A Shallow Velocity Modeling Method Based on the True Earth Surface

Abstract

This invention discloses a shallow velocity modeling method based on the true Earth surface, including obtaining... cmp Time plan of the marker layer starting from the surface T cmp Calculate the thickness of the shallow marker layer starting from the offset surface. D cmp‑d Calculate the shallow marker layer time starting from the offset surface. T cmp‑d Calculate the velocity of the shallow marker layer starting from the offset surface. V i The invention involves steps such as establishing a shallow velocity model. By combining information from micrologging, drilling, and seismic data, this invention achieves multi-dimensional constraints on points, lines, and surfaces. This solves the velocity constraint and smoothing error problems of conventional methods, improving the accuracy of the shallow velocity model and consequently the overall depth migration velocity model accuracy, thus ensuring the accuracy of depth migration imaging. This invention is applicable to shallow velocity modeling methods on the true Earth surface, and is used in the pre-stack depth migration processing of seismic data.

Description

Technical Field

[0001] This invention belongs to the field of seismic exploration technology for oil and gas, and relates to pre-stack depth offset processing of seismic data. Specifically, it is a shallow velocity modeling method based on the true surface. Background Technology

[0002] With the rapid development of the national economy and the huge demand for oil and gas resources, it is imperative to increase domestic oil and gas exploration efforts. Among them, exploration areas with complex surface and subsurface geological conditions are gradually becoming important replacement areas for oil and gas exploration. In areas with complex structures, the surface is undulating and the subsurface is deformed, resulting in severe distortion of seismic wave propagation. Compared with time migration, depth migration can better solve the complex wave field effects caused by local velocity anomalies. Only depth migration using an accurate velocity model can obtain the best superposition and images located at the correct depth (cited from "Depth Migration of Complex Structures", Christof Stork, Advance Geophysical). Therefore, the accuracy of the velocity model is a key factor in improving the quality of depth migration imaging.

[0003] Analysis of the impact of velocity model errors on pre-stack depth migration imaging shows that shallow velocity errors have a greater impact on accurate imaging in the depth domain than mid-to-deep velocity errors. This is mainly reflected in two aspects: 1. Velocity errors in the shallow layer have a wider impact on mid-to-deep imaging, and the errors accumulate and are irreversible; 2. Velocity errors in the shallow layer lead to poorer imaging quality in the mid-to-deep layer. Therefore, how to establish an accurate shallow velocity model is one of the key issues to be addressed in depth migration processing.

[0004] In conventional processing, the methods for obtaining shallow velocity models mainly include the following: 1. Micrologging method; 2. Small refraction method; 3. Surface wave method; 4. Tomographic inversion method; 5. Full waveform inversion method, etc. Furthermore, research revealed that Chinese patent CN106249290B discloses "A method for establishing a surface velocity structure model using multi-level data fusion." This method calculates multiple shallow velocity models using data at different scales, and then fuses these multiple sets of data using an inverse distance weighting algorithm to form a new shallow velocity model. The near-surface velocity model obtained through the above methods is then stitched together with the subsurface velocity model obtained using pre-stack time migration processing to obtain a full-depth velocity model. The above methods have the following two problems: 1. In establishing shallow surface velocity models, micrologging data is usually used as a constraint, but the number of micrologging wells is usually small, making it difficult to accurately control the planar trend; 2. Before performing depth migration processing, the stitched full-depth velocity model needs to be smoothed before it can be used. Because the shallow velocity model has a small thickness and small velocity values, the smoothed velocity has a large error compared to the actual velocity. This error is difficult to eliminate and thus seriously affects the accuracy of imaging the underlying strata. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention aims to provide a shallow velocity modeling method based on the true surface, achieving multi-dimensional constraints of points, lines, and surfaces, improving the accuracy of the shallow velocity model, thereby improving the overall accuracy of the depth migration velocity model and ensuring the accuracy of depth migration imaging.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A shallow velocity modeling method based on the true Earth surface, comprising the following steps performed sequentially:

[0008] S1. Obtain the time plane plot T of the marker layer starting from the CMP plane. cmp

[0009] Using time-domain seismic data and drilled well data, shallow low-velocity conglomerate marker bedding and shallow high-velocity conglomerate marker bedding were identified. The near-surface marker bedding was finely interpreted on the seismic profile, and a marker bedding time plane map T0 was obtained through gridding. Based on T0, the marker bedding time plane map T, calculated from the cmp surface, was then derived. cmp ;

[0010] S2. Calculate the thickness D of the shallow marker layer starting from the offset surface. cmp-d

[0011] S21. Using T cmp The marker layer velocities are obtained from the seismic velocity spectrum, and the velocity variations are constrained and corrected using drilling and micrologging data to obtain the marker layer velocities V. iq ;

[0012] S22. Using T cmp and layer velocity V iq Perform time-depth transformation to obtain the marker layer thickness D. cmp-d ;

[0013] S3. Calculate the shallow marker layer time T starting from the offset surface. cmp-d

[0014] S31. Using the predictable offset surface data, filling speed, and horizontal reference surface data, obtain the filling amount △T0 between the horizontal reference surface and the offset surface;

[0015] S32. Using the predictable static correction data and ΔT0, obtain the static correction peeling amount ΔT. 0b ;

[0016] S33. Through △T 0b With T cmp The time T from the start of the offset surface is obtained. cmp-d ;

[0017] S4. Calculate the shallow marker layer velocity V from the offset surface. i

[0018] Using D cmp-d and T cmp-d The velocity V of the marker layer calculated from the offset surface is obtained. i ;

[0019] S5. Calculation time T using the cmp surface cmp and marker layer velocity V i A shallow velocity model was established, and a medium-deep velocity model was established by combining it with seismic and geological data to obtain a full-depth velocity model.

[0020] As a limitation of the present invention, in step S1, the marker layer time plane diagram T calculated from the cmp plane is... cmp The calculation formula is:

[0021] T cmp =T0-cmp――――――――――Formula (i)

[0022] In equation (i), cmp is the low-frequency static correction amount in seismic data processing, T0 is the marker layer time plane obtained by gridding, and T cmp The time plane diagram of the marker layer, calculated from the CMP plane.

[0023] As another limitation of the present invention, in step S22, the thickness D of the marker layer cmp-d The calculation formula is:

[0024] D cmp-d =T cmp *V iq / 2000――――――――――Form (ii)

[0025] In equation (ii), T cmp V is the marker layer time calculated from the CMP surface. iq The velocity of the marked layer is calculated starting from the CMP surface.

[0026] As a third limitation of the present invention, in step S31, the formula for calculating the filling amount △T0 is:

[0027] △T0=(H p -H d ) / V c *2000――――――――――Form (ⅲ)

[0028] In equation (iii), H p H is the elevation of the horizontal datum plane. d V represents the elevation of the offset surface. c This refers to the filling speed.

[0029] As a fourth limitation of the present invention, in step S32, the static correction peeling amount △T 0b The calculation formula is:

[0030] △T 0b = cmp - △T0―――――――――――Equation (ⅳ)

[0031] In equation (iv), △T 0b The static correction peeling amount is denoted by cmp, which is the static correction data provided by the processing, and ΔT0 is the filling amount between the horizontal reference plane and the offset plane obtained in step S31.

[0032] As a fifth limitation of the present invention, in step S33, the time T from which the offset surface is calculated... cmp-d The calculation formula is:

[0033] T cmp-d =△T 0b +T cmp ――――――――――Form (ⅴ)

[0034] In equation (v), △T 0b For static correction of peeling amount, T cmp The marker layer time is calculated starting from the CMP surface.

[0035] As a sixth limitation of the present invention, in step S4, the marker layer velocity V calculated from the offset surface... i The calculation formula is:

[0036] V i =D cmp-d / T cmp-d *2000――――――――――Formula (ⅵ)

[0037] In equation (ⅵ), D cmp-d T is the thickness of the shallow marker layer calculated from the offset surface. cmp-d The time is calculated from the offset plane.

[0038] The core of the above-mentioned technical solution of the present invention lies in the method for establishing a shallow velocity model calculated from the offset surface:

[0039] Through comprehensive research using multiple information sources, the shallow markers are precisely interpreted and their thickness is accurately determined and constrained. The amount of peeling for static correction and the marker layer time calculated from the offset surface are obtained by processing low-frequency static correction data, offset surface data, and filling speed. The speed is calculated using thickness and offset surface start time, thereby establishing a shallow velocity model and further improving the accuracy of the velocity model.

[0040] This invention utilizes refined velocity modeling to improve the accuracy of depth migration imaging, thereby revealing structural morphology details and providing a reasonable and reliable basis for well location deployment. The related ideas and implementation process specifically include the following aspects:

[0041] ①Based on the processing of low-frequency static correction data, offset surface data and filling speed, the static correction stripping amount is obtained by using the processed low-frequency static correction data and the calculated offset surface static correction data.

[0042] ② The marker layer time from the offset surface is obtained by using the static correction stripping amount and shallow marker layer time data.

[0043] ③ The shallow marker layer velocity is obtained by combining the thickness data calculated from the offset surface after correction with the shallow marker layer time calculated from the offset surface.

[0044] By adopting the above-described technical solution, the beneficial effects achieved by this invention compared to the prior art are as follows:

[0045] The shallow velocity modeling method based on the true surface provided by this invention extends the bottom interface downwards and achieves multi-dimensional constraints of points, lines, and surfaces by combining multiple information such as micrologging, drilling, and seismic data. This can solve the velocity constraint and smoothing error problems of conventional methods, improve the accuracy of the shallow velocity model, and thus improve the accuracy of the overall depth migration velocity model, ensuring the accuracy of depth migration imaging.

[0046] This invention relates to a shallow velocity modeling method applicable to the true Earth surface, which is used in the pre-stack depth offset processing of seismic data. Attached Figure Description

[0047] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0048] Figure 1 Schematic diagram of seismic reflection axis at the bottom interface of low-velocity conglomerate;

[0049] Figure 2. Time plan view of the low-velocity conglomerate bottom interface and the time calculated from the CMP surface.

[0050] Figure 3 Schematic diagram of drilling acoustic data and micro-logging velocity data (G represents drilling, S represents deep micro-logging);

[0051] Figure 4 A plan view of the velocity distribution at each level;

[0052] Figure 5 Plan view of marker layer thickness;

[0053] Figure 6 Plan view of the filling volume between the horizontal reference plane and the offset plane;

[0054] Figure 7Static calibration data planar diagram;

[0055] Figure 8 Static correction of peeling amount;

[0056] Figure 9 Offset plane starting marker layer time plan view;

[0057] Figure 10 Offset surface starting point marker layer velocity plan view;

[0058] Figure 11 is a cross-sectional view comparing the imaging effects before and after the implementation of the method in the embodiment of the present invention. Detailed Implementation

[0059] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and understanding only and are not intended to limit the present invention.

[0060] Example: A shallow velocity modeling method based on the true Earth surface

[0061] This embodiment describes a shallow velocity modeling method based on the true surface in the Gaoquan area of ​​the Junggar Basin. The test area selected in this embodiment has thick gravel, farmland, loess and other surface features. The thickness and velocity of the shallow conglomerate layer vary drastically, making it extremely difficult to accurately establish a shallow velocity model.

[0062] Based on the actual conditions of the work area, three deep micro-logging wells with a depth of 450m were deployed in the gravel Gobi area in the south, the farmland area in the north, and the transition zone to investigate the changes in shallow surface velocity. The deep micro-logging revealed the following: 1. Low-velocity conglomerate and high-velocity conglomerate strata exist in the southern and central parts of the work area, while the northern farmland area contains surface loess and normal strata; 2. The overall velocity of the low-velocity conglomerate is between 1500 and 1700 m / s, while the velocity at the top of the high-velocity conglomerate is around 2800 to 3000 m / s, with a clear vertical velocity interface; 3. The deep micro-logging revealed a good correlation between the bottom interface of the low-velocity conglomerate and the strong shallow seismic reflections.

[0063] Based on this understanding, the shallow velocity modeling was carried out in the following steps:

[0064] S1. Obtain the time plane plot T of the marker layer starting from the CMP plane. cmp

[0065] The bottom interface of low-velocity conglomerate ( Figure 1 As a shallow marker layer, the corresponding seismic reflection axis was determined through fine-tuning well seismic calibration. After fine interpretation, it was gridded to obtain the time plane map T0 of the low-velocity conglomerate bottom interface. Figure 2a The time plane diagram T0 is corrected to the starting time of the CMP surface, that is, the time plane diagram T of the marker layer starting from the CMP surface. cmp ( Figure 2b ),in,

[0066] T cmp =T0-cmp

[0067] In the formula, cmp is the low-frequency static correction amount in seismic data processing, T0 is the marker layer time plane map obtained by gridding, and T cmp The time plane diagram of the marker layer calculated from the CMP plane;

[0068] S2. Calculate the thickness D of the shallow marker layer starting from the offset surface. cmp-d

[0069] S21. Using the time-plane diagram T of the low-velocity conglomerate bottom interface cmp The velocity of the low-velocity conglomerate layer was obtained from the seismic velocity spectrum data obtained during time-domain seismic data processing, and the drilling sonic data and micro-logging velocity data obtained during the well logging process were used. Figure 3 The corrected layer velocity, the resulting marker layer velocity V iq ( Figure 4 ), where V iq The calculation of is implemented in existing software, based on the known dix formula:

[0070]

[0071] In the formula, V R,i Let t be the root mean square velocity of layers 1 to ith. 0,i The self-excitation and self-reception time of layers 1 to 1i;

[0072] S22. The thickness map of the low-velocity conglomerate bottom interface is obtained through time-depth conversion, and the thickness D is corrected using drilling stratification data obtained during well logging and micro-logging thickness data obtained during acquisition. cmp-d ( Figure 5 The time-depth conversion process is as follows:

[0073] D cmp-d =T cmp *V iq / 2000

[0074] In the formula, T cmp V is the marker layer time calculated from the CMP surface. iq The velocity of the marked layer starting from the CMP surface;

[0075] S3. Calculate the shallow marker layer time T starting from the offset surface. cmp-d

[0076] S31. Using the migration surface elevation data (800m~1600m) provided during depth-domain seismic data processing, and the filling velocity (2500m / s) and horizontal datum data (2000m) obtained during time-domain seismic data processing, calculate the filling volume ΔT0 between the horizontal datum and the migration surface. Figure 6 ),in,

[0077] △T0=(H p -H d ) / V c *2000

[0078] In the formula, H p H is the elevation of the horizontal datum plane. d V represents the elevation of the offset surface. c For filling speed;

[0079] S32. Static correction data obtained during time-domain seismic data processing. Figure 7 Subtracting ΔT0 from ΔT0 yields the static correction peeling amount ΔT. 0b ( Figure 8 ),in,

[0080] △T 0b =cmp-△T0

[0081] In the formula, △T 0b The static correction peeling amount is cmp, which is the static correction data provided by the process, and ΔT0 is the filling amount between the horizontal reference plane and the offset plane obtained in step S31.

[0082] S33. Correct the peeling amount △T 0b Time T between the low-velocity conglomerate bottom interface cmp Adding them together gives the time T from which the offset surface determined by the depth offset is calculated. cmp-d ( Figure 9 ),in,

[0083] T cmp-d =△T 0b +T cmp

[0084] In the formula, △T 0b For static correction of peeling amount, T cmp The marker layer time is calculated starting from the CMP plane;

[0085] S4. Calculate the shallow marker layer velocity V from the offset surface. i

[0086] Using the corrected thickness D cmp-d The time T calculated from the offset surface cmp-d Divide to obtain the velocity V of the low-velocity conglomerate layer starting from the offset surface. i( Figure 10 ),in,

[0087] V i =D cmp-d / T cmp-d *2000

[0088] In the formula, D cmp-d T is the thickness of the shallow marker layer calculated from the offset surface. cmp-d The time is calculated from the start of the offset plane;

[0089] S5. Calculation time T using the cmp surface cmp and marker layer velocity V i A shallow velocity model was established, and a medium-deep velocity model was established by combining it with seismic and geological data to obtain a full-depth velocity model.

[0090] The pre-stack depth migration data modeled using this method shows a significant improvement in imaging quality compared to the data before the method was implemented. Figure 11 shows a comparison of the imaging results before and after the method was applied. Figure 11a This is a cross-section before the method is implemented. Figure 11b This is a cross-section after the method was implemented;

[0091] As shown in Figure 11, the imaging effect at shallow, medium and deep depths was significantly improved after the method was implemented;

[0092] The main target layer (K) has a high degree of agreement with the drilling depth. The drilling stratification error with well 1 is 12m. After comprehensive calibration of the newly deployed wells well 2, well 3, and well 4, the pre-stack depth migration data and the drilling stratification error of the new wells are within ±50m, and the relative error is less than 0.8%. The specific data are shown in Table 1.

[0093] Table 1 Comparison and Error Analysis of Measured Drilling Depth and Imaging Depth in the Work Area

[0094]

[0095] As shown in Table 1, this method can effectively improve the imaging quality and accuracy of pre-stack depth migration.

[0096] It should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention 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 substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A shallow velocity modeling method based on the true Earth surface, characterized in that, The method includes the following steps performed sequentially: S1. Obtain the time plane plot T of the marker layer starting from the CMP plane. cmp Using time-domain seismic data and drilled well data, shallow low-velocity conglomerate marker bedding and shallow high-velocity conglomerate marker bedding were identified. The near-surface marker bedding was finely interpreted on the seismic profile, and a marker bedding time plane map T0 was obtained through gridding. Based on T0, the marker bedding time plane map T, calculated from the cmp surface, was then derived. cmp ; S2. Calculate the thickness D of the shallow marker layer starting from the offset surface. cmp-d S21. Using T cmp The marker layer velocities are obtained from the seismic velocity spectrum, and the velocity variations are constrained and corrected using drilling and micrologging data to obtain the marker layer velocities V. iq ; S22. Using T cmp and layer velocity V iq Perform time-depth transformation to obtain the marker layer thickness D. cmp-d ; S3. Calculate the shallow marker layer time T starting from the offset surface. cmp-d S31. Using the predictable offset surface data, filling speed, and horizontal reference surface data, obtain the filling amount △T0 between the horizontal reference surface and the offset surface; S32. Using the predictable static correction data and ΔT0, obtain the static correction peeling amount ΔT. 0b ; S33. Through △T 0b With T cmp The time T from the start of the offset surface is obtained. cmp-d ; S4. Calculate the shallow marker layer velocity V from the offset surface. i Using D cmp-d and T cmp-d The velocity V of the marker layer calculated from the offset surface is obtained. i ; S5. Calculation time T using the cmp surface cmp and marker layer velocity V i A shallow velocity model was established, and a medium-deep velocity model was established by combining it with seismic and geological data to obtain a full-depth velocity model.

2. The shallow velocity modeling method based on the true surface according to claim 1, characterized in that: In step S1, the time plane diagram T of the marker layer calculated from the cmp plane... cmp The calculation formula is: T cmp =T0-cmp――――――――――Formula (i) In equation (i), cmp is the low-frequency static correction amount in seismic data processing, T0 is the marker layer time plane obtained by gridding, and T cmp The time plane diagram of the marker layer, calculated from the CMP plane.

3. The shallow velocity modeling method based on the true surface according to claim 1, characterized in that: In step S22, the thickness D of the marker layer cmp-d The calculation formula is: D cmp-d =T cmp *V iq / 2000――――――――――Form (ii) In equation (ii), T cmp V is the marker layer time calculated from the CMP surface. iq The velocity of the marked layer is calculated starting from the CMP surface.

4. The shallow velocity modeling method based on the true surface according to claim 1, characterized in that: In step S31, the formula for calculating the filling amount ΔT0 is: △T0=(H p -H d ) / V c *2000――――――――――Form (ⅲ) In equation (iii), H p H is the elevation of the horizontal datum plane. d V represents the elevation of the offset surface. c This refers to the filling speed.

5. The shallow velocity modeling method based on the true surface according to claim 1, characterized in that: In step S32, the static correction peeling amount ΔT 0b The calculation formula is: △T 0b = cmp - △T0―――――――――――Equation (ⅳ) In equation (iv), △T 0b The static correction peeling amount is denoted by cmp, which is the static correction data provided by the processing, and ΔT0 is the filling amount between the horizontal reference plane and the offset plane obtained in step S31.

6. The shallow velocity modeling method based on the true surface according to claim 1, characterized in that: In step S33, the time T from which the offset surface is calculated is... cmp-d The calculation formula is: T cmp-d =△T 0b +T cmp ――――――――――Form (ⅴ) In equation (v), △T 0b For static correction of peeling amount, T cmp The marker layer time is calculated starting from the CMP surface.

7. The shallow velocity modeling method based on the true surface according to claim 1, characterized in that: In step S4, the marker layer velocity V calculated from the offset surface... i The calculation formula is: V i =D cmp-d / T cmp-d *2000――――――――――Formula (ⅵ) In equation (ⅵ), D cmp-d T is the thickness of the shallow marker layer calculated from the offset surface. cmp-d The time is calculated from the offset plane.

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