A high-precision velocity modeling method for deep-water deep reservoirs

Abstract

The present application relates to the field of oil and gas seismic exploration technology, more particularly, it relates to a high-precision velocity modeling method for deep water deep reservoirs, the present application is mainly aimed at the deep water deep reservoir depth prediction in the area with few wells, after the quality evaluation of the seismic data of the target area, the present application optimizes part of the seismic data as the basic data for research, on the basis of the fine construction of the geological model, the selection of regional velocity marker layer, well-seismic calibration, velocity main control factor analysis and seismic velocity body optimization, the high-precision velocity modeling fine research is carried out, so as to realize the accurate prediction of the reservoir depth in the deep water deep area with few wells or no well area. The present application strictly improves the fine degree of each step of modeling, the key is to add the change of reservoir physical properties as the main control factor of regional velocity into the seismic velocity body optimization work, compared with the original seismic velocity body, more velocity details matched with the logging data are added, which is beneficial to improve the prediction accuracy of the final velocity model.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas seismic exploration, and more specifically, to a high-precision velocity modeling method for deep-water deep reservoirs. Background Art

[0002] In the process of oil and gas exploration, time-depth conversion is an important bridge connecting seismic data in the time domain and geological structures. The accuracy of velocity calculation directly affects the accuracy of time-depth conversion results, and has an important impact on various links such as structural evaluation, drilling design, and depth prediction. Therefore, finding a velocity research method suitable for the structures and geological conditions of the study area is the key to promoting oil and gas exploration evaluation. Currently, the commonly used velocity research methods mainly include: VSP fitting formula method, constant velocity stripping method, cross-well interpolation method, stacking velocity, migration velocity conversion method, and well-seismic joint velocity modeling method, etc. In the existing velocity modeling technologies, it is difficult to meet the requirements of three-dimensional fine time-depth conversion by simply using logging velocity or seismic processing velocity. The velocity field constructed by the seismic-based velocity modeling method has good lateral continuity, but what is obtained are all low-frequency trends of velocity, and the vertical accuracy needs to be further improved; the velocity field established by the logging-based velocity modeling method has high accuracy near the drilled wells, but the reliability of the velocity between wells is poor; therefore, the full combination of logging and seismic velocities is the development trend to improve the fineness of the three-dimensional velocity model. Currently, the most commonly used method in the process of structural interpretation is the well-seismic joint velocity modeling method, which uses seismic interpretation horizons and the processed migration velocity field as constraints to extrapolate to obtain a layered three-dimensional variable velocity field. This method makes full use of the vertical information of wells and the extended information of seismic data, and has strong applicability.

[0003] When the study area is located directly below the rugged submarine slope break zone in deep water and has a large burial depth, it belongs to a deep-water deep gas field. Affected by the rugged submarine slope break zone, the water depth of the deep-water deep gas field changes greatly, extending from 600 m water depth to 1600 m. The combined influence of water velocity and formation velocity results in a relatively large average velocity in the shallow water area and a relatively small average velocity in the deep water area. Therefore, the time structure cannot reflect the true structural form. The deep-water deep gas field is located in the deep water area. Limited by economic costs and engineering difficulties, there are few drilled wells, and the well control area per single well is too large (about 100 km 2 / well), and the uncertainty of time-depth conversion in the area with few or no well controls is relatively large.

[0004] With the progress of seismic processing technology in recent years, the accuracy of seismic velocity volumes has been greatly improved. However, seismic velocity volumes mainly reflect regional velocity trends or local large-scale velocity anomalies, and there is a large gap compared with the accuracy of logging data. The main characteristics of deep-water deep gas fields are poor reservoir physical properties and a sudden increase in formation velocity relative to the overlying strata. Therefore, it is difficult to predict the detailed characteristics of reservoir velocity mutations only by using seismic velocity volumes. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of current methods that rely solely on seismic velocity volumes to predict the detailed characteristics of abrupt velocity changes in deep-water reservoirs, and to provide a high-precision velocity modeling method for deep-water reservoirs. This invention incorporates regional velocity-controlling factors with sedimentary facies understanding into the accuracy optimization of seismic velocity volumes, effectively predicting reservoir depths in deep-water reservoirs with few or no wells.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0007] A high-precision velocity modeling method for deep-water deep reservoirs includes the following steps:

[0008] Quality assessment of seismic data in the target area and selection of basic data;

[0009] Based on the selected basic data, select and determine the in-phase axis that can be stably tracked in space, is widely distributed, and whose actual burial depth can be determined by well logging data as the regional velocity marker layer;

[0010] By combining the selected basic data and the determined regional velocity marker layer, a fine well-seismic calibration of the regional velocity marker layer was carried out, and the well-seismic calibration results were obtained.

[0011] Seismic interpretation of regional velocity marker layers was carried out based on well seismic calibration results;

[0012] Construct a three-dimensional geological model based on the identified regional marker layers;

[0013] Based on the selected basic data, the seismic velocity volume corresponding to the basic data is selected as the basic data for velocity research;

[0014] Comparative analysis was conducted between the actual drilling sonic velocity curves and the seismic velocity curves of the wellbore surroundings, and reconstructed seismic velocity curves for the entire well section were obtained.

[0015] Analyze the main controlling factors of regional velocity by combining well logging curves, well logging data and geological conditions;

[0016] Based on the analysis results of the main velocity controlling factors in the region, a planar distribution pattern of the main velocity controlling factors in the reservoir section was drawn.

[0017] Under the constraint of the selected seismic velocity volume, the three-dimensional spatial interpolation of the reconstructed seismic velocity curve throughout the well section is controlled by the physical property plane distribution law to obtain a three-dimensional phase-controlled interpolated velocity volume with higher velocity accuracy and consistent with the main regional velocity control factors.

[0018] The planar velocity grid of the three-dimensional phased interpolation velocity volume is extracted along the regional velocity marker layer. The depth grid is obtained by multiplying the planar velocity grid with the time of the regional velocity marker layer. The depth value is obtained by back-cutting the depth grid along the well point. The error value between the depth value and the actual drilling depth is calculated and a planar error grid is formed. The three-dimensional phased interpolation velocity volume is corrected by the error grid corresponding to each regional velocity marker layer to eliminate residual errors. Finally, a high-precision seismic velocity model is obtained, and time-depth conversion is carried out.

[0019] It should be noted that the target area in this invention is a deep-water deep reservoir, and all steps in this invention can be processed using Petrel software.

[0020] It should also be noted that this invention primarily targets reservoir depth prediction in deep-water, deep-seated areas with few wells. After quality assessment of seismic data from the target area, this invention selects a subset of seismic data as the foundation for research. Based on refined geological model construction, selection of regional velocity marker layers, well-seismic calibration, analysis of key velocity control factors, and optimization of the seismic velocity volume, high-precision velocity modeling and detailed research are conducted to achieve accurate prediction of reservoir depth in deep-water, deep-seated areas with few or no wells. This invention rigorously improves the precision of each modeling step, focusing on incorporating reservoir property variations as key regional velocity control factors into the seismic velocity volume optimization process. Compared to the original seismic velocity volume, it adds more velocity details that match well logging data, which helps improve the prediction accuracy of the final velocity model. Compared to existing technologies, this invention combines regional velocity control factors with sedimentary facies understanding into the accuracy optimization of the seismic velocity volume, effectively predicting reservoir depth in deep-water, deep-seated areas with few or no wells.

[0021] Furthermore, the selection of basic data involves evaluating the quality of seismic data by comparing seismic resolution, signal-to-noise ratio, and imaging accuracy, and selecting seismic data with good imaging quality as the basic data for the study. It should be noted that among the existing batches of seismic data, the quality of geological data is distinguished by comparison with each other. Data with high seismic resolution, high signal-to-noise ratio, and clear imaging are preferred, such as those with easier fault section identification and better continuity of phase axes, and the comparison results are used as the method for judging the quality.

[0022] Furthermore, the regional velocity marker layers are selected from the seafloor reflector, the adjacent strata above the reservoir, and the adjacent strata below the reservoir in the deep water area.

[0023] Furthermore, the regional velocity marker layer is the reservoir region, and the regions above and below the reservoir are adjacent marker layers. The seismic interpretation density of the adjacent marker layers is consistent with that of the seismic interpretation of the reservoir region.

[0024] Furthermore, the density can be interpreted as: Main survey line * Connecting survey line = 120m * 120m ~ 130m * 130m. It should be noted that in seismic exploration, the main survey line refers to a profile perpendicular to the regional tectonic strike; while the connecting survey line refers to a profile parallel to the regional tectonic strike.

[0025] Furthermore, when constructing a three-dimensional geological model, the time of the regional velocity marker layers should be arranged from top to bottom.

[0026] Furthermore, the mesh size of the 3D geological model is set to between 180*180 and 220*220. Limiting the mesh size to this range is for computational speed considerations; a mesh size of 180*180 to 220*220 is preferable.

[0027] Furthermore, the acquisition of the reconstructed seismic velocity curve for the entire well area is achieved by using the seismic velocity curve to fill in the shallow missing part of the actual drilling sonic velocity curve, under the condition that the overall seismic velocity trend is basically consistent. The completed actual drilling sonic velocity curve is then sampled into the three-dimensional geological model for coarsening. The coarsened velocity curve of the well passage is then extracted from the three-dimensional geological model. This allows us to obtain the reconstructed seismic velocity curve for the entire well section that can simultaneously reflect the regional velocity trend and the local velocity details of the well logging.

[0028] Furthermore, the primary controlling factor for regional velocity is physical properties. It should be noted that the target area analysis suggests that deep-water, deep-layer reservoirs are affected by burial depth and belong to fan delta deposits. Areas with poor physical properties correspond to high-velocity zones, while areas with good physical properties correspond to low-velocity zones. Therefore, physical properties and velocity have a good correlation.

[0029] Furthermore, based on the physical property data of the main regional velocity control factors, a planar distribution pattern of reservoir physical properties is drawn from the fan root to the leading edge according to the geological sedimentary facies diagram.

[0030] Compared with the prior art, the beneficial effects of the present invention are:

[0031] (1) This invention is mainly aimed at the prediction of reservoir depth in deep water and deep layers with few wells. After evaluating the quality of seismic data in the target area, this invention selects a portion of the seismic data as the basic data for research. Based on the fine construction of geological models, selection of regional velocity marker layers, well-seismic calibration, analysis of velocity control factors, and optimization of seismic velocity volume, high-precision velocity modeling and fine research are carried out to achieve the goal of accurate prediction of reservoir depth in deep water and deep layers with few or no wells.

[0032] (2) This invention rigorously improves the level of modeling at each step. The key is to incorporate reservoir property changes as the main regional velocity control factor into the seismic velocity volume optimization work. Compared with the original seismic velocity volume, it adds more velocity details that match the well logging data, which is conducive to improving the prediction accuracy of the final velocity model. Compared with the prior art, this invention incorporates the main regional velocity control factor into the accuracy optimization of the seismic velocity volume in combination with sedimentary facies knowledge. It can effectively predict the reservoir depth in deep water, deep layers, areas with few or no wells. Attached Figure Description

[0033] Figure 1 This is a flowchart illustrating the steps of an embodiment of the present invention;

[0034] Figure 2 This is a diagram illustrating the construction of a three-dimensional geological model according to an embodiment of the present invention.

[0035] Figure 3 This is a comparison chart of the actual drilling speed curve and the seismic speed curve in an embodiment of the present invention;

[0036] Figure 4 This is a comparison chart of the actual drilling speed curve and the reconstructed seismic speed curve in an embodiment of the present invention;

[0037] Figure 5 This is a schematic diagram of the planar distribution of reservoir layer velocities before the pre-stack depth migration velocity volume is corrected according to the velocity master control factor in this embodiment of the invention;

[0038] Figure 6 This is a schematic diagram of the planar distribution of reservoir layer velocities in the three-dimensional phase-controlled interpolation velocity volume after correction of the main velocity control factor in an embodiment of the present invention.

[0039] Figure 7 This is a schematic cross-sectional view of the reservoir layer velocity before the pre-stack depth migration velocity body is corrected according to the velocity master control factor in an embodiment of the present invention.

[0040] Figure 8 This is a schematic cross-sectional view of the reservoir layer velocity after the correction of the main velocity control factor in an embodiment of the present invention. Detailed Implementation

[0041] The present invention will be further described below with reference to specific embodiments. The accompanying drawings are for illustrative purposes only, representing schematic diagrams rather than actual physical objects, and should not be construed as limiting the scope of this patent. To better illustrate the embodiments of the present invention, some components in the drawings may be omitted, enlarged, or reduced, and do not represent the actual dimensions of the product. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0042] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present patent. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0043] Example 1

[0044] like Figures 1 to 8 The first embodiment of the present invention is shown, a high-precision velocity modeling method for deep-water deep reservoirs, which specifically includes the following steps:

[0045] like Figure 1 As shown, the quality of seismic data in the target area was assessed and basic data was selected. The quality of seismic data was assessed by comparing seismic resolution, signal-to-noise ratio and imaging accuracy, and seismic data with good imaging quality was selected as the basic data for the study.

[0046] Specifically, in this embodiment, the target area is a deep-water deep reservoir;

[0047] More specifically, since pre-stack depth migration (PSM) has a much higher imaging accuracy in complex areas than conventional migration methods, it can better achieve effective imaging of deep-water reservoirs. Therefore, PSM seismic data is used as the evaluation content, and PSM seismic data with good imaging quality is selected as the basic data for the study. Specifically, in this embodiment, the bandwidth of the target layer in the PSM seismic data target area is 4-42Hz, the dominant frequency is 20Hz, the layer velocity of the target layer is 4000m / s, and the seismic resolution is calculated according to quarter wavelength. The seismic resolution of the target layer in the target area is 50m. Since the reservoir thickness is greater than 80m, this batch of data meets the research requirements.

[0048] like Figure 1 As shown, based on the selected basic data, the in-phase axes that can be stably tracked in space, are widely distributed, and whose actual burial depth can be determined by well logging data are selected as regional velocity marker layers; specifically, the regional velocity marker layers are selected from the seafloor reflector layer, the adjacent formation above the reservoir, and the adjacent formation below the reservoir in the deep water area.

[0049] More specifically, the seafloor reflector layer T00 is used as the top layer of the geological model because, compared to other layers, T00 has the highest accuracy in time-depth conversion, which is better able to control the impact of seawater depth changes on velocity. Near the reservoir, thick mudstone deposits are predominant, and the seismic reflection characteristics are not obvious, which is not conducive to regional stratigraphic tracking. In order to control the longitudinal and lateral changes in sand body velocity, the adjacent strata T52 above the reservoir and the adjacent strata T70 below the reservoir, which are closest to the reservoir and have strong seismic reflection characteristics, were selected.

[0050] like Figure 1 As shown, by combining the selected basic data and the determined regional velocity marker layer, fine well-seismic calibration of the regional velocity marker layer is carried out, and the well-seismic calibration results are obtained.

[0051] like Figure 1 As shown, seismic interpretation of regional velocity marker layers is carried out based on well-seismic calibration results. Specifically, the regional velocity marker layer is the reservoir area, and the areas above and below the reservoir are adjacent marker layers. The seismic interpretation density of adjacent marker layers is consistent with that of the reservoir area. The interpretation density is: main survey line * connecting survey line = 125m * 125m. It should be noted that in seismic exploration, the main survey line refers to the profile perpendicular to the regional structural strike, while the connecting survey line refers to the profile parallel to the regional structural strike.

[0052] More specifically, the seafloor reflector T00 is the reservoir region, and the adjacent strata T52 above the reservoir and T70 below the reservoir are the adjacent marker layers. Seismic interpretation is performed on the seafloor reflector T00, the adjacent strata T52 above the reservoir, and the adjacent strata T70 below the reservoir as adjacent marker layers, and a time-domain structural grid data of 125m*125m is formed by the main survey line * connecting survey line.

[0053] like Figure 1 As shown, a three-dimensional geological model is constructed based on the determined regional marker layers. Specifically, the three-dimensional geological model should be constructed by sorting the regional velocity marker layers from top to bottom according to their time. The grid size of the three-dimensional geological model is 200 x 200. Setting the grid size of the three-dimensional geological model to 200 x 200 is for computational speed considerations; a grid size of 200 x 200 is preferable for the model.

[0054] More specifically, such as Figure 2As shown, a three-dimensional geological model of the gas field is established based on the time-domain structural grid data of the selected regional velocity marker layers. The marker layers are arranged from top to bottom in terms of time (i.e., the seafloor reflector T00, the adjacent strata above the reservoir T52, and the adjacent strata below the reservoir T70). Each marker layer has the same area and covers the entire gas field. The three-dimensional grid size of the geological model is 200*200. At this point, the geological model is a large framework, and further refinement of the framework is needed for the internal structure of different layers. The seafloor reflector T00 is interpolated proportionally to the adjacent strata above the reservoir T52 and the adjacent strata below the reservoir T70. The interpolation interval of the seafloor reflector T00 should be the same as the seismic resolution.

[0055] like Figure 1 As shown, the seismic velocity body corresponding to the selected basic data is chosen as the basic data for velocity research.

[0056] More specifically, after selecting the pre-stack depth migration data, the corresponding pre-stack depth migration velocity volume is selected as the basis for the study.

[0057] like Figure 1 As shown, a comparative analysis was conducted between the actual drilling sonic velocity curve and the wellbore seismic velocity curve, and the reconstructed seismic velocity curve for the entire well section was obtained. Specifically, the reconstructed seismic velocity curve for the entire well area was obtained by using the seismic velocity curve to fill in the shallow missing part of the actual drilling sonic velocity curve, under the condition that the overall seismic velocity trend is basically consistent. The completed actual drilling sonic velocity curve was then sampled into a three-dimensional geological model for coarsening. The wellbore coarsened velocity curve was then extracted from the three-dimensional geological model, thus obtaining the reconstructed seismic velocity curve for the entire well section that can simultaneously reflect the regional velocity trend and the local velocity details of the well logging.

[0058] More specifically, such as Figure 3 and Figure 4 As shown, the study on the reconstruction of seismic velocity curves for the entire well section shows that the overall velocity trend of the seismic velocity curves and the actual drilling velocity curves is consistent. However, in the reservoir section, the actual drilling velocity, while maintaining the velocity trend, has added local velocity anomalies that are difficult to characterize by the seismic velocity. The maximum velocity difference between the two is close to 200 m / s. Therefore, based on the characteristic that the overall trends of the two velocity curves are basically consistent, the seismic velocity curves are used to fill in the missing segments of the actual drilling velocity. The completed velocity curves are then sampled into a three-dimensional geological model for coarsening. Finally, the coarsened velocity curves of the wellbore passages are extracted from the three-dimensional geological model to obtain the reconstructed seismic velocity curves for the entire well section that can simultaneously reflect the regional velocity trend and the local velocity details of the well logging.

[0059] like Figure 1As shown, the main controlling factors of regional velocity are analyzed by combining well logging curves, well logging data and geological conditions; specifically, the main controlling factor of regional velocity is physical properties; it should be noted that the target area analysis believes that the deep water deep reservoir is affected by the burial depth and belongs to the fan delta deposition, and the area with poor physical properties corresponds to the high velocity area and the area with good physical properties corresponds to the low velocity area. Therefore, physical properties and velocity have a good correlation.

[0060] like Figure 1 As shown, based on the analysis results of the main velocity control factors in the region, a planar distribution pattern of the main velocity control factors in the reservoir section is drawn; specifically, based on the physical property data in the main velocity control factors in the region, a planar distribution pattern of the physical properties of the reservoir section is drawn from the fan root to the leading edge according to the geological sedimentary facies diagram.

[0061] like Figure 1 As shown, under the constraint of the selected seismic velocity volume, the three-dimensional spatial interpolation of the reconstructed seismic velocity curve throughout the well section is controlled by the physical property plane distribution law to obtain a three-dimensional phase-controlled interpolated velocity volume with higher velocity accuracy and consistent with the main regional velocity control factors.

[0062] More specifically, such as Figure 5 and Figure 7 As shown, since the target area is a fan delta deposit located directly below a rugged deep-water seafloor slope break, the overlying strata at the fan root are thick and subject to strong compaction, while the overlying strata at the fan tip are thin and subject to weak compaction. Actual drilling data show that permeability and porosity are lower at the fan root and better at the fan tip. Therefore, this study selected to draw a reservoir property distribution map along the sedimentary facies distribution. Based on this, the pre-stack depth-migrated seismic velocity volume was used as a spatial trend constraint to perform kriging three-dimensional spatial interpolation on the actual drilling velocity curves. The reservoir property distribution map was used as a reservoir segment velocity interpolation trend constraint to complete the pre-stack depth-migrated seismic velocity volume optimization.

[0063] like Figure 1 As shown, the planar velocity grid of the three-dimensional phased interpolation velocity volume is extracted along the regional velocity marker layer. The depth grid is obtained by multiplying the planar velocity grid with the time of the regional velocity marker layer. The corresponding depth value is obtained by back-cutting the depth grid along the well point. The error value between the depth value and the actual drilling depth is calculated and a planar error grid is formed. The three-dimensional phased interpolation velocity volume is corrected by the error grid corresponding to each regional velocity marker layer to eliminate residual errors. Finally, a high-precision seismic velocity model is obtained, and time-depth conversion work is carried out.

[0064] More specifically, such as Figure 6 and Figure 8As shown, the regional velocity marker layers are selected from stably trackable layers in the region (such as the seafloor reflector T00, the adjacent strata above the reservoir T52, and the adjacent strata below the reservoir T70), which respectively control the velocity variations of water depth, overlying strata, and reservoir segments. The regional marker layer wellpoint velocity correction is obtained from the time-depth data of the three regional velocity marker layers. The velocity correction is interpolated under the control of the geological model using a convergent interpolation algorithm to correct the pre-stack depth migration seismic velocity volume and establish an accurate three-dimensional velocity model that varies along the reflector layer, thereby achieving accurate time-depth conversion of three-dimensional seismic data.

[0065] All steps in this embodiment are processed using Petrel software.

[0066] The advantage of this embodiment lies in its focus on reservoir depth prediction in deep-water, deep-seated areas with few wells. After quality assessment of seismic data in the target area, this invention selects a subset of seismic data as the foundation for research. Based on refined geological model construction, selection of regional velocity marker layers, well-seismic calibration, analysis of key velocity factors, and optimization of the seismic velocity volume, it conducts high-precision velocity modeling and detailed research, achieving the goal of accurate prediction of reservoir depth in deep-water, deep-seated areas with few or no wells. This application rigorously improves the refinement of each modeling step, with a key focus on incorporating reservoir property variations as key regional velocity factors into the seismic velocity volume optimization process. Compared to the original seismic velocity volume, it adds more velocity details that match well logging data, which helps improve the prediction accuracy of the final velocity model. Compared to existing technologies, this application incorporates key regional velocity factors into the accuracy optimization of the seismic velocity volume based on sedimentary facies understanding, effectively predicting reservoir depth in deep-water, deep-seated areas with few or no wells.

[0067] Example 2

[0068] This embodiment is similar to Embodiment 1, except that:

[0069] In this embodiment, seismic interpretation of the regional velocity marker layer is carried out based on the well-seismic calibration results. Specifically, the regional velocity marker layer is the reservoir area, and the areas above and below the reservoir are adjacent marker layers. The seismic interpretation density of the adjacent marker layers is consistent with that of the reservoir area. The interpretation density is: main survey line * connecting survey line = 120m * 120m. It should be noted that in seismic exploration, the main survey line refers to the profile perpendicular to the regional structural strike, while the connecting survey line refers to the profile parallel to the regional structural strike.

[0070] In this embodiment, a three-dimensional geological model is constructed based on the determined regional marker layers. Specifically, when constructing the three-dimensional geological model, the time of the regional velocity marker layers should be sorted from top to bottom, and the grid value of the three-dimensional geological model is 180*180.

[0071] The other structures and principles of this embodiment are the same as those of Embodiment 1.

[0072] Example 3

[0073] This embodiment is similar to Embodiment 1, except that:

[0074] In this embodiment, seismic interpretation of the regional velocity marker layer is carried out based on the well-seismic calibration results. Specifically, the regional velocity marker layer is the reservoir area, and the areas above and below the reservoir are adjacent marker layers. The seismic interpretation density of the adjacent marker layers is consistent with that of the reservoir area. The interpretation density is: main survey line * connecting survey line = 130m * 130m. It should be noted that in seismic exploration, the main survey line refers to the profile perpendicular to the regional structural strike, while the connecting survey line refers to the profile parallel to the regional structural strike.

[0075] In this embodiment, a three-dimensional geological model is constructed based on the determined regional marker layers. Specifically, when constructing the three-dimensional geological model, the time of the regional velocity marker layers should be sorted from top to bottom, and the grid value of the three-dimensional geological model is 220*220.

[0076] The other structures and principles of this embodiment are the same as those of Embodiment 1.

[0077] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art can make other variations or modifications based on the above description. It is neither necessary nor possible to exhaustively describe all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A high-precision velocity modeling method for deep-water deep reservoirs, characterized in that, Specifically, the steps include the following: Quality assessment of seismic data in the target area and selection of basic data; Based on the selected basic data, select and determine the in-phase axis that can be stably tracked in space, is widely distributed, and whose actual burial depth can be determined by well logging data as the regional velocity marker layer; By combining the selected basic data and the determined regional velocity marker layer, a fine well-seismic calibration of the regional velocity marker layer was carried out, and the well-seismic calibration results were obtained. Seismic interpretation of regional velocity marker layers was carried out based on well seismic calibration results; Construct a three-dimensional geological model based on the identified regional marker layers; Based on the selected basic data, the seismic velocity volume corresponding to the basic data is selected as the basic data for velocity research; Comparative analysis was conducted between the actual drilling sonic velocity curves and the seismic velocity curves of the wellbore surroundings, and reconstructed seismic velocity curves for the entire well section were obtained. Based on the analysis of well logging curves, well logging data, and geological conditions, the main controlling factors of regional velocity are identified, and these main controlling factors are physical properties. Based on the physical property data, and according to the geological sedimentary facies diagram, draw a planar distribution pattern of reservoir physical properties from the fan root to the leading edge; Under the constraint of the selected seismic velocity volume, the three-dimensional spatial interpolation of the reconstructed seismic velocity curve throughout the well section is controlled by the physical property plane distribution law to obtain a three-dimensional phase-controlled interpolated velocity volume with higher velocity accuracy and consistent with the main regional velocity control factors. The planar velocity grid of the three-dimensional phased interpolation velocity volume is extracted along the regional velocity marker layer. The depth grid is obtained by multiplying the planar velocity grid with the time of the regional velocity marker layer. The depth value is obtained by back-cutting the depth grid along the well point. The error value between the depth value and the actual drilling depth is calculated and a planar error grid is formed. The three-dimensional phased interpolation velocity volume is corrected by the error grid corresponding to each regional velocity marker layer to eliminate residual errors. Finally, a high-precision seismic velocity model is obtained, and time-depth conversion is carried out.

2. The high-precision velocity modeling method for deep-water deep reservoirs according to claim 1, characterized in that, The basic data selection involves evaluating the quality of seismic data by comparing seismic resolution, signal-to-noise ratio, and imaging accuracy, and selecting seismic data with good imaging quality as the basic data for the study.

3. The high-precision velocity modeling method for deep-water deep reservoirs according to claim 1, characterized in that, The regional velocity marker layers are selected from the seafloor reflector layer, the adjacent strata above the reservoir, and the adjacent strata below the reservoir in the deep water area.

4. The high-precision velocity modeling method for deep-water deep reservoirs according to claim 1, characterized in that, The regional velocity marker layer is the reservoir region, and the regions above and below the reservoir are adjacent marker layers. The seismic interpretation density of the adjacent marker layers is consistent with that of the seismic interpretation of the reservoir region.

5. The high-precision velocity modeling method for deep-water deep reservoirs according to claim 4, characterized in that, The explained density is: main survey line * connecting survey line = 120m * 120m ~ 130m * 130m.

6. The high-precision velocity modeling method for deep-water deep reservoirs according to claim 1, characterized in that, When constructing the three-dimensional geological model, the time of the regional velocity marker layers should be sorted from top to bottom.

7. The high-precision velocity modeling method for deep-water deep reservoirs according to claim 6, characterized in that, The grid value of the three-dimensional geological model is between 180*180 and 220*220.

8. The high-precision velocity modeling method for deep-water deep reservoirs according to claim 1, characterized in that, The acquisition of the reconstructed seismic velocity curve for the entire well section is achieved by using the seismic velocity curve to fill in the shallow missing part of the actual drilling sonic velocity curve, under the condition that the overall seismic velocity trend is basically consistent. The completed actual drilling sonic velocity curve is then sampled into a three-dimensional geological model for coarsening. The coarsened velocity curve of the well passage is then extracted from the three-dimensional geological model. This process yields a reconstructed seismic velocity curve for the entire well section that can simultaneously reflect the regional velocity trend and the local velocity details of the well logging.

Images