A method for oilfield modeling integrating InSAR 3D deformation and geophysical model

Abstract

The present invention discloses a method for modeling an oilfield area by integrating InSAR three-dimensional deformation and a geophysical model, belonging to the technical field of surface deformation monitoring and physical model inversion. The present invention solves the problem of how to provide a method for acquiring three-dimensional deformation of an oilfield area without sacrificing resolution and accuracy. The present invention comprises the following steps: S1: selecting ascending and descending SAR observation data to obtain vertical and east-west deformation components; S2: obtaining north-south deformation components; S3: using the geophysical model integrating the orthogonal rectangular model as a physical inversion model, and introducing it into the nonlinear Bayesian physical parameter inversion of the underground oilfield; S4: using the extracted vertical, east-west, and north-south three-dimensional displacement fields of the oilfield as inversion observations, and utilizing a nonlinear Bayesian inversion method to achieve modeling of the three-dimensional deformation of the underground oilfield. The present invention provides a favorable basis for analyzing the multi-dimensional deformation mechanism and dynamic spatiotemporal evolution of the oilfield.

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 integrating InSAR three-dimensional deformation and geophysical model. Background Art

[0002] Surface deformation in underground oilfields is primarily caused by long-term oil and gas extraction. This process gradually reduces the internal pressure of the underground reservoir, manifesting itself as reservoir compaction and surface deformation. Interferometric Synthetic Aperture Radar (InSAR) technology, with its advantages of wide coverage, all-weather coverage, and high efficiency, has become a primary means of measuring large-scale surface deformation. Subsequent developments in multi-dimensional (MT-InSAR) technologies, such as PS and SBAS, have effectively mitigated the effects of spatiotemporal incoherence and atmospheric delay, further improving the reliability and accuracy of InSAR monitoring and enhancing the time-series analysis of surface deformation. However, current time-series InSAR technology only captures one-dimensional deformation along the radar's line of sight. This is simply a projection of the actual deformation onto the SAR satellite's line of sight and fails to capture the true surface deformation.

[0003] Regarding the acquisition of 3D deformation, multi-aperture interferometry (MAI) and pixel offset tracking (POT) combine monitoring results from different observation angles to fuse 3D deformation. However, this method significantly reduces spatial resolution and is more suitable for large-gradient deformations such as earthquakes and glaciers, but does not meet the needs of oilfield deformation monitoring. Therefore, a method for acquiring 3D deformation in oilfield areas without sacrificing resolution and accuracy is needed. Summary of the Invention

[0004] In response to the problems in the prior art, the present invention provides an oilfield area modeling method that integrates InSAR three-dimensional deformation and geophysical models. Its purpose is to effectively obtain the three-dimensional surface deformation of the oilfield without sacrificing spatial resolution and accuracy, and to invert the reservoir parameters 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 in the present invention is as follows:

[0006] A method for modeling an oilfield area by integrating InSAR three-dimensional deformation and geophysical model, comprising the following steps:

[0007] S1: Select ascending and descending 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;

[0008] S2: By assuming a linear relationship between horizontal deformation and slope, and using the spatial similarity between the vertical and east-west two-dimensional deformation fields and the horizontal deformation, the north-south deformation component is extracted.

[0009] S3: The geophysical model integrated with the orthogonal rectangular model is used as a physical inversion model and introduced into the nonlinear Bayesian physical parameter inversion of underground oil fields;

[0010] S4: The extracted three-dimensional displacement fields of the oil field in the vertical, east-west, and north-south directions (obtained based on the vertical and east-west deformation components and the north-south deformation components) are used as inversion observations and introduced into the parameter inversion of the physical inversion model. The nonlinear Bayesian inversion method is then used to model the three-dimensional deformation of the underground oil field.

[0011] Preferably, the geophysical model integrated with the orthogonal rectangular model in S3 includes three orthogonal rectangular dislocations.

[0012] Preferably, the three orthogonal rectangular dislocations are composed of an XYZ Earth-centered Earth-fixed coordinate system and an xyz-axis Cartesian coordinate system.

[0013] Preferably, the specific steps of S1 include:

[0014] S11: Select ascending and descending SAR observation image data covering the oilfield area, and obtain disentangled interferograms of the ascending and descending data respectively through differential interferometry processing;

[0015] S12: Unwrap the interferograms of ascending and descending orbits that overlap in time and space using a two-dimensional deformation decomposition method, geocode and resample to the same size, and create a time matrix interpolation to unify the spatial and temporal references.

[0016] S13: Use singular value decomposition to obtain the two-dimensional deformation rate, and reconstruct the deformation time series by numerically integrating the deformation rate. In the solution process, the rank deficiency problem of the design equation is eliminated by introducing a regularization equation. Finally, singular value decomposition is used to solve the east-west deformation rate of each pixel. and vertical deformation rate The calculated deformation rate values are used to solve the east-west and vertical deformation time series through numerical integration to obtain the vertical and east-west deformation components.

[0017] Preferably, the specific steps of S2 are as follows:

[0018] S21: In an approximately regular oilfield settlement funnel, the horizontal displacement at the center of the settlement funnel is approximately zero, and the horizontal displacement is the largest in the area with the largest slope. The slope is then expressed as the first-order derivative of the vertical settlement in the horizontal direction:

[0019] (1)

[0020] Where, d UD is the vertical settlement deformation, and Represent the vertical deformation in the east-west and north-south directions, and represent the spatial differentials along the east-west direction and along the north-south direction respectively;

[0021] Step S22: Since the spatial variation characteristics are basically similar in the approximately regular oilfield subsidence funnel, the linear proportional relationship between the slope of the horizontal deformation and the vertical deformation is used to represent the deformation components in the east-west and north-south directions:

[0022] (2)

[0023] Where, d EW represents the east-west deformation component, d NS represents the north-south deformation component, λ Represents the linear scale factor.

[0024] Linear scale factor λ It is related to the geophysical and geological characteristics of the reservoir cover in the oil field area. It is defined by combining the geophysical and geological characteristics of the oil field and based on empirical rules. λ Approximate value of :

[0025] (3)

[0026] Where, r is the radius of the sedimentation funnel of the oil field;

[0027] Step S23: The vertical displacement d UD Calculate the inclination slope of the vertical deformation in the east-west and north-south directions, and divide the east-west deformation component by the inclination slope of the vertical deformation in the east-west direction to calculate the linear scaling factor λ , and then through the linear scaling factor λ The north-south deformation component is obtained by summing the north-south slope of the vertical deformation.

[0028] Preferably, in S3, in the nonlinear Bayesian inversion software, the inversion parameters of the geophysical model of the fused orthogonal rectangular model are modified into a format recognizable by the nonlinear Bayesian inversion, ensuring that the nonlinear Bayesian inversion software can correctly identify and invert.

[0029] Preferably, the specific steps of S4 are as follows:

[0030] S41: generating three sets of inversion observation values for nonlinear Bayesian inversion using the three-dimensional deformation results of the oil field in the vertical direction, the east-west direction, and the north-south direction, respectively, wherein each set of inversion observation values includes three columns of parameters, namely, the longitude, the latitude, and the deformation value corresponding to each deformation point;

[0031] S42: Based on the prior information of the underground oil field reservoir, the Poisson's ratio is set, and the geophysical model of the fused orthogonal rectangular model is used as the physical model. After setting the initial inversion parameters and iterating, the reservoir parameters are converged and the optimal fitting parameters are obtained.

[0032] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0033] 1. By assuming a linear relationship between horizontal deformation and slope, this method uses vertical and east-west deformation to solve north-south deformation and obtain three-dimensional deformation results of the oil field. Compared with multi-aperture interferometry (MAI) and pixel offset tracking (POT) methods, the accuracy of the three-dimensional deformation results is effectively preserved.

[0034] 2. This invention primarily obtains vertical and east-west deformation components through LOS deformation observations on the ascending and descending orbits, and then obtains north-south deformation components based on the assumption of a linear relationship between horizontal and vertical deformations. This method of acquiring a three-dimensional deformation field is simpler and does not require the introduction of additional parameter information for underground oilfield fluids. Regarding underground oilfield modeling and inversion, the physical model we use has more inversion parameters and inversion capabilities, and can more comprehensively reflect the complex mapping relationship between underground reservoir parameters and surface deformation.

[0035] 3. The present invention introduces a geophysical model that integrates an orthogonal rectangular model as a physical inversion model, and introduces the three-dimensional deformation field of the oil field as an inversion observation value to achieve modeling of the three-dimensional deformation of the underground oil field. At the same time, by introducing parameter inversion of the three-dimensional deformation, the non-uniqueness in the inversion results is effectively improved, and nonlinear inversion constraints are further added. This method provides a favorable basis for analyzing the multi-dimensional deformation mechanism and dynamic spatiotemporal evolution of the oil field. Our integrated orthogonal rectangular model consists of ten parameters, including the three-dimensional coordinates of the model's center of mass, rotation angles in three axis directions, 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 use can better constrain and map the underground reservoir. Compared with existing models, such as mogi and ellipsoid models, which are affected by their model mechanisms, there are still limitations in the freedom of rotation parameters. Even the okada model can only rotate in one direction, and still lacks rotational freedom in the direction perpendicular to the free surface. This makes the applicability of existing models in complex geological environments subject to certain restrictions. The model we use is composed of three orthogonal rectangular dislocations, which can represent any three-axis ellipsoid shape. In theory, it can simulate the shape of any direction in space and has complete rotational freedom. Therefore, it will be better than mogi, ellipsoid and other models in modeling and inversion capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a flow chart of a method according to an embodiment of the present invention;

[0037] Figure 2 This is an example diagram of the change in the slope of vertical deformation and horizontal deformation in the present invention;

[0038] Figure 3 is an example diagram of the geophysical model fused with the orthogonal rectangular model in the present invention;

[0039] Figure 4 This is an example diagram of a unified time base in the two-dimensional deformation decomposition of the present invention;

[0040] Figure 5 This is an example diagram of the three-dimensional deformation decomposition of the oil field area in the present invention, where (a), (b), and (c) are the vertical, east-west, and north-south deformation result diagrams of the oil field area, respectively;

[0041] Figure 6 This is an example diagram of the modeling of the vertical fusion 3D deformation and fusion matrix model in the present invention, where (a), (b), and (c) are the vertical observed deformation, inversion simulation deformation, and residual result diagrams;

[0042] Figure 7Figure 1 is an example of modeling the east-west fused 3D deformation and fused matrix model in the present invention, where (a), (b), and (c) are the east-west observed deformation, inversion simulation deformation, and residual result diagrams;

[0043] Figure 8 This is an example diagram of the modeling of the north-south fused three-dimensional deformation and fusion matrix model in the present invention, where (a), (b), and (c) are the north-south observed deformation, inversion simulation deformation, and residual result diagrams. DETAILED DESCRIPTION

[0044] In order to make the purpose, 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 in conjunction with the 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. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application.

[0045] like Figure 1 As shown, a method for modeling an oilfield area by integrating InSAR three-dimensional deformation and geophysical model includes the following steps:

[0046] S1: Select ascending and descending 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;

[0047] S2: Based on the assumption of a linear relationship between horizontal deformation and slope, the north-south deformation component is extracted by using the spatial similarity between the vertical and east-west two-dimensional deformation fields (obtained from the vertical and east-west deformation components decomposed by S1) and the horizontal deformation;

[0048] S3: The geophysical model integrated with the orthogonal rectangular model is used as a physical inversion model and introduced into the nonlinear Bayesian physical parameter inversion of underground oil fields;

[0049] S4: The extracted three-dimensional deformation fields of the oil field in the vertical, east-west, and north-south directions are used as inversion observations and introduced into the parameter inversion of the physical inversion model. The nonlinear Bayesian inversion method is used to realize the modeling of the three-dimensional deformation of the underground oil field.

[0050] In one embodiment, the geophysical model of the orthogonal rectangular model in S3 includes three orthogonal rectangular dislocations. Figure 3 As shown in the figure, the geophysical model of the integrated orthogonal rectangular model consists of three orthogonal rectangular dislocations composed of the XYZ Earth-centered Earth-fixed coordinate system and the xyz axis Cartesian coordinate system. Figure 3 A, B, and C represent the three orthogonal rectangular dislocation planes A, B, and C respectively. The origin of the earth-fixed Cartesian coordinate system of the XYZ axis is located on the surface of the earth. X, Y, and Z represent the X-axis, Y-axis, and Z-axis respectively, and the positive directions of the X-axis, Y-axis, and Z-axis point to the east, north, and up respectively. In the Cartesian coordinate axis of the xyz axis, x, y, and z represent the x-axis, y-axis, and z-axis respectively, and the x-axis, y-axis, and z-axis are perpendicular to the three orthogonal rectangular dislocation planes A, B, and C respectively. The model includes a total of 10 model parameters, namely the east coordinate X0, north coordinate Y0, 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 the model rotated clockwise around the X-axis, and the angle ωY of the model rotated clockwise around the Y-axis 、 Angle of clockwise rotation around the Z axis and the opening u (the opening u is Figure 3 By setting the model's rectangular dislocation semi-axis and rotational posture with high degrees of freedom, it is theoretically possible to simulate any direction in space and represent oilfield reservoir parameters from more angles, which is more consistent with the mapping relationship between underground reservoir parameters and surface deformation.

[0051] In one embodiment, the specific steps of S1 include:

[0052] S11: Select ascending and descending SAR observation image data covering the oilfield area, and obtain disentangled interferograms of the ascending and descending data respectively through differential interferometry. In this embodiment, ascending and descending 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 study area;

[0053] S12: Unwrap the interferogram of ascending and descending orbits that overlap in time and space by using a two-dimensional deformation decomposition method, geocode and resample to the same size, and create a time matrix interpolation to unify the spatial and temporal bases. For example, the time unification is as follows: Figure 4 , assuming that both the ascending and descending datasets consist of 4 SAR images, and at time t -1 , t2, t4 and t5, and the descending SAR images are acquired at time t0, t1, t3 and t6. Δt1-Δt5 are the five time intervals of the adjacent ascending and descending orbits, respectively. The horizontal solid line between two points represents the interferogram (e.g. Figure 4 As shown in I1-I6, I1-I6 represent 6 interferograms respectively); for the acquisition time t of the first ascending SAR image-1 Earlier than the acquisition time t0 of the first descending SAR image, The factor compensation of the first ascending interferogram (such as Figure 4 As shown in I1 in the figure), the same is true with Factor compensation of the last descending interferogram (e.g. Figure 4 As shown in I6 in the figure), after boundary correction, it can be assumed that the ascending and descending data are collected simultaneously at time t0 and t5, ultimately achieving the unification of the time base;

[0054] S13: Use singular value decomposition to obtain the two-dimensional deformation rate, and reconstruct the deformation time series by numerically integrating the deformation rate. In the solution process, the rank deficiency problem of the design equation is eliminated by introducing a regularization equation. Finally, singular value decomposition is used to solve the east-west deformation rate of each pixel. and vertical deformation rate The calculated deformation rate value is used to solve the deformation time series in the east-west and vertical directions through numerical integration to obtain the deformation components in the vertical and east-west directions.

[0055] In one embodiment, the specific steps of S2 are as follows:

[0056] S21: If Figure 2 As shown in the figure, in an approximately regular oilfield settlement funnel, the horizontal displacement at the center of the settlement funnel is approximately zero, and the horizontal displacement is the largest in the area with the largest slope. The slope is expressed as the first-order derivative of the vertical settlement in the horizontal direction:

[0057] (1)

[0058] Where, d UD is the vertical settlement deformation, and Represent the vertical deformation in the east-west and north-south directions, and represent the spatial differentials along the east-west direction and along the north-south direction, respectively.

[0059] Step S22: Since the spatial variation characteristics of the approximately regular oilfield subsidence funnel are basically similar, the linear proportional relationship between the slope of the horizontal deformation and the vertical deformation is used to represent the deformation components in the east-west and north-south directions:

[0060] (2)

[0061] Where, d EW represents the east-west deformation component, d NSrepresents the north-south deformation component, λ Represents the linear scale factor.

[0062] Linear scale factor λ It is related to the geophysical and geological characteristics of the reservoir cover in the oil field area. It is defined by combining the geophysical and geological characteristics of the oil field and based on empirical rules. λ Approximate value of :

[0063] (3)

[0064] Where, r is the radius of the sedimentation funnel of the oil field;

[0065] Step S23: The vertical displacement d UD Calculate the inclination slope of the vertical deformation in the east-west and north-south directions, and divide the east-west deformation component by the inclination slope of the vertical deformation in the east-west direction to calculate the linear scaling factor λ , and then through the linear scaling factor λ The north-south deformation component is obtained by combining the vertical deformation with the north-south inclination slope. Specifically, based on the vertical and east-west deformation components obtained by S13, the first-order derivative of the vertical deformation component in the east-west horizontal direction in formula (1) is used to calculate the vertical deformation in the east-west inclination slope. and vertical deformation in the north-south direction , and then use the east-west deformation component obtained by S13 d EW The vertical deformation is inclined in the east-west direction The linear scaling factor is calculated based on formula (2) λ Finally, based on the calculated linear scaling factor λ and vertical deformation in the north-south direction Estimated calculations are performed and finally the north-south deformation component is calculated.

[0066] Finally, the three-dimensional deformation field of the oil field in the vertical, east-west and north-south directions was completely obtained, see Figure 5 (a), (b), and (c) show that the oilfield area is a typical circular subsidence bowl caused by oil production. The maximum vertical subsidence rate exceeds 220 mm / yr. The three-dimensional deformation field also shows a small centripetal deformation trend toward the subsidence bowl, and the horizontal deformation is smallest in the center of the subsidence bowl and most significant at the outer edge of the subsidence bowl.

[0067] In one embodiment, in S3, in the nonlinear Bayesian inversion software, the inversion parameters of the geophysical model of the fused orthogonal rectangular model are modified into a format recognizable by the nonlinear Bayesian inversion, ensuring that the nonlinear Bayesian inversion software can correctly identify and invert.

[0068] In one embodiment, the specific steps of S4 are as follows:

[0069] S41: Generate three sets of inversion observations for nonlinear Bayesian inversion based on the three-dimensional deformation results of the oil field in the vertical, east-west, and north-south directions. Each set of inversion observations includes three columns of parameters: longitude, latitude, and deformation value corresponding to each deformation point. The deformation value needs to be converted into a phase value in meters based on the deformation value and the wavelength parameter of the Sentinel-1 satellite.

[0070] S42: Based on the prior information of the underground oil field reservoir, the Poisson's ratio is set to 0.25, and the geophysical model of the fused orthogonal rectangular model is used as the physical model. The Bayesian inversion algorithm is used to search for the optimal parameters, and a predefined search range is set for each parameter. For example, the model length is set to 100 to 1000 meters, and the width is set to 10 to 50 meters. After 1 million iterations (too few iterations will lead to the inversion result being unable to fit, resulting in poor inversion effect, and too many iterations will increase the inversion time and low inversion efficiency, so in the reservoir parameter inversion, 1 million iterations are selected as the inversion iteration number to ensure the best fitting effect) to make the reservoir parameters converge and obtain the optimal fitting parameters. The final modeling results are as follows Figure 6-8 As shown, Figure 6 (a) Figure 7 (a) Figure 8 (a) shows the original simulated three-dimensional deformation in the vertical, east-west, and north-south directions, respectively. Figure 6 (b) Figure 7 (b) Figure 8 (b) in the figure shows the vertical, east-west and north-south three-dimensional deformations obtained by inversion. Figure 6 (c) Figure 7 (c) Figure 8 (c) in the figure is the residual between the original simulated three-dimensional deformation and the inverted three-dimensional deformation in the vertical, east-west and north-south directions, respectively. It can be seen that the overall trend of the original simulated three-dimensional deformation is consistent with that of the inverted three-dimensional deformation, and the overall value of the residual result tends to 0 and conforms to the normal distribution, indicating that the three-dimensional deformation inversion and modeling method of the present invention is feasible.

[0071] The above-described embodiments merely represent specific implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of protection of the present application. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the technical concept of the present application, and all such variations and improvements fall within the scope of protection of the present application.

Claims

1. A method for oilfield modeling that integrates InSAR three-dimensional deformation and geophysical models, characterized by: The following steps are involved: S1: Select ascending and descending 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: By assuming a linear relationship between horizontal deformation and slope, and using the spatial similarity between the vertical and east-west two-dimensional deformation fields and the horizontal deformation, the north-south deformation component is extracted. The specific steps of S2 are as follows: S21: In an approximately regular oilfield settlement funnel, the horizontal displacement at the center of the settlement funnel is approximately zero, and the horizontal displacement is the largest in the area with the largest slope. The slope is then expressed as the first-order derivative of the vertical settlement in the horizontal direction: (1) Where, d UD is the vertical settlement deformation, and Represent the vertical deformation in the east-west and north-south directions, and represent the spatial differentials along the east-west direction and along the north-south direction respectively; Step S22: Since the spatial variation characteristics are basically similar in the approximately regular oilfield subsidence funnel, the linear proportional relationship between the slope of the horizontal deformation and the vertical deformation is used to represent the deformation components in the east-west and north-south directions: (2) Where, 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 It is related to the geophysical and geological characteristics of the reservoir cover in the oil field area. It is defined by combining the geophysical and geological characteristics of the oil field and based on empirical rules. λ Approximate value of : (3) Where, r is the radius of the sedimentation funnel of the oil field; Step S23: The vertical displacement d UD Calculate the inclination slope of the vertical deformation in the east-west and north-south directions, and divide the east-west deformation component by the inclination slope of the vertical deformation in the east-west direction to calculate the linear scaling factor λ , and then through the linear scaling factor λ The north-south deformation component is obtained by summing the north-south slope of the vertical deformation; S3: The geophysical model integrated with the orthogonal rectangular model is used as a physical inversion model and introduced into the nonlinear Bayesian physical parameter inversion of underground oil fields; S4: The extracted three-dimensional deformation fields of the oil field in the vertical, east-west, and north-south directions are used as inversion observations and introduced into the parameter inversion of the physical inversion model. The nonlinear Bayesian inversion method is used to realize the modeling of the three-dimensional deformation of the underground oil field.

2. The oilfield modeling method according to claim 1, wherein: The geophysical model of the integrated orthogonal rectangular model in S3 includes three orthogonal rectangular dislocations.

3. The oilfield modeling method integrating InSAR 3D deformation and geophysical model according to claim 2, characterized in that: The three orthogonal rectangular dislocations are composed of the XYZ Earth-centered Earth-fixed coordinate system and the xyz-axis Cartesian coordinate system.

4. The oilfield modeling method integrating InSAR 3D deformation and geophysical model according to any one of claims 1 to 3, characterized in that: The specific steps of S1 include: S11: Select ascending and descending SAR observation image data covering the oilfield area, and obtain disentangled interferograms of the ascending and descending data respectively through differential interferometry processing; S12: Unwrap the interferograms of ascending and descending orbits that overlap in time and space using a two-dimensional deformation decomposition method, geocode and resample to the same size, and create a time matrix interpolation to unify the spatial and temporal 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. In the solution process, the rank deficiency problem of the design equation is eliminated by introducing a regularization equation. Finally, singular value decomposition is used to solve the east-west deformation rate of each pixel. and vertical deformation rate The calculated deformation rate values are used to solve the east-west and vertical deformation time series through numerical integration to obtain the vertical and east-west deformation components.

5. The oilfield modeling method integrating InSAR 3D deformation and geophysical model according to any one of claims 1 to 3, characterized in that: In S3, in the nonlinear Bayesian inversion software, the inversion parameters of the geophysical model of the fused orthogonal rectangular model are modified into a format recognizable by the nonlinear Bayesian inversion to ensure that the nonlinear Bayesian inversion software can correctly identify and invert.

6. The oilfield modeling method integrating InSAR 3D deformation and geophysical model according to any one of claims 1 to 3, characterized in that: The specific steps of S4 are as follows: S41: generating three sets of inversion observation values for nonlinear Bayesian inversion using the three-dimensional deformation results of the oil field in the vertical direction, the east-west direction, and the north-south direction, respectively, wherein each set of inversion observation values includes three columns of parameters, namely, the longitude, the latitude, and the deformation value corresponding to each deformation point; S42: Based on the prior information of the underground oil field reservoir, the Poisson's ratio is set, and the geophysical model of the fused orthogonal rectangular model is used as the physical model. After setting the initial inversion parameters and iterating, the reservoir parameters are converged and the optimal fitting parameters are obtained.

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