Shale gas fracturing well casing deformation risk prediction method, system and equipment and storage medium

Abstract

The invention relates to the technical field of oil-gas exploration and development, and particularly discloses a shale gas fractured well casing deformation risk prediction method, system and device and a storage medium, and the method comprises the steps: calculating the static Young modulus, the static Poisson's ratio, the triaxial ground stress value and the maximum principal stress direction angle of a stratum based on the array wave logging data of a shale gas fractured well; based on the imaging logging data of the shale gas fractured well, the natural fracture occurrence is determined; according to the static Poisson's ratio, the cohesive force and the internal friction coefficient of the natural fracture are calculated, and the hydraulic fracture tail end pressure of the casing deformation risk point is calculated; and calculating the casing deformation safety coefficient and determining the casing deformation risk level according to the stratum maximum principal stress direction angle, the triaxial ground stress value, the natural fracture occurrence, the natural fracture cohesion, the internal friction coefficient and the hydraulic fracture tail end pressure. The risk prediction accuracy of the shale gas fracturing well can be improved, the technical cost is reduced, a reference is provided for optimization of a fracturing scheme, and the success rate of fracturing construction is improved.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration and development technology, and in particular to a method, system, equipment and storage medium for predicting the risk of casing deformation in shale gas fracturing wells. Background Technology

[0002] Shale oil and gas reservoirs utilize a large-scale horizontal well fracturing development model to create a complex three-dimensional fracture network, fully utilizing the reservoir's oil and gas reserves. Shale oil and gas fracturing must avoid shear slippage from natural fractures, which could lead to casing deformation or breakage, affecting construction efficiency and stimulation effectiveness. Casing deformation risk prevention is a key issue hindering the stimulation and development of shale gas reservoirs.

[0003] By performing likelihood and ant-like property analyses on the data volume obtained from seismic exploration, a fracture model can be established to determine the distribution and orientation of natural fractures on the fracturing platform. By comparing this model with the wellbore trajectory, the location where natural fractures cut into the wellbore can be determined, identifying casing deformation risk points. Currently, seismic interpretation software such as Petrel, DSG, and GeoEast are used for natural fracture modeling and analysis.

[0004] like Figure 2 As shown, current predictions of casing deformation risk levels employ a formula for calculating the casing deformation shear activity coefficient based on the Mohr-Coulomb criterion. This method calculates the casing deformation risk coefficient based on the angle between the formation triaxial stress and the natural fracture surface, as well as the cohesion and internal friction coefficient of the natural fracture. This method has been applied to CNPC's FrSmart fracturing design software. However, the confirmation of casing deformation risk points currently requires regional seismic exploration. Due to the high cost of seismic exploration, many blocks have not undergone seismic analysis, lacking fracture distribution information and thus unable to predict casing deformation. Seismic analysis establishes fracture models, but these models are inevitably subject to errors due to the influence of the directional depth relationship. Furthermore, there is a certain deviation between the location of the natural fracture and the wellbore cutting point and the actual casing deformation risk point; therefore, the accuracy of casing deformation risk point judgment needs to be improved. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method, system, equipment, and storage medium for predicting casing deformation risks in shale gas fracturing wells.

[0006] Firstly, the present invention provides a method for predicting the risk of casing deformation in shale gas fracturing wells, the technical solution of which is as follows:

[0007] Based on array wave logging data from shale gas fractured wells, the static Young's modulus, static Poisson's ratio, triaxial geostress values, and maximum principal stress direction angle of the formation at the target casing deformation risk point of the shale gas fractured well are calculated. Based on the imaging logging data from the shale gas fractured wells, the location and natural fracture occurrence of the target casing deformation risk point are determined.

[0008] Based on the static Poisson's ratio, calculate the cohesion and internal friction coefficient of the natural fracture at the target sheathing risk point, and calculate the hydraulic fracture terminal pressure at the target sheathing risk point.

[0009] Based on the maximum principal stress direction angle of the formation, the triaxial stress value, the natural fracture orientation, the natural fracture cohesion, the internal friction coefficient, and the hydraulic fracture terminal pressure, the casing deformation safety factor of the target casing deformation risk point is calculated, and the casing deformation risk level of the target casing deformation risk point is determined according to the magnitude of the casing deformation safety factor.

[0010] The beneficial effects of the shale gas fracturing well casing deformation risk prediction method of the present invention are as follows:

[0011] The method of this invention can effectively improve the accuracy of risk prediction for shale gas fracturing wells, eliminates the need for prior seismic data volume analysis, and reduces technical costs; it also provides a reliable reference for optimizing fracturing schemes and improves the success rate of fracturing operations.

[0012] Based on the above scheme, the method for predicting the risk of casing deformation in shale gas fracturing wells according to the present invention can be further improved as follows.

[0013] In one optional approach, the array wave logging data includes: P-wave transit time, S-wave transit time, rock density, vertical depth, formation pressure coefficient, and fast S-wave azimuth; the triaxial stress values ​​include: vertical principal stress, maximum horizontal principal stress, and minimum horizontal principal stress; the steps of calculating the formation static Young's modulus, static Poisson's ratio, triaxial stress values, and maximum principal stress direction angle of the formation at the target casing deformation risk point of the shale gas fractured well based on the array wave logging data include:

[0014] The P-wave transit time, the S-wave transit time, and the rock density are input into a first preset formula for calculation to obtain the static Young's modulus of the formation; wherein, the first preset formula is: E is the static Young's modulus of the formation, DEN is the rock density, DTS is the P-wave transit time, and DTC is the S-wave transit time.

[0015] The longitudinal wave time difference and the transverse wave time difference are input into a second preset formula for calculation to obtain the static Poisson's ratio; wherein, the second preset formula is: v is the static Poisson's ratio;

[0016] The rock density and the vertical depth are input into a third preset formula for calculation to obtain the vertical principal stress; wherein, the third preset formula is: h is the vertical depth, and σ2 is the vertical principal stress;

[0017] The vertical depth, the static Poisson's ratio, and the vertical principal stress are input into a fourth preset formula for calculation to obtain the maximum horizontal principal stress; wherein, the fourth preset formula is: σ1 is the maximum horizontal principal stress, P por For pore pressure, α p The formation pressure coefficient is mentioned above;

[0018] The static Poisson's ratio, the vertical principal stress, and the pore pressure are input into a fifth preset formula for calculation to obtain the minimum horizontal principal stress; wherein, the fifth preset formula is: σ3 is the minimum horizontal principal stress;

[0019] The azimuth of the fast shear wave is determined as the direction angle of the maximum principal stress of the formation.

[0020] In one alternative approach, the natural fracture occurrence includes: natural fracture dip angle, natural fracture azimuth angle, and natural fracture dip angle; the step of determining the natural fracture occurrence of the target casing deformation risk point based on the imaging logging data of the shale gas fractured well includes:

[0021] The location of the trough in the imaging logging data is determined as the dip angle of the natural fracture.

[0022] The dip angle of the natural crack is input into the sixth preset formula for calculation to obtain the azimuth angle of the natural crack; wherein, the sixth preset formula is: γ=ε±90; ε is the dip angle of the natural crack, and γ is the azimuth angle of the natural crack;

[0023] The peak-to-trough spacing and borehole diameter from the imaging logging data are input into a seventh preset formula for calculation to obtain the natural fracture dip angle; wherein, the seventh preset formula is: T is the peak-to-trough distance, C is the borehole diameter, and β is the natural fracture inclination angle.

[0024] In one alternative approach, the step of calculating the cohesion of the natural cracks and the coefficient of internal friction at the target sheathing risk point based on the static Poisson's ratio includes:

[0025] Based on the eighth preset formula and according to the static Poisson's ratio, the cohesion of the natural crack and the internal friction coefficient of the target sheathing risk point are calculated.

[0026] The eighth preset formula is as follows: C w denoted as the cohesive force within the natural crack, μ as the internal friction coefficient, and SH as the clay content.

[0027] In one alternative approach, the step of calculating the hydraulic fracture terminal pressure at the target risk point includes:

[0028] Based on the ninth preset formula, the pressure at the end of the hydraulic fracture at the target risk point is calculated; wherein, the ninth preset formula is: P = P head +0.01×hl×k; P is the pressure at the end of the hydraulic fracture, P head denoted as the wellhead pressure, l as the length of the tubing from the wellhead to the end of the perforated section in the fracturing well, and k as the friction coefficient at the maximum operating flow rate.

[0029] In one optional approach, the step of calculating the casing deformation safety factor of the target casing deformation risk point based on the maximum principal stress direction angle of the formation, the triaxial stress value, the natural fracture orientation, the natural fracture cohesion, the internal friction coefficient, and the hydraulic fracture terminal pressure includes:

[0030] Based on the tenth preset formula, and according to the maximum principal stress direction angle, the vertical principal stress, the maximum horizontal principal stress, the minimum horizontal principal stress, the dip angle of the natural fracture, the azimuth angle of the natural fracture, the dip angle of the natural fracture, the cohesion of the natural fracture, the internal friction coefficient, and the pressure at the end of the hydraulic fracture, the casing deformation safety factor of the target casing deformation risk point is calculated; wherein, the tenth preset formula is:

[0031]

[0032] fa is the safety factor of the casing deformation, and ω is the direction angle of the maximum principal stress of the formation.

[0033] In one optional approach, the step of determining the risk level of the target risk point based on the magnitude of the relocation safety factor includes:

[0034] When the safety factor of the housing transformation is within a first preset range, the risk level of the housing transformation is determined to be the first level;

[0035] When the safety factor of the housing transformation is within the second preset range, the risk level of the housing transformation is determined to be the second level;

[0036] When the safety factor of the housing transformation is within a third preset range, the risk level of the housing transformation is determined to be level three.

[0037] Secondly, this invention provides a shale gas fracturing well casing variation risk prediction system, the technical solution of which is as follows:

[0038] It includes: a first processing module, a second processing module, and a third processing module;

[0039] The first processing module is used to: calculate the static Young's modulus, static Poisson's ratio, triaxial geostress value and maximum principal stress direction angle of the formation at the target nesting risk point of the shale gas fractured well based on the array wave logging data of the shale gas fractured well; and determine the natural fracture occurrence of the target nesting risk point based on the imaging logging data of the shale gas fractured well.

[0040] The second processing module is used to: calculate the cohesion and internal friction coefficient of the natural fracture at the target sheathing risk point based on the static Poisson's ratio, and calculate the hydraulic fracture end pressure at the target sheathing risk point;

[0041] The third processing module is used to: calculate the casing deformation safety factor of the target casing deformation risk point based on the maximum principal stress direction angle of the formation, the triaxial geostress value, the natural fracture occurrence, the natural fracture cohesion, the internal friction coefficient, and the hydraulic fracture end pressure, and determine the casing deformation risk level of the target casing deformation risk point based on the magnitude of the casing deformation safety factor.

[0042] The beneficial effects of the shale gas fracturing well casing deformation risk prediction system of the present invention are as follows:

[0043] The system of this invention can effectively improve the accuracy of risk prediction for shale gas fracturing wells, eliminates the need for prior seismic data volume analysis, and reduces technical costs; it also provides a reliable reference for optimizing fracturing schemes and improves the success rate of fracturing operations.

[0044] Thirdly, the technical solution of an electronic device according to the present invention is as follows:

[0045] It includes a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of the shale gas fracturing well casing variation risk prediction method of the present invention.

[0046] Fourthly, the technical solution of a computer-readable storage medium provided by the present invention is as follows:

[0047] The computer-readable storage medium stores instructions that, when read, cause the computer-readable storage medium to perform the steps of the shale gas fracturing well casing variation risk prediction method of the present invention.

[0048] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0049] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0050] Figure 1 This is a schematic flowchart illustrating an embodiment of a method for predicting casing deformation risks in shale gas fracturing wells according to the present invention.

[0051] Figure 2 A schematic diagram of the Mohr-Coulomb criterion-based prediction method;

[0052] Figure 3 A schematic diagram illustrating the interpretation of the occurrence of natural fractures in imaging logging data;

[0053] Figure 4 This is a schematic diagram showing the angle between triaxial stress and the fracture surface;

[0054] Figure 5 A schematic diagram illustrating natural fractures in a transverse wellbore displayed using imaging logging.

[0055] Figure 6 This is a schematic diagram showing the direction angle of the maximum principal stress in the formation at 100 degrees.

[0056] Figure 7 A schematic diagram of the calculation results for array wave logging data;

[0057] Figure 8 This is a schematic diagram of an embodiment of a shale gas fracturing well casing variation risk prediction system according to the present invention;

[0058] Figure 9 This is a schematic diagram of an embodiment of an electronic device according to the present invention. Detailed Implementation

[0059] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0060] Figure 1This diagram illustrates a flowchart of an embodiment of a shale gas fracturing well casing deformation risk prediction method provided by the present invention. This method can be executed by electronic devices such as terminal devices or servers. The terminal device can be any fixed or mobile terminal, such as user equipment (UE), mobile device, user terminal, terminal, cellular phone, cordless phone, personal digital assistant (PDA), handheld device, computing device, vehicle-mounted device, or wearable device. The server can be a single server or a server cluster consisting of multiple servers. Any electronic device can implement the shale gas fracturing well casing deformation risk prediction method by having its processor call computer-readable instructions stored in its memory. Figure 1 As shown, it includes the following steps:

[0061] S1. Based on array wave logging data from shale gas fractured wells, calculate the static Young's modulus, static Poisson's ratio, triaxial geostress values, and maximum principal stress direction angle of the formation at the target casing deformation risk point of the shale gas fractured well. Based on imaging logging data from the shale gas fractured wells, determine the natural fracture occurrence of the target casing deformation risk point.

[0062] Based on imaging logging records and logging curves from shale gas fractured wells, and combined with drilling data, casing deformation risk points are identified. Multiple casing deformation risk points may exist in a shale gas fractured well; this embodiment uses any one of them as an example, defined as the target casing deformation risk point. Array wave logging data includes, but is not limited to: P-wave transit time, S-wave transit time, rock density, vertical depth, formation pressure coefficient, and fast S-wave azimuth. Triaxial geostress values ​​include: vertical principal stress, maximum horizontal principal stress, and minimum horizontal principal stress. Natural fracture occurrence includes: natural fracture dip angle, natural fracture azimuth angle, and natural fracture dip angle.

[0063] In S1, specifically:

[0064] 1) Based on array wave logging data from shale gas fractured wells, the steps for calculating the formation static Young's modulus, static Poisson's ratio, triaxial stress values, and maximum principal stress direction angle at the target casing deformation risk point of the shale gas fractured well include:

[0065] The P-wave transit time, S-wave transit time, and rock density are input into the first preset formula for calculation to obtain the static Young's modulus of the formation.

[0066] The first preset formula is: E is the static Young's modulus of the formation, in MPa; DEN is the rock density, in g / cm³. 3 DTS stands for longitudinal wave time difference, in µs / ft; DTC stands for transverse wave time difference, in µs / ft.

[0067] The longitudinal wave time difference and the transverse wave time difference are input into the second preset formula for calculation to obtain the static Poisson ratio.

[0068] The second preset formula is: v is the static Poisson's ratio, which is dimensionless.

[0069] The rock density and vertical depth are input into the third preset formula for calculation to obtain the vertical principal stress.

[0070] The third preset formula is: h is the vertical depth, in meters (m); σ² is the vertical principal stress, in MPa (MPa).

[0071] The vertical depth, static Poisson's ratio, and vertical principal stress are input into the fourth preset formula for calculation to obtain the maximum horizontal principal stress.

[0072] The fourth preset formula is: σ1 is the maximum horizontal principal stress, in MPa; P por Pore ​​pressure, in MPa; α p This is the formation pressure coefficient, which is dimensionless.

[0073] The static Poisson's ratio, vertical principal stress, and pore pressure are input into the fifth preset formula for calculation to obtain the minimum horizontal principal stress.

[0074] The fifth preset formula is: σ3 is the minimum horizontal principal stress, in MPa.

[0075] The fast shear wave azimuth FSA is used to determine the direction angle ω of the maximum principal stress in the formation, in degrees.

[0076] 2) The steps for determining the natural fracture orientation of target casing deformation risk points based on imaging logging data from shale gas fractured wells include:

[0077] The location of the trough in the imaging logging data is determined as the dip angle of the natural fracture.

[0078] Among them, the imaging logging data is microresistivity scanning image, such as Figure 3 As shown. Based on the microresistivity scanning image, the location of the natural fracture cutting into the casing is confirmed. The sine curve in the image represents the location of the target casing deformation risk point, and the trough position represents the natural fracture dip angle ε, in degrees.

[0079] The natural crack dip angle is input into the sixth preset formula for calculation to obtain the natural crack azimuth angle.

[0080] The sixth preset formula is: γ=ε±90; ε is the natural crack dip angle in degrees; γ is the natural crack azimuth angle in degrees.

[0081] The peak-to-trough spacing and borehole diameter from the imaging logging data are input into the seventh preset formula for calculation to obtain the natural fracture dip angle.

[0082] The seventh preset formula is: T is the crest-to-trough distance in cm; C is the borehole diameter in cm; β is the natural fracture dip angle in degrees.

[0083] S2. Based on the static Poisson's ratio, calculate the cohesion and internal friction coefficient of the natural fracture at the target risk point, and calculate the hydraulic fracture end pressure at the target risk point.

[0084] In S2, specifically:

[0085] 1) The steps for calculating the cohesion and internal friction coefficient of natural fractures at the target casing deformation risk point based on the static Poisson's ratio of the formation include:

[0086] Based on the eighth preset formula and according to the static Poisson's ratio, the cohesion of the natural cracks and the coefficient of internal friction at the target sheath risk point are calculated.

[0087] The eighth preset formula is: C w denoted as cohesion within natural cracks, in MPa; μ as coefficient of internal friction, dimensionless; SH as clay content, dimensionless (0-1).

[0088] 2) The steps for calculating the hydraulic fracture terminal pressure at the target risk point include:

[0089] Based on the ninth preset formula, the pressure at the end of the hydraulic fracture at the target risk point is calculated.

[0090] The ninth preset formula is: P = P head +0.01×hl×k; P is the pressure at the end of the hydraulic fracture, in MPa; P head The pressure at the wellhead is the normal value of the pumping pressure in the block, in MPa; l is the length of the tubing from the wellhead to the end of the perforated section in the fracturing well, in m; k is the friction coefficient at the highest operating flow rate, in MPa / m.

[0091] It should be noted that the data on the tubing length, friction coefficient, and vertical depth from the wellhead to the end of the perforated section of the fractured well are derived from the fracturing design scheme.

[0092] S3. Calculate the casing deformation safety factor of the target casing deformation risk point based on the direction angle of the maximum principal stress of the formation, the triaxial stress value, the orientation of natural fractures, the cohesion of natural fractures, the internal friction coefficient, and the pressure at the end of hydraulic fractures. Then, determine the casing deformation risk level of the target casing deformation risk point based on the magnitude of the casing deformation safety factor.

[0093] In S3, specifically:

[0094] 1) The steps for calculating the casing deformation safety factor of the target casing deformation risk point based on the direction angle of the maximum principal stress, triaxial stress values, natural fracture orientation, natural fracture cohesion, internal friction coefficient, and hydraulic fracture terminal pressure include:

[0095] Based on the tenth preset formula, and according to the direction angle of the maximum principal stress of the formation, the vertical principal stress, the maximum horizontal principal stress, the minimum horizontal principal stress, the dip angle of the natural fracture, the azimuth angle of the natural fracture, the dip angle of the natural fracture, the cohesion of the natural fracture, the internal friction coefficient, and the pressure at the end of the hydraulic fracture, the casing deformation safety factor of the target casing deformation risk point is calculated.

[0096] The tenth preset formula is:

[0097]

[0098] fa is the safety factor for the casing deformation, and ω is the direction angle of the maximum principal stress in the formation.

[0099] like Figure 4 As shown, △ABC is the fracture surface, OC is due north, OB is due east, OA is the vertical axis, OC' is the direction of maximum principal stress, OB' is the direction of minimum principal stress, OD⊥BC, EC⊥AB, EC'⊥AB'. ∠ECO, or θ, is the angle between the direction of maximum principal stress and the fracture surface. ∠ABO, or α, is the angle formed by the intersection of the plane containing the vertical stress and the plane containing the minimum horizontal stress with the fracture plane and the direction of the minimum horizontal stress. ∠ADO, or β, is the dip angle of the natural fracture. ∠COD, or γ, is the azimuth angle of the natural fracture, and ∠COC', or ω, is the direction angle of the maximum principal stress in the formation.

[0100] 2) The steps for determining the risk level of the target risk point based on the magnitude of the risk factor of the housing transfer include:

[0101] When the safety factor for the relocation transformer falls within a first preset range, the risk level is determined to be Level 1. When the safety factor falls within a second preset range, the risk level is determined to be Level 2. When the safety factor falls within a third preset range, the risk level is determined to be Level 3.

[0102] The first preset range is [1.5, +∞), the second preset range is [1.0, 1.5), and the third preset range is (-∞, 1.0).

[0103] To better illustrate the technical solution of this embodiment, the following examples are used for explanation:

[0104] The platform where the shale gas fracturing well is located lacks seismic data, making it impossible to determine the distribution of natural fractures through seismic analysis. Analysis of the well logging data revealed natural fractures across the wellbore at depths of 3688m, 3708m, and 3709m. Figure 5 A schematic diagram of natural fractures in a transverse wellbore is shown in the image logging. One fracture (3708m) has a natural fracture dip angle of 240 degrees, a natural fracture azimuth angle of 150 degrees, and a natural fracture dip angle of 82.06 degrees. Figure 6 This diagram shows the azimuth of the fast shear wave and the direction angle of the maximum principal stress in the formation at 100 degrees. Figure 7 The calculation results of array wave logging data are shown. Based on the array wave logging calculations, with the maximum principal stress direction at 100 degrees, the static Young's modulus E of the formation at 3708m is 19.76 MPa, the static Poisson's ratio v is 0.37, the vertical principal stress σ2 is 64.82 MPa, the maximum horizontal principal stress σ1 is 58.9 MPa, and the minimum horizontal principal stress σ3 is 45.4 MPa. The fracture cohesion C is calculated. w The pressure is 13.22 MPa, and the internal friction coefficient μ is -0.02. According to the formula for calculating the casing deformation coefficient, the casing deformation coefficient at 3708m is 1.6, indicating a high risk level (Level 1). For this section of fracturing, spray avoidance measures were implemented at 3708m, and the controlled fluid volume during construction was 1500 m³. 3 10m displacement 3 / min, no cascading changes were observed.

[0105] The technical solution of this embodiment is applicable to the prediction of casing deformation risk in shale oil and gas reservoirs. Compared with existing technologies, it eliminates the need for prior seismic data volume analysis, reducing technical costs. This invention analyzes natural fractures in the cut wellbore based on imaging logging data, resulting in more accurate judgment of fracture location and occurrence, which can guide precise avoidance of casing deformation risk locations during perforation operations. This invention calculates static Young's modulus and static Poisson's ratio, triaxial stress, direction of maximum principal stress, cohesion of natural fractures, and internal friction coefficient based on array sonic logging; the method is simple and highly accurate. The technical solution of this embodiment calculates the casing deformation safety factor based on the occurrence of natural fractures and the mechanical properties of the reservoir and natural fractures; the method is simple and highly accurate. The technical solution of this embodiment can effectively improve the accuracy of casing deformation prediction, assess the risk of fracturing schemes, provide a reliable reference for optimizing fracturing schemes, improve the success rate of fracturing operations, and reduce casing deformation risk.

[0106] Figure 8A schematic diagram of an embodiment of a shale gas fracturing well casing variation risk prediction system 200 provided by the present invention is shown. Figure 8 As shown, the system 200 includes: a first processing module 210, a second processing module 220, and a third processing module 230;

[0107] The first processing module 210 is used to: calculate the static Young's modulus, static Poisson's ratio, triaxial geostress value and maximum principal stress direction angle of the formation at the target casing deformation risk point of the shale gas fractured well based on the array wave logging data of the shale gas fractured well; and determine the natural fracture occurrence of the target casing deformation risk point based on the imaging logging data of the shale gas fractured well.

[0108] The second processing module 220 is used to: calculate the cohesion and internal friction coefficient of the natural fracture at the target sheathing risk point based on the static Poisson's ratio, and calculate the hydraulic fracture end pressure at the target sheathing risk point;

[0109] The third processing module 230 is used to: calculate the casing deformation safety factor of the target casing deformation risk point based on the maximum principal stress direction angle of the formation, the triaxial geostress value, the natural fracture orientation, the natural fracture cohesion, the internal friction coefficient and the hydraulic fracture end pressure, and determine the casing deformation risk level of the target casing deformation risk point based on the magnitude of the casing deformation safety factor.

[0110] In one optional approach, the array wave logging data includes: P-wave transit time, S-wave transit time, rock density, vertical depth, formation pressure coefficient, and fast S-wave azimuth; the triaxial stress values ​​include: vertical principal stress, maximum horizontal principal stress, and minimum horizontal principal stress; the steps in the first processing module 210, based on the array wave logging data from the shale gas fractured well, to calculate the formation static Young's modulus, static Poisson's ratio, triaxial stress values, and the direction angle of the maximum principal stress at the target casing deformation risk point of the shale gas fractured well, include:

[0111] The P-wave transit time, S-wave transit time, and rock density are input into a first preset formula for calculation to obtain the static Young's modulus of the formation; wherein, the first preset formula is: E is the static Young's modulus of the formation, DEN is the rock density, DTS is the P-wave transit time, and DTC is the S-wave transit time.

[0112] The P-wave time difference and S-wave time difference are input into the second preset formula for calculation to obtain the static Poisson ratio; wherein, the second preset formula is: v is the static Poisson's ratio;

[0113] The rock density and vertical depth are input into the third preset formula for calculation to obtain the vertical principal stress; the third preset formula is: h is the vertical depth, and σ2 is the vertical principal stress;

[0114] The vertical depth, static Poisson's ratio, and vertical principal stress are input into the fourth preset formula for calculation to obtain the maximum horizontal principal stress; wherein, the fourth preset formula is: σ1 is the maximum horizontal principal stress, P por For pore pressure, α p This is the formation pressure coefficient;

[0115] The static Poisson's ratio, vertical principal stress, and pore pressure are input into the fifth preset formula for calculation to obtain the minimum horizontal principal stress; wherein, the fifth preset formula is: σ3 is the minimum horizontal principal stress;

[0116] The azimuth of the fast shear wave is determined as the direction angle of the maximum principal stress in the formation.

[0117] In one alternative approach, the natural fracture occurrence includes: natural fracture dip angle, natural fracture azimuth angle, and natural fracture dip angle; the step in the first processing module 210 to determine the natural fracture occurrence of the target casing deformation risk point based on imaging logging data from a shale gas fractured well includes:

[0118] The location of the trough in the imaging logging data is determined as the dip angle of the natural fracture.

[0119] The dip angle of the natural crack is input into the sixth preset formula for calculation to obtain the azimuth angle of the natural crack; where the sixth preset formula is: γ=ε±90; ε is the dip angle of the natural crack, and γ is the azimuth angle of the natural crack;

[0120] The peak-to-trough spacing and borehole diameter from the imaging logging data are input into the seventh preset formula for calculation to obtain the natural fracture dip angle; wherein, the seventh preset formula is: T is the crest-to-trough distance, C is the borehole diameter, and β is the natural fracture dip angle.

[0121] In an alternative approach, the step in the second processing module 220 that calculates the cohesion of the natural cracks and the coefficient of internal friction at the target sheathing risk point based on the static Poisson's ratio includes:

[0122] Based on the eighth preset formula and according to the static Poisson's ratio, the cohesion of natural cracks and the coefficient of internal friction at the target sheathing risk point are calculated; wherein, the eighth preset formula is:

[0123] Cohesion within natural cracks, μ is the internal friction coefficient, and SH is the clay content.

[0124] In one alternative approach, the step of calculating the hydraulic fracture terminal pressure at the target risk point in the second processing module 220 includes:

[0125] Based on the ninth preset formula, the pressure at the end of the hydraulic fracture at the target risk point is calculated; where the ninth preset formula is: P = P head +0.01×hl×k; P is the pressure at the end of the hydraulic fracture, P head denoted as the wellhead pressure, l as the length of the tubing from the wellhead to the end of the perforated section in the fracturing well, and k as the friction coefficient at the maximum operating flow rate.

[0126] In one alternative approach, the step in the third processing module 230 that calculates the casing deformation safety factor of the target casing deformation risk point based on the maximum principal stress direction angle of the formation, triaxial stress values, natural fracture orientation, natural fracture cohesion, internal friction coefficient, and hydraulic fracture terminal pressure includes:

[0127] Based on the tenth preset formula, and according to the direction angle of the maximum principal stress, vertical principal stress, maximum horizontal principal stress, minimum horizontal principal stress, dip angle of natural fractures, azimuth angle of natural fractures, dip angle of natural fractures, cohesion of natural fractures, internal friction coefficient, and pressure at the end of hydraulic fractures, the casing deformation safety factor of the target casing deformation risk point is calculated; wherein, the tenth preset formula is:

[0128]

[0129] fa is the safety factor for the casing deformation, and ω is the direction angle of the maximum principal stress in the formation.

[0130] In one alternative approach, the step in the third processing module 230 of determining the risk level of the target risk point based on the magnitude of the relocation safety factor includes:

[0131] When the safety factor of the housing transformation is within the first preset range, the risk level of the housing transformation is determined to be Level 1.

[0132] When the safety factor of the housing transformation is within the second preset range, the risk level of the housing transformation is determined to be the second level;

[0133] When the safety factor of the housing transaction is within the third preset range, the risk level of the housing transaction is determined to be Level 3.

[0134] The technical solution of this embodiment can effectively improve the accuracy of risk prediction for shale gas fracturing wells, eliminate the need for prior seismic data volume analysis, and reduce technical costs; it also provides a reliable reference for optimizing fracturing schemes and improves the success rate of fracturing operations.

[0135] The parameters and steps for each module in the shale gas fracturing well casing deformation risk prediction system 200 described above can be referred to the parameters and steps in the embodiments of the shale gas fracturing well casing deformation risk prediction method above, and will not be repeated here.

[0136] like Figure 9 As shown, an electronic device 300 according to an embodiment of the present invention includes a processor 320 coupled to a memory 310. The memory 310 stores at least one computer program 330, which is loaded and executed by the processor 320 to enable the electronic device 300 to implement any of the above-mentioned shale gas fracturing well casing risk prediction methods. Specifically:

[0137] The electronic device 300 can vary considerably due to differences in configuration or performance. It may include one or more processors 320 (Central Processing Units, CPUs) and one or more memories 310. The memories 310 store at least one computer program 330, which is loaded and executed by the processors 320 to enable the electronic device 300 to implement any of the shale gas fracturing well casing deformation risk prediction methods provided in the above embodiments. Of course, the electronic device 300 may also have wired or wireless network interfaces, a keyboard, and input / output interfaces for input and output. It may also include other components for implementing device functions, which will not be elaborated upon here.

[0138] An embodiment of the present invention provides a computer-readable storage medium storing at least one computer program, which is loaded and executed by a processor to enable a computer to implement any of the above-mentioned shale gas fracturing well casing risk prediction methods.

[0139] Alternatively, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a read-only optical disc (CD-ROM), magnetic tape, a floppy disk, and an optical data storage device, etc.

[0140] In an exemplary embodiment, a computer program product or computer program is also provided, which includes computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the electronic device to perform any of the above-described shale gas fracturing well casing risk prediction methods.

[0141] It should be noted that the terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and represent a limitation on a specific order or sequence. Where appropriate, the order of use for similar objects can be interchanged so that the embodiments of this application described herein can be implemented in an order other than that shown or described.

[0142] Those skilled in the art will recognize that this invention can be implemented as a system, method, or computer program product. Therefore, this disclosure can be specifically implemented in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, this invention can also be implemented as a computer program product in one or more computer-readable media containing computer-readable program code.

[0143] Any combination of one or more computer-readable media can be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0144] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for predicting the risk of casing deformation in shale gas fracturing wells, characterized in that, include: Based on array wave logging data from shale gas fractured wells, the static Young's modulus, static Poisson's ratio, triaxial geostress values, and maximum principal stress direction angle of the formation at the target casing deformation risk point of the shale gas fractured well are calculated. Based on the imaging logging data from the shale gas fractured wells, the location and natural fracture occurrence of the target casing deformation risk point are determined. Based on the static Poisson's ratio, calculate the cohesion and internal friction coefficient of the natural fracture at the target sheathing risk point, and calculate the hydraulic fracture terminal pressure at the target sheathing risk point. Based on the maximum principal stress direction angle of the formation, the triaxial stress value, the natural fracture orientation, the natural fracture cohesion, the internal friction coefficient, and the hydraulic fracture terminal pressure, the casing deformation safety factor of the target casing deformation risk point is calculated, and the casing deformation risk level of the target casing deformation risk point is determined according to the magnitude of the casing deformation safety factor.

2. The method for predicting casing deformation risk in shale gas fracturing wells according to claim 1, characterized in that, The array wave logging data includes: P-wave transit time, S-wave transit time, rock density, vertical depth, formation pressure coefficient, and fast S-wave azimuth; the triaxial stress values ​​include: vertical principal stress, maximum horizontal principal stress, and minimum horizontal principal stress; based on the array wave logging data of the shale gas fractured well, the steps for calculating the formation static Young's modulus, static Poisson's ratio, triaxial stress values, and the direction angle of the maximum principal stress at the target casing deformation risk point of the shale gas fractured well include: The P-wave transit time, the S-wave transit time, and the rock density are input into a first preset formula for calculation to obtain the static Young's modulus of the formation; wherein, the first preset formula is: E is the static Young's modulus of the formation, DEN is the rock density, DTS is the P-wave transit time, and DTC is the S-wave transit time. The longitudinal wave time difference and the transverse wave time difference are input into a second preset formula for calculation to obtain the static Poisson's ratio; wherein, the second preset formula is: v is the static Poisson's ratio; The rock density and the vertical depth are input into a third preset formula for calculation to obtain the vertical principal stress; wherein, the third preset formula is: h is the vertical depth, and σ2 is the vertical principal stress; The vertical depth, the static Poisson's ratio, and the vertical principal stress are input into a fourth preset formula for calculation to obtain the maximum horizontal principal stress; wherein, the fourth preset formula is: σ1 is the maximum horizontal principal stress, P por For pore pressure, α p The formation pressure coefficient is mentioned above; The static Poisson's ratio, the vertical principal stress, and the pore pressure are input into a fifth preset formula for calculation to obtain the minimum horizontal principal stress; wherein, the fifth preset formula is: σ3 is the minimum horizontal principal stress; The azimuth of the fast shear wave is determined as the direction angle of the maximum principal stress of the formation.

3. The method for predicting casing deformation risk in shale gas fracturing wells according to claim 2, characterized in that, The occurrence of the natural fractures includes: the dip angle, azimuth angle, and dip angle of the natural fractures; the step of determining the occurrence of the natural fractures at the target casing deformation risk point based on the imaging logging data of the shale gas fractured well includes: The location of the trough in the imaging logging data is determined as the dip angle of the natural fracture. The dip angle of the natural crack is input into the sixth preset formula for calculation to obtain the azimuth angle of the natural crack; wherein, the sixth preset formula is: γ=ε±90; ε is the dip angle of the natural crack, and γ is the azimuth angle of the natural crack; The peak-to-trough spacing and borehole diameter from the imaging logging data are input into a seventh preset formula for calculation to obtain the natural fracture dip angle; wherein, the seventh preset formula is: T is the peak-to-trough distance, C is the borehole diameter, and β is the natural fracture inclination angle.

4. The method for predicting casing deformation risk in shale gas fracturing wells according to claim 3, characterized in that, The steps for calculating the cohesion and internal friction coefficient of the natural crack at the target sheathing risk point based on the static Poisson's ratio include: Based on the eighth preset formula and according to the static Poisson's ratio, the cohesion of the natural crack and the internal friction coefficient of the target sheathing risk point are calculated. The eighth preset formula is as follows: C w denoted as the cohesive force within the natural crack, μ as the internal friction coefficient, and SH as the clay content.

5. The method for predicting casing deformation risk in shale gas fracturing wells according to claim 4, characterized in that, The steps for calculating the hydraulic fracture terminal pressure at the target risk point include: Based on the ninth preset formula, the pressure at the end of the hydraulic fracture at the target risk point is calculated; wherein, the ninth preset formula is: P = P head +0.01×hl×k; P is the pressure at the end of the hydraulic fracture, P head denoted as the wellhead pressure, l as the length of the tubing from the wellhead to the end of the perforated section in the fracturing well, and k as the friction coefficient at the maximum operating flow rate.

6. The method for predicting casing deformation risk in shale gas fracturing wells according to claim 5, characterized in that, The steps for calculating the casing deformation safety factor of the target casing deformation risk point based on the maximum principal stress direction angle of the formation, the triaxial stress value, the natural fracture orientation, the natural fracture cohesion, the internal friction coefficient, and the hydraulic fracture terminal pressure include: Based on the tenth preset formula, and according to the maximum principal stress direction angle, the vertical principal stress, the maximum horizontal principal stress, the minimum horizontal principal stress, the dip angle of the natural fracture, the azimuth angle of the natural fracture, the dip angle of the natural fracture, the cohesion of the natural fracture, the internal friction coefficient, and the pressure at the end of the hydraulic fracture, the casing deformation safety factor of the target casing deformation risk point is calculated; wherein, the tenth preset formula is: fa is the safety factor of the casing deformation, and ω is the direction angle of the maximum principal stress of the formation.

7. The method for predicting casing deformation risk in shale gas fracturing wells according to any one of claims 1 to 6, characterized in that, The steps for determining the risk level of the target risk point based on the magnitude of the safety factor of the relocation transformer include: When the safety factor of the housing transformation is within a first preset range, the risk level of the housing transformation is determined to be the first level; When the safety factor of the housing transformation is within the second preset range, the risk level of the housing transformation is determined to be the second level; When the safety factor of the housing transformation is within a third preset range, the risk level of the housing transformation is determined to be level three.

8. A shale gas fracturing well casing variation risk prediction system, characterized in that, include: The first processing module, the second processing module, and the third processing module; The first processing module is used to: calculate the static Young's modulus, static Poisson's ratio, triaxial geostress value and maximum principal stress direction angle of the formation at the target nesting risk point of the shale gas fractured well based on the array wave logging data of the shale gas fractured well; and determine the natural fracture occurrence of the target nesting risk point based on the imaging logging data of the shale gas fractured well. The second processing module is used to: calculate the cohesion and internal friction coefficient of the natural fracture at the target sheathing risk point based on the static Poisson's ratio, and calculate the hydraulic fracture end pressure at the target sheathing risk point; The third processing module is used to: calculate the casing deformation safety factor of the target casing deformation risk point based on the maximum principal stress direction angle of the formation, the triaxial geostress value, the natural fracture occurrence, the natural fracture cohesion, the internal friction coefficient, and the hydraulic fracture end pressure, and determine the casing deformation risk level of the target casing deformation risk point based on the magnitude of the casing deformation safety factor.

9. An electronic device, characterized in that, The electronic device includes a processor coupled to a memory, the memory storing at least one computer program, which is loaded and executed by the processor to enable the electronic device to implement the shale gas fracturing well casing risk prediction method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one computer program, which is loaded and executed by a processor to enable the computer-readable storage medium to implement the shale gas fracturing well casing risk prediction method as described in any one of claims 1 to 7.

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