A method for predicting risk sections of casing deformation of horizontal wells by multi-source information fusion

Abstract

The present application belongs to the technical field of shale oil and gas development, and specifically discloses a method for predicting casing deformation risk section of horizontal well based on multi-source information fusion, comprising: representing wellbore fracture zone information; establishing a structure model and an attribute model of the working area; perturbing the fracture information predicted based on seismic data with the wellbore fracture zone information as a constraint, and establishing a three-dimensional fracture network model; establishing a geomechanics model of the working area to obtain the ground stress distribution characteristics along the horizontal wellbore direction; combining the casing mechanics attribute data and the fracturing construction parameters of the working area to establish a comprehensive casing deformation database of the working area, and obtaining the fracture zone activity factor based on the Mohr-Coulomb criterion; establishing a formation-fracture-wellbore model to obtain the mathematical model of the fracture zone activity factor and the casing deformation degree, and dividing the casing deformation risk level. The present application can realize accurate identification of the wellbore fracture network, and can predict the wellbore fracture activation risk and the casing deformation in advance, thereby providing guidance for the development of targeted casing deformation prevention and control measures.

Description

Technical Field

[0001] The present invention belongs to the technical field of shale oil and gas development, and in particular relates to a method for predicting a horizontal well casing change risk section by fusing multi-source information. Background Art

[0002] my country boasts abundant deep shale gas resources. However, influenced by multiple phases of tectonic movement, faults are generally multi-scale, multi-phase, and complex. Furthermore, deep burial causes the maximum horizontal principal stress in the target strata to be greater than the vertical principal stress, resulting in a strike-slip / compressional stress state. This stress state and complex fault system create the potential for casing deformation triggered by fracturing activation.

[0003] In recent years, extensive research has been conducted both domestically and internationally on casing deformation risk prediction technologies. It is generally believed that fault-activated slip is the primary cause of casing deformation. Therefore, accurate identification of peri-well fractures and their integration with engineering are key to predicting casing deformation. However, current research has largely focused on more accurate calculation of casing forces while ignoring the fundamental factor influencing casing deformation—accurate identification of fractures. This results in missing or erroneous data sources and inaccurate casing deformation prediction results. For example, patent application document CN115907197A, entitled "Method and Apparatus for Predicting Shear Deformation Risk of Horizontal Well Casing in Shale Gas Development," published on April 4, 2023, describes a method and apparatus for predicting shear deformation risk of horizontal well casing in shale gas development. This method uses the intersection of a three-dimensional fault-crack data volume as a casing deformation risk point and, combined with geomechanical and fracture occurrence data as input, determines the risk level of the casing deformation risk point. However, this patent only uses fracture distribution information as basic data input and does not provide a method for obtaining this fracture distribution information. The patent application document entitled "Method for Determining the Location of Fracturing-Induced Oil and Gas Casing Deformation Using Geostress Field Simulation" and published on November 11, 2022, with publication number CN115324560A, provides a method for determining the location of fracturing-induced oil and gas casing deformation using geostress field simulation. In this method, natural fracture data is primarily obtained from earthquake and microseismic event points. The detailed geostress field of the block is used as input data for subsequent fracturing and casing deformation simulation to predict the location of fracturing-induced oil and gas casing deformation. Seismic data is easily interfered with by geological factors and its predicted fracture scale is large. Using this result as input to predict the casing deformation area will inevitably lead to large errors.

[0004] Currently, accurate prediction of casing deformation risk requires careful preliminary geological work and further consideration of factors influencing casing deformation, such as drilling, cementing, and fracturing. Therefore, it is necessary to develop a comprehensive evaluation process based on the integration of geology and engineering. This will provide insights and references for addressing casing deformation issues encountered in deep energy development. Summary of the Invention

[0005] In response to the above-mentioned problems, the purpose of the present invention is to provide a method for predicting the casing change risk section of a horizontal well by fusing multi-source information, which can accurately predict the location and level of the wellbore risk section in a shale gas well, and provide guidance for the formulation of targeted casing change prevention and control measures.

[0006] The technical solution of the present invention is: a method for predicting the risk section of horizontal well casing change by multi-source information fusion, comprising the following steps:

[0007] Obtain drilling and logging parameters of the horizontal section of the target well, casing mechanical property data and fracturing operation parameters of the work area, seismic data of the work area, well location data, layer data, logging data and rock mechanics data.

[0008] The rock breaking energy of the drill bit while drilling is calculated based on the drilling and logging parameters of the horizontal section of the target well, the fracture weakness index of the horizontal well section is evaluated, and the information of the wellbore fracture zone is characterized.

[0009] Based on the well-seismic fusion method and the seismic data, well location data, layer data, logging data and rock mechanics data of the work area, the structural model and attribute model of the work area are established.

[0010] Using the wellbore fracture zone information as a constraint, the fracture information predicted based on seismic data is disturbed to establish a three-dimensional fracture network model.

[0011] A geomechanical model of the work area was established by integrating the structural model, attribute model and three-dimensional fracture network model to obtain the distribution characteristics of the ground stress along the horizontal wellbore direction.

[0012] Based on the three-dimensional fracture network model and ground stress distribution characteristics, combined with the casing mechanical property data and the fracturing operation parameters of the work area, a comprehensive casing deformation database of the work area was established, and the fault zone activity factor was obtained based on the Mohr-Coulomb criterion.

[0013] Based on the finite element method, a formation-fault-wellbore model was established. The fault slip calculated by the total fracture surface slip model was used as the load condition. The casing deformation was calculated and analyzed, and a mathematical model of the fault zone activity factor and the casing deformation degree was obtained to classify the casing deformation risk level.

[0014] Furthermore, the crack weakness index is calculated according to the following formula, and the smaller the value of the crack weakness index is, the more developed the cracks are.

[0015] ;in, Represents the crack weakness index, dimensionless; It represents the mechanical specific energy ratio, dimensionless; It represents the minimum value of mechanical specific energy ratio and is dimensionless; It represents the maximum value of mechanical specific energy ratio and is dimensionless.

[0016] Furthermore, the mechanical specific energy ratio is calculated according to the following formula.

[0017] ;in, , represents mechanical specific energy, MPa; Indicates the mechanical specific energy value corresponding to the mechanical specific energy trend line, MPa; Indicates bit pressure, N; Indicates torque, N·m; Indicates the turntable speed, r / min; Indicates the drill diameter, mm; Indicates drilling speed, m / h.

[0018] Furthermore, based on the fracture weakness index, the base value lines of the fracture development stratum and the matrix stratum are obtained, and the following comparative mathematical model of the fracture development stratum and the matrix stratum is established to characterize the wellbore fracture zone information.

[0019] when When When When the cracks are not developed, Indicates the base value line of the fracture development formation, Indicates the matrix stratum base value line.

[0020] Furthermore, the specific steps of establishing the structural model are: taking seismic data as the core, combining geological stratification to correct the layer structure, establishing the layer model of each layer, and finally completing the structural model.

[0021] The specific steps of establishing the attribute model are: on the basis of constructing the model, discretizing the logging data, performing data analysis and variogram fitting on the discretized data, and establishing the attribute model within the platform using the Kriging interpolation method.

[0022] Furthermore, the specific steps for establishing the three-dimensional fracture network model are as follows: based on the ant body tracking method of the seismic data body, with the wellbore fracture zone information as a constraint, and combining the single well imaging research results and core observation results, a matching relationship between the ant body and the wellbore fracture density is established, and according to the natural fracture density attributes of the well area, a three-dimensional fracture network model is established.

[0023] Furthermore, the specific steps for establishing the geomechanical model of the work area are:

[0024] Based on the structural model and property model of the work area, a one-dimensional mechanical calculation process is adopted to calibrate the one-dimensional mechanical calculation results with the measured formation pressure data and core mechanical test data.

[0025] Based on the three-dimensional rock mechanics data of seismic interpretation and with reference to the one-dimensional rock mechanics results, a three-dimensional rock mechanics model of the work area is established.

[0026] The imaging logging data of single wells in the work area were collected, and the current stress dominant direction around the wellbore was determined based on the wellbore collapse and induced fracture development characteristics interpreted by imaging.

[0027] Based on the finite element numerical simulation method and combined with the dominant stress orientation of the wellbore, a geomechanical model of the work area was established.

[0028] Furthermore, based on the geomechanical model of the work area, the three-dimensional principal stress distribution characteristics of the three-dimensional work area, namely the magnitude and direction of the maximum principal stress, the intermediate principal stress and the minimum principal stress, are obtained; combined with the wellbore trajectory of the target well, the ground stress distribution characteristics can be obtained.

[0029] Furthermore, the fault zone activity factor is determined according to the following formula.

[0030] ;in, , represents the fault zone activity factor, The larger the value, the higher the risk of fault activity; Represents the fracture activation risk, dimensionless; represents the minimum value of the fracture activation risk, represents the maximum value of the fracture activation risk; represents the original formation pressure, MPa; It represents the pore stress at the time of fracture activation, MPa.

[0031] Furthermore, the pore stress at the time of fracture activation is determined according to the following formula.

[0032] .

[0033] ,in, The change in formation pore pressure due to fault activation instability, represents the maximum principal stress, represents the minimum principal stress, represents the fracture approach angle, that is, the angle between the fracture and the maximum principal stress, It represents the friction coefficient of the fracture surface, ranging from 0.6 to 1.0.

[0034] Compared with the existing technology, the beneficial effect of the present invention is that the prediction method proposed in the present invention integrates drilling, logging, seismic, logging and fracturing, which can realize the accurate identification of the peri-well fracture network and the advance prediction of the risk of peri-well fracture activation and wellbore casing variables, providing guidance for the formulation of targeted casing variation prevention and control measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a schematic diagram of the overall structure of the present invention;

[0036] Figure 2 This is a calculation curve of mechanical specific energy of a well in an application example of the present invention;

[0037] Figure 3 、 Figure 4 This is a model for determining the base value line of the matrix stratum and the fracture development stratum in the application example of the present invention; wherein, Figure 3 Determine the model for the matrix stratum base line, Figure 4 Determine the model for the base line of fracture development formation;

[0038] Figure 5 This is a cross-sectional attribute diagram of a wellbore fracture prediction in an application example of the present invention;

[0039] Figure 6 This is a distribution diagram of the fracture zone along the wellbore of an application example of the present invention;

[0040] Figure 7 This is a schematic diagram of the fracture activation risk in a work area of ​​an application example of the present invention;

[0041] Figure 8 This is an application example of the present invention, the formation-fault-wellbore coupling numerical model

[0042] Figure 9 This is a relationship diagram between the fault slip amount and the casing deformation amount in an application example of the present invention;

[0043] Figure 10 yes Figure 8 A partial enlarged view of . DETAILED DESCRIPTION

[0044] The following combination Figures 1 to 10 , the specific embodiments of the present invention are described in detail. In the description of the present invention, it should be understood that the terms "center", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings and are only used to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or components referred to must have a specific direction, be constructed or operate in a specific direction, and therefore should not be understood as limiting the present invention.

[0045] The terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the quantity of the technical features indicated. Therefore, features specified as "first" or "second" may explicitly or implicitly include one or more of such features; in the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0046] Example

[0047] like Figure 1 The method for predicting the risk section of casing change in a horizontal well by fusion of multi-source information shown in the figure includes the following steps:

[0048] Obtain drilling and logging parameters of the horizontal section of the target well, casing mechanical property data and fracturing operation parameters of the work area, seismic data of the work area, well location data, layer data, logging data and rock mechanics data.

[0049] The rock breaking energy of the drill bit while drilling is calculated based on the drilling and logging parameters of the horizontal section of the target well, the fracture weakness index of the horizontal well section is evaluated, and the information of the wellbore fracture zone is characterized.

[0050] Based on the well-seismic fusion method and the seismic data, well location data, layer data, logging data and rock mechanics data of the work area, the structural model and attribute model of the work area are established.

[0051] Using the wellbore fracture zone information as a constraint, the fracture information predicted based on seismic data is disturbed to establish a three-dimensional fracture network model.

[0052] A geomechanical model of the work area was established by integrating the structural model, attribute model and three-dimensional fracture network model to obtain the distribution characteristics of the ground stress along the horizontal wellbore direction.

[0053] Based on the three-dimensional fracture network model and ground stress distribution characteristics, combined with the casing mechanical property data and the fracturing operation parameters of the work area, a comprehensive casing deformation database of the work area was established, and the fault zone activity factor was obtained based on the Mohr-Coulomb criterion.

[0054] Based on the finite element method, a formation-fault-wellbore model was established. The fault slip calculated by the total fracture surface slip model was used as the load condition. The casing deformation was calculated and analyzed, and a mathematical model of the fault zone activity factor and the casing deformation degree was obtained to classify the casing deformation risk level.

[0055] Preferably, the crack weakness index is calculated according to the following formula, and the smaller the value of the crack weakness index is, the more developed the cracks are.

[0056] ;in, Represents the crack weakness index, dimensionless; It represents the mechanical specific energy ratio, dimensionless; It represents the minimum value of mechanical specific energy ratio and is dimensionless; It represents the maximum value of mechanical specific energy ratio and is dimensionless.

[0057] Preferably, the mechanical specific energy ratio is calculated according to the following formula.

[0058] ;in, , represents mechanical specific energy, MPa; Indicates the mechanical specific energy value corresponding to the mechanical specific energy trend line, MPa; Indicates bit pressure, N; Indicates torque, N·m; Indicates the turntable speed, r / min; Indicates the drill diameter, mm; Indicates drilling speed, m / h.

[0059] Preferably, based on the fracture weakness index, base value lines of the fracture development stratum and the matrix stratum are obtained, and the following comparative mathematical model of the fracture development stratum and the matrix stratum is established to characterize the wellbore fracture zone information.

[0060] when When When When the cracks are not developed, Indicates the base value line of the fracture development formation, Indicates the matrix stratum base value line.

[0061] Preferably, the specific steps of establishing the structural model are: taking seismic data as the core, combining geological stratification to correct the layer structure, establishing layer models of each layer, and finally completing the structural model.

[0062] The specific steps of establishing the attribute model are as follows: on the basis of constructing the model, the attribute model is established by discretizing the logging data, performing data analysis and variogram fitting on the discretized data, and using the Kriging interpolation method within the platform.

[0063] Preferably, the specific steps for establishing a three-dimensional fracture network model are: using the wellbore fracture zone information as a constraint, combining the single well imaging research results and core observation results, establishing a matching relationship between the ant body and the wellbore fracture density, and establishing a three-dimensional fracture network model based on the natural fracture density attributes of the well area.

[0064] Preferably, the specific steps for establishing a geomechanical model for the work area are as follows: Based on the structural model and property model, a one-dimensional mechanical calculation process is used to calibrate the one-dimensional mechanical calculation results using measured formation pressure data and core mechanical test data. A three-dimensional rock mechanical model of the work area is established based on the three-dimensional rock mechanical data volume from seismic interpretation and with the one-dimensional rock mechanical results as a reference. Well imaging logging data for individual wells in the work area is collected, and the current dominant stress orientation around the wellbore is determined based on the wellbore collapse and induced fracture development characteristics revealed by the imaging interpretation. A geomechanical model of the work area is established using finite element numerical simulation methods, incorporating the dominant stress orientation of the wellbore.

[0065] Preferably, the step of obtaining the geostress distribution characteristics comprises: obtaining the three-dimensional principal stress distribution characteristics of the three-dimensional work area based on the geomechanical model of the work area, namely, the magnitude and direction of the maximum principal stress, the intermediate principal stress, and the minimum principal stress. In combination with the target wellbore trajectory, the geostress distribution characteristics are obtained.

[0066] Preferably, the fault zone activity factor is determined according to the following formula.

[0067] ;in, , represents the fault zone activity factor, The larger the value, the higher the risk of fault activity; Represents the fracture activation risk, dimensionless; represents the minimum value of the fracture activation risk, represents the maximum value of the fracture activation risk; represents the original formation pressure, MPa; It represents the pore stress at the time of fracture activation, MPa.

[0068] Preferably, the pore stress at the time of fracture activation is determined according to the following formula.

[0069] .

[0070] ,in, The change in formation pore pressure due to fault activation instability, represents the maximum principal stress, represents the minimum principal stress, represents the fracture approach angle, that is, the angle between the fracture and the maximum principal stress, It represents the friction coefficient of the fracture surface, ranging from 0.6 to 1.0.

[0071] Application Examples

[0072] The Wufeng-Longmaxi Formation in the Luzhou area of ​​the southern Sichuan Basin, with a burial depth exceeding 3,500 meters, is the primary stratum for shale gas development. A typical work area was selected as an example. Due to the influence of multiple phases of tectonic movement, reservoir fractures and cracks are well developed, and tectonic stress concentration is significant. This area is highly susceptible to external stress disturbances, which can trigger fault movement and cause casing deformation. The prediction method proposed in the above embodiment is then used to predict the risk of casing deformation in horizontal wells in this area, specifically including the following steps:

[0073] Step 1: Collect drilling and logging parameters of the horizontal section of the target well, including torque, rotary table speed, drill bit diameter, drilling speed, and bit pressure, calculate the drill bit's rock-breaking energy while drilling, i.e., mechanical specific energy, evaluate the fracture weakness index of the horizontal well section, and characterize the drillability of the reservoir rock.

[0074] The formula for calculating mechanical specific energy is as follows:

[0075] ,in, represents mechanical specific energy, MPa; Indicates bit pressure, N; Indicates torque, N·m; Indicates the turntable speed, r / min; Indicates the drill diameter, mm; Indicates drilling speed, m / h.

[0076] Considering the difference in drilling engineering parameters, the mechanical specific energy is induced to be different, resulting in poor comparability of mechanical specific energy in reflecting formation physical properties. Therefore, a mechanical specific energy trend line is calculated for the values ​​on the same wellbore, and the mechanical specific energy value corresponding to the mechanical specific energy trend line is Here, the calculated mechanical specific energy is compared with the trend line mechanical specific energy value to obtain the mechanical specific energy ratio ,Right now .

[0077] Then, the mechanical specific energy ratio along the wellbore is normalized using the range normalization method to obtain the fracture weakness index. , The larger the value, the more developed the cracks.

[0078] ,in, Represents the crack weakness index, dimensionless; It represents the mechanical specific energy ratio, dimensionless; It represents the minimum value of mechanical specific energy ratio and is dimensionless; It represents the maximum value of mechanical specific energy ratio and is dimensionless.

[0079] Finally, based on the finite element numerical simulation method, the Figure 3 、 Figure 4 The mathematical model of the fracture development formation and matrix formation is shown. Based on the above mechanical specific energy-based fracture weakness index calculation model, the base value lines of the fracture development formation and matrix formation are obtained, where the base value line of the fracture development formation is , the matrix stratum base line is .when When When When the fracture is not developed, it is considered that the matrix is ​​dominant. The fracture weakness index prediction result of a typical well in the target area is as follows: Figure 5 As shown in the figure, the distribution of the fault zone along the wellbore is shown in the figure Figure 6 shown.

[0080] Step 2: Using a well-seismic fusion approach, we collected seismic data, well location data, layer data, logging data, and rock mechanics data from the work area to establish a structural model and attribute model for the work area. The structural model is centered on seismic data, combined with geological layering to correct the layer structure, and then construct layer models for each sublayer, ultimately completing the structural model. The attribute model is constructed based on the structural model by discretizing the logging data, performing data analysis and variogram fitting on the discretized data, and using kriging interpolation within the platform.

[0081] Step 3: Using wellbore fracture zone information as a constraint, combined with the results of single-well imaging studies and core observations, a matching relationship between ant bodies and uphole fracture density is established. Based on the natural fracture density properties of the wellbore area, a three-dimensional fracture network model is constructed. Previous modeling efforts often relied on basic fracture data, primarily imaging logging data, core observation data, and microseismic data. These data are scarce and expensive to obtain, resulting in inaccurate fracture modeling. Here, we introduce wellbore fracture zone data based on drilling and seismic data, significantly supplementing the deficiencies in existing basic data. Using the seismic data volume-based ant body tracking method, using wellbore fracture zone information as a constraint, combined with the results of single-well imaging studies and core observations, a matching relationship between ant bodies and uphole fracture density is established. Based on the natural fracture density properties of the wellbore area, a three-dimensional fracture network model is constructed.

[0082] Step 4: Based on the structural model and property model of the work area, the classical one-dimensional mechanical calculation process is adopted, and the one-dimensional mechanical calculation results are calibrated with the measured formation pressure data and core mechanical test data; based on the three-dimensional rock mechanical data volume interpreted from seismic interpretation and with the one-dimensional rock mechanical results as a reference, a three-dimensional rock mechanical model of the work area is established; imaging logging data of single wells in the work area are collected, and the current dominant stress orientation around the wellbore is determined based on the wellbore collapse and induced fracture development characteristics interpreted from imaging; based on the finite element numerical simulation method and combined with the dominant stress orientation of the wellbore, a geomechanical model of the work area is established.

[0083] Based on the geomechanical model of the work area, the three-dimensional principal stress distribution characteristics of the three-dimensional work area, namely the magnitude and direction of the maximum principal stress, the intermediate principal stress and the minimum principal stress, are obtained; combined with the target wellbore trajectory, the ground stress distribution characteristics can be obtained.

[0084] Step 5: Based on the three-dimensional fracture network model and the distribution characteristics of ground stress, combined with the casing mechanical property data and the fracturing operation parameters of the work area, a comprehensive casing variation database of the work area is established, and the fault zone activity factor is obtained based on the Mohr-Coulomb criterion.

[0085] In the original formation, the stress state around the target well can be determined based on the results of step 4. , intermediate principal stress and minimum principal stress , original formation pressure At this time, the formation is in a stable state, that is, the shear stress on the wellbore is balanced with the shear strength. As the fracturing construction progresses, the fluid is continuously injected into the formation to break the formation balance, causing the formation to slide, and then causing the casing to deform. The fracture risk activation chart of this work area is as follows Figure 7 shown.

[0086] The change in formation pore pressure for judging fault activation and instability is: ,but ,in, The change in formation pore pressure due to fault activation instability, represents the maximum principal stress, represents the minimum principal stress, represents the original formation pressure, represents the fracture approach angle, that is, the angle between the fracture and the maximum principal stress, It represents the friction coefficient of the fracture surface, ranging from 0.6 to 1.0.

[0087] Here we define the fault zone activity factor as The fault activity factor is the comparison between the original formation pore pressure and the formation pore pressure when the fault is activated. It is a normalized coefficient. The larger the value, the higher the risk of fault activity. ,in, , , represents the fault zone activity factor, The larger the value, the higher the risk of fault activity; Represents the fracture activation risk, dimensionless; represents the minimum value of the fracture activation risk, represents the maximum value of the fracture activation risk; represents the original formation pressure, MPa; It represents the pore stress at the time of fracture activation, MPa.

[0088] Step 6: Based on the finite element method, a formation-fault-wellbore model is established. The fault slip calculated by the total amount of fracture surface slip model is used as the load condition to calculate and analyze the casing deformation. The mathematical model of the fault zone activity factor and casing deformation degree is obtained to classify the casing deformation risk level. The model size parameter settings are as follows: Figure 8 As shown in the figure, the external formation length is 6m, the wellbore diameter is 215.9mm, the casing outer diameter is 139.7mm, and the casing wall thickness is 12.7mm. At the same time, in order to reduce the boundary effect, the formation cross-section size is set to be no less than 5 times the wellbore. The angle between the fracture and the casing is 72.45° based on the fracture results. Based on the model calculation results, the following can be obtained: Figure 9The relationship between fault slip and casing deformation is shown in the figure. It can be seen that the fault slip and casing deformation have a good linear correlation, with a correlation coefficient R2 of 0.998. Therefore, the casing deformation can be calculated based on the fault slip, and ultimately the casing deformation grade can be obtained.

[0089] The casing change grade is mainly determined based on the change in casing inner diameter. The original casing inner diameter in the study area is 114.3 mm. According to the casing inner diameter, the casing change grade can be divided into three levels: A, B, and C. Among them, the inner diameter of the casing of level A is greater than 85 mm, and the risk level is the lowest. The inner diameter of the casing of level B is 54 mm to 85 mm, and the risk level is medium. The inner diameter of the casing of level C is less than 54 mm, and the risk level is the highest.

[0090] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific embodiments of the present invention and do not limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are included in the scope of protection of the present invention.

Claims

1. A method for predicting risk sections of horizontal well casing changes based on multi-source information fusion, characterized in that: The following steps are involved: Obtain drilling and logging parameters of the horizontal section of the target well, casing mechanical property data and fracturing operation parameters of the work area, seismic data of the work area, well location data, layer data, logging data and rock mechanics data; Calculate the drill bit's rock-breaking energy while drilling based on the drilling and logging parameters of the target well's horizontal section, evaluate the fracture weakness index of the horizontal well section, and characterize the wellbore fracture zone information; Based on the well-seismic fusion method and the seismic data, well location data, layer data, logging data and rock mechanics data of the work area, the structural model and attribute model of the work area are established; Using the wellbore fracture zone information as a constraint, the fracture information predicted based on seismic data is disturbed to establish a three-dimensional fracture network model; A geomechanical model of the work area was established by integrating the structural model, attribute model, and 3D fracture network model to obtain the distribution characteristics of ground stress along the horizontal wellbore direction; Based on the three-dimensional fracture network model and the distribution characteristics of ground stress, combined with the casing mechanical property data and the fracturing operation parameters of the work area, a comprehensive casing deformation database of the work area was established, and the fault zone activity factor was obtained based on the Mohr-Coulomb criterion. Based on the finite element method, a formation-fault-wellbore model was established. The fault slip calculated by the total fracture surface slip model was used as the load condition. The casing deformation was calculated and analyzed, and a mathematical model of the fault zone activity factor and the casing deformation degree was obtained to classify the casing deformation risk level.

2. The method for predicting the risk section of horizontal well casing change based on multi-source information fusion according to claim 1, characterized in that: The crack weakness index is calculated according to the following formula. The smaller the value of the crack weakness index, the more developed the cracks are. ； in, Represents the crack weakness index, dimensionless; It represents the mechanical specific energy ratio, dimensionless; It represents the minimum value of mechanical specific energy ratio and is dimensionless; It represents the maximum value of mechanical specific energy ratio and is dimensionless.

3. The method for predicting the risk section of horizontal well casing change based on multi-source information fusion according to claim 2, characterized in that: The mechanical specific energy ratio is calculated according to the following formula: ； in, , represents mechanical specific energy, MPa; Indicates the mechanical specific energy value corresponding to the mechanical specific energy trend line, MPa; Indicates bit pressure, N; Indicates torque, N·m; Indicates the turntable speed, r / min; Indicates the drill diameter, mm; Indicates drilling speed, m / h.

4. The method for predicting the risk section of horizontal well casing change based on multi-source information fusion according to claim 2, characterized in that: Based on the fracture weakness index, the base value lines of the fracture development stratum and the matrix stratum are obtained, and the following comparative mathematical model of the fracture development stratum and the matrix stratum is established to characterize the wellbore fracture zone information; when When , it is considered that cracks develop; when When , the cracks are considered moderately developed; when When , it is considered that the cracks are not developed; in, Indicates the base value line of the fracture development formation, Indicates the matrix stratum base value line.

5. The method for predicting the risk section of horizontal well casing change based on multi-source information fusion according to claim 1, characterized in that: The specific steps of establishing the structural model are: taking seismic data as the core, combining geological stratification to correct the layer structure, establishing the layer model of each layer, and finally completing the structural model; The specific steps of establishing the attribute model are: on the basis of constructing the model, discretizing the logging data, performing data analysis and variogram fitting on the discretized data, and establishing the attribute model within the platform using the Kriging interpolation method.

6. The method for predicting the risk section of horizontal well casing change based on multi-source information fusion according to claim 1, characterized in that: The specific steps of establishing the three-dimensional fracture network model are: Using the wellbore fracture zone information as a constraint, combined with the results of single well imaging research and core observation, a matching relationship between the ant body and the wellbore fracture density is established, and a three-dimensional fracture network model is established based on the natural fracture density attributes of the well area.

7. The method for predicting the risk section of horizontal well casing change based on multi-source information fusion according to claim 1, characterized in that: The specific steps for establishing the geomechanical model of the work area are: Based on the structural model and property model, a one-dimensional mechanical calculation process is adopted to calibrate the one-dimensional mechanical calculation results with measured formation pressure data and core mechanical test data; Based on the 3D rock mechanics data of seismic interpretation and with reference to the 1D rock mechanics results, a 3D rock mechanics model of the work area is established; Collect imaging logging data from single wells in the work area and use the wellbore collapse and induced fracture development characteristics interpreted by imaging to determine the current stress dominant direction around the wellbore; Based on the finite element numerical simulation method and combined with the dominant stress orientation of the wellbore, a geomechanical model of the work area was established.

8. The method for predicting the risk section of horizontal well casing change based on multi-source information fusion according to claim 7, characterized in that: The steps of obtaining the in-situ stress distribution characteristics are as follows: Based on the geomechanical model of the work area, the three-dimensional principal stress distribution characteristics of the three-dimensional work area, namely the magnitude and direction of the maximum principal stress, the intermediate principal stress and the minimum principal stress, are obtained; Combined with the target wellbore trajectory, the ground stress distribution characteristics are obtained.

9. The method for predicting the risk section of horizontal well casing change based on multi-source information fusion according to claim 8, characterized in that: The fault zone activity factor is determined according to the following formula: ； in, , represents the fault zone activity factor, The larger the value, the higher the risk of fault activity; Represents the fracture activation risk, dimensionless; represents the minimum value of the fracture activation risk, represents the maximum value of the fracture activation risk; represents the original formation pressure, MPa; It represents the pore stress at the time of fracture activation, MPa.

10. The method for predicting risk sections of horizontal well casing changes based on multi-source information fusion according to claim 9, characterized in that: The pore stress at the time of fracture activation is determined according to the following formula: ； ； in, The change in formation pore pressure due to fault activation instability, represents the maximum principal stress, represents the minimum principal stress, represents the original formation pressure, represents the fracture approach angle, that is, the angle between the fracture and the maximum principal stress, It represents the friction coefficient of the fracture surface, ranging from 0.6 to 1.0.

Images