A method and system for predicting drilling risk and reservoir quality

Abstract

The present invention belongs to the field of oil production technology and provides a method and system for predicting drilling risk and reservoir quality. The method comprises the following steps: obtaining well logging data; using the well logging data to calculate the Young's modulus, compressive strength, maximum horizontal principal stress, and minimum horizontal principal stress of the formation; and calculating the stress-intensity balance parameter of the formation based on the Young's modulus, compressive strength, maximum horizontal principal stress, and minimum horizontal principal stress. The method of the present invention proposes for the first time a parameter for quantitatively characterizing formation stress concentration, namely the stress-intensity balance parameter, and forms a set of methods for analyzing formation drilling risk and reservoir quality using this balance parameter. This method enables the prediction of the degree of fracture development in tight sandstone reservoirs and the indication of drilling risk, thereby improving drilling efficiency and reservoir evaluation efficiency. The method can quickly predict the likelihood of fracture development and reservoir quality in tight sandstone reservoirs using well logging data.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of oil exploitation, and particularly relates to a method and system for predicting drilling risk and reservoir quality. BACKGROUND

[0002] Tight reservoirs need to be fractured to improve permeability and increase oil and gas production capacity. The rock strength of the reservoir is an internal factor affecting the formation fracture, and the stress intensity at a certain position is an external factor affecting the rock fracture. Both of them work together to make the reservoir fracture and form a fracture or a crack. Therefore, when evaluating the difficulty of reservoir fracture and whether it can be fractured, the rock strength and stress intensity of the reservoir need to be considered comprehensively.

[0003] At present, the research means is generally to establish a calculation model of reservoir elastic modulus, Poisson's ratio, strength and brittleness through rock mechanics experiment of the reservoir combined with reservoir rock component analysis, and further analyze and calculate the stress size and change through the horizontal principal stress direction of the stress level to determine whether the reservoir will fracture during the fracturing process.

[0004] However, the above analysis process only considers the stress direction and size when considering the influence of the stress on the reservoir. In fact, the influence of the stress on the reservoir has two states, one is stress, and the other is stress (or stress concentration). Stress reflects the absolute size of the stress, while stress reflects the concentration degree of the extrusion effect of the stress on the rock. Obviously, the stress size is only a one-sided embodiment of the stress, and the stress intensity or concentration degree is a comprehensive state reflecting the influence of the stress on the reservoir rock. Therefore, it cannot be simply determined whether the reservoir will fracture according to the stress size, but it is still one of the problems to be solved in the field that whether the state reached after the interaction of different stress sizes and different rock strengths can meet the rock fracture. SUMMARY

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

[0006] In order to achieve the above purpose, the present application adopts the following technical scheme:

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

[0008] Obtaining logging data;

[0009] Calculating the Young's modulus, compressive strength, maximum horizontal principal stress and minimum horizontal principal stress of the formation by using the logging data;

[0010] Based on the Young's modulus, compressive strength, maximum horizontal principal stress and minimum horizontal principal stress, the stress intensity balance parameter of the formation is calculated.

[0011] Obtaining the stress intensity balance parameter curve varying with depth and the formation stress concentration degree parameter by using the stress intensity balance parameter distribution proportion in the depth section;

[0012] According to the stress intensity balance parameter and the formation stress concentration degree parameter, judging the strong stress proportion of the depth section, analyzing the wellbore stability risk and the reservoir quality.

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

[0014] Placing the logging instrument in the wellbore to carry out the top-down test, collecting the logging data reflecting the lithology and its vertical variation, the logging data including the density, acoustic wave, dipole acoustic logging dynamic elastic parameter and pore pressure.

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

[0016] Obtaining the static Young's modulus based on the dipole acoustic logging dynamic elastic parameter;

[0017] Obtaining the compressive strength based on the static Young's modulus;

[0018] Obtaining the shear wave velocity based on the acoustic wave;

[0019] Obtaining the compressive wave velocity based on the shear wave velocity;

[0020] Obtaining the Poisson's ratio based on the shear wave velocity and the compressive wave velocity;

[0021] Obtaining the vertical stress based on the density;

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

[0023] Preferably:

[0024] ;

[0025] ;

[0026] In the formula, and are the linear expansion coefficient and the effective stress coefficient; H, P V , are the formation depth, the formation pore pressure at the calculation depth and the formation temperature variation amount respectively; K h and K H are the minimum and maximum horizontal principal stress direction tectonic stress coefficients respectively; and respectively, are the minimum and maximum horizontal stress additional amount 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, a stress intensity balance parameter of the stratum is calculated based on the Young's modulus, the compressive strength, the maximum horizontal principal stress and the minimum horizontal principal stress, comprising:

[0028] ;

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

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

[0031] a distribution histogram of the stress intensity balance parameter at different depths is established;

[0032] the formula is used to calculate the stratum stress concentration degree parameter k, wherein a and b are two end values of the M value in the histogram which increases and decreases respectively; n M[a, b] represents the number of the M value in the stress concentration interval corresponding to the depth; M is the stress intensity balance parameter, and n is the number of sample points; n M represents the number of the M value in the whole interval of the M value distribution corresponding to the depth, wherein the stress concentration interval ∈ the whole interval;

[0033] 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.

[0034] Preferably, the strong stress proportion of the depth section is judged according to the stress intensity balance parameter and the stratum stress concentration degree parameter, the wellbore stability risk and the reservoir quality are analyzed, comprising the following steps:

[0035] if k is greater than or equal to 50%, the stratum of the corresponding depth section is a strong stress section, and if k is less than 50%, the stratum of the corresponding depth section is not a strong stress section, wherein k is the stratum stress concentration degree parameter;

[0036] the wellbore stability state and the reservoir quality are judged according to the curve of the 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 of the corresponding depth section has a collapse risk, and the reservoir quality is lower than or equal to the intermediate value, and when the M value is lower than the fitting line at the same depth, the wellbore of the corresponding depth section has a loss risk, and the reservoir quality is higher than the intermediate value.

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

[0038] an acquisition unit configured to obtain well logging data;

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

[0040] a second calculation unit configured to calculate stress intensity balance parameters of the formation based on the Young's modulus, the compressive strength, the maximum horizontal principal stress and the minimum horizontal principal stress;

[0041] a third calculation unit configured to obtain a curve of the stress intensity balance parameters varying with depth and a formation stress concentration degree parameter using a stress intensity balance parameter distribution proportion in a depth section;

[0042] an analysis unit configured to determine a strong stress proportion of the depth section, analyze wellbore stability risk and reservoir quality according to the stress intensity balance parameters and the formation stress concentration degree parameter.

[0043] Preferably, the acquisition unit comprises:

[0044] a collection module configured to place a well logging instrument in a wellbore to carry out a top-down test and collect well logging data reflecting lithology and its vertical variation; the well logging data comprises density, acoustic wave, dipole acoustic wave logging dynamic elastic parameters and pore pressure.

[0045] Preferably, the first calculation unit comprises:

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

[0047] obtain compressive strength based on the static Young's modulus;

[0048] obtain shear wave velocity based on the acoustic wave;

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

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

[0051] obtain vertical stress based on the density;

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

[0053] Preferably, the third calculation unit comprises:

[0054] a mapping module configured to establish a distribution histogram of the stress intensity balance parameters at different depths;

[0055] a parameter calculation module for calculating a parameter k of stress concentration degree of a formation by using a formula The parameter k of stress concentration degree of a formation is calculated, wherein a and b are two end values of M value in the histogram in which M value increases and decreases; n M[a, b] represents the number of M value in the stress concentration interval corresponding to the depth; M is a stress intensity balance parameter, and n is the number of sample points; n M represents the number of M value in the full interval of M value distribution corresponding to the depth, wherein the stress concentration interval is in the full interval;

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

[0057] Preferably, the analysis unit comprises:

[0058] A judgment module is configured to judge whether the formation of the corresponding depth section is a strong stress section according to the size of k; if k is greater than or equal to 50%, the formation of the corresponding depth section is a strong stress section; if k is less than 50%, the formation of the corresponding depth section is not a strong stress section; and k is a parameter of stress concentration degree of a formation.

[0059] An analysis module is configured to judge the wellbore stability state and the reservoir quality according to the curve of 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 of the corresponding depth section has a collapse risk, and the reservoir quality is lower than the intermediate value; and when the M value is lower than the fitting line at the same depth, the wellbore of the corresponding depth section has a loss risk, and the reservoir quality is higher than the intermediate value.

[0060] The present application has the following beneficial effects:

[0061] The method of the present application firstly proposes a parameter for quantitatively characterizing the stress concentration phenomenon of a formation, i.e., a stress intensity balance parameter, and forms a set of methods for analyzing the drilling risk and the reservoir quality of the formation by using the balance parameter, realizes the prediction of the fracture development degree of the dense sandstone reservoir and the prompt of the drilling risk, improves the drilling efficiency and the reservoir evaluation efficiency, and can quickly predict the fracture development possibility and the reservoir quality of the dense sandstone reservoir by using the logging data.

[0062] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and achieved by the structure as indicated in the description and the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort based on these drawings.

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

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

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

[0067] Figure 4 A system structure diagram of a method for predicting drilling risk and reservoir quality according to the present application is shown;

[0068] Figure 5 A strong stress and reservoir quality analysis graph of the well logging data of a certain place is shown. DETAILED DESCRIPTION

[0069] In order to make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the following will clearly and completely explain the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort fall within the protection scope of the present application.

[0070] A method for predicting drilling risk and reservoir quality, as shown in Figure 1 , comprises the following steps:

[0071] S1: obtaining well logging data, including density DEN, acoustic wave AC, dynamic elastic parameter Ed of dipole acoustic logging and pore pressure P p ; S2: calculating Young's modulus E, compressive strength C, maximum horizontal principal stress SH and minimum horizontal principal stress Sh of the formation by using the well logging data; S3: calculating stress intensity balance parameter M of the formation by using SH, Sh, E and C through a balance parameter formula; S4: obtaining a curve of M value changing with depth and a formation stress concentration degree parameter k by using the distribution proportion of M in the depth section; S5: judging the strong stress proportion of the depth section, analyzing the wellbore stability risk and the reservoir quality according to the curve of M value changing with depth and the size of k.

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

[0073] The logging tool is placed in the wellbore to conduct a top-down test to collect logging data reflecting the lithology and its vertical variation.

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

[0075] S201: obtaining static Young's modulus E based on the dynamic elastic parameter Ed of the dipole acoustic logging; specifically, the static Young's modulus E is calculated by using the empirical formula E = 0.8765 * Ed; S202: obtaining the compressive strength C based on the static Young's modulus E; specifically, the compressive strength C is calculated by 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: obtaining the shear wave velocity VP based on the acoustic wave AC; specifically, the shear wave velocity VP is calculated by using the empirical formula VP = 0.3048 * 1000000 / AC; S204: obtaining the longitudinal wave velocity VS based on the shear wave velocity VP; specifically, the longitudinal wave velocity VS is calculated by using the empirical formula VS = 2.01731 * VP - 14.616; S205: obtaining the Poisson's ratio P based on the shear wave velocity VP and the longitudinal wave velocity VS; specifically, wherein:

[0078] .

[0079] S206: obtaining the vertical stress SV based on the density DEN; specifically, the vertical stress SV is calculated by using the empirical formula based on the DEN data obtained in step 1:

[0080] ;

[0081] In the formula, is the average density of the i-th formation above the target layer, g / cm3; is the i-th formation thickness above the target layer, m; g is the acceleration of gravity, 9.81 m / s 2 ; n is the number of formations above the target layer, which is an integer; SV is the vertical stress, MPa.

[0082] S207: calculating the maximum horizontal principal stress SH and the minimum horizontal principal stress Sh based on the Poisson's ratio P and the vertical stress SV.

[0083] Further:

[0084] ;

[0085] ;

[0086] Where, and are the linear expansion coefficient and effective stress coefficient, which can be regarded as constants in the same area; H, P V 、 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, which can be regarded as constants within the same block; and 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 the stress intensity balance parameter M at different depths; S402: Use the formula 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; n M[a, b] represents the number of M values ​​in the stress concentration interval of the corresponding depth; M is the stress intensity balance parameter, and n is the number of sample points; n M represents the number of M values ​​in the entire interval of the M value distribution at the corresponding depth, where the stress concentration interval ∈ the entire interval; S403: making a scatter plot of the M value changing with depth, obtaining a curve of the M value changing with depth, and calculating a fitting line of the change trend using the binomial method.

[0092] It should be noted that Figure 3For the histogram and simulation curve of the target well DB901 in a certain area, it can be seen from the figure that in a certain depth section of DB901, the M value is distributed between 1 and 4, and the M value is mainly 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 of the depth section can be obtained.

[0093] Further, at step S5, the following steps are included:

[0094] S501: If k is greater than or equal to 50%, the corresponding depth section of the formation is a strong stress section, and if k is less than 50%, the corresponding depth section of the formation is not a strong stress section; S502: judging the wellbore stability state and reservoir quality according to the relationship between the M value change curve with depth and the fitting line, when the M value is higher than the fitting line at the same depth, the wellbore at this depth section has a collapse risk, and the reservoir quality is lower than the intermediate value (low reservoir quality), when the M value is lower than the fitting line at the same depth, the wellbore at this depth section has a loss risk, and the reservoir quality is higher than the intermediate value (high reservoir quality), when the M value is equal to the fitting line at the same depth, the wellbore at this depth section has no collapse risk and no loss risk, and the reservoir quality is equal to the intermediate value (reservoir quality is medium).

[0095] As shown in Figure 5 , the actual stress intensity balance parameter M logging curve of DB901 well is compared with the balance parameter trend line of the area. The depth is 200-1500m, the M value is less than the fitting line, and the wellbore is prone to have a loss risk and other engineering problems; the depth is 2800-4000m, the M value is greater than the fitting line, and the wellbore is prone to collapse; the depth is located in the reservoir section, the M value is lower than the fitting line, the larger the difference, the higher the reservoir quality. The M value is greater than the fitting line, and the reservoir quality is poor.

[0096] A system for predicting drilling risks and reservoir quality, as shown in Figure 4 , 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 AC, dynamic elastic parameter Ed of dipole acoustic logging and pore pressure P p ; the first calculation unit is used to calculate the Young's modulus E, the compressive strength C, the maximum horizontal principal stress SH and the minimum horizontal principal stress Sh of the formation by using the logging data; the second calculation unit is used to calculate the stress intensity balance parameter M of the formation by using SH, Sh, E and C through the balance parameter formula; the third calculation unit is used to obtain the M value change curve with depth and the stress concentration degree parameter k of the formation by using the M distribution proportion in the depth section; and the analysis unit is used to judge the strong stress proportion of the depth section, analyze the wellbore stability risk and the reservoir quality according to the M value change curve with depth and the size of k.

[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 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; n M[a, b] represents the number of M values ​​in the stress concentration interval of the corresponding depth; M is the stress intensity balance parameter, and n is the number of sample points; n M represents the number of M values ​​in the full interval of the M value distribution at the corresponding depth, where the stress concentration interval ∈ the full interval; the fitting module is used to produce 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 for the system embodiment, since it basically corresponds to the method embodiment, the relevant part can be seen from the part of the method embodiment. The various units and modules of the system for predicting drilling risk and reservoir quality are only divided according to the functional logic, but are not limited to the above division, as long as the corresponding function can be realized; in addition, the specific name of each unit is only for the convenience of mutual differentiation, and is not used to limit the protection scope of the present application.

[0102] Although the present application is described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for predicting drilling risk and reservoir quality, characterized in that: The following steps are involved: Obtain well logging data; Using well logging data, calculate the Young's modulus, compressive strength, maximum horizontal principal stress, and minimum horizontal principal stress of the formation, 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; Based on Young's modulus, compressive strength, maximum horizontal principal stress, and minimum horizontal principal stress, the stress-strength balance parameters of the formation are calculated, including: ; ; Where, and are the linear expansion coefficient and effective stress coefficient; H, P V 、 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; and are 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; Using the distribution ratio of stress intensity balance parameters within the depth section, we can obtain the curve of stress intensity balance parameters changing with depth and the parameters of formation stress concentration, including: Establish the distribution histogram of stress intensity balance parameters at different depths; Using the formula 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; n M[a, b] represents the number of M values ​​in the stress concentration interval of the corresponding depth; M is the stress intensity balance parameter, and n is the number of sample points; n M represents the number of M values ​​in the full interval of the M value distribution at the corresponding depth, where stress concentration interval ∈ full interval; Create a scatter plot of M value versus depth, obtain a curve of M value versus depth based on the scatter plot, and obtain a fitting line of the trend of M value versus depth; 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.

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 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.

3. A method for predicting drilling risk and reservoir quality according to claim 2, characterized in that: Using well 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; Obtain shear wave velocity based on sound waves; Obtain the longitudinal wave velocity based on the shear wave velocity; Poisson's ratio is obtained based on the shear wave velocity and the longitudinal wave velocity; Obtain vertical stress based on density; The maximum horizontal principal stress and the minimum horizontal principal stress are calculated based on Poisson's ratio and vertical stress.

4. The method for predicting drilling risk and reservoir quality according to claim 1, characterized in that: 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, including the following steps: 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. 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.

5. A system for predicting drilling risk and reservoir quality, characterized in that: include: an acquisition unit, 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, 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; The second calculation unit calculates the stress-intensity balance parameters of the formation based on Young's modulus, compressive strength, maximum horizontal principal stress, and minimum horizontal principal stress, including: ; ; Where, and are the linear expansion coefficient and effective stress coefficient; H, P V 、 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; and are 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; The third calculation unit is used to obtain a curve showing the stress intensity balance parameter changing with depth and a formation stress concentration parameter using the distribution ratio of the stress intensity balance parameter within the depth segment, including: Establish the distribution histogram of stress intensity balance parameters at different depths; Using the formula 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; n M[a, b] represents the number of M values ​​in the stress concentration interval of the corresponding depth; M is the stress intensity balance parameter, and n is the number of sample points; n M represents the number of M values ​​in the full interval of the M value distribution at the corresponding depth, where stress concentration interval ∈ full interval; Create a scatter plot of M value versus depth, obtain a curve of M value versus depth based on the scatter plot, and obtain a fitting line of the trend of M value versus depth; 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.

6. The system for predicting drilling risk and reservoir quality according to claim 5, characterized in that: The acquisition unit includes: 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.

7. The system for predicting drilling risk and reservoir quality according to claim 5, characterized in that: The first computing unit includes: A first calculation module is used to obtain a static Young's modulus based on the dynamic elastic parameters of dipole acoustic logging; The compressive strength was obtained based on the static Young's modulus; Obtain shear wave velocity based on sound waves; Obtain the longitudinal wave velocity based on the shear wave velocity; Poisson's ratio is obtained based on the shear wave velocity and the longitudinal wave velocity; Obtain vertical stress based on density; The maximum horizontal principal stress and the minimum horizontal principal stress are calculated based on Poisson's ratio and vertical stress.

8. The system for predicting drilling risk and reservoir quality according to claim 5, characterized in that: The third computing unit includes: A mapping module is used to create distribution histograms of stress intensity balance parameters at different depths; Parameter calculation module, used to use the formula 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; n M[a, b] represents the number of M values ​​in the stress concentration interval of the corresponding depth; M is the stress intensity balance parameter, and n is the number of sample points; n M represents the number of M values ​​in the full interval of the M value distribution at the corresponding depth, where stress concentration interval ∈ full interval; 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.

9. The system for predicting drilling risk and reservoir quality according to claim 5, characterized in that: The analysis unit comprises: 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. 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.

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