A Volcanic Rock Velocity Modeling and Imaging Method Based on Iterative Boundary Correction

Abstract

This application discloses a volcanic rock velocity modeling and imaging method based on iterative boundary correction, belonging to the field of oil and gas geophysical exploration. The method first establishes a background velocity field through conventional grid tomography and initially identifies the target volcanic rock area and its boundaries by integrating acoustic impedance inversion and seismic facies characteristics. Then, it enters the core iterative optimization stage, where velocity scanning is performed within the identified area to generate candidate velocity models. Each candidate velocity model is migrated and the volcanic rock boundary is re-extracted. The optimal velocity and volcanic rock boundary are obtained through joint selection, and the iteration continues based on changes in the volcanic rock boundary. Finally, the optimal velocity is filled into the optimal boundary region and stitched with the background field to obtain the final velocity model, which is then used for pre-stack depth migration imaging. This application overcomes the smoothing limitations of traditional tomographic inversion and effectively solves the "velocity-depth" coupling problem in volcanic rock areas through closed-loop optimization, significantly improving the imaging accuracy of the underlying structures of volcanic rocks.

Description

Technical Field

[0001] This application relates to the field of oil and gas geophysical exploration, specifically to a method for modeling and imaging volcanic rock velocity based on iterative boundary correction. It is particularly suitable for fine-grained structural imaging of volcanic rock-covered areas with strong vertical and horizontal velocity abrupt changes. Background Technology

[0002] In seismic exploration of oil and gas, pre-stack depth migration is a key technology for obtaining images of complex structures, and its imaging accuracy heavily depends on the accuracy of the velocity model. The conventional grid tomography inversion velocity modeling method is the mainstream approach in the industry. It optimizes the velocity model through iterative updates and can adapt well to scenarios with continuous and gradually varying velocity fields.

[0003] However, when underground geological bodies such as volcanic rock masses exist, there is a significant, laterally abrupt difference in the rate of change between them and the surrounding rocks. Conventional grid tomography methods have inherent limitations: 1. Insensitive to abrupt changes: Tomographic inversion is based on ray theory, and its smoothing constraints on velocity and low-frequency update characteristics make it difficult to accurately characterize the boundaries of high-speed or low-speed anomalies with lateral abrupt changes in volcanic rocks. 2. "Velocity-Depth" Coupling Effect: Inaccurate volcanic rock velocities can cause distortion of the imaging ray paths of the underlying strata, thereby creating false structures in the underlying strata (such as pull-up or pull-down phenomena), severely distorting the true geological structure and misleading geological interpretation and drilling deployment.

[0004] Existing techniques such as full waveform inversion (high computational cost and sensitivity to the initial model) and purely interpretive processing (high subjectivity and low efficiency) all have their own shortcomings and have failed to effectively solve the problem of characterizing volcanic rock velocities. Therefore, there is an urgent need in this field for a novel velocity modeling method that can accurately characterize volcanic rock boundaries and velocities, thereby ensuring accurate imaging of the underlying strata. Summary of the Invention

[0005] The technical problem this application aims to solve is to address the shortcomings of the existing technologies by proposing an iterative boundary correction-based method for volcanic rock velocity modeling and imaging. This method, based on the macroscopic background velocity field provided by conventional grid tomography, initially identifies volcanic rocks through cross-validation of acoustic impedance inversion and seismic facies characteristics. Then, through velocity scanning and imaging feedback, iteratively corrects the boundaries and velocities to achieve refined model construction. The specific steps are as follows: Step 1: Establish the background velocity field and preliminarily identify the volcanic rock target area and its boundaries; Step 2: Perform iterative boundary correction and determine the optimal speed. This step includes: Based on the prior knowledge of volcanic rock velocities obtained from drilling in the study area and / or adjacent exploration areas, the volcanic rock velocity scanning range is determined, and a series of velocity values ​​are set for filling to generate candidate velocity models. For each candidate velocity model, migration imaging and feature extraction are performed. Pre-stack depth migration is then performed using each candidate velocity model to obtain candidate migration data volumes. Wave impedance inversion and seismic facies interpretation are then performed on each candidate migration data volume to obtain the corresponding candidate volcanic rock boundaries. The optimal velocity and optimal volcanic rock boundary of the candidate velocity model with the best imaging quality and the most reliable boundary features are obtained through joint selection; and iterative judgment is performed, comparing the current optimal boundary with the boundary of the previous round. If the boundary changes significantly, the current optimal boundary is taken as the new volcanic rock identification area, and the velocity filling and scanning steps are returned. If the boundary is stable and the imaging is satisfactory, the iteration terminates. Step 3: Generate the final velocity model and perform imaging.

[0006] Furthermore, step one includes: An initial pre-stack depth migration velocity model was established using the grid tomography inversion method, and pre-stack depth migration processing was carried out using the pre-stack depth migration velocity model to obtain the initial depth migration data volume. Well logging, vertical seismic profiles and low-frequency velocity trends derived from the initial velocity model were comprehensively utilized in the work area. Impedance inversion is performed on the depth migration data volume. This impedance inversion is a process of converting seismic reflection data into subsurface rock impedance, i.e., formation properties. The formula for calculating impedance is: Z =ρ×Vp Where ρ is the formation density, Vp is the P-wave velocity, and Z is the wave impedance; The sparse pulse inversion and / or model-based iterative inversion ultimately output a wave impedance data volume, in which each data point represents the wave impedance value of the formation.

[0007] Volcanic rock identification and extraction: quantitative extraction of target geological information from inversion results.

[0008] Furthermore, the process of quantitatively extracting target geological information from the inversion results includes: Based on the logging data of wells that pass through known volcanic rocks in the work area, the range of wave impedance values ​​of the volcanic rock section and the range of wave impedance values ​​of the surrounding rock were statistically determined. Based on the distribution of the wave impedance values ​​of the volcanic rock section and the surrounding rock section, one or more wave impedance thresholds are determined to distinguish between volcanic rocks and surrounding rocks. By applying a determined wave impedance threshold, continuous regions are automatically extracted from the data volume through attribute extraction and / or 3D volume sculpting techniques, i.e., the initially delineated potential development areas of volcanic rocks. By comparing the boundary of the potential volcanic rock development area with the reflection characteristics on the seismic profile, areas that do not conform to the geological characteristics of volcanic rocks are eliminated, and the volcanic rock development area is determined. The depth migration data volume profile is overlaid with the initial pre-stack depth migration velocity model for display, and areas with typical seismic facies characteristics of volcanic rocks are intelligently identified. The identification of potential volcanic rock development areas and typical volcanic rock seismic facies characteristic areas is achieved through spatial convergence and fusion to form an initial volcanic rock identification area and its boundary.

[0009] Furthermore, prior information refers to the experience gained from drilling in the study area and / or adjacent exploration areas regarding volcanic rock velocities.

[0010] Furthermore, in step two, the boundary obtained by the volume wave impedance inversion of each candidate migration data is fused with the boundary obtained by the seismic phase interpretation to obtain the candidate volcanic rock boundary.

[0011] Furthermore, the criteria for joint selection in step two include: Boundary reliability, including boundary clarity and geological plausibility; Imaging quality of underlying strata, including the continuity of phase axes and the degree of tectonic distortion correction.

[0012] Further, step three includes: filling the region delineated by the optimal volcanic rock boundary with the finally determined optimal velocity and smoothly stitching it with the regional background velocity field to obtain a high-precision final velocity model; using the final model to perform pre-stack depth migration to obtain a high-quality imaging data volume.

[0013] Compared with the prior art, this application achieves the following technical effects: 1. Overcoming the smoothness limitation of tomographic inversion: By using a deterministic method of "fill-scan-verify", an accurate velocity value is directly assigned to the volcanic rock mass, fundamentally solving the problem that grid tomography cannot characterize lateral velocity abrupt changes.

[0014] 2. A closed-loop optimization of "velocity-boundary-imaging" is formed: This application introduces a key iterative loop to solve the problem of "velocity-depth" coupling in geophysics. In each iteration, the velocity model and the geological body boundary promote each other and jointly approximate the real situation, so that the method has self-correction and self-adaptation capabilities.

[0015] 3. Multi-information fusion for more accurate identification: This application innovatively combines wave impedance inversion (physical properties) with seismic phase velocity field superposition identification (geological morphology), and uses imaging results at different velocities in the iteration to compare and select the most reliable boundary, which significantly reduces ambiguity and subjectivity and greatly improves the accuracy of boundary characterization.

[0016] 4. Imaging-driven with a clear objective: The final evaluation criterion is "optimal imaging quality of the underlying strata," which makes the velocity modeling process directly serve the imaging target, with clear physical meaning and strong practicality.

[0017] 5. Streamlined and highly operable: The method described in this application has clear steps, is easy to implement on existing seismic processing software platforms, has good prospects for industrial promotion, can significantly improve the imaging accuracy of the underlying structures of volcanic rocks, and provide a reliable basis for the fine description of oil and gas reservoirs.

[0018] 6. Reduce the possibility of multiple interpretations: Not all high wave impedance anomalies are volcanic rocks. For example, some dense carbonate rocks and igneous rocks may also have high wave impedance. The ingenuity of the "dual verification" in this invention lies in providing an objective and quantitative target candidate area through wave impedance inversion. The subsequent combination with seismic phase velocity field superposition identification is a geological filter and confirmation of this result, effectively reducing multiple interpretations. Attached Figure Description

[0019] For ease of explanation, this application is described in detail below with reference to specific embodiments and accompanying drawings.

[0020] Figure 1 A flowchart illustrating the overall process of a volcanic rock velocity modeling and imaging method based on iterative boundary correction. Figures 2(a)-(c) are schematic diagrams of the comprehensive delineation of volcanic rock identification areas based on a volcanic rock velocity modeling and imaging method with iterative boundary correction; wherein, Figure 2(a) is a profile of a potential volcanic rock development area, Figure 2(b) is a seismic facies profile of two volcanic bodies (smaller on the left and larger on the right), and Figure 2(c) is a seismic facies profile of two volcanic bodies (larger on the left and smaller on the right). Figures 3(a)-(b) are schematic diagrams of boundary changes during one iteration of the velocity model using traditional grid tomography and the velocity model using the technology of this application; Figures 4(a)-(b) are schematic diagrams comparing the velocity scanning and imaging effects using the traditional grid tomography velocity model and the velocity model using the technology of this application. Detailed Implementation

[0021] The following are specific embodiments of this application, described in conjunction with the accompanying drawings, to further illustrate the technical solutions of this application. However, this application is not limited to these embodiments. Specific details, such as particular configurations, are provided in the following description merely to aid in a comprehensive understanding of the embodiments of this application. Therefore, those skilled in the art should understand that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application.

[0022] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0023] This embodiment provides a volcanic rock velocity modeling and imaging method based on iterative boundary correction, which is described in three stages, specifically including: Phase 1: Establishment of background velocity field and preliminary identification of volcanic rock target area.

[0024] S1. Initial Modeling and Migration: An initial pre-stack depth migration velocity model is established using conventional grid tomography inversion methods. This model is then used to perform pre-stack depth migration processing to obtain the initial depth migration data volume. Well logging data, vertical seismic profiles, and low-frequency velocity trends derived from the initial velocity model are comprehensively utilized within the work area.

[0025] S2. Preliminary multi-attribute identification: S2.1, Impedance Inversion Identification: Impedance inversion is performed on the depth-migrated data volume. Using the impedance characteristics of volcanic rocks, potential development areas of volcanic rocks (denoted as Region A) are initially delineated on the impedance volume. Details are as follows: Wave impedance inversion is performed on the depth migration data volume. This wave impedance inversion is a process of converting seismic reflection data, i.e., interface information, into subsurface rock wave impedance, i.e., formation properties. The formula for calculating wave impedance is: Z =ρ×Vp Where ρ is the formation density, Vp is the P-wave velocity, and Z is the wave impedance; Volcanic rocks typically exhibit significant acoustic impedance differences compared to surrounding rocks. Sparse pulse inversion and / or model-based iterative inversion are used to ultimately output an acoustic impedance data volume, in which each data point represents the acoustic impedance value of the formation.

[0026] Volcanic rock identification and extraction: Quantitatively extracting target geological information from the inversion results. The specific process is as follows: First, determine the wave impedance threshold: based on the logging data of wells that pass through known volcanic rocks in the work area, calculate the wave impedance value range of the volcanic rock section; at the same time, analyze the wave impedance value range of the surrounding rock.

[0027] Based on the distribution of the wave impedance values ​​of the volcanic rock section and the surrounding rock section, one or more wave impedance thresholds are determined to distinguish between volcanic rocks and surrounding rocks. By applying a defined wave impedance threshold, and through attribute extraction and / or 3D volume sculpting techniques, all continuous regions that are above or below (selected according to specific circumstances) the threshold are automatically extracted from the data volume, i.e., the initially delineated potential development areas of volcanic rocks. Observe the three-dimensional spatial morphology of the extracted potential volcanic rock development area. Volcanic rock bodies usually have one or more specific morphologies such as mound, plate, and puncture. Compare the boundary of the potential volcanic rock development area with the reflection characteristics on the seismic profile, eliminate areas whose geology does not conform to the characteristics of volcanic rocks, and determine the volcanic rock development area, namely area A. S2.2 Seismic facies feature identification: The depth migration data volume profile is overlaid with the initial pre-stack depth migration velocity model for display, and the region with typical seismic facies features of volcanic rocks is intelligently identified and denoted as region B; S2.3 Comprehensive Delineation of Initial Volcanic Rock Boundaries: The identification of potential volcanic rock development areas and typical volcanic rock seismic facies characteristic areas is achieved through spatial convergence and fusion (e.g., taking the intersection) to form the initial volcanic rock identification area and its boundary. initial .

[0028] The second stage, iterative boundary correction and optimal velocity determination, is an iterative optimization process that includes velocity scanning, offset imaging, and boundary reinterpretation. It aims to solve the coupling problem that "accurate imaging requires accurate velocity, while obtaining accurate velocity depends on accurate imaging boundaries".

[0029] S3. Velocity Filling and Scanning: Within the current volcanic rock identification area, the volcanic rock velocity scanning range [Vmin, Vmax] is determined based on prior information, and a series of velocity values ​​{V1, V2, ..., Vn} are set for filling to generate a series of candidate velocity models; where the prior information is...

[0030] S4. Migration Imaging and Feature Extraction: Pre-stack depth migration is performed using each candidate velocity model to obtain the corresponding candidate migration data volume {Image}. V1 Image V2 Image Vn}; For each candidate offset data volume Image Vi Then, impedance inversion and seismic phase interpretation were performed again to extract the volcanic boundary boundary at that velocity. IPVi and Boundary SesVi And by fusing them, the candidate volcanic rock boundary corresponding to this velocity is obtained. Vi .

[0031] S5. Joint Selection: Comparative analysis of all candidate velocity models (Image) Vi Boundary ViA joint selection process was conducted, with selection criteria including boundary reliability and underlying stratum imaging quality. Boundary reliability included whether the boundary sharpness met the standards and whether the geology was reasonable. Underlying stratum imaging quality included whether the phase axis was continuous and whether tectonic distortion was eliminated. The optimal velocity V corresponding to the candidate velocity model with the best imaging quality and the most reliable boundary features was selected. optimal and optimal volcanic rock boundary Boundary optimal .

[0032] S6. Iterative judgment: Boundary optimal Compare the boundary with the previous round. If the boundary changes significantly or the model needs optimization, then the boundary is changed. optimal As a new volcanic rock identification area, return to step S3 to start a new round of iteration. If the boundary is stable and the imaging is satisfactory, the iteration terminates.

[0033] Phase 3: Final model generation and imaging.

[0034] S7, finalize the V optimal Fill into Boundary optimal The defined region is then smoothly stitched together with the background velocity field to obtain a high-precision final velocity model.

[0035] S8. Use this final model to perform the final pre-stack depth migration to obtain high-quality imaging data volume.

[0036] Those skilled in the art to which this application pertains may make various modifications or additions to the specific embodiments described, or adopt similar methods to replace them, without departing from the inventive concept of this application or exceeding the scope defined by the appended claims.

Claims

1. A method for modeling and imaging volcanic rock velocity based on iterative boundary correction, comprising the following steps: Step 1: Establish the background velocity field and preliminarily identify the volcanic rock target area and its boundaries; Step 2: Perform iterative boundary correction and determine the optimal speed. This step includes: Based on the prior knowledge of volcanic rock velocities obtained from drilling in the study area and / or adjacent exploration areas, the volcanic rock velocity scanning range is determined, and a series of velocity values ​​are set for filling to generate candidate velocity models. For each candidate velocity model, migration imaging and feature extraction are performed. Pre-stack depth migration is then performed using each candidate velocity model to obtain candidate migration data volumes. Wave impedance inversion and seismic facies interpretation are then performed on each candidate migration data volume to obtain the corresponding candidate volcanic rock boundaries. The optimal velocity and optimal volcanic rock boundary of the candidate velocity model with the best imaging quality and the most reliable boundary features are obtained through joint selection; and iterative judgment is performed, comparing the current optimal boundary with the boundary of the previous round. If the boundary changes significantly, the current optimal boundary is taken as the new volcanic rock identification area, and the velocity filling and scanning steps are returned. If the boundary is stable and the imaging is satisfactory, the iteration terminates. Step 3: Generate the final velocity model and perform imaging; Step one includes the following process: An initial pre-stack depth migration velocity model was established using the grid tomography inversion method, and pre-stack depth migration processing was carried out using the pre-stack depth migration velocity model to obtain the initial depth migration data volume. Well logging, vertical seismic profiles and low-frequency velocity trends derived from the initial velocity model were comprehensively utilized in the work area. Impedance inversion is performed on the depth migration data volume. This impedance inversion is a process of converting seismic reflection data into subsurface rock impedance, i.e., formation properties. The formula for calculating impedance is: Z =ρ×Vp Where ρ is the formation density, Vp is the P-wave velocity, and Z is the wave impedance; The sparse pulse inversion and / or model-based iterative inversion are used to finally output a wave impedance data volume, in which each data point represents the wave impedance value of the formation. Volcanic rock identification and extraction: quantitatively extracting target geological information from inversion results; Step three includes: The final determined optimal velocity is filled into the region delineated by the optimal volcanic rock boundary and smoothly stitched with the regional background velocity field to obtain a high-precision final velocity model. The final model is then used for pre-stack depth migration to obtain a high-quality imaging data volume.

2. The volcanic rock velocity modeling and imaging method based on iterative boundary correction according to claim 1, characterized in that, The process of quantitatively extracting target geological information from the inversion results includes: Based on the logging data of wells that pass through known volcanic rocks in the work area, the range of wave impedance values ​​of the volcanic rock section and the range of wave impedance values ​​of the surrounding rock were statistically determined. Based on the distribution of the wave impedance values ​​of the volcanic rock section and the surrounding rock section, one or more wave impedance thresholds are determined to distinguish between volcanic rocks and surrounding rocks. By applying a determined wave impedance threshold, continuous regions are automatically extracted from the data volume through attribute extraction and / or 3D volume sculpting techniques, and potential development areas of volcanic rocks are preliminarily delineated. By comparing the boundary of the potential volcanic rock development area with the reflection characteristics on the seismic profile, areas that do not conform to the geological characteristics of volcanic rocks are eliminated, and the volcanic rock development area is determined. The depth migration data volume profile is overlaid with the initial pre-stack depth migration velocity model for display, and areas with typical seismic facies characteristics of volcanic rocks are intelligently identified. The identification of potential volcanic rock development areas and typical volcanic rock seismic facies characteristic areas is achieved through spatial convergence and fusion to form an initial volcanic rock identification area and its boundary.

3. The volcanic rock velocity modeling and imaging method based on iterative boundary correction according to claim 1, characterized in that, The prior information refers to the experience gained from drilling in the study area and / or adjacent exploration areas regarding volcanic rock velocities.

4. The volcanic rock velocity modeling and imaging method based on iterative boundary correction according to claim 1, characterized in that, In step two, the boundary obtained by the volume wave impedance inversion of each candidate migration data is fused with the boundary obtained by the seismic phase interpretation to obtain the candidate volcanic rock boundary.

5. The volcanic rock velocity modeling and imaging method based on iterative boundary correction according to claim 1, characterized in that, The criteria for joint selection in step two include: Boundary reliability, including boundary clarity and geological plausibility; Imaging quality of underlying strata, including the continuity of phase axes and the degree of tectonic distortion correction.

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