While-drilling local tomography velocity modeling method, electronic device, medium and apparatus

Abstract

The application discloses a while-drilling local tomography velocity modeling method, electronic equipment, medium and device, and comprises the following steps: 1) calculating well-seismic velocity error by using a seismic velocity model to form a well velocity constraint regularization term; 2) performing well-seismic error statistics according to an imaging profile and well layer depth to form a well layering constraint term; 3) performing well-surrounding imaging gather residual velocity spectrum scanning to obtain a conventional tomography inversion term; 4) combining the well velocity constraint regularization term and the well layering constraint term to form a precondition operator, and combining the conventional tomography inversion term to establish a target function; and 5) solving the target function to obtain a precondition solution, i.e., a well-surrounding velocity update amount, so as to complete well-surrounding velocity modeling. The application is used for guiding well-surrounding velocity tomography inversion, improving well-surrounding inversion precision and resolution, and thus improving subsequent local imaging effect.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of geophysical exploration, and more particularly relates to a while-drilling local tomographic velocity modeling method, an electronic device, a medium and an apparatus. BACKGROUND

[0002] Conventional seismic modeling imaging technology has limited precision, and cannot distinguish small structures and thin layers in the underground, so that the real geological conditions of the underground cannot be fully understood, thus there is still great uncertainty in the drilling process, thereby causing many safety hazards, and not only cannot guarantee hitting the target reservoir, but also causes personnel and economic losses, and increases development costs. While-drilling seismic is a technology that uses a drilling bit to detect various geophysical data during drilling, simultaneously completes data acquisition, to accurately and timely obtain the latest geological information in front of the drilling bit, and comprehensively utilizes logging and geophysical processing technology to quickly update information of the formation and structure in front of the drilling bit, and simultaneously quickly adjusts the drilling scheme, which can help save drilling costs and improve drilling safety.

[0003] Real-time logging data acquisition and targeted rapid processing technology during drilling are keys of while-drilling seismic technology. For complex geological conditions, conventional seismic technology cannot timely and accurately predict the geological conditions of the drilling area, and drilling operations often face the problems of high risk and high cost. While-drilling seismic technology timely and accurately predicts the depth, velocity, pressure and other properties of the formation in front of the drilling bit, to provide services for drilling engineering such as adjustment of the drilling trajectory, selection of the casing position and size, and selection of the drilling fluid density, effectively reduces drilling risks, and improves drilling efficiency; meanwhile, the while-drilling seismic technology also provides more accurate imaging results and fine interpretation data for oil and gas reservoir prediction, and has very important significance for oil and gas reservoir exploration and development.

[0004] At present, there is a lack of effective targeted rapid modeling imaging technology for while-drilling seismic. Conventional depth domain modeling imaging technology has low efficiency, and the calculation time period of high-precision modeling imaging is difficult to meet the real-time requirement of while-drilling, which usually requires data update period to be less than two days, and the conventional modeling imaging technology cannot achieve a high-precision imaging standard in a short time for pre-drilling guidance, which is a main bottleneck restricting the development of while-drilling technology.

[0005] Therefore, it is expected to develop a while-drilling local tomographic velocity modeling method, an electronic device, a medium and an apparatus, to update the seismic velocity in front of the drilling bit based on new information provided by while-drilling logging, to improve imaging precision, and provide new and more accurate seismic results for drilling. SUMMARY

[0006] The application aims to provide a drilling local tomographic velocity modeling method, an electronic device, a medium and an apparatus, to provide real-time horizon information for drilling logging, to develop a drilling local tomographic velocity modeling technology based on well horizon information constraint by using well-provided horizon depth information, to guide tomographic inversion of well surrounding velocity, to improve well surrounding inversion accuracy and resolution, and to improve subsequent local imaging effect.

[0007] To achieve the above-mentioned purpose, the application provides a drilling local tomographic velocity modeling method, which comprises the following steps:

[0008] 1) calculating well-seismic velocity error by using seismic velocity model to form well velocity constraint regularization term;

[0009] 2) performing well-seismic error statistics according to imaging profile and well horizon depth to form well layering constraint term;

[0010] 3) performing well surrounding imaging gather residual velocity spectrum scanning to obtain conventional tomographic inversion term;

[0011] 4) combining the well velocity constraint regularization term and the well layering constraint term to form a preconditioning operator, and combining the conventional tomographic inversion term to establish an objective function;

[0012] 5) solving the objective function to obtain a preconditioned solution, i.e. well surrounding velocity update, to complete velocity modeling.

[0013] Optionally, the well velocity constraint regularization term is expressed as:

[0014]

[0015] wherein v grid represents seismic velocity, v well represents logging velocity, z represents depth, and represents an optimal solution operator in the least square sense.

[0016] Optionally, the well layering constraint term is expressed as:

[0017]

[0018] wherein z mig represents seismic profile horizon depth, and z well represents logging layering thickness.

[0019] Optionally, the conventional tomographic inversion term is expressed as:

[0020]

[0021] wherein z true represents real depth of underground formation, and zpick represents the imaging depth corresponding to the current velocity.

[0022] Optionally, the step 4) comprises:

[0023] 4.1) obtaining a general tomographic inversion equation after discretizing a general model preconditioned tomographic equation on a rectangular grid;

[0024] 4.2) obtaining a damped least square equation of the general tomographic inversion equation based on a damping factor, i.e., the inversion equation;

[0025] 4.3) bringing the preconditioned operator into the inversion equation to establish an objective function.

[0026] Optionally, the objective function is expressed as:

[0027]

[0028] wherein G(m) represents a preconditioned operator, and ε1 and ε2 are weighting coefficients.

[0029] Optionally, the objective function is expressed as:

[0030] S T L T LSu+εu=SLΔτ

[0031] wherein L is a linearization operator, S is a preconditioned operator, u is a preconditioned solution, ε is a damping factor, and Δτ is a residual time difference.

[0032] The present application also provides an electronic device, which comprises a memory and a processor;

[0033] The memory stores executable instructions;

[0034] The processor executes the executable instructions in the memory to implement the above-mentioned method for modeling a local tomographic velocity while drilling.

[0035] The present application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the above-mentioned method for modeling a local tomographic velocity while drilling.

[0036] The present application also provides a device for modeling a local tomographic velocity while drilling based on a well logging horizon constraint, which comprises a well circumference velocity updating amount calculation module and is used to execute the above-mentioned method for modeling a local tomographic velocity while drilling.

[0037] The present application has the beneficial effect that in the seismic tomographic inversion, the spatial distribution characteristics of the model parameters are constrained by the underground structure information, the correlation characteristics of the model parameters in space are extracted by the structure information, and the information is added to the tomographic inversion by combining the preconditioning idea, so that the estimated model parameters can be significantly improved. For the while-drilling seismic, the local Gaussian beam tomography not only uses the gather flattening criterion for constraint, but more importantly, uses the well position information for constraint, that is, the well position depth information provided by the well is used to guide the velocity tomographic inversion around the well, so as to improve the inversion accuracy and resolution around the well, thereby improving the subsequent local imaging effect. The present application aims at the rapid velocity modeling problem of while-drilling seismic, and is based on the real-time position information provided by the while-drilling logging. By using the well velocity and position depth information provided by the well, the while-drilling local rapid tomographic velocity modeling technology based on well position information constraint is developed, which is used to guide the velocity tomographic inversion around the well, improve the inversion accuracy and resolution around the well, and thereby improve the subsequent local imaging effect.

[0038] Other features and advantages of the present application will be described in detail in the following specific embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0039] The above and other objects, features and advantages of the present application will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings in which like reference characters refer to like parts throughout the different views of the drawings.

[0040] Figure 1 The logging velocity (left) and seismic velocity (right) for calculating the well velocity constraint regularization term in an embodiment of the present application.

[0041] Figure 2 The seismic profile and well layer superimposed display diagram for calculating the well layer constraint term in an embodiment of the present application.

[0042] Figure 3 The initial velocity before the while-drilling rapid velocity modeling in an embodiment of the present application.

[0043] Figure 4 The velocity update quantity calculated by the while-drilling rapid velocity modeling in an embodiment of the present application.

[0044] Figure 5 The updated velocity after the while-drilling rapid velocity modeling in an embodiment of the present application.

[0045] Figure 6 The imaging profile corresponding to the initial velocity before the while-drilling rapid velocity modeling in an embodiment of the present application.

[0046] Figure 7The imaging profile corresponding to the updated speed of the fast speed modeling while drilling in an embodiment of the present application. DETAILED DESCRIPTION

[0047] Preferred embodiments of the present application will be described in more detail below. Although the following describes preferred embodiments of the present application, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present application will be thorough and complete, and will fully convey the scope of the present application to those skilled in the art.

[0048] In the description of the present application, it should be understood that the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0049] The present application discloses a method for locally tomographic velocity modeling while drilling, which comprises the following steps:

[0050] 1) Calculate the well-seismic velocity error using the seismic velocity model to form a well velocity constrained regularization term;

[0051] 2) Perform well-seismic error statistics according to the imaging profile and well depth to form a well layering constraint term;

[0052] 3) Perform residual velocity spectrum scanning of the imaging gather around the well to obtain a conventional tomographic inversion term;

[0053] 4) Combine the well velocity constrained regularization term and the well layering constraint term to form a preconditioning operator, and combine the conventional tomographic inversion term to establish an objective function;

[0054] 5) Solve the objective function to obtain the preconditioned solution, i.e. the updated velocity around the well, to complete the velocity modeling around the well.

[0055] Specifically, in the seismic tomographic inversion, the underground structure information is used to constrain the spatial distribution characteristics of the model parameters, the correlation characteristics of the model parameters in space are extracted through the structure information, and the information is added to the tomographic inversion combined with the preconditioning idea, so that the estimated model parameters can be significantly improved. For the while-drilling seismic, in addition to using the gather flattening criterion for constraint, more importantly, the well position information is used for constraint, that is, the well position depth information provided by the well is used to guide the velocity tomographic inversion around the well, so that the inversion accuracy and resolution around the well are improved, and the subsequent local imaging effect is improved.

[0056] The present application is aimed at the rapid velocity modeling problem of while-drilling seismic, and based on the real-time position information provided by the while-drilling logging, the while-drilling local rapid tomographic velocity modeling technology based on well position information constraint is developed by using the well velocity and well position depth information provided by the well, which is used to guide the velocity tomographic inversion around the well, improve the inversion accuracy and resolution around the well, and improve the subsequent local imaging effect.

[0057] As an optional solution, the well velocity constraint regularization term is expressed as:

[0058]

[0059] Wherein, v grid represents the seismic velocity, v well represents the logging velocity, z represents the depth, represents the optimal solution operator in the least square sense.

[0060] Specifically, this term uses the drilled formation velocity information of the while-drilling logging to construct a new tomographic inversion objective function, which can alleviate the multi-solution problem of tomographic inversion, and can adjust the accuracy of the velocity field around the well in real time. The logging velocity resolution obtained from the acoustic curve is high in vertical direction, and the difference with the seismic velocity is very large, so it cannot be directly used for modeling. Therefore, the formal differences such as resolution and sampling rate are corrected first. The well velocity is processed through removing outliers, median filtering, slowness smoothing, resampling and the like, so as to ensure that the velocity trend before and after correction is basically consistent. The resolution of the corrected velocity is low, the sampling rate is reduced, there is no high-frequency oscillation of the original logging velocity outliers and burrs, and it is more in line with the characteristics of the seismic velocity, and at the same time, it does not lose too much thin layer information, and the detail characteristics are well maintained. In addition, instead of directly using the velocity for hard constraint to prevent logging information error, the partial derivative of the velocity to the depth is used as a constraint term, so that the inversion is solved in the correct updating direction.

[0061] As an optional solution, the well layering constraint term is expressed as:

[0062]

[0063] Wherein, z migz represents the depth of the seismic profile layer well z represents the thickness of the logging sublayer.

[0064] Specifically, the constraint term can further adjust the accuracy of the well velocity, reduce the well seismic error, make the tomographic inversion always satisfy the well seismic closure in the iterative updating process, realize higher precision velocity inversion and migration imaging, and accurately guide the drilling direction.

[0065] As an optional solution, the conventional tomographic inversion term is represented as:

[0066]

[0067] z represents the true depth of the underground formation true z represents the true depth of the underground formation pick z represents the imaging depth corresponding to the current velocity.

[0068] As an optional solution, step 4) comprises:

[0069] 4.1) After the conventional model preconditioned tomographic equation is discretized on a rectangular grid, a general tomographic inversion equation is obtained;

[0070] 4.2) Based on the damping factor, a damped least squares equation of the general tomographic inversion equation, i.e. the inversion equation, is obtained.

[0071] 4.3) The preconditioning operator is brought into the inversion equation to establish an objective function.

[0072] As an optional solution, the objective function is represented as:

[0073]

[0074] G(m) represents the preconditioning operator, and ε1 and ε2 are weighting coefficients, and ε1 and ε2 are small positive real numbers, used to weight the weight between the data fitting term and the regularization term.

[0075] Specifically, the seismic data is often limited and insufficient to constrain all model components, and the data often contains noise. According to singular value analysis, small noise in the data will be infinitely amplified under underdetermined conditions, so that the estimated solution is completely deviated from the true solution, which destroys the stability of the inversion. Therefore, well velocity and well sublayer information are introduced for regularization constraint, because well information is measured and reliable, so that the solution can develop in the correct direction after introducing the information.

[0076] As an optional solution, the objective function is represented as:

[0077] S T L T LSu+εu=SLΔτ

[0078] where L is a linearization operator, S is a preconditioning operator, u is a preconditioned solution, epsilon is a damping factor, and Delta tau is a residual time difference.

[0079] Specifically, the general model preconditioning tomography equation is obtained after the rectangular grid discretization of the general model equation, as follows:

[0080] LSu = Delta tau

[0081] Considering the damping factor epsilon, the damping least square equation of the tomography equation can be expressed as:

[0082] S T L T LSu + epsilon u = SL Delta tau

[0083] When the preconditioning operator S is a smoothing operator containing well information, the equation is a well information constrained regularization tomography equation, and the corresponding solution is a smoothed solution after regularization.

[0084] The application further discloses an electronic device, which comprises a memory and a processor.

[0085] The memory stores executable instructions.

[0086] The processor runs the executable instructions in the memory to implement the drilling-while-drilling local tomography velocity modeling method.

[0087] The application further discloses a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the drilling-while-drilling local tomography velocity modeling method.

[0088] The application further discloses a drilling-while-drilling local tomography velocity modeling device based on well position constraint, which comprises a well peripheral velocity updating amount calculation module and is used for implementing the drilling-while-drilling local tomography velocity modeling method.

[0089] Embodiment

[0090] The embodiment is based on the real-time position information provided by drilling-while-drilling logging, and a drilling-while-drilling local fast tomography velocity modeling technology based on well position information constraint is developed by using the well peripheral velocity and position depth information provided by the well, which is used for guiding the tomography inversion of the well peripheral velocity, improving the well peripheral inversion precision and resolution, and thus improving the subsequent local imaging effect. The specific steps are as follows.

[0091] 1) The well seismic velocity error is calculated by using the seismic velocity model to form a well velocity constraint regularization term.

[0092] 2) The well seismic error is counted from the imaging profile and the well position depth to form a well layered constraint term.

[0093] 3) Develop the residual velocity spectrum scanning of the imaging gathers around the well, and obtain the conventional tomographic inversion term

[0094] 4) Form the preconditioning operator S by using steps 1-3, and bring it into the inversion matrix to establish the objective function, S T L T LSu+εu=SLΔτ;

[0095] 5) Solve the objective function to obtain the well velocity update amount u, and complete the well velocity modeling work.

[0096] Wherein, as shown in formula (1), it is the logging velocity (left) and the seismic velocity (right) for calculating the well velocity constraint regularization term in the embodiment, and the logging velocity constraint regularization term in the preconditioning operator can be calculated by using the data. Figure 1 As shown in formula (2), it is the seismic profile and the well layering superimposed display diagram for calculating the well layering constraint term, and the well layering constraint term in the preconditioning operator can be calculated by using the superimposed display.

[0097] Figure 2 As shown in formula (3), it is the initial velocity before the fast velocity modeling while drilling in the embodiment, and the velocity is the seismic velocity before the update.

[0098] As shown in formula (4), it is the velocity update amount calculated by using the fast velocity modeling while drilling. It can be seen that the update amount is mainly concentrated in the layer position of the well layering, and the distribution is reasonable. Figure 3 As shown in formula (5), it is the updated velocity after the fast velocity modeling while drilling in the embodiment, that is, the initial velocity of

[0099] plus the update amount of Figure 4 to obtain the updated velocity.

[0100] As shown in formula (6), it is the imaging profile corresponding to the initial velocity, and it can be seen that the well-seismic error is large, and the fast velocity correction around the well is needed. Figure 5 Figure 3 As shown in formula (7), it is the imaging profile corresponding to the updated velocity, and it can be seen that the well-seismic error is obviously reduced, and the effect of the fast local velocity modeling while drilling is remarkable. Figure 4

[0101] As shown in formula (8), it is the imaging profile corresponding to the initial velocity, and it can be seen that the well-seismic error is large, and the fast velocity correction around the well is needed. Figure 6 Figure 3 As shown in formula (9), it is the imaging profile corresponding to the updated velocity, and it can be seen that the well-seismic error is obviously reduced, and the effect of the fast local velocity modeling while drilling is remarkable.

[0102] As shown in formula (10), it is the imaging profile corresponding to the initial velocity, and it can be seen that the well-seismic error is large, and the fast velocity correction around the well is needed. Figure 7 Figure 5 As shown in formula (11), it is the imaging profile corresponding to the updated velocity, and it can be seen that the well-seismic error is obviously reduced, and the effect of the fast local velocity modeling while drilling is remarkable.

[0103] ​​​​​Having described various embodiments of the application, it is to be understood that the above description is meant to be illustrative only, and that many modifications and variations of the embodiments are possible without departing from the scope and spirit of the described embodiments. Many modifications and variations of the described embodiments are possible in light of the above teachings. It is, therefore, to be understood that within the scope of the appended claims and their equivalents, the described embodiments can be practiced otherwise than as specifically described.

Claims

1. A local tomographic velocity modeling method while drilling, characterized in that: The method comprises the following steps: 1) Calculate the well seismic velocity error using the seismic velocity model to form a well velocity constraint regularization term; 2) Perform well-seismic error statistics based on imaging sections and well layer depths to form well layer constraint terms; 3) Scan the residual velocity spectrum of the wellbore imaging gather to obtain conventional tomographic inversion terms; 4) forming a preconditioner by combining the well velocity constraint regularization term and the well stratification constraint term, and establishing an objective function in combination with the conventional tomographic inversion term; 5) solving the objective function to obtain a pre-conditioned solution, i.e., an update of the wellbore velocity, to complete velocity modeling; The well velocity constraint regularization term is expressed as: Among them, v grid represents the earthquake velocity, v well represents the logging speed, z represents the depth, represents the optimal solution operator in the sense of least squares.

2. The method for local tomographic velocity modeling while drilling according to claim 1, characterized in that: The well stratification constraint term is expressed as: Among them, z mig Indicates the depth of the seismic profile, z well Indicates the logging layer thickness.

3. The method for local tomographic velocity modeling while drilling according to claim 2, characterized in that: The conventional tomographic inversion term is expressed as: Among them, z true Indicates the true depth of the underground stratum, z pick Indicates the imaging depth corresponding to the current speed.

4. The method for local tomographic velocity modeling while drilling according to claim 3, characterized in that: The objective function is expressed as: Among them, G(m) represents the objective function, and ε1 and ε2 are weighting coefficients.

5. An electronic device, characterized in that: The electronic device includes a memory and a processor; The memory stores executable instructions; The processor runs the executable instructions in the memory to implement the method for local tomographic velocity modeling while drilling according to any one of claims 1 to 4.

6. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the method for local tomographic velocity modeling while drilling according to any one of claims 1 to 4.

7. A local tomographic velocity modeling device for drilling based on logging horizon constraints, characterized in that: The device includes a wellbore velocity update amount calculation module, which is used to execute the while-drilling local tomography velocity modeling method according to any one of claims 1-4.

Images