Method, device and computer readable storage medium for establishing a velocity model

Abstract

The present disclosure relates to the technical field of velocity model establishment, in particular to a velocity model establishment method, device and computer readable storage medium, which combines seismic data and logging data to determine reflection travel time, ray path and observed travel time, updates the second depth domain velocity model based on the reflection travel time, the ray path and the observed travel time, obtains a target depth domain velocity model, and can establish a more accurate velocity model.

Description

Technical Field

[0001] This disclosure relates to the field of velocity model building technology, and particularly to a method, apparatus and computer-readable storage medium for building a velocity model. Background Technology

[0002] As oil exploration targets become increasingly complex and concealed, pre-stack depth migration is being applied more and more frequently in production. Pre-stack depth migration can achieve high-precision seismic imaging of complex subsurface structures, accurately reflecting subsurface structures in areas with complex structures and dramatic lateral velocity variations. However, establishing an accurate velocity model is crucial for pre-stack migration imaging. The correctness or accuracy of the velocity model directly affects the success or failure of the imaging process. Summary of the Invention

[0003] This disclosure provides a method, apparatus, and computer-readable storage medium for establishing a speed model, which can establish a relatively accurate speed model.

[0004] Firstly, this disclosure provides a method for establishing a velocity model, including:

[0005] Acquire seismic and well logging data for the target area; determine the time-domain stratigraphic interpretation results and root mean square velocity model for the target area based on the seismic data; calibrate the time-domain stratigraphic interpretation results at the well location based on the well logging data to obtain the average well logging velocity at the well location;

[0006] Based on the well logging average velocity and the root mean square velocity model, a seismic average velocity model for the target area is determined; based on the seismic average velocity model, depth domain stratigraphic interpretation results are determined; based on the depth domain stratigraphic interpretation results and the time domain stratigraphic interpretation results, a first depth domain velocity model is determined; and based on the depth domain stratigraphic interpretation results, the local dip field of the depth domain stratigraphic layers is determined.

[0007] The observation travel time of each reflection point on the depth domain layer is determined based on the time of the time domain layer corresponding to the depth domain layer and the shot-receiver relationship on the corresponding CMP gather. The reflection travel time and ray path of each reflection point are determined based on the first depth domain velocity model, the depth domain layer and the local dip field corresponding to the depth domain layer. The first depth domain velocity model is updated based on the observation travel time to obtain the second depth domain velocity model.

[0008] The second depth domain velocity model is updated based on the reflection travel time, the ray path, and the observation travel time to obtain the target depth domain velocity model.

[0009] In some embodiments, determining the seismic average velocity model of the target area based on the well logging average velocity and the root mean square velocity model includes:

[0010] Using the well logging average velocity as the first variable and the root mean square velocity as the second variable, co-kriging interpolation is performed to obtain the seismic average velocity model of the target area.

[0011] In some embodiments, determining the depth domain horizon interpretation results based on the seismic mean velocity model includes:

[0012] The updated time-domain torsional interpretation results are determined based on the aforementioned seismic mean velocity model;

[0013] The updated temporal-domain hierarchical interpretation results are converted to the depth domain to obtain the depth-domain hierarchical interpretation results.

[0014] In some embodiments, determining the observation travel time of each reflection point on the depth-domain horizon based on the time of the time-domain horizon corresponding to the depth-domain horizon and the shot-receiver relationship on the corresponding CMP gather includes:

[0015] Determine the time of the time domain layer corresponding to each grid point in each depth domain layer;

[0016] Extract the shot and receiver positions on each CMP gather corresponding to each grid point;

[0017] The travel time of each CMP gather is calculated based on the shot and receiver positions on each CMP gather and the time corresponding to each grid point.

[0018] The travel time of each CMP gather is determined as the observation travel time of each reflection point on the depth domain layer.

[0019] In some embodiments, determining the reflection travel time and ray path of each reflection point based on the first depth domain velocity model, the depth domain layer, and the local dip field corresponding to the depth domain layer includes:

[0020] Based on the depth domain velocity model, depth domain layer, local dip field corresponding to the depth domain layer, and shot-receiver relationship in the CMP gather of each reflection point, ray tracing is performed from each reflection point toward the ground to determine the reflection travel time and ray path of each reflection point.

[0021] In some embodiments, updating the second depth domain velocity model based on the reflection travel time, the ray path, and the observation travel time to obtain a target depth domain velocity model includes:

[0022] Based on the reflection travel time, the ray path, and the observation travel time, a set of tomographic inversion equations is constructed, wherein the set of inversion equations includes velocity update and reflection interface depth update.

[0023] The velocity update and the reflection interface depth update are determined based on the tomographic inversion equations.

[0024] The second depth domain velocity model is updated based on the velocity update amount and the reflection interface depth update amount to obtain the target depth domain velocity model.

[0025] In some embodiments, determining the velocity update and the reflection interface depth update based on the tomographic inversion equations includes:

[0026] The tomographic inversion equation is solved using the conjugate gradient method or the least square matrix decomposition method to obtain the velocity update and the reflection interface depth update.

[0027] Secondly, this disclosure provides an apparatus for establishing a velocity model, comprising:

[0028] The acquisition module is used to acquire seismic data and well logging data of the target area; determine the time-domain stratigraphic interpretation results and root mean square velocity model of the target area based on the seismic data; and calibrate the time-domain stratigraphic interpretation results at the well location based on the well logging data to obtain the average well logging velocity at the well location.

[0029] The first determining module is used to determine the seismic mean velocity model of the target area based on the well logging mean velocity and the root mean square velocity model; determine the depth domain stratigraphic interpretation result based on the seismic mean velocity model; determine the first depth domain velocity model based on the depth domain stratigraphic interpretation result and the time domain stratigraphic interpretation result; and determine the local dip field of the depth domain stratigraphic layer based on the depth domain stratigraphic interpretation result.

[0030] The second determining module is used to determine the observation travel time of each reflection point on the depth domain layer based on the time of the time domain layer corresponding to the depth domain layer and the shot-receiver relationship on the corresponding CMP gather, determine the reflection travel time and ray path of each reflection point based on the first depth domain velocity model, the depth domain layer and the local dip field corresponding to the depth domain layer, and update the first depth domain velocity model based on the observation travel time to obtain the second depth domain velocity model.

[0031] The module is used to update the second depth domain velocity model based on the reflection travel time, the ray path, and the observation travel time to obtain the target depth domain velocity model.

[0032] Thirdly, this disclosure provides a computer device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the foregoing aspects.

[0033] Fourthly, this disclosure provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the methods described in the above aspects.

[0034] Fifthly, this disclosure provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the methods described in the foregoing aspects.

[0035] This disclosure provides a method for establishing a velocity model, which involves acquiring seismic data and well logging data for a target area; determining time-domain stratigraphic interpretation results and a root-mean-square (RMS) velocity model for the target area based on the seismic data; calibrating the time-domain stratigraphic interpretation results at the well location based on the well logging data to obtain the well logging average velocity at the well location; determining a seismic average velocity model for the target area based on the well logging average velocity and the RMS velocity model; determining depth-domain stratigraphic interpretation results based on the seismic average velocity model; determining a first depth-domain velocity model based on the depth-domain stratigraphic interpretation results and the time-domain stratigraphic interpretation results; and determining a first depth-domain velocity model based on the depth-domain stratigraphic interpretation results. The interpretation results determine the local dip field of the depth domain layer; based on the time of the time domain layer corresponding to the depth domain layer and the shot-receiver relationship on the corresponding CMP gather, the observation travel time of each reflection point on the depth domain layer is determined; based on the first depth domain velocity model, the depth domain layer, and the local dip field corresponding to the depth domain layer, the reflection travel time and ray path of each reflection point are determined, and the first depth domain velocity model is updated based on the observation travel time to obtain the second depth domain velocity model; based on the reflection travel time, the ray path, and the observation travel time, the second depth domain velocity model is updated to obtain the target depth domain velocity model, which can establish a relatively accurate velocity model. Attached Figure Description

[0036] The present disclosure will be described in more detail below based on embodiments and with reference to the accompanying drawings:

[0037] Figure 1 This is a flowchart illustrating a method for establishing a velocity model according to an embodiment of the present disclosure.

[0038] Figure 2 A schematic diagram illustrating the implementation process of a speed model establishment method provided for the implementation of this application;

[0039] Figure 3 This is a schematic diagram of a velocity model building device provided in an embodiment of this application.

[0040] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation

[0041] To enable those skilled in the art to better understand the technical solutions of this disclosure, and to fully understand and implement the process of how this disclosure applies technical means to solve technical problems and achieve corresponding technical effects, the technical solutions in 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 embodiments of this disclosure, not all embodiments. The embodiments of this disclosure and the various features within them can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort should fall within the protection scope of this disclosure.

[0042] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0043] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0044] Before introducing the embodiments of this application, a brief introduction to related technologies is provided. Velocity can be obtained from well logging data, core measurement data, and seismic data. Velocity acquisition from seismic data is generally referred to as velocity analysis, which includes stacking velocity analysis, migration velocity analysis, layer velocity analysis, and tomographic inversion. As their names suggest, different velocity analysis methods yield different velocities, and their underlying principles, required data, velocity properties, and applications also differ. Stacking velocity analysis uses CMP gathers as input and obtains the time-domain velocity that best achieves the stacking effect. Migration velocity analysis, depending on its migration algorithm, can use different input data, such as common shot datasets and common offset datasets, and the obtained velocity model can be a time-domain velocity (pre-stack time migration) or a depth-domain velocity model (pre-stack depth migration). Layer velocity analysis generally requires CMP gathers and reflection interfaces as input, obtaining a depth-domain layer velocity model. Tomographic inversion can obtain a depth-domain velocity model using reflection travel time (reflection tomography), or it can simultaneously use travel time and amplitude information to perform waveform inversion to obtain a depth-domain velocity model. Among these methods, stacking velocity analysis is relatively simple and efficient, and therefore the most widely used. However, its accuracy is relatively low, and it only yields velocities in the time domain. Migration velocity analysis produces velocity models with higher accuracy than those obtained from stacking velocity analysis, making it more suitable for complex geological conditions.

[0045] Early velocity models were constructed by performing velocity analysis through stacking or pre-stack time migration to obtain root-mean-square velocities. These velocities were then converted into layer velocities using the DIX formula. The initial model velocity volume was obtained through DIX constraint inversion, and tomography was used to interactively extract remaining velocities for model optimization. However, stacking velocity analysis is no longer suitable for complex geological conditions such as lateral velocity variations and stratigraphic dips, and therefore cannot meet the required accuracy for velocity analysis.

[0046] Therefore, based on the initial velocity model provided by the above method, residual velocity analysis is performed using the sensitivity of pre-stack depth migration to migration velocity errors. The initial residual velocity analysis involves creating a gamma spectrum, followed by manual gamma spectrum picking and interpretation, similar to stacking velocity analysis. On one hand, gamma spectrum picking and interpretation requires excessive manual operation, making it tedious and time-consuming. On the other hand, creating the gamma spectrum utilizes common imaging point gathers at each grid point (X,Y), similar to CMP gathers in stacking velocity analysis. This method operates on a single-point basis and cannot adequately account for the influence of velocities at other points in the velocity model on the current point. Tomographic inversion allows for global adjustment of the velocity model. Tomography was first applied in medicine and later in geophysics, but it primarily applies to transmitted waves. Mathematically, tomographic inversion involves solving a system of linear equations: L·ΔS=Δt. Here, L is a matrix whose elements represent the length of a ray in the grid, ΔS represents the change in slowness within each grid (slowness is the reciprocal of velocity), and Δt is the observed travel time T. obs With calculation of travel time T cal The difference. Among them, T cal This is calculated using the initial velocity model. Although the tomographic inversion method is relatively mature, in practical applications, it is necessary to extract T from seismic observation data. obs In calculating T cal In addition to the initial velocity model, the locations of the excitation and receiving points are also required. This is because, in transmitted waves or first-arrival tomography, the T value is picked up... obsRelatively simple, tomographic inversion methods are mainly applied to transmission wave tomography and first-arrival tomography in seismic exploration. However, for surface seismic exploration, which relies primarily on reflected waves as the effective signal, the target needs to be explored in the middle and deep layers. First-arrival tomography can only obtain the surface velocity model, while transmission wave tomography has high requirements for the number and spacing of wells. Therefore, these two tomographic inversion methods cannot be applied to the establishment of velocity models in the middle and deep layers of seismic exploration. Reflection wave tomography utilizes reflected wave information from the middle and deep layers, and therefore can be used to establish velocity models in the middle and deep layers. Traditional reflection wave tomography, like first-arrival tomography and transmission wave tomography, requires travel time information. However, in practical industrial applications, the problem of quickly and accurately picking up the travel time of first-arrival and transmission waves has been successfully solved, while quickly and accurately picking up the travel time of reflected waves is very difficult. Therefore, reflection wave tomography has not been as widely used as first-arrival and transmission wave tomography. Unlike traditional data domain reflection wave tomography, tomographic migration velocity analysis uses data from common imaging point gathers generated by pre-stack depth migration, thus making reflected waves more clearly visible. Furthermore, the velocity model used in pre-stack depth migration can serve as the initial velocity model for tomographic inversion, thus making the inversion more stable. Pre-stack depth migration can also generate depth-domain seismic profiles, making reflection point picking relatively easy. Moreover, tomographic migration velocity analysis can utilize well-established inversion algorithms in tomographic inversion. After comprehensively considering factors such as implementation difficulty, computational complexity, and application effectiveness, tomographic migration velocity analysis has begun to be widely adopted in industry. However, tomographic migration velocity analysis is based on imaging gathers provided by pre-stack depth migration, and the quality of these imaging gathers depends on the initial depth-domain velocity model; therefore, the construction of the initial depth-domain velocity model remains crucial.

[0047] Example 1

[0048] To address the problems in related technologies, embodiments of this application provide a method for establishing a velocity model. Figure 1 This is a flowchart illustrating a method for establishing a velocity model according to an embodiment of this disclosure. Figure 1 As shown, the method for establishing the velocity model includes:

[0049] Step S101: Obtain seismic data and well logging data for the target area; determine the time-domain stratigraphic interpretation results and root mean square velocity model for the target area based on the seismic data; calibrate the time-domain stratigraphic interpretation results at the well location based on the well logging data to obtain the average well logging velocity at the well location.

[0050] In this embodiment, the target area can be the study area. Seismic data is obtained through seismic exploration technology, mainly including signals that are generated by seismic waves on the surface or seabed, propagate through the subsurface medium, and are received by a receiver. This data is used to infer the subsurface geological structure. Well logging data is data directly measured in the well using well logging techniques (such as sonic logging, resistivity logging, etc.). Well logging data provides detailed physical property information of the strata surrounding the well, such as velocity, density, and resistivity.

[0051] In this embodiment, the time-domain stratigraphic interpretation result refers to the location of subsurface reflection layers in the time domain (i.e., the time axis of the seismic record), obtained based on the interpretation of seismic data. These layers typically represent reflections from different geological interfaces. The root-mean-square velocity model is a model of the propagation velocity of seismic waves underground, expressed as root-mean-square velocity. It is a commonly used velocity representation in seismic data processing, used to convert time-domain data into depth-domain data. The average velocity of the formation at the well location, obtained based on well logging data, is used to calibrate and verify the interpretation results of the seismic data.

[0052] In this embodiment of the application, determining the seismic mean velocity model of the target area based on the well logging average velocity and the root mean square velocity model includes: performing co-location co-kriging interpolation with the well logging average velocity as a first variable and the root mean square velocity as a second variable to obtain the seismic mean velocity model of the target area.

[0053] In this embodiment, co-kriging is a geostatistical method that utilizes the spatial correlation between two or more related variables to improve the interpolation results of a single variable. Well logging mean velocity (as the first variable) and root mean square velocity (as the second variable) are used for co-kriging to obtain a seismic mean velocity model for the target area.

[0054] Step S102: Determine the seismic mean velocity model of the target area based on the well logging mean velocity and the root mean square velocity model; determine the depth domain stratigraphic interpretation results based on the seismic mean velocity model; determine the first depth domain velocity model based on the depth domain stratigraphic interpretation results and the time domain stratigraphic interpretation results; and determine the local dip field of the depth domain stratigraphic layers based on the depth domain stratigraphic interpretation results.

[0055] In this embodiment, the seismic mean velocity model is a combination of well logging mean velocity and root mean square velocity models, resulting in the seismic mean velocity distribution across the entire target area. The time-domain stratigraphic interpretation results are converted into locations in the depth domain (i.e., the actual subsurface depth), providing a more intuitive reflection of the subsurface geological structure. The first depth-domain velocity model is a preliminary velocity model established based on the depth-domain stratigraphic interpretation results, used for subsequent velocity analysis and updates. The dip field describes the field of local dip angles of subsurface strata.

[0056] In this embodiment of the application, determining the depth domain stratigraphic interpretation result based on the seismic mean velocity model includes: determining an updated time domain stratigraphic interpretation result based on the seismic mean velocity model; and converting the updated time domain stratigraphic interpretation result to the depth domain to obtain the depth domain stratigraphic interpretation result.

[0057] In this embodiment, the seismic mean velocity model provides velocity distribution information of the subsurface medium, which can be used to correct and update time-domain stratigraphic interpretation results. The inverse process of depth transformation of time-domain stratigraphic layers using the seismic mean velocity model (i.e., the inverse operation of time-depth transformation) can be used to obtain more accurate stratigraphic locations within the time domain. This typically involves iterative adjustments to the velocity model to better match the time-domain stratigraphic layers with the seismic data. Once more accurate time-domain stratigraphic interpretation results are obtained, these layers can be transformed from the time domain to the depth domain using the seismic mean velocity model. This transformation is typically achieved by multiplying each point on the time-domain stratigraphic layer by the velocity at that point's location (obtained from the seismic mean velocity model). Since velocity typically varies with depth, this transformation needs to account for this velocity variation. After the transformation, the layers originally represented in the time domain become layers represented in the depth domain, which more intuitively reflect the actual depth of the subsurface geological structure.

[0058] In this embodiment of the application, the first depth domain velocity model is determined based on the depth domain layer interpretation results and the time domain layer interpretation results, and can be expressed by the following formula:

[0059]

[0060] Among them, T ow This represents a one-way trip, where x and y are coordinates and i is the depth. ow (x, y, i)-T ow (x, y, i-1) represents the time between layers, and D(x, y, i)-D(x, y, i-1) represents the depth.

[0061] In this embodiment of the application, the local dip field of the updated depth domain horizon can be calculated from the updated depth domain interpretation horizon: φ x (x,y,z), φ y (x,y,z).

[0062] Step S103: Based on the time of the time domain layer corresponding to the depth domain layer and the shot-receiver relationship on the corresponding CMP gather, determine the observation travel time of each reflection point on the depth domain layer; based on the first depth domain velocity model, the depth domain layer and the local dip field corresponding to the depth domain layer, determine the reflection travel time and ray path of each reflection point; and update the first depth domain velocity model based on the observation travel time to obtain the second depth domain velocity model.

[0063] In this embodiment, the CMP gather is a common center point gather, a data organization format used in seismic data processing to analyze the propagation characteristics and velocity variations of seismic waves. Observational travel time is the actual time it takes for a seismic wave to travel from the source to the receiver, while reflection travel time is the theoretical propagation time calculated based on the velocity model and geometric path. The ray path is the path of seismic wave propagation underground, typically calculated using ray tracing methods. The second depth domain velocity model is a velocity model obtained by updating the first depth domain velocity model based on the matching of observational and reflection travel times.

[0064] In this embodiment of the application, the step of determining the observation travel time of each reflection point on the depth domain layer based on the time of the time domain layer corresponding to the depth domain layer and the shot-receiver relationship on the corresponding CMP gather includes: determining the time of the time domain layer corresponding to each grid point in each depth domain layer; extracting the shot-receiver position on each CMP gather corresponding to each grid point; calculating the travel time of each CMP gather based on the shot-receiver position on each CMP gather and the time corresponding to each grid point; and determining the travel time of each CMP gather as the observation travel time of each reflection point on the depth domain layer.

[0065] In this embodiment, the time of the time-domain interpretation layer corresponding to the depth-domain layer can be denoted as T0(x,y). The shot-receiver position of each trace in the CMP gather corresponding to each grid point (x,y) is extracted. The travel time on each CMP gather is then calculated according to the following formula, and this travel time is taken as the observation travel time T at the reflection point R(x,y,z) in the depth-domain layer. obs :

[0066]

[0067] Where h is half the distance between the gun and receiver, i.e., the half offset distance.

[0068] In some embodiments, this formula represents the reflection travel time T for a reflection point with a half offset of h on a CMP gather. obs The relationship between h and T is hyperbolic, therefore T can be obtained without picking up this reflection during travel. obs That is, T obs=T(h). However, in more practical situations, when the surface or reflecting interface is not horizontal, or when the layer velocity of a certain overlying stratum has a relatively large lateral variation, or when the layer velocity of a certain overlying stratum exhibits azimuthal anisotropy, or when dynamic correction stretching occurs due to excessive offset, the reflection travel time T of a reflecting point at an upper half offset of h in the CMP gather is... obs The relationship with h is no longer hyperbolic. At this point, the hyperbolic relationship described above can be used to perform NMO correction on the CMP gather to obtain the NMO-corrected CMP gather. Then, on the corrected CMP gather, a window of duration t is opened centered at T0(x,y) of each reflection point. Next, following the order of increasing offset, the trace data of each trace in the corrected CMP gather with duration t and starting times from T0(x,y)-t to T0(x,y)+t are cross-correlated with the trace of duration t centered at T0(x,y) with the smallest offset in the CMP gather (or the superposition energy is calculated). Then, the time shift g (i.e., the cross-correlation criterion or superposition energy criterion) when the cross-correlation value or superposition energy is maximum during the scanning process is recorded. Then T... obs =T0(x,y)+γ+△T NMO .

[0069] In this embodiment of the application, determining the reflection travel time and ray path of each reflection point based on the first depth domain velocity model, the depth domain layer, and the local dip field corresponding to the depth domain layer includes: performing ray tracing from each reflection point to the ground according to the depth domain velocity model, the depth domain layer, the local dip field corresponding to the depth domain layer, and the shot-receiver relationship in the CMP gather of each reflection point, to determine the reflection travel time and ray path of each reflection point.

[0070] In this embodiment, the normal direction of the reflection interface at the reflection point can be obtained from each reflection point R(x,y,z) and the local dip field φ(x,y,z) of the corresponding depth offset profile. Then, starting from the reflection point, ray tracing is performed on both sides of the normal at the same angle θ. The emission points of these two rays on the ground are recorded as the excitation point and the receiver point, respectively. Ray pairs whose distances from the shot receiver point to the shot receiver point are less than a certain threshold are selected as effective rays. Thus, the travel time and ray path of each trace on the CMP gather at each reflection point are calculated, forming the ray path L of the current reflection point and the calculated travel time T. cal During this process, with the initial layer velocity of the current layer's depth domain as the center, and using a Markov chain Monte Carlo (MCMC) random walk method, the ray path L and travel time T are calculated again in the manner described above. cal .

[0071] In this embodiment of the application, the first depth domain velocity model can be updated based on the observed travel time to obtain the second depth domain velocity model, which can be obtained through the obtained T obs The closest T cal And the current layer velocity, which serves as the new layer velocity for the current layer.

[0072] Step S104: Update the second depth domain velocity model based on the reflection travel time, the ray path, and the observation travel time to obtain the target depth domain velocity model.

[0073] In this embodiment of the application, a tomographic inversion equation set can be constructed based on the reflection travel time, the ray path, and the observation travel time, wherein the inversion equation set includes a velocity update and a reflection interface depth update; the velocity update and the reflection interface depth update are determined based on the tomographic inversion equation set; the second depth domain velocity model is updated based on the velocity update and the reflection interface depth update to obtain the target depth domain velocity model.

[0074] In this embodiment of the application, the tomographic inversion equations can be expressed as:

[0075] △T=T obs -T cal =△S·L+(cosθ) r +cosθ s )·S·△Z;

[0076] Where S is the reciprocal of the layer velocity, derived from the initial layer velocity model; θ s and θ r These are the angles between the ray reaching the gun receiver and the normal to the reflecting interface.

[0077] In this embodiment, solving the above equations yields the velocity update ΔS and the reflection interface depth update ΔZ, thereby updating the initial velocity model. There are many methods for solving the equations, such as the conjugate gradient method and the least squares QR decomposition method.

[0078] This disclosure provides a method for establishing a velocity model, which involves acquiring seismic data and well logging data for a target area; determining time-domain stratigraphic interpretation results and a root-mean-square (RMS) velocity model for the target area based on the seismic data; calibrating the time-domain stratigraphic interpretation results at the well location based on the well logging data to obtain the well logging average velocity at the well location; determining a seismic average velocity model for the target area based on the well logging average velocity and the RMS velocity model; determining depth-domain stratigraphic interpretation results based on the seismic average velocity model; determining a first depth-domain velocity model based on the depth-domain stratigraphic interpretation results and the time-domain stratigraphic interpretation results; and determining a first depth-domain velocity model based on the depth-domain stratigraphic interpretation results. The interpretation results determine the local dip field of the depth domain layer; based on the time of the time domain layer corresponding to the depth domain layer and the shot-receiver relationship on the corresponding CMP gather, the observation travel time of each reflection point on the depth domain layer is determined; based on the first depth domain velocity model, the depth domain layer, and the local dip field corresponding to the depth domain layer, the reflection travel time and ray path of each reflection point are determined, and the first depth domain velocity model is updated based on the observation travel time to obtain the second depth domain velocity model; based on the reflection travel time, the ray path, and the observation travel time, the second depth domain velocity model is updated to obtain the target depth domain velocity model, which can establish a relatively accurate velocity model.

[0079] Example 2

[0080] Based on the above embodiments, this application further provides a method for establishing a velocity model, which integrates seismic data and well logging data, and utilizes seismic tectonic interpretation results without the need for reflection point picking. The method automatically picks the travel time T of the reflected wave through a software program. obs This enables a layer-by-layer tomography velocity modeling based on automatic picking.

[0081] The method for establishing a velocity model provided in this application specifically includes:

[0082] (1) Perform conventional processing (pre-stack time migration PSTM or stacking) on ​​the raw ground seismic data collected in the field to obtain the root mean square velocity model and the processed seismic data (PSTM or stacking data volume and CMP gather). At the same time, perform fine time-domain structural interpretation based on PSTM or stacking data volume to obtain time-domain structural (layer) interpretation results.

[0083] (2) Under the above time-domain layer constraints, the time-domain layer velocity model is obtained from the root mean square velocity using the DIX formula:

[0084]

[0085] Where the planar position or coordinates of the grid points are (x, y), V int V represents the velocity in the time domain.rms T represents the root mean square velocity, and T represents the travel time.

[0086] Assuming the processing reference plane depth is D0 = D(x,y,0), then based on the time-domain layer velocity and the interpretation layer time mentioned above, the time-domain interpretation layer can be converted to the depth domain layer by layer using the following formula:

[0087]

[0088] Where T ow When indicating a one-way trip;

[0089] Furthermore, the initial earthquake mean velocity model is calculated by interpreting the time and depth of the layers in the time domain:

[0090]

[0091] The initial depth domain layer velocity model can be calculated from the time and depth between layers:

[0092]

[0093] (3) Using well logging data and its stratigraphic interpretation results, the time-domain stratigraphic interpretation results at the well location are calibrated through well-seismic calibration, and the average logging velocity V at the well location is obtained. ave_well .

[0094] (4) Using the well logging average velocity at the well location as the first variable and the seismic root mean square velocity as the second variable, co-location kriging interpolation is performed to obtain the seismic average velocity at all grid points.

[0095] (5) Use the above-mentioned earthquake mean velocity model to convert the time domain interpretation horizon to the depth domain to obtain the updated depth domain interpretation horizon, and calculate the updated depth domain layer velocity model from the updated depth domain horizon and the original time domain interpretation horizon.

[0096] (6) Calculate the local dip field of the updated depth domain horizon from the updated depth domain interpretation horizon: φ x (x,y,z), φ y (x,y,z).

[0097] (7) The time of the time domain interpretation layer corresponding to the depth domain layer is denoted as T0(x,y). The shot-receiver position of each trace in the CMP gather corresponding to each grid point (x,y) is extracted. The travel time on each CMP gather is calculated according to the following formula, and this travel time is taken as the observation travel time T at the reflection point R(x,y,z) in the depth domain layer. obs :

[0098]

[0099] Where h is half the distance between the gun and receiver, i.e., half the offset distance;

[0100] This formula shows the reflection travel time T for a reflection point with a half offset of h on a CMP gather. obs The relationship between h and T is hyperbolic, therefore T can be obtained without picking up this reflection during travel. obs That is, T obs =T(h). However, in more practical situations, when the surface or reflecting interface is not horizontal, or when the layer velocity of a certain overlying stratum has a relatively large lateral variation, or when the layer velocity of a certain overlying stratum exhibits azimuthal anisotropy, or when dynamic correction stretching occurs due to excessive offset, the reflection travel time T of a reflecting point at an upper half offset of h in the CMP gather is... obs The relationship with h is no longer hyperbolic. At this point, the hyperbolic relationship described above can be used to perform NMO correction on the CMP gather to obtain the NMO-corrected CMP gather. Then, on the corrected CMP gather, a window of duration t is opened centered at T0(x,y) of each reflection point. Next, following the order of increasing offset, the trace data of each trace in the corrected CMP gather with duration t and starting times from T0(x,y)-t to T0(x,y)+t are cross-correlated with the trace of duration t centered at T0(x,y) with the smallest offset in the CMP gather (or the superposition energy is calculated). Then, the time shift g (i.e., the cross-correlation criterion or superposition energy criterion) when the cross-correlation value or superposition energy is maximum during the scanning process is recorded. Then T... obs =T0(x,y)+γ+△T NMO .

[0101] (8) For each reflection point R(x,y,z) in step (7), ray tracing is performed from the reflection point to the ground based on the updated depth domain horizon and dip angle and depth domain layer velocity model, according to the shot-receiver relationship in the CMP gather of each reflection point. First, the normal direction of the reflection interface at the reflection point is obtained from each reflection point R(x,y,z) and the local dip angle field φ(x,y,z) of the corresponding depth offset profile. Then, ray tracing is performed on both sides of the normal at the same angle θ as the normal. The emission points of these two rays on the ground are recorded as the excitation point and the receiver point, respectively. Ray pairs with a distance of less than a certain threshold between the excitation point and the receiver point and the shot-receiver point are selected as effective rays. Thus, the travel time and ray path of each trace on the CMP gather of each reflection point are calculated to form the ray path L of the current reflection point and the calculated travel time T. calDuring this process, with the initial layer velocity of the current layer's depth domain as the center, and using a Markov chain Monte Carlo (MCMC) random walk method, the ray path L and travel time T are calculated again in the manner described above. cal Choose the T obtained in step (7) obs The closest T cal And the current layer velocity, as the new layer velocity for the current layer; in this way, a new depth domain layer velocity model is obtained, along with the corresponding ray path L and the calculated travel time T. cal As the initial velocity model for the next step of tomographic inversion;

[0102] (9) Construct a set of tomographic inversion equations based on the above calculation results:

[0103] △T=T obs -T cal =△S·L+(cosθ) r +cosθ s )·S·△Z;

[0104] Where S is the reciprocal of the layer velocity, derived from the initial layer velocity model; θ s and θ r These are the angles between the ray reaching the gun receiver and the normal to the reflecting interface;

[0105] Solving the above system of equations yields the updated velocity ΔS and the updated reflection interface depth ΔZ, thus updating the initial velocity model. There are many methods for solving the system of equations, such as the conjugate gradient method and the least squares QR decomposition method.

[0106] Through the above steps, the depth domain velocity model can be finally obtained by layer-by-layer inversion. It can be used as the initial velocity model for pre-stack depth migration. However, during the tomographic inversion process, it is not necessary to pick up the reflection interface or the reflection travel time on the pre-stack gather.

[0107] Example 3

[0108] Based on the above embodiments, this application further provides a method for establishing a velocity model. Figure 2 This application provides a schematic diagram illustrating the implementation process of a method for establishing a velocity model, as shown in the embodiment. Figure 2The process includes: performing routine processing on raw surface seismic data acquired in the field to obtain a root mean square velocity model, processed seismic data, and structural interpretation data; using well logging data and well logging horizon interpretation results, calibrating the time-domain horizon interpretation results at the well location through well-seismic calibration, and simultaneously obtaining the well logging average velocity at the well location; using the well logging average velocity at the well location as the first variable and the seismic root mean square velocity as the second variable, performing co-kriging interpolation to obtain the seismic average velocity at all grid points; and using the seismic average velocity model to transform the seismic horizon interpretation results to the depth domain to obtain... The depth domain horizon and initial velocity model are calculated, along with the dip field of the depth domain horizon. Ray tracing is performed using the depth domain horizon, its dip field, and the initial velocity model to calculate the reflection travel time and ray path of each trace on the CMP gather. Simultaneously, the observation travel time on the CMP gather is calculated using the grid points on the time-domain seismic interpretation horizon and the corresponding shot-receiver relationship on the CMP gather, based on the root mean square velocity model. From the observation travel time, the calculated travel time, and the ray path, a tomographic equation set is established, tomographic inversion is performed, the update amount of the velocity model is obtained, and the velocity model is updated.

[0109] Example 4

[0110] This application provides an apparatus for establishing a velocity model. Figure 3 This is a schematic diagram of a velocity model building device provided in an embodiment of this application, as shown below. Figure 3 As shown, it includes:

[0111] The acquisition module is used to acquire seismic data and well logging data of the target area; determine the time-domain stratigraphic interpretation results and root mean square velocity model of the target area based on the seismic data; and calibrate the time-domain stratigraphic interpretation results at the well location based on the well logging data to obtain the average well logging velocity at the well location.

[0112] The first determining module is used to determine the seismic mean velocity model of the target area based on the well logging mean velocity and the root mean square velocity model; determine the depth domain stratigraphic interpretation result based on the seismic mean velocity model; determine the first depth domain velocity model based on the depth domain stratigraphic interpretation result and the time domain stratigraphic interpretation result; and determine the local dip field of the depth domain stratigraphic layer based on the depth domain stratigraphic interpretation result.

[0113] The second determining module is used to determine the observation travel time of each reflection point on the depth domain layer based on the time of the time domain layer corresponding to the depth domain layer and the shot-receiver relationship on the corresponding CMP gather, determine the reflection travel time and ray path of each reflection point based on the first depth domain velocity model, the depth domain layer and the local dip field corresponding to the depth domain layer, and update the first depth domain velocity model based on the observation travel time to obtain the second depth domain velocity model.

[0114] The module is used to update the second depth domain velocity model based on the reflection travel time, the ray path, and the observation travel time to obtain the target depth domain velocity model.

[0115] Example 5

[0116] Based on the above embodiments, this embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the above embodiments.

[0117] In some embodiments of this example, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the method described in the above embodiments.

[0118] In some embodiments of this example, a computer program product is provided, including a computer program / instructions, which, when executed by a processor, implements the steps of the method described in the above embodiments.

[0119] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic component, for executing the methods in the above embodiments.

[0120] Computer-readable storage media can be implemented by any type of volatile or non-volatile storage device or a combination thereof. Computer-readable storage media may include, but are not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, and computer storage media (e.g., hard disks, floppy disks, solid-state drives, removable disks, CD-ROMs, DVD-ROMs, Blu-ray discs, etc.).

[0121] Computer-readable storage media may also store at least one computer-executable program / instruction, such as computer-readable instructions. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above can be performed.

[0122] In addition, the computer device may include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (e.g., keyboard, mouse, speakers, etc.).

[0123] The processor can communicate with external devices via the I / O bus through wired or wireless networks.

[0124] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product / computer program product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.

[0125] In the embodiments provided in this disclosure, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0126] It should be noted that, in this disclosure, 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 limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0127] While the embodiments disclosed herein are as described above, the foregoing content is merely for the purpose of facilitating understanding of this disclosure and is not intended to limit this disclosure. Any person skilled in the art to which this disclosure pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope of this disclosure; however, the scope of patent protection of this disclosure shall still be determined by the scope defined in the appended claims.

Claims

1. A method for establishing a velocity model, characterized in that, include: Acquire seismic and well logging data for the target area; Based on the seismic data, determine the time-domain stratigraphic interpretation results and root mean square velocity model for the target area; Based on the logging data, the time-domain stratigraphic interpretation results at the well location are calibrated to obtain the average logging velocity at the well location. Based on the well logging average velocity and the root mean square velocity model, a seismic average velocity model for the target area is determined; based on the seismic average velocity model, depth domain stratigraphic interpretation results are determined; The first depth domain velocity model is determined based on the depth domain layer interpretation results and the time domain layer interpretation results; And based on the depth domain stratigraphic interpretation results, the local dip field of the depth domain stratigraphic level is determined; The observation travel time of each reflection point on the depth domain layer is determined based on the time of the time domain layer corresponding to the depth domain layer and the shot-receiver relationship on the corresponding CMP gather. The reflection travel time and ray path of each reflection point are determined based on the first depth domain velocity model, the depth domain layer and the local dip field corresponding to the depth domain layer. The first depth domain velocity model is updated based on the observation travel time to obtain the second depth domain velocity model. The second depth domain velocity model is updated based on the reflection travel time, the ray path, and the observation travel time to obtain the target depth domain velocity model.

2. The method according to claim 1, characterized in that, The method for determining the seismic mean velocity model of the target area based on the well logging average velocity and the root mean square velocity model includes: Using the well logging average velocity as the first variable and the root mean square velocity as the second variable, co-kriging interpolation is performed to obtain the seismic average velocity model of the target area.

3. The method according to claim 1, characterized in that, The depth domain horizon interpretation results determined based on the seismic mean velocity model include: The updated time-domain torsional interpretation results are determined based on the aforementioned seismic mean velocity model; The updated temporal-domain hierarchical interpretation results are converted to the depth domain to obtain the depth-domain hierarchical interpretation results.

4. The method according to claim 1, characterized in that, The determination of the observation travel time of each reflection point on the depth-domain horizon based on the time of the time-domain horizon corresponding to the depth-domain horizon and the shot-receiver relationship on the corresponding CMP gather includes: Determine the time of the time domain layer corresponding to each grid point in each depth domain layer; Extract the shot and receiver positions on each CMP gather corresponding to each grid point; The travel time of each CMP gather is calculated based on the shot and receiver positions on each CMP gather and the time corresponding to each grid point. The travel time of each CMP gather is determined as the observation travel time of each reflection point on the depth domain layer.

5. The method according to claim 1, characterized in that, The determination of the reflection travel time and ray path of each reflection point based on the first depth domain velocity model, the depth domain layer, and the local dip field corresponding to the depth domain layer includes: Based on the depth domain velocity model, depth domain layer, local dip field corresponding to the depth domain layer, and shot-receiver relationship in the CMP gather of each reflection point, ray tracing is performed from each reflection point toward the ground to determine the reflection travel time and ray path of each reflection point.

6. The method according to claim 1, characterized in that, The step of updating the second depth domain velocity model based on the reflection travel time, the ray path, and the observation travel time to obtain the target depth domain velocity model includes: Based on the reflection travel time, the ray path, and the observation travel time, a set of tomographic inversion equations is constructed, wherein the set of inversion equations includes velocity update and reflection interface depth update. The velocity update and the reflection interface depth update are determined based on the tomographic inversion equations. The second depth domain velocity model is updated based on the velocity update amount and the reflection interface depth update amount to obtain the target depth domain velocity model.

7. The method according to claim 6, characterized in that, The determination of velocity update and reflection interface depth update based on the tomographic inversion equations includes: The tomographic inversion equation is solved using the conjugate gradient method or the least square matrix decomposition method to obtain the velocity update and the reflection interface depth update.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 7.

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