CN116466397A - Modeling method and related device for converted wave depth domain speed model - Google Patents
Modeling method and related device for converted wave depth domain speed model Download PDFInfo
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Abstract
The invention discloses a modeling method and a related device of a converted wave depth domain speed model, wherein the method comprises the following steps: inversion updating is carried out on the longitudinal wave depth domain velocity model to obtain longitudinal wave velocity; according to the longitudinal wave speed, carrying out one-dimensional inversion updating on a converted wave depth domain speed model to update the converted wave speed; performing depth migration through a longitudinal wave depth domain velocity model to obtain a longitudinal wave channel set, performing depth migration through a converted wave depth domain velocity model to obtain a converted wave channel set, and performing joint inversion through the longitudinal wave channel set and the converted wave channel set to obtain a converted wave migration channel set; judging whether the offset superposition profile of the converted wave and the offset gather of the converted wave are reasonable or not, and whether the same phase axes of the longitudinal wave and the converted wave are leveled or not, if so, outputting a depth domain speed model of the converted wave. The method improves the accuracy of the depth domain speed modeling of the converted wave by joint inversion of the longitudinal wave and the transverse wave, and effectively avoids uncertainty factors brought by a GAMMA field in time migration processing.
Description
Technical Field
The invention relates to the technical field of oil and gas field exploration, in particular to a modeling method and device for a converted wave depth domain speed model, computing equipment and a computer storage medium.
Background
At present, a large amount of converted wave data on the sea in China are not developed and utilized, and the area of the sea is increased year by year. The converted wave is the most critical factor for making up the deficiency of longitudinal wave exploration, how to process the converted wave is always a difficult problem in the industry, the company at home and abroad has few successful cases, and the case that the converted wave depth migration technology is successful is more the phoenix-shaped living being. Converted waves can be simply understood as longitudinal waves which are incident and transverse waves which are emergent, the ray paths of the converted waves are geometrically asymmetric, and the propagation rule of the transverse waves and the converted waves between the ground layers is far more complex than that of the longitudinal waves. The above-described features of the converted wave are direct causes of difficulties in velocity analysis, extraction of common center points, depth domain velocity modeling, and the like.
Because of the asymmetry of the propagation paths of converted waves, when pre-stack time migration imaging is carried out, a common conversion point is needed to be found through a GAMMA (GAMMA) field, the key parameter for finding the conversion point is the GAMMA field, meanwhile, three parameters VP, VS, GAMMA are needed in the migration process, the difficulty in solving the three parameters is high, the influence of human factors of the GAMMA field is too great, uncertainty is filled, and the imaging position obtained through time migration is inaccurate, so that the subsequent interpretation and reservoir prediction work are influenced.
Disclosure of Invention
In view of the foregoing, the present invention has been made to provide a modeling method and apparatus, a computing device, and a computer storage medium for a converted wave depth domain velocity model capable of effectively avoiding the existence of an uncertainty in a converted wave prestack time migration technique.
According to an aspect of the present invention, there is provided a modeling method of a converted wave depth domain velocity model, including:
step S1, inversion updating is carried out on a longitudinal wave depth domain velocity model to obtain a longitudinal wave velocity;
step S2, carrying out one-dimensional inversion updating on a converted wave depth domain speed model according to the longitudinal wave speed so as to update the converted wave speed;
s3, performing depth migration through a longitudinal wave depth domain speed model to obtain a longitudinal wave channel set, performing depth migration through a converted wave depth domain speed model to obtain a converted wave channel set, and performing joint inversion through the longitudinal wave channel set and the converted wave channel set to obtain a converted wave migration channel set;
step S4, judging whether the offset superposition profile of the converted wave and the offset gather of the converted wave are reasonable, and whether the same phase axes of the longitudinal wave and the converted wave are leveled, if not, carrying out three-dimensional inversion updating on the depth domain velocity model of the converted wave, and executing step S2; if so, outputting a converted wave depth domain velocity model.
In an alternative manner, the longitudinal wave depth domain velocity model is used to define a ray path from the shot point to the imaging point; the converted wave depth domain velocity model is used to define the ray path from the detector point to the imaging point.
In an alternative manner, before the step S1, the method further includes: an initial longitudinal wave depth domain velocity model and an initial converted wave depth domain velocity model are respectively established, wherein the initial converted wave depth domain velocity model is established according to logging data, gamma field parameters and velocity scanning.
In an alternative manner, the step S2 further includes:
performing horizon interpretation on the longitudinal wave and the converted wave in a depth domain;
based on horizon matching requirements, obtaining converted wave speed to be updated according to the longitudinal wave speed;
and carrying out one-dimensional inversion updating on the converted wave depth domain speed model according to the converted wave speed to be updated.
In an alternative manner, the three-dimensional inversion updating of the converted wave depth domain velocity model further includes:
picking up the remaining curvature based on the converted wave offset gathers;
picking up inclination angle information based on the converted wave superposition profile;
performing tomographic inversion according to the picked residual curvature and the inclination angle information, and calculating the transverse wave velocity disturbance quantity;
and carrying out three-dimensional inversion updating on the converted wave depth domain speed model according to the transverse wave speed disturbance quantity.
In an alternative manner, after the outputting the converted wave depth domain velocity model, the method further comprises:
obtaining converted wave data of a depth domain according to the converted wave depth domain speed model;
and converting the converted wave data of the depth domain into a time domain to obtain the converted wave data of the time domain.
According to another aspect of the present invention, there is provided a modeling apparatus of a converted wave depth domain velocity model, including:
the longitudinal wave inversion updating module is used for carrying out inversion updating on the longitudinal wave depth domain speed model to obtain the longitudinal wave speed;
the one-dimensional inversion updating module is used for carrying out one-dimensional inversion updating on the converted wave depth domain speed model according to the longitudinal wave speed and updating the converted wave speed;
the migration channel set acquisition module is used for carrying out depth migration through a longitudinal wave depth domain speed model to obtain a longitudinal wave channel set, carrying out depth migration through a converted wave depth domain speed model to obtain a converted wave channel set, and carrying out joint inversion through the longitudinal wave channel set and the converted wave channel set to obtain a converted wave migration channel set;
the three-dimensional inversion updating module is used for judging whether the offset converted wave superposition profile and the converted wave offset gather are reasonable or not, and whether the same phase axes of the longitudinal wave and the converted wave are leveled or not, if not, carrying out three-dimensional inversion updating on the converted wave depth domain speed model, and triggering the one-dimensional inversion updating module; if so, outputting a converted wave depth domain velocity model.
According to yet another aspect of the present invention, there is provided a computing device comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the modeling method of the converted wave depth domain speed model.
According to still another aspect of the present invention, there is provided a computer storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the modeling method of the converted wave depth domain velocity model described above.
According to the scheme provided by the invention, inversion updating is carried out on the longitudinal wave depth domain velocity model to obtain the longitudinal wave velocity; according to the longitudinal wave speed, carrying out one-dimensional inversion updating on a converted wave depth domain speed model to update the converted wave speed; performing depth migration through a longitudinal wave depth domain velocity model to obtain a longitudinal wave channel set, performing depth migration through a converted wave depth domain velocity model to obtain a converted wave channel set, and performing joint inversion through the longitudinal wave channel set and the converted wave channel set to obtain a converted wave migration channel set; judging whether the offset superposition profile of the converted wave and the offset gather of the converted wave are reasonable or not, and whether the same phase axes of the longitudinal wave and the converted wave are leveled or not, if not, carrying out three-dimensional inversion updating on the depth domain velocity model of the converted wave, and triggering one-dimensional inversion updating; if so, outputting a converted wave depth domain velocity model. The method improves the accuracy of the depth domain speed modeling of the converted wave by joint inversion of the longitudinal wave and the transverse wave, and effectively avoids uncertainty factors brought by a GAMMA field in time migration processing.
The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present invention more readily apparent.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
FIG. 1 is a flow chart of a method for modeling a converted wave depth domain velocity model according to an embodiment of the present invention;
FIG. 2 shows a schematic diagram of a longitudinal and transverse wave combined imaging process according to an embodiment of the invention;
FIGS. 3a to 3b are schematic diagrams showing longitudinal and transverse wave offset point correspondence according to embodiments of the present invention;
FIG. 4 shows a schematic diagram of a longitudinal and transverse wave joint modeling flow according to an embodiment of the invention;
FIG. 5 shows a schematic of a three-dimensional tomographic inversion process according to an embodiment of the invention;
FIG. 6 is a schematic diagram of corresponding superposition, trace set and residual curvature spectrum γ before transverse wave velocity update according to an embodiment of the present invention;
FIG. 7 is a schematic diagram showing matching of a longitudinal and transverse wave depth domain after a transverse wave speed update according to an embodiment of the present invention;
FIG. 8 is a schematic structural diagram of a modeling apparatus of a converted wave depth domain velocity model according to an embodiment of the present invention;
FIG. 9 illustrates a schematic diagram of a computing device in accordance with an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Prior to implementing the embodiments of the present invention, technical terms referred to hereinafter are explained in detail:
p wave: p represents Primary (Primary) or compression (Pressure), which is a longitudinal wave, the direction of vibration of the particles being parallel to the wave front.
S wave: s means Secondary or Shear, a transverse wave, the direction of vibration of the particles being perpendicular to the direction of wave travel.
Converted wave: also known as converted reflected waves or C waves, when either a longitudinal wave or a transverse wave is obliquely incident on an elastic interface, the reflected transverse wave, reflected longitudinal wave, transmitted transverse wave, transmitted longitudinal wave are generated simultaneously. For example, when a longitudinal wave (P-wave) is incident on a certain reflective layer interface at a non-zero angle of incidence, several waves can be formed: reflecting the upward P wave (PP), transmitting the downward P wave, converting the upward S wave (PS), and converting the transmitted S wave.
PP wave: also known as reflected longitudinal waves.
PS wave: also known as reflected transverse waves, PS waves are one type of S wave.
PSDM: pre-stack depth migration (Pre-stack depth migration, PSDM for short) is a processing technique for realizing spatial homing of geologic structures.
CMP: common Mid Point (CMP) refers to the process of extracting the tracks with Common center points in different shot sets to form a new set called Common center Point gather.
CCP: common transition point trace sets (Common Conversion Point, CCP for short).
ACP: asymptotic transition point gathers (Asymptotic Conversion Point, ACP for short).
CIG: common imaging point gathers (Common Image Gather, CIG for short).
CDP: a common depth point (or common reflection point) gather (Common Depth Point, CDP for short).
In order to more clearly describe the flow chart of the modeling method of the converted wave depth domain velocity model shown in fig. 1 in this embodiment, the object of the present invention is first described.
When pre-stack depth migration imaging is carried out, imaging can be carried out only by obtaining VP (velocity of longitudinal wave) and VS (velocity of transverse wave) in a depth domain, converted wave depth migration accurate imaging can be realized by theoretically improving depth migration velocity modeling precision, and chromatographic inversion precision can be effectively improved by a longitudinal and transverse wave joint inversion technology, so that an ideal imaging effect of the converted wave depth domain is obtained. The invention thus has mainly the following three purposes:
1. the existing converted wave prestack time migration technology is required to depend on the GAMMA field, and prestack depth migration effectively avoids the uncertainty factor of the GAMMA field.
2. The existing converted wave prestack time migration can only obtain a time domain result, and the speed model obtained through depth domain longitudinal and transverse wave joint modeling can be subjected to depth migration, so that the depth domain, converted wave time domain and longitudinal wave time domain migration results can be obtained simultaneously to meet various requirements.
3. In the time migration velocity calculation process, the GAMMA field of the middle-deep layer is close to 1, namely the longitudinal and transverse wave velocity ratio is difficult to adjust in the middle-deep layer, so that the time migration imaging of the middle-deep layer converted wave is not ideal, the longitudinal wave velocity and the transverse wave velocity can be obtained through longitudinal and transverse wave joint inversion in the depth migration velocity modeling, and the middle-deep layer can be imaged accurately.
FIG. 1 is a flow chart of a method for modeling a converted wave depth domain velocity model according to an embodiment of the present invention. The method improves the accuracy of the depth domain speed modeling of the converted wave by joint inversion of the longitudinal wave and the transverse wave. Specifically, as shown in fig. 1, the method comprises the following steps:
and step S101, carrying out inversion updating on the longitudinal wave depth domain velocity model to obtain the longitudinal wave velocity.
And establishing a longitudinal wave depth domain initial velocity model, and carrying out inversion updating on the longitudinal wave depth domain velocity model to obtain a relatively accurate longitudinal wave velocity.
In an alternative way, before step S101, the method further includes: an initial longitudinal wave depth domain velocity model and an initial converted wave depth domain velocity model are respectively established, wherein the initial converted wave depth domain velocity model is established according to logging data, gamma field parameters and velocity scanning.
In an alternative approach, a longitudinal wave depth domain velocity model is used to define the ray path from shot to imaging point.
For example, the ray path from shot to imaging point is defined by a P-wave (Vp 0) velocity model.
Step S102, carrying out one-dimensional inversion updating on the converted wave depth domain velocity model according to the longitudinal wave velocity so as to update the converted wave velocity.
For example, a higher-accuracy longitudinal wave velocity is obtained after the PP wave velocity model is established, and the PS wave velocity update initial model can be performed on the basis of the longitudinal wave velocity.
In an alternative approach, a converted wave depth domain velocity model is used to define the ray path from the detector point to the imaging point.
For example, the S-wave (Vs 0) velocity model is used to define the ray path from the detector point to the imaging point.
In an alternative manner, step S102 further includes:
performing horizon interpretation on the longitudinal wave and the converted wave in a depth domain;
based on horizon matching requirements, obtaining converted wave speed to be updated according to the longitudinal wave speed;
and carrying out one-dimensional inversion updating on the converted wave depth domain speed model according to the converted wave speed to be updated.
Step S103, performing depth migration through a longitudinal wave depth domain velocity model to obtain a longitudinal wave channel set, performing depth migration through a converted wave depth domain velocity model to obtain a converted wave channel set, and performing joint inversion through the longitudinal wave channel set and the converted wave channel set to obtain a converted wave migration channel set.
The theoretical basis of converted wave speed modeling is that PP and PS homophase shafts are in the same position in a depth domain and have a good corresponding relation with geological layering, so that PP and PS gathers are leveled by updating an anisotropic model. A longitudinal and transverse wave combined imaging process as shown in fig. 2, in which PS wave depth offsets combine travel timetables at the shot point end and the detector point end, image at a common transition point instead of a common center point. Fig. 3a to 3b show correspondence of longitudinal and transverse wave offset points.
In the embodiment, in order to ensure accuracy of speed update, longitudinal waves are modeled at high precision and then transverse wave speeds are obtained, and final longitudinal waves and converted waves are consistent in imaging position in depth domain through longitudinal and transverse wave joint inversion. As shown in fig. 4, PP wave tomographic inversion is performed on the longitudinal wave depth domain velocity model to obtain a PP velocity model (i.e., obtain a longitudinal wave velocity), and 1D (one-dimensional) inversion update is performed on the converted wave depth domain velocity model according to the longitudinal wave velocity, delta/epsilon (Delta/epsilon is the anisotropy of the far offset, used for leveling the gather), and the like, to update the converted wave velocity.
The down wave of the converted wave is a longitudinal wave in the propagation process, and the transverse wave generated after passing through the reflection point is received by the speed detector, so that joint inversion work of two signals, namely longitudinal and transverse wave joint inversion, is needed. After an accurate longitudinal wave velocity model is obtained through chromatographic inversion, the transverse wave is subjected to iterative updating, and a final depth migration converted wave velocity model is obtained.
Specifically, a longitudinal wave is subjected to depth migration through a longitudinal wave depth domain velocity model to obtain a longitudinal wave channel set, a converted wave channel set is obtained through depth migration through a converted wave depth domain velocity model, and joint inversion is performed through the longitudinal wave channel set and the converted wave channel set to obtain a converted wave migration channel set.
Step S104, judging whether the offset superposition profile of the converted wave and the offset gather of the converted wave are reasonable, and whether the same phase axes of the longitudinal wave and the converted wave are leveled, if not, carrying out three-dimensional inversion updating on the depth domain velocity model of the converted wave, and executing step S102; if so, outputting a converted wave depth domain velocity model.
Specifically, judging whether the offset converted wave superposition profile and the converted wave offset gather are reasonable, and whether the in-phase axes of the longitudinal wave and the converted wave are leveled to determine whether the speed is reasonable and whether there is an improvement space, if not (i.e. unreasonable or not there is an improvement space), performing three-dimensional inversion updating on the converted wave depth domain speed model, and after the three-dimensional inversion updating, executing step S102 (triggering one-dimensional inversion updating again); if so, outputting a converted wave depth domain velocity model. As shown in fig. 5, the longitudinal wave velocity model and the converted wave velocity model are respectively subjected to depth migration to obtain a longitudinal wave gather and a converted wave gather, whether the offset converted wave superposition profile and the offset converted wave gather are reasonable, whether the same phase axis is leveled and the like are determined whether the velocity is reasonable or not, and whether there is an improvement space is determined, if so, residual curvature and inclination angle information are picked up on the offset converted wave migration gather, 3D inversion updating is performed on the converted wave depth domain velocity model, and after the 3D inversion updating, 1D inversion updating is triggered again.
In an alternative manner, the three-dimensional inversion updating of the converted wave depth domain velocity model further comprises:
picking up the remaining curvature based on the converted wave offset gathers;
picking up inclination angle information based on the converted wave superposition profile;
performing tomographic inversion according to the picked residual curvature and inclination angle information, and calculating the transverse wave velocity disturbance quantity;
and carrying out three-dimensional inversion updating on the converted wave depth domain speed model according to the transverse wave speed disturbance quantity.
Specifically, residual curvature is picked up on the offset converted wave offset gather, inclination angle information is picked up based on the converted wave superposition profile, tomographic inversion is performed according to the picked residual curvature and inclination angle information, transverse wave velocity disturbance quantity is calculated, a transverse wave velocity model is updated, one-dimensional inversion updating is performed on the updated transverse wave velocity model again, if the velocity, the precision and the like of the transverse wave velocity model are unreasonable or there is room for improvement, the depth offset of the second round is performed by using the newly obtained transverse wave velocity model until a reasonable transverse wave velocity model is obtained. In order to obtain a better depth offset result, a multi-round speed update iteration process is generally required, and whether the change trend of a speed control model, CIG pickup parameters and the like are reasonable or not is carefully controlled. Only the trend of each speed update is to guarantee the reliability and quality of the final offset result on the premise of correctness.
Optionally, updating and inverting the longitudinal wave depth domain speed model preferentially, solving a relatively accurate speed, and respectively performing optimization processing on the CDP gathers of the longitudinal wave and the converted wave to pick up respective residual curvature and inclination angle information.
Optionally, the velocity models of the longitudinal wave and the transverse wave are input simultaneously, and the respective residual curvature and inclination angle information are subjected to joint nonlinear tomographic inversion.
Optionally, for data which cannot be subjected to conventional inversion, a transverse wave velocity model is subjected to scanning filling and other methods to obtain accurate velocity.
In this embodiment, both longitudinal wave and converted wave imaging in the depth domain satisfy the condition of performing tomography on the residual curvature of the converted wave offset gather, and in the process of performing cross-wave joint inversion, the two are required to be picked up by the residual curvature of the converted wave offset gather, and the data-driven mode is adopted to perform the cross-wave joint inversion.
As shown in FIG. 6, which shows the superposition, trace set and velocity spectrum corresponding to the transverse wave velocity model before updating, it can be seen that the trace set is not leveled at this time and the velocity spectrum energy mass is not centered. Therefore, it is necessary to pick up the remaining delay amount, and to update the speed by picking up the remaining delay amount. The method specifically comprises the steps of obtaining a depth domain CIG and a converted wave superposition profile (grid 50m is 5 m) by adopting Kirchhoff prestack depth migration based on an initial layer speed model, picking up the residual curvature based on the CIG, picking up the inclination angle in the X, Y direction based on the converted wave superposition profile, carrying out three-dimensional tomographic inversion to update a depth-layer speed body, and gradually reducing the residual curvature of the CIG after a plurality of rounds of updating, so that the speed becomes more accurate.
After several rounds of iterative updating, the velocity precision of the transverse wave becomes high, the imaging position of the longitudinal wave and the converted wave in the depth domain is consistent in the same stratum theory, the updated converted wave achievement needs to be matched and compared with the longitudinal wave in the depth domain, and fig. 7 shows the imaging situation of the longitudinal wave and the transverse wave in the depth domain, and the imaging situation of the longitudinal wave and the transverse wave in the same position is basically consistent, so that the velocity precision of the transverse wave obtained by longitudinal wave and transverse wave joint inversion is high.
In an alternative way, after outputting the converted wave depth domain velocity model, the method further comprises:
obtaining converted wave data of a depth domain according to the converted wave depth domain speed model;
converting the converted wave data in the depth domain into the time domain to obtain the converted wave data in the time domain.
Through longitudinal wave and transverse wave joint inversion, longitudinal wave imaging depth matching is consistent, good converted wave depth domain imaging quality can be obtained, for example, converted wave data in a depth domain can be converted into a time domain to obtain time domain results, so that subsequent interpretation, reservoir prediction, crack prediction, fluid detection and other work development can be conducted.
According to the scheme provided by the embodiment of the invention, inversion updating is carried out on the longitudinal wave depth domain velocity model to obtain the longitudinal wave velocity; according to the longitudinal wave speed, carrying out one-dimensional inversion updating on a converted wave depth domain speed model to update the converted wave speed; performing depth migration through a longitudinal wave depth domain velocity model to obtain a longitudinal wave channel set, performing depth migration through a converted wave depth domain velocity model to obtain a converted wave channel set, and performing joint inversion through the longitudinal wave channel set and the converted wave channel set to obtain a converted wave migration channel set; judging whether the offset superposition profile of the converted wave and the offset gather of the converted wave are reasonable or not, and whether the same phase axes of the longitudinal wave and the converted wave are leveled or not, if not, carrying out three-dimensional inversion updating on the depth domain velocity model of the converted wave, and triggering one-dimensional inversion updating; if so, outputting a converted wave depth domain velocity model. According to the invention, through joint inversion of the longitudinal wave and the transverse wave, the accuracy of depth domain velocity modeling of the converted wave is improved, meanwhile, a longitudinal wave velocity model is used for defining a ray path from a shot point to an imaging point in the depth migration imaging process of the converted wave, and a transverse wave velocity model is used for defining a ray path from a detection point to the imaging point, so that uncertainty caused by a GAMMA field in time migration processing is effectively avoided, and the problem of depth domain velocity modeling is effectively solved.
Fig. 8 shows a schematic structural diagram of a modeling apparatus of a converted wave depth domain velocity model according to an embodiment of the present invention. The modeling device of the converted wave depth domain velocity model comprises: the longitudinal wave inversion updating module 810, the one-dimensional inversion updating module 820, the offset gather acquisition module 830 and the three-dimensional inversion updating module 840.
The longitudinal wave inversion updating module 810 is configured to perform inversion updating on a longitudinal wave depth domain velocity model to obtain a longitudinal wave velocity;
the one-dimensional inversion updating module 820 is configured to perform one-dimensional inversion updating on the converted wave depth domain velocity model according to the longitudinal wave velocity, so as to update the converted wave velocity;
the offset gather obtaining module 830 is configured to obtain a longitudinal wave gather by performing depth offset through a longitudinal wave depth domain velocity model, obtain a converted wave gather by performing depth offset through a converted wave depth domain velocity model, and obtain a converted wave offset gather by performing joint inversion through the longitudinal wave gather and the converted wave gather;
the three-dimensional inversion updating module 840 is configured to determine whether the offset converted wave superposition profile and the converted wave offset gather are reasonable, and whether the in-phase axes of the longitudinal wave and the converted wave are leveled, and if not, perform three-dimensional inversion updating on the converted wave depth domain velocity model, and trigger the one-dimensional inversion updating module; if so, outputting a converted wave depth domain velocity model.
In an alternative manner, the longitudinal wave depth domain velocity model is used to define a ray path from the shot point to the imaging point; the converted wave depth domain velocity model is used to define the ray path from the detector point to the imaging point.
In an alternative, the apparatus further comprises: an initial model building module (not shown in the figure) is used for respectively building an initial longitudinal wave depth domain velocity model and an initial converted wave depth domain velocity model, wherein the initial converted wave depth domain velocity model is built according to logging data, gamma field parameters and velocity scanning.
In an alternative manner, the one-dimensional inversion update module 820 is further configured to:
performing horizon interpretation on the longitudinal wave and the converted wave in a depth domain;
based on horizon matching requirements, obtaining converted wave speed to be updated according to the longitudinal wave speed;
and carrying out one-dimensional inversion updating on the converted wave depth domain speed model according to the converted wave speed to be updated.
In an alternative manner, the three-dimensional inversion updating module 840 is further configured to:
picking up the remaining curvature based on the converted wave offset gathers;
picking up inclination angle information based on the converted wave superposition profile;
performing tomographic inversion according to the picked residual curvature and the inclination angle information, and calculating the transverse wave velocity disturbance quantity;
and carrying out three-dimensional inversion updating on the converted wave depth domain speed model according to the transverse wave speed disturbance quantity.
In an alternative, the apparatus further comprises: a converted wave data generating module (not shown in the figure) for obtaining converted wave data of a depth domain according to the converted wave depth domain speed model;
and converting the converted wave data of the depth domain into a time domain to obtain the converted wave data of the time domain.
According to the scheme provided by the embodiment of the invention, inversion updating is carried out on the longitudinal wave depth domain velocity model to obtain the longitudinal wave velocity; according to the longitudinal wave speed, carrying out one-dimensional inversion updating on a converted wave depth domain speed model to update the converted wave speed; performing depth migration through a longitudinal wave depth domain velocity model to obtain a longitudinal wave channel set, performing depth migration through a converted wave depth domain velocity model to obtain a converted wave channel set, and performing joint inversion through the longitudinal wave channel set and the converted wave channel set to obtain a converted wave migration channel set; judging whether the offset superposition profile of the converted wave and the offset gather of the converted wave are reasonable or not, and whether the same phase axes of the longitudinal wave and the converted wave are leveled or not, if not, carrying out three-dimensional inversion updating on the depth domain velocity model of the converted wave, and triggering one-dimensional inversion updating; if so, outputting a converted wave depth domain velocity model. According to the invention, through joint inversion of the longitudinal wave and the transverse wave, the accuracy of depth domain velocity modeling of the converted wave is improved, meanwhile, a longitudinal wave velocity model is used for defining a ray path from a shot point to an imaging point in the depth migration imaging process of the converted wave, and a transverse wave velocity model is used for defining a ray path from a detection point to the imaging point, so that uncertainty caused by a GAMMA field in time migration processing is effectively avoided, and the problem of depth domain velocity modeling is effectively solved.
FIG. 9 illustrates a schematic diagram of an embodiment of a computing device of the present invention, and the embodiments of the present invention are not limited to a particular implementation of the computing device.
As shown in fig. 9, the computing device may include: a processor 902, a communication interface (Communications Interface), a memory 906, and a communication bus 908.
Wherein: processor 902, communication interface 904, and memory 906 communicate with each other via a communication bus 908. A communication interface 904 for communicating with network elements of other devices, such as clients or other servers. The processor 902 is configured to execute the program 910, and may specifically perform relevant steps in the modeling method embodiment of the converted wave depth domain velocity model.
In particular, the program 910 may include program code including computer-operating instructions.
The processor 902 may be a central processing unit, CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included by the computing device may be the same type of processor, such as one or more CPUs; but may also be different types of processors such as one or more CPUs and one or more ASICs.
A memory 906 for storing a program 910. Memory 906 may comprise high-speed RAM memory or may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
Embodiments of the present invention provide a non-volatile computer storage medium storing at least one executable instruction for performing a method for modeling a converted wave depth domain velocity model in any of the above method embodiments.
The algorithms or displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general-purpose systems may also be used with the teachings herein. The required structure for a construction of such a system is apparent from the description above. In addition, embodiments of the present invention are not directed to any particular programming language. It will be appreciated that the teachings of the present invention described herein may be implemented in a variety of programming languages, and the above description of specific languages is provided for disclosure of enablement and best mode of the present invention.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the above description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be construed as reflecting the intention that: i.e., the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the apparatus of the embodiments may be adaptively changed and disposed in one or more apparatuses different from the embodiments. The modules or units or components of the embodiments may be combined into one module or unit or component and, furthermore, they may be divided into a plurality of sub-modules or sub-units or sub-components. Any combination of all features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be used in combination, except insofar as at least some of such features and/or processes or units are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.
Various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components according to embodiments of the present invention may be implemented in practice using a microprocessor or Digital Signal Processor (DSP). The present invention can also be implemented as an apparatus or device program (e.g., a computer program and a computer program product) for performing a portion or all of the methods described herein. Such a program embodying the present invention may be stored on a computer readable medium, or may have the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names. The steps in the above embodiments should not be construed as limiting the order of execution unless specifically stated.
Claims (10)
1. A method for modeling a converted wave depth domain velocity model, comprising:
step S1, inversion updating is carried out on a longitudinal wave depth domain velocity model to obtain a longitudinal wave velocity;
step S2, carrying out one-dimensional inversion updating on a converted wave depth domain speed model according to the longitudinal wave speed so as to update the converted wave speed;
s3, performing depth migration through a longitudinal wave depth domain speed model to obtain a longitudinal wave channel set, performing depth migration through a converted wave depth domain speed model to obtain a converted wave channel set, and performing joint inversion through the longitudinal wave channel set and the converted wave channel set to obtain a converted wave migration channel set;
step S4, judging whether the offset superposition profile of the converted wave and the offset gather of the converted wave are reasonable, and whether the same phase axes of the longitudinal wave and the converted wave are leveled, if not, carrying out three-dimensional inversion updating on the depth domain velocity model of the converted wave, and executing step S2; if so, outputting a converted wave depth domain velocity model.
2. The method of claim 1, wherein the longitudinal wave depth domain velocity model is used to define a ray path from a shot point to an imaging point; the converted wave depth domain velocity model is used to define the ray path from the detector point to the imaging point.
3. The method according to claim 1 or 2, characterized in that before said step S1, the method further comprises: an initial longitudinal wave depth domain velocity model and an initial converted wave depth domain velocity model are respectively established, wherein the initial converted wave depth domain velocity model is established according to logging data, gamma field parameters and velocity scanning.
4. The method according to claim 1 or 2, wherein the step S2 further comprises:
performing horizon interpretation on the longitudinal wave and the converted wave in a depth domain;
based on horizon matching requirements, obtaining converted wave speed to be updated according to the longitudinal wave speed;
and carrying out one-dimensional inversion updating on the converted wave depth domain speed model according to the converted wave speed to be updated.
5. The method of claim 1 or 2, wherein the three-dimensional inversion updating of the converted wave depth domain velocity model further comprises:
picking up the remaining curvature based on the converted wave offset gathers;
picking up inclination angle information based on the converted wave superposition profile;
performing tomographic inversion according to the picked residual curvature and the inclination angle information, and calculating the transverse wave velocity disturbance quantity;
and carrying out three-dimensional inversion updating on the converted wave depth domain speed model according to the transverse wave speed disturbance quantity.
6. The method of claim 1, wherein after the outputting of the converted wave depth domain velocity model, the method further comprises:
obtaining converted wave data of a depth domain according to the converted wave depth domain speed model;
and converting the converted wave data of the depth domain into a time domain to obtain the converted wave data of the time domain.
7. A modeling apparatus for a converted wave depth domain velocity model, comprising:
the longitudinal wave inversion updating module is used for carrying out inversion updating on the longitudinal wave depth domain speed model to obtain the longitudinal wave speed;
the one-dimensional inversion updating module is used for carrying out one-dimensional inversion updating on the converted wave depth domain speed model according to the longitudinal wave speed and updating the converted wave speed;
the migration channel set acquisition module is used for carrying out depth migration through a longitudinal wave depth domain speed model to obtain a longitudinal wave channel set, carrying out depth migration through a converted wave depth domain speed model to obtain a converted wave channel set, and carrying out joint inversion through the longitudinal wave channel set and the converted wave channel set to obtain a converted wave migration channel set;
the three-dimensional inversion updating module is used for judging whether the offset converted wave superposition profile and the converted wave offset gather are reasonable or not, and whether the same phase axes of the longitudinal wave and the converted wave are leveled or not, if not, carrying out three-dimensional inversion updating on the converted wave depth domain speed model, and triggering the one-dimensional inversion updating module; if so, outputting a converted wave depth domain velocity model.
8. The apparatus of claim 7, wherein the longitudinal wave depth domain velocity model is used to define a ray path from a shot point to an imaging point; the converted wave depth domain velocity model is used to define the ray path from the detector point to the imaging point.
9. A computing device, comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
the memory is configured to store at least one executable instruction that causes the processor to perform operations corresponding to the method for modeling a converted wave depth domain velocity model according to any one of claims 1-6.
10. A computer storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the method of modeling a converted wave depth domain velocity model according to any one of claims 1-6.
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