Depth migration phase control velocity inversion modeling method in complex sedimentary environment

Abstract

The invention discloses a depth migration phase control velocity inversion modeling method in a complex sedimentary environment. The method comprises the following steps: constructing an initial depth domain interval velocity model; obtaining a CIP gather and superposition data thereof; obtaining a residual velocity field, and updating the velocity model; iteratively updating the speed model to obtain an intermediate speed model; obtaining intermediate pre-stack depth migration imaging result data; forming a sedimentary facies boundary constraint file; and on the basis of the intermediate velocity model, sedimentary facies control is carried out on the inversion process and result through a sedimentary facies boundary constraint file, and a final pre-stack depth migration layer velocity model is obtained through multiple iterations. On the basis of a chromatography velocity inversion technology, a sedimentary facies model and a velocity model are fused, and phase control velocity model inversion modeling of a complex sedimentary environment is achieved; the consistency of the constructed velocity model and the sedimentary facies model is better, the pre-stack depth migration imaging quality corresponding to the velocity model constructed based on the method is better, and homing is more accurate.

Description

Technical Field

[0001] The invention belongs to the field of oil and gas exploration and development, and in particular relates to a deep migration phase-controlled velocity inversion modeling method under a complex sedimentary environment. Background Art

[0002] Prestack depth migration is one of the main means of seismic imaging today. The depth domain layer velocity model required for migration is a key factor affecting the quality of imaging. The existing depth domain velocity model is constructed by using the tomographic velocity inversion method, which is data-driven and obtains the best depth domain layer velocity model after multiple rounds of iterations. The tomographic velocity inversion method is efficient in constructing the depth domain layer velocity model, but there are still the following problems in practical applications: 1) The existing technical solution is only applicable to seismic data with a high signal-to-noise ratio. When the signal-to-noise ratio of seismic data is low, the existing technology will analyze the noise signal as an effective signal to a certain extent, and the constructed velocity model is more conducive to the imaging of the noise signal. 2) When the sedimentary diagenetic environment in the study area is complex and changeable, in the seismic phase analysis, some geological body envelopes have strong reflection interfaces, and the inner wall often presents messy or blank reflections. The existing technical solution cannot pick up the effective reflection signal of the inner wall of the geological body, which affects the accuracy of velocity modeling and thus affects the quality of seismic imaging. Summary of the invention

[0003] The present invention is proposed to solve the problem of uncontrollable results when using data-driven velocity inversion for low signal-to-noise ratio data and the problem of inaccurate velocity modeling in complex sedimentary environments. Its purpose is to provide a depth migration phase-controlled velocity inversion modeling method in complex sedimentary environments.

[0004] The present invention is achieved through the following technical solutions:

[0005] A method for depth migration phase-controlled velocity inversion modeling in a complex sedimentary environment includes the following steps:

[0006] S1. Acquire the time-domain processed seismic data volume and the pre-stack time migration velocity data volume, and construct an initial depth-domain layer velocity model;

[0007] S2, carry out pre-stack depth grid point migration to obtain CIP gathers and their stacking data; among them, grid S1, obtains time domain processed seismic data volume and pre-stack time migration velocity data volume, and constructs initial depth domain layer velocity model;

[0008] S2. Carry out pre-stack depth grid point migration to obtain CIP gathers and their stacking data;

[0009] S3, using the CIP gathers obtained in step S2 and the stacked data thereof, conventional tomographic velocity inversion technology is used to carry out high-precision grid tomographic velocity inversion, obtain the residual velocity field, and update the depth domain layer velocity model;

[0010] S4, repeating steps S2 and S3 for multiple times to iteratively update the depth domain layer velocity model until the obtained CIP gather event axes are basically flattened, and a set of stable velocity models is obtained as the intermediate depth domain layer velocity model;

[0011] S5. Use the intermediate depth domain layer velocity model obtained in S4 to carry out pre-stack depth migration. After stacking, time-depth conversion, post-stack denoising, frequency enhancement and energy compensation, the intermediate pre-stack depth migration imaging data is obtained.

[0012] S6. Carry out geological analysis based on the intermediate data obtained in step S5, identify the seismic phase of the basin according to the characteristics of the seismic profile, systematically determine its possible sedimentary phase types, determine the distribution range, trace the interpretation boundary, and form a sedimentary phase boundary constraint file;

[0013] S7. Based on the intermediate depth domain layer velocity model obtained in step S4, steps S2 and S3 are repeated. The sedimentary phase boundary constraint file obtained in step S6 is added to the high-precision grid tomography velocity inversion process, and sedimentary phase control is implemented on the inversion process and results. After multiple iterations, the final pre-stack depth migration layer velocity model is obtained.

[0014] In the above technical solution, the depth domain layer velocity model constructed by the pre-stack time migration velocity is further interpolated, smoothed and time-to-depth converted.

[0015] In the above technical solution, the input data used for conventional tomographic velocity inversion in step S3 is the CIP gathers and their superimposed data obtained in step S2. The CIP gather data after optimization processing is used for residual velocity spectrum calculation, and the superimposed data of the CIP gathers is used for structural dip parameter analysis.

[0016] In the above technical solution, the deposition types include fan delta phase, braided river delta phase, alluvial fan phase and gravity flow deposition phase.

[0017] In the above technical solution, the sedimentary phase control includes a tomographic inversion method adding phase control file constraints and a sedimentary phase constraint correction method for the inversion result.

[0018] In the above technical solution, the number of iterations in step S7 is three or four times.

[0019] In the above technical solution, during the iteration process of step S7, when the external geometric shape and internal reflection structure imaging of the target geological body change significantly, steps S5 and S6 are repeated to re-analyze the sedimentary phase and improve the boundary constraint file.

[0020] The beneficial effects of the present invention are:

[0021] The present invention provides a method for phase-controlled velocity inversion modeling of depth migration under complex sedimentary environment, realizes phase control in the velocity inversion process, integrates sedimentary phase analysis with tomographic velocity inversion, and is suitable for deep domain layer velocity inversion modeling of seismic data processing under complex geological conditions (especially turbidite fan bodies such as slump turbidite fan, nearshore underwater fan, fan delta, etc.). The present invention can effectively solve the problem of inaccurate velocity modeling in complex sedimentary environment, and the constructed velocity model has better consistency with sedimentary phase characteristics, thereby improving the quality of pre-stack depth migration imaging. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a schematic flow diagram of the method of the present invention;

[0023] Figure 2 It is the initial depth domain layer velocity model diagram in the present invention;

[0024] Figure 3 It is a layer velocity model diagram in the intermediate depth domain constructed by the conventional tomographic inversion technology in the present invention;

[0025] Figure 4 It is the top and bottom envelope morphology diagram of the fan body tracked by geological analysis in the present invention;

[0026] Figure 5 It is a quality control constraint file diagram formed by the fan body envelope in the present invention;

[0027] Figure 6 It is a depth domain layer velocity model diagram of phase-controlled tomography velocity inversion obtained based on the technical solution of the present invention;

[0028] Figure 7 This is a comparison between conventional tomography inversion depth domain layer velocity model migration imaging (left) and phase-controlled tomography velocity inversion depth domain layer velocity model migration imaging (right).

[0029] For ordinary technicians in this field, other relevant drawings can be obtained based on the above drawings without any creative work. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention is further described below with reference to the accompanying drawings and through specific implementation methods.

[0031] like Figure 1 As shown, a method for depth migration phase-controlled velocity inversion modeling in a complex sedimentary environment includes the following steps:

[0032] S1. Obtain the time domain processed seismic data volume and the pre-stack time migration velocity data volume, convert the pre-stack time migration velocity into layer velocity using the DIX formula, and generate an initial depth domain layer velocity model through interpolation, smoothing and time-depth conversion. The obtained initial depth domain layer velocity model is as follows: Figure 2 As shown;

[0033] S2. Use the time-domain processed seismic data volume and the initial depth-domain layer velocity model to carry out pre-stack depth grid point migration to obtain CIP (Common Imaging Point) gathers and their stacking data; the grid point migration bin size is consistent with the initial depth-domain layer velocity model, and the obtained CIP gathers need to be optimized by denoising, amplitude compensation and other processes;

[0034] S3. Use conventional tomographic velocity inversion technology to carry out high-precision grid tomographic velocity inversion, obtain the residual velocity field, and update the depth domain layer velocity model;

[0035] The input data used for conventional tomographic velocity inversion is the CIP gathers and their stacked data obtained in step S2. The CIP gather data after optimization is used for residual velocity spectrum calculation, and the stacked data of the CIP gathers is used for structural dip parameter analysis.

[0036] S4, repeating steps S2 and S3 for multiple times to iteratively update the velocity model until the event axes of the obtained CIP gathers are basically flattened, and a set of stable velocity models is obtained as the velocity model of the intermediate depth domain layer;

[0037] The stability of the velocity model is mainly determined by the flattening degree of the CIP gather event axis after migration. In general, the conventional tomographic inversion method driven by data is used. After three or four rounds of iteration, the event axis of the gather is basically flattened, and the overall spatial structure of the velocity model is basically stable. The intermediate depth domain layer velocity model is obtained as follows: Figure 3 ;

[0038] S5. Using the intermediate depth domain layer velocity model obtained in S4, prestack depth migration is carried out to generate common offset data, which are then extracted to form common imaging point data (CIP) and stacked. Post-stack denoising, frequency enhancement and energy compensation are then performed to improve the signal-to-noise ratio of the depth migration imaging data, thus obtaining intermediate prestack depth migration imaging data.

[0039] S6. Carry out geological analysis based on the intermediate data obtained in step S5;

[0040] Based on the amplitude, phase and frequency characteristics of the seismic profile, we can identify the seismic facies of the basin, systematically determine the possible sedimentary facies types, determine the distribution range, trace the interpretation boundaries, and form sedimentary facies boundary constraint files;

[0041] This method is mainly used for geological bodies with disordered or blank internal structures in seismic reflection, and the corresponding main sedimentary types are: fan delta phase, braided river delta phase, alluvial fan phase and gravity flow sedimentary phase;

[0042] The top and bottom envelope morphology of the fan body tracked by geological analysis in this embodiment is shown in the figure below. Figure 4 As shown in the figure, the three groups of turbidite fans overlap in space and develop successively. The sedimentary facies boundary constraint files are as follows: Figure 5 As shown;

[0043] S7, based on the intermediate depth domain layer velocity model obtained in step S4, repeat steps S2 and S3, add the sedimentary phase boundary constraint file in the high-precision grid tomography velocity inversion process, implement sedimentary phase control on the inversion process and results, and obtain the final pre-stack depth migration layer velocity model ( Figure 6 ).

[0044] The sedimentary phase control includes a tomographic inversion method adding phase control file constraints and a sedimentary phase constraint correction method for the inversion result.

[0045] Three or four rounds of inversion iterations are sufficient. During the process, the interpolated velocity value is adjusted in each round to improve the accuracy of the velocity model. When the external geometry of the target geological body and the internal reflection structure imaging change significantly, it is necessary to repeat steps S5 and S6, re-analyze the sedimentary phase, and improve the boundary constraint file.

[0046] The result section of the conventional tomographic inversion depth domain layer velocity model migration imaging is as follows Figure 7 As shown on the left, the result section of the phase-controlled tomography inversion depth domain layer velocity model migration imaging in this embodiment is as follows Figure 7 As shown on the right, compared with the conventional method, the cross-section sector boundary and interior imaging obtained by the method of this embodiment are clearer, and the boundary fracture imaging effect is significantly improved.

[0047] The applicant declares that the above is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention shall fall within the protection scope and disclosure scope of the present invention.

Claims

1. A method for depth migration phase-controlled velocity inversion modeling in a complex sedimentary environment, characterized by: The following steps are involved: S1. Acquire the time-domain processed seismic data volume and the pre-stack time migration velocity data volume, and construct an initial depth-domain layer velocity model; S2. Carry out pre-stack depth grid point migration to obtain CIP gathers and their stacking data; S3, using the CIP gathers obtained in step S2 and the stacked data thereof, conventional tomographic velocity inversion technology is used to carry out high-precision grid tomographic velocity inversion, obtain the residual velocity field, and update the depth domain layer velocity model; S4, repeating steps S2 and S3 for multiple times to iteratively update the depth domain layer velocity model until the obtained CIP gather event axes are basically flattened, and a set of stable velocity models is obtained as the intermediate depth domain layer velocity model; S5. Use the intermediate depth domain layer velocity model obtained in S4 to carry out pre-stack depth migration. After stacking, time-depth conversion, post-stack denoising, frequency enhancement and energy compensation, the intermediate pre-stack depth migration imaging data is obtained. S6. Carry out geological analysis based on the intermediate data obtained in step S5, identify the seismic phase of the basin according to the characteristics of the seismic profile, systematically determine its possible sedimentary phase types, determine the distribution range, trace the interpretation boundary, and form a sedimentary phase boundary constraint file; S7. Based on the intermediate depth domain layer velocity model obtained in step S4, steps S2 and S3 are repeated. The sedimentary phase boundary constraint file obtained in step S6 is added to the high-precision grid tomography velocity inversion process, and sedimentary phase control is implemented on the inversion process and results. After multiple iterations, the final pre-stack depth migration layer velocity model is obtained.

2. The method for depth migration phase-controlled velocity inversion modeling in a complex sedimentary environment according to claim 1, characterized in that: The depth domain layer velocity model constructed by the pre-stack time migration velocity is further interpolated, smoothed and time-to-depth converted.

3. The method for depth migration phase-controlled velocity inversion modeling in a complex sedimentary environment according to claim 1, characterized in that: The input data used for conventional tomographic velocity inversion in step S3 is the CIP gathers and their superimposed data obtained in step S2. The CIP gather data after optimization is used for residual velocity spectrum calculation, and the superimposed data of the CIP gathers is used for structural dip parameter analysis.

4. The method for depth migration phase-controlled velocity inversion modeling in a complex sedimentary environment according to claim 1, characterized in that: The sedimentary types include fan delta facies, braided river delta facies, alluvial fan facies and gravity flow sedimentary facies.

5. The method for depth migration phase-controlled velocity inversion modeling in a complex sedimentary environment according to claim 1, characterized in that: The sedimentary phase control includes a tomographic inversion method adding phase control file constraints and a sedimentary phase constraint correction method for the inversion result.

6. The method for depth migration phase-controlled velocity inversion modeling in a complex sedimentary environment according to claim 1, characterized in that: The number of iterations in step S7 is three or four.

7. The method for phase-controlled velocity inversion modeling for depth migration in a complex sedimentary environment according to claim 1, characterized in that: During the iteration process of step S7, when the external geometric shape and internal reflection structure imaging of the target geological body change significantly, steps S5 and S6 are repeated to re-analyze the sedimentary phase and improve the boundary constraint file.

8. The method for phase-controlled velocity inversion modeling for depth migration in a complex sedimentary environment according to claim 1, characterized in that: The grid point offset bin size in step S2 is consistent with the depth domain layer velocity model, and the obtained CIP gather is subjected to denoising and amplitude compensation optimization processing.

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