Igneous Rock Constraint Velocity Modeling Method, System, Computer Device, and Storage Medium

Abstract

The present application relates to a method, system, computer device, and storage medium for igneous rock constraint velocity modeling. The method includes: obtaining spatial distribution characteristic information of igneous rocks at different scales by using igneous rock seismic facies; taking the spatial distribution characteristics as constraint conditions, constructing an initial objective function in the objective function of conventional tomography inversion, wherein the spatial distribution characteristics are used to perform seismic facies constraint on the objective function of conventional tomography inversion; applying the igneous rock regional velocity interval information extracted from the seismic facies to the inequality regularization term, obtaining a new objective function from the initial objective function, and establishing a new objective function of seismic facies-controlled tomography inversion with inequality constraint; applying the new objective function to the tomography inversion process to perform igneous rock velocity modeling based on inequality regularization; being able to reasonably control velocity anomalies of igneous rocks with different lithologies and improve the accuracy and stability of igneous rock modeling.

Description

Technical Field

[0001] The present application relates to the field of geophysical exploration, and particularly to a method, system, computer device, and storage medium for igneous rock constrained velocity modeling. Background Art

[0002] Currently, in the field of seismic exploration, the most commonly used method in the industry is still the ray-based tomography velocity modeling technology. Even for a simple tomography method based on ray theory approximation, a large amount of manpower and material resources are still required to construct and update the initial velocity. Moreover, the constructed velocity is a low wavenumber background with low accuracy, and the accuracy of velocity modeling for igneous rocks of different scales, especially small-scale igneous rocks, is insufficient, resulting in poor inversion results and ultimately poor imaging accuracy of the igneous rock region.

[0003] Based on this, whether in academia or industry, many scholars have taken a series of measures to improve the velocity modeling accuracy of the igneous rock region. The most commonly used method is to manually carve the imaged igneous rock and fill the velocity according to experience. Although this method seems effective, it overly relies on the subjective understanding of the processing and interpretation personnel. Once an error occurs, false structures often appear. We usually refer to this method as the igneous rock velocity modeling technology under "hard constraints". In contrast, another method is to introduce structural constraints during tomography, perform regularization structural constraints through existing data, and invert the velocity model of the igneous rock region completely based on data-driven, which can be correspondingly referred to as "soft constraint" igneous rock velocity modeling. Although this method fully respects the data itself and avoids the subjective judgment of the processing personnel, pure data-driven cannot well invert the velocity of small-scale igneous rocks, and the effect of igneous rock velocity modeling is not satisfactory. Summary of the Invention

[0004] Based on this, it is necessary to provide an igneous rock constrained velocity modeling method, system, computer device, and storage medium that can reasonably control velocity anomalies of igneous rocks with different lithologies and improve the accuracy and stability of igneous rock modeling for the above technical problems.

[0005] One aspect of the present invention discloses an igneous rock constrained velocity modeling method, and the method includes:

[0006] Obtain spatial distribution characteristic information of igneous rocks of different scales using igneous rock seismic facies;

[0007] Use the spatial distribution characteristics as constraint conditions and add them to the objective functional of the conventional tomography inversion to construct an initial objective functional, where the spatial distribution characteristics are used to perform seismic facies constraints on the objective functional of the conventional tomography inversion;

[0008] Extracting the velocity interval information of the igneous rock region from the seismic phase and applying it to the inequality regularization term, obtaining a new target functional through the initial target functional, and establishing the new target functional of the seismic phase-controlled tomographic inversion with inequality constraints;

[0009] The new target functional is applied to the tomographic inversion process to form a seismic phase-controlled igneous rock velocity modeling based on inequality constraint regularization.

[0010] Optionally, the igneous rock seismic facies are used to obtain spatial distribution characteristics of igneous rocks at different scales, including:

[0011] The seismic phase pattern of igneous rocks is identified by combining well-seismic data to obtain the spatial distribution characteristics of igneous rocks of different scales, wherein the spatial distribution characteristic information includes one or two of the following: the distribution range of igneous rocks and the top and bottom thickness of the structure.

[0012] Optional, target functionals for conventional tomographic inversion include:

[0013]

[0014] Among them, S(m) is the gather flattening term, which belongs to the criterion of conventional tomographic inversion. pick is the picked reflection point position, z true is the actual reflection point position. When the tomographic velocity is accurate, S(m) is the minimum.

[0015] Optionally, the initial target functional includes:

[0016]

[0017] Among them, W mask is the distribution range of igneous rocks obtained by calculating the seismic phase, Δv is the velocity update of the previous round, and ε1 is the constraint weight factor, which is usually between 0 and 1 according to the actual situation.

[0018] Optionally, the velocity interval information of the igneous rock region extracted from the seismic phase is applied to the inequality regularization term, and a new target functional is obtained through the initial target functional, including:

[0019] The velocity interval information of the igneous rock region is applied to the inequality regularization term by using a logarithmic boundary function, and the new target functional of the inequality-constrained seismic phase-controlled tomography inversion is established.

[0020] Optionally, the igneous rock region velocity interval information is applied to the inequality regularization term using a logarithmic boundary function, including:

[0021] The inequality regularization technology is introduced to realize the inversion of velocity values in igneous rock regions of different scales, and the expression after seismic phase-controlled tomography inversion of the new initial objective functional with inequality constraints includes:

[0022]

[0023] Among them, the 3rd and 4th terms in the above formula are the inequality regularization terms, v min and v max represent the maximum and minimum velocity values extracted from wells or seismic phases. I() represents the logarithmic boundary function, whose function is to compress the inversion null space and constrain the regional velocity update range. Its expression form is as follows:

[0024]

[0025] Optionally, the velocity interval information of the igneous rock region includes: the maximum and minimum velocity values of the igneous rock region.

[0026] In the second aspect of the present invention, an igneous rock constrained velocity modeling system is disclosed. The system includes:

[0027] An acquisition module, configured to obtain the spatial distribution characteristic information of igneous rocks of different scales by using igneous rock seismic phases;

[0028] A functional construction module, configured to add the spatial distribution characteristics as constraint conditions to the objective functional of conventional tomography inversion to construct an initial objective functional, wherein the spatial distribution characteristics are used to perform seismic phase constraint on the objective functional of the conventional tomography inversion;

[0029] An inequality regularization reference module, configured to apply the velocity interval information of the igneous rock region extracted from the seismic phase to the inequality regularization term, obtain a new objective functional through the initial objective functional, and establish seismic phase-controlled tomography inversion of the new objective functional with inequality constraints;

[0030] A modeling module, configured to apply the new objective functional to the tomography inversion process to form seismic phase-controlled igneous rock velocity modeling based on inequality constraint regularization.

[0031] Optionally, the acquisition module is specifically configured to:

[0032] Identify the igneous rock seismic phase pattern through well-seismic combination means to obtain the spatial distribution characteristics of the igneous rocks of different scales, wherein the spatial distribution characteristic information includes one or both of the following: the distribution range of igneous rocks and the top and bottom thickness of the structure.

[0033] Optionally, the objective functional of conventional tomography inversion includes:

[0034]

[0035] Among them, S(m) is the flattening term of the gather, which belongs to the criterion of conventional tomographic inversion. z pick is the picked reflection point position, and z true is the true reflection point position. When the tomographic velocity is accurate, S(m) is minimized.

[0036] Optionally, the initial objective functional includes:

[0037]

[0038] Among them, W mask is the distribution range of igneous rocks obtained by calculating seismic facies, and Δv is the velocity update amount of the previous round. ε1 is the constraint weight factor, which is usually valued between 0 and 1 according to the actual situation.

[0039] Optionally, the inequality regularization reference module includes:

[0040] A function introduction unit for applying the velocity interval information of the igneous rock region to the inequality regularization term by using a logarithmic boundary function, and establishing an inequality-constrained seismic facies-controlled tomographic inversion of the new objective functional.

[0041] Optionally, the function introduction unit is specifically used for:

[0042] Introducing inequality regularization technology to realize the inversion of velocity values in igneous rock regions of different scales, and the expression after obtaining the inequality-constrained seismic facies-controlled tomographic inversion of the new objective functional includes:

[0043]

[0044] Among them, the 3rd and 4th terms of the above formula are the inequality regularization terms, v min and v max represent the maximum and minimum velocity values extracted from the well or seismic facies, I() represents the logarithmic boundary function, whose function is to compress the inversion null space and constrain the regional velocity update range, and its expression form is as follows:

[0045]

[0046] Optionally, the velocity interval information of the igneous rock region includes: the maximum and minimum values of the velocity values in the igneous rock region.

[0047] In the third aspect of the present invention, a computer device is disclosed, including a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the steps of the method described in any one of the above are implemented.

[0048] In a fourth aspect of the present invention, a computer-readable storage medium is disclosed, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method described in any one of the above are implemented.

[0049] The above igneous rock constrained velocity modeling method, system, computer device and storage medium identify the seismic facies pattern of igneous rocks by using the well-seismic combination means, obtain the spatial distribution characteristic information of different igneous rock lithologies, and provide constraint information for high-precision modeling of igneous rocks through the spatial distribution characteristic information; on the basis of the established igneous rock seismic facies pattern, an inequality tomography constraint technology is proposed to realize the reasonable control of velocity anomalies of igneous rocks with different lithologies and improve the accuracy and stability of igneous rock modeling. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is an application environment diagram of an igneous rock constrained velocity modeling method in an embodiment;

[0051] Figure 2 It is a schematic flowchart of an igneous rock constrained velocity modeling method in an embodiment;

[0052] Figure 3 It is the seismic facies interpreted by using the well-seismic combination means in Embodiment 1 of the present invention;

[0053] Figure 4 It is the velocity model constrained by the seismic facies in Embodiment 1 of the present invention;

[0054] Figure 5 It is the distribution diagram of velocity upper and lower limit constraint information obtained from the well curve in Embodiment 1 of the present invention;

[0055] Figure 6 In Embodiment 1 of the present invention, using Figure 3 the velocity upper and lower limit distribution range after adding inequality regularization to obtain the velocity model;

[0056] Figure 7 It is the velocity model obtained by conventional tomography inversion in Embodiment 2 of the present invention;

[0057] Figure 8 In Embodiment 2 of the present invention, corresponding to Figure 5 the migration result obtained from the velocity model;

[0058] Figure 9 It is the velocity model obtained by inverting using the algorithm of the present invention in Embodiment 2 of the present invention;

[0059] Figure 10 In Embodiment 2 of the present invention, corresponding to Figure 7 the migration result obtained from the velocity model;

[0060] Figure 11 It is a structural block diagram of a modeling system for igneous rock constraint velocity in an embodiment;

[0061] Figure 12 It is an internal structure diagram of a computer device in an embodiment. Specific implementation manners

[0062] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0063] Figure 1 It is an application environment diagram of a method for modeling igneous rock constraint velocity in an embodiment; Figure 2 It is a schematic flowchart of a method for modeling igneous rock constraint velocity in an embodiment; Figure 3 It is the seismic facies interpreted by means of well-seismic combination in the first embodiment of the present invention; Figure 4 It is the velocity model constrained by the seismic facies in the first embodiment of the present invention; Figure 5 It is the distribution diagram of velocity upper and lower limit constraint information obtained from well curves in the first embodiment of the present invention; Figure 6 In the first embodiment of the present invention, by using Figure 3 the velocity model obtained after adding inequality regularization to the distribution range of the velocity upper and lower limits; Figure 7 It is the velocity model obtained by conventional tomographic inversion in the second embodiment of the present invention; Figure 8 In the second embodiment of the present invention, corresponding to Figure 5 the migration result obtained from the velocity model; Figure 9 It is the velocity model obtained by inverting using the algorithm of the present invention in the second embodiment of the present invention; Figure 10 In the second embodiment of the present invention, corresponding to Figure 7 the migration result obtained from the velocity model; Figure 11 It is a structural block diagram of a modeling system for igneous rock constraint velocity in an embodiment; Figure 12 It is an internal structure diagram of a computer device in an embodiment.

[0064] First embodiment:

[0065] One implementation manner of the igneous rock constraint velocity modeling method provided by the present application is as follows: It can be applied to, for example, Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through a network. The terminal 102 obtains the spatial distribution characteristic information of igneous rocks at different scales; and sends the spatial distribution characteristic information to the server 104 through the network. The server 104 uses the spatial distribution characteristic as a constraint condition to construct an initial objective functional in the objective functional of conventional tomographic inversion. Among them, the spatial distribution characteristic is used to perform seismic facies constraint on the objective functional of the conventional tomographic inversion; the velocity interval information of the igneous rock area is applied to the inequality regularization term, and a new objective functional is obtained through the initial objective functional, so that the seismic facies-controlled tomographic inversion of the inequality constraint is performed on the new objective functional; the new objective functional is applied to the tomographic inversion process to perform seismic facies-controlled igneous rock velocity modeling based on inequality regularization. Among them, the terminal 102 can be but is not limited to various seismic automatic monitoring instruments, personal computers, laptop computers, smart phones, tablet computers and portable wearable devices, and the server 104 can be implemented by an independent server or a server cluster composed of multiple servers. Of course, the solution executed by the server 104 can also be executed by other terminals 102.

[0066] Therefore, by using the well-seismic combination method to identify the seismic facies pattern of igneous rocks, obtaining the spatial distribution characteristic information of different igneous rock lithologies, and providing constraint information for high-precision modeling of igneous rocks through the spatial distribution characteristic information; on the basis of the established seismic facies pattern of igneous rocks, an inequality tomography constraint technology is proposed to realize the reasonable control of velocity anomalies of igneous rocks with different lithologies and improve the accuracy and stability of igneous rock modeling.

[0067] Second Embodiment:

[0068] As Figure 2 shown, this embodiment provides a constraint method between "soft" and "hard". By developing a lithology semi-quantitative constraint tomographic inversion technology and introducing an inequality tomography regularization technology, the reasonable control of velocity anomalies of igneous rocks at different scales is realized, and the accuracy and stability of velocity modeling of igneous rocks in complex lithology areas are improved.

[0069] Specifically, the method includes the following steps:

[0070] Step S11: Use the seismic facies of igneous rocks to obtain the spatial distribution characteristic information of igneous rocks at different scales;

[0071] Step S12: Use the spatial distribution characteristic as a constraint condition and add it to the objective functional of conventional tomographic inversion to construct an initial objective functional;

[0072] Among them, the spatial distribution characteristic is used to perform seismic facies constraint on the objective functional of the conventional tomographic inversion;

[0073] Step S13: extracting the velocity interval information of the igneous rock region from the seismic phase and applying it to the inequality regularization term, obtaining a new target functional through the initial target functional, and establishing the new target functional of the seismic phase-controlled tomography inversion with inequality constraints;

[0074] Step S14: applying the new target functional to the tomographic inversion process to form a seismic phase-controlled igneous rock velocity modeling based on inequality constraint regularization.

[0075] In steps S11-S14, the seismic phase pattern of igneous rocks is identified by combining well-seismic data and the spatial distribution characteristics of different igneous rock lithologies are established to provide constraint information for high-precision modeling of igneous rocks. Then, based on the established seismic phase pattern of igneous rocks, an inequality tomographic constraint technology is proposed to achieve reasonable control of velocity anomalies of igneous rocks of different lithologies and improve the accuracy and stability of igneous rock modeling.

[0076] Specifically, this embodiment uses the spatial distribution characteristic information and the velocity interval information of the igneous rock region as seismic phase constraints, and constructs a new target functional through the target functional of the above-mentioned conventional tomographic inversion; based on this functional, seismic phase-controlled igneous rock velocity modeling based on inequality regularization is implemented.

[0077] Optionally, an implementation of step S11 includes:

[0078] The seismic phase pattern of igneous rocks is identified by combining well-seismic methods to obtain the spatial distribution characteristics of igneous rocks of different scales.

[0079] The spatial distribution characteristic information includes one or two of the following: the distribution range of igneous rocks and the top and bottom thickness of the structure.

[0080] Optional, target functionals for conventional tomographic inversion include:

[0081]

[0082] Among them, S(m) is the gather flattening term, which belongs to the criterion of conventional tomographic inversion. pick is the picked reflection point position, z true is the actual reflection point position. When the tomographic velocity is accurate, S(m) is the minimum.

[0083] Optionally, the initial target functional includes:

[0084]

[0085] Among them, W mask is the distribution range of igneous rocks obtained by calculating the seismic phase, Δv is the velocity update of the previous round, and ε1 is the constraint weight factor, which is usually between 0 and 1 according to the actual situation.

[0086] Optionally, one implementation of the above step S13 includes:

[0087] Apply the igneous rock area velocity interval information to the inequality regularization term by using a logarithmic bounding function, and implement seismic phase-controlled tomography inversion of the new objective functional with inequality constraints.

[0088] In another embodiment, applying the igneous rock area velocity interval information to the inequality regularization term by using a logarithmic bounding function includes:

[0089] Introduce the inequality regularization technique to implement the inversion of the velocity values in igneous rock areas of different scales. The expression after seismic phase-controlled tomography inversion of the new objective functional with inequality constraints includes:

[0090]

[0091] Among them, the 3rd and 4th terms in the above formula are the inequality regularization terms, v min and v max represent the maximum and minimum velocity values extracted from wells or seismic phases. I() represents the logarithmic bounding function, whose function is to compress the inversion null space and constrain the regional velocity update range. Its expression form is as follows:

[0092]

[0093] In another embodiment, the igneous rock area velocity interval information includes the maximum and minimum values of the igneous rock area velocity values.

[0094] Third Embodiment:

[0095] The present application provides a constraint method between "soft" and "hard". By developing lithology semi-quantitative constrained tomography inversion technology and introducing inequality tomography regularization technology, reasonable control of igneous rock velocity anomalies of different scales is achieved, and the accuracy and stability of igneous rock velocity modeling in complex lithology areas are improved.

[0096] As Figure 3 shown, this is the seismic phase data interpreted by the means of combining well and seismic data in Embodiment 1.

[0097] As Figure 4 shown, this is the velocity model obtained only by seismic phase constraint in Embodiment 1. It can be seen that the igneous rock between depths of 400 - 600 has been globally inverted, but the local details have not been well characterized.

[0098] As Figure 5 shown, this is the distribution range of the maximum and minimum igneous rock velocities extracted from well data in Embodiment 1, which is used in the inequality regularization.

[0099] As Figure 6 shown, this is the velocity model obtained by adding inequality regularization on the basis of seismic facies constraint in the first embodiment. It can be seen that the internal details in the igneous rock area have been better inverted with higher accuracy.

[0100] As Figure 7 shown, this is the result obtained by using conventional tomography inversion in the second embodiment. The distribution of igneous rocks with different scales in the middle can be seen.

[0101] According to Figure 3-7 shown, the present invention provides a method and system for seismic facies constrained velocity modeling of igneous rocks based on inequality regularization. The method includes: identifying the seismic facies pattern of igneous rocks by using the well-seismic combination means, establishing the spatial distribution characteristics of different igneous rock lithologies, providing constraint information for high-precision modeling of igneous rocks. Then, on the basis of establishing the seismic facies pattern of igneous rocks, an inequality tomography constraint technology is proposed to realize the reasonable control of velocity anomaly bodies of igneous rocks with different lithologies, and improve the accuracy and stability of igneous rock modeling. The specific steps are as follows:

[0102] 1) Obtain the distribution range of igneous rocks and the thickness of the top and bottom of the structure by using the seismic facies of igneous rocks;

[0103] 2) Incorporate the information such as the distribution range of igneous rocks obtained from the seismic facies into the objective functional, construct a new objective functional, and realize seismic facies constrained tomography inversion;

[0104] 3) Extract the upper and lower limit information of the velocity values in the igneous rock area from the well data;

[0105] 4) Apply the velocity upper and lower limits to the inequality regularization term by using the logarithmic boundary function to realize the objective functional of inequality constrained seismic facies controlled tomography inversion;

[0106] 5) Apply the new objective functional to the tomography inversion process to finally realize seismic facies controlled igneous rock velocity modeling based on inequality regularization;

[0107] In the above process, because the traditional tomography inversion technology performs global inversion from bottom to top, the inversion resolution of local mutation anomaly bodies (such as igneous rocks) is insufficient, resulting in the distortion of the target horizon under the anomaly body.

[0108] Therefore, in this application, it is necessary to develop an inequality regularization constrained tomography backprojection technology, construct a new high-resolution tomography objective function for igneous rocks, increase the velocity update weight in the igneous rock development area, and realize the resolution of igneous rock high-velocity anomaly bodies. The objective functional of conventional tomography inversion is usually as follows:

[0109]

[0110] Among them, S(m) is the gather flattening term, which belongs to the criterion of conventional tomographic inversion. pick is the picked reflection point position, z true is the actual reflection point position. When the tomographic velocity is accurate, S(m) is the minimum.

[0111] However, in actual situations, since the tomographic matrix is a sparse matrix, it is difficult to obtain good results by relying solely on the gather flattening term of formula (1) without using prior information constraints. Here, we use the combination of well and seismic data to identify the seismic phase of igneous rocks, obtain the spatial distribution characteristics of igneous rocks at different scales, and apply them to the target functional for seismic phase constraints. The formula is as follows:

[0112]

[0113] Among them, W mask is the distribution range of igneous rocks obtained by calculating the seismic phase, Δv is the velocity update of the previous round, and ε1 is the constraint weight factor, which is usually between 0 and 1 according to the actual situation.

[0114] Furthermore, by introducing the inequality regularization technology, the inversion of velocity values of igneous rock regions of different scales can be realized, the stability of the inversion can be improved, the stratigraphic constraints can be better adjusted, and the quantitative control of local anomalies in fine inversion can be achieved.

[0115]

[0116] The third and fourth terms in the above formula are the inequality regularization terms, v min and v max It represents the maximum and minimum velocity values extracted from the well or seismic phase, and I() represents the logarithmic boundary function, which is used to compress the inversion null space and constrain the regional velocity update range. Its expression is as follows:

[0117]

[0118] Formula 3 is the target functional corresponding to the inequality regularized igneous rock seismic phase constrained velocity modeling technology proposed in the present invention. By using this target functional, the velocity range of the volcanic rock velocity anomaly body can be "softly constrained", thereby improving the rationality of the igneous rock velocity modeling.

[0119] In this regard, by utilizing the combination of well and seismic data to identify the seismic phase pattern of igneous rocks, the spatial distribution characteristic information of different igneous rock lithologies is obtained, and the spatial distribution characteristic information is used to provide constraint information for high-precision modeling of igneous rocks. Based on the established seismic phase model of igneous rocks, inequality tomography constraint technology is developed to achieve reasonable control of velocity anomalies in igneous rocks of different lithologies and improve the accuracy and stability of igneous rock modeling.

[0120] Fourth embodiment:

[0121] like Figure 10 As shown, this embodiment provides an igneous rock constrained velocity modeling system, including: an acquisition module 110, a functional construction module 120, an inequality regularization reference module 130 and a modeling module 140, wherein:

[0122] An acquisition module 110 is used to acquire spatial distribution characteristic information of igneous rocks of different scales using igneous rock seismic phases;

[0123] A functional construction module 120 is used to add the spatial distribution characteristics as constraints to the target functional of conventional tomography inversion to construct an initial target functional, wherein the spatial distribution characteristics are used to perform seismic phase constraints on the target functional of conventional tomography inversion;

[0124] An inequality regularization reference module 130 is used to extract the velocity interval information of the igneous rock region from the seismic phase and apply it to the inequality regularization term, obtain a new target functional through the initial target functional, and establish the new target functional of the seismic phase-controlled tomography inversion with inequality constraints;

[0125] The modeling module 140 is used to apply the new target functional to the tomographic inversion process to form a seismic phase-controlled igneous rock velocity modeling based on inequality constraint regularization.

[0126] Optionally, the acquisition module is specifically used to:

[0127] The seismic phase pattern of igneous rocks is identified by combining well-seismic data to obtain the spatial distribution characteristics of igneous rocks of different scales, wherein the spatial distribution characteristic information includes one or two of the following: the distribution range of igneous rocks and the top and bottom thickness of the structure.

[0128] Optional, target functionals for conventional tomographic inversion include:

[0129]

[0130] Among them, S(m) is the gather flattening term, which belongs to the criterion of conventional tomographic inversion. pick is the picked reflection point position, z true is the actual reflection point position. When the tomographic velocity is accurate, S(m) is the minimum.

[0131] Optionally, the initial target functional includes:

[0132]

[0133] Among them, W mask is the distribution range of igneous rocks obtained by calculating the seismic phase, Δv is the velocity update of the previous round, and ε1 is the constraint weight factor, which is usually between 0 and 1 according to the actual situation.

[0134] Optionally, the inequality regularization reference module includes:

[0135] A function introduction unit, which is used to apply the igneous rock area velocity interval information to the inequality regularization term by using a logarithmic boundary function, and establish a new objective functional for seismic phase-controlled tomography inversion with inequality constraints.

[0136] Optionally, the function introduction unit is specifically used for:

[0137] Introduce the inequality regularization technology to realize the inversion of the velocity values in igneous rock areas of different scales. The expression after obtaining the new objective functional for seismic phase-controlled tomography inversion with inequality constraints includes:

[0138]

[0139] Among them, the 3rd and 4th terms in the above formula are the inequality regularization terms, v min and v max represent the maximum and minimum velocity values extracted from the well or seismic phase. I() represents the logarithmic boundary function, whose function is to compress the inversion null space and constrain the regional velocity update range. Its expression form is as follows:

[0140]

[0141] Optionally, the igneous rock area velocity interval information includes: the maximum and minimum values of the igneous rock area velocity values.

[0142] Thus, by using the well-seismic combination method to identify the igneous rock seismic facies pattern, obtain the spatial distribution characteristic information of different igneous rock lithologies, and provide constraint information for high-precision igneous rock modeling through the spatial distribution characteristic information; on the basis of the established igneous rock seismic facies pattern, it is planned to develop an inequality tomography constraint technology to realize the reasonable control of velocity anomalies of igneous rocks with different lithologies and improve the accuracy and stability of igneous rock modeling.

[0143] The fifth embodiment:

[0144] According to Figure 11 shown, this embodiment provides a computer device, which can be a server, and its internal structure diagram can be as Figure 11As shown in the figure. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store relevant data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a method for igneous rock constrained velocity modeling.

[0145] Those skilled in the art can understand that Figure 4 the structure shown in the figure is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0146] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

[0147] Utilize igneous rock seismic facies to obtain spatial distribution characteristic information of igneous rocks at different scales;

[0148] Take the spatial distribution characteristics as constraint conditions and add them to the objective functional of conventional tomography inversion to construct an initial objective functional. Among them, the spatial distribution characteristics are used to perform seismic facies constraint on the objective functional of the conventional tomography inversion;

[0149] Apply the igneous rock region velocity interval information extracted from the seismic facies to the inequality regularization term, and obtain a new objective functional through the initial objective functional, and establish an inequality-constrained seismic facies-controlled tomography inversion for the new objective functional;

[0150] Apply the new objective functional to the tomography inversion process to form an igneous rock velocity modeling based on inequality-constrained regularization.

[0151] Optionally, utilizing igneous rock seismic facies to obtain spatial distribution characteristic information of igneous rocks at different scales includes:

[0152] Identify the igneous rock seismic facies pattern through well-seismic combination means to obtain the spatial distribution characteristics of the igneous rocks at different scales. Among them, the spatial distribution characteristic information includes one or both of the following: the distribution range of igneous rocks and the top and bottom thickness of the structure.

[0153] Optionally, the objective functional of conventional tomography inversion includes:

[0154]

[0155] Among them, S(m) is the flattened term of the gather, which belongs to the criterion of conventional tomographic inversion. z pick is the picked reflection point position, and z true is the true reflection point position. When the tomographic velocity is accurate, S(m) is minimized.

[0156] Optionally, the initial objective functional includes:

[0157]

[0158] Among them, W mask is the distribution range of igneous rock obtained by calculating seismic facies, and Δv is the velocity update amount of the previous round. ε1 is the constraint weight factor, which is usually valued between 0 and 1 according to the actual situation.

[0159] Optionally, applying the velocity interval information of the igneous rock area extracted from the seismic facies to the inequality regularization term, a new objective functional is obtained through the initial objective functional, including:

[0160] Applying the velocity interval information of the igneous rock area to the inequality regularization term by using the logarithmic boundary function, and establishing the seismic facies-controlled tomographic inversion with inequality constraints for the new objective functional.

[0161] Optionally, applying the velocity interval information of the igneous rock area to the inequality regularization term by using the logarithmic boundary function includes:

[0162] Introducing the inequality regularization technology to realize the inversion of the velocity values in igneous rock areas of different scales, and the expression after obtaining the new initial objective functional of the seismic facies-controlled tomographic inversion with inequality constraints includes:

[0163]

[0164] Among them, the 3rd and 4th terms of the above formula are the inequality regularization terms, and v min and v max represent the maximum and minimum velocity values extracted from the well or seismic facies, and I() represents the logarithmic boundary function, whose function is to compress the inversion null space and constrain the regional velocity update range, and its expression form is as follows:

[0165]

[0166] Optionally, the velocity interval information of the igneous rock area includes: the maximum and minimum values of the velocity values in the igneous rock area.

[0167] Sixth Embodiment:

[0168] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0169] The spatial distribution characteristics are used as constraints and added to the target functional of conventional tomography inversion to construct an initial target functional, wherein the spatial distribution characteristics are used to perform seismic phase constraints on the target functional of conventional tomography inversion;

[0170] Extracting the velocity interval information of the igneous rock region from the seismic phase and applying it to the inequality regularization term, obtaining a new target functional through the initial target functional, and establishing the new target functional of the seismic phase-controlled tomographic inversion with inequality constraints;

[0171] The new target functional is applied to the tomographic inversion process to form a seismic phase-controlled igneous rock velocity modeling based on inequality constraint regularization.

[0172] Optionally, the igneous rock seismic facies are used to obtain spatial distribution characteristics of igneous rocks at different scales, including:

[0173] The seismic phase pattern of igneous rocks is identified by combining well-seismic data to obtain the spatial distribution characteristics of igneous rocks of different scales, wherein the spatial distribution characteristic information includes one or two of the following: the distribution range of igneous rocks and the top and bottom thickness of the structure.

[0174] Optional, target functionals for conventional tomographic inversion include:

[0175]

[0176] Among them, S(m) is the gather flattening term, which belongs to the criterion of conventional tomographic inversion. pick is the picked reflection point position, z true is the actual reflection point position. When the tomographic velocity is accurate, S(m) is the minimum.

[0177] Optionally, the initial target functional includes:

[0178]

[0179] Among them, W mask is the distribution range of igneous rocks obtained by calculating the seismic phase, Δv is the velocity update of the previous round, and ε1 is the constraint weight factor, which is usually between 0 and 1 according to the actual situation.

[0180] Optionally, the velocity interval information of the igneous rock region extracted from the seismic phase is applied to the inequality regularization term, and a new target functional is obtained through the initial target functional, including:

[0181] Apply the velocity interval information of the igneous rock region to the inequality regularization term by using a logarithmic partition function, and establish a seismic phase-controlled tomography inversion with inequality constraints for the new objective functional.

[0182] Optionally, applying the velocity interval information of the igneous rock region to the inequality regularization term by using a logarithmic partition function includes:

[0183] Introduce inequality regularization technology to realize the inversion of velocity values in igneous rock regions of different scales. The expression after the new initial objective functional of the seismic phase-controlled tomography inversion with inequality constraints includes:

[0184]

[0185] Among them, the 3rd and 4th terms in the above formula are the inequality regularization terms, v min and v max represent the maximum and minimum velocity values extracted from wells or seismic phases. I() represents the logarithmic partition function, whose function is to compress the inversion null space and constrain the regional velocity update range. Its expression form is as follows:

[0186]

[0187] Optionally, the velocity interval information of the igneous rock region includes: the maximum and minimum values of the velocity values in the igneous rock region.

[0188] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to memory, storage, database, or other media provided in the various embodiments of the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0189] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0190] The above-described embodiments only represent several implementation manners of the present application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the appended claims.

Claims

1. A method for modeling the constraint velocity of igneous rocks, characterized in that, The method includes: Obtaining spatial distribution characteristic information of igneous rocks at different scales by using igneous rock seismic facies; Taking the spatial distribution characteristics as constraint conditions and adding them to the objective functional of conventional tomography inversion to construct an initial objective functional, where the spatial distribution characteristics are used to perform seismic facies constraint on the objective functional of the conventional tomography inversion; Applying the igneous rock region velocity interval information extracted from the seismic facies to the inequality regularization term, obtaining a new objective functional through the initial objective functional, and establishing an inequality-constrained seismic facies-controlled tomography inversion for the new objective functional; Applying the new objective functional to the tomography inversion process to form an igneous rock velocity modeling with seismic facies control based on inequality-constrained regularization; The objective functional of conventional tomography inversion includes: Among them, S(m) is the flattening term of the gather, which belongs to the criterion of conventional tomographic inversion; z pick is the picked reflection point position, and z true is the true reflection point position; when the tomographic velocity is accurate, S(m) is minimized; The initial objective functional includes: Among them, W mask is the distribution range of igneous rocks obtained by calculating seismic facies, Δv is the velocity update amount in the previous round; ε1 is a constraint weight factor, which takes values between 0 and 1 according to the actual situation; Applying the igneous rock region velocity interval information extracted from the seismic facies to the inequality regularization term, obtaining a new objective functional through the initial objective functional, including: Applying the igneous rock region velocity interval information to the inequality regularization term by using a logarithmic boundary function, and establishing an inequality-constrained seismic facies-controlled tomography inversion for the new objective functional; Applying the igneous rock region velocity interval information to the inequality regularization term by using a logarithmic boundary function, including: Introducing an inequality regularization technique to realize the inversion of velocity values in igneous rock regions at different scales, and the expression after obtaining the inequality-constrained seismic facies-controlled tomography inversion for the new objective functional includes: Among them, the 3rd and 4th terms in the above formula are the inequality regularization terms, $v$ min and $v$ max represent the maximum and minimum velocities extracted from the well or seismic phase, and $I()$ represents the logarithmic boundary function, whose function is to compress the inversion null space and constrain the velocity update range of the region. Its expression is as follows:

2. The method according to claim 1, wherein Obtaining spatial distribution characteristic information of igneous rocks at different scales by using igneous rock seismic facies, including: Identifying the igneous rock seismic facies pattern through well-seismic combination means to obtain the spatial distribution characteristics of the igneous rocks at different scales, where the spatial distribution characteristic information includes one or both of the following: the distribution range of igneous rocks and the top and bottom thicknesses of the structure.

3. The method according to claim 1, wherein The igneous rock region velocity interval information includes: the maximum and minimum values of the igneous rock region velocity values.

4. A modeling system for igneous rock constraint velocity, characterized in that, The system includes: An acquisition module for obtaining spatial distribution characteristic information of igneous rocks at different scales by using igneous rock seismic facies; A functional construction module for taking the spatial distribution characteristics as constraint conditions and adding them to the objective functional of conventional tomography inversion to construct an initial objective functional, where the spatial distribution characteristics are used to perform seismic facies constraint on the objective functional of the conventional tomography inversion; An inequality regularization reference module for applying the igneous rock region velocity interval information extracted from the seismic facies to the inequality regularization term, obtaining a new objective functional through the initial objective functional, and establishing an inequality-constrained seismic facies-controlled tomography inversion for the new objective functional; A modeling module for applying the new objective functional to the tomography inversion process to form an igneous rock velocity modeling with seismic facies control based on inequality-constrained regularization; The objective functional of conventional tomography inversion includes: Among them, S(m) is the flattening term of the gather, which belongs to the criterion of conventional tomographic inversion; z pick is the picked reflection point position, and z true is the true reflection point position; when the tomographic velocity is accurate, S(m) is minimized; The initial objective functional includes: Among them, W mask is the distribution range of igneous rocks obtained by calculating seismic facies, Δv is the velocity update amount in the previous round; ε1 is a constraint weight factor, which takes values between 0 and 1 according to the actual situation; The inequality regularization reference module includes: A function introduction unit for applying the igneous rock region velocity interval information to the inequality regularization term by using a logarithmic boundary function, and establishing an inequality-constrained seismic facies-controlled tomography inversion for the new objective functional; The function introduction unit is used to introduce the inequality regularization technology to realize the inversion of the velocity values in igneous rock regions of different scales, and the expression after obtaining the new objective functional of seismic phase-controlled tomography with inequality constraints includes: Among them, the 3rd and 4th terms in the above formula are the inequality regularization terms, v min and v max represent the maximum and minimum velocities extracted from well or seismic phases, and I() represents the logarithmic demarcation function, whose function is to compress the inversion null space and constrain the velocity update range in the region. Its expression form is as follows:

5. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it realizes the steps of the method described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, A computer program is stored thereon, and when the computer program is executed by a processor, it realizes the steps of the method described in any one of claims 1 to 3.

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