Method for calculating near-surface anisotropy parameters

Abstract

The application discloses a method for calculating near-surface anisotropy parameters, which comprises the following steps: after a near-surface velocity model is established, the average velocity of each micro-logging horizon is calculated, and the velocity of each horizon of the near-surface velocity model is calculated; then, the thickness of each micro-logging horizon and the thickness of the corresponding horizon of the near-surface velocity model are calculated; and finally, the near-surface anisotropy parameters are obtained. The application is used for calculating the near-surface anisotropy parameters, applied to forming a near-surface anisotropy parameter field, thereby reducing the error of the pre-stack depth migration result in depth caused by the near-surface anisotropy, and improving the imaging precision of the pre-stack depth migration.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of seismic exploration data processing of oil, and relates to the calculation of anisotropy parameters, in particular to a calculation method of near-surface anisotropy parameters. BACKGROUND

[0002] Transversely isotropic medium belongs to the highest symmetry hexagonal system in anisotropic medium, which uses Thomsen parameters such as ε, δ and γ to represent elastic parameters. In actual geoscience problems, many rocks and minerals have anisotropy characteristics similar to transversely isotropic medium, so it is of great value to improve imaging quality, identify lithology, infer the dominant direction of fracture or porosity and porosity by calculating Thomsen parameters to analyze the anisotropy characteristics of transversely isotropic medium.

[0003] Although there are many methods for calculating anisotropy parameters, in actual production application, the mainstream method for calculating anisotropy parameters, especially the calculation of δ, often uses VSP or logging data. However, both VSP and logging data only contain less shallow information, and most logging data only contain data of the target formation, so the calculation of anisotropy parameters and velocity updating often only consider the middle-deep layer, and ignore the near-surface. In addition, the thickness of the near-surface layer is thin, generally between 10-300m, which also leads to the fact that the influence of near-surface anisotropy is often ignored. Although Luo Yong et al. mentioned the problem of near-surface azimuthal anisotropy in 2021, and used methods such as azimuthal dynamic and static correction and azimuthal weighted prestack time migration imaging processing, the main purpose was to improve migration imaging, and the azimuthal anisotropy parameters were not really calculated.

[0004] In fact, due to the complexity of the near-surface structure, especially in the loess tableland area in the southern Ordos Basin, the thickness of the thick area reaches more than 300m, and the velocity changes rapidly laterally, so the problem of near-surface anisotropy has a substantial impact on the prediction of drilling depth, and can cause errors in the depth of prestack depth migration results, and the well-seismic error generally reaches 5-30m. In the process of anisotropy processing, since logging interpretation often focuses on the target formation, it is often difficult to obtain related parameters of the shallow layer, and the calculation of near-surface anisotropy parameters also faces practical difficulties. SUMMARY

[0005] The purpose of the present application is to provide a calculation method of near-surface anisotropy parameters, which uses near-surface velocity model and micro-logging data to calculate near-surface anisotropy parameters, so as to reduce the error in the depth of prestack depth migration results caused by near-surface anisotropy, and improve the imaging accuracy of prestack depth migration.

[0006] To achieve the above purpose, the technical scheme adopted by the present application is as follows:

[0007] A method for calculating near-surface anisotropy parameters, comprising the following steps performed in sequence:

[0008] S1. Establishing a near-surface velocity model

[0009] Performing grid tomographic inversion using the first arrival of the shot to establish the near-surface velocity model, wherein the microlog interpretation results are applied to constrain the grid tomographic inversion;

[0010] S2. Microlog horizon division

[0011] Divide the horizons with the inflection points of the microlog interpretation result curves as boundaries;

[0012] Wherein, the inflection point represents the change point of velocity, so the horizons can be divided according to the inflection points.S3. Calculate the average velocity of each microlog horizon

[0013] Calculate the average velocity of the same horizons in all micrologs as the average velocity of the horizons corresponding to the final microlog interpretation results;

[0014] S4. Determine the sub-horizon horizons corresponding to the microlog sub-horizons on the near-surface velocity model

[0015] Determine the corresponding horizons in the near-surface velocity model with the average velocities of the upper and lower adjacent microlog horizons;

[0016] In the near-surface velocity model, the horizons are determined by velocity, so in this technology, the average velocities of the upper and lower adjacent microlog horizons are used as the basis for dividing the horizons in the near-surface velocity model;

[0017] S5. Calculate the thickness of the microlog horizons and the thickness of the corresponding near-surface velocity model horizons at the microlog points;

[0018] S6. Calculate the near-surface anisotropy parameter δ

[0019] The near-surface anisotropy parameter δ is calculated by the following formula:

[0020]

[0021] Wherein, is the thickness of the near-surface velocity model horizon; is the thickness of the microlog horizon.

[0022] As a limitation, the inflection points are the inflection point G1 with the minimum distance to the origin, the inflection point G3 with the maximum distance to the origin, and the inflection point G2 between G1 and G3.

[0023] Wherein, the origin is the origin of the coordinates, and the meaning of represents the starting depth and starting time of the microlog measurement.

[0024] As another limitation, the layer position comprises a first layer, a second layer, a third layer and a fourth layer, wherein:

[0025] The first layer is the stratum between the stratum corresponding to the inflection point G1 and the surface;

[0026] The second layer is the stratum between the stratum corresponding to the inflection point G1 and the stratum corresponding to the inflection point G2;

[0027] The third layer is the stratum between the stratum corresponding to the inflection point G2 and the stratum corresponding to the inflection point G3;

[0028] The fourth layer is the stratum corresponding to the inflection point G3 and below.

[0029] As a further limitation, in step S5, the microlog layer position thickness The calculation formula is:

[0030]

[0031] In the formula, is the depth of the i-th layer microlog layer position.

[0032] As a further limitation, in step S5, the near-surface velocity model layer position thickness The calculation formula is:

[0033]

[0034] In the formula, is the elevation of the near-surface velocity model layer position at the microlog point.

[0035] The anisotropy parameter δ field can be interpolated along the layer position by using the layer interpolation method.

[0036] Due to the use of the above technical solutions, the present application has the following technical progress compared with the prior art:

[0037] The method of the present application calculates the near-surface anisotropy parameter δ by using the near-surface velocity model and microlog data, and carries out anisotropy depth migration by using the parameter, thereby eliminating the influence of near-surface anisotropy, reducing the error of the prestack depth migration result in depth caused by near-surface anisotropy, and improving the imaging precision of prestack depth migration.

[0038] The calculation method of the near-surface anisotropy parameter of the application has good application effect on the loess tableland and desert combined zone such as the Ordos Basin with complex near-surface structure and large thickness variation, the thickness error between the near-surface velocity model and the corresponding layer of the micro-logging is analyzed, the anisotropy parameter is obtained, after the application of the near-surface anisotropy parameter, the depth migration processing is carried out, the influence of the near-surface anisotropy can be well eliminated, and the depth migration precision is effectively improved.

[0039] The application can be applied to the field of seismic exploration data processing technology of petroleum, further high-precision calculation of the near-surface anisotropy parameter δ is used for reducing the depth error caused by the near-surface anisotropy, and near-surface anisotropy correction processing is realized.

[0040] The application will be further described in detail below with reference to the drawings and specific embodiments. DESCRIPTION OF DRAWINGS

[0041] Figure 1 It is a micro-logging horizon division schematic diagram in step S2 in embodiment 1 of the application;

[0042] Figure 2 It is a near-surface velocity model layer division result diagram in step S4 in embodiment 1 of the application;

[0043] Figure 3 It is a near-surface anisotropy parameter δ field result diagram obtained in step S7 in embodiment 1 of the application;

[0044] Figure 4 It is a comparison diagram of depth migration seismic profiles in pre-stack depth migration results before and after the application of the near-surface anisotropy parameter field obtained by the application in embodiment 2 of the application; the left diagram is a depth migration seismic profile obtained before the application of the method of the application, and the right diagram is a depth migration seismic profile obtained after the application of the method of the application. DETAILED DESCRIPTION

[0045] Embodiment 1, a calculation method of a near-surface anisotropy parameter

[0046] In this embodiment, the near-surface anisotropy parameter of the Ordos Basin Huianbao three-dimensional area (Huianbao Town of Yanchi County, Wuzhong City, Ningxia Autonomous Region) is calculated, and the specific calculation method comprises the following steps in sequence:

[0047] S1. Establishing a near-surface velocity model

[0048] The near-surface application grid tomography inversion method of the big cannon first arrival is used to establish the near-surface velocity model of the Ordos Basin Huianbao area, and the micro-logging interpretation result is applied; through inversion, higher velocity precision is obtained.

[0049] S2. Micro-logging horizon division

[0050] Because the velocity differences between different layers are significant in the micrologging interpretation results, and the inflection point of the curve represents the velocity interface between different layers, the inflection point of the micrologging interpretation curve is used as the boundary to divide the layers; for example... Figure 1 As shown, Figure 1 The broken line from top to bottom represents the interpretation results of micrologging, indicating the change in velocity from shallow to deep, with inflection points marking stratigraphic boundaries. Figure 1 The vertical axis represents depth, indicating the depth measured by the micrologging, while the horizontal axis represents time, indicating the time elapsed during the micrologging measurement. Micrologging wells A, B, and C each have three distinct inflection points: the one with the smallest distance from the origin is inflection point G1, the one with the largest distance is inflection point G3, and the one located between G1 and G3 is inflection point G2. The micrologging wells are divided into four formations, with each of the three inflection points corresponding to a specific formation. and The stratigraphic positions of the three strata.

[0051] The first layer is In the above formations, the layer velocities corresponding to the micrologging points of micrologging wells A, B, and C are 570 m / s, 550 m / s, and 580 m / s, respectively; the second layer is... and The formation between the two micro-logging wells, the layer velocities corresponding to the micro-logging points of micro-logging wells A, B, and C are 990 m / s, 995 m / s, and 970 m / s, respectively; the third layer is... and The formation between these layers has micrologging points at wells A, B, and C with layer velocities of 1882 m / s, 1890 m / s, and 1865 m / s, respectively; the fourth layer is... The formations above and below are high-velocity layers. The layer velocities corresponding to the micrologging points of micrologging wells A, B, and C are 2580 m / s, 2585 m / s, and 2590 m / s, respectively.

[0052] S3. Calculate the average velocity at each micrologging layer.

[0053] Calculate the average velocity at the same level in each micrologging well, and use the average velocity of each level as the final average velocity of all levels in all micrologging wells; the following formula is used for calculation:

[0054]

[0055] in, The average velocity at each micrologging layer;

[0056] This represents the layer velocity at the micro-logging point corresponding to the desired formation.

[0057] n represents the total number of micrologging operations used.

[0058] (1) Calculate the average velocity of the first layer

[0059] Substitute 570 m / s, 550 m / s and 580 m / s into the above formula, and the average velocity of the first layer is

[0060]

[0061] (2) Calculate the average velocity of the second layer

[0062] Substitute 990 m / s, 995 m / s and 970 m / s into the above formula, and the average velocity of the second layer is

[0063] (3) Calculate the average velocity of the third layer

[0064] Substitute 1882 m / s, 1890 m / s and 1865 m / s into the above formula, and the average velocity of the third layer is

[0065] (4) Calculate the average velocity of the fourth layer

[0066] Substitute 2580 m / s, 2585 m / s and 2590 m / s into the above formula, and the average velocity of the fourth layer is

[0067] S4. Calculate the velocity of each layer of the near-surface velocity model

[0068] According to the microlog layer division, the corresponding near-surface velocity model layer is determined, and the near-surface velocity model layer division result is shown in

[0069] In the figure, Figure 2 one-to-one correspondence Figure 1

[0070] The average velocity of the microlog layer below and above is used to determine the velocity of each layer of the near-surface velocity model. The calculation formula is:

[0071]

[0072] Wherein, is the velocity of each layer of the near-surface velocity model;

[0073] is the average velocity of the adjacent upper microlog layer;

[0074] ​​​​​The average velocity of the adjacent lower microlog layer.

[0075] (S41) The first layer velocity of the near-surface velocity model

[0076] When the first layer velocity of the near-surface velocity model is calculated, The first layer average velocity of the microlog calculated in S3 is 566 m / s; The second layer average velocity of the microlog calculated in S3 is 985 m / s, which is substituted into the above formula to obtain the first layer

[0077] (S42) The second layer velocity of the near-surface velocity model

[0078] When the second layer velocity of the near-surface velocity model is calculated, The second layer average velocity of the microlog calculated in S3 is 985 m / s; The third layer average velocity of the microlog calculated in S3 is 1879 m / s, which is substituted into the above formula to obtain the second layer

[0079] (S43) The third layer velocity of the near-surface velocity model

[0080] When the third layer velocity of the near-surface velocity model is calculated, The third layer average velocity of the microlog calculated in S3 is 1879 m / s; The fourth layer average velocity of the microlog calculated in S3 is 2585 m / s, which is substituted into the above formula to obtain the second layer

[0081] S5. Calculate the microlog layer thickness and the corresponding near-surface velocity model layer thickness at the microlog point.

[0082] (S51) The calculation formula of the microlog layer thickness is:

[0083]

[0084] In the formula, The microlog layer thickness; The depth of the i-th layer microlog layer.

[0085] The microlog layer thickness calculation results and related data are shown in Table 1.

[0086] Table 1: Statistical table of microlog layer depth and layer thickness calculation results

[0087]

[0088] (S52) The formula for calculating the thickness of the near-surface velocity model horizon is:

[0089]

[0090] In the formula, is the thickness of the near-surface velocity model horizon; is the thickness of the near-surface velocity model horizon is the elevation of the micro-logging point.

[0091] The calculation results of the thickness of the near-surface velocity model horizon and related data at the micro-logging points are shown in Table 2.

[0092] Table 2 Calculation results of the thickness of the near-surface velocity model horizon and related data at the micro-logging points

[0093]

[0094]

[0095] S6. Calculate the near-surface anisotropy parameter δ

[0096] The near-surface anisotropy parameter δ is calculated by the following formula:

[0097]

[0098] In the formula, is the thickness of the near-surface velocity model horizon; is the thickness of the micro-logging horizon;

[0099] The calculation results of the near-surface anisotropy parameter δ and related data are shown in Table 3.

[0100] Table 3 Calculation results of the near-surface anisotropy parameter δ

[0101]

[0102] S7. The anisotropy parameters calculated at each micro-logging point are interpolated into the near-surface anisotropy parameter δ field along the horizon using the along-horizon interpolation method, and the results are shown in Figure 3 .

[0103] Application effect of the near-surface anisotropy parameter δ field in Example 2

[0104] In this example, the near-surface anisotropy parameter δ field obtained in Example 1 is applied to carry out near-surface anisotropy depth migration processing in the Hua'anbao area of the Ordos Basin.

[0105] The near-surface anisotropy parameter field δ calculated in Example 1 is input into a depth migration module for depth migration processing; the depths of each layer of a known production well (Well Z) and the depths of each layer of a pre-stack depth migration seismic profile are compared, and the difference is the error. The application effect of the near-surface anisotropy parameter field is shown by comparing the depth error of the depth migration before and after the application of the near-surface anisotropy parameter field; the depth migration seismic profiles obtained by the depth migration processing before and after the application of the near-surface anisotropy parameter field calculated in Example 1 are shown in FIG. 2, and the specific error analysis data of the known Well Z are shown in Table 4. Figure 4

[0106] Table 4. Calculation results before and after the application of Example 1

[0107]

[0108] From the seismic stacking profile shown in FIG. 1, it can be seen that before the application of the near-surface anisotropy parameter field δ, there is a significant error between the depths of each corresponding layer on the seismic profile and Well Z; after the depth migration processing by the application of the near-surface anisotropy parameter field δ of the present application, the depth error between each layer on the depth migration profile and each layer on Well Z is significantly reduced, and the well-seismic coincidence degree is significantly improved. Figure 4

[0109] As can be seen from Table 4, after the depth migration processing by the application of the near-surface anisotropy parameter field δ of the present application, the well-seismic error of each layer is reduced from 10-15 m before the application to 1-3 m, the depth error is significantly reduced, the problem of the depth error caused by the near-surface anisotropy is well solved, the near-surface anisotropy correction processing in the Ordos Basin is realized, and the imaging precision of the pre-stack depth migration is improved.

[0110] It should be noted that the above only describes the preferred embodiments of the present application, and is not intended to limit the present application, although the present application has been described in detail with reference to the above embodiments, those skilled in the art can still modify the technical solutions described in the above embodiments, or make equivalent replacements to some technical features. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the claims of the present application.​​

Claims

1. A method of calculating near-surface anisotropy parameters, characterized in that, Comprise the following steps in turn: S1. Establishing near-surface velocity model The first arrival of the cannon is used to carry out grid tomography inversion to establish the near-surface velocity model, wherein the micro-logging interpretation results are applied to constrain the grid tomography inversion; S2. Micro-logging horizon division The inflection point of the micro-logging interpretation result curve is used to divide the horizon; S3. Calculating the average velocity of each horizon of micro-logging The average velocity of the same horizon in all micro-logging is calculated as the average velocity of the corresponding horizon of the final micro-logging interpretation result; S4. Determining the horizon layer corresponding to the micro-logging layer in the near-surface velocity model The average velocity of the adjacent micro-logging horizons is used to determine the corresponding horizon in the near-surface velocity model; S5. Calculate the microlog point, microlog horizon thickness and the corresponding near-surface velocity model horizon thickness ; S6. Calculate near-surface anisotropy parameters The near-surface anisotropy parameters are calculated by the following equation : 。 2. The method of calculating near-surface anisotropy parameters according to claim 1, characterized in that, In step S2, The inflection point is the inflection point G1 with the minimum distance to the origin, the inflection point G3 with the maximum distance to the origin, and the inflection point G2 between G1 and G3.

3. The method of calculating near-surface anisotropy parameters according to claim 1 or 2, characterized in that In step S2, The horizon includes a first layer, a second layer, a third layer and a fourth layer, wherein: The first layer is the stratum between the stratum corresponding to the inflection point G1 and the surface; The second layer is the stratum between the stratum corresponding to the inflection point G1 and the stratum corresponding to the inflection point G2; The third layer is the stratum between the stratum corresponding to the inflection point G2 and the stratum corresponding to the inflection point G3; The fourth layer is the stratum corresponding to the inflection point G3 and below.

4. The method of calculating near-surface anisotropy parameters according to claim 1 or 2, characterized in that, In step S5, the microlog layer thickness The calculation formula is: ； wherein is the depth at the i-th microlog horizon. Dp is the depth at the i-1th microlog layer.

5. The method of calculating near-surface anisotropy parameters according to claim 3, wherein, In step S5, the microlog layer thickness The calculation formula is: ； wherein is the depth at the i-th microlog layer location; Dp is the depth at the i-1th microlog layer.

6. The method of calculating near-surface anisotropy parameters according to claim 1, 2 or 5, characterized in that, In step S5, the near-surface velocity model layer thickness The calculation formula is: ； wherein is a near-surface velocity model horizon elevation at microlog point; Horizons for near-surface velocity model Elevation at microlog point.

7. The method of calculating near-surface anisotropy parameters according to claim 3, wherein, In step S5, the near-surface velocity model layer thickness The calculation formula is: ； wherein is a near-surface velocity model horizon elevation at microlog point; Horizons for near-surface velocity model Elevation at microlog point.

8. The method of calculating near-surface anisotropy parameters according to claim 4, wherein, In step S5, the near-surface velocity model layer thickness The calculation formula is: ； wherein is a near-surface velocity model horizon elevation at microlog point; to a near-surface velocity model horizon elevation at the microlog point.

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