Lithology compensation-based sedimentary facies control high-resolution inversion method and system

Abstract

The invention provides a sedimentary facies high-resolution inversion method and system based on lithology compensation, and the method comprises the steps: S1, obtaining a GR curve, carrying out the preprocessing of the GR curve, and converting the GR curve into a lithology compensation coefficient; s2, establishing a regional geologic structure model under the control of a fine interpretation horizon and a fault structure framework, and establishing sedimentary microfacies model data of each sand group of a target stratum on the basis of variation function analysis; s3, compensating the wave impedance data by using the lithologic coefficient, establishing a three-dimensional initial wave impedance model, and obtaining a sedimentary phased wave impedance model through the step S2; s4, well control waveform slimming high-resolution processing is carried out; and S5, using the sedimentary facies wave impedance model as a constraint condition, and carrying out sedimentary facies iteration inversion for multiple times. The multi-solution property of inversion is reduced, and the method has better operability, innovativeness and practicability.

Description

Technical Field

[0001] The invention relates to the technical field of fine prediction of medium-deep thin reservoirs in petroleum exploration and development, and in particular to a sedimentary phase-controlled high-resolution inversion method and system based on lithology compensation. Background Art

[0002] The target layer in the study area has complex faults, thin reservoir sand bodies, and strong heterogeneity. The prediction accuracy of thin sand reservoirs has a great impact on oil field productivity. In order to improve the prediction accuracy of thin sand reservoirs in this study area, the present invention integrates sedimentary, well logging, seismic and other information, and proposes a sedimentary facies-controlled high-resolution inversion method based on lithology compensation.

[0003] At present, there are many studies on seismic phase-controlled inversion methods at home and abroad. Huang Handong (2007), Zhang Zhiwei (2011), and Zhang Sheng (2018) proposed nonlinear random inversion under seismic phase control for different research blocks to improve the reliability of inversion; Hang (2009) proposed a statistical inversion method under seismic phase control, which was successfully applied to the prediction of sandstone reservoirs; Liu et al. (2018), Wang et al. (2018), and Li et al. (2019) proposed seismic phase-controlled geostatistical inversion methods in different research blocks to improve the accuracy of reservoir prediction. accuracy; Wang Dongkun (2022) obtained the sedimentary characteristic variation function by analyzing the direct relationship between seismic phase and sedimentary phase and applied it to geostatistical inversion to quantitatively predict thin sand bodies; there are few studies on geological sedimentary phase constrained inversion. Wang et al. (2009) proposed an inversion method under the control of well data and geological sedimentary phase to improve the inversion resolution; Yang et al. (2016) proposed a random inversion method under the constraint of geological sedimentary phase; Huang et al. (2020) proposed an iterative phase-controlled deterministic inversion method, adding geological sedimentary phase constraints to iteratively improve the inversion accuracy. The seismic phase-constrained inversion method has certain limitations, and some seismic phases do not match the actual sedimentary characteristics. In addition, under the limitation of low-frequency seismic data, the conventional phase-controlled inversion method cannot reliably identify thin sandstone in areas without wells. Summary of the invention

[0004] In view of the above problems, the present invention is proposed to provide a sedimentary facies-controlled high-resolution inversion method and system based on lithology compensation, which overcomes the above problems or at least partially solves the above problems.

[0005] According to one aspect of the present invention, a sedimentary facies-controlled high-resolution inversion method based on lithology compensation is provided, the inversion method comprising:

[0006] Step S1, obtaining a GR curve, preprocessing the GR curve, and converting it into a lithology compensation coefficient;

[0007] Step S2, establishing a regional geological structure model under the control of fine interpretation of the horizon and fault structure framework, and establishing sedimentary microfacies model data of each sand group in the target layer based on variogram analysis;

[0008] Step S3, using lithology coefficients to compensate for wave impedance data, establishing a three-dimensional initial wave impedance model, and constraining the three-dimensional initial wave impedance model through the sedimentary phase model in step S2 to obtain a sedimentary phase-controlled wave impedance model;

[0009] Step S4, performing high-resolution processing of well control waveform slimming;

[0010] Step S5, based on the high-resolution data volume, using the sedimentary phase-controlled wave impedance model as a constraint condition, perform multiple iterative inversions.

[0011] Optionally, the preprocessing of the GR curve specifically includes: performing low-frequency correction and dimensionless mapping processing on the GR curve.

[0012] Optionally, the step S1, obtaining a GR curve, preprocessing the GR curve, and converting the GR curve into a lithology compensation coefficient specifically includes:

[0013] Based on the analysis of the rock physical characteristics of the target layer in the study area, the logging data was optimized, and the GR curve was subjected to low-frequency correction to remove the low-frequency trend of the logging curve. The formula is:

[0014]

[0015] Where: N is the filter order, f c is the filter cutoff frequency, G is the logging GR data, and Gl is the GR low-frequency corrected data.

[0016] Optionally, the dimensionless projection mapping process is performed on the basis of the low-frequency correction to convert it into a lithology compensation coefficient, and the formula is:

[0017]

[0018] Among them, Gl is the GR low-frequency corrected data, a and b are the value ranges of the constraint coefficients, which are determined according to the relative change amplitude of the maximum and minimum values ​​of the original wave impedance, a is 0.8-0.9, and b is 1.1-1.2.

[0019] Optionally, the step S2, establishing a regional geological structure model under the control of the fine interpretation of the horizon and the fault structure framework, and establishing the sedimentary microfacies model data of each sand group of the target layer specifically includes:

[0020] Establish regional geological structural models under the control of fine interpretation of horizons and fault structural frameworks and establish constraints;

[0021] Based on the variogram analysis, the sedimentary microfacies model data of each sand group in the target layer are established.

[0022] Optionally, the constraint conditions specifically include: seismic attribute distribution, sand body thickness distribution and sedimentary paleo-geomorphology map.

[0023] Optionally, the step S2, establishing a regional geological structure model under the control of the fine interpretation of the horizon and the fault structure framework, and establishing the sedimentary microfacies model data of each sand group of the target layer specifically includes:

[0024] Under the control of fine interpretation of horizons and fault structure framework, structural modeling is carried out to establish the regional geological structure model F(x,y,z);

[0025] Taking the seismic attribute distribution, sand body thickness distribution and sedimentary paleo-geomorphology map as constraint conditions, the sedimentary microfacies data f of the i-th sand group of the target layer is established based on the variogram analysis. i (x,y), the formula is:

[0026]

[0027] Where N is the number of sedimentary microfacies, L N is the boundary range of the Nth sedimentary microfacies;

[0028] Under the three-dimensional geological structure model, the sedimentary phase data volume F(x,y,z) is obtained:

[0029] F(x,y,z)=f i (x,y),z i <z<z i+1

[0030] Among them, z i is the time range of the top surface of the i-th sand group.

[0031] Optionally, the step S3, using lithology coefficients to compensate for wave impedance data, establishing a three-dimensional initial wave impedance model, and constraining the three-dimensional initial wave impedance model by the sedimentary phase model in step S2 to obtain a sedimentary phase-controlled wave impedance model specifically includes:

[0032] The three-dimensional wave impedance model P is established by using the wave impedance data after constraint coefficient lithology compensation. lit ;

[0033] The three-dimensional lithology compensation wave impedance model is constrained by the sedimentary phase data F to obtain the phase-controlled wave impedance data P facies :

[0034] P facies =P lit +α·β·(F*G)

[0035]

[0036]

[0037] Among them, P lit is the wave impedance data after lithology compensation of constraint coefficient, α and β are adjustment factors, α ranges from 1 to 3, and β ranges from 2000 to 5000, which are determined by the average velocity of the target layer in the study area;

[0038] F is the obtained sedimentary facies model data volume, G is the adjustment function, and σ is the standard deviation.

[0039] Optionally, the adjustment function adopts a Gaussian function.

[0040] Optionally, the step S4 of performing high-resolution processing of well control waveform slimming specifically includes:

[0041] Perform high-resolution slimming processing of well-controlled waveforms, use the deconvolution theory, and iterate through well-seismic calibration to determine the slimming factor, and obtain the high-resolution seismic data volume y(t):

[0042]

[0043]

[0044] Among them, Y(f) is the frequency domain of the seismic data y(t) after slimming down, X(f) is the original seismic frequency domain data, W(f) is the original seismic wavelet, W'(f) is the wavelet after slimming down, s w It is the well-controlled slimming factor, R w is the well point reflection coefficient, W w is the given weight loss subwave, X 0 is the seismic data near the well, and M is the number of well points in the study area.

[0045] Optionally, the step S5, based on the high-resolution data volume, using the sedimentation phase-controlled wave impedance model as a constraint condition, performing multiple iterative inversions specifically includes:

[0046] Based on the high-resolution well control data, the phase-controlled wave impedance model is used as the trend constraint condition to establish the minimum objective function E:

[0047]

[0048] Among them, r is the reflection coefficient, y is the seismic high-resolution data, and s is the convolution synthetic seismic data. is the phase-controlled wave impedance model data, P i is the actual seismic wave impedance data, N is the total number of data samples, and λ and m are weighting factors.

[0049] The present invention also provides a sedimentary facies-controlled high-resolution inversion system based on lithology compensation, which applies the above-mentioned sedimentary facies-controlled high-resolution inversion method based on lithology compensation. The inversion system specifically includes:

[0050] A lithology compensation coefficient processing module is used to obtain a GR curve, pre-process the GR curve, and convert it into a lithology compensation coefficient;

[0051] Sedimentary facies model data establishment module is used to establish a regional geological structure model under the control of fine interpretation of the horizon and fault structure framework, and to establish sedimentary microfacies model data for each sand group in the target layer;

[0052] The phase-controlled wave impedance model acquisition module is used to use the lithology coefficient to compensate the wave impedance data, establish a three-dimensional initial wave impedance model, constrain the three-dimensional initial wave impedance model through the sedimentary phase model in step S2, and obtain the sedimentary phase-controlled wave impedance model;

[0053] Improved resolution processing module, used for high-resolution processing of well control waveform slimming;

[0054] The sedimentary phase-controlled iterative inversion module is used to perform multiple iterative inversions based on high-resolution data volumes using the sedimentary phase-controlled wave impedance model as a constraint condition.

[0055] The present invention provides a sedimentary phase-controlled high-resolution inversion method and system based on lithology compensation, the inversion method comprising: step S1, obtaining a GR curve, pre-processing the GR curve, and converting it into a lithology compensation coefficient; step S2, establishing a regional geological structure model under the control of a fine interpretation layer and a fault structure framework, and establishing sedimentary microfacies model data of each sand group in the target layer on the basis of variogram analysis; step S3, using lithology coefficients to compensate for wave impedance data, establishing a three-dimensional initial wave impedance model, and constraining the three-dimensional initial wave impedance model through the sedimentary phase model in step S2 to obtain a sedimentary phase-controlled wave impedance model; step S4, performing well-controlled waveform slimming high-resolution processing; step S5, based on a high-resolution data body, using the sedimentary phase-controlled wave impedance model as a constraint condition, and performing multiple sedimentary phase-controlled iterative inversions. More geological and seismic information is added to participate in the inversion, reducing the multi-solution of the inversion, and achieving better practical application effects.

[0056] The results of the present invention improve the vertical resolution of thin-layer sand bodies vertically, and are consistent with the sedimentary law horizontally and can reflect the lateral heterogeneity. More geological and seismic information is added to participate in the inversion, which reduces the multi-solution of the inversion and has better operability, innovation and practicality.

[0057] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0059] Figure 1 A flow chart of a sedimentary facies-controlled high-resolution inversion method based on lithology compensation provided by an embodiment of the present invention;

[0060] Figure 2 A low-frequency trend diagram of the GR curve removed provided by an embodiment of the present invention;

[0061] Figure 3 A schematic diagram of compensation coefficients for lithology information provided by an embodiment of the present invention;

[0062] Figure 4 A comparison diagram of the wave impedance curve after lithology coefficient compensation and the original wave impedance curve provided by the implementation example of the present invention;

[0063] Figure 5 The intersection diagram of wave impedance and GR before and after compensation of the CB151 well provided for the implementation example of the present invention;

[0064] Figure 6 A sedimentary facies model diagram obtained under a three-dimensional geological structure model provided for an embodiment of the present invention;

[0065] Figure 7 A cross-sectional diagram comparing the phase-controlled wave impedance model of the north-south Inline2275 line and the conventional wave impedance model provided for the implementation example of the present invention;

[0066] Figure 8 A cross-sectional diagram comparing the effects of high-resolution processing of east-west seismic data of Chengbei 35 Well provided as an example of the present invention;

[0067] Fig. 9 A cross-sectional diagram comparing sedimentary phase-controlled high-resolution inversion and conventional inversion provided in an embodiment of the present invention;

[0068] Fig.10 A plane comparison diagram of the effects of sedimentary phase-controlled high-resolution inversion and conventional inversion provided by an embodiment of the present invention;

[0069] Fig.11 The planar distribution diagram of the thin sand of the Dongying Formation described on the basis of phase-controlled inversion is provided as an implementation example of the present invention. DETAILED DESCRIPTION

[0070] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0071] The terms "comprises" and "having" and any variations thereof in the description embodiments, claims and drawings of the present invention are intended to cover non-exclusive inclusions, for example, including a series of steps or units.

[0072] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0073] like Figure 1 As shown, the purpose of the present invention is to provide a new thin reservoir sedimentary phase-controlled inversion method. The purpose of the present invention can be achieved by the following technical measures: Step 1, low-frequency correction and dimensionless mapping processing are performed on the GR curve to convert it into a lithology compensation coefficient; Step 2, a regional geological structure model is established under the control of a fine interpretation of the horizon and a fault structure framework, and then the seismic attribute distribution, sand body thickness distribution, and sedimentary paleo-geomorphology map are used as constraints. On the basis of the variogram analysis, the sedimentary microfacies model data of each sand group in the target layer are established; Step 3, the wave impedance data is compensated by using the lithology coefficient, and a three-dimensional initial wave impedance model is established. The three-dimensional initial wave impedance model is constrained by the sedimentary phase model in step 2 to obtain a sedimentary phase-controlled wave impedance model; Step 4, high-resolution processing of well-controlled waveform slimming is performed; Step 5, multiple iterative inversions are performed based on the high-resolution data body using the sedimentary phase-controlled wave impedance model as a constraint condition.

[0074] The present invention provides a sedimentary facies-controlled high-resolution inversion method based on lithology compensation, comprising:

[0075] Step 101, based on the analysis of the rock physical characteristics of the Dongying Formation in the study area, a Butterworth filter is used to perform low-frequency correction processing, and the low cutoff frequency is selected as 3 Hz to remove the low-frequency trend of the logging curve ( Figure 2 );Use the formula to correct the GR curve after low frequency De-dimensionalization mapping is performed to map the compensation coefficients that can reflect lithology information ( Figure 3), the mapping range is required to be 1 at the mudstone baseline, a is taken as 0.9 and b is taken as 1.2 in this study area, and Gl in the formula is the GR low-frequency corrected data. The lithology compensation coefficient is multiplied by the wave impedance data for compensation. Figure 4 The blue curve in the left figure is the wave impedance curve after lithology coefficient compensation, and the purple curve in the right figure is the uncompensated original wave impedance curve. It can be clearly seen that the compensated data is highly consistent with the GR curve, and low GR corresponds to high impedance value, which can better distinguish sandstone and mudstone. Figure 5 This is the wave impedance intersection diagram before and after compensation of Well CB151. The sandstone is red-yellow. By comparing the diagrams, we can see that the impedance data after compensation can better distinguish sandstone and mudstone.

[0076] Step 102, under the control of fine interpretation of the horizon and fault structure framework, structural modeling F(x, y, z) is performed, and then the seismic attribute distribution, sand body thickness distribution, sedimentary paleo-geomorphology and other maps are used as constraints, and the sedimentary microfacies data f of the i-th sand group of the target layer is established based on the variogram analysis. i (x, y), a total of 3 layers of sand group sedimentary microfacies i=3 were established in this study area. Comprehensive logging phase, lithofacies and other analyses determined that this area is dominated by nearshore underwater fans, and there are 3 sedimentary microfacies L1, L2, L3:

[0077]

[0078] Under the three-dimensional geological structure model, the sedimentary phase data volume F(x,y,z) is obtained:

[0079]

[0080] Among them, z i is the time range of the top surface of the i-th sand group.

[0081] Step 103: Using the wave impedance data after lithology coefficient compensation, a three-dimensional wave impedance model P is established. lit , the three-dimensional lithology compensation wave impedance model is constrained by the sedimentary phase data F, and the phase-controlled wave impedance data P is obtained. facies :

[0082] p facies =P lit +α·β·(F*G)

[0083]

[0084]

[0085] Among them, P lit is the wave impedance data after lithology coefficient compensation, α and β are adjustment factors, α is 2, and β is 3500 in this study area. F is the sedimentary facies model data volume obtained, and σ is the standard deviation.

[0086] Figure 7 This is a comparison section of the Inline2275 wave impedance model in the north-south direction. It can be seen that the wave impedance model after adding the sedimentary phase constraint condition has the concept of sedimentary phase, and the profile characteristics are more in line with the sedimentary law.

[0087] Step 104, perform high-resolution slimming processing of well-controlled waveforms. Using the deconvolution theory, the slimming factor is determined by repeated iterations of seismic calibration of 10 wells in the study area to obtain a high-resolution seismic data volume y(t):

[0088]

[0089]

[0090] Among them, Y(f) is the frequency domain of the seismic data y(t) after slimming down, X(f) is the original seismic frequency domain data, W(f) is the original seismic wavelet, W'(f) is the wavelet after slimming down, s w It is the well-controlled slimming factor, R w is the well point reflection coefficient, W w is the given weight loss subwave, X 0 is the seismic data near the well, and M is the number of well points in the study area.

[0091] Figure 8 This is a comparison section of the high-resolution processing effect of the east-west seismic data in Chengbei Well 35. From the processing effect, the frequency band of the original seismic data has been significantly broadened after processing, the resolution of the seismic phase axis is higher, the main frequency of the seismic data has been widened from 22Hz to 50Hz, the resolution of the seismic data has been significantly improved, and the recognition ability of thin sand bodies has been increased, laying the foundation for the later phase-controlled inversion.

[0092] In step 105, based on the well control high-resolution data volume, the phase-controlled wave impedance model is used as a trend constraint condition to establish the minimum objective function E:

[0093]

[0094] Among them, r is the reflection coefficient, y is the seismic high-resolution data, and s is the convolution synthetic seismic data. is the phase-controlled wave impedance model data, P i is the actual seismic wave impedance data, N is the total number of data samples, and λ and m are weighting factors.

[0095] Fig. 9 It is a comparative section of sedimentary phase-controlled high-resolution inversion and conventional inversion. It can be seen that the inversion data of the present invention can identify thin-layer sand bodies and has a high degree of consistency with the logging curve. Obvious progradational reflection features can be seen on the section, which are typical seismic reflection features of underwater fans.

[0096] Fig.10This is a plane comparison diagram of the sedimentary phase-controlled high-resolution inversion and conventional inversion effects. It can be seen that the distribution characteristics of the conventional inversion plane are not obvious, and the sedimentary distribution characteristics cannot be reliably judged. The inversion adds the sedimentary phase as a constraint condition, and the plane distribution characteristics are clearer. The sediment source comes from the northwest direction, which is consistent with the actual sedimentary law of the study area. Fig.11 It is a planar distribution map of the thin sands of the Dongying Formation described on the basis of phase-controlled inversion, with 28 sets of detailed descriptions and quantitative characterizations, covering a total area of ​​31.89 km 2 .

[0097] Beneficial effects: The sedimentary phase-controlled high-resolution inversion method based on lithology compensation in the present invention improves the resolution of the seismic data itself by performing high-resolution well-controlled processing on conventional seismic data. The GR curve is converted into a lithology compensation coefficient, and the main sedimentary direction is determined by variogram analysis. The sedimentary phase model is established by comprehensively measuring and recording lithology, seismic attributes, paleo-geomorphology, sedimentary phases and other information, and more geological and seismic information is added to participate in the inversion; the two are combined to obtain a sedimentary phase-controlled wave impedance model based on lithology coefficient compensation. As a constraint condition, multiple iterative inversions are performed using the data with improved resolution, which reduces the multi-solution of the inversion and improves the inversion accuracy of the well-free area. While improving the vertical resolution of thin-layer sand bodies, the present invention realizes the quantification of sedimentary phase control. The results are consistent with the sedimentary law in the horizontal direction and can reflect the lateral heterogeneity. The predicted reservoir distribution characteristics are more in line with the regional geological law, with better operability, innovation and practicality. It has achieved significant application effects in the prediction of thin reservoirs in Chengdao Oilfield and provides a reliable technical guarantee for increasing reserves in shallow-water oilfields.

[0098] The above specific implementation methods 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 implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A sedimentary facies-controlled high-resolution inversion method based on lithology compensation, characterized in that: The inversion method comprises: Step S1, obtaining a GR curve, preprocessing the GR curve, and converting it into a lithology compensation coefficient; Step S2, establishing a regional geological structure model under the control of fine interpretation of the horizon and fault structure framework, and establishing sedimentary microfacies model data of each sand group in the target layer based on variogram analysis; Step S3, using lithology coefficients to compensate for wave impedance data, establishing a three-dimensional initial wave impedance model, and constraining the three-dimensional initial wave impedance model through the sedimentary phase model in step S2 to obtain a sedimentary phase-controlled wave impedance model; Step S4, performing high-resolution processing of well control waveform slimming; Step S5, based on the high-resolution data volume, using the sedimentary phase-controlled wave impedance model as a constraint condition, perform multiple iterative inversions.

2. The sedimentary facies-controlled high-resolution inversion method based on lithology compensation according to claim 1 is characterized in that: The preprocessing of the GR curve specifically includes: performing low-frequency correction and dimensionless mapping processing on the GR curve.

3. The sedimentary facies-controlled high-resolution inversion method based on lithology compensation according to claim 1, characterized in that: The step S1, obtaining the GR curve, preprocessing the GR curve, and converting it into a lithology compensation coefficient specifically includes: Based on the analysis of the rock physical characteristics of the target layer in the study area, the logging data was optimized, and the GR curve was subjected to low-frequency correction to remove the low-frequency trend of the logging curve. The formula is: Where: N is the filter order, f c is the filter cutoff frequency, G is the logging GR data, and Gl is the GR low-frequency corrected data.

4. The sedimentary facies-controlled high-resolution inversion method based on lithology compensation according to claim 3 is characterized in that: The dimensionless projection mapping process is performed on the basis of low-frequency correction and converted into a lithology compensation coefficient, and the formula is: Among them, Gl is the GR low-frequency corrected data, a and b are the value ranges of the constraint coefficients, which are determined according to the relative change amplitude of the maximum and minimum values ​​of the original wave impedance, a is 0.8-0.9, and b is 1.1-1.

2.

5. The sedimentary facies-controlled high-resolution inversion method based on lithology compensation according to claim 1, characterized in that: The step S2, establishing a regional geological structure model under the control of the fine interpretation of the horizon and the fault structure framework, and establishing the sedimentary microfacies model data of each sand group in the target layer specifically includes: Establish regional geological structural models under the control of fine interpretation of horizons and fault structural frameworks and establish constraints; Based on the variogram analysis, the sedimentary microfacies model data of each sand group in the target layer are established.

6. The sedimentary facies-controlled high-resolution inversion method based on lithology compensation according to claim 5, characterized in that: The constraint conditions specifically include: seismic attribute distribution, sand body thickness distribution and sedimentary paleo-geomorphology map.

7. The sedimentary facies-controlled high-resolution inversion method based on lithology compensation according to claim 1, characterized in that: The step S2, establishing a regional geological structure model under the control of the fine interpretation of the horizon and the fault structure framework, and establishing the sedimentary microfacies model data of each sand group in the target layer specifically includes: Under the control of fine interpretation of horizons and fault structure framework, structural modeling is carried out to establish the regional geological structure model F(x,y,z); Taking the seismic attribute distribution, sand body thickness distribution and sedimentary paleo-geomorphology map as constraint conditions, the sedimentary microfacies data f of the i-th sand group of the target layer is established based on the variogram analysis. i (x,y), the formula is: Where N is the number of sedimentary microfacies, L N is the boundary range of the Nth sedimentary microfacies; Under the three-dimensional geological structure model, the sedimentary phase data volume F(x,y,z) is obtained: F(x,y,z)=f i (x,y),z i <z<z i+1 Among them, z i is the time range of the top surface of the i-th sand group.

8. The sedimentary facies-controlled high-resolution inversion method based on lithology compensation according to claim 1, characterized in that: The step S3, using the lithology coefficient to compensate the wave impedance data, establishes a three-dimensional initial wave impedance model, and constrains the three-dimensional initial wave impedance model through the sedimentary phase model in step S2 to obtain the sedimentary phase-controlled wave impedance model, specifically includes: The three-dimensional wave impedance model P is established by using the wave impedance data after constraint coefficient lithology compensation. lit ; The three-dimensional lithology compensation wave impedance model is constrained by the sedimentary phase data F to obtain the phase-controlled wave impedance data P facies : P facies =P lit +a·b·(F*G) Among them, P lit is the wave impedance data after lithology compensation of constraint coefficient, α and β are adjustment factors, α ranges from 1 to 3, and β ranges from 2000 to 5000, which are determined by the average velocity of the target layer in the study area; F is the obtained sedimentary facies model data volume, G is the adjustment function, and σ is the standard deviation.

9. The sedimentary facies-controlled high-resolution inversion method based on lithology compensation according to claim 8, characterized in that: The adjustment function adopts a Gaussian function.

10. The sedimentary facies-controlled high-resolution inversion method based on lithology compensation according to claim 1, characterized in that: The step S4, performing high-resolution processing of well control waveform slimming, specifically includes: Perform high-resolution slimming processing of well-controlled waveforms, use the deconvolution theory, and iterate through well-seismic calibration to determine the slimming factor, and obtain the high-resolution seismic data volume y(t): Among them, Y(f) is the frequency domain of the seismic data y(t) after slimming down, X(f) is the original seismic frequency domain data, W(f) is the original seismic wavelet, W'(f) is the wavelet after slimming down, s w It is the well-controlled slimming factor, R w is the well point reflection coefficient, W w is the given weight loss subwave, X 0 is the seismic data near the well, and M is the number of well points in the study area.

11. The sedimentary facies-controlled high-resolution inversion method based on lithology compensation according to claim 1, characterized in that: The step S5, based on the high-resolution data volume, using the sedimentation phase-controlled wave impedance model as a constraint condition, performs multiple iterative inversions, specifically including: Based on the high-resolution well control data, the phase-controlled wave impedance model is used as the trend constraint condition to establish the minimum objective function E: Among them, r is the reflection coefficient, y is the seismic high-resolution data, and s is the convolution synthetic seismic data. is the phase-controlled wave impedance model data, P i is the actual seismic wave impedance data, N is the total number of data samples, and λ and m are weighting factors.

12. A sedimentary facies-controlled high-resolution inversion system based on lithology compensation, using a sedimentary facies-controlled high-resolution inversion method based on lithology compensation as described in any one of claims 1 to 11, characterized in that: The inversion system specifically comprises: A lithology compensation coefficient processing module is used to obtain a GR curve, pre-process the GR curve, and convert it into a lithology compensation coefficient; Sedimentary facies model data establishment module is used to establish a regional geological structure model under the control of fine interpretation of the horizon and fault structure framework, and to establish sedimentary microfacies model data for each sand group in the target layer; The phase-controlled wave impedance model acquisition module is used to use the lithology coefficient to compensate the wave impedance data, establish a three-dimensional initial wave impedance model, constrain the three-dimensional initial wave impedance model through the sedimentary phase model in step S2, and obtain the sedimentary phase-controlled wave impedance model; Improved resolution processing module, used for high-resolution processing of well control waveform slimming; The sedimentary phase-controlled iterative inversion module is used to perform multiple iterative inversions based on high-resolution data volumes using the sedimentary phase-controlled wave impedance model as a constraint condition.

Images