Oil field area modeling method fusing InSAR three-dimensional deformation and geophysical model

Abstract

The invention discloses an oil field area modeling method fusing InSAR three-dimensional deformation and a geophysical model, and belongs to the technical field of surface deformation monitoring and physical model inversion. The invention solves the problem of how to provide a method for obtaining the three-dimensional deformation of the oil field area on the premise of not abandoning the resolution and the precision. The method comprises the following steps: S1, selecting rail ascending and rail descending SAR observation data to obtain deformation components in the vertical direction and the east-west direction; s2, deformation components in the north-south direction are obtained; s3, taking the geophysical model fused with the orthogonal rectangular model as a physical inversion model, and introducing the physical inversion model into underground oil field nonlinear Bayesian physical parameter inversion; and S4, on the basis of taking the extracted vertical, east-west and north-south three-dimensional displacement fields of the oil field as inversion observed quantities, realizing modeling of three-dimensional deformation of the underground oil field by using a nonlinear Bayesian inversion method. According to the method, a favorable basis is provided for analyzing a multi-dimensional deformation mechanism and dynamic spatio-temporal evolution of the oil field.

Description

Technical Field

[0001] The present invention belongs to the technical field of surface deformation monitoring and physical model inversion, and particularly relates to an oilfield area modeling method that integrates InSAR three-dimensional deformation and geophysical models. Background Art

[0002] The surface deformation of underground oilfields is mainly caused by long-term underground oil and gas resource exploitation activities. During the exploitation process, the internal pressure of the underground reservoir gradually decreases and is presented in the form of reservoir compaction and surface deformation. (Interferometric Synthetic Aperture Radar, InSAR) With its advantages of large range, all-weather and all-time, and high efficiency, InSAR technology has also been used as the main means for large-scale surface deformation monitoring. Subsequently developed MT-InSAR technologies such as PS and SBAS effectively weaken the influence of spatio-temporal decorrelation and atmospheric delay, further improving the reliability and accuracy of InSAR monitoring, and also enhancing the ability of time-series analysis of surface deformation. However, at present, time-series InSAR technology can only obtain one-dimensional deformation along the radar line of sight, which is only the projection of the real deformation in the direction of the SAR satellite line of sight and cannot reflect the real surface deformation.

[0003] For the method of obtaining three-dimensional deformation, multi-aperture interferometry (MAI) and pixel offset tracking (POT) combine the monitoring results of different observation angles to fuse three-dimensional deformation. However, this method will greatly reduce the spatial resolution, and it is more suitable for large-gradient deformations such as earthquakes and glaciers, and does not meet the requirements of oilfield deformation monitoring. Therefore, a method for obtaining three-dimensional deformation in the oilfield area without sacrificing resolution and accuracy is needed. Summary of the Invention

[0004] Aiming at the problems in the prior art, the present invention provides an oilfield area modeling method that integrates InSAR three-dimensional deformation and geophysical models, and its purpose is to effectively obtain the three-dimensional surface deformation of the oilfield without sacrificing spatial resolution and accuracy, and to perform reservoir parameter inversion of the three-dimensional surface deformation of the oilfield by introducing a geophysical model that integrates an orthogonal rectangular model.

[0005] The technical solution adopted by the present invention is as follows: An oilfield area modeling method that integrates InSAR three-dimensional deformation and geophysical models, comprising the following steps: S1: Select ascending and descending orbit SAR observation data covering the oilfield area, and decompose the LOS line-of-sight deformation into vertical and east-west deformation components based on time-series InSAR technology and two-dimensional decomposition; S2: Assume a linear relationship between horizontal deformation and tilt slope, and utilize the spatial similarity between the vertical and east-west two-dimensional deformation fields and horizontal deformation to calculate and extract the deformation component in the north-south direction; S3: Use the geophysical model integrating the orthogonal rectangular model as the physical inversion model and introduce it into the non-linear Bayesian physical parameter inversion of the underground oilfield; S4: Take the extracted three-dimensional displacement fields in the vertical, east-west, and north-south directions of the oilfield (obtained from the deformation components in the vertical and east-west directions and the deformation component in the north-south direction) as the inversion observation quantities, introduce them into the parameter inversion of the physical inversion model, and use the non-linear Bayesian inversion method to realize the modeling of the three-dimensional deformation of the underground oilfield.

[0006] Preferably, the geophysical model integrating the orthogonal rectangular model in S3 includes three orthogonal rectangular dislocations.

[0007] Preferably, the three orthogonal rectangular dislocations are composed of the XYZ geocentric earth-fixed coordinate system and the xyz-axis Cartesian coordinate system.

[0008] Preferably, the specific steps of S1 include: S11: Select the SAR observation image data of ascending and descending orbits covering the oilfield area, and respectively obtain the unwrapped interferograms of the ascending and descending orbit data through differential interferometry processing; S12: Use the two-dimensional deformation decomposition method to geocode and resample the overlapping ascending and descending orbit unwrapped interferograms in time and space to the same size, and create a time matrix interpolation to achieve the unification of the spatial and time references; S13: Use singular value decomposition to obtain the two-dimensional deformation rate, and reconstruct the deformation time series through numerical integration of the deformation rate. During the solution process, introduce a regularization equation to eliminate the problem of rank deficiency of the design equation, and finally use singular value decomposition to solve the east-west deformation rate and the vertical deformation rate values of each pixel, and use the calculated deformation rate values to solve the east-west and vertical deformation time series through numerical integration to obtain the deformation components in the vertical and east-west directions.

[0009] Preferably, the specific steps of S2 are as follows: S21: In an approximately regular oilfield subsidence funnel, the horizontal displacement at the center of the subsidence funnel is approximately zero, and the horizontal displacement is the largest in the area with the largest tilt slope. Then the tilt slope is expressed as the first derivative of the vertical subsidence in the horizontal direction: (1) In the formula, d UD is the subsidence deformation amount in the vertical direction, and respectively represent the tilt slopes of the vertical deformation in the east - west and north - south directions, and respectively represent the spatial differentials along the east - west direction and the north - south direction;

[0010] Step S22: Since in an approximately regular oil - field subsidence funnel, the spatial variation characteristics are basically similar, the linear proportional relationship between the horizontal deformation and the tilt slope of the vertical deformation is used to represent the deformation components in the east - west and north - south directions: (2) In the formula, d EW represents the deformation component in the east - west direction, d NS represents the deformation component in the north - south direction, λ represents the linear proportionality factor.

[0011] The linear proportionality factor λ is related to the geophysical and geological characteristics of the reservoir overburden in the oil - field area. By combining the geophysical and geological characteristics of the oil - field location and according to the empirical rule, the approximate value of λ is defined: (3) In the formula, r is the radius of the subsidence funnel of the oil - field where it is located; Step S23: Calculate the tilt slopes of the vertical deformation in the east - west and north - south directions through the subsidence deformation amount d UD in the vertical direction, and divide the deformation component in the east - west direction by the tilt slope of the vertical deformation in the east - west direction to calculate the linear proportionality factor λ , and then obtain the deformation component in the north - south direction through the linear proportionality factor λ and the tilt slope of the vertical deformation in the north - south direction.

[0012] Preferably, in the non - linear Bayesian inversion software in S3, modify the inversion parameters of the geophysical model integrating the orthogonal rectangle model into the format recognizable by the non - linear Bayesian inversion to ensure that the non - linear Bayesian inversion software can correctly identify and invert.

[0013] Preferably, the specific steps of S4 are as follows: S41: Generate three groups of inversion observation values for non - linear Bayesian inversion from the three - dimensional deformation results of the vertical, east - west, and north - south directions of the oil - field. Each group of inversion observation values includes three columns of parameters: longitude, latitude, and deformation value corresponding to each deformation point; S42: Set the Poisson's ratio according to the prior information of the underground oilfield reservoir. Use the geophysical model integrating the orthogonal rectangular model as the physical model. Set the initial inversion parameters, and through iteration, make the reservoir parameters converge, and obtain the optimal fitting parameters.

[0014] In summary, due to the adoption of the above technical solutions, the beneficial effects of the present invention are as follows: 1. Through the linear hypothesis relationship between horizontal deformation and tilt slope, the present invention solves the north-south deformation by using the vertical and east-west deformations, and obtains the three-dimensional deformation result of the oilfield. Compared with the multi-aperture interferometry (MAI) and pixel offset tracking (POT) methods, the accuracy of the three-dimensional deformation result is effectively retained.

[0015] 2. The present invention mainly obtains the vertical and east-west deformation components through the ascending and descending orbit LOS-direction deformation observations, and then obtains the north-south deformation component based on the linear relationship hypothesis between horizontal and vertical deformations. This way of obtaining the three-dimensional deformation field is simpler and does not require introducing additional parameter information of underground oilfield fluids. In terms of the modeling inversion of underground oilfields, in the selection of the inversion model, the physical model we adopted has more inversion parameters and inversion capabilities, and can more comprehensively reflect the complex mapping relationship between underground reservoir parameters and surface deformations.

[0016] 3. The present invention introduces the geophysical model integrating the orthogonal rectangular model as the physical inversion model, and introduces the three-dimensional deformation field of the oilfield as the inversion observation value to realize the modeling of the three-dimensional deformation of the underground oilfield. At the same time, by introducing the parameter inversion of the three-dimensional deformation, the non-uniqueness in the inversion result is effectively improved, and the nonlinear inversion constraint is further increased. This method provides a favorable basis for analyzing the multi-dimensional deformation mechanism and dynamic spatio-temporal evolution of the oilfield. Our integrated orthogonal rectangular model consists of ten parameters, including the three-dimensional coordinates of the model centroid, the rotation angles in the three axis directions, the three semi-axes, and the opening amount. In terms of the number of model parameters, more model parameter constraints can more accurately model the underground reservoir. The model parameters we adopted can better constrain and map the underground reservoir. Compared with existing models, such as the mogi and ellipsoid models, due to the influence of their model mechanisms, there are still limitations in the degree of freedom of the rotation parameters. Even the okada model can only rotate in one direction and still lacks the rotation degree of freedom in the direction perpendicular to the free surface, which limits the applicability of existing models in complex geological environments. The model we adopted is composed of three orthogonal rectangular dislocations, which can represent any triaxial ellipsoidal shape and can theoretically simulate any shape in space and has complete rotational freedom. Therefore, its modeling inversion ability is better than that of the mogi, ellipsoid and other models. Description of the Drawings

[0017] Figure 1 is the flowchart of the method according to an embodiment of the present invention; Figure 2 is an example diagram of the change in the tilt slope of vertical deformation and horizontal deformation in the present invention; Figure 3 is an example diagram of the geophysical model integrating the orthogonal rectangle model in the present invention; Figure 4 is an example diagram of the unification of the time reference in the two-dimensional deformation decomposition in the present invention; Figure 5 is an example diagram of the three-dimensional deformation decomposition in the oilfield area in the present invention, where (a), (b), and (c) are the vertical, east-west, and north-south deformation result diagrams of the oilfield area respectively; Figure 6 is an example diagram of the modeling of the vertical integration of three-dimensional deformation and the fusion matrix model in the present invention, where (a), (b), and (c) are the observed deformation, inversion simulation deformation, and residual result diagrams in the vertical direction; Figure 7 is an example diagram of the modeling of the east-west integration of three-dimensional deformation and the fusion matrix model in the present invention, where (a), (b), and (c) are the observed deformation, inversion simulation deformation, and residual result diagrams in the east-west direction; Figure 8 is an example diagram of the modeling of the north-south integration of three-dimensional deformation and the fusion matrix model in the present invention, where (a), (b), and (c) are the observed deformation, inversion simulation deformation, and residual result diagrams in the north-south direction. Detailed implementation manners

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Usually, the components of the embodiments of the present application described and illustrated herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application to be protected, but only represents the selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts shall fall within the scope of protection of the present application.

[0019] As Figure 1 shown, a method for modeling an oilfield area by integrating InSAR three-dimensional deformation and a geophysical model includes the following steps: S1: Select ascending and descending orbit SAR observation data covering the oilfield area, and decompose the LOS line-of-sight deformation into vertical and east-west deformation components based on time series InSAR technology and two-dimensional decomposition; S2: Assume a linear relationship between horizontal deformation and tilt slope, and utilize the spatial similarity between the vertical and east-west two-dimensional deformation fields (obtained from the vertical and east-west deformation components decomposed according to S1) and the horizontal deformation to calculate and extract the north-south deformation component; S3: Introduce the geophysical model integrating the orthogonal rectangular model as a physical inversion model into the nonlinear Bayesian physical parameter inversion of the underground oilfield; S4: Use the extracted three-dimensional deformation fields in the vertical, east-west, and north-south directions of the oilfield as inversion observables, introduce them into the parameter inversion of the physical inversion model, and use the nonlinear Bayesian inversion method to realize the modeling of the three-dimensional deformation of the underground oilfield.

[0020] In one embodiment, the geophysical model integrating the orthogonal rectangular model in S3 includes three orthogonal rectangular dislocations. Specifically, as Figure 3 shown, the geophysical model integrating the orthogonal rectangular model consists of three orthogonal rectangular dislocations formed by the XYZ geocentric earth-fixed coordinate system and the xyz-axis Cartesian coordinate system. Figure 3 In, A, B, and C respectively represent the three orthogonal rectangular dislocation planes A, B, and C. The origin of the earth-fixed Cartesian coordinate system of the XYZ axis is located on the earth's surface. X, Y, and Z respectively represent the X-axis, Y-axis, and Z-axis, and the positive directions of the X-axis, Y-axis, and Z-axis point east, north, and upward respectively; in the Cartesian coordinate axes of the xyz axis, x, y, and z respectively represent the x-axis, y-axis, and z-axis, and the x-axis, y-axis, and z-axis are respectively perpendicular to the three orthogonal rectangular dislocation planes A, B, and C. This model includes a total of 10 model parameters, namely the east coordinate X0, north coordinate Y0, and depth -d of the model centroid, the length a of the model semi-axis along the x-axis 、 the length b along the y-axis, the length c along the z-axis, the angle ωX of clockwise rotation around the X-axis, the angle ωY of clockwise rotation around the Y-axis 、 the angle of clockwise rotation around the Z-axis and the opening amount u (the opening amount u is not shown in Figure 3 ). By setting the semi-axes and rotation postures of the rectangular dislocations of the model with high degrees of freedom, it is theoretically possible to simulate any direction in space, and can represent the oilfield reservoir parameters at more angles, which is more in line with the mapping relationship between the underground reservoir parameters and the surface deformation.

[0021] In one embodiment, the specific steps of S1 include: S11: Select the SAR observation image data of the ascending and descending orbits covering the oilfield area, and respectively obtain the unwrapped interferograms of the ascending and descending orbit data through differential interferometry processing. In this embodiment, the ascending and descending orbit Sentinel-1 SAR data from January 2021 to December 2021 are used, and an oilfield production area in the Liaohe Oilfield is selected as the research area; S12: The unwrapped interferograms of ascending and descending orbits that overlap in time and space are decomposed by a two-dimensional deformation decomposition method, geocoded and resampled to the same size, and a time matrix interpolation is created to unify the spatial and temporal benchmarks. An example of the temporal unification is as follows Figure 4 , assuming that both the ascending and descending orbit datasets consist of 4 SAR images, and the ascending orbit SAR images are acquired at times t -1 , t2, t4, and t5, and the descending orbit SAR images are acquired at times t0, t1, t3, and t6. Δt1 - Δt5 are the 5 time intervals between adjacent ascending and descending orbit acquisitions. The horizontal solid lines between two points represent the interferograms (as shown by I1 - I6 in Figure 4 ; I1 - I6 represent 6 interferograms respectively); for the acquisition time t -1 of the first ascending orbit SAR image, which is earlier than the acquisition time t0 of the first descending orbit SAR image, i.e., the first ascending orbit interferogram (as shown by I1 in ) is compensated by a factor of Figure 4 , and similarly, the last descending orbit interferogram (as shown by I6 in ) is compensated by a factor of Figure 4 . After boundary correction, it can be considered that the ascending and descending orbit data are both acquired simultaneously at times t0 and t5, and finally the temporal benchmark is unified; S13: Singular value decomposition is used to obtain the two-dimensional deformation rate, and the deformation time series is reconstructed by numerically integrating the deformation rate. During the solution process, a regularization equation is introduced to eliminate the rank deficiency problem of the design equation. Finally, singular value decomposition is used to solve the east-west and vertical deformation rates of each pixel , and the east-west and vertical deformation time series are solved by numerical integration using the calculated deformation rate values to obtain the vertical and east-west deformation components;

[0022] In one embodiment, the specific steps of S2 are as follows: S21: As shown in Figure 2 , in an approximately regular oilfield subsidence funnel, the horizontal displacement at the center of the subsidence funnel is approximately zero, and the horizontal displacement is the largest in the area with the largest slope. Then the slope is expressed as the first derivative of the vertical subsidence in the horizontal direction: (1) where d UD is the subsidence deformation amount in the vertical direction, and represent the slopes of the vertical deformation in the east-west and north-south directions respectively, and represent the spatial differentials along the east-west and north-south directions respectively.

[0023] Step S22: Since the spatial variation characteristics are basically similar in the oilfield subsidence funnel with approximate rules, the deformation components in the east-west and north-south directions are represented by the linear proportional relationship between the horizontal deformation and the inclination slope of the vertical deformation: (2) In the formula, d EW represents the deformation component in the east-west direction, d NS represents the deformation component in the north-south direction, λ represents the linear proportionality factor.

[0024] Linear proportionality factor λ is related to the geophysical and geological characteristics of the reservoir overburden in the oilfield area. By combining the geophysical and geological characteristics of the oilfield location and defining the approximate value of λ according to the empirical rule: (3) In the formula, r is the radius of the subsidence funnel of the oilfield where it is located; Step S23: Calculate the inclination slopes of the vertical deformation in the east-west and north-south directions through the subsidence deformation amount d UD in the vertical direction, and divide the deformation component in the east-west direction by the inclination slope of the vertical deformation in the east-west direction to calculate the linear proportionality factor λ . Then, obtain the deformation component in the north-south direction through the linear proportionality factor λ and the inclination slope of the vertical deformation in the north-south direction. Specifically: First, based on the vertical and east-west deformation components obtained in S13, use the first-order derivative of the vertical deformation component in the east-west horizontal direction in formula (1) to calculate the inclination slope of the vertical deformation in the east-west direction and the inclination slope of the vertical deformation in the north-south direction. Then, use the deformation component d EW in the east-west direction obtained in S13 and the inclination slope of the vertical deformation in the east-west direction to calculate the value of the linear proportionality factor λ based on formula (2). Finally, based on the calculated linear proportionality factor λ and the inclination slope of the vertical deformation in the north-south direction, perform the estimation calculation to finally calculate the deformation component in the north-south direction.

[0025] Finally, the three-dimensional deformation fields in the vertical, east-west, and north-south directions of the oilfield area are completely obtained. See Figure 5For (a), (b), and (c), it can be seen from the extracted three-dimensional field results that the oilfield area is a typical circular settlement bowl caused by oil production. The maximum vertical settlement rate exceeds 220 mm / yr. The three-dimensional deformation field also shows a centripetal deformation trend towards the center of the settlement bowl, and the deformation in the horizontal direction is the smallest at the center of the settlement bowl and the most significant at the outer edge of the settlement bowl.

[0026] In one embodiment, in the non-linear Bayesian inversion software in S3, the inversion parameters of the geophysical model integrating the orthogonal rectangular model are modified into a format recognizable by the non-linear Bayesian inversion to ensure that the non-linear Bayesian inversion software can correctly identify and invert.

[0027] In one embodiment, the specific steps of S4 are as follows: S41: Generate three groups of inversion observation values for non-linear Bayesian inversion from the three-dimensional deformation results in the vertical, east-west, and north-south directions of the oilfield. Each group of inversion observation values includes three columns of parameters: longitude, latitude, and deformation value corresponding to each deformation point. The deformation value needs to be converted. Based on the deformation value and the wavelength parameter of the Sentinel-1 satellite, the deformation value is converted into a phase value in meters. S42: According to the prior information of the underground oilfield reservoir, set the Poisson's ratio to 0.25. Use the geophysical model integrating the orthogonal rectangular model as the physical model, use the Bayesian inversion algorithm to search for the optimal parameters, and set a predefined search range for each parameter. For example, set the model length to 100 to 1000 meters and the width to 10 to 50 meters. After 1 million iterations (too few iterations will cause the inversion result to not fit well, resulting in a poor inversion effect, and too many iterations will increase the inversion time and reduce the inversion efficiency. Therefore, in the inversion of reservoir parameters, 1 million iterations are selected as the inversion iteration times to ensure the best fitting effect), the reservoir parameters reach convergence, and the optimal fitting parameters are obtained. The final modeling results are as Figures 6 - 8 shown, where Figure 6 in (a) Figure 7 in (a) Figure 8 in (a) respectively show the original simulated three-dimensional deformations in the vertical, east-west, and north-south directions. Figure 6 in (b) Figure 7 in (b) Figure 8 in (b) are respectively the three-dimensional deformations in the vertical, east-west, and north-south directions obtained by inversion. Figure 6 in (c) Figure 7 in (c) Figure 8Among them, (c) are the residuals between the three-dimensional deformations of the original simulations in the vertical, east-west, and north-south directions and the three-dimensional deformations obtained by inversion. It can be seen that the overall trends of the three-dimensional deformations of the original simulations and the three-dimensional deformations obtained by inversion are consistent. The overall values of the residual results tend to be 0 and conform to the normal distribution, indicating that the three-dimensional deformation inversion and modeling method of the present invention is effective.

[0028] The above-described embodiments only represent the specific implementation manners of the present application, and the description thereof is relatively specific and detailed. However, it should not be construed as a limitation to the protection scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the technical solution of the present application, several deformations and improvements can still be made, and these all belong to the protection scope of the present application.

Claims

1. A modeling method for oilfield areas that integrates InSAR three-dimensional deformation and geophysical models, characterized in that: It includes the following steps: S1: Select ascending and descending orbit SAR observation data covering the oilfield area, and decompose the deformation in the LOS line-of-sight direction into vertical and east-west deformation components based on time-series InSAR technology and two-dimensional decomposition; S2: Assume a linear relationship between horizontal deformation and tilt slope, and use the spatial feature similarity between the two-dimensional vertical and east-west deformation fields and horizontal deformation to solve and extract the north-south deformation component; S3: Introduce the geophysical model integrating the orthogonal rectangular model as a physical inversion model into the nonlinear Bayesian physical parameter inversion of the underground oilfield; S4: Use the extracted three-dimensional deformation fields in the vertical, east-west, and north-south directions of the oilfield as inversion observables, introduce them into the parameter inversion of the physical inversion model, and use the nonlinear Bayesian inversion method to realize the modeling of the three-dimensional deformation of the underground oilfield.

2. The oilfield area modeling method integrating InSAR three-dimensional deformation and geophysical model according to claim 1, characterized in that: The geophysical model integrating the orthogonal rectangular model in S3 includes three orthogonal rectangular dislocations.

3. A method for modeling an oilfield area that integrates InSAR three-dimensional deformation and geophysical models according to claim 2, characterized in that: The three orthogonal rectangular dislocations are composed of the XYZ geocentric earth-fixed coordinate system and the xyz-axis Cartesian coordinate system.

4. A method for modeling an oilfield area that integrates InSAR three-dimensional deformation and geophysical models, according to any one of claims 1-3, characterized in that: The specific steps of S1 include: S11: Select ascending and descending orbit SAR observation image data covering the oilfield area, and obtain the unwrapped interferograms of the ascending and descending orbit data respectively through differential interferometry processing; S12: Use the two-dimensional deformation decomposition method to geocode and resample the overlapping ascending and descending orbit unwrapped interferograms in time and space to the same size, and create a time matrix interpolation to achieve the unification of the spatial and time references; S13: Use singular value decomposition to obtain the two-dimensional deformation rate, and reconstruct the deformation time series by numerically integrating the deformation rate. During the solution process, introduce a regularization equation to eliminate the rank deficiency problem of the design equation. Finally, use singular value decomposition to solve the east-west deformation rate of each pixel. and the vertical deformation rate values, and use the calculated deformation rate values to numerically integrate and solve the east-west and vertical deformation time series to obtain the vertical and east-west deformation components.

5. A method for modeling an oilfield area that integrates InSAR three-dimensional deformation and a geophysical model, according to any one of claims 1-3, characterized in that: The specific steps of S2 are as follows: S21: In an approximately regular oilfield subsidence funnel, the horizontal displacement at the center of the subsidence funnel is approximately zero, and the horizontal displacement is the largest in the area with the largest tilt slope. Then the tilt slope is expressed as the first derivative of the vertical subsidence in the horizontal direction: (1) In the formula, d UD is the settlement deformation quantity in the vertical direction, and respectively represent the tilt slopes of the vertical deformation in the east-west and north-south directions, and respectively represent the spatial differentials along the east-west and north-south directions; Step S22: Since the spatial variation characteristics are basically similar in an approximately regular oilfield subsidence funnel, the deformation components in the east-west and north-south directions are represented by the linear proportional relationship between the horizontal deformation and the tilt slope of the vertical deformation: (2) In the formula, d EW represents the east-west deformation component, d NS represents the north-south deformation component, λ represents the linear scale factor; Linear scale factor λ Relates to the geophysical and geological characteristics of the reservoir cover in the oil field area. By combining the geophysical and geological characteristics of the oil field and defining according to the rule of thumb λ The approximate value of: (3) In the formula, r is the radius of the drawdown funnel of the oilfield where it is located; Step S23: Based on the settlement deformation amount in the vertical direction d UD Calculate the tilt slopes of the vertical deformation in the east-west direction and the north-south direction, and divide the east-west deformation component by the tilt slope of the vertical deformation in the east-west direction to calculate the linear scale factor λ , and then through the linear scale factor λ and the tilt slope of the vertical deformation in the north-south direction, obtain the north-south deformation component.

6. A method for modeling an oilfield area that integrates InSAR three-dimensional deformation and a geophysical model, according to any one of claims 1-3, characterized in that: In S3, in the nonlinear Bayesian inversion software, modify the inversion parameters of the geophysical model integrating the orthogonal rectangular model into a format recognizable by the nonlinear Bayesian inversion to ensure that the nonlinear Bayesian inversion software can correctly identify and invert.

7. A method for modeling an oilfield area that integrates InSAR three-dimensional deformation and geophysical models, according to any one of claims 1 to 3, characterized in that: The specific steps of S4 are as follows: S41: Generate three groups of inversion observations for the nonlinear Bayesian inversion from the three-dimensional deformation results in the vertical, east-west, and north-south directions of the oilfield. Each group of inversion observations includes three columns of parameters: longitude, latitude, and deformation value corresponding to each deformation point; S42: According to the prior information of the underground oilfield reservoir, set the Poisson's ratio, use the geophysical model integrating the orthogonal rectangular model as the physical model, set the initial inversion parameters, and make the reservoir parameters converge after iteration to obtain the optimal fitting parameters.

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