Method and apparatus for surface constraint inversion modeling based on ray depth matching

Abstract

The present disclosure relates to a method and device for surface constraint inversion modeling based on ray depth matching, the method comprising: determining the thickness distribution characteristics of a low-velocity zone in a surface medium of an exploration area; dividing the low-velocity zone into one or more thickness regions according to the thickness distribution characteristics; determining a target tomographic inversion ray depth and a corresponding target tomographic inversion offset distance matched with a smaller depth in the position relationship between a surface investigation depth and each thickness region in the low-velocity zone; performing surface constraint tomographic inversion by taking the target tomographic inversion offset distance as a constraint condition to establish a low-velocity zone model; and performing inversion on the basis of the low-velocity zone model to obtain a surface model, wherein the surface model is used to represent the structural characteristics of the low-velocity zone in the surface medium or the structural characteristics of the low-velocity zone and the region below the low-velocity zone. The constructed surface model has high precision.

Description

Technical Field

[0001] This disclosure relates to the fields of oil and gas exploration and tomographic inversion technology, and in particular to a method and apparatus for surface constraint inversion modeling based on ray depth matching. Background Technology

[0002] In the process of oil and gas exploration, geological structures are usually explored based on seismic waves. The propagation and echo of seismic waves in the geological structure are used to analyze the geological physical structure and characteristics.

[0003] In some regions, exploration features are characterized by complex surface and subsurface structures. Due to the complexity of the subsurface structure, increasingly concealed targets, and drastic variations in the lithology, velocity, and thickness of the surface medium, the signal-to-noise ratio of the acquired seismic data is extremely low. In particular, the low modeling accuracy caused by the complex surface structure makes it difficult to address the impact of complex static corrections on imaging and affects pre-stack depth migration imaging, becoming a major challenge hindering breakthroughs in high-precision imaging of seismic data in these complex regions. Summary of the Invention

[0004] To address, or at least partially address, the following technical problems: In complex terrain, the varying depths of surface survey points lead to inaccurate constraints on tomographic inversion, resulting in significant inversion errors; constraints established based on surface survey results with varying depths cause mutual interference during inversion, generating velocity anomaly zones and consequently lower inversion model accuracy; embodiments of this disclosure provide a method and apparatus for surface constraint inversion modeling based on ray depth matching.

[0005] In a first aspect, embodiments of this disclosure provide a method for surface-constrained inversion modeling based on ray depth matching. The method includes: determining the thickness distribution characteristics of a low-velocity zone in the surface medium of an exploration area; dividing the low-velocity zone into one or more thickness regions based on the thickness distribution characteristics; determining a target tomographic inversion ray depth and a corresponding target tomographic inversion offset that match the smaller depth in the aforementioned positional relationship, based on the positional relationship between the surface survey depth and each thickness region in the low-velocity zone; performing surface-constrained tomographic inversion using the target tomographic inversion offset as a constraint condition to establish a low-velocity zone model; and performing inversion based on the low-velocity zone model to obtain a surface model, wherein the surface model is used to characterize the structural features of the low-velocity zone in the surface medium or the structural features of the low-velocity zone and the region below it.

[0006] According to embodiments of this disclosure, determining the target tomographic inversion ray depth and corresponding target tomographic inversion offset distance that matches the smaller depth in the aforementioned positional relationship with the surface survey depth and each thickness region in the aforementioned low-velocity zone, includes: determining whether the positional relationship between the surface survey depth of the survey point in the current region and the thickness of the current region is consistent for each thickness region in the aforementioned low-velocity zone; if the positional relationship is consistent, determining the relatively smaller of the surface survey depth and the thickness of the current region; taking the relatively smaller one as the matching object, and determining the target tomographic inversion ray depth and corresponding target tomographic inversion offset distance that matches the matching object.

[0007] According to embodiments of this disclosure, when the surface investigation depth in the current region is greater than the thickness of the current region, a first tomographic inversion ray depth matching the thickness of the current region is determined as the target tomographic inversion ray depth, wherein the value of the first tomographic inversion ray depth exceeds the thickness of the current region by a preset grid size; the target tomographic inversion offset is the tomographic inversion offset corresponding to the first tomographic inversion ray depth; when the surface investigation depth in the current region is less than the thickness of the current region, a second tomographic inversion ray depth matching the surface investigation depth in the current region is determined as the target tomographic inversion ray depth, wherein the value of the second tomographic inversion ray depth exceeds the maximum value of the surface investigation depth of the current region by another preset grid size; the target tomographic inversion offset is the tomographic inversion offset corresponding to the second tomographic inversion ray depth.

[0008] According to embodiments of this disclosure, based on the positional relationship between the surface survey depth and the thickness regions in the aforementioned low-velocity zone, a target tomographic inversion ray depth and a corresponding target tomographic inversion offset are determined that match the smaller depth in the aforementioned positional relationship. The method further includes: in cases of inconsistent positional relationships, determining that the target positional relationship with a relatively large number of survey points in the current region is either a first positional relationship where the surface survey depth is less than the thickness of the current region, or a second positional relationship where the surface survey depth is greater than the thickness of the current region; when the target positional relationship is the first positional relationship, the second tomographic inversion ray depth matching the surface survey depth in the current region is determined as the first-level tomographic inversion ray depth, and the first tomographic inversion ray depth matching the thickness of the current region is determined as the second-level tomographic inversion ray depth. The target tomographic inversion ray depth includes the first-level tomographic inversion ray depth and the second-level tomographic inversion ray depth, and the target tomographic inversion offset includes: the first-level tomographic inversion offset corresponding to the first-level tomographic inversion ray depth and the second-level tomographic inversion offset corresponding to the second-level tomographic inversion ray depth.

[0009] According to an embodiment of this disclosure, the target tomographic inversion offset is used as a constraint condition to perform surface-constrained tomographic inversion and establish a low-velocity zone model, including: performing surface-constrained tomographic inversion based on the first-level tomographic inversion offset as a constraint condition to obtain a basic low-velocity zone model; and, based on the basic low-velocity zone model, continuing surface-constrained tomographic inversion based on the second-level tomographic inversion ray depth as a constraint condition to obtain the low-velocity zone model.

[0010] According to an embodiment of this disclosure, based on the positional relationship between the surface survey depth and each thickness region in the aforementioned low-velocity zone, a target tomographic inversion ray depth and a corresponding target tomographic inversion offset that match the smaller depth in the aforementioned positional relationship are determined. The method further includes: when the aforementioned target positional relationship is a second positional relationship, determining a first tomographic inversion ray depth that matches the thickness of the current region as the target tomographic inversion ray depth, and the aforementioned target tomographic inversion offset being the tomographic inversion offset corresponding to the aforementioned first tomographic inversion ray depth.

[0011] According to embodiments of this disclosure, an inversion is performed based on the aforementioned low-velocity zone model to obtain a surface model, including: keeping the aforementioned low-velocity zone model unchanged, performing inversion and spatial domain (CMP) stratification control point constraints based on adjusted offsets, wherein the adjusted offsets are offsets corresponding to the depth of the adjusted ray that is greater than the depth of the target tomographic inversion ray, to obtain velocity information of the region below the aforementioned surface investigation depth within the aforementioned low-velocity zone or velocity information of the high-speed zone below the aforementioned low-velocity zone; generating a supplementary model based on the aforementioned velocity information; and integrating the aforementioned low-velocity zone model and the aforementioned supplementary model to obtain the surface model.

[0012] Secondly, embodiments of this disclosure provide an apparatus for surface constraint inversion modeling based on ray depth matching. The apparatus includes: a thickness distribution determination module, a region division module, a ray depth matching module, and a constraint inversion module. The thickness distribution determination module is used to determine the thickness distribution characteristics of a low-velocity gradient zone in the surface medium of an exploration area. The region division module is used to divide the low-velocity gradient zone into one or more thickness regions based on the thickness distribution characteristics. The ray depth matching module is used to determine the target tomographic inversion ray depth and the corresponding target tomographic inversion offset that match the smaller depth in the positional relationship between the surface survey depth and each thickness region in the low-velocity gradient zone. The constraint inversion module is used to perform surface constraint tomographic inversion using the target tomographic inversion offset as a constraint condition to establish a low-velocity gradient zone model. The constraint inversion module is also used to perform inversion based on the low-velocity gradient zone model to obtain a surface model, which characterizes the structural features of the low-velocity gradient zone in the surface medium or the structural features of the low-velocity gradient zone and its underlying region.

[0013] Thirdly, embodiments of this disclosure provide an electronic device. The electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, communication interface, and memory communicate with each other via the communication bus; the memory stores computer programs; and the processor, when executing the program stored in the memory, implements the surface constraint inversion modeling method based on ray depth matching as described above.

[0014] Fourthly, embodiments of this disclosure provide a computer-readable storage medium. The computer-readable storage medium stores a computer program that, when executed by a processor, implements the surface constraint inversion modeling method based on ray depth matching as described above.

[0015] Some of the technical solutions provided in the embodiments of this disclosure have at least some or all of the following advantages:

[0016] By determining the thickness distribution characteristics of the low-velocity zone in the exploration area, the low-velocity zone is divided into one or more thickness regions. Based on the positional relationship between the surface survey depth and each thickness region in the low-velocity zone, the target tomographic inversion ray depth and the corresponding target tomographic inversion offset that match the smaller depth in the positional relationship are determined. This target tomographic inversion ray depth can match different positional relationships between the surface survey depth and the low-velocity zone. In geological environments with complex surface and subsurface structures, or both, and where the surface investigation depth h is less than the thickness H of the corresponding thickness region or greater than the thickness H of the corresponding thickness region, this system can adapt to various positional relationships to obtain suitable target tomographic inversion ray depths and corresponding target tomographic inversion offsets. It achieves effective combination and matching of surface discretization information with varying depths and first arrival information (target tomographic inversion ray depths and corresponding target tomographic inversion offsets) across different ranges, avoiding under-constraint phenomena, reducing inversion errors caused by under-constraints, and ensuring that the velocity information in the low-velocity zone is as accurate and realistic as possible, rather than equivalent velocity. The low-velocity zone model established by surface-constrained tomographic inversion based on the target tomographic inversion offset as a constraint condition has high accuracy. While solving the static correction problem, it provides a high-precision velocity field for pre-stack depth migration processing, laying the foundation for static correction calculations and pre-stack depth migration imaging processing in complex plateau areas.

[0017] Some of the technical solutions provided in the embodiments of this disclosure have at least some or all of the following advantages:

[0018] When at least one of the following situations exists: the surface investigation depth h is less than the thickness H of the corresponding thickness region, or the surface investigation depth h is greater than the thickness H of the corresponding thickness region, the target tomographic inversion ray depth and corresponding target tomographic inversion offset can be adapted to various positional relationships. For example, when h > H, the target tomographic inversion ray depth matched with the smaller depth in the above positional relationship can ensure that the thickness (or depth) of the low-velocity zone matches the tomographic ray velocity, avoiding the homogenization effect of deep rays on the shallow low-velocity zone velocity. At the same time, the corresponding target tomographic inversion ray depth contains all the information of the surface investigation, and there is no under-constraint phenomenon. The surface constraint depth extends to the high-velocity layer. When h < H, the target tomographic inversion ray depth matching the smaller depth in the above positional relationship ensures that the constraints for tomographic inversion are adapted to the actual surface survey information. At this time, the ray depth contains all the information of the surface survey, and there is no under-constraint phenomenon. It can also avoid the problem of inaccurate equivalent velocity caused by the inclusion of data between h and H in the constraints, ensuring that the velocity information of the low-velocity zone is as accurate and true as possible, rather than being an equivalent velocity. Based on this, the low-velocity zone model constructed by tomographic inversion has high accuracy. Based on this low-velocity zone model, further inversion can be performed on areas in the low-velocity zone where the surface survey depth h is insufficient, such as areas between h and H (corresponding to the case of h < H), or on deeper areas below the low-velocity zone (areas with a depth greater than H, such as the high-velocity layer) to obtain the final surface model. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0020] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, those skilled in the art can obtain other drawings based on these drawings without creative effort.

[0021] Figure 1 A flowchart illustrating a method for surface constraint inversion modeling based on ray depth matching according to an embodiment of the present disclosure is shown schematically.

[0022] Figure 2 This illustration schematically shows the effect of dividing a low-speed-deceleration zone into one or more thickness regions based on the thickness distribution characteristics of the low-speed-deceleration zone according to an embodiment of the present disclosure.

[0023] Figure 3This schematically illustrates an embodiment of the present disclosure where, in a certain region, the surface investigation depth h is greater than the thickness H of the corresponding thickness region, a target tomographic inversion ray depth and a corresponding target tomographic inversion offset that match the smaller of the aforementioned positional relationships are determined.

[0024] Figure 4 This schematically illustrates an embodiment of the present disclosure where, in a certain region, the surface investigation depth h is less than the thickness H of the corresponding thickness region, a target tomographic inversion ray depth and a corresponding target tomographic inversion offset that match the smaller of the aforementioned positional relationships are determined.

[0025] Figure 5 A detailed implementation flowchart of step S130 of an embodiment of this disclosure is illustrated schematically;

[0026] Figure 6 A structural block diagram of an apparatus for surface constraint inversion modeling based on ray depth matching according to an embodiment of the present disclosure is schematically shown; and

[0027] Figure 7 A schematic block diagram of an electronic device provided in an embodiment of the present disclosure is shown. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this disclosure. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0029] The first exemplary embodiment of this disclosure provides a method for surface constraint inversion modeling based on ray depth matching.

[0030] Figure 1 A flowchart illustrating a method for surface constraint inversion modeling based on ray depth matching according to an embodiment of the present disclosure is shown schematically.

[0031] Reference Figure 1 As shown in the embodiments of this disclosure, the method for surface constraint inversion modeling based on ray depth matching includes the following steps: S110, S120, S130, S140, and S150. Steps S110 to S150 can be performed by an electronic device with a display screen.

[0032] In step S110, the thickness distribution characteristics of the low-velocity zone in the surface medium of the exploration area are determined.

[0033] In the process of oil and gas exploration, several shot points are set up on the surface of the exploration area. The shot points emit seismic waves to explore the geological structure. The propagation and echo of the seismic waves in the geological structure are used to analyze the geological physical structure and characteristics.

[0034] Due to spatial variations in elevation, thickness, and velocity near the Earth's surface, seismic waves experience unequal time delays when passing through it, resulting in significant noise in the reflection time-distance curve. The surface medium is divided into a low-velocity layer (generally less than 1000 m / s), a decreasing-velocity layer (1000 m / s to 2000 m / s), and a high-velocity layer (greater than 2000 m / s) based on velocity. The high-velocity layer is typically composed of diagenetic strata. In the embodiments of this disclosure, the low-velocity layer and the decreasing-velocity layer are collectively referred to as the low-decreasing-velocity zone.

[0035] In one embodiment, step S110 above, obtaining the thickness distribution characteristics of the low-velocity zone in the surface medium of the exploration area through initial arrival stratification in the spatial domain (CMP domain), specifically includes: acquiring single-shot initial arrival data; displaying single-shot initial arrival data at different locations in the CMP domain; performing refraction stratification on the displayed data to obtain the thickness of the low-velocity zone in the surface medium at different locations within the exploration area; and obtaining the thickness distribution characteristics based on the thickness of the low-velocity zone in the surface medium at different locations. In fact, the thickness of the low-velocity zone is measured from a downward perspective along the vertical line from the ground, and can also be considered as depth.

[0036] In step S120, based on the aforementioned thickness distribution characteristics, the aforementioned low-speed reduction zone is divided into one or more thickness regions.

[0037] Figure 2 The illustration schematically shows the effect of dividing a low-speed-deceleration zone into one or more thickness regions based on the thickness distribution characteristics of the low-speed-deceleration zone according to an embodiment of the present disclosure.

[0038] For example, refer to Figure 2 As shown, the surface interface 210 is represented by a thick solid line, the low-velocity zone interface 220 by a thin solid line, and the various shot points 201 are represented by circles distributed at different locations on the surface interface 210. The thickness of the low-velocity zone refers to the depth dimension from the surface interface 210 to the low-velocity zone interface 220. Figure 2 In the example terrain corresponding to the embodiment, the thickness distribution features are along Figure 2 The middle horizontal line, from left to right, is as follows: very thick, thick, relatively thin, relatively thick, etc. The front regions of the very thick and thick are assigned to the thickness region 231 of the piedmont zone, the middle region of the relatively thin is assigned to the thickness region 232 of the top of the structure, and the tail region of the relatively thick is assigned to the thickness region 233 of the wing of the structure.

[0039] In step S130, based on the positional relationship between the surface investigation depth and the thickness regions in the aforementioned low-velocity zone, the target tomographic inversion ray depth and the corresponding target tomographic inversion offset distance that match the smaller depth in the aforementioned positional relationship are determined.

[0040] Tomographic inversion-based velocity models consider various phenomena of seismic wave propagation in the near-surface medium and can describe the longitudinal and lateral velocity variations in complex near-surface velocity structures, making it a highly adaptable surface modeling technique. However, as a generalized linear inversion algorithm, tomographic inversion suffers from multiple solutions and equivalence issues in practical applications. Therefore, initial condition constraints need to be added during the inversion process to improve the accuracy of the inversion model. In some embodiments, surface survey information can be used for inversion constraints. This information is typically obtained through surface survey methods such as small refraction and micrologging. Small refraction is suitable for flat surfaces with simple surface structures; micrologging is generally used in "dual-complex" areas with dramatic topographic relief and complex underground structures.

[0041] In realizing the technical concept disclosed herein, it was discovered that for complex terrain, such as dual-complex terrain with both complex surface and underground structures, current surface survey methods for inversion modeling have many technical shortcomings: due to the combined influence of factors such as arrangement length, micrologging drilling capacity, surface structure, construction environment, and cost, the actual detection depth of micrologging or small refraction varies greatly; in particular, in very thick work areas, there may be many survey points where the thickness of the low-velocity zone has not been investigated. When using the survey results of these points as constraints, only the velocity changes of the thinner areas are constrained, and the inversion error caused by the "under-constraint" of relatively deep parts is large, making it difficult to effectively utilize the surface information of shallow survey depths; at the same time, the surface survey results with varying depths and large differences influence each other when constraining inversion, which can easily form velocity anomaly zones and adversely affect the velocity model.

[0042] In view of this, the embodiments of this disclosure determine the target tomographic inversion ray depth and the corresponding target tomographic inversion offset distance that match the smaller depth in the above-mentioned positional relationship based on the positional relationship between the surface investigation depth and the thickness regions in the low velocity reduction zone. This target tomographic inversion offset distance is used as a constraint condition for tomographic inversion to establish a low velocity reduction zone model. This model is suitable for situations where the actual detection depth varies and can avoid under-constraint phenomena. The resulting low velocity reduction zone model has small errors and high accuracy.

[0043] Based on step S130, when there is at least one situation where the surface investigation depth h is less than the thickness H of the corresponding thickness region or the surface investigation depth h is greater than the thickness H of the corresponding thickness region, the appropriate target tomographic inversion ray depth and corresponding target tomographic inversion offset can be obtained by adapting to various positional relationships.

[0044] The aforementioned target tomographic inversion offset can be adapted to various thickness regions and surface survey depths.

[0045] Figure 3 The illustration schematically shows an embodiment of the present disclosure where, in a certain region, the surface investigation depth h is greater than the thickness H of the corresponding thickness region, a target tomographic inversion ray depth and a corresponding target tomographic inversion offset that match the smaller of the aforementioned positional relationships are determined.

[0046] Figure 3 In the example where the positional relationship within the three thickness regions—the foreland belt 231, the structural top 232, and the structural wing 233—is h > H, other embodiments may have positional relationships where h < H within some thickness regions, as will be discussed later. Figure 4 As described in the embodiment, h < H exists in the piedmont zone 231.

[0047] In this embodiment, refer to Figure 3 As shown, for all thickness regions, when h > H, in step S130, the target tomographic inversion ray depth that matches the smaller depth (thickness H of the thickness region) in the above positional relationship is determined. This ensures that the thickness (or depth) of the low-velocity zone matches the tomographic ray velocity, avoiding the homogenization effect of deep rays on the velocity of the shallow low-velocity zone. At the same time, the corresponding target tomographic inversion ray depth contains all the information of the surface survey (e.g., the geological structure information corresponding to the surface survey depth), and there is no under-constraint phenomenon. The surface constraint depth extends to the high-velocity layer.

[0048] In some embodiments, within a certain thickness region, the method of matching the thickness of that region can be slightly larger than the thickness H of the current thickness region, for example, exceeding the thickness H of the current thickness region by a preset grid size. The preset grid size can be a preset parameter, for example, 1 to 2 grids. For example, for a thickness of approximately 200m, the preset grid size is, for example, 5m to 10m.

[0049] Figure 4 The illustration schematically shows an embodiment of the present disclosure where, in a certain region, the surface investigation depth h is less than the thickness H of the corresponding thickness region, a target tomographic inversion ray depth and a corresponding target tomographic inversion offset that match the smaller of the aforementioned positional relationships are determined. Figure 4 The bar chart in the middle illustrates the depth of the surface survey.

[0050] Reference Figure 4As shown, taking the positional relationship within the piedmont zone 231 as an example where h < H. When h < H, the target tomographic inversion ray depth matching the smaller depth (surface survey depth h) in the above positional relationship ensures that the constraints for tomographic inversion are adapted to the actual surface survey information (e.g., information on the geological structure corresponding to surface survey depth h). At this time, the ray depth contains all the information from the surface survey, and there is no under-constraint phenomenon. It also avoids the problem of inaccurate equivalent velocity caused by data between h and H in the constraints, ensuring that the velocity information of the low-velocity zone is as accurate and true as possible, rather than being an equivalent velocity. Based on this, the low-velocity zone model constructed by tomographic inversion has high accuracy. Based on this low-velocity zone model, further inversion can be performed on areas in the low-velocity zone where the surface survey depth h is insufficient, such as areas between h and H (corresponding to the case of h < H), or on deeper areas below the low-velocity zone (areas with a depth greater than H, such as high-velocity layers) to obtain the final surface model.

[0051] In step S140, the target tomographic inversion offset is used as a constraint condition to perform surface-constrained tomographic inversion and establish a low-speed-deceleration zone model.

[0052] In step S150, an inversion is performed based on the above-mentioned low-velocity zone model to obtain a surface model. The surface model is used to characterize the structural features of the low-velocity zone in the surface medium or the structural features of the low-velocity zone and the region below it.

[0053] Based on the above steps S110 to S150, by determining the thickness distribution characteristics of the low-velocity zone in the exploration area, the low-velocity zone is divided into one or more thickness regions. According to the positional relationship between the surface survey depth and each thickness region in the low-velocity zone, the target tomographic inversion ray depth and the corresponding target tomographic inversion offset that match the smaller depth in the above positional relationship are determined. The target tomographic inversion ray depth can match different positional relationships between the surface survey depth and the low-velocity zone. In geological environments with complex surface and subsurface structures, or both, and where the surface investigation depth h is less than the thickness H of the corresponding thickness region or greater than the thickness H of the corresponding thickness region, this system can adapt to various positional relationships to obtain suitable target tomographic inversion ray depths and corresponding target tomographic inversion offsets. It achieves effective combination and matching of surface discretization information with varying depths and first arrival information (target tomographic inversion ray depths and corresponding target tomographic inversion offsets) across different ranges, avoiding under-constraint phenomena, reducing inversion errors caused by under-constraints, and ensuring that the velocity information in the low-velocity zone is as accurate and realistic as possible, rather than equivalent velocity. The low-velocity zone model established by surface-constrained tomographic inversion based on the target tomographic inversion offset as a constraint condition has high accuracy. While solving the static correction problem, it provides a high-precision velocity field for pre-stack depth migration processing, laying the foundation for static correction calculations and pre-stack depth migration imaging processing in complex plateau areas.

[0054] Within the same thickness region, multiple survey points exist simultaneously. In most cases, the positional relationship between the surface survey depth of each survey point and the thickness of the current region is consistent. However, in some implementation scenarios, this relationship may be inconsistent. For example, within the same thickness region, the surface survey depth of some survey points may be greater than the thickness of the current region, while the surface survey depth of some survey points may be less than the thickness of the current region. To address this scenario, embodiments of this disclosure also propose processing logic for determining the target tomographic inversion ray depth and the corresponding target tomographic inversion offset based on whether the positional relationship is consistent. For the typical scenario where the positional relationship is consistent, executing the branch indicating consistent positional relationship is sufficient. The following section combines... Figure 5 Let me give you a detailed introduction.

[0055] Figure 5 A detailed implementation flowchart of step S130 of an embodiment of the present disclosure is shown schematically.

[0056] According to embodiments of this disclosure, referring to Figure 5As shown, in step S130 above, based on the positional relationship between the surface investigation depth and each thickness region in the low velocity reduction zone, the target tomographic inversion ray depth and the corresponding target tomographic inversion offset that match the smaller depth in the positional relationship are determined, including: S510, S520a and S530a.

[0057] In step S510, for each thickness region in the aforementioned low-speed reduction zone, it is determined whether the positional relationship between the surface investigation depth of the investigation point in the current region and the thickness of the current region is consistent.

[0058] In step S520a, if the positional relationship is consistent, determine the smaller of the surface survey depth and the thickness of the current area.

[0059] In step S530a, the smaller one is taken as the target to be matched, and the target tomographic inversion ray depth and the corresponding target tomographic inversion offset that match the target to be matched are determined.

[0060] According to embodiments of this disclosure, when the surface investigation depth h in the current region is greater than the thickness H of the current region, for example, referring to... Figure 3 As shown, when h > H, the first tomographic inversion ray depth matching the thickness of the current region is determined as the target tomographic inversion ray depth, and the target tomographic inversion offset is the tomographic inversion offset corresponding to the first tomographic inversion ray depth. The value of the first tomographic inversion ray depth exceeds the thickness H of the current region by a preset grid size (e.g., 1 to 2 grid sizes). Here, the target tomographic inversion offset corresponding to the thickness region when h > H is denoted as L.

[0061] For example, in one embodiment, for the case where h > H, the offset inversion scan is first performed using all shot points: such as using 100m, 200m, 300m, 400m, ... etc. to perform preliminary tomographic inversion tests on the initial arrival data of the offset distance. Based on the matching of tomographic inversion ray depth and the thickness of the low-velocity zone, the range of surface inversion offset distances for different regions is determined. For example, the thickness of the 231 region in the foreland belt of the low-velocity zone is 200m. After offset inversion experiments, the tomographic inversion ray depth at an offset distance of 600m is found to be slightly greater than the maximum thickness of the 231 region (slightly greater can be greater than the maximum thickness of the region with a preset grid size, as shown in previous examples, and will not be repeated here). Therefore, the target tomographic inversion offset distance for the 231 region can be determined to be around 600m. Similarly, the thickness of the 232 region at the top of the structure in the low-velocity zone is 50m. Based on the same inversion experiment method, the corresponding target tomographic inversion offset distance is 200m. The thickness of the 233 wing of the structure in the low-velocity zone is 100m, and the corresponding target tomographic inversion offset distance is 400m.

[0062] First-arrival offset ranges for different regions: Based on the offset ranges for different thickness regions determined above, shot points are selected for these regions, and the range of the inverted first-arrival data is limited. For example, the first-arrival data of shot point 231 in the foreland zone is limited to the range of 0-600m, the first-arrival data of shot point 232 at the top of the structure is limited to the range of 0-200m, and the first-arrival data of shot point 233 in the wing of the structure is limited to the range of 0-400m. This ensures that the thickness of the low-velocity zone matches the tomographic ray velocity and avoids the homogenization effect of deep rays on the shallow low-velocity zone velocity.

[0063] When establishing a low-velocity zone model through tomographic inversion based on the aforementioned range limitations as constraints, the constraints corresponding to the ray depth contain all the information from the surface survey, and there is no under-constraint phenomenon.

[0064] According to embodiments of this disclosure, when the surface investigation depth h in the current region is less than the thickness H of the current region, for example, referring to... Figure 4 As shown, when h < H, the second tomographic inversion ray depth that matches the surface survey depth h in the current region is determined as the target tomographic inversion ray depth, and the target tomographic inversion offset is the tomographic inversion offset corresponding to the second tomographic inversion ray depth. The value of the second tomographic inversion ray depth exceeds the maximum surface survey depth of the current region by another preset grid size (e.g., 0, 1, or 2 grid sizes). Here, the target tomographic inversion offset corresponding to the thickness region when h < H is denoted as r.

[0065] In this embodiment, when h < H, a ray depth slightly greater than the maximum depth of the surface survey is selected to determine the offset range (denoted as r). At this point, the ray depth contains all the information from the surface survey, and there is no under-constraint phenomenon. This offset range r is used for constrained inversion. That is, when h < H, the offset range r is used as the constraint condition for the entire region to perform surface constrained tomography inversion and establish a low-velocity zone model.

[0066] According to embodiments of this disclosure, referring to Figure 5 As shown, in addition to steps S510, S520a, and S530a, step S130 also includes the following steps: S520b and S531b; in other embodiments, refer to Figure 5 As shown in the dashed box, it may also include a branch step S532b where the target position relationship is the second position relationship.

[0067] In step S520b, when the positional relationships are inconsistent, the target positional relationship with the relatively larger number of survey points in the current area is determined to be either a first positional relationship where the surface survey depth h is less than the thickness H of the current area, or a second positional relationship where the surface survey depth h is greater than the thickness H of the current area.

[0068] In step S531b, when the target position relationship is the first position relationship, the second tomographic inversion ray depth matching the surface investigation depth h in the current region is determined as the first-level tomographic inversion ray depth, and the first tomographic inversion ray depth matching the thickness H of the current region is determined as the second-level tomographic inversion ray depth. The target tomographic inversion ray depth includes the first-level tomographic inversion ray depth and the second-level tomographic inversion ray depth. The target tomographic inversion offset includes the first-level tomographic inversion offset corresponding to the first-level tomographic inversion ray depth and the second-level tomographic inversion offset corresponding to the second-level tomographic inversion ray depth. For example, the first-level tomographic inversion offset corresponds to the target tomographic inversion offset r when h < H, and the second-level tomographic inversion offset corresponds to the target tomographic inversion offset L when h > H.

[0069] In an embodiment including step S531b, in step S140, the target tomographic inversion offset is used as a constraint condition to perform surface-constrained tomographic inversion and establish a low-velocity zone model. This includes: performing surface-constrained tomographic inversion based on the first-level tomographic inversion offset (e.g., r) as a constraint condition to obtain a basic low-velocity zone model; and continuing surface-constrained tomographic inversion based on the second-level tomographic inversion ray depth (e.g., L) as a constraint condition to obtain the low-velocity zone model.

[0070] In step S532b, when the target position relationship is the second position relationship, the first tomographic inversion ray depth that matches the thickness H of the current region is determined as the target tomographic inversion ray depth, and the target tomographic inversion offset is the tomographic inversion offset corresponding to the first tomographic inversion ray depth.

[0071] In embodiments including the above steps {S510, S520a, and S530a}, or including {S510, S520a, S530a, S520b, and S531b}, or including {S510, S520a, S530a, S520b, S531b, and S532b}, regardless of whether a certain thickness region is h > H, h < H, or both h > H and h < H exist simultaneously in the same thickness region, when h > H, the target tomographic inversion ray depth matching the smaller of the above positional relationships can ensure that the thickness (or depth) of the low-velocity zone matches the tomographic ray velocity, avoiding the homogenization effect of deep rays on the shallow low-velocity zone velocity. At the same time, the corresponding target tomographic inversion ray depth contains all the information of the surface investigation information, and there is no under-constraint phenomenon. The surface constraint depth extends to the high-velocity layer. When h < H, the target tomographic inversion ray depth that matches the smaller depth in the above positional relationship can ensure that the constraints for tomographic inversion are adapted to the actual surface survey information. At this time, the ray depth contains all the information of the surface survey information, and there is no under-constraint phenomenon. It can also avoid the problem of inaccurate equivalent velocity caused by the inclusion of data between h and H in the constraints, and ensure that the velocity information of the low-deceleration zone is as accurate and true as possible, rather than being an equivalent velocity.

[0072] In step S150, based on the low-velocity zone model obtained in step S140 (ensuring that the velocity information of the low-velocity zone is as accurate and real as possible, not equivalent velocity), the shallow basic model is kept as unchanged as possible (inversion weight settings are implemented through professional software). Large offset inversion and CMP domain hierarchical control point constraints are used to obtain reliable velocity information of deeper layers below the high-velocity top, and a surface model is established to lay the foundation for subsequent pre-stack depth migration modeling.

[0073] In one embodiment, step S150 above, which involves inverting the low-velocity zone model to obtain a surface model, includes: keeping the low-velocity zone model unchanged, performing inversion and spatial domain (CMP) stratification control point constraints based on the adjusted offset distance, wherein the adjusted offset distance is the offset distance corresponding to the adjusted ray depth whose depth is greater than the depth of the target tomographic inversion ray, to obtain velocity information of the region below the surface investigation depth within the low-velocity zone or velocity information of the high-speed zone below the low-velocity zone; generating a supplementary model based on the velocity information; and integrating the low-velocity zone model and the supplementary model to obtain the surface model.

[0074] Because the constructed low-velocity zone model has high accuracy, further inversion based on this model can be performed on areas in the low-velocity zone where the surface investigation depth h is insufficient, such as areas between h and H (corresponding to the case where h < H), or on deeper areas below the low-velocity zone (areas with a depth greater than H, such as the high-velocity layer) to obtain the final surface model (the surface velocity model).

[0075] In one application example, the method provided in this disclosure was explored and applied in the processing of 3D seismic depth migration data in complex terrain areas such as the Hero Ridge area of ​​the Qaidam Basin and the Kulongshan area of ​​the Jiuquan Basin. This method fully leverages the application effect of surface velocity information from micrologging at different depths, improving the modeling accuracy of surface models in complex scenarios involving both surface and subsurface structures. It breaks through the conventional approach of using equivalent surface velocities, making the surface model closer to the actual velocity and contributing to improved accuracy of pre-stack depth migration imaging of seismic data in complex areas.

[0076] It is understood that although the embodiments of this disclosure can effectively solve the problem of low model accuracy for complex terrains, the method can also be applied to simpler terrains.

[0077] A second exemplary embodiment of this disclosure provides an apparatus for surface constraint inversion modeling based on ray depth matching.

[0078] Figure 6 A schematic block diagram of an apparatus for surface constraint inversion modeling based on ray depth matching according to an embodiment of the present disclosure is shown.

[0079] Reference Figure 6 As shown, the apparatus 600 for surface constraint inversion modeling based on ray depth matching provided in this embodiment includes: a thickness distribution determination module 601, a region division module 602, a ray depth matching module 603, and a constraint inversion module 604.

[0080] The aforementioned thickness distribution determination module 601 is used to determine the thickness distribution characteristics of the low-velocity zone in the surface medium of the exploration area.

[0081] The aforementioned region division module 602 is used to divide the aforementioned low speed reduction zone into one or more thickness regions based on the aforementioned thickness distribution characteristics.

[0082] The aforementioned ray depth matching module 603 is used to determine the target tomographic inversion ray depth and the corresponding target tomographic inversion offset distance that match the smaller depth in the aforementioned positional relationship, based on the positional relationship between the surface survey depth and each thickness region in the aforementioned low velocity reduction zone.

[0083] The aforementioned constraint inversion module 604 is used to perform surface constraint tomography inversion using the aforementioned target tomography inversion offset as a constraint condition, and to establish a low-speed reduction zone model.

[0084] The aforementioned constraint inversion module 604 is also used to perform inversion based on the aforementioned low-velocity zone model to obtain a surface model. The surface model is used to characterize the structural features of the low-velocity zone in the aforementioned surface medium or the structural features of the aforementioned low-velocity zone and the region below it.

[0085] The various functional modules in the device provided in this embodiment may further include functional modules or sub-modules that can implement the various detailed steps corresponding to the first embodiment. These can be understood with reference to the detailed steps in the first embodiment, and will not be repeated here.

[0086] Any multiple of the aforementioned thickness distribution determination module 601, region partitioning module 602, ray depth matching module 603, and constraint inversion module 604 can be combined into one module, or any one of these modules can be split into multiple modules. Alternatively, at least some of the functionality of one or more of these modules can be combined with at least some of the functionality of other modules and implemented in one module. At least one of the thickness distribution determination module 601, region partitioning module 602, ray depth matching module 603, and constraint inversion module 604 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging circuitry, or implemented in hardware or firmware, or in any one of software, hardware, and firmware implementations, or in a suitable combination of any of these. Alternatively, at least one of the thickness distribution determination module 601, region division module 602, ray depth matching module 603, and constraint inversion module 604 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0087] A third exemplary embodiment of this disclosure provides an electronic device.

[0088] Figure 7 A schematic block diagram of an electronic device provided in an embodiment of the present disclosure is shown.

[0089] Reference Figure 7As shown, the electronic device 700 provided in this embodiment includes a processor 701, a communication interface 702, a memory 703, and a communication bus 704. The processor 701, the communication interface 702, and the memory 703 communicate with each other through the communication bus 704. The memory 703 is used to store computer programs. When the processor 701 executes the program stored in the memory, it implements the surface constraint inversion modeling method based on ray depth matching as described above.

[0090] A fourth exemplary embodiment of this disclosure also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program that, when executed by a processor, implements the surface constraint inversion modeling method based on ray depth matching as described above.

[0091] The computer-readable storage medium may be included in the device / apparatus described in the above embodiments; or it may exist independently and not assembled into the device / apparatus. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0092] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0093] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0094] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for surface constraint inversion modeling based on ray depth matching, characterized in that, include: Determine the thickness distribution characteristics of the low-velocity zone in the surface medium of the exploration area; Based on the thickness distribution characteristics, the low-speed reduction zone is divided into one or more thickness regions; Based on the positional relationship between the surface survey depth and each thickness region in the low-velocity zone, determine the target tomographic inversion ray depth and the corresponding target tomographic inversion offset that match the smaller depth in the positional relationship. Using the target tomographic inversion offset as a constraint, surface-constrained tomographic inversion is performed to establish a low-speed-deceleration zone model. Based on the low-velocity zone model, an inversion is performed to obtain a surface model, which is used to characterize the structural features of the low-velocity zone in the surface medium or the structural features of the low-velocity zone and the region below it. Based on the positional relationship between the surface survey depth and the thickness regions in the low-velocity zone, determine the target tomographic inversion ray depth and corresponding target tomographic inversion offset that match the smaller depth in the positional relationship, including: For each thickness region in the low-speed reduction zone, determine whether the positional relationship between the surface investigation depth of the investigation point in the current region and the thickness of the current region is consistent; Given consistent location relationships, determine the smaller of the surface survey depth and the thickness of the current area; The smaller one is taken as the object to be matched, and the target tomographic inversion ray depth and the corresponding target tomographic inversion offset that match the object to be matched are determined. When the surface investigation depth in the current region is greater than the thickness of the current region, the first tomographic inversion ray depth that matches the thickness of the current region is determined as the target tomographic inversion ray depth. The value of the first tomographic inversion ray depth exceeds the thickness of the current region by a preset grid size. The target tomographic inversion offset is the tomographic inversion offset corresponding to the first tomographic inversion ray depth. When the surface survey depth in the current region is less than the thickness of the current region, the second tomographic inversion ray depth that matches the surface survey depth in the current region is determined as the target tomographic inversion ray depth. The value of the second tomographic inversion ray depth exceeds the maximum surface survey depth of the current region by another preset grid size. The target tomographic inversion offset is the tomographic inversion offset corresponding to the second tomographic inversion ray depth.

2. The method according to claim 1, characterized in that, Based on the positional relationship between the surface survey depth and the thickness regions within the low-velocity zone, the target tomographic inversion ray depth and corresponding target tomographic inversion offset that match the smaller depth in the positional relationship are determined, further including: In cases of inconsistent location relationships, the target location relationship with a relatively large number of survey points in the current area is determined to be either the first location relationship where the surface survey depth is less than the thickness of the current area, or the second location relationship where the surface survey depth is greater than the thickness of the current area. When the target position relationship is the first position relationship, the second tomographic inversion ray depth that matches the surface survey depth in the current area is determined as the first-level tomographic inversion ray depth, and the first tomographic inversion ray depth that matches the thickness of the current area is determined as the second-level tomographic inversion ray depth. The target tomographic inversion ray depth includes the first-level tomographic inversion ray depth and the second-level tomographic inversion ray depth. The target tomographic inversion offset includes the first-level tomographic inversion offset corresponding to the first-level tomographic inversion ray depth and the second-level tomographic inversion offset corresponding to the second-level tomographic inversion ray depth.

3. The method according to claim 2, characterized in that, Using the target tomographic inversion offset as a constraint, surface-constrained tomographic inversion is performed to establish a low-velocity zone model, including: Based on the first-level tomographic inversion offset as a constraint condition, surface-constrained tomographic inversion is performed to obtain the basic low-speed reduction zone model. Based on the basic low-velocity zone model, surface-constrained tomography is performed using the second-level tomography inversion ray depth as a constraint condition to obtain the low-velocity zone model.

4. The method according to claim 2, characterized in that, Based on the positional relationship between the surface survey depth and the thickness regions within the low-velocity zone, the target tomographic inversion ray depth and corresponding target tomographic inversion offset that match the smaller depth in the positional relationship are determined, further including: When the target position relationship is the second position relationship, the first tomographic inversion ray depth that matches the thickness of the current region is determined as the target tomographic inversion ray depth, and the target tomographic inversion offset is the tomographic inversion offset corresponding to the first tomographic inversion ray depth.

5. The method according to claim 1, characterized in that, Based on the aforementioned low-speed-deceleration-band model, an inversion is performed to obtain the surface model, including: Keeping the low-velocity zone model unchanged, inversion and spatial domain hierarchical control point constraints are performed based on the adjusted offset distance. The adjusted offset distance is the offset distance corresponding to the adjusted ray depth whose depth is greater than the depth of the target tomographic inversion ray. This yields the velocity information of the region below the surface investigation depth within the low-velocity zone or the velocity information of the high-velocity zone below the low-velocity zone. Based on the speed information, a supplementary model is generated; By integrating the low-speed-deceleration-band model and the supplementary model, a surface model is obtained.

6. A device for surface constraint inversion modeling based on ray depth matching, characterized in that, include: The thickness distribution determination module is used to determine the thickness distribution characteristics of the low-velocity zone in the surface medium of the exploration area. The region division module is used to divide the low deceleration zone into one or more thickness regions based on the thickness distribution characteristics. The ray depth matching module is used to determine the target tomographic inversion ray depth and the corresponding target tomographic inversion offset distance that match the smaller depth in the positional relationship with the surface investigation depth and the thickness regions in the low velocity reduction zone, based on the positional relationship between the surface investigation depth and the thickness regions in the low velocity reduction zone. The constraint inversion module is used to perform surface constraint tomography inversion using the target tomography inversion offset as a constraint condition, and to establish a low-speed-deceleration zone model. The constraint inversion module is also used to perform inversion based on the low-velocity zone model to obtain a surface model. The surface model is used to characterize the structural features of the low-velocity zone in the surface medium or the structural features of the low-velocity zone and the region below it. Based on the positional relationship between the surface survey depth and the thickness regions in the low-velocity zone, determine the target tomographic inversion ray depth and corresponding target tomographic inversion offset that match the smaller depth in the positional relationship, including: For each thickness region in the low-speed reduction zone, determine whether the positional relationship between the surface investigation depth of the investigation point in the current region and the thickness of the current region is consistent; Given consistent location relationships, determine the smaller of the surface survey depth and the thickness of the current area; The smaller one is taken as the object to be matched, and the target tomographic inversion ray depth and the corresponding target tomographic inversion offset that match the object to be matched are determined. When the surface investigation depth in the current region is greater than the thickness of the current region, the first tomographic inversion ray depth that matches the thickness of the current region is determined as the target tomographic inversion ray depth. The value of the first tomographic inversion ray depth exceeds the thickness of the current region by a preset grid size. The target tomographic inversion offset is the tomographic inversion offset corresponding to the first tomographic inversion ray depth. When the surface survey depth in the current region is less than the thickness of the current region, the second tomographic inversion ray depth that matches the surface survey depth in the current region is determined as the target tomographic inversion ray depth. The value of the second tomographic inversion ray depth exceeds the maximum surface survey depth of the current region by another preset grid size. The target tomographic inversion offset is the tomographic inversion offset corresponding to the second tomographic inversion ray depth.

7. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the method of any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1-5.

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