Method and system for predicting drilling risk and reservoir quality

Abstract

The invention belongs to the technical field of oil exploitation, and provides a method and system for predicting drilling risks and reservoir quality, and the method comprises the following steps: obtaining logging data; the Young modulus, the compressive strength, the maximum horizontal principal stress and the minimum horizontal principal stress of the stratum are calculated through logging data; and calculating a stress intensity balance parameter of the stratum based on the Young modulus, the compressive strength, the maximum horizontal principal stress and the minimum horizontal principal stress. According to the method, a parameter, namely the stress intensity balance parameter, for quantitatively representing the stratum stress concentration phenomenon is proposed for the first time, a set of method for analyzing the stratum drilling risk and the reservoir quality by using the balance parameter is formed, the development degree of the tight sandstone reservoir fracture is predicted, the drilling risk is prompted, and the reservoir quality is improved. The drilling efficiency and the reservoir evaluation efficiency are improved, and the fracture development possibility and the reservoir quality of the tight sandstone reservoir can be quickly predicted by quickly utilizing logging information.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil extraction, and in particular relates to a method and system for predicting drilling risks and reservoir quality. Background Art

[0002] Tight reservoirs require hydraulic fracturing to increase permeability and increase oil and gas production. While reservoir rock strength is an internal factor influencing formation fracturing, the intensity of geostress at a specific location is an external factor. The combined effect of these two factors can lead to reservoir rupture, forming fractures or cracks. Therefore, when evaluating the difficulty of reservoir fracturing and whether hydraulic fracturing is feasible, it is important to consider both reservoir rock strength and geostress intensity.

[0003] At present, the research method is generally to conduct rock mechanics experiments on the reservoir, combined with reservoir rock component analysis, to establish a calculation model for the reservoir elastic modulus, Poisson's ratio, strength and brittleness, and further calculate the stress magnitude and changes through the analysis of the principal stress orientation of the ground stress level to determine whether rupture will occur during the reservoir fracturing transformation process.

[0004] However, the above analysis process only considers the stress orientation and magnitude when considering the impact of geostress on the reservoir. In reality, geostress has two effects on the reservoir: high stress and strong stress (or stress concentration). High stress reflects the absolute magnitude of the geostress, while strong stress reflects the concentration of the geostress's squeezing effect on the rock formation. Obviously, the magnitude of stress is only a unilateral reflection of geostress; the strength or concentration of stress is a comprehensive reflection of the impact of geostress on the reservoir rock. Therefore, whether a reservoir will fracture cannot be determined solely based on the magnitude of stress. Instead, it is necessary to analyze whether the state achieved by the interaction of different geostress magnitudes with different rock strengths is sufficient to achieve rock fracture. This remains one of the urgent issues to be addressed in this field. Summary of the Invention

[0005] In order to solve at least one problem in the background technology, the present invention provides a method and system for predicting drilling risk and reservoir quality.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for predicting drilling risk and reservoir quality comprises the following steps:

[0008] Obtain well logging data;

[0009] Using well logging data, calculate the Young's modulus, compressive strength, maximum horizontal principal stress and minimum horizontal principal stress of the formation;

[0010] Calculate the stress-intensity balance parameters of the formation based on Young's modulus, compressive strength, maximum horizontal principal stress, and minimum horizontal principal stress;

[0011] Using the distribution ratio of stress intensity balance parameters within the depth section, the curve of stress intensity balance parameters changing with depth and the parameters of formation stress concentration degree are obtained;

[0012] Based on stress intensity balance parameters and formation stress concentration parameters, the proportion of strong stress in the depth section is determined, and the wellbore stability risk and reservoir quality are analyzed.

[0013] Preferably, obtaining the well logging data comprises the following steps:

[0014] A logging instrument is placed in the wellbore to conduct top-down testing to collect logging data reflecting lithology and its vertical changes. The logging data includes density, acoustic wave, dipole acoustic wave logging dynamic elastic parameters and pore pressure.

[0015] Preferably, calculating the Young's modulus, compressive strength, maximum horizontal principal stress and minimum horizontal principal stress of the formation using well logging data comprises the following steps:

[0016] The static Young's modulus is obtained based on the dynamic elastic parameters of dipole acoustic logging;

[0017] The compressive strength was obtained based on the static Young's modulus;

[0018] Obtain shear wave velocity based on sound waves;

[0019] Obtain the longitudinal wave velocity based on the shear wave velocity;

[0020] Poisson's ratio is obtained based on the shear wave velocity and the longitudinal wave velocity;

[0021] Obtain vertical stress based on density;

[0022] The maximum horizontal principal stress and the minimum horizontal principal stress are calculated based on Poisson's ratio and vertical stress.

[0023] Preferably:

[0024]

[0025]

[0026] Where, α τ and α are the linear expansion coefficient and effective stress coefficient; H, P V and ΔT are the formation depth, the formation pore pressure at the calculated depth, and the formation temperature change, respectively; K h and K H are the tectonic stress coefficients in the directions of minimum and maximum horizontal principal stress, respectively; Δσ h and Δσ Hare the minimum and maximum horizontal stress additions considering stratum erosion; Sh is the minimum horizontal principal stress; SH is the maximum horizontal principal stress; P is Poisson's ratio; SV is the vertical stress; P p is the pore pressure; E is the Young's modulus.

[0027] Preferably, the stress-intensity balance parameter of the formation is calculated based on Young's modulus, compressive strength, maximum horizontal principal stress, and minimum horizontal principal stress, including:

[0028]

[0029] Where M is the stress-intensity balance parameter; Sh is the minimum horizontal principal stress; SH is the maximum horizontal principal stress; E is Young's modulus; and C is the compressive strength.

[0030] Preferably, the stress intensity balance parameter distribution ratio within the depth section is used to obtain a curve of stress intensity balance parameter variation with depth and a formation stress concentration parameter, comprising the following steps:

[0031] Establish distribution histograms of stress intensity balance parameters at different depths;

[0032] Using the formula k= n M[a,b] n M is used to calculate the formation stress concentration parameter k, where a and b are the two end values ​​of the histogram where the M value increases and decreases, M is the stress intensity balance parameter, and n is the number of sample points;

[0033] A scatter plot of the M value versus depth was made, a curve of the M value versus depth was obtained based on the scatter plot, and a fitting line of the trend of the M value versus depth was obtained.

[0034] Preferably, judging the proportion of strong stress in the depth section and analyzing the wellbore stability risk and reservoir quality based on the stress intensity balance parameter and the formation stress concentration parameter includes the following steps:

[0035] If k is greater than or equal to 50%, the stratum in the corresponding depth segment is a strong stress segment. If k is less than 50%, the stratum in the corresponding depth segment is not a strong stress segment. k is a parameter of the stress concentration degree of the stratum.

[0036] The wellbore stability status and reservoir quality are judged based on the curve of M value changing with depth and the fitting line. When the M value is higher than or equal to the fitting line at the same depth, the wellbore in the corresponding depth section is at risk of collapse, and the reservoir quality is lower than or equal to the median value. When the M value is lower than the fitting line at the same depth, the wellbore in the corresponding depth section is at risk of leakage, and the reservoir quality is higher than the median value.

[0037] A system for predicting drilling risk and reservoir quality, comprising:

[0038] an acquisition unit, for acquiring well logging data;

[0039] The first calculation unit is used to calculate the Young's modulus, compressive strength, maximum horizontal principal stress and minimum horizontal principal stress of the formation using the well logging data;

[0040] The second calculation unit calculates the stress-intensity balance parameter of the formation based on Young's modulus, compressive strength, maximum horizontal principal stress and minimum horizontal principal stress;

[0041] The third calculation unit is used to obtain a curve of stress intensity balance parameter variation with depth and a formation stress concentration degree parameter by using the distribution ratio of the stress intensity balance parameter within the depth segment;

[0042] The analysis unit is used to determine the proportion of strong stress in the depth section based on the stress intensity balance parameters and the formation stress concentration parameters, and to analyze the wellbore stability risk and reservoir quality.

[0043] Preferably, the acquiring unit includes:

[0044] The acquisition module is used to place the logging instrument in the wellbore to conduct top-down testing and collect logging data reflecting the lithology and its vertical changes; the logging data includes density, acoustic wave, dipole acoustic wave logging dynamic elastic parameters and pore pressure.

[0045] Preferably, the first calculation unit includes:

[0046] A first calculation module is used to obtain a static Young's modulus based on the dynamic elastic parameters of dipole acoustic logging;

[0047] The compressive strength was obtained based on the static Young's modulus;

[0048] Obtain shear wave velocity based on sound waves;

[0049] Obtain the longitudinal wave velocity based on the shear wave velocity;

[0050] Poisson's ratio is obtained based on the shear wave velocity and the longitudinal wave velocity;

[0051] Obtain vertical stress based on density;

[0052] The maximum horizontal principal stress and the minimum horizontal principal stress are calculated based on Poisson's ratio and vertical stress.

[0053] Preferably, the third calculation unit includes:

[0054] A mapping module is used to create distribution histograms of stress intensity balance parameters at different depths;

[0055] Parameter calculation module, used to use the formula k= n M[a,b] nMCalculate the formation stress concentration parameter k, where a and b are the two end values ​​of the histogram where the M value increases and decreases, and M is the stress intensity balance parameter;

[0056] The fitting module is used to create a scatter plot of the M value changing with depth, obtain a curve of the M value changing with depth based on the scatter plot, and obtain a fitting line of the trend of the M value changing with depth.

[0057] Preferably, the analysis unit comprises:

[0058] A judgment module is used to judge whether the formation of the corresponding depth segment is a high stress segment based on the value of k. If k is greater than or equal to 50%, the formation of the corresponding depth segment is a high stress segment. If k is less than 50%, the formation of the corresponding depth segment is not a high stress segment. k is a parameter of formation stress concentration degree.

[0059] The analysis module is used to judge the wellbore stability status and reservoir quality based on the M value variation curve with depth and the fitting line. When the M value is higher than the fitting line at the same depth, the wellbore in the corresponding depth section is at risk of collapse and the reservoir quality is lower than the median value. When the M value is lower than the fitting line at the same depth, the wellbore in the corresponding depth section is at risk of leakage and the reservoir quality is higher than the median value.

[0060] Beneficial effects of the present invention:

[0061] The method of the present invention proposes for the first time a parameter for quantitatively characterizing the phenomenon of formation stress concentration, namely the stress intensity balance parameter, and forms a set of methods for analyzing formation drilling risks and reservoir quality using this balance parameter. It realizes the prediction of the degree of fracture development in tight sandstone reservoirs and the indication of drilling risks, improves drilling efficiency and reservoir evaluation efficiency, and can quickly predict the possibility of fracture development and reservoir quality in tight sandstone reservoirs using logging data.

[0062] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0064] Figure 1 A flow chart showing a method for predicting drilling risk and reservoir quality according to the present invention is shown;

[0065] Figure 2 A data graph of well logging at a certain location is shown;

[0066] Figure 3 The histogram and simulation curve graph of the well logging data at a certain location are shown;

[0067] Figure 4 The strong stress and reservoir quality analysis diagram of the well logging data at a certain location is shown;

[0068] Figure 5 A system structure diagram for predicting drilling risk and reservoir quality according to the present invention is shown. DETAILED DESCRIPTION

[0069] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0070] A method for predicting drilling risk and reservoir quality, such as Figure 1 As shown, the following steps are included:

[0071] S1: Obtain logging data, including density DEN, acoustic AC, dipole acoustic logging dynamic elastic parameter Ed and pore pressure P p ; S2: Using logging data, calculate the Young's modulus E, compressive strength C, maximum horizontal principal stress SH and minimum horizontal principal stress Sh of the formation; S3: Using SH, Sh, E and C, calculate the stress intensity balance parameter M of the formation through the balance parameter formula; S4: Using the distribution ratio of M in the depth section, obtain the curve of M value changing with depth and the formation stress concentration parameter k; S5: According to the curve of M value changing with depth and the size of k, judge the proportion of strong stress in the depth section and analyze the wellbore stability risk and reservoir quality.

[0072] Furthermore, in step S1, the following steps are included:

[0073] Logging instruments are placed in the wellbore to conduct top-down testing and collect logging data reflecting lithology and its vertical changes.

[0074] Furthermore, in step S2, the following steps are included:

[0075] S201: Obtain the static Young's modulus E based on the dynamic elastic parameter Ed of dipole acoustic logging; specifically, calculate the static Young's modulus E using the empirical formula E=0.8765*Ed; S202: Obtain the compressive strength C based on the static Young's modulus E; specifically, calculate the compressive strength C using the empirical formula C=3677.7*E.

[0076] In addition, in step S2, the steps of obtaining the maximum horizontal principal stress SH and the minimum horizontal principal stress Sh include:

[0077] S203: Obtain the shear wave velocity VP based on the acoustic wave AC; specifically, calculate the shear wave velocity VP using the empirical formula: VP = 0.3048 * 1000000 / AC; S204: Obtain the longitudinal wave velocity VS based on the shear wave velocity VP; specifically, calculate the longitudinal wave velocity VS using the empirical formula: VS = 2.01731 * VP - 14.616; S205: Obtain the Poisson's ratio P based on the shear wave velocity VP and the longitudinal wave velocity VS; specifically, wherein:

[0078]

[0079] S206: Obtain vertical stress SV based on density DEN. Specifically, the vertical stress SV is calculated using the empirical formula using the DEN data obtained in step 1:

[0080]

[0081] Where, ρ bi is the average density of the i-th section of the stratum above the target layer, g / cm3; ΔH i is the thickness of the ith layer above the target layer, m; g is the acceleration of gravity, 9.81 m / s 2 ; n is the number of strata above the target layer, which is an integer; SV is the vertical stress, MPa.

[0082] S207: Based on the Poisson's ratio P and the vertical stress SV, the maximum horizontal principal stress SH and the minimum horizontal principal stress Sh are calculated.

[0083] Further:

[0084]

[0085]

[0086] Where, α τ and α are the linear expansion coefficient and effective stress coefficient, which can be regarded as constants in the same area; H, P V and ΔT are the formation depth, the formation pore pressure at the calculated depth, and the formation temperature change, respectively; K h and KH are the tectonic stress coefficients in the directions of minimum and maximum horizontal principal stress, respectively, and can be considered as constants within the same block; Δσ h and Δσ H are the minimum and maximum horizontal stress additions considering stratum erosion, respectively, and can be regarded as constants within the same block.

[0087] It should be noted that if Figure 2 As shown in Figure 1, the above method is used to calculate the target well DB901 using well logging data. Here, DEN, AC, Pp, and Ed are the original well logging data, P, C, and E are the calculated rock mechanics parameters, and SH, Sh, and SV are the calculated in-situ stress data.

[0088] Furthermore, in step S3, the step of calculating the stress intensity balance parameter M includes: calculating the stress intensity balance parameter M using the Young's modulus E, the compressive strength C, the maximum horizontal principal stress SH and the minimum horizontal principal stress Sh obtained in step (2) using the formula:

[0089]

[0090] Furthermore, in step S4, the following steps are included:

[0091] S401: Establish a distribution histogram of stress intensity balance parameter M at different depths; S402: Use the formula k= n M[a,b] nM Calculate the formation stress concentration parameter k, where a and b are the two end values ​​of the histogram where the M value increases and decreases, and n represents the number of sample points; S403: Create a scatter plot of the M value versus depth, obtain a curve of the M value versus depth, and calculate a fitting line of the change trend using the binomial method.

[0092] It should be noted that Figure 3 The histogram and simulation curve for target well DB901 are shown in the figure. As can be seen, in a certain depth interval of DB901, the M values ​​are distributed between 1 and 4, with the M values ​​primarily distributed between 1.5 and 2. By dividing the number of M values ​​distributed between 1.5 and 2 by the number of M values ​​distributed between 1 and 4, the stress concentration parameter k for this depth interval can be obtained.

[0093] Furthermore, in step S5, the following steps are included:

[0094] S501: If k is greater than or equal to 50%, the formation in the corresponding depth section is a high stress section; if k is less than 50%, the formation in the corresponding depth section is not a high stress section; S502: The wellbore stability state and reservoir quality are judged based on the relationship between the curve of the M value changing with depth and the fitting line. When the M value is higher than the fitting line at the same depth, the wellbore in this depth section is at risk of collapse, and the reservoir quality is lower than the middle value (low reservoir quality); when the M value is lower than the fitting line at the same depth, the wellbore in this depth section is at risk of leakage, and the reservoir quality is higher than the middle value (high reservoir quality); when the M value is equal to the fitting line at the same depth, the depth section has no collapse risk, no leakage risk, and the reservoir quality is equal to the middle value (medium reservoir quality).

[0095] like Figure 4 As shown in the figure, the actual logging curve of the stress-strength balance parameter M from Well DB901 is compared with the balance parameter trend line for the region. At burial depths of 200-1500 m, M values ​​are less than the fitted line, indicating a high risk of engineering problems such as wellbore leakage. At burial depths of 2800-4000 m, M values ​​are greater than the fitted line, indicating a high risk of wellbore collapse. At depths within the reservoir zone, M values ​​are lower than the fitted line; the greater the difference, the higher the reservoir quality. M values ​​greater than the fitted line indicate poor reservoir quality.

[0096] A system for predicting drilling risk and reservoir quality, such as Figure 5 As shown, it includes an acquisition unit, a first calculation unit, a second calculation unit, a third calculation unit and an analysis unit. The acquisition unit is used to obtain logging data, including density DEN, acoustic wave AC, dipole acoustic wave logging dynamic elastic parameter Ed and pore pressure P p ; The first calculation unit is used to calculate the Young's modulus E, compressive strength C, maximum horizontal principal stress SH and minimum horizontal principal stress Sh of the formation using logging data; the second calculation unit is used to calculate the stress intensity balance parameter M of the formation through the balance parameter formula using SH, Sh, E and C; the third calculation unit is used to use the M distribution ratio in the depth section to obtain the curve of M value changing with depth and the formation stress concentration parameter k; the analysis unit is used to judge the proportion of strong stress in the depth section based on the curve of M value changing with depth and the size of k, and analyze the wellbore stability risk and reservoir quality.

[0097] Furthermore, the acquisition unit includes an acquisition module, which is used to place a logging instrument in the wellbore to conduct a top-down test and collect logging data reflecting lithology and its vertical changes.

[0098] Furthermore, the first calculation unit includes a first calculation module. Specifically, the first calculation module is used to obtain a static Young's modulus E based on a dynamic elastic parameter Ed obtained from dipole acoustic logging; obtain a compressive strength C based on the static Young's modulus E; obtain a shear wave velocity VP based on the acoustic wave AC; obtain a longitudinal wave velocity VS based on the shear wave velocity VP; obtain a Poisson's ratio P based on the shear wave velocity VP and the longitudinal wave velocity VS; obtain a vertical stress SV based on a density DEN; and calculate a maximum horizontal principal stress SH and a minimum horizontal principal stress Sh based on the Poisson's ratio P and the vertical stress SV.

[0099] Furthermore, the third calculation unit includes a mapping module, a parameter calculation module and a fitting module. The mapping module is used to establish a distribution histogram of the stress intensity balance parameter M at different depths; the parameter calculation module is used to use the formula k= n M[a,b] nM Calculate the formation stress concentration parameter k, where a and b are the two end values ​​of the histogram where the M value increases and decreases. The fitting module is used to create a scatter plot of the M value changing with depth, obtain a curve of the M value changing with depth, and calculate a fitting line of the change trend using the binomial method.

[0100] Furthermore, the analysis unit includes a judgment module and an analysis module. The judgment module is used to judge whether the formation of the corresponding depth section is a high stress section based on the value of k. If k is greater than or equal to 50%, the formation of the corresponding depth section is a high stress section. If k is less than 50%, the formation of the corresponding depth section is not a high stress section. The analysis module is used to judge the wellbore stability state and reservoir quality based on the relationship between the M value variation curve with depth and the fitting line. When the M value is higher than the fitting line at the same depth, the wellbore of the depth section is at risk of collapse and the reservoir quality is lower than the median value. When the M value is lower than the fitting line at the same depth, the wellbore of the depth section is at risk of leakage and the reservoir quality is higher than the median value.

[0101] It should be noted that, since the system embodiments generally correspond to the method embodiments, reference should be made to the description of the method embodiments for relevant details. The various units and modules of the system for predicting drilling risk and reservoir quality are divided according to functional logic, but are not limited to the above divisions, as long as they can achieve the corresponding functions. In addition, the specific names of the various units are only for the purpose of distinguishing them from each other and are not intended to limit the scope of protection of the present invention.

[0102] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting drilling risk and reservoir quality, characterized in that: The following steps are involved: Obtain well logging data; Using logging data, calculate the Young's modulus, compressive strength, maximum horizontal principal stress and minimum horizontal principal stress of the formation; Calculate the stress intensity balance parameters of the formation based on Young's modulus, compressive strength, maximum horizontal principal stress and minimum horizontal principal stress; Using the distribution ratio of stress intensity balance parameters in the depth section, the curve of stress intensity balance parameters changing with depth and the parameters of formation stress concentration degree are obtained; Based on the stress intensity balance parameters and formation stress concentration parameters, the proportion of strong stress in the depth section is determined, and the wellbore stability risk and reservoir quality are analyzed.

2. A method for predicting drilling risk and reservoir quality according to claim 1, characterized in that: Obtaining well logging data includes the following steps: A logging instrument is placed in the wellbore to carry out top-down testing to collect logging data reflecting lithology and its vertical changes, including density, acoustic wave, dipole acoustic wave logging dynamic elastic parameters and pore pressure.

3. A method for predicting drilling risk and reservoir quality according to claim 2, characterized in that: Using the logging data, Young's modulus, compressive strength, maximum horizontal principal stress and minimum horizontal principal stress of the formation are calculated, including the following steps: The static Young's modulus is obtained based on the dynamic elastic parameters of dipole acoustic logging; The compressive strength was obtained based on the static Young's modulus; Based on the sound wave, the shear wave velocity is obtained; The longitudinal wave velocity is obtained based on the shear wave velocity; Poisson's ratio is obtained based on the shear wave velocity and the longitudinal wave velocity; Based on the density, vertical stress is obtained; The maximum horizontal principal stress and the minimum horizontal principal stress are calculated based on Poisson's ratio and vertical stress.

4. A method for predicting drilling risk and reservoir quality according to claim 3, characterized in that: In the formula, α τ and α are the linear expansion coefficient and effective stress coefficient; H, P V , ΔT are the formation depth, the formation pore pressure and the formation temperature change at the calculated depth respectively; K h and K H are the tectonic stress coefficients in the directions of minimum and maximum horizontal principal stress, respectively; Δσ h and Δσ H are the minimum and maximum horizontal stress additions considering stratum erosion, respectively; Sh is the minimum horizontal principal stress; SH is the maximum horizontal principal stress; P is Poisson's ratio; SV is the vertical stress; P p is the pore pressure; E is the Young's modulus.

5. A method for predicting drilling risk and reservoir quality according to claim 1, characterized in that: Based on Young's modulus, compressive strength, maximum horizontal principal stress and minimum horizontal principal stress, the stress intensity balance parameters of the formation are calculated, including: Where M is the stress intensity balance parameter; Sh is the minimum horizontal principal stress; SH is the maximum horizontal principal stress; E is Young's modulus; C is the compressive strength.

6. A method for predicting drilling risk and reservoir quality according to claim 1, characterized in that: Using the distribution ratio of stress intensity balance parameters in the depth section, a curve of stress intensity balance parameters changing with depth and formation stress concentration degree parameters are obtained, including the following steps: Establish distribution histograms of stress intensity balance parameters at different depths; Using the formula k = n M[a,b] n M is used to calculate the formation stress concentration parameter k, where a and b are the two end values ​​where the M value increases and decreases in the histogram, M is the stress intensity balance parameter, and n is the number of sample points; A scatter plot of the M value changing with depth is made, a curve of the M value changing with depth is obtained based on the scatter plot, and a fitting line of the trend of the M value changing with depth is obtained.

7. A method for predicting drilling risk and reservoir quality according to claim 5, characterized in that: According to the stress intensity balance parameters and the formation stress concentration parameters, the proportion of strong stress in the depth section is determined, and the wellbore stability risk and reservoir quality are analyzed, including the following steps: If k is greater than or equal to 50%, the formation at the corresponding depth segment is a strong stress segment. If k is less than 50%, the formation at the corresponding depth segment is not a strong stress segment. k is a parameter of formation stress concentration. The wellbore stability state and reservoir quality are judged based on the curve of M value changing with depth and the fitting line. When the M value is higher than or equal to the fitting line at the same depth, the wellbore in the corresponding depth section is at risk of collapse, and the reservoir quality is lower than or equal to the middle value. When the M value is lower than the fitting line at the same depth, the wellbore in the corresponding depth section is at risk of leakage, and the reservoir quality is higher than the middle value.

8. A system for predicting drilling risk and reservoir quality, characterized in that: include: An acquisition unit, used for acquiring well logging data; The first calculation unit is used to calculate the Young's modulus, compressive strength, maximum horizontal principal stress and minimum horizontal principal stress of the formation using the well logging data; The second calculation unit calculates the stress intensity balance parameter of the formation based on Young's modulus, compressive strength, maximum horizontal principal stress and minimum horizontal principal stress; The third calculation unit is used to obtain a curve of stress intensity balance parameter variation with depth and a formation stress concentration degree parameter by using the distribution ratio of the stress intensity balance parameter in the depth section; The analysis unit is used to determine the proportion of strong stress in the depth section according to the stress intensity balance parameters and the formation stress concentration degree parameters, and to analyze the wellbore stability risk and reservoir quality.

9. A system for predicting drilling risk and reservoir quality according to claim 8, characterized in that: The acquisition unit comprises: The acquisition module is used to place the logging instrument in the wellbore to carry out top-down testing and collect logging data reflecting the lithology and its vertical changes; the logging data includes density, acoustic wave, dipole acoustic wave logging dynamic elastic parameters and pore pressure.

10. A system for predicting drilling risk and reservoir quality according to claim 8, characterized in that: The first computing unit comprises: A first calculation module is used to obtain a static Young's modulus based on a dynamic elastic parameter of dipole acoustic logging; The compressive strength was obtained based on the static Young's modulus; Based on the sound wave, the shear wave velocity is obtained; The longitudinal wave velocity is obtained based on the shear wave velocity; Poisson's ratio is obtained based on the shear wave velocity and the longitudinal wave velocity; The vertical stress is obtained based on the density; The maximum horizontal principal stress and the minimum horizontal principal stress are calculated based on Poisson's ratio and vertical stress.

11. A system for predicting drilling risk and reservoir quality according to claim 8, characterized in that: The third computing unit comprises: A mapping module is used to establish distribution histograms of stress intensity balance parameters at different depths; Parameter calculation module, used to use the formula k = n M[a,b] nM Calculate the formation stress concentration parameter k, where a and b are the two end values ​​where the M value becomes larger and smaller in the histogram, and M is the stress intensity balance parameter; The fitting module is used to make a scatter plot of the M value changing with depth, obtain a curve of the M value changing with depth based on the scatter plot, and obtain a fitting line of the trend of the M value changing with depth.

12. A system for predicting drilling risk and reservoir quality according to claim 8, characterized in that: The analysis unit comprises: A judgment module is used to judge whether the stratum of the corresponding depth segment is a strong stress segment according to the size of k. If k is greater than or equal to 50%, the stratum of the corresponding depth segment is a strong stress segment. If k is less than 50%, the stratum of the corresponding depth segment is not a strong stress segment. k is a parameter of the stratum stress concentration degree. The analysis module is used to judge the wellbore stability state and reservoir quality based on the M value variation curve with depth and the fitting line. When the M value is higher than the fitting line at the same depth, the wellbore in the corresponding depth section is at risk of collapse and the reservoir quality is lower than the middle value. When the M value is lower than the fitting line at the same depth, the wellbore in the corresponding depth section is at risk of leakage and the reservoir quality is higher than the middle value.

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