Complex broken basin fine structure interpretation method, electronic equipment and storage medium

Abstract

The invention discloses a complex fault basin fine structure interpretation method, electronic equipment and a storage medium, and the method comprises the steps: determining the development direction of a main fracture of a target region based on original seismic data, and carrying out the dominant azimuth reconstruction of the original seismic data; performing multidirectional dip angle scanning on the seismic data after the dominant azimuth reconstruction to obtain a dip angle data body; by taking the inclination angle data volume as a constraint, carrying out structure-oriented filtering noise suppression on the seismic data after the dominant azimuth reconstruction; performing fault likelihood attribute analysis on the seismic data after noise suppression to obtain a fault likelihood attribute data volume; carrying out refined fault likelihood attribute analysis on the fault likelihood attribute data volume to obtain fault volume data; and the fault volume data and the seismic data after noise suppression are fused, and fine structure interpretation of the section and the plane of the research area is completed. According to the method, the distribution characteristics of the fractures in the complex target area can be accurately described, and prediction of the reservoir development area controlled by the fractures can be effectively guided.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of oil and gas field development and mineral evaluation and prediction, and more particularly relates to a fine structure interpretation method for a complex faulted basin, an electronic device and a storage medium. BACKGROUND

[0002] In the process of oil and gas exploration and development, the existence of faults can serve as a channel for oil and gas migration and as a barrier to form the boundary of structural traps. Therefore, the fine depiction of fault systems is closely related to the evaluation of oil and gas migration system and the description of traps. Realizing more advanced coherent body calculation and fault enhancement technology is the research focus in the field of oil and gas exploration and development.

[0003] The quality of seismic data is affected by various factors such as random noise, observation system design, acquisition footprint, etc. The signal-to-noise ratio of the data is often low, and the imaging quality of events, faults and special rock bodies is poor, which leads to multiple solutions in the interpretation of faults and horizons in the process of reservoir prediction. In order to improve the accuracy of structural interpretation of seismic data and enhance the reliability of reservoir prediction, interpreters have made many explorations on how to better present fault information on profiles and more reasonably display fault combination information on planes based on post-stack seismic data. For example, coherent body, likelihood data, ant body and curvature attribute body are used. Among them, the three-dimensional coherent value data body is obtained by calculating the correlation value between the horizontal and vertical adjacent channels, so as to convert the three-dimensional seismic amplitude data body into a coherent data body, and the effect is limited by the quality of seismic data; the ant body has poor effect in noise suppression, and its ability to depict faults and planar combination is limited, and it is mainly suitable for the prediction of fractured reservoirs; the likelihood attribute has good prediction effect on small fractures and faults, but it is difficult to identify large faults and planar combination of faults; the curvature attribute is difficult to quantitatively characterize parallel faults and complex structures with directional changes on the horizontal plane or along the layer plane.

[0004] In the sea areas of China, such as the extensional strike-slip basin in the East China Sea and the strong extensional basin in the South China Sea, especially in the deep and complex fault development area, the quality of seismic data is poor, and the continuity, boundary and combination characteristics of fault prediction are often poor. The above commonly used coherent techniques cannot accurately depict the distribution characteristics of faults in the complex target area, cannot provide sufficient basis for structural interpretation, and cannot effectively guide the prediction of reservoir development areas controlled by faults. SUMMARY

[0005] The purpose of the present application is to provide a fine structure interpretation method for a complex faulted basin, an electronic device and a storage medium, which can accurately depict the distribution characteristics of faults in the complex target area and effectively guide the prediction of reservoir development areas controlled by faults.

[0006] To achieve the above object, in a first aspect, the application provides a fine structure interpretation method for complex fault-depression basin, comprising:

[0007] Based on the original seismic data, the development direction of the main fault in the target area is determined, and the original seismic data is reconstructed in the dominant direction;

[0008] The seismic data reconstructed in the dominant direction is subjected to multi-directional dip scanning to obtain a dip data volume;

[0009] The seismic data reconstructed in the dominant direction is subjected to structure-oriented filtering noise suppression with the dip data volume as a constraint to obtain noise-suppressed seismic data;

[0010] The noise-suppressed seismic data is subjected to fault likelihood attribute analysis to obtain a fault likelihood attribute data volume;

[0011] The fault likelihood attribute data volume is subjected to refined fault likelihood attribute analysis to obtain a fault volume data;

[0012] The fault volume data and the noise-suppressed seismic data are fused to complete fine structure interpretation of the profile and plane of the study area.

[0013] Optionally, the method of determining the development direction of the main fault in the target area based on the original seismic data and reconstructing the original seismic data in the dominant direction comprises:

[0014] The main fault direction analysis of the original seismic data is performed to select the direction perpendicular to the main fault as the dominant direction of the seismic data, and the seismic data is reconstructed in the dominant direction, so that the main direction of the reconstructed seismic survey network is perpendicular to the main fault direction.

[0015] Optionally, the method of reconstructing the seismic data in the dominant direction and performing structure-oriented filtering noise suppression comprises:

[0016] The seismic data reconstructed in the dominant direction is subjected to structure-oriented filtering noise suppression, and the seismic data reconstructed in the dominant direction is subjected to directional filtering with edge detection and edge protection to strengthen the continuity of the seismic events and highlight the discontinuous features.

[0017] In the process of structure-oriented filtering noise suppression, the structure of the target area is subjected to structure-oriented filtering with the dip detection data volume as a constraint, the information parallel to the events is subjected to smoothing processing, and the information perpendicular to the event direction is retained.

[0018] The seismic profile of the seismic data after the structure-oriented filter noise suppression is subjected to quality control analysis, the noise profile is extracted, it is judged whether effective information exists in the noise profile, and the seismic profile before and after the noise suppression is compared, the continuity of the seismic event after the noise suppression, the signal-to-noise ratio, and whether the fracture information is clearer are analyzed, if the effective information exists in the noise profile and / or the continuity of the seismic event after the noise suppression, the signal-to-noise ratio, and the fracture information are not clearer, the structure-oriented filter is re-performed until the extracted noise profile has no effective information and the continuity of the seismic event after the noise suppression, the signal-to-noise ratio, and the fracture information are clearer.

[0019] Optionally, the fault likelihood attribute analysis on the seismic data after the noise suppression comprises:

[0020] The fault likelihood attribute between any two seismic traces is calculated by the following formula:

[0021]

[0022] Wherein:

[0023]

[0024] In the formula, S is the fault likelihood attribute value between two seismic traces, (x A ,y A ) and (x B ,y B ) are coordinates corresponding to data points of two seismic traces, dt represents a sampling interval, t represents time, t1 represents the top boundary of a time window when the likelihood attribute is calculated, t2 represents the bottom boundary of the time window, and u is an attribute value of a corresponding sample point of seismic data.

[0025] Optionally, the fault likelihood attribute analysis on the fault likelihood attribute data volume after the refinement comprises:

[0026] With the information of the stratigraphic dip angle and the azimuth angle as constraints, a multi-round iteration calculation is performed to complete the refined fault likelihood attribute analysis and obtain the fault volume data.

[0027] Optionally, the refined fault likelihood attribute analysis is calculated by the following formula:

[0028] S thinned = F(D E [K l *S]-w) n

[0029] Wherein, S thinned is the refined fault likelihood attribute value, F represents an iteration function, n is the number of iterations, and K lThe maximum value of the maximum likelihood attribute background noise, S is the fault likelihood attribute value between two seismic traces, D E The maximum value of the maximum likelihood attribute background noise, S is the fault likelihood attribute value between two seismic traces, D

[0030] Optionally, the fault body data and the noise-suppressed seismic data are fused to complete fine structure interpretation of a profile and a plane of the study area, including:

[0031] The fault body data and the noise-suppressed seismic data are fused to superimpose and display the fault body data in a seismic profile and plane.

[0032] In the fault interpretation process of a faulted basin, small cracks and fracture-cavity information are filtered out by controlling the size of the fault body value to complete profile and plane interpretation of main faults.

[0033] Optionally, the method further includes: when the fault plane is combined, the stratum dislocation information is combined to complete omnibearing intelligent optimization and recombination of the fault.

[0034] In a second aspect, the present application provides an electronic device, the electronic device comprising:

[0035] at least one processor; and

[0036] a memory in communication with the at least one processor; wherein

[0037] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the complex faulted basin fine structure interpretation method of the first aspect.

[0038] In a third aspect, the present application provides a non-transitory computer readable storage medium storing computer instructions for causing a computer to execute the complex faulted basin fine structure interpretation method of the first aspect.

[0039] The present application has the following beneficial effects:

[0040] (1) The conventional coherent technique has poor anti-interference ability in detecting fault information, and when the stratum dip angle is too large and changes rapidly, the predicted fault result often has errors. The interpretation method of the present application can remove noise (especially mid-deep layer noise) and other interference information in the noise suppression process while retaining the fault information of the original seismic data, thereby improving the data quality and preserving the fault edge information.

[0041] (2) The interpretation method of the present application adopts a fault refinement calculation method based on different dip angle and azimuth data control when refining fault likelihood bodies, and for a complex faulted basin, the dip angle and azimuth information of the main trunk fault can be selectively used to strengthen the imaging of the main trunk fault, and similarly, the dip angle and azimuth information of secondary, tertiary or minor faults can be used to constrain the calculation of the fault body, so as to further highlight the main fault information in the present reservoir prediction process.

[0042] (3) The interpretation method of the present application is more clear in the breakpoint position on the profile fused by the final seismic data and the fault body data, can guide the interpreter to quickly and accurately complete the fine structure interpretation, improve the accuracy of reservoir prediction in the study area, improve the accuracy and work efficiency of the interpreter in fault interpretation, and promote the efficient exploration and development of complex faulted basin structure-lithology oil and gas reservoirs.

[0043] (4) In the process of fault combination on the plane, in addition to the plane-section combination method, the development of the fault and the dislocation phenomenon of the strata on the hanging wall and foot wall of the fault can be well displayed in the isochronal or layer slice of the seismic fault body fusion data, guiding the interpreter to complete the plane combination of the fault.

[0044] The system of the present application has other characteristics and advantages, which will be apparent or will be described in detail in the accompanying drawings and subsequent detailed description incorporated herein, which together serve to explain the specific principles of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0045] The above and other objects, features and advantages of the present application will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings, in which like reference characters refer to like parts throughout the figures, and wherein:

[0046] Figure 1 A flow chart of a fine structure interpretation method for a complex faulted basin according to the present application is shown.

[0047] Figure 2 The development characteristics of the faults in the study area and the rose diagram of the main trunk faults in one embodiment of the present application are shown.

[0048] Figure 3 An optimal survey network main direction diagram in one embodiment of the present application is shown.

[0049] Figure 4a And Figure 4b Seismic profiles before and after seismic data advantage direction reconstruction in one embodiment of the present application are shown.

[0050] Figure 5a and Figure 5b respectively show the seismic profile before and after the guided filtering noise suppression in one embodiment of the present application.

[0051] Figure 6 show the noise profile after the noise suppression in one embodiment of the present application.

[0052] Figure 7 show the profile effect after the seismic fault body fusion in one embodiment of the present application.

[0053] Figure 8 show the plane effect after the seismic fault body fusion in one embodiment of the present application.

[0054] Figure 9a and Figure 9b respectively show the artificial interpretation result and the data-driven fault body plane result in one embodiment of the present application. DETAILED DESCRIPTION

[0055] The present application will be described in more detail by referring to the attached drawings. Although the preferred embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so as to make the present application more thorough and complete, and to fully convey the scope of the present application to those skilled in the art.

[0056] Example 1

[0057] As shown in Figure 1 , the present embodiment provides a complex fault basin fine structure interpretation method based on seismic fault body technology, comprising:

[0058] S1: based on the original seismic data, determining the development direction of the main fault in the target area and performing advantage direction reconstruction on the original seismic data;

[0059] This step specifically includes:

[0060] Based on seismic, logging and geological data, the main fault direction of the original seismic data is analyzed, the direction perpendicular to the main fault is selected as the advantage direction of the seismic data, and the advantage direction reconstruction of the seismic data is performed, so that the main direction (i.e. inline line) of the reconstructed seismic survey network is perpendicular to the main fault direction.

[0061] S2: performing multi-azimuth dip scanning on the seismic data after the advantage direction reconstruction to obtain a dip data volume;

[0062] This step specifically includes:

[0063] The seismic data after the dominant azimuth reconstruction is subjected to multi-azimuth dip scanning to obtain a dip data volume, and a formula for calculating a stratigraphic dip Dip is:

[0064] Dip = ΔT / ΔX;

[0065] wherein ΔT represents a sampling interval in a time domain direction, and ΔX represents a sampling interval in a space domain direction.

[0066] S3: subjecting the seismic data after the dominant azimuth reconstruction to structure-oriented filtering noise suppression with the dip data volume as a constraint to obtain the seismic data after the noise suppression;

[0067] This step specifically includes:

[0068] S301: subjecting the seismic data after the dominant azimuth reconstruction to structure-oriented filtering noise suppression, performing directional, edge detection, and edge protection directional filtering on the seismic data after the dominant azimuth reconstruction to improve the quality of the seismic data and promote the continuity of seismic events to be strengthened while highlighting the discontinuous features;

[0069] S302: in the process of the structure-oriented filtering noise suppression, subjecting the dip detection data volume to constraint to perform structure-oriented filtering on the target area, performing smoothing processing on information parallel to the events, and reserving information perpendicular to the events (i.e., not performing smoothing processing on information perpendicular to the events);

[0070] S303: performing quality control analysis on the seismic profile of the seismic data after the structure-oriented filtering noise suppression, extracting a noise profile, judging whether effective information exists in the noise profile, comparing the seismic profile before and after the noise suppression, analyzing whether the continuity of the seismic events, the signal-to-noise ratio, and the fracture information after the noise suppression are clearer, and if effective information exists in the noise profile and / or the continuity of the seismic events, the signal-to-noise ratio, and the fracture information after the noise suppression are not clearer, then re-performing the structure-oriented filtering until no effective information exists in the extracted noise profile and the continuity of the seismic events, the signal-to-noise ratio, and the fracture information after the noise suppression are clearer. This step performs quality control analysis on the seismic profile of the seismic data after the structure-oriented filtering noise suppression, extracts a noise profile, and determines that no effective information exists in the noise profile, compares the seismic profile before and after the noise suppression, and analyzes whether the continuity of the seismic events, the signal-to-noise ratio, and the fracture information are clearer. If yes, then the next step S4 is entered, otherwise, the step S302 is returned to be adjusted again.

[0071] S4: performing fault likelihood attribute analysis on the seismic data after the noise suppression to obtain a fault likelihood attribute data volume;

[0072] Specifically, the core of the seismic fault body technology is to analyze the fault likelihood attribute of the seismic data after structure-oriented filtering and noise suppression, that is, to analyze the fault similarity u(x, y, t) between two seismic traces. If the seismic traces are regarded as vector coordinates in space, the likelihood attribute can be regarded as the Euclidean distance between two vectors after the vector length is normalized, and the fault likelihood attribute between two seismic traces (x A ,y A ) and (x B ,y B ) is:

[0073]

[0074] Wherein:

[0075]

[0076] In the formula, S is the fault likelihood attribute value between two seismic traces, (x A ,y A ) and (x B ,y B ) are the coordinates corresponding to the data points of two seismic traces respectively, dt represents the sampling interval, t represents time, t1 represents the top boundary of the time window when the likelihood attribute is calculated, t2 represents the bottom boundary of the time window, and u is the attribute value of the seismic data corresponding to the sample point. It can be known from the calculation result that when the fault is strongly developed, the value of S tends to 0; and when the fault is not active, the value of S tends to 1. This step performs fault likelihood attribute analysis on the seismic data after noise suppression based on the above calculation method to obtain a fault likelihood attribute data body.

[0077] S5: performing refined fault likelihood attribute analysis on the fault likelihood attribute data body to obtain a fault body data;

[0078] This step performs refined fault likelihood attribute analysis through multiple iterations based on the constraint of the stratigraphic dip angle and azimuth information to obtain the fault body data. The refined fault likelihood attribute analysis is calculated through the following formula:

[0079] S thinned =F(D E [K l *S]-w) n

[0080] Wherein, S thinned is the refined fault likelihood attribute value, F represents the iteration function, n is the number of iterations, K l represents the maximum value of the maximum likelihood attribute background noise, S is the fault likelihood attribute value between two seismic traces, and D Ew is the maximum background noise value corresponding to the conventional likelihood attribute calculation.

[0081] Finally, a refined fault likelihood attribute volume is obtained, referred to as a fault volume data, with a value range of 0-1.

[0082] S6: The fault volume data and the noise-pressed seismic data are fused to complete fine structure interpretation of the profile and plane of the study area.

[0083] In this step, the fault volume data and the noise-pressed seismic data are fused, and the fault volume data is superimposed and displayed in the seismic profile and plane.

[0084] Preferably, in the fault interpretation process of the faulted basin, the size of the fault volume value is controlled to filter out small cracks and fracture-cavity information, so as to complete the profile and plane interpretation of the main fault.

[0085] Preferably, in the fault plane combination, the stratum dislocation information is combined to complete the omnibearing intelligent optimization and recombination of the fault.

[0086] The fine structure interpretation method of the complex faulted basin can solve the problem of fine fault description when the original seismic data quality is poor and the signal-to-noise ratio is low by controlling the fault volume processing through structure-oriented filtering and adding an artificial quality control process. The method uses the seismic fault technology to superimpose the fault volume data and the seismic data, presents the start and end information of the fault on the seismic profile, makes the fault return accurate and clear, and assists the interpreter in the profile interpretation of the fault. Meanwhile, through the seismic fault volume technology, the obtained along-layer slice data contains both fault information and horizon information, the fault is intelligently combined in space, and the interpreter is assisted to improve the accuracy of the fault plane combination. For the structural oil and gas reservoir or the structural-lithologic oil and gas reservoir, the seismic fault volume technology is used to improve the fault profile and plane interpretation accuracy, so as to reduce the risk in reservoir prediction.

[0087] Example 2

[0088] The formation of the South China Sea peripheral basin is controlled by the early subduction and dragging of the ancient South China Sea, the late extension and faulting of the new South China Sea, and the thermal subsidence after the expansion of the South China Sea stops. Therefore, the prototype of the basin formed in the northern continental margin of the South China Sea is mainly a faulted basin controlled by a deep fault or detachment fault, and the reservoir type in the basin is a structural or structural-lithologic oil and gas reservoir.

[0089] The case is located in the Beibuwan Basin in the northern continental margin of the South China Sea, and is affected by the NW-SE expansion direction of the South China Sea, so the main fault direction in the basin is NE-SW, and therefore the designed main line inline direction is NW-SE (such as Figure 2The target area is mainly controlled by fault A with a NEE direction (as shown in FIG. 1), so the new survey direction is NNE and perpendicular to the direction of the main fault A of the target area by advantage direction reconstruction of the seismic data. Figure 3 The target area is mainly controlled by fault A with a NEE direction (as shown in FIG. 1), so the new survey direction is NNE and perpendicular to the direction of the main fault A of the target area by advantage direction reconstruction of the seismic data. Figure 4a The target area is mainly controlled by fault A with a NEE direction (as shown in FIG. 1), so the new survey direction is NNE and perpendicular to the direction of the main fault A of the target area by advantage direction reconstruction of the seismic data. Figure 4b The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. Figure 4b The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault.

[0090] The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. Figure 5a The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. Figure 5b The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. Figure 5b The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault.

[0091] The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. Figure 6 The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault.

[0092] The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault.

[0093] The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. Figure 7 The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. Figure 2 The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault.

[0094] The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. Figure 8 The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. Figure 9a The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. Figure 9b The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. Figure 9a The comparison effect diagram of the seismic profiles before and after the advantage direction reconstruction can be seen from FIG. 2, in the seismic profile (2) after the advantage direction reconstruction, the fault is clearer and more distinct, and in addition, the angle between the fault and the stratum is increased near the main fault, which is helpful for the interpretation of the stratum and the fault. Figure 9b) one-to-one correspondence, the accuracy meets the requirements of the current complex fault basin reservoir prediction.

[0095] Example 3

[0096] The embodiment provides a fine structure interpretation device for a complex fault basin, which comprises:

[0097] A seismic data reconstruction module is configured to determine the development direction of a main fault in a target area based on original seismic data and reconstruct the original seismic data in a dominant direction.

[0098] An inclination scanning module is configured to perform multi-directional inclination scanning on the seismic data reconstructed in the dominant direction to obtain an inclination data volume.

[0099] A noise suppression module is configured to perform structure-oriented filter noise suppression on the seismic data reconstructed in the dominant direction by taking the inclination data volume as a constraint to obtain seismic data after noise suppression.

[0100] A likelihood attribute analysis module is configured to perform fault likelihood attribute analysis on the seismic data after noise suppression to obtain a fault likelihood attribute data volume.

[0101] A likelihood attribute refinement module is configured to perform refined fault likelihood attribute analysis on the fault likelihood attribute data volume to obtain a fault volume.

[0102] A data fusion module is configured to fuse the fault volume and the seismic data after noise suppression to complete fine structure interpretation of a profile and a plane of a study area.

[0103] In the embodiment, the seismic data reconstruction module is specifically configured to perform main fault direction analysis of a basin and a sag on the original seismic data, select a direction perpendicular to the main fault as a dominant direction of the seismic data, and reconstruct the seismic data in the dominant direction, so that the main direction of the reconstructed seismic survey network is perpendicular to the direction of the main fault.

[0104] In the embodiment, the noise suppression module is specifically configured to perform structure-oriented filter noise suppression on the seismic data reconstructed in the dominant direction, and perform directional filtering, edge detection and edge protection on the seismic data reconstructed in the dominant direction, so as to strengthen the continuity of seismic events and highlight the discontinuous features.

[0105] In the process of structure-oriented filter noise suppression, the structure-oriented filter noise suppression is performed on the target area by taking the inclination detection data volume as a constraint, parallel information of the events is smoothed, and information perpendicular to the direction of the events is reserved.

[0106] The seismic profile of the seismic data after the structure-oriented filter noise suppression is subjected to quality control analysis, the noise profile is extracted, it is judged whether effective information exists in the noise profile, and the seismic profile before and after the noise suppression is compared, the continuity of the seismic event after the noise suppression, the signal-to-noise ratio, and whether the fracture information is clearer are analyzed, if the effective information exists in the noise profile and / or the continuity of the seismic event after the noise suppression, the signal-to-noise ratio, and the fracture information are not clearer, the structure-oriented filter is re-performed until the extracted noise profile has no effective information and the continuity of the seismic event after the noise suppression, the signal-to-noise ratio, and the fracture information are clearer.

[0107] In the embodiment, the fault likelihood attribute analysis on the seismic data after the noise suppression comprises:

[0108] The fault likelihood attribute between any two seismic traces is calculated by the following formula:

[0109]

[0110] Wherein:

[0111]

[0112] In the formula, S is the fault likelihood attribute value between two seismic traces, (x A ,y A ) and (x B ,y B ) are coordinates corresponding to data points of two seismic traces, dt represents a sampling interval, t represents time, t1 represents the top boundary of a time window when the likelihood attribute is calculated, t2 represents the bottom boundary of the time window, and u is an attribute value of a corresponding sample point of seismic data.

[0113] In the embodiment, the fault likelihood attribute analysis on the fault likelihood attribute data volume after the refinement comprises:

[0114] With the information of the stratigraphic dip angle and the azimuth angle as constraints, multi-round iterative calculation is performed to complete the refined fault likelihood attribute analysis and obtain the fault volume data.

[0115] The refined fault likelihood attribute analysis is calculated by the following formula:

[0116] S thinned = F(D E [K l *S]-w) n

[0117] Wherein, S thinned is the refined fault likelihood attribute value, F represents an iterative function, n is the number of iterations, and K lSmax represents the maximum value of the background noise of the maximum likelihood attribute, S represents the fault likelihood attribute value between two seismic traces, D E Smax represents the maximum value of the background noise of the maximum likelihood attribute, S represents the fault likelihood attribute value between two seismic traces, D

[0118] In this embodiment, the data fusion and structure interpretation module is specifically configured to:

[0119] The fault body data and the noise- suppressed seismic data are fused, and the fault body data is displayed in superposition in a seismic profile and a plane.

[0120] Preferably, in the fault interpretation process of a faulted basin, small cracks and fracture-cavity information are filtered out by controlling the size of the fault body value, so as to complete profile and plane interpretation of main faults. In addition, in the fault plane combination, the full- range intelligent optimization and recombination of the faults are completed in combination with the stratum dislocation information.

[0121] Example 4

[0122] The embodiment provides an electronic device, which comprises:

[0123] at least one processor; and

[0124] a memory in communication with the at least one processor; wherein

[0125] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the complex faulted basin fine structure interpretation method described in Embodiment 1.

[0126] The electronic device according to the embodiment of the present disclosure comprises a memory and a processor, the memory is used to store non-transitory computer readable instructions. Specifically, the memory can comprise one or more computer program products, which can comprise various forms of computer readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory, etc. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0127] The processor can be a central processing unit (CPU) or other forms of processing units with data processing capability and / or instruction execution capability, and can control other components in the electronic device to perform desired functions. In an embodiment of the present disclosure, the processor is used to run the computer readable instructions stored in the memory.

[0128] Those skilled in the art should understand that, in order to solve the technical problem of how to obtain a good user experience effect, the embodiment can also include well-known structures such as a communication bus, an interface, and the like, which should also be included in the protection scope of the present disclosure.

[0129] The detailed description of the present embodiment can refer to the corresponding description in the foregoing embodiments, and will not be repeated here.

[0130] Example 5

[0131] The embodiment provides a non-transitory computer readable storage medium storing computer instructions for causing a computer to execute the complex fault basin fine structure interpretation method described in the embodiment 1.

[0132] The computer readable storage medium according to the embodiment of the present disclosure has non-transitory computer readable instructions stored thereon. When the non-transitory computer readable instructions are run by a processor, all or part of the steps of the method of the embodiments of the present disclosure are executed.

[0133] The computer readable storage medium includes but is not limited to optical storage media (for example, CD-ROM and DVD), magneto-optical storage media (for example, MO), magnetic storage media (for example, magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (for example, memory card), and media with built-in ROM (for example, ROM cartridge).

[0134] The above has described the embodiments of the present application, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes are obvious to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for fine structural interpretation of complex rift basins, characterized in that, include: Based on the original seismic data, the development direction of the main fault in the target area is determined and the dominant orientation is reconstructed from the original seismic data. Multi-azimuth dip scanning is performed on the seismic data after reconstruction in the dominant azimuth to obtain dip data volumes; Using the dip angle data volume as a constraint, constructive guidance filtering noise suppression is performed on the seismic data reconstructed in the dominant azimuth to obtain noise-suppressed seismic data; Fault likelihood attribute analysis was performed on the noise-suppressed seismic data to obtain the fault likelihood attribute data volume. A detailed fault likelihood attribute analysis is performed on the fault likelihood attribute data volume to obtain fault volume data; By fusing the fault body data with the noise-suppressed seismic data, a detailed structural interpretation of the profile and plan of the study area is completed.

2. The method for fine structural interpretation of complex rift basins according to claim 1, characterized in that, The process of determining the development direction of the main fault in the target area based on the original seismic data and reconstructing the dominant azimuth of the original seismic data includes: The original seismic data is analyzed for the direction of the main fault in the basin and depression. The direction perpendicular to the main fault is selected as the dominant orientation of the seismic data. The dominant orientation of the seismic data is then reconstructed so that the main orientation of the reconstructed seismic network is perpendicular to the direction of the main fault.

3. The method for fine structural interpretation of complex rift basins according to claim 1, characterized in that, The step of using the dip angle data volume as a constraint to perform structural steering filter noise suppression on the seismic data reconstructed in the dominant azimuth includes: Structural guidance filtering is applied to the reconstructed seismic data in the dominant azimuth to suppress noise. Directional filtering with directional, edge detection, and edge protection is also applied to the reconstructed seismic data in the dominant azimuth to enhance the continuity of seismic phase axes and highlight discontinuity features. During the construction-guided filtering noise suppression process, the tilt angle detection data volume is used as a constraint to perform construction-guided filtering in the target area of ​​the study. Information parallel to the phase axis is smoothed, while information perpendicular to the phase axis is retained. Quality control analysis is performed on the seismic profiles of the seismic data after noise suppression via structure-guided filtering. Noise profiles are extracted to determine whether there is any valid information in them. Simultaneously, the seismic profiles before and after noise suppression are compared to analyze whether the continuity, signal-to-noise ratio, and fracture information of the seismic phase axes are clearer after noise suppression. If there is valid information in the noise profile and / or the continuity, signal-to-noise ratio, and fracture information of the seismic phase axes do not become clearer after noise suppression, structure-guided filtering is repeated until there is no valid information in the extracted noise profile and the continuity, signal-to-noise ratio, and fracture information of the seismic phase axes are clearer after noise suppression.

4. The method for fine structural interpretation of complex rift basins according to claim 1, characterized in that, The fault likelihood property analysis of the noise-suppressed seismic data includes: The fault likelihood property between any two seismic traces can be calculated using the following formula: in: In the formula, S is the fault likelihood attribute value between two seismic traces, (x A ,y A ) and (x B ,y B ) represent the coordinates of the two seismic trace data samples, dt represents the sampling interval, t represents time, t1 represents the top interface of the time window opened when calculating the likelihood attribute, t2 represents the bottom interface of the time window opened, and u is the attribute value of the corresponding sample point of the seismic data.

5. The method for fine structural interpretation of complex rift basins according to claim 1, characterized in that, The detailed fault likelihood attribute analysis of the fault likelihood attribute data volume includes: Using stratigraphic dip and azimuth information as constraints, multiple rounds of iterative calculations are performed to complete a detailed fault likelihood analysis and obtain fault body data.

6. The method for fine structural interpretation of complex rift basins according to claim 5, characterized in that, The following formula is used to perform refined fault likelihood property analysis calculations: S thinned =F(D E [K l *S]-w) n Among them, S thinned For refined fault likelihood attribute values, F represents the iteration function, n is the number of iterations, and K... l The maximum value of the background noise represents the maximum likelihood attribute, S is the fault likelihood attribute value between the two seismic traces, and D is the maximum value of the background noise representing the maximum likelihood attribute. E This represents the parameter value used for edge detection enhancement of the fault, and w is the maximum background noise value corresponding to the conventional likelihood attribute calculation.

7. The method for fine structural interpretation of complex rift basins according to claim 1, characterized in that, The process of fusing the fault body data and noise-suppressed seismic data to complete the detailed structural interpretation of the profiles and planes of the study area includes: The fault body data and noise-suppressed seismic data are fused together, and the fault body data is superimposed and displayed in seismic profiles and planes. In the process of fault interpretation in rift basins, by controlling the size of the fault body, small cracks and cavities are filtered out to complete the cross-sectional and planar interpretation of the main faults.

8. The method for fine structural interpretation of complex rift basins according to claim 7, characterized in that, Also includes: When combining fault planes, the faults are intelligently optimized and reorganized in all aspects by incorporating stratigraphic displacement information.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the fine structural interpretation method for complex rift basins as described in any one of claims 1-8.

10. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions for causing a computer to perform the method for fine structural interpretation of complex rift basins as described in any one of claims 1-8.

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