Pre-stack OVT domain low-order fault identification method based on azimuth and frequency domain control

Abstract

The present application relates to the technical field of geophysical exploration, in particular to a pre-stack OVT domain low-order fault identification method based on azimuth and frequency domain control. The method comprises the following steps: performing pre-stack OVT domain gather anisotropy analysis; analyzing target area tectonic stress characteristics, performing OVT domain gather data azimuth optimization and division, and performing partial data stacking on OVT gathers; constructing data volumes controlled by different azimuths and frequency domains through improved generalized S transform spectral decomposition; extracting coherent attribute analysis; and drawing a target area fault distribution plan. The method can effectively improve the accuracy and reliability of low-order fault interpretation, meet the needs of fine fault system interpretation at different exploration and development stages, and provide reliable basis for oilfield exploration and development target optimization and drilling and completion scheme design.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of geophysical exploration, in particular to a pre-stack OVT domain low-order fault identification method based on azimuth and frequency domain control. BACKGROUND

[0002] Fault interpretation is the key to structural interpretation of oil and gas exploration, and the accuracy and rationality of fault interpretation directly affect the accuracy of structural interpretation. For a long time, researchers have made a lot of efforts around the accurate description of fault system, and have proposed and applied many description methods for post-stack seismic data, successfully extracting many discontinuous attribute bodies of prominent fault information from three-dimensional seismic data. Among them, the coherent body technology is the most widely used and mature, such as Chinese patent application CN105334534A discloses a low-order fault interpretation method based on structural pattern guidance, mainly including the following steps: 1) loading post-stack high-precision three-dimensional seismic data, well logging data and production data; 2) seismic data analysis and processing; 3) three-dimensional visualization browsing of the processed seismic data body to determine the basic structural framework of the main fault system; 4) combining local tectonic stress field, according to the combination relationship between the main fault and the secondary fault, a low-order fault interpretation mode is established; 5) using frequency division coherent body, curvature body, edge detection and ant body technology, the low-order fault is identified and combined in plane and profile; 6) using production dynamics to test the low-order fault interpretation result, adjusting the fault interpretation mode to obtain the fault system diagram consistent with the oil reservoir development.

[0003] Although this technology has good noise suppression ability, for local trend low-order faults or seismic data with poor data quality, the fault detection effect is still not ideal.

[0004] In recent years, with the development of OVT technology, high-density data provides a good data basis for fine interpretation of low-order faults, and its wide azimuth and wide frequency characteristics can improve the fine identification of faults, especially low-order faults. However, existing researches mainly focus on the selection of stacking processing parameters of azimuth and offset, which can identify and distinguish faults to some extent, but the detection effect of developed local trend low-order faults is still not ideal. At present, there is no related report on fault identification in frequency domain based on pre-stack OVT domain gathers. SUMMARY

[0005] The main purpose of the present application is to provide a pre-stack OVT domain low-order fault identification method based on azimuth and frequency domain control. The present application optimizes the selection of azimuth and frequency domain, effectively improving the accuracy and reliability of low-order fault interpretation.

[0006] To achieve the above purpose, the present application adopts the following technical scheme:

[0007] The application provides a pre-stack OVT domain low-order fault identification method based on azimuth angle and frequency domain control, which comprises the following steps: performing pre-stack OVT domain gather anisotropy analysis; analyzing target area structural stress characteristics, performing OVT domain gather data azimuth angle division and division, and performing partial data stacking on the OVT gathers; constructing different azimuth angle and frequency domain controlled data bodies by improving generalized S transform spectrum decomposition; extracting coherent attribute analysis; and drawing a target area fault distribution plan.

[0008] Further, the pre-stack OVT domain data anisotropy analysis is performed, first, the amplitude slice of the sampling point is analyzed, and the anisotropy characteristics of the amplitude slice along the target layer are observed; if the gather data anisotropy characteristics are obvious, the low-order fault identification can be performed, otherwise, the low-order fault identification cannot be performed.

[0009] Further, the pre-stack OVT domain data refers to the pre-stack wide-azimuth gather data formed by the OVT processing technology; the amplitude slice analysis is to detect the anisotropy characteristics of the data body by detecting the amplitude value of the sampling point by using the seismic data processing module in the interpretation software.

[0010] Further, the analysis of the target area structural stress characteristics comprises determining the horizontal maximum principal stress direction of the target area and determining the main fault development direction; the average fault throw size and the average stratum velocity of the target area fault are determined according to the drilling data analysis.

[0011] Further, the azimuth angle division should follow the principle of equal stacking times in the range of the offset, so as to highlight the azimuth anisotropy characteristic difference of the low-order fault; the same or similar azimuth angle coverage is ensured according to the extraction principle through the analysis of the observation system.

[0012] Further, the vertical main fault direction, the parallel main fault direction, the positive oblique main fault direction and the reverse oblique main fault direction are selected for the azimuth angle division.

[0013] Further, the seismic data processing and interpretation system is used to perform partial stacking on the OVT gather data.

[0014] Further, the improved generalized S transform spectrum decomposition is performed, the spectrum decomposition principle is determined according to the seismic reflection tuning principle, the low-order fault reflection characteristics are highlighted to the greatest extent according to the development size of the low-order fault throw, so as to realize the clear identification of the low-order fault; the improved generalized S transform spectrum decomposition is performed on the partial stacking data according to the tuning frequency, that is, the different azimuth angle and frequency domain controlled data bodies are constructed.

[0015] Further, the improved generalized S transform expression is as follows:

[0016]

[0017] In the formula, S (τ, f) is the time-frequency spectrum value after the improved S transform, h (t) is the time-frequency spectrum value of the input signal, τ is time, f is frequency, and p is a Gaussian window adjustment parameter, which ranges from 0 to 1.

[0018] Further, the coherent attribute of the data volume controlled by different azimuth angles and frequency domains is extracted, and comparative analysis is conducted in combination with the characteristics of the target area, so that the optimal parameter combination for identifying the low-order faults in the OVT domain controlled by azimuth angles and frequency domains is determined.

[0019] Compared with the prior art, the present application has the following advantages:

[0020] According to the present application, the anisotropy of the pre-stack OVT domain gather is analyzed first, the basic characteristics of the tectonic stress and fault development in the area are determined according to the geological and logging data analysis, and then the azimuth angle optimization and division of the OVT domain gather data are conducted, and part of the OVT gather data is stacked; further, the frequency domain optimized data volume is constructed through the improved generalized S transform spectrum decomposition, and finally, the fault distribution plan of the target area is drawn according to the coherent attribute extracted by the optimal parameter combination.

[0021] The present application fully considers the anisotropy and frequency domain variation characteristics of the low-order faults, can reflect some low-order faults that are not easy to be identified by conventional data volumes, and fills the blank of the lack of similar research in the field.

[0022] The present application can effectively improve the accuracy and reliability of the low-order fault interpretation, meet the needs of fine fault system interpretation at different exploration and development stages, provide reliable basis for the oilfield exploration and development target optimization and drilling and completion plan design, and has good application effect and popularization prospect. BRIEF DESCRIPTION OF DRAWINGS

[0023] The drawings accompanying the specification of the present application serve to provide a further understanding of the present application, and the schematic embodiments of the present application and the description thereof serve to explain the present application, and do not constitute an improper limitation on the present application.

[0024] Figure 1 The flowchart of the pre-stack OVT domain low-order fault identification method based on the azimuth angle and frequency domain control in the embodiment 1 of the present application;

[0025] Figure 2 The OVT domain gather anisotropy analysis graph of the research area in the embodiment 1 of the present application: a. amplitude slice, obvious anisotropy; b. amplitude slice, poor anisotropy;

[0026] Figure 3 The azimuth angle optimization and division scheme of the OVT domain gather in the embodiment 1 of the present application;

[0027] Figure 4 Seismic data volume controlled by different azimuth and frequency domain in embodiment 1 of the present application;

[0028] Figure 5 Pre-stack OVT domain low-order fault coherence attribute map controlled by optimal parameter combination based on azimuth and frequency domain in embodiment 1 of the present application;

[0029] Figure 6 Low-order fault coherence attribute map of conventional seismic data in embodiment 1 of the present application;

[0030] Figure 7 Conventional seismic profile in embodiment 1 of the present application;

[0031] Figure 8 Seismic profile controlled by optimal parameter combination based on azimuth and frequency domain in embodiment 1 of the present application;

[0032] Figure 9 Structure map of upper top surface of Sha 3 in working area in embodiment 1 of the present application. DETAILED DESCRIPTION

[0033] It should be noted that the following detailed description is exemplary in nature and is intended to provide further description of the present application. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0034] It is to be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments consistent with the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, steps, operations, elements, and / or groups thereof, but do not preclude the presence or addition of one or more other features, steps, operations, elements, and / or groups thereof.

[0035] In order to enable a person skilled in the art to more clearly understand the technical solutions of the present application, the technical solutions of the present application will be described in detail below in combination with specific embodiments.

[0036] Embodiment 1

[0037] As shown in the figure, the pre-stack OVT domain low-order fault identification method based on azimuth and frequency domain control comprises the following steps: Figure 1

[0038] ​In step 101, anisotropy analysis is performed on the pre-stack OVT domain data. Using the seismic data processing module in the interpretation software, the instantaneous amplitude and time difference at different data points are detected to assess the anisotropy characteristics of the data volume. Specifically, amplitude slice analysis is first performed on the sampling points to observe the anisotropy characteristics along the target layer. The amplitude slice represents the instantaneous amplitude values ​​of each data point read from the gather along the target layer. If the amplitude values ​​of different data points on the amplitude slice show significant variations, such as… Figure 2 As shown in Figure a, this indicates that the gather data exhibits significant anisotropic characteristics, and OVT domain data can be used for low-order tomography identification; otherwise, if the amplitude values ​​of different data points on the amplitude slice change very little or not at all, such as Figure 2 As shown in b, the trace gathering data exhibits inconspicuous anisotropy and cannot be used for low-order tomography identification using OVT domain data.

[0039] In step 102, the direction of the principal stress was analyzed primarily using geological data from the study area. Based on wellbore collapse azimuth or imaging logging data, the direction of the maximum horizontal principal stress in the area was determined to be northeast-east, thus confirming the orientation of the main faults. Furthermore, statistical analysis of drilled well data revealed that the average fault displacement (H) in the study area was 18 m, and the average formation velocity (V) was 2740 m / s. Based on this, according to the theory of azimuth anisotropy, azimuth angle optimization and division were performed. To ensure high coverage and signal-to-noise ratio in some overlay processing, the azimuth angle optimization should adhere to the principle of maintaining a relatively balanced number of overlays within the shot-receiver distance range to highlight the differences in azimuth anisotropy characteristics of minor faults. The 3D seismic data in the study area was acquired using a wide azimuth angle acquisition method, resulting in good seismic data quality, high signal-to-noise ratio and resolution, and good amplitude preservation.

[0040] Through analysis of the observation system, and based on the extraction principle to ensure that each azimuth angle has the same or similar coverage, in order to highlight the differences in azimuth anisotropy characteristics caused by faults, four azimuth angle division schemes were initially determined, such as... Figure 3 As shown: 10°~80°, 60°~130°, 100°~170°, 330°~40°. These four azimuths have the following relationships with the main fault strikes in the work area: perpendicular to the main fault, parallel to the main fault, or perpendicular to the main fault. This division method, which is perpendicular, parallel, and oblique to the main fault, can highlight the information of most faults to the greatest extent, while also taking into account the requirements of high amplitude preservation and clear imaging for some stacked data. Based on the optimal azimuth division, OVT gather data were partially stacked in these four azimuths using a seismic data processing and interpretation system.

[0041] In step 103, for some of the superimposed data, data volumes with different azimuth angles and frequency domain controls are constructed by improving the generalized S-variance spectral decomposition; the improved generalized S-variance expression is:

[0042]

[0043] where S(τ, f) is the time-frequency spectrum value after the improved S transform, h(t) is the time-frequency spectrum value of the input signal, τ is time, f is frequency, and p is a Gaussian window adjustment parameter with a value range of 0-1.

[0044] The principle of spectrum decomposition is determined according to the seismic reflection tuning principle. According to the development size of fault throw, the fault reflection characteristics are highlighted to the greatest extent, so as to realize clear identification of faults. According to the seismic wave tuning principle, different geological bodies have corresponding tuning thickness. Using the average size of fault throw (H) of 18 m and the average velocity (V) of stratum of 2740 m / s, according to the solving formula f = V / (4*H), the tuning frequency f of the fault in the area is solved as 38 Hz, so the improved generalized S transform spectrum decomposition based on the tuning frequency (38 Hz) of the fault in the area can reflect the fault characteristics to the greatest extent. The determination of the tuning frequency in the spectrum decomposition is based on the specific situation of the actual work area; the improved generalized S transform spectrum decomposition is performed on the azimuth part of the stacked data according to the tuning frequency, that is, the data volume controlled by different azimuth angles and frequency domains is constructed, as shown in FIG. 2. Figure 4

[0045] In step 104, the coherent attribute is extracted from the data volume controlled by different azimuth angles and frequency domains, and comparative analysis is performed in combination with the geological characteristics of the study area, so as to determine that the optimal parameter combination for identifying low-order faults in the OVT domain based on the azimuth angle and the frequency domain control in the area is: the azimuth angle is 60°-130°, and the main frequency of the spectrum decomposition is 38 Hz. The corresponding azimuth direction of the combination is perpendicular to the strike of the main fault, and the main frequency corresponds to the tuning frequency. The determination of the optimal parameter combination is based on the specific situation of the actual work area. It can be seen from the comparison of the coherent attribute graphs extracted from the data volumes with different parameter combinations that the coherent attribute graph completed based on the optimal parameter combination has the best effect on the identification of low-order faults, as shown in FIG. 3. The fault detection graph well presents the planar distribution characteristics of the low-order faults; and the coherent attribute based on other azimuth angle and frequency domain parameter combinations has a poorer effect on the detection of low-order faults, as shown in FIG. 4. This also shows that the optimization of the azimuth angle and the frequency domain plays an important role in the identification of low-order faults. Figure 5 Figure 6 Meanwhile, the characteristics of the low-order faults on the seismic profile are also clearer, in which the low-order fault shown in FIG. 5 appears as a phase axis twist feature on the conventional seismic profile, while the phase axis of the fault on the seismic profile completed by using the new method appears as a fault, as shown in FIG. 6. The reflection characteristics of the section are clearer, and the fault is very easy to identify.

[0046] Figure 7 Figure 8

[0047] ​​​​​In step 105, according to the coherent attribute map extracted from the optimal parameter combination in step 104, the fault system combination is optimized, and the structural map of the top surface of the third member of Shahejie Formation is interpreted, as shown in Fig. Figure 9 .

[0048] The method described in the embodiment improves the accuracy and reliability of drawing the fault plane map, and provides an important reference for efficient exploration and development of fault block reservoirs.

[0049] The above embodiment is a preferred embodiment of the present application, but the embodiments of the present application are not limited to the above embodiment, and any changes, modifications, substitutions, combinations, simplifications made without departing from the spirit and principles of the present application should be equivalent replacement methods, and are all included in the protection scope of the present application.

Claims

1. A pre-stack OVT domain low-order fault identification method based on azimuth angle and frequency domain control, characterized in that, It comprises the following steps: Carrying out pre-stack OVT domain gather anisotropy analysis; analyzing target area structural stress characteristics, carrying out OVT domain gather data azimuth angle division and optimization, and carrying out partial data stacking of OVT gather; constructing data volume controlled by different azimuth angles and frequency domains through improved generalized S transform spectral decomposition; extracting coherent attribute analysis; drawing target area fault distribution plan; Carrying out pre-stack OVT domain data anisotropy analysis, first analyzing amplitude slice of sampling points, and observing anisotropy characteristics of amplitude slice along target layer; If gather data anisotropy characteristics are obvious, it can be used for low-order fault identification, otherwise, it cannot be used for low-order fault identification; The pre-stack OVT domain data refers to pre-stack wide-azimuth gather data formed through OVT processing technology; the amplitude slice analysis is to detect data volume anisotropy characteristics by detecting amplitude value of sampling points using seismic data processing module in interpretation software; Analyzing target area structural stress characteristics comprises determining horizontal maximum principal stress direction of target area, and determining main fault development trend; according to drilling data analysis, determining average fault throw size and average stratum velocity of target area; Azimuth angle division and optimization should follow the principle of equal stacking times in offset range, so as to highlight azimuth anisotropy characteristic difference of low-order fault; through observation system analysis, ensure same or similar coverage of each azimuth angle according to extraction principle; Selecting vertical main fault direction, parallel main fault direction, positive oblique main fault direction, and reverse oblique main fault direction for azimuth angle division; Carrying out improved generalized S transform spectral decomposition, spectral decomposition principle is determined according to seismic reflection tuning principle, and according to low-order fault throw development size, highlight low-order fault reflection characteristics to the greatest extent, so as to realize clear identification of low-order fault; According to tuning frequency, carry out improved generalized S transform spectral decomposition on azimuth angle partial stacking data, namely constructing data volume controlled by different azimuth angles and frequency domains; Extract coherent attribute from data volume controlled by different azimuth angles and frequency domains, and compare and analyze according to target area characteristics, so as to determine optimal parameter combination of azimuth angle and frequency domain controlled OVT domain low-order fault identification.

2. The method of claim 1, wherein, Analyzing target area structural stress characteristics comprises determining horizontal maximum principal stress direction of target area, and determining main fault development trend; according to drilling data analysis, determining average fault throw size and average stratum velocity of target area.

3. The method of claim 1, wherein, Azimuth angle division and optimization should follow the principle of equal stacking times in offset range, so as to highlight azimuth anisotropy characteristic difference of low-order fault; through observation system analysis, ensure same or similar coverage of each azimuth angle according to extraction principle.

4. The method of claim 1, wherein, Using seismic data processing and interpretation system, carrying out partial stacking of OVT gather data.

5. The method of claim 1 or 4, wherein, Improved generalized S transform expression is as follows: In the formula, S(τ, f) is time-frequency spectrum value after improved S transform, h(t) is time-frequency spectrum value of input signal, τ is time, f is frequency, and p is Gaussian window adjustment parameter, and its value range is 0-1.

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