Method for calculating total organic carbon content of continental deposition thin shale gas reservoir

Abstract

The invention relates to the technical field of oil and gas field exploration and development, in particular to a method for calculating the total organic carbon content of a continental deposition thin-layer shale gas reservoir, which comprises the following steps of: respectively calculating a resistivity baseline and an interval transit time baseline according to an interval transit time curve and a resistivity curve; and according to the overlapping degree of the interval transit time curve and the interval transit time base line and the overlapping degree of the resistivity curve and the resistivity base line, establishing a calculation model of the total organic carbon content TOC. By means of the total organic carbon content calculation method, the problem that the TOC parameter evaluation precision of an existing continental deposition thin layer shale gas unconventional reservoir is not ideal can be effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas field exploration and development, and particularly relates to a method for calculating the total organic carbon content of thin continental sedimentary shale gas reservoirs. Background Art

[0002] In the evaluation research of unconventional shale gas exploration and development, at present, the evaluation idea of the total organic carbon (TOC) of the Longmaxi marine sedimentary shale gas is mainly based on the method proposed by Passey in 1990. The acoustic travel time curve and the resistivity curve are superimposed. The acoustic travel time curve uses a linear scale, and the resistivity curve uses a common logarithm scale. When the two curves overlap within a meaningful depth range or the curves are "consistent", the overlapping section is the baseline, which represents the fine-grained non-source rock. Then, the reading (△LgR) of the distance (amplitude difference) between the two curves on the logarithmic resistivity coordinate is determined. The relative scale is 100 μs / ft (-328 μs / m) for every two logarithmic resistivity cycles, and the ratio relative to 1 resistivity unit is 50 μs / ft or (164 μs / m). The two curves are superimposed together, and the fine-grained non-source rock is used as the baseline. The condition for the existence of the baseline is that the two curves are "traced" consistently or overlap within a meaningful depth range. The amplitude difference between the two curves is defined as △lgR. The formula for calculating △lgR is as follows:

[0003] △lgR = lg(RT / RT b ) + K×(AC - AC b )

[0004] In the formula, △lgR is the distance between the two curves, RT is the resistivity value of the calculation point, Ω·m; AC is the acoustic travel time value of the calculation point, μs / ft; RT b is the resistivity value at the baseline, Ω·m; AC b is the acoustic travel time value at the baseline, μs / ft.

[0005] The total organic carbon content can be calculated using the empirical equation of △lgR and the total organic carbon content. The formula is:

[0006]

[0007] In the formula, R o is the vitrinite reflectance of the gas-bearing shale, representing the maturity of the shale.

[0008] This method is called the △LgR method for obtaining TOC, as shown in the attached Figure 3 of the specification. It can be seen that with R oThe total organic carbon content of the source rock can be calculated. Since this method is mainly used for calculating the total organic carbon content in shale gas evaluation, substituting Ro reflects some regional attributes. The tight sandstone itself also has a certain TOC value. This method does not consider the rock density factor that affects the physical properties and organic carbon content of shale. Generally, density is inversely proportional to the organic carbon content. At the same time, it does not consider factors such as the natural gamma ray GR and well diameter CAL that affect lithology identification. Therefore, scholars such as Zhu Guangyou introduced an influence factor coefficient and modified the formula as follows:

[0009] TOC = (a * LgR + b * △t + c) / d

[0010] In the formula, d is the density log value; a, b, and c are dimensionless factor coefficients, which can be obtained by analyzing systematically collected samples in the study area and fitting them using the least squares method.

[0011] The updated model still needs to determine the lithology baseline through manual operation, which may bring relatively large errors and is also rather cumbersome and inconvenient to operate. Moreover, the existing baselines are all fixed values, resulting in unsatisfactory evaluation accuracy of TOC parameters for current continental shale gas unconventional reservoirs. Summary of the Invention

[0012] To solve the above technical problems, the present invention proposes a method for calculating the total organic carbon content of a continental sedimentary thin-layer shale gas reservoir, which can effectively solve the problem of unsatisfactory evaluation accuracy of TOC parameters for current continental shale gas unconventional reservoirs.

[0013] The present invention is realized by adopting the following technical solutions:

[0014] A method for calculating the total organic carbon content of a continental sedimentary thin-layer shale gas reservoir includes the following steps:

[0015] Step S1. Calculate the resistivity baseline and the acoustic time difference baseline respectively according to the acoustic time difference curve and the resistivity curve;

[0016] The acoustic time difference baseline is:

[0017] AC b = ACXS * [a * (lg(RT)) 4 + b * (lg(RT)) 3 + c * (lg(RT)) 2 + d * lg(RT) + e](1)

[0018] The resistivity baseline is:

[0019] RT b = RTXS * [f * (AC) 4 + g * (AC) 3 + h * (AC)2 +i*AC + j](2)

[0020] Wherein, AC b is the acoustic time difference value corresponding to the acoustic time difference baseline, ACXS is the acoustic time difference correction index, lg(RT) is the common logarithm value of the measured resistivity curve, and RT b is the resistivity value corresponding to the resistivity baseline, AC is the measured acoustic time difference value, RTXS is the resistivity correction index, and a, b, c, d, e, f, g, h, i, and j are respectively the least squares fitting coefficients;

[0021] Step S2. Establish a calculation model for the total organic carbon content TOC according to the overlapping degree between the acoustic time difference curve and the acoustic time difference baseline, and the overlapping degree between the resistivity curve and the resistivity baseline:

[0022] TOC = (lg(RT / RT b ) + k*(AC - AC b )) * 10 (2.297-0.168*LOM) (3)

[0023] Wherein, TOC is the total organic carbon content, RT is the measured deep lateral resistivity value, LOM is the maturity index, and k is the least squares fitting coefficient.

[0024] In the said step S1, the calculation method of the resistivity baseline includes the following steps:

[0025] Step S 111 . Establish a resistivity baseline according to the fourth - order function of the acoustic time difference curve:

[0026] RT b = RTXS * [f*(AC) 4 + g*(AC) 3 + h*(AC) 2 + i*AC + j]

[0027] Wherein, RT b is the resistivity value corresponding to the resistivity baseline, AC is the measured acoustic time difference value, RTXS is the resistivity correction index, and f, g, h, i, and j are respectively the least squares fitting coefficients;

[0028] Step S 112 . Calculate the resistivity correction index RTXS and each least squares fitting coefficient to obtain the final resistivity baseline; the calculation method of the resistivity correction index RTXS is: in the tight sandstone formation section, adjust the resistivity correction index RTXS to make the resistivity curve basically coincide with the resistivity baseline, and then obtain the resistivity correction index RTXS.

[0029] The value of the resistivity correction index RTXS ranges from 0.35 to 0.55.

[0030] In the step S1, the calculation method of the acoustic time difference baseline includes the following steps:

[0031] Step S 121 . Establish the acoustic time difference baseline according to the fourth power function of the logarithm of the resistivity curve:

[0032] AC b = ACXS * [a * (lg(RT)) 4 + b * (lg(RT)) 3 + c * (lg(RT)) 2 + d * lg(RT) + e]

[0033] In the formula, AC b is the acoustic time difference value corresponding to the acoustic time difference baseline, ACXS is the acoustic time difference correction index, lg(RT) is the common logarithm value of the measured resistivity curve, and a, b, c, d, and e are the least squares fitting coefficients respectively;

[0034] Step S 122 . Calculate the acoustic time difference correction index ACXS and each least squares fitting coefficient to obtain the final acoustic time difference baseline; the calculation method of the acoustic time difference correction index ACXS is: in the tight sandstone formation section, adjust the acoustic time difference correction index ACXS so that the acoustic time difference baseline basically coincides with the acoustic time difference curve, and then obtain the acoustic time difference correction index ACXS.

[0035] The value of the acoustic time difference correction index ACXS ranges from 0.9 to 0.99.

[0036] The least squares fitting coefficients a, b, c, d, e, f, g, h, i, j, and k are determined by least squares fitting according to the actual experimental data of the region.

[0037] The specific determination method of the least squares fitting coefficients a, b, c, d, e, f, g, h, i, j, and k is: obtain the measured data of the core TOC content, the measured acoustic logging data, and the measured resistivity logging data of the calibration well, and substitute them into the above formulas (1), (2), and (3). By using the optimization algorithm, adjust the parameters of the resistivity correction index RTXS and the acoustic time difference correction index ACXS to obtain the model with the minimum error, and thus determine the least squares fitting coefficients a, b, c, d, e, f, g, h, i, j, and k.

[0038] It also includes verifying the determined least squares fitting coefficients to judge whether the error requirements are met.

[0039] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0040] 1. The present invention proposes a dedicated calculation method for the total organic carbon content for unconventional reservoirs of continental thin-layer shale gas. The calculation method is simple and the accuracy of the calculation results is relatively high. Specifically: according to the overlap degree between the acoustic travel time baseline and the acoustic travel time curve, and the overlap degree between the resistivity baseline and the resistivity curve, the present invention establishes a calculation model for the total organic carbon content TOC. And in the present application, the acoustic travel time baseline and the resistivity baseline are not fixed values compared with the prior art, but variable values obtained through calculation and processing, making the calculation results of the present application more accurate.

[0041] 2. Due to differences in logging series, logging instruments, mud properties, wellbore conditions, and well diameter sizes for each well, the resistivity baseline and the acoustic travel time baseline are different, and they are not fixed values. Through the calculation method in the present application, the changes in the resistivity value corresponding to the resistivity baseline and the acoustic travel time value corresponding to the acoustic travel time baseline in the tight sandstone formation section of each well can be captured, and the calculation results are more accurate.

[0042] 3. Since in the same block and the same structure, each least squares fitting coefficient is a fixed value and does not change, the least squares fitting coefficients a, b, c, d, e, f, g, h, i, j, and k in the present application can be determined by fitting according to actual experimental data in the region. The calculation method is simple and accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The present invention will be further described in detail below in conjunction with the specification drawings and specific embodiments, where:

[0044] Figure 1 is a schematic diagram of the XX well Xuwu section overlapping method for calculating TOC in the present invention;

[0045] Figure 2 is a schematic diagram of the relationship between vitrinite reflectance and LOM;

[0046] Figure 3 is a schematic diagram of the acoustic travel time and resistivity overlapping method in the prior art. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] Example 1

[0048] As a basic embodiment of the present invention, the present invention includes a calculation method for the total organic carbon content of unconventional continental thin-layer shale gas reservoirs, comprising the following steps:

[0049] Step S1. Calculate the resistivity baseline and the acoustic travel time baseline respectively according to the acoustic travel time curve and the resistivity curve.

[0050] The acoustic travel time baseline is:

[0051] AC b = ACXS * [a * (lg(RT)) 4 + b * (lg(RT)) 3 + c * (lg(RT)) 2 + d * lg(RT) + e](1)

[0052] The resistivity baseline is as follows:

[0053] RT b = RTXS * [f * (AC) 4 + g * (AC) 3 + h * (AC) 2 + i * AC + j] (2)

[0054] In the formula, AC b is the acoustic time difference value corresponding to the acoustic time difference baseline, ACXS is the acoustic time difference correction index, lg(RT) is the common logarithm value of the measured resistivity curve, RT b is the resistivity value corresponding to the resistivity baseline, AC is the measured acoustic time difference value, RTXS is the resistivity correction index, and a, b, c, d, e, f, g, h, i, and j are the least squares fitting coefficients respectively.

[0055] Step S2. Establish a calculation model for the total organic carbon content TOC based on the overlapping degree between the acoustic time difference curve and the acoustic time difference baseline, and the overlapping degree between the resistivity curve and the resistivity baseline:

[0056] TOC = (lg(RT / RT b ) + k * (AC - AC b )) * 10 (2.297-0.168*LOM) (3)

[0057] In the formula, TOC is the total organic carbon content, RT is the measured deep lateral resistivity value, LOM is the maturity index, and k is the least squares fitting coefficient.

[0058] Embodiment 2

[0059] As a preferred embodiment of the present invention, the present invention includes a method for calculating the total organic carbon content of an unconventional continental thin-layer shale gas reservoir, comprising the following steps:

[0060] Step S1. Calculate the resistivity baseline and the acoustic time difference baseline respectively according to the acoustic time difference curve and the resistivity curve.

[0061] The calculation method of the resistivity baseline includes the following steps:

[0062] Step S 111. Establish the resistivity baseline according to the fourth - power function of the acoustic travel - time curve:

[0063] RT b = RTXS * [f * (AC) 4 + g * (AC) 3 + h * (AC) 2 + i * AC + j]

[0064] In the formula, RT b is the resistivity value corresponding to the resistivity baseline, AC is the measured acoustic travel - time value, RTXS is the resistivity correction index, and f, g, h, i, and j are the least - squares fitting coefficients respectively.

[0065] Step S 112 . Calculate the resistivity correction index RTXS and the fitting coefficients to obtain the final resistivity baseline. The calculation method of the resistivity correction index RTXS is as follows: in the tight sandstone formation section, adjust the resistivity correction index RTXS to make the resistivity curve basically coincide with the resistivity baseline, and then obtain the resistivity correction index RTXS.

[0066] In step S1, the calculation method of the acoustic travel - time baseline includes the following steps:

[0067] Step S 121 . Establish the acoustic travel - time baseline according to the fourth - power function of the logarithm of the resistivity curve:

[0068] AC b = ACXS * [a * (lg(RT)) 4 + b * (lg(RT)) 3 + c * (lg(RT)) 2 + d * lg(RT)+ e]

[0069] In the formula, AC b is the acoustic travel - time value corresponding to the acoustic travel - time baseline, ACXS is the acoustic travel - time correction index, lg(RT) is the common logarithm value of the measured resistivity curve, and a, b, c, d, and e are the least - squares fitting coefficients respectively.

[0070] Step S 122 . Calculate the acoustic travel - time correction index ACXS and the least - squares fitting coefficients to obtain the final acoustic travel - time baseline. The calculation method of the acoustic travel - time correction index ACXS is as follows: in the tight sandstone formation section, adjust the acoustic travel - time correction index ACXS to make the acoustic travel - time baseline basically coincide with the acoustic travel - time curve, and then obtain the acoustic travel - time correction index ACXS.

[0071] Step S2. Establish a calculation model for the total organic carbon content TOC based on the overlapping degree between the acoustic time difference curve and the acoustic time difference baseline, and the overlapping degree between the resistivity curve and the resistivity baseline:

[0072] TOC = (lg(RT / RT b ) + k*(AC - AC b )) * 10 (2.297-0.168*LOM)

[0073] In the formula, TOC is the total organic carbon content, RT is the measured deep lateral resistivity value, LOM is the maturity index, and k is the least squares fitting coefficient.

[0074] Example 3

[0075] As another preferred embodiment of the present invention, the present invention includes a method for calculating the total organic carbon content of a continental sedimentary thin-layer shale gas reservoir, comprising the following steps:

[0076] Step S1. Calculate the resistivity baseline and the acoustic time difference baseline respectively according to the acoustic time difference curve and the resistivity curve.

[0077] The acoustic time difference baseline is:

[0078] AC b = ACXS * [a*(lg(RT)) 4 + b*(lg(RT)) 3 + c*(lg(RT)) 2 + d*lg(RT) + e] (1)

[0079] The resistivity baseline is:

[0080] RT b = RTXS * [f*(AC) 4 + g*(AC) 3 + h*(AC) 2 + i*AC + j] (2)

[0081] In the formula, RT b is the resistivity value corresponding to the resistivity baseline, AC is the measured acoustic time difference value, RTXS is the resistivity correction index, AC b is the acoustic time difference value corresponding to the acoustic time difference baseline, ACXS is the acoustic time difference correction index, lg(RT) is the common logarithm value of the measured resistivity curve, and a, b, c, d, e, f, g, h, i, and j are respectively the least squares fitting coefficients.

[0082] Step S2. Establish a calculation model for the total organic carbon content TOC based on the overlapping degree between the acoustic time difference curve and the acoustic time difference baseline, and the overlapping degree between the resistivity curve and the resistivity baseline:

[0083] TOC = (lg(RT / RT b ) + k*(AC - AC b )) * 10 (2.297-0.168*LOM) (3)

[0084] In the formula, TOC is the total organic carbon content, RT is the measured deep lateral resistivity value, LOM is the maturity index, and k is the least squares fitting coefficient.

[0085] The fitting coefficients a, b, c, d, e, f, g, h, i, j, and k are determined by least squares fitting according to the actual experimental data of the region. The specific determination method is as follows: Obtain the measured data of the core TOC content, the measured acoustic logging data, and the measured resistivity logging data of the calibration well, and substitute them into the above formulas (1), (2), and (3). By using the optimization algorithm, adjust the parameters of the resistivity correction index RTXS and the acoustic time difference correction index ACXS to obtain the model with the minimum error, and thus determine the least squares fitting coefficients a, b, c, d, e, f, g, h, i, j, and k.

[0086] Example 4

[0087] As the best implementation mode of the present invention, the present invention includes a method for calculating the total organic carbon content of a continental sedimentary thin-layer shale gas reservoir. The formation organic carbon content is the mass of organic carbon elements in a unit mass of rock, which can indicate the organic abundance in the source rock and is an important parameter for evaluating the hydrocarbon generation potential of the source rock. Based on the data of the Tianfu core block in the Sichuan Basin, this example calculates the total organic carbon content TOC for the unconventional continental sedimentary thin-layer shale gas in the Xuwu section of Well XX, which specifically includes the following steps:

[0088] Step S1. Due to differences in logging series, logging instruments, mud properties, wellbore conditions, and well diameter sizes for each well, the resistivity baseline and the acoustic time difference baseline are not the same, and neither is a fixed value. The resistivity values corresponding to the resistivity baseline and the acoustic time difference values corresponding to the acoustic time difference baseline will change in the tight sandstone formation section of each well. Therefore, in this example, the resistivity baseline and the acoustic time difference baseline are calculated respectively according to the acoustic time difference curve and the resistivity curve.

[0089] The calculation method of the resistivity baseline includes the following steps:

[0090] Step S 111 . Establish the resistivity baseline according to the fourth-power function of the acoustic time difference curve:

[0091] RT b = RTXS * [f*(AC) 4 + g*(AC) 3 + h*(AC) 2+i*AC + j] (2)

[0092] In the formula, RT b is the resistivity value corresponding to the resistivity baseline, AC is the measured acoustic time difference, RTXS is the resistivity correction index, and f, g, h, i, and j are the least squares fitting coefficients respectively.

[0093] Step S 112 . Calculate the resistivity correction index RTXS and each least squares fitting coefficient to obtain the final resistivity baseline.

[0094] The resistivity correction index RTXS varies with the borehole conditions of different wells, different logging series, and different logging instruments. Taking the Tianfu core block as an example, the value of the resistivity correction index RTXS ranges from 0.35 to 0.55. The specific calculation method of the resistivity correction index RTXS is as follows: In the tight sandstone formation section, adjust the resistivity correction index RTXS between 0.35 and 0.55 to make the resistivity curve basically coincide with the resistivity baseline and the TOC content is basically zero, so as to obtain the resistivity correction index RTXS.

[0095] The least squares fitting coefficients f, g, h, i, and j are determined by least squares fitting according to the actual experimental data of the region. In different blocks and different structures, the least squares fitting coefficients are different. However, in the same block and the same structure, each least squares fitting coefficient is a fixed value and will not change.

[0096] The calculation method of the acoustic time difference baseline includes the following steps:

[0097] Step S 121 . Establish the acoustic time difference baseline according to the fourth power function of the logarithm of the resistivity curve:

[0098] AC b = ACXS * [a * (lg(RT)) 4 + b * (lg(RT)) 3 + c * (lg(RT)) 2 + d * lg(RT) + e](1)

[0099] In the formula, AC b is the acoustic time difference value corresponding to the acoustic time difference baseline, ACXS is the acoustic time difference correction index, lg(RT) is the common logarithm value of the measured resistivity curve, and a, b, c, d, and e are the least squares fitting coefficients respectively.

[0100] Step S 122 . Calculate the acoustic time difference correction index ACXS and the least squares fitting coefficient to obtain the final acoustic time difference baseline.

[0101] The acoustic time difference correction index ACXS varies with the borehole conditions, logging series, and logging instruments of different wells. Taking the Tianfu core block as an example, the value of the acoustic time difference correction index RTXS ranges from 0.9 to 0.99. The calculation method of the acoustic time difference correction index ACXS is as follows: in the tight sandstone formation section, adjust the acoustic time difference correction index ACXS between 0.9 and 0.99 to make the acoustic time difference baseline basically coincide with the acoustic time difference curve, and the TOC content is basically 0, so as to obtain the acoustic time difference correction index ACXS.

[0102] The least squares fitting coefficients a, b, c, d, and e are determined by least squares fitting based on the actual experimental data of the region. For different blocks and different structures, the least squares fitting coefficients are different. However, in the same block and the same structure, each least squares fitting coefficient is a fixed value and will not change.

[0103] After the acoustic time difference correction index ACXS, the resistivity correction index RTXS, and each least squares fitting coefficient are determined, they can be verified through another cored well. After meeting the error requirements, they can be promoted in this region.

[0104] Step S2. After passing the verification, in the thin shale section of the fifth member of the Xujiahe Formation in the Tianfu core block of continental sedimentation, compare and overlap the acoustic time difference curve with the acoustic time difference baseline, and compare and overlap the resistivity curve with the resistivity baseline. The two form an envelope area respectively. The larger the envelope area, the greater the difference between the two and the larger the calculated TOC.

[0105] △lgR = lg(RT / RT b ) + k×(AC - AC b )

[0106] Among them, k is the least squares fitting coefficient. For different blocks and different structures, the k value is different.

[0107] TOC is linearly correlated with △lgR and is a function of maturity. LOM is a parameter related to the maturity of the fifth member of the Xujiahe Formation shale in the Tianfu core block. The higher the maturity, the larger the LOM, and:

[0108] TOC = △lgR * 10 (2.297-0.1688×LOM)

[0109] Therefore, the calculation model for establishing the total organic carbon content TOC is:

[0110] TOC = (lg(RT / RT b ) + k * (AC - AC b )) * 10 (2.297-0.168*LOM) (3)

[0111] Wherein, TOC is the total organic carbon content, RT is the measured deep lateral resistivity value, and AC is the measured acoustic time difference value. LOM is the maturity index, which varies between 5 and 18. The higher the maturity, the higher the LOM value. As shown in the attached Figure 2 description, a large number of studies have been conducted on this relationship abroad, and this embodiment will not elaborate further. The maturity of the Xujiahe Formation, Member 5 in the Tianfu Core Block is high, generally above 2.5. Therefore, when using the above formula, the value of LOM is greater than 12.

[0112] Among them, the specific determination method of the least squares fitting coefficients a, b, c, d, e, f, g, h, i, j, and k is as follows: Obtain the measured core TOC content data, measured acoustic logging data, and measured resistivity logging data of the calibration well, and substitute them into the above formulas (1), (2), and (3). By using the optimization algorithm, adjust the parameters of the resistivity correction index RTXS and the acoustic time difference correction index ACXS to obtain the model with the minimum error, and thus determine the least squares fitting coefficients a, b, c, d, e, f, g, h, i, j, and k.

[0113] Referring to the attached Figure 1 description, by the above method, when calculating the total organic carbon content using this calculation model in Well Yongqian 7 (in Well XX), Member 5 of the Xujiahe Formation, RTXS = 0.55, ACXS = 0.95, and LOM = 12. The comparison chart of the calculated total organic carbon TOC result with the core is in good agreement.

[0114] In summary, after those of ordinary skill in the art read the documents of the present invention, all other corresponding transformation schemes that can be made without creative mental labor according to the technical solutions and technical concepts of the present invention fall within the scope protected by the present invention.

Claims

1. A calculation method for the total organic carbon content of a continental sediment thin-layer shale gas reservoir, characterized in that: It includes the following steps: Step S1. Calculate the resistivity baseline and the acoustic travel time baseline respectively according to the acoustic travel time curve and the resistivity curve; The acoustic travel time baseline is: AC b = ACXS * [a * (lg(RT)) 4 + b * (lg(RT)) 3 + c * (lg(RT)) 2 + d * lg(RT) + e] (1) The resistivity baseline is: RT b = RTXS * [f * (AC) 4 + g * (AC) 3 + h * (AC) 2 + i * AC + j] (2) Wherein, AC b is the acoustic time difference value corresponding to the acoustic time difference baseline, ACXS is the acoustic time difference correction index, lg(RT) is the common logarithm value of the measured resistivity curve, RT b is the resistivity value corresponding to the resistivity baseline, AC is the measured acoustic time difference value, RTXS is the resistivity correction index, and a, b, c, d, e, f, g, h, i, and j are respectively the least squares fitting coefficients; Step S2. Establish a calculation model for the total organic carbon content TOC according to the overlapping degree between the acoustic travel time curve and the acoustic travel time baseline, and the overlapping degree between the resistivity curve and the resistivity baseline: TOC=(lg(RT / RT b )+k*(AC-AC b ))*10 (2.297-0.168*LOM) (3) In the formula, TOC is the total organic carbon content, RT is the measured deep lateral resistivity value, LOM is the maturity index, and k is the least squares fitting coefficient.

2. The calculation method of the total organic carbon content of a continental sedimentary thin-layer shale gas reservoir according to claim 1, characterized in that: In the said Step S1, the calculation method of the resistivity baseline includes the following steps: Step S 111 . Establish a resistivity baseline according to the quartic function of the acoustic travel-time curve: RT b = RTXS * [f * (AC) 4 + g * (AC) 3 + h * (AC) 2 + i * AC + j] where RT b is the resistivity value corresponding to the resistivity baseline, AC is the measured acoustic time difference, RTXS is the resistivity correction index, and f, g, h, i, and j are the least squares fitting coefficients respectively; Step S 112 . Calculate the resistivity correction index RTXS and each least-squares fitting coefficient to obtain the final resistivity baseline; the calculation method of the resistivity correction index RTXS is as follows: in the tight sandstone formation section, adjust the resistivity correction index RTXS to make the resistivity curve basically coincide with the resistivity baseline, thereby obtaining the resistivity correction index RTXS.

3. The calculation method for the total organic carbon content of a continental sedimentary thin-layer shale gas reservoir according to claim 2, characterized in that: The value of the resistivity correction index RTXS ranges from 0.35 to 0.

55.

4. The calculation method for the total organic carbon content of a continental sedimentary thin-layer shale gas reservoir according to claim 1 or 3, characterized in that: In the said Step S1, the calculation method of the acoustic travel time baseline includes the following steps: Step S 121 . Establish the acoustic travel time baseline according to the fourth power function of the logarithm of the resistivity curve: AC b = ACXS * [a * (lg(RT)) 4 + b * (lg(RT)) 3 + c * (lg(RT)) 2 + d * lg(RT) + e] where AC b is the acoustic time difference value corresponding to the acoustic time difference baseline, ACXS is the acoustic time difference correction index, lg(RT) is the common logarithm value of the measured resistivity curve, and a, b, c, d, and e are the least squares fitting coefficients respectively; Step S 122 . Calculate the acoustic time difference correction index ACXS and each least squares fitting coefficient to obtain the final acoustic time difference baseline; the calculation method of the acoustic time difference correction index ACXS is: in the tight sandstone formation section, adjust the acoustic time difference correction index ACXS to make the acoustic time difference baseline basically coincide with the acoustic time difference curve, and then obtain the acoustic time difference correction index ACXS.

5. The calculation method for the total organic carbon content of a continental sedimentary thin-layer shale gas reservoir according to claim 4, characterized in that: The value of the acoustic travel time correction index ACXS ranges from 0.9 to 0.

99.

6. The calculation method of the total organic carbon content of a continental sedimentary thin-layer shale gas reservoir according to claim 1, characterized in that: The least squares fitting coefficients a, b, c, d, e, f, g, h, i, j, and k are determined by least squares fitting according to the actual experimental data of the region.

7. The calculation method of the total organic carbon content of a continental sedimentary thin-layer shale gas reservoir according to claim 6, characterized in that: The specific determination method of the least squares fitting coefficients a, b, c, d, e, f, g, h, i, j, and k is: obtain the measured data of the core TOC content, the measured acoustic logging data, and the measured resistivity logging data of the calibration well, and substitute them into the above formulas (1), (2), and (3). By using the optimization algorithm, adjust the parameters of the resistivity correction index RTXS and the acoustic travel time correction index ACXS to obtain the model with the minimum error, and thus determine the least squares fitting coefficients a, b, c, d, e, f, g, h, i, j, and k.

8. The calculation method of the total organic carbon content of a continental sedimentary thin-layer shale gas reservoir according to claim 7, characterized in that: It also includes verifying the determined least squares fitting coefficients to judge whether the error requirements are met.

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