A method and device for evaluating carbon content of a continental tight reservoir by well logging

Abstract

The application discloses a kind of terrestrial dense reservoir carbon content evaluation method and device, comprising: using logging data to determine pure sandstone section;Fixed resistivity curve scale and adjust acoustic time difference curve scale, ensure that acoustic curve and resistivity curve coincide in pure sandstone section, obtain reference value;Based on the reference value, obtain apparent carbon content indication curve;Using multi-mineral rock volume model obtains carbon content;Establish the linear relationship between the carbon content and the apparent carbon content indication curve, obtain carbon content calculation model.The method has a reliable theoretical basis, strong operability, good practical application effect;In addition, by calculating the carbon content of reservoir, further exclude the influence of carbon content on porosity calculation result, and then accurately evaluate the porosity parameter of reservoir, provide help for geological evaluation, favorable layer selection, reserves calculation and the like.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of oil and gas geophysical exploration, and more particularly relates to a method and device for evaluating carbon content of a terrestrial dense reservoir through well logging. BACKGROUND

[0002] Carbon content in a reservoir is a feature of terrestrial sedimentary strata, and the carbon content can reflect the depositional environment and be affected by its evolution. The presence of carbon also significantly affects the physical characteristics of the reservoir. Liu Xuan, Zhong Jianhua, et al. in the document "Analysis of Factors Affecting the Reservoir Properties of Dense Sandstone Reservoirs in Shuixigou Group in Tuha Basin" (Journal of Northwest University. Natural Science Edition, Jun., 2014, Vol. 44, No. 3) show that the carbon content significantly affects the reservoir properties, and thus it is necessary to evaluate the carbon content. Data show that carbon has similar physical properties to coal and is significantly different from sedimentary rocks. The obvious logging response characteristics of carbon are low natural gamma, large acoustic wave, large neutron, and high resistivity. These characteristics can easily identify carbon-containing layers in sedimentary rocks. However, the composition, quality, and maturity of carbon in sedimentary rocks are difficult to determine, and thus it is difficult to calculate the carbon content. The composition of carbon has large acoustic wave, large neutron, and low density logging response characteristics, which greatly affects the calculation of reservoir properties. In practical applications, for conventional reservoirs with good properties and high porosity, the low carbon content has little effect on the reservoir porosity, and can be ignored in reservoir evaluation. For dense sandstone reservoirs with low porosity (generally less than 10%), the carbon content significantly affects the properties. Therefore, it is necessary to evaluate the carbon content using logging data, further calculate the carbon porosity content of the reservoir, and then obtain the reservoir porosity unaffected by the carbon porosity, which is one of the important tasks of logging.

[0003] Data query shows that there are less literatures about the relationship between the evaluation of carbon content and the porosity of carbon, and the literature "The Influence of Carbon in Sediment on the Results of Grain Size Analysis and the Discussion of Pretreatment Methods" (Dryland Research, May 2008, Vol. 25, No. 3) edited by Zhang Li and Mu Guijin points out that the existence of carbon will affect the test analysis of particle size, and the loss on ignition method is used as the method for obtaining the carbon content of the test sample, but there is no literature about the logging evaluation method of the carbon content of sedimentary rock. At present, the method for evaluating the carbon content by using logging data is based on the multi-mineral volume model, and in the calculation of the multi-mineral volume model, the skeleton of carbon is the coal skeleton value (coal skeleton value: gamma 20 API, acoustic wave 500 us / m, neutron 60%, density 1.5 g / cm3, resistivity 500 ohmm), and the content of various minerals including carbon is obtained according to the geological condition constraint, and the method has certain adaptability, but since the skeleton value of carbon is borrowed from the skeleton value of coal, the calculated carbon content is relatively high, and the calculated porosity of the reservoir in the section containing carbon is much lower than the actual porosity, and the degree of coincidence with the core test data is low.

[0004] The present application is aimed at the above problems, and provides a logging evaluation method and device for the carbon content of a terrestrial tight reservoir. SUMMARY

[0005] Therefore, the present application aims to provide a logging evaluation method and device for the carbon content of a terrestrial tight reservoir, which can accurately evaluate the carbon content of the reservoir.

[0006] To achieve the above-mentioned purpose, in one aspect, the present application provides a logging evaluation method for the carbon content of a terrestrial tight reservoir, comprising:

[0007] determining a pure sandstone section by using logging data;

[0008] fixing the resistivity curve scale and adjusting the acoustic travel time curve scale to ensure that the acoustic travel time curve and the resistivity curve coincide in the pure sandstone section, and the resistivity value and the acoustic travel time value at the coincidence position of the pure sandstone section are determined as the resistivity and acoustic travel time reference values, respectively;

[0009] based on the resistivity and acoustic travel time reference values, obtaining a virtual carbon indicator curve of each depth point;

[0010] obtaining the carbon content by using a multi-mineral rock volume model;

[0011] establishing a linear relationship between the carbon content and the virtual carbon indicator curve to obtain a carbon content calculation model.

[0012] Preferably, the virtual carbon indicator curve is a dimensionless curve obtained by calculating the envelope area between the resistivity curve and the acoustic travel time curve of each depth logging data point.

[0013] Preferably, the envelope area between the resistivity curve and the acoustic time curve of each depth logging data point is calculated by using the following calculation formula:

[0014] FCOAL=(RD-RD base )-K*(AC-AC base )

[0015] Wherein, K is the number of lateral curve scale channels, RD base , AC base are the resistivity value and acoustic value of the pure sandstone section; RD, AC are the resistivity curve value and acoustic time difference value, respectively.

[0016] Preferably, by adjusting the selection of the mineral skeleton, the porosity of the carbon debris containing section is ensured to be the same as the core test porosity, and the carbon debris content is obtained.

[0017] Preferably, the carbon debris content calculation model comprises:

[0018] The value of the apparent carbon debris indication curve of the same depth point and the carbon debris content value obtained by the volume model are extracted, and the crossplot technique is used to establish the linear relationship between the carbon debris content and the apparent carbon debris indication curve.

[0019] Preferably, the linear relationship between the carbon debris content and the apparent carbon debris indication curve is:

[0020] VCOAL=A*(FCOAL)+B

[0021] Wherein, A and B are the correlation coefficients of the linear relationship, respectively.

[0022] In another aspect, the present application also includes a device for logging evaluation of carbon debris content in continental tight reservoirs, comprising:

[0023] The obtaining module is used to determine the pure sandstone section by using logging data;

[0024] The reference value module is used to fix the resistivity curve scale and adjust the acoustic time difference curve scale, to ensure that the acoustic curve and the resistivity curve coincide in the pure sandstone section, and the resistivity value and the acoustic time difference value at the coincidence position of the pure sandstone section are determined as the resistivity and acoustic time difference reference values, respectively;

[0025] The apparent carbon debris indication curve obtaining module is used to obtain the apparent carbon debris indication curve of each depth point based on the resistivity and acoustic time difference reference values;

[0026] The carbon debris content obtaining module is used to obtain the carbon debris content by using a multi-mineral rock volume model;

[0027] The model establishing module is used to establish the linear relationship between the carbon debris content and the apparent carbon debris indication curve, and obtain a carbon debris content calculation model.

[0028] Preferably, the apparent coal indicator curve calculates the envelope area between the resistivity curve and the acoustic time difference curve of each depth logging data point as a dimensionless curve, and the envelope area between the resistivity curve and the acoustic time difference curve of each depth logging data point is calculated by using the following calculation formula:

[0029] FCOAL=(RD-RD base )-K*(AC-AC base )

[0030] Wherein, K is the number of lateral curve scale channels, RD base and AC base are the resistivity value and acoustic value of the pure sandstone section; RD and AC are the resistivity curve value and acoustic time difference value.

[0031] Preferably, the linear relationship between the coal content and the apparent coal indicator curve is:

[0032] VCOAL=A*(FCOAL)+B

[0033] Wherein, A and B are the correlation coefficients of the linear relationship.

[0034] Preferably, the coal content module comprises: obtaining the coal content by adjusting the selection of the mineral skeleton to ensure that the porosity of the coal-containing layer section is the same as the core test porosity.

[0035] The present application has the following beneficial effects:

[0036] The present application first obtains a pure sandstone section; adjusts the acoustic curve scale to ensure that the acoustic curve scale and the resistivity curve coincide in the pure sandstone section, and obtains a reference value; then obtains an apparent coal indicator curve based on the reference value; and obtains the coal content by using a multi-mineral rock volume model; establishes a linear relationship between the coal content and the apparent coal indicator curve, and obtains a coal content calculation model. The method has a reliable theoretical basis, strong operability, and good practical application effect; in addition, by calculating the coal content of the reservoir, the influence of the coal content on the porosity calculation result is further excluded, and the porosity parameters of the reservoir are accurately evaluated, thereby providing help for geological evaluation, favorable layer selection, and reserve calculation.

[0037] Other features and advantages of the present application will be described in detail in the following specific embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0038] The above and other objects, features and advantages of the present application will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings in which like reference characters refer to like parts throughout the several views, and wherein the exemplary embodiments of the present application are shown and will be described with the following drawings: - figure 1 shows a schematic view of a well log according to the present application;

[0039] Figure 1 A flow chart of a method for evaluating the carbon content of a continental tight reservoir is shown in the embodiment one of the present application;

[0040] Figure 2 A carbon content evaluation result map for the method for evaluating the carbon content of a continental tight reservoir in the embodiment two of the present application;

[0041] Figure 3 A linear relationship diagram of carbon content and apparent carbon content indicator curve for the method for evaluating the carbon content of a continental tight reservoir in the embodiment two of the present application. DETAILED DESCRIPTION

[0042] The present application utilizes the similar characteristics of carbon medium and organic matter, and uses the method for calculating the content of organic matter, i.e., the classic calculation formula ΔLogR (resistivity and acoustic time difference overlap method) for calculating the content of organic matter. The present application only changes the selection of the baseline. When calculating the content of organic matter, a pure mudstone section is selected as the baseline, and when calculating the content of carbon, a pure sandstone section is selected as the baseline. Finally, the size of the envelope area between the resistivity and porosity curves is used to determine the content of carbon.

[0043] The theoretical basis is that a pure sandstone section is selected as the baseline to ensure that the resistivity and porosity curves coincide in the pure sandstone section, and at this time, the carbon content of the pure sandstone section is considered to be zero. The significant feature of carbon medium is high resistivity and large porosity value, so the relative size of the carbon content can be estimated by using the envelope area between the resistivity and porosity curves, i.e., the larger the envelope area, the higher the carbon content.

[0044] Since the composition and maturity of carbon in sedimentary rocks are not clear, and there is no core test data for its content, there is no direct way to obtain the carbon content. The present application uses indirect means to obtain the carbon content. The specific idea is to establish a multi-mineral model containing carbon, and on the basis of mineral content evaluation, the reservoir porosity is obtained. When the core porosity matches the logging calculated porosity, the carbon content value can be obtained. However, since the composition and physical properties of carbon are not clear, it is difficult to determine the carbon skeleton parameters, and it is not easy to obtain reliable carbon content. Therefore, the carbon content obtained by the multi-mineral model can be related to the resistivity and porosity envelope area to complete the rapid acquisition of the carbon content.

[0045] In the present application, first, a pure sandstone section with low and stable natural gamma is selected, the scales of resistivity and acoustic logging curves are adjusted, the resistivity of the pure sandstone section is ensured to coincide with the acoustic logging curve, the resistivity and acoustic envelope area of the coinciding section are calculated as the reference values, and the dimensionless apparent carbon content (FCOAL) is obtained. In the logging evaluation multi-mineral model, the special mineral of carbon is introduced, on the basis of ensuring the skeleton of other minerals unchanged, the skeleton parameters of the mineral are reasonably adjusted, so that the logging calculated porosity is consistent with the core porosity, at this time, the coal-like mineral content can be considered as the carbon content (VCOAL), then the relationship between the carbon value and the apparent carbon content curve is established, and the carbon content calculation model VCOAL=A*(FCOAL)+B is obtained.

[0046] To specifically illustrate the technical scheme, the present application is described in more detail through the following exemplary embodiments.

[0047] Embodiment one

[0048] Reference Figure 1 The present application provides a logging evaluation method for carbon content in a continental tight reservoir, and the specific steps include:

[0049] S1: determining a pure sandstone section by using logging data;

[0050] S2: fixing the scale of the resistivity curve and adjusting the scale of the acoustic travel time curve, ensuring that the acoustic curve and the resistivity curve coincide in the pure sandstone section, and determining the resistivity value and the acoustic travel time value at the coinciding position of the pure sandstone section as the reference values of resistivity and acoustic travel time, respectively;

[0051] S3: obtaining an apparent carbon indicator curve at each depth point based on the reference values of resistivity and acoustic travel time;

[0052] S4: obtaining the carbon content by using a multi-mineral rock volume model;

[0053] S5: establishing a linear relationship between the carbon content and the apparent carbon indicator curve, and obtaining a carbon content calculation model.

[0054] The above steps are specifically described as follows.

[0055] S1: determining a pure sandstone section by using logging data;

[0056] Specifically, the pure sandstone section is determined by using various data, and the pure sandstone section has the characteristics of regular borehole, low gamma, no carbon content characteristics, and stable resistivity value.

[0057] S2: fixing the scale of the resistivity curve and adjusting the scale of the acoustic travel time curve, ensuring that the acoustic curve and the resistivity curve coincide in the pure sandstone section, and determining the resistivity value and the acoustic travel time value at the coinciding position of the pure sandstone section as the reference values of resistivity and acoustic travel time, respectively.

[0058] Specifically, first fix the resistivity curve scale, then adjust the acoustic curve scale, ensure that the acoustic curve coincides with the resistivity curve in the pure sandstone section, at this time the resistivity and acoustic values are baseline values.

[0059] S3: Based on the resistivity and acoustic travel time baseline values, obtain the apparent carbon indicator curve of each depth point.

[0060] Further, the envelope area between the resistivity curve and the acoustic travel time curve of each depth logging data point is calculated as a dimensionless curve.

[0061] The envelope area of the resistivity curve and the acoustic curve is converted to obtain the apparent carbon indicator curve by using a corresponding evaluation method.

[0062] Further, the envelope area between the resistivity curve and the acoustic travel time curve of each depth logging data point is calculated as a dimensionless curve.

[0063] FCOAL = (RD-RD base )-K*(AC-AC base )

[0064] Wherein, K is the number of horizontal curve scales, RD base , AC base are the resistivity value and acoustic value of the pure sandstone section; RD, AC are the resistivity curve value and acoustic travel time value.

[0065] S4: Obtain the carbon content by using a multi-mineral rock volume model.

[0066] Further, the use of a multi-mineral rock volume model to obtain the carbon content includes:

[0067] By adjusting the selection of the mineral skeleton, ensure that the porosity of the carbon-containing layer section is the same as the core test porosity, and obtain the carbon content.

[0068] Specifically, by adjusting the selection of the mineral skeleton, ensure that the calculated porosity of the carbon-containing layer section is the same as the core test porosity, at this time, the carbon content VCOAL can be obtained.

[0069] S5: Establish a linear relationship between the carbon content and the apparent carbon indicator curve to obtain a carbon content calculation model.

[0070] Further, the carbon content calculation model includes:

[0071] Extract the apparent carbon indicator curve value and the carbon content value obtained by the volume model of the same depth point, and use the crossplot technique to establish a linear relationship between the carbon content and the apparent carbon indicator curve.

[0072] Further, the linear relationship between the content of the carbon debris and the apparent carbon debris indicating curve is:

[0073] VCOAL=A*(FCOAL)+B

[0074] Wherein, A and B are the correlation coefficients of the linear relationship.

[0075] The present application firstly acquires a pure sandstone section; by adjusting the scale of the acoustic curve, it ensures that the scale of the acoustic curve and the resistivity curve coincide in the pure sandstone section, and acquires a reference value; then based on the reference value, it acquires an apparent carbon debris indicating curve; and then utilizes a multi-mineral rock volume model to acquire the content of the carbon debris; and establishes a linear relationship between the content of the carbon debris and the apparent carbon debris indicating curve, and acquires a carbon debris content calculation model. The method has a reliable theoretical basis, strong operability, and good practical application effect; in addition, by calculating the content of the carbon debris in the reservoir, the influence of the content of the carbon debris on the calculation result of the porosity is further excluded, and then the porosity parameter of the reservoir is accurately evaluated, which provides help for geological evaluation, favorable layer selection, reserve calculation and the like.

[0076] Example Two

[0077] By utilizing the present application to process the logging data of the Xujiahe Formation Xujiahe 2 Member in the Sichuan Basin, the evaluation result is as follows:

[0078] Reference Figure 2 , figure data description:

[0079] From left to right:

[0080] The first one is the depth and lithology indicating channel, which lists the natural gamma curve; the 4762-4774 meter well section is selected as the standard sandstone section. The characteristics are that the natural gamma value is low, the resistivity, neutron and acoustic curves are stable, there is no obvious abnormal section and no carbon debris.

[0081] The second one is the resistivity display channel: which lists the deep and shallow resistivity curves and the relationship.

[0082] The third one is the porosity curve channel: which lists the acoustic and neutron curves and the relationship.

[0083] The fourth one is the resistivity and acoustic superposition and lithology division channel: which lists the characteristics of the resistivity curve and the acoustic curve when the curves coincide in the pure sandstone section. It can be seen that there is an obvious envelope area between the resistivity and acoustic curves in the carbon debris containing layer section.

[0084] The fifth one is the apparent carbon debris content indicating channel: the curve is calculated by the envelope area of the resistivity and acoustic.

[0085] The sixth track is a porosity comparison track: core porosity and logging model calculated porosity comparison track, solid line is the calculated porosity of the model containing carbon debris, dotted line is the calculated porosity of the model not containing carbon debris, and rod-shaped line is the core test porosity.

[0086] The seventh track is a carbon content comparison track, which shows that the solid line is the calculated carbon content of the present application, and the dotted line is the carbon content when the core porosity is close to the logging calculated porosity.

[0087] ①In the figure, the well section of 4819-4921.6, 4831.6-4834.8 meters, the natural gamma is about 53, 57 API respectively, the neutron, acoustic and resistivity curves are flat and stable, meeting the pure sandstone baseline condition.

[0088] ②In the figure, there are four sections with high carbon content and three sections with low carbon content, as shown in the lithology track: Figure 2 The four sections with high carbon content have larger resistivity and acoustic superimposed area, as shown in the shadow part of the track, and the corresponding apparent carbon content curve value is also high, with a maximum value of 33. The three sections with low carbon content have relatively small superimposed area, as shown in the shadow part of the track, and the corresponding apparent carbon content value is small, basically less than 10.

[0089] ③In the sections with high carbon content, there is a significant difference in the formation porosity when considering the carbon content and not considering the carbon content during logging evaluation, and there is a significant difference between the dotted line and the solid line in the sixth track in the figure.

[0090] ④As shown in the seventh track, the calculated results of the carbon content evaluation model are similar, and the corresponding content and trend meet the evaluation precision requirement, which can be applied in other areas. Figure 3

[0091] Reference Figure 3 , the abscissa is the apparent carbon content value calculated by superimposing the resistivity and acoustic curves, and the ordinate is the formation carbon content value when the core porosity is close to the logging calculated porosity.

[0092] The relationship in the figure is:

[0093] The fast evaluation of the formation carbon content can use the following relationship:

[0094] Vcoal=0.1882*Fcoal+0.0079

[0095] Correlation coefficient: R 2 =0.9432

[0096] In the formula: Vcoal is the formation carbon content, unit: %; Fcoal is the formation apparent carbon content, dimensionless.

[0097] Example Three​

[0098] The embodiment of the present application provides a device for evaluating carbon content of a continental dense reservoir through well logging, comprising:

[0099] An acquisition module is configured to determine a pure sandstone section by using well logging data;

[0100] A reference value module is configured to fix the scale of the resistivity curve and adjust the scale of the acoustic time difference curve, so as to ensure that the acoustic curve and the resistivity curve coincide in the pure sandstone section, and the resistivity value and the acoustic time difference value at the coincidence position of the pure sandstone section are determined as the resistivity reference value and the acoustic time difference reference value respectively;

[0101] A virtual carbon indicator curve acquisition module is configured to acquire a virtual carbon indicator curve of each depth point based on the resistivity reference value and the acoustic time difference reference value.

[0102] A carbon content acquisition module is configured to acquire the carbon content by using a multi-mineral rock volume model.

[0103] A model establishment module is configured to establish a linear relationship between the carbon content and the virtual carbon indicator curve, and acquire a carbon content calculation model.

[0104] Specifically, the virtual carbon indicator curve calculates the envelope area between the resistivity curve and the acoustic time difference curve of each depth data point of well logging as the virtual carbon indicator curve, and the envelope area between the resistivity curve and the acoustic time difference curve of each depth data point of well logging is calculated by using the following calculation formula:

[0105] FCOAL=(RD-RD base )-K*(AC-AC base )

[0106] Wherein, K is the number of horizontal curve scale channels, RD base and AC base are the resistivity value and the acoustic value of the pure sandstone section respectively; and RD and AC are the resistivity curve value and the acoustic time difference value respectively.

[0107] Specifically, the linear relationship between the carbon content and the virtual carbon indicator curve is as follows:

[0108] VCOAL=A*(FCOAL)+B

[0109] Wherein, A and B are the correlation coefficients of the linear relationship respectively.

[0110] Specifically, the carbon content module comprises: the carbon content is acquired by adjusting the selection of the mineral skeleton, so as to ensure that the porosity of the carbon-containing layer section is the same as the core test porosity.

[0111] Having described various embodiments of the application, it is to be understood that the above description is meant to be illustrative only, and that many modifications and variations of the embodiments are possible without departing from the scope and spirit of the described embodiments. Many modifications and variations of the described embodiments are possible in light of the above teachings. It is, therefore, to be understood that within the scope of the appended claims and their equivalents, the described embodiments can be practiced otherwise than as specifically described.

Claims

1. A well logging evaluation method for carbonaceous debris content in continental tight reservoirs, characterized in that, include: Use well logging data to identify pure sandstone sections; Fixed resistivity curve scale and adjusted acoustic transit time curve scale to ensure that acoustic transit time curve and resistivity curve coincide in pure sandstone section. The resistivity value and acoustic transit time value at the point of overlap in pure sandstone section are determined as resistivity and acoustic transit time reference values, respectively. Based on the resistivity and acoustic time difference reference values, the apparent carbon debris indicator curves at each depth point are obtained; Carbon content was obtained using a multi-mineral rock volume model; Establish a linear relationship between the carbon dust content and the apparent carbon dust indicator curve to obtain a carbon dust content calculation model; The apparent carbon debris indicator curve is a dimensionless curve calculated by the envelope area between the resistivity curve and the sonic transit time curve of each depth logging data point. The envelope area between the resistivity curve and the sonic transit time curve at each depth logging data point is calculated using the following formula: FCOAL=(RD- RD base )-K (AC-AC base ) Where K is the number of horizontal curve scale lines, RD base AC base Resistivity and acoustic wave values ​​for the pure sandstone section are respectively; RD and AC are resistivity curve values ​​and acoustic wave curve values, respectively. The method of obtaining carbon fragment content using a multi-mineral rock volume model includes: By selecting and adjusting the mineral framework, the porosity of the carbonaceous layer is ensured to be the same as that of the core test porosity, and the carbonaceous content is obtained. The carbon dust content calculation model includes: The values ​​of the apparent carbon debris indicator curves at the same depth points and the values ​​of the carbon debris content obtained from the volume model are extracted, and a linear relationship between the carbon debris content and the apparent carbon debris indicator curves is established using cross-plot technology.

2. The well logging evaluation method for carbonaceous debris content in continental tight reservoirs according to claim 1, characterized in that, The linear relationship between the carbon dust content and the apparent carbon dust indicator curve is as follows: VCOAL=A (FCOAL)+B Where A and B are the correlation coefficients of the linear relationship, and VCOAL is the carbon dust content.

3. A well logging evaluation device for assessing the carbonaceous debris content in terrestrial tight reservoirs, characterized in that, include: The acquisition module is used to determine pure sandstone sections using well logging data; The reference value module is used to fix the scale of the resistivity curve and adjust the scale of the acoustic transit curve to ensure that the acoustic curve and the resistivity curve coincide in the pure sandstone section. The resistivity value and acoustic transit value at the point of overlap in the pure sandstone section are determined as the resistivity and acoustic transit reference values, respectively. The visible carbon debris indicator curve acquisition module acquires the visible carbon debris indicator curve at each depth point based on the resistivity and acoustic time difference reference values. The carbon fragment content acquisition module uses a multi-mineral rock volume model to obtain the carbon fragment content. The model building module is used to establish a linear relationship between the carbon dust content and the apparent carbon dust indicator curve, and to obtain a carbon dust content calculation model. The apparent carbon debris indicator curve is a dimensionless curve calculated by the envelope area between the resistivity curve and the sonic transit time curve of each depth logging data point. The envelope area between the resistivity curve and the sonic transit time curve at each depth logging data point is calculated using the following formula: FCOAL=(RD- RD base )-K (AC-AC base ) Where K is the number of horizontal curve scale lines, RD base AC base Resistivity and acoustic wave values ​​for the pure sandstone section are respectively; RD and AC are resistivity curve values ​​and acoustic wave curve values, respectively. The method of obtaining carbon fragment content using a multi-mineral rock volume model includes: By selecting and adjusting the mineral framework, the porosity of the carbonaceous layer is ensured to be the same as that of the core test porosity, and the carbonaceous content is obtained. The carbon dust content calculation model includes: The values ​​of the apparent carbon debris indicator curves at the same depth points and the values ​​of the carbon debris content obtained from the volume model are extracted, and a linear relationship between the carbon debris content and the apparent carbon debris indicator curves is established using cross-plot technology.

4. The apparatus according to claim 3, characterized in that, The linear relationship between the carbon dust content and the apparent carbon dust indicator curve is as follows: VCOAL=A (FCOAL)+B Where A and B are the correlation coefficients of the linear relationship, and VCOAL is the carbon dust content.

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