gas exploration and development is mainly aimed at drilling in mud shale strata. Land-based mud shale strata in China are faced with problems such as complex lithofacies types, high clay mineral content, and easy collapse and loss of strata, and therefore, an oil-based mud drilling fluid system is often used in the drilling process to maintain wellbore stability.

[0003] In the prior art, the organic carbon TOC content under a water-based mud system is usually used to evaluate geochemical indexes of a target area in the drilling process, and the mud does not need to be considered for the test result of the organic carbon TOC content (one of the geochemical indexes). In the drilling process of some unconventional shale oil and gas horizontal wells, in order to maintain wellbore stability, the TOC content under an oil-based mud system is used to evaluate the geochemical indexes of the target area, which has an impact on the test of the organic carbon TOC content, and the numerical value of the test result is usually high, and the accuracy of the evaluation is low. SUMMARY

[0004] The present application provides a method for evaluating geochemical indexes of shale oil under an oil-based mud system, which is used to improve the accuracy of the evaluation of the geochemical indexes.

[0005] To achieve the above-mentioned purpose, the present application provides a method for evaluating geochemical indexes of shale oil, which comprises the following steps:

[0006] establishing a mathematical model of the geochemical indexes under the oil-based mud system;

[0007] measuring the organic carbon TOC content under the water-based mud system and the organic carbon TOC content under the oil-based mud system at the same depth of the same reference well;

[0008] establishing a linear regression equation of the geochemical indexes under the oil-based mud system according to the mathematical model of the geochemical indexes and the measured results;

[0009] determining the organic carbon TOC content under the water-based mud system of a to-be-predicted area based on the linear regression equation;

[0010] evaluating the geochemical indexes of the to-be-predicted area according to the organic carbon TOC content under the water-based mud system of the to-be-predicted area.

[0011] In some embodiments of the present application, the mathematical model is Y=a+bX, wherein Y is the organic carbon TOC content under the water-based mud system, X is the organic carbon TOC content under the oil-based mud system, a is a regression constant, and b is a regression coefficient.

[0012] In some embodiments of this application, the actual measurement of the total organic carbon (TOC) content in multiple water-based mud systems and oil-based mud systems at the same depth in the same reference well includes:

[0013] The total organic carbon (TOC) content in n water-based mud systems and oil-based mud systems at the same depth was measured to obtain the measured value array Y of the TOC content in the water-based mud system. a =[Y1,Y2,…,Y n [, and obtain the measured value array X of the total organic carbon (TOC) content in the oil-based mud system.] a =[X1,X2,…,X n ], where Y n Let X be the total organic carbon (TOC) content in the nth water-based mud system. n Let be the total organic carbon (TOC) content in the nth oil-based mud system, where n ≥ 31.

[0014] In some embodiments of this application, establishing linear regression equations for geochemical indices in oil-based mud systems based on mathematical models and measured results of geochemical indices includes:

[0015] The regression constant and regression coefficients are calculated according to equation (1).

[0016]

[0017] In equation (1), Y i Let TOC be the organic carbon content in the i-th water-based mud system. X represents the average of the measured TOC content across all water-based mud systems. i Let TOC be the total organic carbon content in the i-th oil-based mud system. The average value of the measured TOC content in all oil-based mud systems is given by , where a is the regression constant and b is the regression coefficient.

[0018] Substituting the regression constant and regression coefficient into the mathematical model of the localization index under the oil-based mud system yields the linear regression equation of the localization index under the oil-based mud system.

[0019] In some embodiments of this application, the linear regression equation is: Y = -2.8599 + 1.0676X, where Y is the total organic carbon (TOC) content in the water-based mud system and X is the total organic carbon (TOC) content in the oil-based mud system.

[0020] In some embodiments of this application, the evaluation method for shale oil geochemical indicators further includes: verifying the linear regression equation;

[0021] If the linear regression equation is verified to be reasonable, an organic carbon TOC content of a water-based mud system in the to-be-predicted area is determined based on the linear regression equation, and a geochemical index of the to-be-predicted area is evaluated according to the organic carbon TOC content of the water-based mud system in the to-be-predicted area.

[0022] In some embodiments of the present application, the verifying the linear regression equation comprises verifying the linear regression equation with a correlation coefficient according to formula (2),

[0023]

[0024] In formula (2), R is a correlation coefficient, Y i is an organic carbon TOC content of an i-th water-based mud system, Y′ i is a fitting value corresponding to X i according to the linear regression equation, is an average of measured values of the organic carbon TOC contents of all water-based mud systems.

[0025] In some embodiments of the present application, the verifying the linear regression equation comprises verifying the linear regression equation with significance of a regression coefficient according to formula (3),

[0026]

[0027] In formula (3), t b is significance of a regression coefficient, b is a regression coefficient, X i is an organic carbon TOC content of an i-th oil-based mud system, is an average of measured values of the organic carbon TOC contents of all oil-based mud systems, Y i is an organic carbon TOC content of an i-th water-based mud system, Y′ i corresponding to X i according to the linear regression equation.

[0028] In some embodiments of the present application, the verifying the linear regression equation comprises verifying the linear regression equation with significance of a regression equation according to formula (4),

[0029]

[0030] In formula (4), F is significance of a regression equation, Y′ i corresponding to X i according to the linear regression equation, is an average of measured values of the organic carbon TOC contents of all water-based mud systems, Y i is an organic carbon TOC content of an i-th water-based mud system.

[0031] In some embodiments of the present application, the determining the organic carbon TOC content under the water-based mud system of the area to be predicted based on the linear regression equation comprises:

[0032] measuring the organic carbon TOC content under the oil-based mud system of the area to be predicted;

[0033] calculating the organic carbon TOC content under the water-based mud system of the area to be predicted according to the organic carbon TOC content under the oil-based mud system of the area to be predicted and the linear regression equation.

[0034] The present application has the following beneficial effects:

[0035] The shale oil geochemical index evaluation method provided by the present application takes advantage of the fact that the water-based mud has little effect on the organic carbon TOC content, establishes a regression equation between the organic carbon TOC content under the water-based mud system and the organic carbon TOC content under the oil-based mud system by using the actual measurement results, only needs to measure the organic carbon TOC content under the oil-based mud system of one well (reference well), calculates the organic carbon TOC content under the water-based mud system of the area to be predicted according to the regression equation, and evaluates the geochemical parameters of other wells in the area to be predicted according to the regression equation and the organic carbon TOC content under the water-based mud system, which improves the accuracy of the geochemical index evaluation by more than 80.1% on average, reaching more than 98%, and improves the average work efficiency by more than 70%. In the drilling process, the benefits brought by the oil-based mud for the well wall are ensured, and the pollution of the oil-based mud to the rock or cuttings is avoided, which can objectively evaluate the organic carbon content, restore the actual value of the organic carbon TOC content under the water-based mud system, and make up for the deficiencies brought by the oil-based mud drilling fluid, thereby ensuring the reliability of the geochemical index. BRIEF DESCRIPTION OF DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0037] Figure 1 is a flowchart of the shale oil geochemical index evaluation method in the embodiments of the present application. DETAILED DESCRIPTION

[0038] The embodiments of the present application will be further described in detail below in combination with the drawings and examples. The terms used in the embodiments of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the present application.

[0039] In the prior art, Ma Yongsheng et al. published in Acta Geologica 2022, Vol. 96, No. 1, “Geological characteristics and exploration practice of continental shale oil in China” records: Continental shale oil as an important replacement field for increasing reserves and production of oil and gas in China is increasingly attracting widespread attention. This paper systematically expounds the geological characteristics, theoretical and technical research progress of continental shale oil in China, and prospects the development prospects of continental shale oil: (1) Compared with North American marine shale, Chinese continental shale has the characteristics of strong heterogeneity, large cumulative thickness, small distribution area, relatively low thermal evolution degree, and diverse organic matter types; (2) China's continental lake basins mainly include faulted basins and depressed basins, with diverse shale deposition environments, mainly developing two types of sedimentary systems rich in carbonate and felsic, freshwater, brackish water, salt lake environments can form organic-rich shale; Continental shale generally has good reservoir properties, with inorganic pores and microfractures as the main reservoir space types, and organic pores gradually increase with increasing thermal evolution degree; (3) Organic matter abundance, lithofacies type, thermal evolution degree, preservation conditions, flowability and fracturability are the main factors controlling the enrichment and high production of continental shale oil in China; (4) After years of research, a series of technologies for continental shale oil evaluation, sweet spot geophysical prediction, long horizontal well drilling and completion, and staged fracturing reconstruction have been formed, providing effective support for the exploration breakthrough of shale oil; (5) In order to promote the development of shale oil industry, it is suggested to further strengthen the research on enrichment mechanism and distribution prediction of different types of shale oil, shale oil flow mechanism and development technology policy, long horizontal well fast drilling and completion and high-efficiency fracturing technology, and supporting equipment and material research.

[0040] In the paper "Several issues worth paying attention to in current continental shale oil exploration and development" published in Oil and Gas Exploration and Development, Vol. 48, No. 6, 2021, based on the current situation of shale oil exploration and development at home and abroad, and through field observation, analysis and testing of typical shale oil areas, the authors compared the differences in geological and engineering characteristics of shale oil between Chinese and American continental and marine basins, and proposed and analyzed several issues worth paying attention to in the exploration and development of continental shale oil in typical basins in China, including the concepts of tight oil and shale oil, the differences between continental and marine shale oil, low and high maturity, vertical and horizontal permeability, source and cap rock, geology and engineering, selection criteria, and basic and applied research. By comparing the geological characteristics of the large-area developed organic-rich shale in the Triassic Yanchang Formation of the Ordos Basin, the Permian Lucushuo Formation of the Jimusa Sag in the Junggar Basin, the Permian Fengcheng Formation in the Mahu Sag, the Cretaceous Qingshankou and Nenjiang formations in the Songliao Basin, and the Paleogene Kongdian and Shahejie formations in the Bohai Bay Basin, the authors believe that future exploration and development of continental shale oil should focus on three key scientific issues: the physical, chemical and biological processes of fine-grained sedimentation in continental basins and the formation mechanism of organic-rich shale, the dynamic evolution of diagenesis-hydrocarbon generation-reservoir formation and hydrocarbon accumulation mechanism, and the fracturing mechanism of shale in different diagenetic stages and the multi-phase and multi-scale flow mechanism of shale oil in different maturity stages. The authors also believe that it is necessary to clarify the main controlling factors of reservoir properties, oiliness and compressibility of different shale formations and the mobility of shale oil in different maturity stages, establish a shale oil enrichment model, develop an evaluation method for shale oil exploration, and explore effective development methods for shale oil, so as to provide a theoretical basis and technical support for the large-scale economic exploration and development of continental shale oil in China.

[0041] The Chinese patent CN 113050191 A discloses a shale oil TOC prediction method and device based on double parameters, which comprises: obtaining resistivity data, acoustic time difference data and core data of a plurality of shale layers according to logging data of the plurality of shale layers; constructing a TOC function of shale oil according to the resistivity data and the acoustic time difference data, the TOC function being used to represent the relationship between TOC data and the resistivity data and the acoustic time difference data; fitting the TOC function by using the core data to determine fitting coefficients of the TOC function; determining TOC data of seismic attribute information mapping of the plurality of shale layers based on the TOC function; and performing weighted stacking on the TOC data of the seismic attribute information mapping of the plurality of shale layers to predict a TOC data value of shale oil in a target shale layer. The present application can predict shale oil TOC with high prediction accuracy.

[0042] A paper titled "Shale oil resource evaluation method, parameter standard and typical evaluation example" published by Guo Qiulin et al. in China Petroleum Exploration, Vol. 27, No. 6, 2022, states that in view of the strong heterogeneity of Chinese continental shale, it is pointed out that the small face volume method is suitable for interlayer shale oil resource evaluation, and the small face volume method is suitable for pure shale oil resource evaluation. The S1 and TOC fitting relationship curve and the light hydrocarbon recovery coefficient and R o relationship curve are established to obtain the original S1. Four key parameters (S1, TOC, c and shale thickness) for pure shale oil resource evaluation and three key parameters (interlayer cumulative thickness, porosity and oil saturation) for interlayer shale oil resource evaluation are determined, and the parameter lower limit standard is accordingly formulated. Under the unified evaluation method and standard, the Cretaceous Qingshankou Formation shale oil in the northern Songliao Basin, the Triassic Yanchang Formation shale oil in the Ordos Basin and the Permian Lucushuo Formation shale oil in the Junggar Basin are selected as typical evaluation examples. The evaluation results reveal that the pure shale oil resource of the first member of Qingshankou Formation (Qing I) is 52.23×10 8 t, wherein the light oil (R o >1.2%) is 11.18×10 8 t; the shale oil resource of the Chang 73 submember of Yanchang Formation is 66.80×10 8 t, wherein the interlayer shale oil resource is 27.73×10 8 t, and the pure shale oil resource is 39.07×10 8 t; the shale oil resource of Lucushuo Formation is 15.62×10 8 t, wherein the interlayer shale oil resource is 11.99×10 8 t, and the pure shale oil resource is 3.63×10 8 t.

[0043] As can be seen from the above prior art, in the prior art, the TOC content of organic carbon is usually evaluated in the target area in the drilling process using a water-based mud system, without considering the influence of mud on the test results of TOC content, and in the drilling process of some unconventional shale oil and gas horizontal wells, in order to maintain the stability of the well wall, the TOC content is evaluated in the target area using an oil-based mud system, which affects the test results of TOC content, and the accuracy of the evaluation is low.

[0044] As Figure 1 shown, to solve the technical problems in the prior art, in the embodiments of the present application, an evaluation method for shale oil geochemical indicators under an oil-based mud system is provided, which comprises the following steps:

[0045] determining parameters of geochemical indexes under an oil-based mud system, and establishing a mathematical model of the geochemical indexes under the oil-based mud system;

[0046] measuring the organic carbon TOC content under the water-based mud system and the organic carbon TOC content under the oil-based mud system at the same depth of the same reference well;

[0047] establishing a linear regression equation of the geochemical indexes under the oil-based mud system according to the mathematical model of the geochemical indexes and the measurement results;

[0048] determining the organic carbon TOC content under the water-based mud system of the to-be-predicted area based on the linear regression equation;

[0049] evaluating the geochemical indexes of the to-be-predicted area according to the organic carbon TOC content under the water-based mud system of the to-be-predicted area.

[0050] In some embodiments of the present embodiment, the mathematical model is Y=a+bX, where Y is the organic carbon TOC content under the water-based mud system, X is the organic carbon TOC content under the oil-based mud system, a is a regression constant, and b is a regression coefficient.

[0051] As shown in Table 1, in some embodiments of the present embodiment, the measuring the organic carbon TOC content under the water-based mud system and the organic carbon TOC content under the oil-based mud system at the same depth of the same reference well comprises:

[0052] For the same reference well, the organic carbon TOC content under the water-based mud system and the organic carbon TOC content under the oil-based mud system at n same depths of the reference well are measured to obtain an array Y of measured values of the organic carbon TOC content under the water-based mud system a =[Y1, Y2, …, Y n ], and an array X of measured values of the organic carbon TOC content under the oil-based mud system a =[X1, X2, …, X n ], where Y n is the organic carbon TOC content under the nth water-based mud system, X n is the organic carbon TOC content under the nth oil-based mud system, and n≥31.

[0053] The water-based mud has little effect on the geochemical parameter of the organic carbon TOC content, which can be ignored, so the samples taken at the same sampling depth are equally divided into two parts, which are soaked in the oil-based mud and the water-based mud respectively for 15 days, and then the organic carbon TOC content under different mud systems is measured respectively. 15 days is the value according to the conventional drilling period in the area.

[0054]

[0055]

[0056] Table 1

[0057] In some embodiments of the present embodiment, the linear regression equation of the geochemical index under the oil-based mud system is established according to the mathematical model of the geochemical index and the measured results, and includes:

[0058] The regression constant and the regression coefficient are calculated according to formula (1),

[0059]

[0060] In formula (1), Y i is the organic carbon TOC content under the i th (i = 1, 2, 3, … n) water-based mud system, is the average value of the measured values of the organic carbon TOC content under all water-based mud systems, X ii is the organic carbon TOC content under the i th oil-based mud system, is the average value of the measured values of the organic carbon TOC content under all oil-based mud systems, a is the regression constant, and b is the regression coefficient.

[0061] The regression constant and the regression coefficient are substituted into the mathematical model of the geochemical index under the oil-based mud system to obtain the linear regression equation of the geochemical index under the oil-based mud system.

[0062] In some embodiments of the present embodiment, the linear regression equation is Y = -2.8599 + 1.0676X, wherein Y is the organic carbon TOC content under the water-based mud system, and X is the organic carbon TOC content under the oil-based mud system.

[0063] In some embodiments of the present embodiment, the shale oil geochemical index evaluation method further includes verifying the linear regression equation.

[0064] If the linear regression equation is verified to be reasonable, the organic carbon TOC content under the water-based mud system of the to-be-predicted area is determined based on the linear regression equation, and the geochemical index of the to-be-predicted area is evaluated according to the organic carbon TOC content under the water-based mud system of the to-be-predicted area.

[0065] As shown in Table 2, in some embodiments of the present embodiment, the verification of the linear regression equation includes verifying the linear regression equation according to formula (2) using the correlation coefficient,

[0066]

[0067] In formula (2), R is the correlation coefficient, Y i is the organic carbon TOC content under the i th water-based mud system, Y′ i is X ithe fitted value corresponding to X is the average of the measured values of the organic carbon TOC content of all the water-based mud systems.

[0068] Y' i The definition is recorded in the book "Modern Consulting Methods and Practices" published by China Planning Press in April 2003, the first edition, page 35.

[0069] When the degrees of freedom n-2 (n is the sample number 31) and the significant level a=0.05, R=0.6861 is greater than the critical value 0.361, which indicates that the linear relationship between X and Y is established.

[0070] The critical value table of the correlation coefficient is recorded in the book "Modern Consulting Methods and Practices" published by China Planning Press in April 2003, the first edition, page 257.

[0071]

[0072]

[0073] Table 2

[0074] As shown in Table 3, in some embodiments of the present embodiment, the verification linear regression equation includes: verifying the linear regression equation according to formula (3) with the significance of the regression coefficient,

[0075]

[0076] In formula (3), t b is the significance of the regression coefficient, b is the regression coefficient, X i is the organic carbon TOC content of the i-th water-based mud system, is the average of the measured values of the organic carbon TOC content of all the water-based mud systems, Y i is the organic carbon TOC content of the i-th water-based mud system, Y' i is the fitted value corresponding to X i .

[0077] The significance of the regression coefficient is used to determine whether the linear assumption between variables X and Y is reasonable; the calculation result t b =5.3271 is greater than t(a / 2, n-2)=2.0484, the parameter t test is passed, and the linear assumption between variables X and Y is reasonable.

[0078] The t(a / 2, n-2) distribution table is recorded in the book "Modern Consulting Methods and Practices" published by China Planning Press in April 2003, the first edition, page 258.

[0079]

[0080]

[0081] Table 3

[0082] As shown in Table 4, in some embodiments of the present embodiment, the verification of the linear regression equation includes verifying the linear regression equation according to formula (4) using the significance of the regression equation,

[0083]

[0084] In formula (4), F is the significance of the regression equation, Y' is the fitted value of the organic carbon TOC content of the water-based mud system according to the linear regression equation, i corresponding to X, i Y is the average value of the measured values of the organic carbon TOC content of all water-based mud systems, i Yi is the organic carbon TOC content of the i-th water-based mud system.

[0085] The calculation result F = 28.8930 is greater than the F value when the significance level a = 0.05, the degrees of freedom n1 = 1, n2 = n-2, which is 4.20, and the F test passes. The regression equation well reflects the linear relationship between the variables X and Y.

[0086] The F distribution table for the significance F test of the regression equation is recorded in the book “Modern Consulting Methods and Practices” published by China Planning Press in April 2003, first edition, pages 259-260.

[0087]

[0088]

[0089] In some embodiments of the present embodiment, the determination of the organic carbon TOC content of the water-based mud system in the to-be-predicted area based on the linear regression equation includes:

[0090] Measuring the organic carbon TOC content of the oil-based mud system in the to-be-predicted area;

[0091] Calculating the organic carbon TOC content of the water-based mud system in the to-be-predicted area according to the organic carbon TOC content of the oil-based mud system in the to-be-predicted area and the linear regression equation.

[0092] Taking well H2CHF (to-be-predicted area) as an example, the application of the mathematical model of the present application is described in detail.

[0093] ​H2CHF well, the organic carbon TOC content under the oil-based mud system is 5.134%, obtained according to the mathematical model Y=-2.8599+1.0676X, the organic carbon TOC content under the water-based mud system is X=2.621%, which is consistent with the range of TOC measured in the drilling under the water-based mud system in the block, the TOC range in the area is 0.32%-3.96%, the data is reliable, the accuracy is improved by 81.24 percentage points, reaches 99.24%, and the work efficiency is improved by 72.5%.

[0094] Taking the HY3HF well (the area to be predicted) as an example, the application of the mathematical model of the present application is described in detail.

[0095] The HY3HF well, the organic carbon TOC content under the oil-based mud system is 4.835%, obtained according to the mathematical model Y=-2.8599+1.0676X, the organic carbon TOC content under the water-based mud system is X=2.302%, which is consistent with the range of TOC measured in the drilling under the water-based mud system in the block, the data is reliable, the TOC range in the area is 0.32%-3.96%, the data is reliable, the accuracy is improved by 80.54 percentage points, reaches 98.8%, and the work efficiency is improved by 80.6%.

[0096] In summary, according to the mathematical prediction of the measured 31 actual water-based mud TOC content and oil-based mud TOC content, the correlation coefficient R test, the significance t test of the regression coefficient, and the significance F test of the regression equation all reflect that the linear relationship between the variables X and Y is reasonable. Therefore, Y=-2.8599+1.0676X can be used to determine the geochemical parameters under the oil-based mud system. In the drilling process, the evaluation method in the embodiment not only ensures the benefits brought by the oil-based mud for the well wall, but also avoids the pollution of the oil-based mud to the rock or cuttings, so as to objectively evaluate the organic carbon content, restore the actual value of the organic carbon TOC content under the water-based mud system, and make up for the deficiencies caused by the oil-based mud drilling fluid. The application is applied to 15 wells in the block, the accuracy rate is 99%, the accuracy is improved by 80.1 percentage points, reaches 98%, and the work efficiency is improved by more than 70%.

[0097] The above embodiments are only an explanation of the present application, which is not a limitation of the present application, and those skilled in the art can make modifications to the embodiments of the present application without creative contribution after reading the present specification, but as long as the scope of the claims of the present application is within the scope of the present application.

Claims

1. A method for evaluating shale oil geochemical indicators, characterized in that, The method comprises the following steps: establishing a mathematical model of geochemical indexes under an oil-based mud system; measuring the organic carbon TOC content under a water-based mud system and the organic carbon TOC content under the oil-based mud system at the same depth of a same reference well; establishing a linear regression equation of the geochemical indexes under the oil-based mud system according to the mathematical model of the geochemical indexes and the measurement results; determining the organic carbon TOC content under the water-based mud system of a to-be-predicted area based on the linear regression equation; evaluating the geochemical indexes of the to-be-predicted area according to the organic carbon TOC content under the water-based mud system of the to-be-predicted area.

2. The method for evaluating shale oil geochemical indicators according to claim 1, characterized in that, The mathematical model is Y=a+bX, wherein Y is the organic carbon TOC content under the water-based mud system, X is the organic carbon TOC content under the oil-based mud system, a is a regression constant, and b is a regression coefficient.

3. The method of claim 2, wherein, The measurement of the organic carbon TOC content under the water-based mud system and the organic carbon TOC content under the oil-based mud system at the same depth of the same reference well comprises: The organic carbon TOC content under n same depth water-based mud systems and the organic carbon TOC content under oil-based mud systems are measured, to obtain an array Y of measured values of the organic carbon TOC content under water-based mud systems a =[Y1,Y2,…,Y n ] and an array X of measured values of the organic carbon TOC content under oil-based mud systems a =[X1,X2,…,X n ], wherein Y n is the organic carbon TOC content under the nth water-based mud system, X n is the organic carbon TOC content under the nth oil-based mud system, and n≥31.

4. The method of claim 3, wherein, The establishment of the linear regression equation of the geochemical indexes under the oil-based mud system according to the mathematical model of the geochemical indexes and the measurement results comprises: the regression constant and the regression coefficient are calculated according to formula (1), In formula (1), Y i is the measured value of the organic carbon TOC content under the i-th water-based mud system, is the average value of the measured values of the organic carbon TOC content under all water-based mud systems, X i is the measured value of the organic carbon TOC content under the i-th oil-based mud system, is the average value of the measured values of the organic carbon TOC content under all oil-based mud systems, a is a regression constant, and b is a regression coefficient; the regression constant and the regression coefficient are substituted into the mathematical model of the geochemical indexes under the oil-based mud system to obtain the linear regression equation of the geochemical indexes under the oil-based mud system.

5. The method of claim 4, wherein, The linear regression equation is Y=-2.8599+1.0676X, wherein Y is the organic carbon TOC content under the water-based mud system, and X is the organic carbon TOC content under the oil-based mud system.

6. The method of claim 1, wherein, The evaluation method of the shale oil geochemical indexes further comprises verifying the linear regression equation. If the linear regression equation is verified to be reasonable, the organic carbon TOC content under the water-based mud system of the to-be-predicted area is determined based on the linear regression equation, and the geochemical indexes of the to-be-predicted area are evaluated according to the organic carbon TOC content under the water-based mud system of the to-be-predicted area.

7. The method of claim 6, wherein, The verification of the linear regression equation comprises verifying the linear regression equation with the correlation coefficient according to formula (2), In formula (2), R is a correlation coefficient, Y i is the measured value of the organic carbon TOC content under the i-th water-based mud system, Y′ i is the average value of the measured values of the organic carbon TOC content under all water-based mud systems. i corresponding to the fitting value obtained according to the linear regression equation, is the average value of the measured values of the organic carbon TOC content under all water-based mud systems.

8. The method of claim 6, wherein, The verification of the linear regression equation comprises verifying the linear regression equation with the significance of the regression coefficient according to formula (3), In Equation (3), t b is the significance of the regression coefficient, b is the regression coefficient, X i is the measured value of the organic carbon TOC content under the i-th oil-based mud system, Y is the average value of the measured values of the organic carbon TOC content under all oil-based mud systems, Y i is the measured value of the organic carbon TOC content under the i-th water-based mud system, Y′ i is the measured value of the organic carbon TOC content under the i-th oil-based mud system, Y i is the fitted value according to the linear regression equation corresponding to X 9. The method of claim 6, wherein, The verification of the linear regression equation comprises verifying the linear regression equation with the significance of the regression equation according to formula (4), In formula (4), F is the significance of the regression equation, Y' i is the fitted value according to the linear regression equation, i is the average of the measured values of the organic carbon TOC content under all water-based mud systems, Y i is the organic carbon TOC content under the i-th water-based mud system.​ 10. The method of claim 1, wherein, The determination of the organic carbon TOC content under the water-based mud system of the to-be-predicted area based on the linear regression equation comprises: measuring the organic carbon TOC content under the oil-based mud system of the to-be-predicted area; calculating the organic carbon TOC content under the water-based mud system of the to-be-predicted area according to the organic carbon TOC content under the oil-based mud system of the to-be-predicted area and the linear regression equation.

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