Small-scale fracture-cave identification method and system

Abstract

The present application relates to a small-scale fracture-cave identification method and system, the identification method comprising: 1) based on pre-stack depth migration seismic data volume, the inclination volume and azimuth volume are calculated; 2) the coherent amplitude gradient data volume is calculated by using the inclination volume obtained in step 1) to carry out horizontal directional scanning; 3) the azimuth coherent amplitude gradient data volume is calculated by using the azimuth volume obtained in step 1) to carry out azimuth directional scanning. Compared with the prior art, the present application obtains three-dimensional inclination volume and azimuth volume by pre-stack depth migration seismic data, considers the inclination change of stratum and the difference of different azimuth small-scale geological anomaly volume, calculates the coherent amplitude gradient and azimuth coherent amplitude gradient data volume, fully considers the change of inclination, azimuth and three-dimensional data volume line, trace direction time shift, avoids the defects that the traditional coherent attribute algorithm horizontal scanning calculation or can only define a single stratum inclination, and improves the identification precision of small-scale fracture-cave group.

Description

Technical Field

[0001] This invention relates to the field of oil and gas geophysics, and particularly to a method and system for identifying small-scale fractures and cavities. Background Technology

[0002] The main targets for carbonate rock development in the Tarim Oilfield are weathered crust remnants, large-scale fractured-cavity bodies, and fault-dissolved bodies. Currently, large-scale reservoirs are largely well-controlled, with an increasing proportion of high-water-cut wells and complex oil-water relationships. Small fractured-cavity clusters, as alternative development sites, possess significant exploration and development potential. These clusters, formed by interconnected pores, fractures, and cavities due to karst or tectonic activity, are genetically linked and widely distributed, often developing along faults, bedding planes, or low-amplitude weathered crust remnants. They can be distributed in contiguous areas and possess considerable potential for profitable exploitation. Previous research has developed a series of techniques for identifying large and medium-sized fractured-cavity reservoirs, including high-precision depth-domain seismic imaging, amplitude variation rate, seismic tensor, post-stack impedance inversion, and high-precision coherence. However, data and methods for identifying small-scale fractured-cavity reservoirs are relatively limited. Currently, the most direct understanding and description of small-scale fractures and cavities at home and abroad mainly relies on core observation. By comparing and analyzing the characteristics of core samples with those of well logging, the reservoir can be finely divided and identified. However, the amount of data from core wells is limited, which is difficult to meet the actual exploration and development needs.

[0003] Chinese patent application CN201210317008.1 proposes a seismic diffraction wave separation imaging method. This method has a good identification effect on fracture-vuggy reservoirs that can form diffraction waves, but many small fractures and vuggies are difficult to form diffraction waves and will be missed. Chinese patent application CN201710077430.7 proposes a method for seismic identification of small-scale fracture-vuggy reservoirs. It proposes to use pre-stack near-offset gather stacked data volumes to perform sparse pulse inversion, obtaining a spatial distribution of small-scale fracture-vuggy reservoirs with an increased number of fractures and vuggies. Chinese patent application CN201810863032.2 proposes a method for highlighting small-scale fracture-vuggy information under strong earthquake reflection interfaces. It generates seismic data volumes that highlight small-scale fracture-vuggy information by reconstructing reflection coefficients. This method is greatly affected by wavelet and reconstruction methods. Summary of the Invention

[0004] This invention provides a method for identifying small-scale seam holes, comprising the following steps:

[0005] (1) Based on the pre-stack depth migration seismic data volume, the dip volume and azimuth volume are calculated;

[0006] (2) Use the tilt body obtained in step (1) to perform lateral guiding scanning and calculate the coherent amplitude gradient data volume;

[0007] (3) Use the azimuth volume obtained in step (1) to perform azimuth guidance scanning and calculate the azimuth coherent amplitude gradient data volume.

[0008] In one implementation, the following steps are also included:

[0009] (4) Based on the coherent amplitude gradient data volume obtained in step (2) and the azimuth coherent amplitude gradient data volume obtained in step (3), calculate the higher-order derivatives to obtain the higher-order azimuth coherent amplitude data volume.

[0010] In one implementation, the following steps are also included:

[0011] (5) Considering the changes in different orientations, the high-order azimuth coherent amplitude data volumes of different orientations are obtained by using step (4) to form multiple calculation volumes. The calculation results of different orders are extracted and superimposed to form a high-order multi-azimuth coherent amplitude gradient data volume.

[0012] In one implementation, it further includes:

[0013] (6) Based on the high-order multi-directional coherent amplitude gradient data volume obtained in step (5), the gradient structure seismic tensor data volume is calculated.

[0014] In one implementation, in step (1), the dip body and azimuth body are calculated, including calculating the vector dip angle using the gradient construction tensor, and finding the direction of the greatest change in seismic data within a small analysis window to obtain the dip body and azimuth body.

[0015] In one implementation, when calculating the coherent amplitude gradient data volume in step (2), the time shift between adjacent seismic traces is considered to improve the calculation accuracy of small amplitude fluctuations.

[0016] In one embodiment, in step (3), the azimuth coherent amplitude gradient data volume is calculated, including calculating the coherent amplitude gradient of different azimuths, finding the azimuth with the largest amplitude change, thereby forming the dominant azimuth coherent amplitude gradient data volume.

[0017] In one implementation, in step (4), higher-order derivatives are calculated using the frequency domain Fourier transform.

[0018] In one implementation, step (6) further includes using a construction smoothing filter technique to perform three-dimensional filtering on the gradient structure seismic tensor data volume, and combining it with imaging logging calibration to obtain a seismic tensor data volume suitable for describing the structure of small slot cavern groups.

[0019] In one implementation, prior to step (1), the method further includes preparing pre-stack depth migration seismic data volumes and imaging logging data.

[0020] The present invention also provides a small-scale seam hole identification system, comprising the following modules:

[0021] The first module calculates the dip volume and azimuth volume based on pre-stack depth migration seismic data.

[0022] The second module uses the tilting body to perform lateral guided scanning and calculates the coherent amplitude gradient data volume.

[0023] The third module uses the azimuth volume to perform azimuth-guided scanning and calculates the azimuth coherent amplitude gradient data volume.

[0024] In one embodiment, the system further includes the following modules:

[0025] The fourth module calculates higher-order derivatives based on the coherent amplitude gradient data volume and the azimuth coherent amplitude gradient data volume to obtain higher-order azimuth coherent amplitude data volume.

[0026] The fifth module acquires high-order azimuth coherent amplitude data volumes from different directions to form multiple computational volumes. By extracting and superimposing the computational results of different orders, a high-order multi-azimuth coherent amplitude gradient data volume is formed.

[0027] The sixth module calculates the gradient structure seismic tensor data volume based on the high-order multi-directional coherent amplitude gradient data volume, performs three-dimensional filtering on the gradient structure seismic tensor data volume using construction smoothing filtering technology, and combines imaging logging calibration to obtain a seismic tensor data volume suitable for describing the structure of small fracture-cavity groups.

[0028] Compared with existing technologies, the small-scale fracture-cavity group identification method and system provided by this invention obtains three-dimensional high-precision dip and azimuth volumes using high-precision pre-stack depth migration seismic data. Based on this, considering variations in stratum dip angle and differences in small-scale geological anomalies at different azimuths, it calculates coherent amplitude gradient and azimuth coherent amplitude gradient data volumes. This fully considers the changes in dip angle, azimuth angle, and the time-shift of lines and traces in the three-dimensional data volume, avoiding the shortcomings of traditional coherent attribute algorithms that rely on horizontal scanning calculations or can only define a single stratum dip angle. This results in higher calculation accuracy, better reflection of small geological targets, and improved identification accuracy of small-scale fracture-cavity groups. The method also employs a frequency domain Fourier algorithm. This study utilizes high-order azimuth coherent amplitude gradients to overcome the drawbacks of low-order calculation methods that suppress high-wavenumber (i.e., small-scale) targets, thus highlighting small-scale geological targets. Simultaneously, considering the development patterns of small-scale fractures and cavities, a new high-order multi-azimuth coherent amplitude gradient data volume is constructed by superimposing high-order amplitude gradients from different azimuths. This data volume better reflects small-scale fractured-cavity reservoirs with directional arrangement or special azimuth development. Finally, based on the exploration and development needs of small-scale fractured-cavity reservoirs, structural seismic tensor technology is used to identify the contours of small-scale fractured-cavity groups, and calibration is performed in conjunction with imaging logging results. Ultimately, this provides a better technical method and process for identifying small-scale fractured-cavity reservoirs (groups). It also effectively solves the problem of difficult identification of small-scale fractures and cavities in carbonate rocks. Attached Figure Description

[0029] The invention will now be described in more detail with reference to embodiments and the accompanying drawings.

[0030] Figure 1 This is a schematic diagram of the process structure of the present invention;

[0031] Figure 2 This is a pre-stack depth migration seismic profile of the large fracture development area in a certain work area, passing through well W1;

[0032] Figure 3 This is a profile of the dip angle attributes of the large fracture development area of ​​a certain work area through well W1;

[0033] Figure 4 This is a profile of the azimuth attributes of the W1 well in the large fracture development area of ​​a certain work area;

[0034] Figure 5 This is a pre-stack depth migration seismic profile of the W2 well within a small-slit-cavity development zone of a certain work area.

[0035] Figure 6 A high-order multi-directional amplitude gradient profile of well W2 within a small-slit-cavity development zone of a certain work area;

[0036] Figure 7 This is a seismic tensor profile of the gradient structure of well W2 within a small-slit-cavity development zone of a certain work area.

[0037] Figure 8 For imaging logging calibration of the small fractured cavity development area in a certain work area, the pre-stack depth migration seismic profile and gradient structure seismic tensor profile of well W2 were determined.

[0038] Figure 9 This is a schematic diagram of a small-scale crack / hole identification system. Detailed Implementation

[0039] The invention will now be further described with reference to the accompanying drawings.

[0040] Example 1

[0041] like Figure 1 As shown, the present invention provides a method for identifying small-scale seams, comprising the following steps:

[0042] Step S1: Based on the pre-stack depth migration seismic data volume, calculate the dip volume and azimuth volume.

[0043] Based on pre-stack depth migration seismic data volumes, the gradient construction tensor is used to calculate the vector dip angle. Within a small analysis window, the direction of the greatest change in seismic data is found to obtain the dip volume and azimuth volume.

[0044] Figures 2 to 4 The seismic profiles, dip attribute profiles, and azimuth attribute profiles of the pre-stack depth of the large fracture-cavity development area through well W1 in a certain work area are shown respectively, and compared. Figures 2 to 4 It is evident that the dip and azimuth profiles clearly express the details of changes around the fracture and the cavity, providing a basis for subsequent dip and azimuth guided scanning.

[0045] Step S2: Using the tilt body obtained in step S1, perform a lateral guided scan to calculate the coherent amplitude gradient data volume.

[0046] Considering the change in the dip angle of the reflector, a lateral guided scan is performed using the dip volume obtained in step S1. The coherent amplitude gradient data volume is calculated using the parameters obtained from the scan. The time shift between adjacent seismic traces is taken into account during the calculation to improve the calculation accuracy of small amplitude fluctuations.

[0047] Step S3: Using the azimuth volume obtained in step S1, perform azimuth-guided scanning to calculate the azimuth coherent amplitude gradient data volume.

[0048] When identifying small-scale fissures, especially oriented cracks or small-scale pores, variations in orientation should be considered. Using the azimuth volume obtained in step S1, an azimuth-guided scan is performed. The parameters obtained from the scan are used to calculate the coherent amplitude gradient in different azimuths, identifying the azimuth with the greatest amplitude variation. This forms the dominant azimuth coherent amplitude gradient data volume, thereby improving the ability to identify oriented small geological targets.

[0049] If the identification accuracy of small-scale cracks is still insufficient after the above steps S1 to S3, the following processing can be continued:

[0050] Step S4: Based on the coherent amplitude gradient data volume obtained in Step S2 and the azimuth coherent amplitude gradient data volume obtained in Step S3, calculate the higher-order derivative to obtain the higher-order azimuth coherent amplitude data volume.

[0051] The conventional amplitude change rate calculation employs a higher-order first derivative method, utilizing multiple points (traces) in the same azimuth. Based on the coherent amplitude gradient data volume obtained in step S2 and the azimuth coherent amplitude gradient data volume obtained in step S3, a higher-order derivative is calculated using frequency-domain Fourier transform to obtain a higher-order azimuth coherent amplitude data volume. Increasing the calculation order helps to extend the role of high-wavenumber targets, thereby highlighting the accuracy of identifying small-scale geological targets such as fracture-cavity reservoirs, overcoming the drawback of low-order calculation methods suppressing high-wavenumber (i.e., small-scale) targets.

[0052] Step S5: Considering the changes in different orientations, use the high-order azimuth coherent amplitude data volumes obtained in step S4 to form multiple calculation volumes. Extract the calculation results of different orders and superimpose them to form a new high-order multi-azimuth coherent amplitude gradient data volume. The high-order multi-azimuth coherent amplitude gradient data volume can better reflect small geological anomalies with a certain orientation or directional distribution.

[0053] Figure 5 and Figure 6 The seismic profiles showing the pre-stack depth migration and high-order multi-azimuth amplitude gradient profiles of the small fractured cavity development zone in a certain work area are shown respectively, for comparison. Figure 5 , Figure 6 It is evident that high-order multi-directional amplitude gradient data can identify small-scale fracture-cavity reservoirs.

[0054] Step S6: Based on the high-order multi-directional coherent amplitude gradient data volume obtained in step S5, calculate the gradient structure seismic tensor data volume.

[0055] Since individual small fractures and cavities do not meet the needs of profitable exploration and development, it is necessary to conduct contour identification of small fracture and cavity groups. Based on the high-order multi-directional coherent amplitude gradient data volume obtained in step S5, gradient structure seismic tensor calculation is carried out, and structural smoothing filtering technology is used to perform three-dimensional filtering on the gradient structure seismic tensor data volume. Combined with imaging logging calibration, a seismic tensor data volume suitable for describing the structure of small fracture and cavity groups is obtained.

[0056] Figure 7 This paper presents a seismic tensor profile of the gradient structure through well W2 within a small-slit cave development area of ​​a certain work zone, and compares it with the previous data. Figure 7 and Figure 5It is evident that gradient structure tensor data volumes can effectively identify the contour features of small-scale crevice-cavity reservoirs.

[0057] Figure 8 The image shows the pre-stack depth migration seismic profile and gradient structure seismic tensor profile of well W2 in a small fractured and cavitary development area of ​​a certain work area. As can be seen from the figure, the imaging logging sections ① and ② encountered fractured-dissolution-type reservoirs, which showed weak reflections on the seismic profile and obvious anomalous features on the gradient structure tensor profile.

[0058] Example 2

[0059] like Figure 9 As shown, in this embodiment, the first module 10 executes step S1 of embodiment 1, the second module 20 executes step S2 of embodiment 1, the third module 30 executes step S3 of embodiment 1, the fourth module 40 executes step S4 of embodiment 1, the fifth module 50 executes step S5 of embodiment 1, and the sixth module 60 executes step S6 of embodiment 1. Further details are omitted here.

[0060] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device, or fabricating them separately as individual integrated circuit modules, or fabricating multiple modules or steps as a single integrated circuit module. Thus, the present invention is not limited to any particular hardware and software combination.

[0061] Although the invention has been described with reference to preferred embodiments, various modifications can be made and components can be replaced with equivalents without departing from the scope of the invention. In particular, the technical features mentioned in the various embodiments can be combined in any manner as long as there is no structural conflict. The invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A method for identifying small-scale seams and holes, characterized in that, Includes the following steps: (1) Based on the pre-stack depth migration seismic data volume, the dip volume and azimuth volume are calculated; (2) Use the tilt body obtained in step (1) to perform lateral guiding scanning and calculate the coherent amplitude gradient data volume; (3) Use the azimuth volume obtained in step (1) to perform azimuth guidance scanning and calculate the azimuth coherence amplitude gradient data volume; It also includes the following steps: (4) Based on the coherent amplitude gradient data volume obtained in step (2) and the azimuth coherent amplitude gradient data volume obtained in step (3), calculate the higher-order derivatives to obtain the higher-order azimuth coherent amplitude data volume. It also includes the following steps: (5) Considering the changes in different orientations, use step (4) to obtain high-order azimuth coherent amplitude data volumes in different orientations to form multiple calculation volumes. Extract the calculation results of different orders and superimpose them to form a high-order multi-azimuth coherent amplitude gradient data volume. Also includes: (6) Based on the high-order multi-directional coherent amplitude gradient data volume obtained in step (5), the gradient structure seismic tensor data volume is calculated; Step (6) also includes using structural smoothing filtering technology to perform three-dimensional filtering on the gradient structure seismic tensor data volume, and combining it with imaging logging calibration to obtain a seismic tensor data volume suitable for describing the structure of small fracture-cavity groups.

2. The method for identifying small-scale seams and holes according to claim 1, characterized in that, In step (1), the dip body and azimuth body are calculated, including using gradient construction tensor to calculate vector dip angle, and within a small analysis window, finding the direction of the greatest change in seismic data to obtain the dip body and azimuth body.

3. The method for identifying small-scale seams and holes according to claim 1, characterized in that, In step (2), when calculating the coherent amplitude gradient data volume, the time shift between adjacent seismic traces is considered to improve the calculation accuracy of small amplitude fluctuations.

4. The method for identifying small-scale seams and holes according to claim 1, characterized in that, In step (3), the azimuth coherent amplitude gradient data volume is calculated, including calculating the coherent amplitude gradient of different azimuths, finding the azimuth with the largest amplitude change, and thus forming the dominant azimuth coherent amplitude gradient data volume.

5. The method for identifying small-scale seams and holes according to claim 1, characterized in that, In step (4), the higher-order derivatives are calculated using the frequency domain Fourier transform.

6. The method for identifying small-scale seams and holes according to claim 1, characterized in that, Before step (1), there are also steps to prepare pre-stack depth migration seismic data volumes and imaging logging data.

7. A small-scale crack / hole identification system, characterized in that, Includes the following modules: The first module calculates the dip volume and azimuth volume based on pre-stack depth migration seismic data. The second module uses the tilting body to perform lateral guided scanning and calculates the coherent amplitude gradient data volume. The third module uses the azimuth volume to perform azimuth guidance scanning and calculates the azimuth coherence amplitude gradient data volume. The fourth module calculates higher-order derivatives based on the coherent amplitude gradient data volume and the azimuth coherent amplitude gradient data volume to obtain higher-order azimuth coherent amplitude data volume. The fifth module acquires high-order azimuth coherent amplitude data volumes from different directions to form multiple computational volumes. By extracting and superimposing the computational results of different orders, a high-order multi-azimuth coherent amplitude gradient data volume is formed. The sixth module calculates the gradient structure seismic tensor data volume based on the high-order multi-directional coherent amplitude gradient data volume, performs three-dimensional filtering on the gradient structure seismic tensor data volume using construction smoothing filtering technology, and combines imaging logging calibration to obtain a seismic tensor data volume suitable for describing the structure of small fracture-cavity groups.

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