Carbonate rock scale reservoir multidimensional space positioning method

Abstract

The invention provides a carbonate rock-scale reservoir multi-dimensional space positioning method, and relates to the technical field of oil and gas geophysics, and the method combines a three-dimensional seismic data volume and a three-dimensional seismic attribute volume, and calculates and utilizes the amplitude anisotropy characteristics of a carbonate rock-scale reservoir on a seismic imaging gather, so as to obtain a three-dimensional seismic data volume and a three-dimensional seismic attribute volume. A matched method process is invented, and accurate identification and spatial positioning of the carbonate rock scale reservoir by using multi-dimensional seismic data are realized by scanning an imaging gather of all imaging points where a target geologic body is located, calculating a scale reservoir coefficient and performing spatial positioning on a spatial range and a central point of the scale reservoir. And an important data basis is provided for accurately searching an oil and gas well drilling scale target.

Description

Technical Field

[0001] The invention relates to the technical field of oil and gas geophysics, and in particular to a multi-dimensional spatial positioning method for carbonate rock scale reservoirs. Background Art

[0002] Deep-ultra-deep marine carbonate rocks contain abundant oil and gas resources and are an important direction for the search for oil and gas. Accurate identification and precise spatial positioning of carbonate reservoirs can allow drilling to quickly encounter oil and gas reservoirs while avoiding formations prone to collapse accidents. This is the key to the efficient discovery and use of carbonate oil and gas resources. However, this field currently faces many technical difficulties. Carbonate formations have developed high-steep strike-slip fault zones, and the internal reservoirs are extremely heterogeneous, with the characteristics of "multiple types, multiple scales, multiple combinations, and multiple changes". The seismic identification mode of strike-slip fault zones is unclear, the geological analysis mode is single, and the main section is difficult to identify. The description and evaluation of fault-controlled fracture-cavity closures and the optimization technology of large-scale targets have not yet been systematically established.

[0003] In recent years, there is no mature experience to learn from at home and abroad in the field of spatial positioning of carbonate reservoirs. Seismic attribute extraction and phase-controlled inversion technology are often used to characterize carbonate reservoirs. Related research includes a method and system for locating the position of carbonate karst cave geothermal energy reservoirs disclosed in patent CN110941028B. The invention processes seismic data, eliminates noise, and performs seismic trace integration to transform the seismic data reflecting the position of carbonate karst geothermal energy reservoirs from zero phase to peaks and troughs. After the corresponding Fourier transformation, the center point of the carbonate karst geothermal energy reservoir corresponds to the position of the maximum peak (trough) of the seismic data, thereby determining the position of the carbonate karst geothermal energy reservoir. Another example is the literature: Wang Zhen, Wen Huan, Hu Wenge. Research on the prediction method of spatial position of carbonate fractures and caves in Tahe Oilfield [J]. Journal of Engineering Geophysics, 2019(004):016. The "three-determination" technology for comprehensively predicting the spatial position of fractures and caves using pre-stack depth migration technology, frequency division technology and impedance inversion technology was proposed. The prediction effect of the spatial position of carbonate fractures and caves in the western Tahe District 10 shows that the "three-determination" technology has improved the target rate of new wells, effectively guided the demonstration of the potential of measures, and improved the development effect. However, the above patents or documents are based on three-dimensional post-stack seismic data and post-stack inversion attributes. Due to the comprehensive amplitude response of the amplitude characteristics of carbonate reservoirs on conventional three-dimensional post-stack data, the strong heterogeneity and strong anisotropy characteristics of carbonate reservoirs are not considered, so the accuracy is insufficient. In addition, the literature: Wang Chong, Zhu Zhongqian, Shi Hongxiang, et al. Carbonate cave positioning technology based on VSP data [J]. Petroleum Geophysical Exploration, 2018 (A02): 9. A wellside cave positioning technology based on VSP data is proposed to accurately predict the spatial position of the cave, provide the coordinates of the drilling target in real time, and improve the accuracy of hitting the target. This technology can be subdivided into well-ground joint cave positioning based on zero-well source distance VSP data and Walkaround-VSP wellside cave positioning. Now this technology has been widely used in the carbonate rock area of ​​the Tarim Basin, improving the direct drilling rate of such reservoirs and providing new ideas for the secondary transformation of old wells. However, the well-ground joint cave positioning and Walkaround-VSP wellside cave positioning based on zero-well source distance VSP data in this literature are essentially based on three-dimensional post-stack seismic data. Due to the comprehensive amplitude response of the amplitude characteristics of carbonate reservoirs on the three-dimensional post-stack data, the strong heterogeneity and strong anisotropy of carbonate reservoirs are not considered, so the accuracy is insufficient.

[0004] In view of the problems existing in the existing technology, it is necessary to find a more accurate multi-dimensional spatial positioning method for large-scale carbonate reservoirs. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention provides a multi-dimensional spatial positioning method for carbonate rock scale reservoirs. The present invention realizes accurate identification and spatial positioning of carbonate rock scale reservoirs using multi-dimensional seismic data by analyzing the amplitude anisotropy characteristics of seismic imaging gathers, combining three-dimensional seismic data volumes and three-dimensional seismic attribute volumes, and the positioning accuracy is less than or equal to the grid size of the common center point (CMP point) of seismic data processing horizontally, and less than or equal to the depth sampling interval of seismic data processing vertically. The problem of identifying high-quality scale reservoirs and positioning drilling targets in the deployment of oil and gas wells is solved.

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

[0007] The present invention provides a multi-dimensional spatial positioning method for carbonate rock scale reservoirs, comprising the following steps:

[0008] (1) Clarify the seismic response characteristics of carbonate reservoirs in the work area on seismic imaging profiles and imaging gathers;

[0009] (2) Input CMP gather data and depth domain velocity volume data, and generate imaging gather data volume A through seismic migration imaging calculation method;

[0010] (3) stacking the imaging gather data volume A in step (2) to generate an imaging stacked data volume B;

[0011] (4) in the imaging stacked data volume B of step (3), confirm that the carbonate reservoir body Ci is the carbonate reservoir body target;

[0012] (5) on the basis of step (4) and in combination with step (1), determine whether the carbonate reservoir Ci is a large-scale carbonate reservoir; if so, perform spatial positioning;

[0013] (6) Obtain the spatial range and center coordinates of carbonate reservoirs.

[0014] Furthermore, large-scale carbonate reservoirs often show "beaded" seismic response characteristics on seismic imaging profiles; they often show amplitude anisotropy characteristics on imaging gathers, that is, the amplitude varies in strength with different offset distances and incident angle ranges. The larger the reservoir size, the greater the proportion of offset distances and incident angle ranges with strong amplitudes.

[0015] Furthermore, the seismic response characteristics in step (1) are analyzed by forward modeling of the geological-seismic model of the work area and the seismic characteristics of high-yield wells drilled in carbonate reservoirs.

[0016] Furthermore, the carbonate reservoir target in step (4) is confirmed by seismic interpretation and geological analysis.

[0017] Furthermore, the seismic migration imaging calculation method in step (2) includes a Kirchhoff prestack depth migration imaging method.

[0018] Furthermore, step (5) specifically includes:

[0019] ① Find the seismic line number or spatial range where the carbonate reservoir Ci is located, where the X-coordinate direction range is (cix1, cix2), the Y-coordinate direction range is (ciy1, ciy2), and the Z-coordinate direction range is (ciz1, ciz2);

[0020] ② Find all the corresponding imaging gather data points of the data volume A within the range of (cix1, cix2), (ciy1, ciy2) and (ciz1, ciz2), and record the amplitude value at each data point;

[0021] ③ On the basis of step (1), the maximum threshold and minimum threshold of the amplitude value recorded in the imaging gather data points of carbonate rock scale reservoir are set, and the gather data range corresponding to the data points with continuous amplitude values ​​between the maximum threshold and the minimum threshold of the nth segment is set as (cion1, cion2), which is the dominant gather range of the scale reservoir; the whole gather data range is set as (cio_min, cio_max), and the coefficient of carbonate rock scale reservoir is set as S, then:

[0022] S=∑ n≥0 (cion2-cion1) / (cio_max-cio_min);

[0023] When S is greater than or equal to S g When , the corresponding carbonate reservoir is a carbonate-scale reservoir;

[0024] Among them, S g is the proportion of strong amplitude data to all offset data;

[0025] ④ Scan the imaging gather data body A along the Y direction, starting from the imaging data point ciy1 to ciy2, and gradually scan to find the imaging point range corresponding to the carbonate rock scale reservoir within the spatial range of the carbonate rock reservoir body Ci; filter out the Y coordinate range of the imaging gather data point number corresponding to S greater than or equal to Sg, and record the Y coordinates of the minimum and maximum points as ciyy1 and ciyy3 respectively, and the Y coordinate of the point number corresponding to the maximum value of the coefficient S is ciyy2; that is, the Y coordinate range of the carbonate rock scale reservoir is (ciyy1, ciyy3), and the Y coordinate of the center position of the carbonate rock scale reservoir is ciyy2;

[0026] ⑤ Scan the imaging gather data body A along the X direction, starting from the imaging data point cix1 and gradually scanning to cix2, to find the imaging point range corresponding to the carbonate rock scale reservoir within the spatial range of the carbonate rock reservoir body Ci; filter out the X coordinate range of the imaging gather data point number corresponding to S greater than or equal to Sg, and record the X coordinates of the minimum and maximum points as cixx1 and cixx3 respectively, and the X coordinate of the point number corresponding to the maximum value of the coefficient S is cixx2; that is, the X coordinate range of the carbonate rock scale reservoir is (cixx1, cixx3), where the X coordinate of the center position of the carbonate rock scale reservoir is cixx2;

[0027] ⑥ Scan the imaging gather data volume A along the Z direction, starting from the imaging data point ciz1 and gradually scanning to ciz2, to find the imaging point range corresponding to the carbonate rock scale reservoir within the spatial range of the carbonate rock reservoir body Ci; screen out the Z coordinate range of the imaging gather data point number corresponding to S greater than or equal to Sg, and record the Z coordinates of the minimum and maximum points as cizz1 and cizz3 respectively, and the Z coordinate of the point number corresponding to the maximum value of the coefficient S is cizz2; that is, the Z coordinate range of the carbonate rock scale reservoir is (cizz1, cizz3), and the Z coordinate of the center position of the carbonate rock scale reservoir is cizz2.

[0028] In some specific implementations, in step ①, the X-coordinate direction range is (c1x1, c1x2), the Y-coordinate direction range is (c1y1, c1y2), and the Z-coordinate direction range is (c1z1, c1z2).

[0029] Furthermore, the spatial range of the carbonate rock scale reservoir is (cixx1, ciyy1, cizz1), (cixx1, ciyy3, cizz1), (cixx3, ciyy1, cizz1), (cixx3, ciyy3, cizz1), (cixx1, ciyy1, cizz3), (cixx1, ciyy3, cizz3), (cixx3, ciyy1, cizz3), (cixx3, ciyy3, cizz3), and the center position coordinates are (cixx2, ciyy2, cizz2).

[0030] Furthermore, assuming that the number of imaging points corresponding to the range (cix1, cix2) is M, the number of imaging points corresponding to the range (ciy1, ciy2) is N, and the number of imaging points corresponding to the range (ciz1, ciz2) is L, the total number of data points scanned in steps ④, ⑤, and ⑥ should be greater than or equal to M+N+L-2 and less than or equal to M×N×L.

[0031] Further, regarding the S in step (3) g, explained as follows: In the imaging gather data, the amplitude changes with the energy strength of the offset range, where the strong amplitude within the threshold value corresponds to a certain offset range, and Sg represents the proportion of this section of strong amplitude data to all offset data, and its value range is between 0 and 1. It is generally believed that the larger the ratio, the larger the scale of reservoir development. For the Ordovician reservoir in Shunbei Oil and Gas Field, this value is generally around 0.5.

[0032] Furthermore, step (6) is specifically as follows: stacking and imaging the dominant gather range of the large-scale reservoir body screened out in step ③, generating a dominant imaging stacking data volume, obtaining a seismic attribute volume, and combining the spatial positioning in step (5) to obtain the spatial range and center position coordinates of the large-scale carbonate reservoir body.

[0033] The technical effects achieved by the present invention are:

[0034] The present invention realizes accurate identification and spatial positioning of carbonate rock reservoirs using multi-dimensional seismic data, and the positioning accuracy is less than or equal to the grid size of the common center point (CMP point) of seismic data processing in the horizontal direction, and less than or equal to the depth sampling interval of seismic data processing in the vertical direction. It solves the problem of identifying high-quality carbonate rock reservoirs and locating drilling targets in the deployment of oil and gas wells. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 Forward modeling of carbonate reservoirs of different scales, where (a) is a small-scale reservoir stacking section, (b) is a small-scale reservoir forward model, (c) is a small-scale reservoir imaging gather, (d) is a large-scale reservoir stacking section, (e) is a large-scale reservoir forward model, and (f) is a large-scale reservoir imaging gather;

[0036] Figure 2 Actual data of carbonate reservoirs of different scales, among which (a) is the stacked section of Well A (low-yield well with small-scale reservoir), (b) is the imaging gather of Well A (low-yield well with small-scale reservoir), (c) is the stacked section of Well B (high-yield well with large-scale reservoir), and (d) is the imaging gather of Well B (high-yield well with large-scale reservoir);

[0037] Figure 3 The amplitude characteristics of the imaging gathers at the non-reservoir position, where (a) is the stacked section at the non-reservoir position, (b) is the forward model at the non-reservoir position, and (c) is the imaging gathers at the non-reservoir position; Figure 4 The amplitude characteristics of the imaging gathers at the location of the large-scale reservoir, where (a) is the stacked section at the location of the large-scale reservoir, (b) is the forward model at the location of the large-scale reservoir, and (c) is the imaging gathers at the location of the large-scale reservoir;

[0038] Figure 5The imaging gathers are scanned along the Y direction, where (a) is the stacked section at the scanning point, (b) is the forward model at the scanning point, and (c) is the imaging gathers at the scanning point;

[0039] Figure 6 The figure is a comparison of the application effects of the method of the present invention and the conventional method, wherein (a) is the stacking section of the conventional method, and (b) is the stacking section of the dominant gather;

[0040] Figure 7 The flowchart of the multi-dimensional spatial positioning method of carbonate rock reservoirs in the present invention is shown in FIG. DETAILED DESCRIPTION

[0041] The following describes the embodiments of the present invention through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention.

[0042] Before further describing the specific embodiments of the present invention, it should be understood that the scope of protection of the present invention is not limited to the specific embodiments described below; it should also be understood that the terms used in the examples of the present invention are for describing specific embodiments rather than for limiting the scope of protection of the present invention.

[0043] When the embodiment gives a numerical range, it should be understood that, unless otherwise specified in the present invention, the two endpoints of each numerical range and any numerical value between the two endpoints can be selected. Unless otherwise defined, all technical and scientific terms used herein have the same meanings as those of ordinary skill in the art to which the present invention belongs.

[0044] Example 1

[0045] Taking the seismic data of a certain application block of oil and gas exploration in the Tarim Basin in northwest China as an example, the application process and effect of the invention are demonstrated. The flow chart of the multi-dimensional spatial positioning method of carbonate rock scale reservoir is shown in Figure 7 , specifically including the following steps:

[0046] Step (1): Analyze the seismic response characteristics of carbonate reservoirs. Figure 1 It is the forward modeling result of the geological-seismic model of carbonate reservoirs of different scales in the work area. It can be seen that at 7500-8000 meters, the energy of small-scale reservoirs on imaging profiles and imaging gathers is shown as weak amplitude, while the energy of large-scale reservoirs on imaging profiles and imaging gathers is shown as strong amplitude. Figure 2Well A is an oil well drilled into a small-scale reservoir (low-yield well), and Well B is an oil well drilled into a large-scale reservoir (high-yield well). It can be seen that at 4700 milliseconds, both wells show "beaded" seismic response characteristics on the imaging section and are difficult to distinguish on the imaging section; but on the imaging gathers, the energy of the gathers at the reservoir of Well A is weak, and some strong energy segments account for a small proportion of the total offset distance, while the energy of the gathers at the reservoir of Well B is very strong, and the strong energy segments account for a high proportion of the total offset distance.

[0047] Step (2): Generate an imaging gather data volume A1 through a seismic migration imaging calculation method. This data volume contains four-dimensional information: coordinates x, y, z and offset distance.

[0048] Step (3): Overlay the imaging gather data volume A1 to generate the imaging stacked data volume B. Figure 3 As shown in the figure, from left to right are the stacked data volume B imaging section, b1 model, and A1 common offset CIP gather. Among them, A1 and B are the data of b1 after forward modeling, and then calculated by the migration algorithm. That is, the three have a strict corresponding relationship.

[0049] Step (4): In the imaging stacked data volume B, through seismic interpretation and geological analysis technology, it is preliminarily confirmed that the dotted box in the figure is a carbonate reservoir Ci.

[0050] Step (5):

[0051] Steps ①-②:

[0052] from Figure 3 It can be seen that the b1 model has a large-scale reservoir body, and there is a corresponding strong energy anomaly body on the imaging section. The grid range occupied in the track direction (Y direction) is approximately 3292-3395 surface element grids, and the depth (Z direction) is approximately 7500-7750 meters.

[0053] Step 3:

[0054] This step determines whether a certain position on the data volume B is a large-scale reservoir by recognizing the amplitude anisotropy characteristics on the pre-stack imaging gathers, which is one of the main factors for the outstanding effect of the present invention.

[0055] The carbonate reservoir coefficient, denoted by S, should be calculated using the following formula:

[0056] S=∑ n≥0 (cion2-cion1) / (cio_max-cio_min);

[0057] When S is greater than or equal to S g When , the corresponding carbonate reservoir is a carbonate-scale reservoir; in the above formula, S gis the proportion of strong amplitude data to all offset data; the maximum and minimum thresholds of the amplitude values ​​recorded at the imaging gather data points of carbonate rock scale reservoirs, the gather data range corresponding to the data points with continuous amplitude values ​​between the maximum and minimum thresholds of the nth segment is set as (cion1, cion2), which is the dominant gather range of the scale reservoir; the range of all gather data is set as (cio_min, cio_max).

[0058] For example, in Figure 3 In the data, at track number 3259 (i.e., Y is 3259), the track gather A1 has weak energy on the 7500-7750 m event axis. The amplitude threshold is set based on the experience of processing this area, and the carbonate rock scale reservoir coefficient S is obtained to be about 0.1, which determines that no scale reservoir has developed at this location.

[0059] exist Figure 4 In the data set, at track number 3353 (i.e., Y is 3353), track A1 has strong energy on the 7500-7750 m event axis. The amplitude threshold is set based on the experience of processing this area, and the proportion of the strong energy data range to the entire track data range is calculated, that is, the carbonate rock scale reservoir coefficient S is obtained to be about 0.9, which determines that a scale reservoir has developed at this location.

[0060] Step 4:

[0061] Scan the imaging gather data volume A along the Y direction, starting from imaging data point 3292 to 3395, and gradually scan to find the imaging point range of the scale reservoir within this range, calculate the scale reservoir coefficient S, and select the Y coordinate range of the imaging gather data point number corresponding to S greater than or equal to 0.5 (based on the law recognition of step (1) and work area experience). Figure 5 At the track number 3374 (i.e. Y is 3374), the track gather A1 has strong energy on the phase axis of 7500-7750 meters, and the coefficient S of the carbonate rock scale reservoir is about 0.8, which determines that a scale reservoir is developed at this location. By scanning the imaging track gather, the range of the scale reservoir in the Y direction is (3296, 3385), where the Y coordinate of the point number corresponding to the maximum value of the coefficient S is 3374, that is, the Y coordinate of the center position of the scale reservoir is 3374.

[0062] Step ⑤:

[0063] Similarly, the imaging gather data volume A is scanned along the X direction. After scanning 120 (1896-2096) imaging points in this direction, the range of the large-scale reservoir in the X direction is located as (1905, 2086), where the X coordinate of the center position of the large-scale reservoir is 2000.

[0064] Step 6:

[0065] Similarly, the imaging gather data volume A was scanned along the Z direction. After scanning 25 depth sampling points (7500-7750 meters, 10-meter sampling interval) in this direction, the range of the large-scale reservoir in the Z direction was located as (7530, 7740), and the Z coordinate of the center position of the large-scale reservoir was 7640 meters.

[0066] Step (6):

[0067] The dominant gather data of carbonate reservoirs selected in step ③ are stacked and imaged to generate a dominant imaging stacked data volume (such as Figure 6 ), on this basis, the application of seismic interpretation and geological analysis technology can obtain higher-precision seismic attribute bodies, which can better carry out drilling trajectory design and large-scale target point optimization, and realize efficient drilling of oil and gas wells.

[0068] The method of the present invention can achieve a large-scale reservoir drilling rate of 85%, which can increase the drilling success rate by more than 6.25% compared with the prior art.

[0069] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions of the technical solution of the present invention by ordinary technicians in this field do not deviate from the essence and scope of the technical solution of the present invention.

Claims

1. A multi-dimensional spatial positioning method for carbonate rock reservoirs, characterized by: The following steps are involved: (1) Clarify the seismic response characteristics of carbonate reservoirs in the work area on seismic imaging profiles and imaging gathers; (2) Input CMP gather data and depth domain velocity volume data, and generate imaging gather data volume A through seismic migration imaging calculation method; (3) stacking the imaging gather data volume A in step (2) to generate an imaging stacked data volume B; (4) in the imaging stacked data volume B of step (3), confirm that the carbonate reservoir body Ci is the carbonate reservoir body target; (5) on the basis of step (4) and in combination with step (1), determine whether the carbonate reservoir Ci is a large-scale carbonate reservoir; if so, perform spatial positioning; (6) Obtain the spatial range and center coordinates of carbonate reservoirs.

2. The multi-dimensional spatial positioning method for carbonate rock reservoirs according to claim 1, characterized in that: The seismic response characteristics described in step (1) are analyzed by forward modeling of the geological-seismic model of the work area and the seismic characteristics of high-yield wells drilled in carbonate reservoirs.

3. The multi-dimensional spatial positioning method for carbonate rock reservoirs according to claim 1, characterized in that: The carbonate reservoir target in step (4) is confirmed through seismic interpretation and geological analysis.

4. The multi-dimensional spatial positioning method for carbonate rock reservoirs according to claim 1, characterized in that: The seismic migration imaging calculation method described in step (2) includes a Kirchhoff prestack depth migration imaging method.

5. The multi-dimensional spatial positioning method for carbonate rock reservoirs according to claim 1, characterized in that: Step (5) specifically includes: ① Find the seismic line number or spatial range where the carbonate reservoir Ci is located, where the X-coordinate direction range is (cix1, cix2), the Y-coordinate direction range is (ciy1, ciy2), and the Z-coordinate direction range is (ciz1, ciz2); ② Find all the corresponding imaging gather data points of the data volume A within the range of (cix1, cix2), (ciy1, ciy2) and (ciz1, ciz2), and record the amplitude value at each data point; ③ On the basis of step (1), the maximum threshold and minimum threshold of the amplitude value recorded in the imaging gather data points of carbonate rock scale reservoir are set, and the gather data range corresponding to the data points with continuous amplitude values ​​between the maximum threshold and the minimum threshold of the nth segment is set as (cion1, cion2), which is the dominant gather range of the scale reservoir; the whole gather data range is set as (cio_min, cio_max), and the coefficient of carbonate rock scale reservoir is set as S, then: S=∑ n≥0 (cion2-cion1) / (cio_max-cio_min); When S is greater than or equal to S g When , the corresponding carbonate reservoir is a carbonate-scale reservoir; Among them, S g is the proportion of strong amplitude data to all offset data; ④ Scan the imaging gather data body A along the Y direction, starting from the imaging data point ciy1 to ciy2, and gradually scan to find the imaging point range corresponding to the carbonate rock scale reservoir within the spatial range of the carbonate rock reservoir body Ci; filter out the Y coordinate range of the imaging gather data point number corresponding to S greater than or equal to Sg, and record the Y coordinates of the minimum and maximum points as ciyy1 and ciyy3 respectively, and the Y coordinate of the point number corresponding to the maximum value of the coefficient S is ciyy2; that is, the Y coordinate range of the carbonate rock scale reservoir is (ciyy1, ciyy3), and the Y coordinate of the center position of the carbonate rock scale reservoir is ciyy2; ⑤ Scan the imaging gather data body A along the X direction, starting from the imaging data point cix1 and gradually scanning to cix2, to find the imaging point range corresponding to the carbonate rock scale reservoir within the spatial range of the carbonate rock reservoir body Ci; filter out the X coordinate range of the imaging gather data point number corresponding to S greater than or equal to Sg, and record the X coordinates of the minimum and maximum points as cixx1 and cixx3 respectively, and the X coordinate of the point number corresponding to the maximum value of the coefficient S is cixx2; that is, the X coordinate range of the carbonate rock scale reservoir is (cixx1, cixx3), where the X coordinate of the center position of the carbonate rock scale reservoir is cixx2; ⑥ Scan the imaging gather data volume A along the Z direction, starting from the imaging data point ciz1 and gradually scanning to ciz2, to find the imaging point range corresponding to the carbonate rock scale reservoir within the spatial range of the carbonate rock reservoir body Ci; screen out the Z coordinate range of the imaging gather data point number corresponding to S greater than or equal to Sg, and record the Z coordinates of the minimum and maximum points as cizz1 and cizz3 respectively, and the Z coordinate of the point number corresponding to the maximum value of the coefficient S is cizz2; that is, the Z coordinate range of the carbonate rock scale reservoir is (cizz1, cizz3), and the Z coordinate of the center position of the carbonate rock scale reservoir is cizz2.

6. The multi-dimensional spatial positioning method for carbonate rock reservoirs according to claim 5, characterized in that: The spatial range of the carbonate rock reservoir is (cixx1, ciyy1, cizz1), (cixx1, ciyy3, cizz1), (cixx3, ciyy1, cizz1), (cixx3, ciyy3, cizz1), (cixx1, ciyy1, cizz3), (cixx1, ciyy3, cizz3), (cixx3, ciyy1, cizz3), (cixx3, ciyy3, cizz3), and the center position coordinates are (cixx2, ciyy2, cizz2).

7. The multi-dimensional spatial positioning method for carbonate rock reservoirs according to claim 5, characterized in that: Assume that the number of imaging points corresponding to the range (cix1, cix2) is M, the number of imaging points corresponding to the range (ciy1, ciy2) is N, and the number of imaging points corresponding to the range (ciz1, ciz2) is L. The total number of data points scanned in steps ④, ⑤, and ⑥ should be greater than or equal to M+N+L-2 and less than or equal to M×N×L.

8. The multi-dimensional spatial positioning method for carbonate rock reservoirs according to claim 5, characterized in that: Step (6) is specifically as follows: stack imaging is performed on the dominant gather range of the large-scale reservoir body screened out in step ③ to generate a dominant imaging stack data volume, obtain a seismic attribute volume, and combine the spatial positioning of step (5) to obtain the spatial range and center position coordinates of the large-scale carbonate reservoir body.

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