A method for evaluating in-situ oil and gas enrichment capacity of fault-controlled source rock based on weight assignment of multiple structure parameters

Abstract

The present application relates to a kind of based on the evaluation method of in-situ enrichment capacity of oil and gas in fracture source rock control, belong to the field of oil and gas exploration geology, including: selecting key fracture parameter as evaluation factor, key fracture parameter includes four types such as fracture structural style, fracture density, vertical fault throw and drilling-fracture nearest distance;Quantitative scoring model of each key fracture parameter is constructed, and fracture structural style score, fracture density score, vertical fault throw score and drilling-fracture nearest distance score are obtained;Fracture reservoir-controlling index is calculated;Based on fracture reservoir-controlling index, reservoir-controlling capacity is classified.The present application builds complete fracture structural parameter system, establishes the quantitative scoring model of each parameter, and builds fracture reservoir-controlling index using weight assignment method, realizes the quantitative evaluation of fracture reservoir-controlling capacity, standardization and comparability.

Description

Technical Field

[0001] This invention relates to a method for evaluating the in-situ enrichment capacity of oil and gas in fracture-controlled source rocks based on the weighting of multiple structural parameters, belonging to the field of petroleum and natural gas exploration geology technology. Background Technology

[0002] Shale oil, as a typical unconventional oil and gas resource, is simultaneously controlled by reservoir quality, organic matter content, and tectonic activity during its formation. Among these factors, fractures not only control reservoir property modification, differences in oil-bearing properties, and the efficiency of oil and gas migration channels, but also profoundly influence the preservation conditions for in-situ enrichment of oil and gas within the source rock. Due to the significant heterogeneity of fracture development, its impact on production capacity exhibits obvious regional differences and nonlinear effects. Furthermore, the mechanisms by which fractures affect unconventional oil and gas systems differ significantly at different scales and evolutionary stages. On the one hand, extensional or shear fractures formed during tectonic activity can enhance reservoir modification and increase the density of microfractures, thereby improving the seepage conditions of oil and gas within the source rock; however, if the openness is too high, it may form effective drainage channels, disrupting the sealing of the reservoir. On the other hand, the geometric characteristics of fracture combinations, their continuity, and connectivity determine the directionality and effectiveness of oil and gas flow. The stress concentration effect under different fracture patterns, the degree of development of associated fractures, and the complexity of the fracture grid structure all have positive or negative impacts on actual production capacity.

[0003] Therefore, fractures not only affect the generation, migration, and accumulation of shale oil, but also create complex, multi-scale, and multi-factor superimposed effects through comprehensive regulation of reservoir properties, sealing conditions, and geostress distribution. Under different tectonic backgrounds and stress states, the dominant factors and intensity of these effects vary significantly, resulting in fracture-controlled reservoirs exhibiting typical spatial heterogeneity and nonlinear response characteristics. Due to these complex multi-source coupling effects, existing fracture-controlled reservoir methods mostly rely on empirical or qualitative descriptions, lacking multi-parameter comprehensive evaluation models and weighting mechanisms to reflect the differences in importance of different tectonic factors, making it difficult to achieve quantitative classification of fracture-controlled reservoir capacity. Therefore, there is an urgent need for a quantitative evaluation method that can comprehensively consider key factors such as fracture structural style, density, fault displacement, and drill-fracture distance, and utilize weighting methods to construct a unified fracture-controlled reservoir index, in order to improve the accuracy of predicting favorable in-situ enrichment areas of hydrocarbons within source rocks. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention proposes a method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on the weighting of multiple structural parameters. By constructing a complete fault structural parameter system, establishing a quantitative scoring model for each parameter, and using the weighting method to construct a fault-controlled hydrocarbon index, the method achieves quantitative, standardized, and comparable evaluation of the fault-controlled hydrocarbon capacity.

[0005] The present invention adopts the following technical solution:

[0006] A method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on the weighting of multiple structural parameters includes the following steps:

[0007] S1, based on the coupling relationship between in-situ hydrocarbon enrichment and fracture structures within the source rock, selects key fracture parameters with clear geological significance as evaluation factors. These key fracture parameters include fracture structure style and fracture density. Vertical displacement and the closest distance between the well and the fracture Four categories;

[0008] S2, Construct a quantitative scoring model for each key fracture parameter to obtain a fracture structure score. Fracture density score Vertical displacement score Drilling-Fault Closest Distance Rating ;

[0009] S3, Calculate the fracture-controlled reservoir index based on the score obtained in step S2. It is used to comprehensively reflect the impact of fractures on the in-situ enrichment capacity of oil and gas in source rocks;

[0010] S4, based on the fault-controlled reservoir index The ability to control Tibet is classified into three categories: Category I (strong Tibet control area), Category II (medium Tibet control area), and Category III (weak Tibet control area).

[0011] Preferably, in step S1, the specific values ​​of the key fracture parameters are obtained from the results of three-dimensional seismic interpretation, the results of structural attribute volume analysis, and the drilling-fracture mapping data.

[0012] Preferably, in step S2, a fracture structure style scoring model is constructed based on fracture morphology and distribution continuity as follows:

[0013]

[0014] in, As a basic component of structural morphology; This is a continuity correction term, with a value between 0 and 0.2. The correction factor is set to 0.5. The average yield varies significantly across different structural styles; the base score for each structural style is determined based on yield statistics. The continuity correction term is used to refine the differences within the same structural style.

[0015] Preferably, the fracture morphology includes twisted, en echelon, parallel, checkerboard, and claw-like patterns, with the en echelon pattern being the most common. =1.0; parallel =0.8; twisted =0.6; claw-like =0.4; checkerboard pattern =0.2;

[0016] When the trend is consistent, the arrangement is regular, and the continuity is strong =0.20; when continuity is moderate and slight local discontinuities occur. =0.10; when continuity is weak, bifurcation is obvious, or fragmentation occurs. =0.00.

[0017] Preferred fracture density score Adopting the principle of moderate optimality, the evaluation is conducted using a quadratic function model, as shown in the following formula:

[0018]

[0019] in, The correlation coefficient has a value between 5 and 20. The optimal fracture density is 0.27-0.54 fractures / km².

[0020] Preferred, vertical displacement scoring A linear decay model is used to reflect the change in closure, and the formula is:

[0021]

[0022] in, This is the first attenuation coefficient, with a value ranging from 0.01 to 0.05; The optimal dislocation threshold is [value]. When [condition]... The score is highest within a certain range, and gradually decreases after exceeding the optimal breakpoint threshold.

[0023] Preferred, Drill-Fracture Closest Distance Rating The optimal distance window model is used to reflect the fracture influence range, and the formula is:

[0024]

[0025] in, This is the second attenuation coefficient; The optimal distance.

[0026] The highest score is achieved when the well spacing is close to the optimal distance.

[0027] The basic score of a construction style is determined by the difference in average yield corresponding to different construction styles. The optimal fracture density was determined by statistically analyzing the changes in yield across different density ranges. By statistically analyzing the relationship between well spacing and production, the optimal distance can be determined. The optimal vertical dislocation threshold was determined by analyzing the trend of production output with vertical dislocation. .

[0028] Preferably, in step S3, the fracture-controlled storage index The formula is as follows:

[0029]

[0030] in, These are the weighting coefficients corresponding to the fracture structure style score, fracture density score, vertical fault displacement score, and borehole-fracture nearest distance score, respectively. ; The higher the value, the stronger the ability to control mineral deposits through fractures.

[0031] Preferably, in step S4, based on the fracture control index... Statistical distribution is divided into breaks, when If the threshold T1 is greater than or equal to the threshold T2, it is classified as a Class I heavily controlled Tibetan area; if the threshold T2 is less than or equal to the threshold T1, it is classified as a Class I heavily controlled Tibetan area. <Threshold T1, classified as a Class II medium-sized controlled storage area; when If the threshold T2 is less than the threshold, it is classified as a Category III weakly controlled Tibetan area;

[0032] Thresholds T1 and T2 are determined based on the distribution characteristics of the production data.

[0033] For any details not covered in this invention, please refer to the prior art.

[0034] The beneficial effects of this invention are as follows:

[0035] (1) This invention constructs a comprehensive evaluation system that includes four types of key fracture parameters, covering multiple key factors such as fracture geometry, preservation conditions, activity intensity and well location relationship, and more comprehensively reflects the reservoir control mechanism;

[0036] (2) For the first time, the fracture strike was introduced into the quantitative evaluation system, which solved the shortcomings of the previous neglect of the strike-stress matching relationship and improved the accuracy of the evaluation of the ability to control reservoirs;

[0037] (3) The fracture-controlled reservoir index was constructed by using the weighting method, which realized the comprehensive characterization of the differentiated contributions of multiple parameters, and made the evaluation results quantifiable, comparable and regionally applicable;

[0038] (4) The reservoir control index obtained by this invention can be used for fault zone selection, in-situ enrichment sweet spot prediction of oil and gas in source rocks and well location optimization, and has clear application value for exploration decision making. Attached Figure Description

[0039] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute an undue limitation of this application.

[0040] Figure 1 This is a schematic diagram of the overall process of the present invention;

[0041] Figure 2 This is a diagram showing the relationship between fracture structure patterns and single-well production in a certain embodiment.

[0042] Figure 3 This is a graph showing the relationship between fracture density and single-well production in one embodiment;

[0043] Figure 4 This is a diagram showing the relationship between vertical displacement and single-well production in one embodiment;

[0044] Figure 5 This is a graph showing the relationship between the closest drilling-fracture distance and single-well production in one embodiment. Detailed Implementation

[0045] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. However, this is not the only description; all aspects not described in detail herein are based on conventional techniques in the field.

[0046] Example 1

[0047] A method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on the weighting of multiple structural parameters, such as... Figure 1 As shown, it includes the following steps:

[0048] S1, based on the coupling relationship between in-situ hydrocarbon enrichment and fracture structures within the source rock, selects key fracture parameters with clear geological significance as evaluation factors. These key fracture parameters include fracture structure style and fracture density. Vertical displacement and the closest distance between the well and the fracture Four categories;

[0049] The specific values ​​of key fracture parameters were obtained from the results of three-dimensional seismic interpretation, structural attribute volume analysis, and drilling-fracture mapping data, and have clear and quantifiable characteristics.

[0050] S2, Construct a quantitative scoring model for each key fracture parameter to obtain a fracture structure score. Fracture density score Vertical displacement score Drilling-Fault Closest Distance Rating ;

[0051] S3, Calculate the fracture-controlled reservoir index based on the score obtained in step S2. It is used to comprehensively reflect the impact of fractures on the in-situ enrichment capacity of oil and gas in source rocks;

[0052] S4, based on the fault-controlled reservoir index The ability to control Tibet is classified into three categories: Category I (strong Tibet control area), Category II (medium Tibet control area), and Category III (weak Tibet control area).

[0053] Example 2

[0054] A method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on the weighting of multiple structural parameters, as described in Example 1, differs in that, in step S2, a fracture structural style scoring model is constructed based on fracture morphology and distribution continuity as follows:

[0055]

[0056] in, As a basic component of structural morphology; This is a continuity correction term, with a value between 0 and 0.2. The correction factor is set to 0.5. The average yield varies significantly across different structural styles; the base score for each structural style is determined based on yield statistics. The continuity correction term is used to refine the differences within the same structural style.

[0057] In this embodiment, fracture structure pattern scoring This is achieved by quantitatively transforming the geometric characteristics of fracture combinations and their corresponding oil trial yields. Based on publicly available oil trial data, the average yields corresponding to different fracture structure patterns exhibit stable differences, showing the following order: en echelon > parallel > twisted > claw-foot > checkerboard. To convert this difference into a calculable quantitative factor, this invention scores the fracture structure patterns. Divided into basic points Continuity of display correction item Two parts, of which This reflects the differences in the control capabilities of the structural style types themselves. Used to describe subtle differences in continuity and integrity within the same construction style.

[0058] Based on the oil production statistics, the average oil production capacity and relative advantages / disadvantages of different fracture structural styles are clearly distinguishable. Based on the ranking of production from high to low, to ensure that the scores fall within a uniform 0-1 range and facilitate weighted integration with other normalized parameters, this embodiment assigns the following to the five structural styles: Figure 2 Standardized base score:

[0059] Goose formation =1.0; parallel =0.8; twisted =0.6; claw-footed =0.4; checkerboard pattern =0.2;

[0060] To further characterize the differences in reservoir control effects within the same structural style due to variations in strike consistency, fracture connectivity, and branch development, this embodiment introduces a continuity correction term. . The value range is 0, 0.10, 0.20:

[0061] When the trend is consistent, the arrangement is regular, and the continuity is strong =0.20; when continuity is moderate and slight local discontinuities occur. =0.10; when continuity is weak, bifurcation is obvious, or fragmentation occurs. =0.00.

[0062] Therefore, in this embodiment:

[0063] .

[0064] Example 3

[0065] A method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on multi-structural parameter weighting, as described in Example 2, differs in that it uses fracture density scoring. Adopting the principle of moderate optimality, the evaluation is conducted using a quadratic function model, as shown in the following formula:

[0066]

[0067] in, The correlation coefficient has a value between 5 and 20. The optimal fracture density;

[0068] In this embodiment, the optimal fracture density is 0.27-0.54 fractures / km² (corresponding to a high yield of 4-5 t / d). Figure 3 Density that is too high or too low is not conducive to enrichment. A quadratic function scoring model is adopted, with D0 = 0.40 lines / km. 2 The optimal fracture density, as defined in this method, was obtained through calibration tests in the example area.

[0069]

[0070] Among them, the correlation coefficient =10 (based on a density deviation of ±0.13 stripes / km² corresponding to a 50–70% decrease in yield).

[0071] For example: the fracture density around a well The fracture density here is 0.35 fractures / km². The results of the structural property analysis, calculated from the structural map, are obtained by first dividing the structural map into a 2km × 2km grid, then counting the number of fractures N in each grid cell, and finally calculating the fracture density within that cell. =N / 4, and after obtaining the value in each cell, the fracture density contour map can be generated using the Shuanghu software. In this way, if you want to know the fracture density at a certain location, you can obtain it from the values ​​of the contour lines in the construction map.

[0072]

[0073] This indicates that its fracture density is close to the optimal range.

[0074] Example 4

[0075] A method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on the weighting of multiple structural parameters, as described in Example 3, differs in that it uses vertical fault displacement scoring. A linear decay model is used to reflect the change in closure, and the formula is:

[0076]

[0077] in, This is the first attenuation coefficient, with a value ranging from 0.01 to 0.05; The optimal dislocation threshold is [value]. When [condition]... The score is highest within a certain range, and gradually decreases after exceeding the optimal breakpoint threshold.

[0078] Depend on Figure 4 It can be seen that the yield is highest when the gap is less than 40m; and drops to 20-30% when the gap is greater than 60m.

[0079] The scoring formula is:

[0080]

[0081] =40m (optimal break-off threshold)

[0082] =0.02 (guaranteed) The attenuation is 0 at 90m.

[0083] For example: Vertical displacement near a well 55m (vertical displacement) The data was obtained through interpretation and measurement using Geoeast software. First, the seismic data volume, fault, and stratigraphic interpretation scheme were imported into Geoeast software. Then, the fault to be measured was located, and a seismic profile perpendicular to the fault strike and passing through the well was selected. Next, the ordinate coordinates Y1 and Y2 of the corresponding points on the top surface reflection layer of the oil layer cut by the fault were measured on this seismic profile, and the vertical fault displacement was calculated. =Y1-Y2), then:

[0084]

[0085] This indicates that the fracture activity is relatively strong and the sealing performance is reduced.

[0086] Example 5

[0087] A method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on multi-structural parameter weighting, as described in Example 4, differs in that it uses a drilling-fracture nearest distance scoring method. The optimal distance window model is used to reflect the fracture influence range, and the formula is:

[0088]

[0089] in, This is the second attenuation coefficient; The optimal distance.

[0090] The highest score is achieved when the well spacing is close to the optimal distance.

[0091] Figure 5 This embodiment shows that 2km is the optimal distance for a certain region (yield of about 3-7t / d).

[0092] therefore:

[0093] The optimal distance is 5km; yield drops significantly after that distance.

[0094] (This reduces the score by approximately 30% for distances between 5.5 and 9.5 km)

[0095]

[0096] For example: the closest distance between a drilling well and a fracture 3km (nearest distance between well and fracture) It was determined on the structural map. First, the well location was found. Then, a perpendicular line was drawn through the well to the direction of the nearest fracture. The length l of the perpendicular line was measured on the structural map, and then converted into the actual distance according to the scale of the structural map. ).

[0097] but:

[0098]

[0099] This indicates that the well spacing is close to the optimal range.

[0100] Example 6

[0101] A method for evaluating the enrichment capacity of fracture-controlled shale oil based on the weighting of multiple structural parameters, as described in Example 5, differs in that, in step S3, the fracture-controlled reservoir index... The formula is as follows:

[0102]

[0103] in, These are the weighting coefficients corresponding to the fracture structure style score, fracture density score, vertical fault displacement score, and borehole-fracture nearest distance score, respectively. ;

[0104] The higher the value, the stronger the ability to control mineral deposits through fractures.

[0105] Using the oil production rate as the evaluation result variable, Pearson correlation analysis was performed on key fracture parameters such as fracture density, vertical fracture displacement, structural style, and the closest distance between the well and the fracture in 20 wells in the study area, and then the absolute value of the correlation coefficient was taken.

[0106] The formula for calculating the Pearson correlation coefficient is as follows:

[0107]

[0108] in, and They represent the first The well's oil production and key fracture parameter values ​​were determined. and These represent the test oil production and the average value of the corresponding key fracture parameters, respectively.

[0109] get:

[0110] |Fracture Structure Pattern| = 0.402;

[0111] | Fracture density |=0.550;

[0112] |Vertical displacement |=0.508;

[0113] Drilling-Fracture Closest Distance |=0.215;

[0114] Summation:

[0115]

[0116] The weight coefficients corresponding to each score are obtained by the absolute value normalization method:

[0117] Weighting coefficients for fracture structure style scoring:

[0118]

[0119] Weighting coefficients for fracture structure style scoring:

[0120]

[0121] Weighting coefficients for vertical displacement scoring:

[0122]

[0123] Weighting coefficients for the closest distance score between drilling and fracture:

[0124]

[0125] Fault-controlled storage index The formula is as follows (rounded to two decimal places):

[0126]

[0127] Example 7

[0128] A method for evaluating the enrichment capacity of fracture-controlled shale oil based on the weighting of multiple structural parameters, as described in Example 6, differs in that, in step S4, the enrichment capacity is evaluated based on the fracture-controlled reservoir index. Statistical distribution is divided into breaks, when If the threshold T1 is greater than or equal to the threshold T2, it is classified as a Class I heavily controlled Tibetan area; if the threshold T2 is less than or equal to the threshold T1, it is classified as a Class I heavily controlled Tibetan area. <Threshold T1, classified as a Class II medium-sized controlled storage area; when If the threshold T2 is less than the threshold, it is classified as a Category III weakly controlled Tibetan area;

[0129] Thresholds T1 and T2 are determined based on the distribution characteristics of the production data.

[0130] In this field, high-yield wells have a production rate of ≥4 t / d; medium-yield wells have a production rate of 1-4 t / d; and low-yield wells have a production rate of <1 t / d. The following two examples (Example A and Example B) illustrate the fault-controlled reservoir index. And the ability to control and store resources is classified.

[0131] Example A: High-yield well J3 (6.72t / d oil production during testing)

[0132] Vertical displacement: 8.18m (small, good sealing)

[0133] Drilling-fracture closest distance: 620m (close, but not into the oil spill area)

[0134] Fracture density: 4 fractures / km² (moderate)

[0135] Fracture structure pattern: twisted (score = 0.6)

[0136] =0.60

[0137] ≈1−0.02(8.18−40)≈1

[0138] ≈e (−0.005(620−2000)²) ≈0.83

[0139] =1−10(4.0−0.4)²≈0.71

[0140] Substitute :

[0141]

[0142]

[0143] Corresponding yield from trial oil production: 6.72 t / d (extremely high yield)

[0144] It has been classified as a Category I heavily controlled Tibetan area.

[0145] Example B: J4 (test oil production 0.10t / d)

[0146] Vertical displacement: 42.77m (relatively large, good sealing)

[0147] Drilling-fracture closest distance: 589m (too close, risk of oil spill)

[0148] Fracture density: 11 fractures / km² (high density)

[0149] Fracture structure pattern: checkerboard (score = 0.2)

[0150] =0.20

[0151] ≈1−0.02(42.77−40)=0.94

[0152] ≈e (−0.005(589−2000)²) ≈0.10

[0153] =1−10(0.1−0.4)²≈0.10

[0154] Substitute :

[0155]

[0156]

[0157] Corresponding yield from trial oil production: 0.1 t / d (low yield)

[0158] It was classified as a Category III weakly controlled Tibetan area.

[0159] After completing the reservoir control index of each well After calculation, using the test oil production rate as a constraint, the results were applied to wells of different production levels. Statistical analysis was performed on the distribution characteristics.

[0160] The results show that high-yield wells correspond to The values ​​are mainly concentrated above 0.70, medium-yield wells are concentrated in the 0.50-0.70 range, while low-yield wells... The values ​​are generally below 0.50.

[0161] Therefore, the threshold T1 is selected. and This serves as an empirical threshold for classifying the capacity of faults to control geological resources, enabling effective differentiation of regions with different capacities for controlling geological resources.

[0162] get Distribution characteristics and corresponding yield:

[0163] ≥0.70: Class I strongly controlled Tibetan area, high-yield well;

[0164] 0.50≤ <0.70: Class II medium-yield reservoir, medium-yield well;

[0165] <0.50: Class III weakly controlled reservoir area, low-yield well;

[0166] Based on the statistics of 20 population samples from the example area, as shown in Table 1:

[0167] Table 1. Statistical table of a sample of 20 people in a certain region

[0168]

[0169] Category I: 12 wells (average production > 4t / d);

[0170] Category II: 4 wells (average production 1–4 t / d);

[0171] Category III: 4 wells (average production <1t / d);

[0172] The overall matching accuracy is approximately 85%, indicating that this method is reliable.

[0173] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on the weighting of multiple structural parameters, characterized in that, Includes the following steps: S1. Key fracture parameters are selected as evaluation factors, including fracture structure pattern and fracture density. Vertical displacement and the closest distance between the well and the fracture Four categories; S2, Construct a quantitative scoring model for each key fracture parameter to obtain a fracture structure score. Fracture density score Vertical displacement score Drilling-Fault Closest Distance Rating ; S3, Calculate the fracture-controlled reservoir index based on the score obtained in step S2. It is used to comprehensively reflect the impact of fractures on the in-situ enrichment capacity of oil and gas in source rocks; S4, based on the fault-controlled reservoir index The ability to control Tibet is classified into three categories: Class I (strong Tibet control area), Class II (medium Tibet control area), and Class III (weak Tibet control area).

2. The method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on the weighting of multiple structural parameters as described in claim 1, characterized in that, In step S1, the specific values ​​of key fracture parameters are obtained through three-dimensional seismic interpretation results, structural attribute volume analysis results, and drilling-fracture mapping data.

3. The method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on the weighting of multiple structural parameters as described in claim 2, is characterized in that... In step S2, a fracture structure style scoring model is constructed based on fracture morphology and distribution continuity as follows: in, As a basic component for constructing morphology, For the continuity correction term, The correction factor is set to 0.

5.

4. The method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on the weighting of multiple structural parameters as described in claim 3, is characterized in that... Fracture morphologies include twisted, en echelon, parallel, checkerboard, and claw-like patterns, with the en echelon pattern being the most common. =1.0; parallel =0.8; twisted =0.6; claw-like =0.4; checkerboard pattern =0.2; When the trend is consistent, the arrangement is regular, and the continuity is strong =0.20; when continuity is moderate and slight local discontinuities occur. =0.10; When continuity is weak, bifurcation is obvious, or fragmentation occurs =0.

00.

5. The method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on the weighting of multiple structural parameters as described in claim 4, characterized in that, Fracture density score Adopting the principle of moderate optimality, the evaluation is conducted using a quadratic function model, as shown in the following formula: in, The correlation coefficient has a value between 5 and 20. The optimal fracture density is 0.27-0.54 fractures / km².

6. The method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on the weighting of multiple structural parameters as described in claim 5, is characterized in that... Vertical displacement score A linear decay model is used to reflect the change in closure, and the formula is: in, This is the first attenuation coefficient, with a value ranging from 0.01 to 0.05; This is the optimal break distance threshold.

7. The method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on the weighting of multiple structural parameters as described in claim 6, characterized in that, Drilling-Fault Closest Distance Rating The optimal distance window model is used to reflect the fracture influence range, and the formula is: in, This is the second attenuation coefficient; The optimal distance.

8. The method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on the weighting of multiple structural parameters as described in claim 7, characterized in that, In step S3, the fracture-controlled reservoir index The formula is as follows: in, These are the weighting coefficients corresponding to the fracture structure style score, fracture density score, vertical fault displacement score, and borehole-fracture nearest distance score, respectively. ; The higher the value, the stronger the ability to control mineral deposits through fractures.

9. The method for evaluating the in-situ enrichment capacity of hydrocarbons in fracture-controlled source rocks based on the weighting of multiple structural parameters as described in claim 8, characterized in that, In step S4, when If the threshold T1 is greater than or equal to the threshold T2, it is classified as a Class I heavily controlled Tibetan area; if the threshold T2 is less than or equal to the threshold T1, it is classified as a Class I heavily controlled Tibetan area. <Threshold T1, classified as a Class II medium-sized controlled storage area; when If the threshold T2 is less than the threshold, it is classified as a Category III weakly controlled Tibetan area; Thresholds T1 and T2 are determined based on the distribution characteristics of the production data.

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