A small and micro fault fusion recognition method based on five-dimensional data

Abstract

The application provides a small and micro fault fusion recognition method based on five-dimensional data, and the method comprises the following steps: S1, collecting seismic data through wide-azimuth acquisition and variable-bin high-density wide-azimuth three-dimensional seismic acquisition technology; S2, dividing out five-dimensional data dominant gather azimuth data meeting preset conditions; S3, guiding the recognition technology of small and micro faults based on a five-dimensional data geological comprehensive mode; and S4, describing small and micro faults based on multi-azimuth attributes of five-dimensional data, and completing the plane combination of small and micro faults. The application provides an integrated optimization fusion method based on high-density wide-azimuth seismic acquisition-five-dimensional data processing and interpretation-multi-azimuth data small and micro fault fine description, which can effectively recognize small and micro faults, discover complex small fault block trap groups, and improve the success rate of drilling.

Description

Technical Field

[0001] This invention belongs to the field of petroleum exploration and development, and specifically relates to a method for identifying micro-faults based on five-dimensional data fusion. Background Technology

[0002] For complex small-block development areas, micro-faults play an important role in the discovery of structures and the deployment of development well networks. However, the identification of micro-faults in low signal-to-noise ratio areas has always been a challenge. At the same time, structural interpreters generally only participate in the identification of micro-faults from the interpretation of data.

[0003] In areas with low signal-to-noise ratios under complex surface geological conditions, the identification of small faults based on conventional data acquisition and processing methods (without azimuth information), seismic characteristic methods, coherence volume and dip volume attribute analysis techniques are often ambiguous, leading to low confirmation of small fault block traps. At the same time, the target stratigraphy of some older 3D acquisition data has changed, that is, the non-target stratigraphy has now become the target stratigraphy, which to some extent causes the signal-to-noise ratio and resolution of the processed data to be relatively low, making it difficult to identify small faults. Summary of the Invention

[0004] This application provides a method for identifying micro-faults based on five-dimensional data. It establishes an integrated optimization and fusion method that combines high-density wide-azimuth seismic acquisition, five-dimensional data processing and interpretation, and fine characterization of micro-faults from multi-azimuth data. It also promotes collaboration among multiple disciplines such as geophysics, geology, and geotectonics, thereby improving the accuracy of micro-fault identification.

[0005] This application provides a method for identifying micro-fault fusion based on five-dimensional data, including:

[0006] S1 acquires seismic data using wide-azimuth acquisition and variable-area high-density wide-azimuth 3D seismic acquisition technology;

[0007] S2, divide the five-dimensional data advantage set orientation data that meets the preset conditions;

[0008] S3, a technology for identifying micro-faults based on a geological integrated model using five-dimensional data;

[0009] S4, based on five-dimensional data, uses multi-directional attributes to characterize micro-faults and completes the planar combination of micro-faults.

[0010] In step S1, the aspect ratio is 0.72, the minimum area is 10m×10m, the number of coverages is 180, and the ballistic density is 1.8 million ballistics per square kilometer.

[0011] In step S2, a division principle for gather orientation guided by geological understanding and signal-to-noise ratio is established: based on the geological structure of the study area, according to the regional tectonic background and the direction of the fault, orientation data volumes perpendicular to and parallel to the fault are divided; while ensuring the signal-to-noise ratio, the number of coverages is kept consistent.

[0012] In step S2, the first region is determined to be divided into four directional superimposed data volumes to obtain the dominant directional five-dimensional data.

[0013] Among them, the identification of micro-faults using multi-azimuth seismic data revealed that the micro-faults in the 20-37 and 200-237 azimuth seismic data of the OVT domain were the clearest.

[0014] In step S3, based on regional geological patterns, tectonic movements, and the main fault system, the development of the negative flower-like tectonic model of the main fault transition zone is clarified.

[0015] In step S4, the micro-faults are characterized by multi-directional attributes such as coherence enhancement, curvature, tilt volume, and surface slices based on five-dimensional data, thus completing the planar combination of the micro-faults.

[0016] In step S4, the multi-directional attributes also include the coherent attributes of different shot spacing data volumes.

[0017] In step S4, when the incident angle is 6-24 degrees, the data volume can clearly identify micro-faults.

[0018] In step S4, when the incident angle is 0-6 degrees, the interference is severe and the micro-faults are unclear; when the incident angle is 24-30 degrees, the effective information is reduced and the micro-faults are also unclear.

[0019] The micro-fault fusion identification method based on five-dimensional data in this application has the following beneficial effects:

[0020] This application provides an integrated optimization and fusion method based on high-density wide-azimuth seismic acquisition, five-dimensional data processing and interpretation, and fine characterization of micro-faults from multi-azimuth data. This method can effectively identify micro-faults, discover complex small-block trap groups, and improve drilling success rate. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the process for identifying micro-faults based on five-dimensional data, as described in an embodiment of this application.

[0022] Figure 2(a) shows the signal-to-noise ratio of high-precision data acquired in a narrow azimuth region.

[0023] Figure 2(b) is a comparison of the signal-to-noise ratio of wide-azimuth (b) and narrow-azimuth (a) data collected in a certain area;

[0024] Figure 3 An overlay map of OVT (Outer Ventilation Transmission) area gather location data for a certain region;

[0025] Figure 4 Identify micro-faults in seismic data from different locations in a certain area;

[0026] Figure 5 Schematic diagram for identifying micro-faults using negative flower-like structural patterns;

[0027] Figure 6 To identify micro-faults using the coherence properties of data volumes with different shot spacings;

[0028] Figure 7 A comparison image of micro-faults identified from five-dimensional data and conventional data of a certain layer in a certain area. Detailed Implementation

[0029] The present application will be further described below with reference to the accompanying drawings and embodiments.

[0030] The following description provides several embodiments of the present invention. Different embodiments can be substituted or combined. Therefore, this application can also be considered to include all possible combinations of the same and / or different embodiments described. Thus, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then this application should also be considered to include embodiments containing one or more other possible combinations of features A, B, C, and D, even if such embodiments are not explicitly described in the following text.

[0031] Example 1

[0032] The method for identifying small faults based on five-dimensional data in this application includes: S1, acquiring seismic data through wide-azimuth acquisition and high-density wide-azimuth three-dimensional seismic acquisition technology with variable surface elements; S2, dividing the five-dimensional data into advantageous gather azimuth data that meet preset conditions; S3, using a geological comprehensive model based on five-dimensional data to guide the identification technology of small faults; and S4, characterizing small faults based on the multi-azimuth attributes adopted by the five-dimensional data to complete the planar combination of small faults.

[0033] This application establishes an integrated optimization and fusion method for high-density wide-azimuth seismic acquisition, five-dimensional data processing and interpretation, and fine characterization of micro-faults from multi-azimuth data. It promotes collaboration among multiple disciplines such as geophysics, geology, and geotectonics, thereby improving the accuracy of micro-fault identification.

[0034] Example 2

[0035] like Figure 1 As shown, this application provides a method for effectively identifying small faults in areas with low signal-to-noise ratio under complex surface geological conditions, including:

[0036] 1. To address the acquisition of complex fault zones under complex surface geological conditions, we conducted research and development on high-density wide-azimuth 3D seismic acquisition experiments. We aimed to find a balance between the high signal-to-noise ratio (SNR) but low resolution of large-area processing and the high resolution but low SNR of small-area processing. Ultimately, we adopted wide-azimuth acquisition and variable-area high-density wide-azimuth 3D seismic acquisition technology. The optimized parameters were: aspect ratio of 0.72, minimum area of ​​10m×10m, approximately 180 times of coverage, and a shot density of 1.8 million shots / square kilometer. The wide bandwidth of the wide-azimuth high-density acquisition data is shown in Figures 2(a) and 2(b). This significantly improved the SNR of the processed data, with 50% of the data having an SNR > 9, and the well and seismic data showed good agreement.

[0037] 2. Research and development of techniques for delineating the advantageous azimuth data from five-dimensional data sources. Under the influence of regional right-lateral extensional-torsional tectonic stress and fault depression, the main fault zone in a certain area extends in an east-west to northeast-east direction. Within its internal tectonic transition zone, a series of small regulating faults, primarily northeast and northwest, may develop, forming a complex set of small fault-block traps with the main fault, representing a favorable area for hydrocarbon accumulation. Narrow-azimuth conventional data suffers from unclear fault points and difficulty in identifying small faults when the observation direction is not perpendicular to them. Wide-azimuth five-dimensional data can overcome these shortcomings; however, theoretically, five-dimensional data can superimpose N local data volumes within a 360-degree azimuth. This results in a massive amount of data for processing and interpretation, hindering researchers' ability to quickly identify small faults, leading to a situation where effort is wasted. Therefore, delineating the advantageous azimuth data from gathers that can effectively identify small faults is a key technical challenge. Previous methods for dividing gather locations primarily fall into two categories: ① equal-angle division, which fails to consider inconsistent coverage times, leading to significant differences in signal-to-noise ratio (SNR) among the azimuth data; ② uneven division based on the attributes of the observation system, which is not closely integrated with the underground geological structure and cannot effectively reflect small faults. Therefore, this study innovatively establishes a principle for dividing gather locations based on geological understanding and SNR: ① considering the geological structure of the study area, and based on the regional tectonic background and fault strike, dividing the azimuth data into vertical and parallel azimuth data volumes; ② maintaining a relatively consistent coverage times while ensuring a high SNR. This results in a final division of a certain area into four azimuth superimposed data volumes, such as... Figure 3 As shown, five-dimensional data of the dominant azimuth can be obtained. Using multi-azimuth seismic data to identify micro-faults, it was found that the micro-faults reflected most clearly are those in the azimuth data volumes approximately perpendicular to the fault strike, such as... Figure 4 As shown, the micro-faults in the seismic data of the OVT domain at azimuths 20-37 and 200-237 are clearer, and micro-faults with a displacement of about 10 meters can be identified.

[0038] 3. Geological comprehensive model based on five-dimensional data to guide the identification technology of micro-faults: The main fault zone in a certain area is a fault system formed under the action of extensional strike-slip couple. Through the study of regional geological patterns, tectonic movements and the main fault system, such as... Figure 5 As shown, the development of the main fault transform zone exhibits a negative flower-like structural pattern, thus helping interpreters to clarify complex structural styles and quickly and reasonably identify micro-faults. Figure 5 In the profile, the five-dimensional data under the negative flower-like structural model identified eight more micro-faults than conventional data. In the past, in areas with low signal-to-noise ratios under complex surface geological conditions, the local reflection amplitude anomalies caused by small faults in conventional seismic data processing were often masked by various factors, resulting in the inability to effectively identify micro-faults and low confirmation of small block traps. However, based on the relatively high resolution of five-dimensional data, the seismic characteristic method can better identify micro-faults on the profile.

[0039] 4. Based on five-dimensional data, multi-directional attributes such as coherence enhancement, curvature, dip volume, and surface slicing are used to characterize micro-faults, completing the planar combination of micro-faults. In particular, the coherence attributes of data volumes with different shot spacings can finely describe micro-faults, such as... Figure 6 As shown, data volumes at intermediate angles (incident angles of 6-24 degrees) clearly identify micro-faults; data volumes at near angles (incident angles of 0-6 degrees) suffer from severe interference, resulting in unclear micro-faults; data volumes at far angles (incident angles of 24-30 degrees) contain less effective information, also leading to unclear micro-faults. Conventional data acquisition and processing methods using coherence and tilt volume attribute analysis techniques result in multiple interpretations of the identified micro-faults. However, the high coverage and high signal-to-noise ratio provided by five-dimensional data enhance the effectiveness of various attribute-based techniques, improving the accuracy and number of micro-faults identified on the plane.

[0040] 5. Effective identification of small faults in areas with low signal-to-noise ratio under complex surface geological conditions has always been a technical challenge in exploration work. The identification of small faults is typically handled by structural interpretation personnel. Previously, these personnel only participated in the data interpretation phase, while seismic acquisition and processing were handled by other departments, resulting in well-seismic mismatch and inaccurate imaging of small faults. Although high-density, wide-azimuth seismic acquisition, as used in this project, is becoming more widespread, processing and interpretation techniques are not yet widely applied. Therefore, the oilfield attached great importance to this, establishing a joint task force for acquisition, processing, and interpretation. Quality control was implemented starting from seismic acquisition—the source of small fault identification—with the needs of interpretation personnel as the guiding principle. This resulted in the acquisition of wide-bandwidth raw data rich in both high and low frequency information, laying the foundation for the effective application of subsequent seismic data processing and interpretation techniques. During the five-dimensional data processing, researchers closely communicated, employing detailed geological briefings, drilling-controlled velocity models, and geologically guided advantageous gather azimuth division techniques. This resulted in a set of effective methods for the fusion and identification of high-density, wide-azimuth seismic acquisition, five-dimensional data processing and interpretation, and multi-azimuth data micro-faults. Figure 7 As shown, Figure 7 The red area represents small faults identified by five-dimensional data, while the black area represents small faults identified by conventional data. Ultimately, more micro-faults were identified from the five-dimensional data, and the distribution of these micro-faults exhibited regularity and rationality. A number of complex small fault block structures with high-zone loops and main fault transition zone loops were discovered. Subsequently, 19 wells selected for drilling yielded high-yield oil flows, with a drilling success rate of 83%, far exceeding the previous success rate of approximately 45%. The results of rolling exploration of complex small fault blocks are significant.

[0041] The advantages of this application are as follows:

[0042] 1. This application adopts quality control from the source of micro-fault identification to the design of seismic acquisition, to ensure the effective use of subsequent seismic data processing and interpretation techniques.

[0043] 2. The five-dimensional data obtained by high-density wide-azimuth acquisition and processing in this application has azimuth information in the gathers, which can be superimposed to obtain seismic data in multiple azimuths. By interpreting the data in different azimuths, the accuracy of the interpretation of micro-faults can be improved, and micro-faults that cannot be identified by conventional seismic data can be identified.

[0044] 3. Based on the multi-directional, multi-scale coherence volume and dip volume multi-attribute analysis technology of five-dimensional data, this application can accurately identify more micro-faults.

[0045] In this application, a five-dimensional data dominance orientation division technique based on geological understanding is employed: ① Considering the geological structure of the study area, and based on the regional tectonic background and fault strike, azimuth data volumes are divided parallel to or perpendicular to the faults in the study area, resulting in the most reasonable azimuth division; ② While ensuring the signal-to-noise ratio, the coverage times are kept basically consistent. Based on the above division principles, the number of azimuth overlay data volumes for a given area is determined, yielding the dominant azimuth five-dimensional data. The dominant azimuth data can be effectively used to identify small and micro-faults.

[0046] This application establishes an integrated optimization and fusion method based on high-density wide-azimuth seismic acquisition, five-dimensional data processing and interpretation, and fine characterization of micro-faults from multi-azimuth data. This method can effectively identify micro-faults, discover complex small-block trap groups, and improve drilling success rate.

[0047] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for identifying micro-faults based on five-dimensional data, characterized in that, include: S1 acquires seismic data using wide-azimuth acquisition and variable-area high-density wide-azimuth 3D seismic acquisition technology; S2, divide the five-dimensional data advantage set orientation data that meets the preset conditions; S3, a technology for identifying micro-faults based on a comprehensive geological model using five-dimensional data; S4, based on five-dimensional data, uses multi-directional attributes to characterize micro-faults and completes the planar combination of micro-faults; In step S1, the aspect ratio is 0.72, the minimum area is 10m×10m, the number of coverages is 180, and the ballistic density is 1.8 million ballistics / square kilometer. In step S2, a division principle for the orientation of gathers is established based on geological understanding and signal-to-noise ratio: according to the geological structure of the study area, based on the regional tectonic background and the direction of the faults, orientation data volumes perpendicular to and parallel to the faults are divided; while ensuring the signal-to-noise ratio, the number of coverages is kept consistent. In step S3, based on regional geological patterns, tectonic movements, and the main fault system, the negative flower-like tectonic model of the main fault transformation zone is clarified. In step S4, the micro-faults are characterized by multi-directional attributes such as coherence enhancement, curvature, tilt volume, and surface slices based on five-dimensional data, thus completing the planar combination of the micro-faults. In step S4, when the incident angle is 6-24 degrees, the data volume can clearly identify micro-faults.

2. The method for small-scale tomographic fusion identification based on five-dimensional data according to claim 1, characterized in that, In step S2, the first region is determined to be divided into four directional superimposed data volumes to obtain the dominant directional five-dimensional data.

3. The method for small-scale tomographic fusion identification based on five-dimensional data according to claim 1, characterized in that, By using multi-azimuth seismic data to identify micro-faults, it was found that the micro-faults in the 20-57 and 200-237 azimuth seismic data of the OVT domain were the clearest.

4. The method for small-scale tomographic fusion identification based on five-dimensional data according to claim 1, characterized in that, In step S4, the multi-directional attributes also include the coherence attributes of different shot-receiver distance data volumes.

5. The method for small-scale tomographic fusion identification based on five-dimensional data according to claim 1, characterized in that, In step S4, when the incident angle is 0-6 degrees, the interference is severe and the micro-faults are unclear; when the incident angle is 24-30 degrees, the effective information is reduced and the micro-faults are also unclear.

Images