Lateral velocity analysis and construction mapping method and device and storage medium

Abstract

The invention discloses a lateral velocity analysis and construction mapping method and device and a storage medium, lateral velocity research is carried out on the basis of a large amount of exploration and development actual drilling data of an oil field, and a lateral velocity gradient method is summarized. The method comprises the following steps: firstly, carrying out qualitative analysis on a regional velocity change rule, and then carrying out statistics on a time-depth conversion equation of a regional lateral velocity gradient method by utilizing VSP data of a large number of wells; according to the method, through multi-level fitting, parameter averaging processing, relative value fitting analysis and comprehensive application, the accuracy of the target oil field depth structure map is remarkably improved, and a more reliable geological basis is provided for oil field exploration and development. Lateral velocity analysis and construction mapping can be more accurately carried out, and the method can be widely applied to the technical field of construction time-depth conversion.

Description

Technical Field

[0001] The present invention relates to the technical field of structural time-depth conversion, and in particular to a lateral velocity analysis and structural mapping method, device and storage medium. Background Art

[0002] For anticline structures, the largest oil column and the most oil-bearing sand layers are always found at the top of the structure. From a production perspective, in order to achieve the maximum recovery rate of the oil field, the high part of the structure is always the main area for the deployment of development wells. The reliability of the structural morphology plays a key role in the development design and risk assessment of an oil field. However, from the actual drilling situation of developed oil fields, the deep structural highs of many oil fields deviate from the position of the temporal structural highs. Studies have found that the lateral variation of the layer velocity of the overlying strata of the target layer of the oil field group is the main reason for the deviation of the temporal structural highs from the true position. Therefore, studying and analyzing the lateral variation law of the layer velocity is the key to implementing the deep structure to provide a basis for the next development plan of the oil field.

[0003] Among the related technologies, the main methods to solve the deviation of temporal structural high points from their true positions are variable speed structural mapping and velocity inversion. The variable speed structural mapping method constructs an initial space-variable velocity field based on the processed stacking velocity and the time-depth relationship calibrated on the well, performs corresponding corrections on the initial velocity field, obtains the corrected space-variable velocity field, and uses the velocity field to perform time-depth conversion to form a depth structural map. The velocity inversion method combines the processed velocity and drilling data to perform velocity body inversion, and then uses the inverted velocity body to perform time-depth conversion.

[0004] However, the current variable velocity structural mapping method has obvious technical disadvantages: (1) The spatial variable velocity field in the variable velocity mapping is based on the stacking velocity generated during the seismic data processing, which has low accuracy. This is because the stacking velocity spectrum is obtained by an idealized parabolic time-distance curve at a certain CMP interval during time domain processing, and cannot accurately reflect the change in formation velocity. (2) There are also human factors in the corresponding correction of the initial velocity field. If the correction amount is not accurately grasped, there is also the possibility of increasing the structural error. (3) The velocity volume inversion method has a large amount of calculation and high inversion cost. Summary of the invention

[0005] The present invention aims to solve the problem of related art limitations at least to a certain extent. To this end, the present invention provides a lateral velocity analysis and configuration mapping method, device and storage medium, which can accurately perform lateral velocity analysis and configuration mapping.

[0006] On the one hand, an embodiment of the present invention provides a lateral velocity analysis and construction mapping method, comprising the following steps:

[0007] Obtain time-depth data for each well in the target oil field;

[0008] Fitting the time-depth data based on a preset time-depth relationship to obtain a first parameter value of a time-depth parameter of each well in the preset time-depth relationship; wherein the time-depth parameter includes one-way travel time, acceleration, velocity, intercept and depth;

[0009] Refitting the preset time-depth relationship based on a first average value of all intercepts in the first parameter value to obtain a first time-depth relationship;

[0010] Fitting the time-depth data based on the first time-depth relationship to obtain a second parameter value of the time-depth parameter of each well in the first time-depth relationship;

[0011] refitting the first time-depth relationship based on a second average value of all velocities and a third average value of all accelerations in the second parameter value to obtain a second time-depth relationship;

[0012] Based on the first parameter value combined with the second average value and the third average value, the velocity relative value and the acceleration relative value of each well are obtained, and then the fitting relationship between the velocity relative value and the acceleration relative value of all wells is obtained by fitting; the acceleration relative value represents the lateral velocity gradient;

[0013] The third time-depth relationship is obtained based on the second time-depth relationship combined with the fitting relationship conversion;

[0014] Based on the third time-depth relationship, the lateral velocity gradient of each well is obtained by using the time-depth data corresponding to the seismic layer after layer calibration; the lateral velocity gradient trend diagram is compiled according to the lateral velocity gradient corresponding to each well in the target oil field;

[0015] Substitute the single-layer reflection time and lateral velocity gradient trend diagram of the seismic layer into the third time-depth relationship to obtain the depth structure map of the target oil field.

[0016] Optionally, the method further comprises the following steps:

[0017] According to the principle of seismic reflection time-distance curve, the preset time-depth relationship is set;

[0018] Among them, the expression of the preset time-depth relationship is:

[0019] D=A W T 2 +B W T+C W ;

[0020] Where D represents depth; A W represents acceleration; T represents one-way travel time; B W Indicates speed; C W represents the intercept.

[0021] Optionally, re - fit the preset time - depth relationship based on the first average value of all intercepts in the first parameter value to obtain the first time - depth relationship, including the following steps:

[0022] Obtain the average error of all wells for fitting time - depth data based on the preset time - depth relationship;

[0023] Set the intercept setting value according to the first average value and the average error;

[0024] Substitute the intercept setting value into the intercept of the preset time - depth relationship to obtain the first time - depth relationship; the intercept in the time - depth parameters of the first time - depth relationship is fixed to the intercept setting value;

[0025] Wherein, the expression of the first time - depth relationship is:

[0026] D = A W T 2 + B W T + C 平均 ;

[0027] Wherein, D represents depth; A W represents acceleration; T represents one - way travel time; B W represents velocity; C 平均 represents the intercept setting value.

[0028] Optionally, re - fit the first time - depth relationship based on the second average value of all velocities and the third average value of all accelerations in the second parameter value to obtain the second time - depth relationship, including the following steps:

[0029] Substitute the second average value into the velocity of the first time - depth relationship and substitute the third average value into the acceleration of the first time - depth relationship to obtain the second time - depth relationship; the velocity in the time - depth parameters of the second time - depth relationship is fixed to the second average value and the acceleration is fixed to the third average value;

[0030] Wherein, the expression of the second time - depth relationship is:

[0031] D = A REF T 2 + B REF T + C 平均 ;

[0032] Wherein, D represents depth; A REF represents the third average value; T represents one - way travel time; B REF represents the second average value; C 平均 represents the intercept setting value preset based on the first average value.

[0033] Optionally, based on the first parameter value, the relative velocity value and relative acceleration value of each well are processed by combining the second average value and the third average value, and then the fitting relationship between the relative velocity value and the relative acceleration value of all wells is obtained by fitting, including the following steps:

[0034] Obtain the relative velocity value of each well according to the ratio of the velocity of each well in the first parameter value to the second average value;

[0035] Obtain the relative acceleration value of each well according to the ratio of the acceleration of each well in the first parameter value to the third average value;

[0036] Obtain the fitting relationship between the relative velocity value and the relative acceleration value of all wells by fitting according to the relative velocity value and relative acceleration value corresponding to all wells;

[0037] Among them, the expression of the fitting relationship is:

[0038] B W / B REF = X1(A W / A REF ) 2 - X2(A W / A REF ) + X3;

[0039] Among them, B W represents velocity; B REF represents the second average value; A W represents acceleration; A REF represents the third average value; X1, X2 and X3 represent fitting parameter values.

[0040] Optionally, based on the second time-depth relationship, the third time-depth relationship is obtained by conversion in combination with the fitting relationship, including the following steps:

[0041] Based on the relative velocity value and relative acceleration value, the converted time-depth relationship of any well is obtained by conversion according to the second time-depth relationship;

[0042] Substitute the fitting relationship into the converted time-depth relationship to obtain the third time-depth relationship;

[0043] Among them, the expression of the second time-depth relationship is: D = A REF T 2 + B REF T + C 平均 ; D represents depth; A REF represents the third average value; T represents one-way travel time; B REF represents the second average value; C 平均 represents the intercept setting value preset based on the first average value;

[0044] The expression of the converted time-depth relationship is: D = AREF (A W / A REF )T 2 +(B REF B W / B REF )T+C 平均 ; B W Indicates speed, B REF represents the second average value, B W / B REF Indicates the relative value of speed; A W represents acceleration, A REF represents the third average value, A W / A REF Indicates the relative value of acceleration;

[0045] The expression of the conversion time-depth relationship is: B W / B REF =X1(A W / A REF ) 2 -X2(A W / A REF )+X3; X1, X2 and X3 represent the fitting parameter values;

[0046] The expression of the third time-depth relationship is:

[0047] D=A REF (A W / A REF )T 2 +B REF [X1(A W / A REF ) 2 -X2(A W / A REF )+X3]T+C 平均 .

[0048] Optionally, based on the third time-depth relationship, the lateral velocity gradient of each well is obtained by using the time-depth data corresponding to the seismic horizon after horizon calibration, including the following steps:

[0049] The time and depth corresponding to the seismic layer after layer calibration are obtained, and then substituted into the third time-depth relationship for inverse solution to obtain the lateral velocity gradient of each well.

[0050] Optionally, the method further comprises the following steps:

[0051] Conduct 3D seismic data tracking and interpretation on the seismic layer to obtain a double-layer reflection time structure map of the seismic layer;

[0052] Divide the grid of the double-layer reflection time construction map by 2 to obtain the single-layer reflection time.

[0053] On the other hand, an embodiment of the present invention provides a lateral velocity analysis and structure mapping device, including:

[0054] A first module, configured to obtain the time-depth data of each well in the target oilfield;

[0055] A second module, configured to fit the time-depth data based on a preset time-depth relationship to obtain a first parameter value of the time-depth parameter of each well in the preset time-depth relationship; wherein, the time-depth parameter includes one-way travel time, acceleration, velocity, intercept, and depth;

[0056] A third module, configured to refit the preset time-depth relationship based on the first average value of all intercepts in the first parameter value to obtain a first time-depth relationship;

[0057] A fourth module, configured to fit the time-depth data based on the first time-depth relationship to obtain a second parameter value of the time-depth parameter of each well in the first time-depth relationship;

[0058] A fifth module, configured to refit the first time-depth relationship based on the second average value of all velocities and the third average value of all accelerations in the second parameter value to obtain a second time-depth relationship;

[0059] A sixth module, configured to process based on the first parameter value combined with the second average value and the third average value to obtain the relative velocity value and relative acceleration value of each well, and then fit to obtain the fitting relationship between the relative velocity value and the relative acceleration value of all wells; the relative acceleration value characterizes the lateral velocity gradient;

[0060] A seventh module, configured to convert to obtain a third time-depth relationship based on the second time-depth relationship combined with the fitting relationship;

[0061] An eighth module, configured to obtain the lateral velocity gradient of each well based on the time-depth data corresponding to the seismic horizon after horizon calibration according to the third time-depth relationship; prepare a lateral velocity gradient trend map according to the lateral velocity gradient corresponding to each well in the target oilfield;

[0062] A ninth module, configured to substitute the single-layer reflection time of the seismic layer and the lateral velocity gradient trend map into the third time-depth relationship to convert and obtain the depth structure map of the target oilfield.

[0063] Optionally, the device further includes:

[0064] A tenth module, configured to set a preset time-depth relationship according to the principle of seismic reflection travel-time curve;

[0065] Wherein, the expression of the preset time-depth relationship is:

[0066] D = A W T 2 + BW T+C W ;

[0067] Where D represents depth; A W represents acceleration; T represents one-way travel time; B W Indicates speed; C W represents the intercept.

[0068] Optionally, the device further comprises:

[0069] The eleventh module is used to perform three-dimensional seismic data tracking and interpretation on the horizon of the seismic layer to obtain a double-layer reflection time structure map of the seismic layer;

[0070] The twelfth module is used to divide the grid of the double-layer reflection time structure diagram by 2 to obtain the single-layer reflection time.

[0071] On the other hand, an embodiment of the present invention provides an electronic device, including: a processor and a memory; the memory is used to store programs; the processor executes the program to implement the above-mentioned lateral velocity analysis and mapping method.

[0072] On the other hand, an embodiment of the present invention provides a computer storage medium, in which a program executable by a processor is stored. When the program executable by the processor is executed by the processor, it is used to implement the above-mentioned lateral velocity analysis and mapping method.

[0073] The embodiment of the present invention obtains the time-depth data of each well in the target oil field; fits the time-depth data based on a preset time-depth relationship to obtain a first parameter value of the time-depth parameter of each well in the preset time-depth relationship; wherein the time-depth parameter includes one-way travel time, acceleration, speed, intercept and depth; refits the preset time-depth relationship based on a first average value of all intercepts in the first parameter value to obtain a first time-depth relationship; fits the time-depth data based on the first time-depth relationship to obtain a second parameter value of the time-depth parameter of each well in the first time-depth relationship; refits the first time-depth relationship based on a second average value of all speeds and a third average value of all accelerations in the second parameter value to obtain a second time-depth relationship; refits the first time-depth relationship based on a second average value of all speeds and a third average value of all accelerations in the second parameter value to obtain a second time-depth relationship A parameter value is combined with the second average value and the third average value to obtain the velocity relative value and acceleration relative value of each well, and then the fitting relationship between the velocity relative value and the acceleration relative value of all wells is obtained by fitting; the acceleration relative value represents the lateral velocity gradient; the third time-depth relationship is obtained based on the second time-depth relationship combined with the fitting relationship; based on the third time-depth relationship, the lateral velocity gradient of each well is obtained by the time-depth data corresponding to the seismic layer after layer calibration; the lateral velocity gradient trend diagram is compiled according to the lateral velocity gradient corresponding to each well in the target oil field; the single-layer reflection time of the seismic layer and the lateral velocity gradient trend diagram are substituted into the third time-depth relationship to obtain the depth structure map of the target oil field. The beneficial effects of the present invention include at least:

[0074] 1. Multi-level fitting optimization: By fitting time-depth data multiple times and continuously adjusting the preset time-depth relationship, more accurate time-depth relationships (such as the first time-depth relationship, the second time-depth relationship, etc.) are obtained, thereby improving the accuracy of time-depth conversion.

[0075] 2. Parameter averaging processing: Re-fitting the time-depth relationship using the average values of intercept, velocity, and acceleration reduces the influence of accidental errors and improves the stability and reliability of the parameters.

[0076] 3. Relative value fitting analysis: By fitting the relationship between the relative value of velocity and the relative value of acceleration, the lateral velocity gradient is characterized, providing a more accurate reference basis for subsequent conversion.

[0077] 4. Comprehensive application to improve accuracy: Combining the time-depth data of seismic horizons after horizon calibration and the lateral velocity gradient trend chart, substituting the finally optimized time-depth relationship (the third time-depth relationship), calculating the lateral velocity gradient and compiling the trend chart, further improving the accuracy of the depth structure map.

[0078] Through multi-level fitting, parameter averaging processing, relative value fitting analysis, and comprehensive application, the present invention significantly improves the accuracy of the depth structure map of the target oilfield, providing a more reliable geological basis for oilfield exploration and development. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] The drawings are used to provide a further understanding of the technical solutions of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the technical solutions of the present invention and do not constitute a limitation to the technical solutions of the present invention.

[0080] Figure 1 It is a schematic diagram of an implementation environment for lateral velocity analysis and structure mapping provided by an embodiment of the present invention;

[0081] Figure 2 It is a schematic flowchart of a method for lateral velocity analysis and structure mapping provided by an embodiment of the present invention;

[0082] Figure 3 It is a schematic diagram of the relationship between acceleration and velocity factor of a relative reference well provided by an embodiment of the present invention;

[0083] Figure 4 It is a schematic diagram of the planar distribution of the oilfield lateral velocity gradient VLF provided by an embodiment of the present invention;

[0084] Figure 5 It is a schematic diagram of the seismic double-layer reflection time structure provided by an embodiment of the present invention;

[0085] Figure 6 It is a schematic diagram of the depth structure of the lateral velocity gradient method provided by an embodiment of the present invention;

[0086] Figure 7 Schematic diagram of the principle of time structure migration caused by lateral velocity variation in the overlying formation provided by the embodiment of the present invention;

[0087] Figure 8 Schematic diagram of the overall process of the specific application of the lateral velocity analysis and structure mapping method provided by the embodiment of the present invention;

[0088] Figure 9 Schematic diagram of the structure of a lateral velocity analysis and structure mapping device provided by the embodiment of the present invention;

[0089] Figure 10 Schematic diagram of the structure of an electronic device provided by the embodiment of the present invention. Detailed implementation manners

[0090] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention 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 invention and are not used to limit the present invention.

[0091] It should be noted that although functional module division is performed in the system schematic diagram and the logical sequence is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order from the module division in the system or the sequence in the flowchart. Terms such as "first / S100", "second / S200", etc. in the specification, claims and the above-mentioned drawings are used to distinguish similar objects and do not necessarily need to describe a specific order or sequence.

[0092] Referring to "embodiment" herein means that a specific feature, structure or characteristic described in connection with the embodiment may be included in at least one embodiment of the present invention. The phrase appears in various positions in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described herein may be combined with other embodiments.

[0093] It can be understood that the lateral velocity analysis and structure mapping method provided by the embodiments of the present invention can be applied to any computer device with data processing and computing capabilities, and this computer device can be various types of terminals or servers. When the computer device in the embodiment is a server, the server is an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. Optionally, the terminal is a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto.

[0094] For the convenience of understanding the technical solutions of the present invention, first, the technical feature proper nouns that may appear in the embodiments of the present invention are explained:

[0095] As Figure 1 shown, it is a schematic diagram of an implementation environment provided by the embodiments of the present invention. Referring to Figure 1 , this implementation environment includes at least one terminal 102 and a server 101. The terminal 102 and the server 101 can be network-connected by wireless or wired means to complete data transmission and exchange.

[0096] The server 101 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0097] In addition, the server 101 can also be a node server in a blockchain network. Among them, the blockchain is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, and encryption algorithm.

[0098] The terminal 102 can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, etc., but is not limited thereto. The terminal 102 and the server 101 can be directly or indirectly connected by wired or wireless communication means, and the embodiments of the present invention do not make any restrictions here.

[0099] Exemplarily based on Figure 1In the implementation environment shown, an embodiment of the present invention provides a lateral velocity analysis and structure mapping method. Taking the application of this lateral velocity analysis and structure mapping method in server 101 as an example for illustration, it can be understood that this lateral velocity analysis and structure mapping method can also be applied to terminal 102.

[0100] Referring to Figure 2 , Figure 2 is the flowchart of the lateral velocity analysis and structure mapping method applied to the server provided by the embodiment of the present invention. The execution subject of this lateral velocity analysis and structure mapping method can be any of the aforementioned computer devices (including servers or terminals). Referring to Figure 2 , this method includes the following steps:

[0101] S100. Obtain the time-depth data of each well in the target oilfield;

[0102] S200. Fit the time-depth data based on the preset time-depth relationship to obtain the first parameter value of the time-depth parameter of each well in the preset time-depth relationship;

[0103] Among them, the time-depth parameters include one-way travel time, acceleration, velocity, intercept, and depth;

[0104] Among them, in some embodiments, the method may further include the following steps: According to the principle of the seismic reflection traveltime curve, set the preset time-depth relationship; among them, the expression of the preset time-depth relationship is:

[0105] D = A W T 2 + B W T + C W ;

[0106] Among them, D represents depth; A W represents acceleration; T represents one-way travel time; B W represents velocity; C W represents intercept.

[0107] Exemplarily, in some specific embodiments, according to the principle of the seismic reflection traveltime curve, the time-depth relationship of each well can be expressed by the following equation:

[0108] D = A W T 2 + B W T + C W

[0109] In the formula, D represents depth, in meters; T represents one-way travel time, in seconds; A W represents acceleration, in meters per second 2 ; B W represents velocity, in meters per second; CW is the intercept, i.e., the depth at time T = 0, in meters.

[0110] There are five variables in this equation, and different wells A W , B W , C W have different values. The process of quantitative analysis is to statistically analyze the patterns (if any) of all equations, and then perform a series of mathematical transformations. After simplification, a relational expression of depth D varying with variable T is formed, and this process is equivalent to normalization.

[0111] S300. Re - fit the preset time - depth relationship based on the first average value of all intercepts in the first parameter value to obtain the first time - depth relationship;

[0112] It should be noted that in some embodiments, step S300 may include the following steps: obtaining the average error of all wells in fitting the time - depth data based on the preset time - depth relationship; setting the intercept set value according to the first average value and the average error; substituting the intercept set value into the intercept of the preset time - depth relationship to obtain the first time - depth relationship; fixing the intercept in the time - depth parameters of the first time - depth relationship as the intercept set value; where the expression of the first time - depth relationship is:

[0113] D = A W T 2 + B W T + C 平均 ;

[0114] where D represents depth; A W represents acceleration; T represents one - way travel time; B W represents velocity; C 平均 represents the intercept set value.

[0115] Exemplarily, in some specific embodiments, it is elaborated by combining specific fitting data examples:

[0116] As shown in Table 1, it is a statistical table of the regression equations of the time - depth relationships (five variables) of 21 wells. In the table, the minimum value of item C is 102.27, the maximum value is 179.02, and the average value is 143.0. The range of the average depth error of each well (the average of the errors between the actual depth and the depth obtained by the equation) is 0.5 - 2.1. According to the preset redundancy rule, the intercepts of the time - depth relationships of all wells can be set to 140, or the intercept can be directly set to 142.5 or 140.9 according to the extreme values of the error range. In some specific application scenarios, the intercept can also be directly set to the average value of 143.0. Thus, new time - depth relationship equations for each well can be obtained.

[0117] Table 1

[0118]

[0119]

[0120] Table 2

[0121]

[0122]

[0123] S400. Fit the time-depth data based on the first time-depth relationship to obtain the second parameter value of the time-depth parameter of each well in the first time-depth relationship;

[0124] Exemplarily, in some specific embodiments, taking the intercept (140) set in the specific example of Table 1 described above as an example, after obtaining the new time-depth relationship equations for each well, the second parameter values of the re-fitted time-depth parameters are shown in Table 2 (4 variables, the intercept is set to a fixed value), and the average error range of the well depth of each well is 0.6 - 2.1 m, with a relatively small average error, indicating that this transformation can ensure the accuracy of each equation.

[0125] Table 2

[0126]

[0127]

[0128] S500. Re-fit the first time-depth relationship based on the second average value of all velocities and the third average value of all accelerations in the second parameter value to obtain the second time-depth relationship;

[0129] It should be noted that in some embodiments, step S500 may include the following steps: substituting the second average value into the velocity of the first time-depth relationship and substituting the third average value into the acceleration of the first time-depth relationship to obtain the second time-depth relationship; the velocity in the time-depth parameter of the second time-depth relationship is fixed to the second average value and the acceleration is fixed to the third average value; where the expression of the second time-depth relationship is:

[0130] D = A REF T 2 + B REF T + C 平均 ;

[0131] where D represents depth; A REF represents the third average value; T represents one-way travel time; B REF represents the second average value; C 平均 represents the intercept setting value preset based on the first average value.

[0132] Exemplarily, in some specific embodiments, further obtain the average acceleration factor A W of each well to obtain the acceleration factor A of the reference wellREF ; and calculate the average velocity factor B of each well W , and obtain the velocity factor B of the reference well REF Then, the time-depth relationship equation of the reference well can be set as D = A REF T 2 +B REF T+C 平均 .

[0133] S600, obtaining a velocity relative value and an acceleration relative value of each well based on the first parameter value combined with the second average value and the third average value, and then fitting to obtain a fitting relationship between the velocity relative values ​​and the acceleration relative values ​​of all wells;

[0134] Among them, the relative value of acceleration represents the lateral velocity gradient;

[0135] It should be noted that, in some embodiments, step S600 may include the following steps: obtaining the relative velocity value of each well according to the ratio of the velocity of each well in the first parameter value to the second average value; obtaining the relative acceleration value of each well according to the ratio of the acceleration of each well in the first parameter value to the third average value; obtaining the fitting relationship between the relative velocity values ​​and the relative acceleration values ​​of all wells according to the relative velocity values ​​and the relative acceleration values ​​corresponding to all wells; wherein the expression of the fitting relationship is:

[0136] B W / B REF =X1(A W / A REF ) 2 -X2(A W / A REF )+X3;

[0137] Among them, B W Indicates speed; B REF Indicates the second average value; A W Indicates acceleration; A REF represents the third mean value; X1, X2, and X3 represent fitting parameter values.

[0138] For example, in some specific implementations, the description is expanded based on the specific example in Table 2 above, and the data examples shown in Table 3 are further sorted out. The A values ​​of all wells in Table 3 are statistically analyzed. W and B W The relationship between A W and B W There is a certain linear relationship. Select a reference well and take the average value of all wells. Then the A of the reference well is REF =1256.0, B REF =1120.0, thus obtaining the A of any well relative to the reference well W / A REF and B W / B REF (Table 3).

[0139] In some specific embodiments, based on the example parameters in Table 3, for any well, the relationship between A W / A REF and B W / B REF (taking the example parameters as an example, as Figure 3 shown): B W / B REF = 0.6769(A W / A REF ) 2 - 1.8813(A W / A REF ) + 2.2069; the goodness of fit R 2 = 0.9602.

[0140]

[0141]

[0142] S700. The third time-depth relationship is obtained by converting the second time-depth relationship in combination with the fitting relationship;

[0143] It should be noted that in some embodiments, step S700 may include the following steps: based on the relative velocity value and the relative acceleration value, converting to obtain the converted time-depth relationship of any well according to the second time-depth relationship; substituting the fitting relationship into the converted time-depth relationship to obtain the third time-depth relationship;

[0144] Among them, the expression of the second time-depth relationship is: D = A REF T 2 + B REF T + C 平均 ; D represents depth; A REF represents the third average value; T represents the one-way travel time; B REF represents the second average value; C 平均 represents the intercept setting value preset based on the first average value;

[0145] The expression of the converted time-depth relationship is: D = A REF (A W / A REF )T 2 + (B REF B W / B REF )T + C 平均 ; B W represents velocity, B REF represents the second average value, BW / B REF represents the relative value of speed; A W represents acceleration, A REF represents the third average value, A W / A REF represents the relative value of acceleration;

[0146] The expression for converting time-depth relationship is: B W / B REF = X1(A W / A REF ) 2 - X2(A W / A REF ) + X3; X1, X2 and X3 represent the fitting parameter values;

[0147] The expression for the third time-depth relationship is:

[0148] D = A REF (A W / A REF )T 2 + B REF [X1(A W / A REF ) 2 - X2(A W / A REF ) + X3]T + C 平均 .

[0149] Exemplarily, in some specific embodiments, the time-depth relationship equation of the reference well can be inferred to obtain the time-depth relationship equation of any well (taking the example parameters) as: D = 1256.0*(A W / A REF )T 2 + 1120.0*(B W / B REF )T + 140.

[0150] Specifically, A W / A REF and B W / B REF The regression results show that these two have a good linear relationship. Substituting B W / B REF into the time-depth relationship of any well, the equation (taking the example parameters) is obtained:

[0151] D = 1256*(A W / A REF )T 2 + 1120*[0.6769(A W / A REF ) 2-1.8813(A W / A REF )+2.2069]T+140;

[0152] Define the lateral velocity gradient VLF = A W / A REF , we can get the time-depth formula of the lateral velocity gradient method for any well (taking the instance parameters as an example):

[0153] D=1256*(VLF)T 2 +1120*[0.6769(VLF) 2 -1.8813(VLF)+2.2069]T+140.

[0154] S800, based on the third time-depth relationship, the lateral velocity gradient of each well is obtained by using the time-depth data corresponding to the seismic layer after layer calibration; and a lateral velocity gradient trend diagram is compiled according to the lateral velocity gradient corresponding to each well in the target oil field;

[0155] It should be noted that, in some embodiments, based on the third time-depth relationship, the lateral velocity gradient of each well is obtained by using the time-depth data corresponding to the seismic layer after layer calibration, which can include the following steps: obtaining the time and depth corresponding to the seismic layer after layer calibration, and then substituting them into the third time-depth relationship for inverse solution to obtain the lateral velocity gradient of each well.

[0156] For example, in some specific implementations, based on the actual situation of the oil field, the VLF value of each well point is obtained by using the time corresponding to the seismic layer after layer calibration and the actual drilling depth, and then the lateral velocity gradient VLF trend diagram of the oil field is compiled with reference to the change trend of the regional VLF. The specific steps are as follows:

[0157] (1) Synthetic records and horizon calibration;

[0158] (2) According to the time corresponding to the seismic layer after layer calibration and the actual drilling depth, the lateral velocity gradient VLF value of each well point can be obtained by inversely solving the following equation;

[0159] D=1256*(VLF)T 2 +1120*[0.6769(VLF) 2 -1.8813(VLF)+2.2069]T+140;

[0160] (3) According to the VLF value of the actual well point and the change trend of VLF in the reference area, a VLF trend diagram of the lateral velocity gradient of the oil field is compiled (such as Figure 4 shown).

[0161] Among them, in some embodiments, the method may further include the following steps: performing three-dimensional seismic data tracing and interpretation on the horizons of the seismic layer to obtain a double-layer reflection time structure map of the seismic layer; dividing the grid of the double-layer reflection time structure map by 2 to obtain the single-layer reflection time.

[0162] Exemplarily, in some specific embodiments, performing three-dimensional seismic data tracing and interpretation on the horizons after synthetic seismogram calibration can obtain a double-layer reflection time structure map of this layer (as Figure 5 shown), and dividing the grid of this double-layer reflection time structure map by 2 can obtain the single-layer reflection time T.

[0163] S900. Substitute the single-layer reflection time of the seismic layer and the lateral velocity gradient trend map into the third time-depth relationship to convert and obtain the depth structure map of the target oilfield.

[0164] Exemplarily, in some specific embodiments, substitute the VLF grid and the single-layer reflection time T grid obtained above into the final time-depth relationship formula for time-depth conversion, and after well-point correction, the final depth structure map can be obtained (as Figure 6 shown).

[0165] To explain the principle of the technical solution of the present invention in detail, the overall process of the present invention will be described below in conjunction with some specific embodiments. It is easy to understand that the following is an explanation of the technical principle of the present invention and should not be regarded as a limitation of the present invention.

[0166] First of all, it should be noted that there are still many problems with the variable velocity mapping method currently used in oil and gas field exploration and development, and it is difficult to meet the accuracy requirements of the structure in the oilfield development stage. The present invention proposes a lateral velocity gradient and structure mapping technology. This technology conducts research on lateral velocity on the basis of a large number of actual drilling data in oilfield exploration and development, and summarizes the method of lateral velocity gradient. It first qualitatively analyzes the regional velocity change law, and then uses the VSP data of a large number of wells to statistically obtain the time-depth conversion equation of the regional lateral velocity gradient method.

[0167] Specifically, as Figure 7 shown, in combination with the specific parameter examples in the foregoing Tables 1 to 3, the method embodiment of the present invention can be specifically implemented as follows:

[0168] 1. Analysis of the reasons for the time structure offset caused by the lateral velocity change of the overlying formation:

[0169] The seismic reflection principle shows that due to the lateral (horizontal) differences in shallow layer velocity, the time structure high point will shift from the direction of low velocity to the direction of higher velocity (as Figure 8 shown), which is the essential reason for the time structure high point deviating from the true position.

[0170] 2. Lateral velocity gradient quantization analysis and derivation of time-depth conversion formula:

[0171] According to the principle of seismic reflection travel-time curve, the time-depth relationship of each well can be expressed by the following equation:

[0172] D = A W T 2 + B W T + C W ;

[0173] In the formula, D represents depth, with the unit of meter; T represents one-way travel time, with the unit of second; A W represents acceleration, with the unit of m / s 2 ; B W represents velocity, with the unit of m / s; C W is the intercept, that is, the depth at time T = 0, with the unit of meter.

[0174] There are five variables in this equation, and the values of A W , B W , C W are different for different wells. The quantization analysis process is to statistically analyze the laws (if any) of all equations, and then perform a series of mathematical transformations. After simplification, a relational expression of depth D varying with variable T is formed, and this process is equivalent to normalization.

[0175] Referring to Table 1 mentioned above, it is the statistical table of the regression equations of the time-depth relationships of 21 wells. In the table, the minimum value of item C is 102.27, the maximum value is 179.02, and the average value is 143.0. The range of the average depth error of each well (the average value of the error between the actual depth and the depth obtained by the equation) is 0.5 - 2.1. By setting the intercept of the time-depth relationship of all wells to 140, new time-depth relationship equations for each well are obtained. Referring to Table 2 mentioned above, the range of the average error of the well depth of each well is 0.6 - 2.1m, and the average error is relatively small, indicating that this transformation can ensure the accuracy of each equation.

[0176] Statistically analyze the relationship between A W and B W of all wells in Table 3 mentioned above. It can be seen that there is a certain linear relationship between A W and B W . Select a reference well and take the average value of all wells. Then, for the reference well, A REF = 1256.0, B REF = 1120.0. Thus, the A W / A REF and B W / B REF (Table 3) of any well relative to the reference well are obtained.

[0177] The time-depth relationship equation of the reference well is:

[0178] D = 1256.0T 2 + 1120.0T + 140;

[0179] The time-depth relationship equation for any well is:

[0180] D = 1256.0*(A W / A REF )T 2 + 1120.0*(B W / B REF )T + 140;

[0181] The relationship between A W / A REF and B W / B REF for any well relative to the reference well (refer to Figure 3 ):

[0182] B W / B REF = 0.6769(A W / A REF ) 2 - 1.8813(A W / A REF ) + 2.2069;

[0183] The goodness of fit R 2 = 0.9602;

[0184] A W / A REF and B W / B REF The regression results show that there is a good linear relationship between the two. Substituting B W / B REF into the time-depth relationship of any well gives the equation:

[0185] D = 1256*(A W / A REF )T 2 + 1120*[0.6769(A W / A REF ) 2 - 1.8813(A W / A REF ) + 2.2069]T + 140;

[0186] Define the lateral velocity gradient VLF = A W / A REF , and the time-depth formula for the lateral velocity gradient method of any well is:

[0187] D = 1256*(VLF)T2 +1120 * [0.6769(VLF) 2 -1.8813(VLF) + 2.2069]T + 140;

[0188] 3. Compilation of lateral velocity gradient plan view:

[0189] Based on the actual situation of the oilfield, use the time corresponding to the seismic horizons after horizon calibration and the actual drilling depth to obtain the VLF values at each well point, and then refer to the changing trend of the regional VLF to compile the lateral velocity gradient VLF trend map of the oilfield. The specific steps are as follows:

[0190] (1) Synthetic seismogram and horizon calibration;

[0191] (2) According to the time corresponding to the seismic horizons after horizon calibration and the actual drilling depth, perform inverse solution using the following equation to obtain the lateral velocity gradient VLF values at each well point;

[0192] D = 1256 * (VLF)T 2 +1120 * [0.6769(VLF) 2 -1.8813(VLF) + 2.2069]T + 140;

[0193] (3) According to the VLF values of the actual well points, refer to the changing trend of the regional VLF to compile the lateral velocity gradient VLF trend map of the oilfield (refer to Figure 4 );

[0194] 4. Time-depth conversion by lateral velocity gradient method:

[0195] Perform 3D seismic data tracing and interpretation on the horizons after synthetic seismogram calibration to obtain the double-layer reflection time structure map of this layer (refer to Figure 5 ), divide the grid of this double-layer reflection time structure map by 2 to obtain the single-layer reflection time T.

[0196] Substitute the obtained VLF grid and single-layer reflection time T grid into the following formula for time-depth conversion, and after well point correction, obtain the final depth structure map (refer to Figure 6 ).

[0197] D = 1256 * (VLF)T 2 +1120 * [0.6769(VLF) 2 -1.8813(VLF) + 2.2069]T + 140;

[0198] In summary, based on a large amount of actual drilling data from oilfield exploration and development, the present invention conducts lateral velocity research and summarizes a method for lateral velocity gradient. It first qualitatively analyzes the regional velocity variation law, and then uses the VSP data of a large number of wells to statistically obtain the time-depth conversion equation of the regional lateral velocity gradient method. The present invention can accurately perform depth structure and meet the accuracy requirements of the structure in the oilfield development stage.

[0199] On the other hand, as Figure 9 shown, an embodiment of the present invention provides a lateral velocity analysis and structure mapping device 900, which may include:

[0200] A first module 901 for obtaining the time-depth data of each well in the target oilfield;

[0201] A second module 902 for fitting the time-depth data based on a preset time-depth relationship to obtain a first parameter value of the time-depth parameter of each well in the preset time-depth relationship; wherein, the time-depth parameter includes one-way travel time, acceleration, velocity, intercept, and depth;

[0202] A third module 903 for refitting the preset time-depth relationship based on the first average value of all intercepts in the first parameter value to obtain a first time-depth relationship;

[0203] A fourth module 904 for fitting the time-depth data based on the first time-depth relationship to obtain a second parameter value of the time-depth parameter of each well in the first time-depth relationship;

[0204] A fifth module 905 for refitting the first time-depth relationship based on the second average value of all velocities and the third average value of all accelerations in the second parameter value to obtain a second time-depth relationship;

[0205] A sixth module 906 for processing based on the first parameter value combined with the second average value and the third average value to obtain the relative velocity value and relative acceleration value of each well, and then fitting to obtain the fitting relationship between the relative velocity value and the relative acceleration value of all wells; the relative acceleration value represents the lateral velocity gradient;

[0206] A seventh module 907 for converting to obtain a third time-depth relationship based on the second time-depth relationship combined with the fitting relationship;

[0207] An eighth module 908 for obtaining the lateral velocity gradient of each well based on the time-depth data corresponding to the seismic horizon after horizon calibration according to the third time-depth relationship; compiling a lateral velocity gradient trend map according to the lateral velocity gradient corresponding to each well in the target oilfield;

[0208] A ninth module 909 for substituting the single-layer reflection time of the seismic layer and the lateral velocity gradient trend map into the third time-depth relationship to convert and obtain the depth structure map of the target oilfield.

[0209] In some embodiments, the apparatus may further include:

[0210] A tenth module, configured to set a preset time-depth relationship according to the principle of the seismic reflection traveltime curve;

[0211] wherein, the expression of the preset time-depth relationship is:

[0212] D = A W T 2 + B W T + C W ;

[0213] wherein, D represents depth; A W represents acceleration; T represents one-way travel time; B W represents velocity; C W represents intercept.

[0214] In some embodiments, the apparatus may further include:

[0215] An eleventh module, configured to perform three-dimensional seismic data tracing and interpretation on the horizons of the seismic layer to obtain a two-layer reflection time structure map of the seismic layer;

[0216] A twelfth module, configured to divide the grid of the two-layer reflection time structure map by 2 to obtain the single-layer reflection time.

[0217] The content of the method embodiments of the present invention is applicable to the apparatus embodiments of the present invention. The functions specifically implemented by the apparatus embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method embodiments.

[0218] On the other hand, an embodiment of the present invention further provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the above lateral velocity analysis and structure mapping method is implemented. The electronic device may be any intelligent terminal including a tablet computer, an in-vehicle computer, etc.

[0219] It can be understood that the content in the above method embodiments is applicable to the device embodiments of the present invention. The functions specifically implemented by the device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method embodiments.

[0220] As Figure 10 shown, Figure 10 schematically shows the hardware structure of an electronic device 1000 according to another embodiment. The electronic device 1000 includes:

[0221] The processor 1001 can be implemented in the form of a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present invention;

[0222] The memory 1002 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM), etc. The memory 1002 can store an operating system and other application programs. When implementing the technical solutions provided in the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 1002 and are called by the processor 1001 to execute the network node population optimization method of the embodiments of the present invention;

[0223] The input / output interface 1003 is used to implement information input and output;

[0224] The communication interface 1004 is used to implement communication interaction between this device and other devices, and can communicate through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.);

[0225] The bus 1005 transmits information between the various components of the device (such as the processor 1001, the memory 1002, the input / output interface 1003, and the communication interface 1004);

[0226] Among them, the processor 1001, the memory 1002, the input / output interface 1003, and the communication interface 1004 achieve communication connections with each other inside the device through the bus 1005.

[0227] The above-described embodiments of the electronic device are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0228] The content of the method embodiments of the present invention is applicable to the embodiments of this electronic device. The functions specifically implemented by the embodiments of this electronic device are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method.

[0229] On the other hand, an embodiment of the present invention also provides a computer-readable storage medium storing a program, which when executed by a processor implements the foregoing method.

[0230] It should be noted that the computer-readable medium shown in the embodiments of the present invention may be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0231] The content of the method embodiments of the present invention is applicable to the embodiments of this computer-readable storage medium. The functions specifically implemented by the embodiments of this computer-readable storage medium are the same as those of the foregoing method embodiments, and the beneficial effects achieved are also the same as those of the foregoing methods.

[0232] An embodiment of the present invention also discloses a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. The processor of a computer device can read the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, causing the computer device to execute the foregoing method.

[0233] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code, and the above-mentioned module, segment of a program, or part of code contains 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 that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, as well as combinations of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0234] It should be noted that although several modules of devices for action execution are mentioned in the above detailed description, such a division is not mandatory. In fact, according to the embodiments of the present invention, the features and functions of two or more of the above-mentioned modules or units can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0235] Through the description of the above embodiments, those skilled in the art can easily understand that the example embodiments described herein can be implemented by software, or can be implemented by a combination of software and necessary hardware. Therefore, the technical solutions according to the embodiments of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present invention.

[0236] In some alternative embodiments, the functions / operations mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the functions / operations involved, two consecutive blocks shown may actually be executed substantially simultaneously or the blocks can sometimes be executed in the reverse order. In addition, the embodiments presented and described in the flowcharts of the present invention are provided by way of example for the purpose of providing a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logical flows presented herein. Alternative embodiments are foreseeable, in which the order of various operations is changed and the sub-operations described as part of a larger operation are executed independently.

[0237] In addition, although the present invention has been described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and / or features may be integrated in a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It should also be understood that a detailed discussion of the actual implementation of each module is not necessary for understanding the present invention. Rather, given the attributes, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the modules will be understood within the ordinary skills of an engineer. Thus, those skilled in the art can implement the present invention as set forth in the claims without undue experimentation. It should also be understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0238] If a function is implemented in the form of a software functional unit and sold or used as an independent product, it may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, may be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0239] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definitional sequence of executable instructions for implementing logical functions, which can be specifically implemented in any computer-readable medium for use by an instruction execution apparatus, device, or equipment (such as a computer-based device, a device including a processor, or other devices that can fetch and execute instructions from the instruction execution apparatus, device, or equipment), or in combination with these instruction execution apparatuses, devices, or equipment. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution apparatus, device, or equipment.

[0240] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection (electronic device) having one or more wirings, a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable media can even be paper or other suitable media on which a program can be printed, as the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or, if necessary, other suitable processing, and then storing it in a computer memory.

[0241] It should be understood that various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution device. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0242] In the description of this specification, the description referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc., means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0243] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the claims and their equivalents.

[0244] The above has specifically described the preferred embodiments of the present invention, but the present invention is not limited to the embodiments. Those skilled in the art can also make various equivalent deformations or substitutions without departing from the spirit of the present invention, and these equivalent deformations or substitutions are all included within the scope defined by the claims of the present invention.

Claims

1. A method for lateral velocity analysis and structural mapping, characterized in that: The following steps are involved: Obtain time-depth data for each well in the target oil field; Fitting the time-depth data based on a preset time-depth relationship to obtain a first parameter value of a time-depth parameter of each well in the preset time-depth relationship; wherein the time-depth parameter includes one-way travel time, acceleration, velocity, intercept and depth; Refitting the preset time-depth relationship based on a first average value of all the intercepts in the first parameter value to obtain a first time-depth relationship; Fitting the time-depth data based on the first time-depth relationship to obtain a second parameter value of the time-depth parameter of each well in the first time-depth relationship; refitting the first time-depth relationship based on a second average value of all the velocities and a third average value of all the accelerations in the second parameter value to obtain a second time-depth relationship; Based on the first parameter value combined with the second average value and the third average value, the velocity relative value and the acceleration relative value of each well are obtained, and then the fitting relationship between the velocity relative value and the acceleration relative value of all the wells is obtained by fitting; the acceleration relative value represents the lateral velocity gradient; Based on the second time-depth relationship and the fitting relationship, a third time-depth relationship is obtained; Based on the third time-depth relationship, the lateral velocity gradient of each well is obtained by using the time-depth data corresponding to the seismic horizon after horizon calibration; a lateral velocity gradient trend graph is compiled according to the lateral velocity gradient corresponding to each well in the target oil field; The single-layer reflection time of the seismic layer and the lateral velocity gradient trend diagram are substituted into the third time-depth relationship to obtain a depth structure map of the target oil field.

2. The lateral velocity analysis and structure mapping method according to claim 1, characterized in that: The method further comprises the following steps: According to the principle of seismic reflection time-distance curve, the preset time-depth relationship is set; The expression of the preset time-depth relationship is: D=A W T 2 +B W T+C W ; Where D represents depth; A W represents acceleration; T represents one-way travel time; B W Indicates speed; C W represents the intercept.

3. The lateral velocity analysis and structure mapping method according to claim 1, characterized in that: The step of refitting the preset time-depth relationship based on a first average value of all the intercepts in the first parameter value to obtain a first time-depth relationship comprises the following steps: Obtaining an average error of all the wells in fitting the time-depth data based on a preset time-depth relationship; Obtaining an intercept setting value according to the first average value and the average error setting; Substituting the intercept setting value into the intercept of the preset time-depth relationship to obtain the first time-depth relationship; the intercept in the time-depth parameter of the first time-depth relationship is fixed to the intercept setting value; The expression of the first time-depth relationship is: D=A W T 2 +B W T+C 平均 ; Where D represents depth; A W represents acceleration; T represents one-way travel time; B W Indicates speed; C 平均 Indicates the intercept setting value.

4. The lateral velocity analysis and structure mapping method according to claim 1, characterized in that: The step of refitting the first time-depth relationship based on the second average value of all the velocities and the third average value of all the accelerations in the second parameter value to obtain a second time-depth relationship comprises the following steps: Substituting the second average value into the velocity of the first time-depth relationship, and substituting the third average value into the acceleration of the first time-depth relationship, to obtain the second time-depth relationship; the velocity in the time-depth parameters of the second time-depth relationship is fixed to the second average value, and the acceleration is fixed to the third average value; The expression of the second time-depth relationship is: D=A REF T 2 +B REF T+C 平均 ; Where D represents depth; A REF represents the third average value; T represents the one-way travel time; B REF represents the second average value; C 平均 Indicates the intercept setting value preset based on the first mean value.

5. The lateral velocity analysis and structure mapping method according to claim 1, characterized in that: The process of obtaining the velocity relative value and the acceleration relative value of each well based on the first parameter value combined with the second average value and the third average value, and then fitting to obtain the fitting relationship between the velocity relative value and the acceleration relative value of all the wells, comprises the following steps: Obtaining the relative velocity value of each well according to the ratio of the velocity of each well in the first parameter value to the second average value; Obtaining the acceleration relative value of each of the wells according to the ratio of the acceleration of each of the wells in the first parameter value to the third average value; According to the relative velocity values ​​and the relative acceleration values ​​corresponding to all the wells, a fitting relationship between the relative velocity values ​​and the relative acceleration values ​​of all the wells is obtained; Wherein, the expression of the fitting relationship is: B W / B REF =X1(A W / A REF ) 2 -X2(A W / A REF )+X3; Among them, B W Indicates speed; B REF Indicates the second average value; A W Indicates acceleration; A REF represents the third mean value; X1, X2, and X3 represent fitting parameter values.

6. The lateral velocity analysis and structure mapping method according to claim 1, characterized in that: The converting the second time-depth relationship into a third time-depth relationship based on the second time-depth relationship combined with the fitting relationship comprises the following steps: Based on the velocity relative value and the acceleration relative value, converting the second time-depth relationship to obtain a converted time-depth relationship of any of the wells; Substituting the fitting relationship into the converted time-depth relationship to obtain the third time-depth relationship; The expression of the second time-depth relationship is: D = A REF T 2 +B REF T+C 平均 ; D stands for depth; A REF represents the third average value; T represents the one-way travel time; B REF represents the second average value; C 平均 represents an intercept setting value preset based on the first mean value; The expression of the conversion time-depth relationship is: D = A REF (A W / A REF )T 2 +(B REF B W / B REF )T+C 平均 ; B W Indicates speed, B REF represents the second average value, B W / B REF Indicates the relative value of speed; A W represents acceleration, A REF represents the third average value, A W / A REF Indicates the relative value of acceleration; The expression of the conversion time-depth relationship is: W / B REF =X1(A W / A REF ) 2 -X2(A W / A REF )+X3; X1, X2 and X3 represent the fitting parameter values; The expression of the third time-depth relationship is: D=A REF (A W / A REF )T 2 +B REF [X1(A W / A REF ) 2 -X2(A W / A REF )+X3]T+C 平均 。 7. The lateral velocity analysis and structure mapping method according to claim 1, characterized in that: The method of obtaining the lateral velocity gradient of each well based on the third time-depth relationship by using the time-depth data corresponding to the seismic horizon after horizon calibration comprises the following steps: The time and depth corresponding to the seismic layer after layer calibration are obtained, and then substituted into the third time-depth relationship for inverse solution to obtain the lateral velocity gradient of each well.

8. The lateral velocity analysis and structure mapping method according to claim 1, characterized in that: The method further comprises the following steps: Conducting three-dimensional seismic data tracking and interpretation on the layers of the seismic layer to obtain a double-layer reflection time structure map of the seismic layer; The grid of the double-layer reflection time structure diagram is divided by 2 to obtain the single-layer reflection time.

9. A lateral velocity analysis and structure mapping device, characterized in that: include: The first module is used to obtain the time-depth data of each well in the target oil field; The second module is used to fit the time-depth data based on a preset time-depth relationship to obtain a first parameter value of the time-depth parameter of each well in the preset time-depth relationship; wherein the time-depth parameter includes one-way travel time, acceleration, velocity, intercept and depth; A third module is used to refit the preset time-depth relationship based on a first average value of all the intercepts in the first parameter value to obtain a first time-depth relationship; A fourth module is used to fit the time-depth data based on the first time-depth relationship to obtain a second parameter value of the time-depth parameter of each well in the first time-depth relationship; A fifth module, configured to refit the first time-depth relationship based on a second average value of all the velocities and a third average value of all the accelerations in the second parameter value to obtain a second time-depth relationship; A sixth module is used to obtain a velocity relative value and an acceleration relative value of each well based on the first parameter value combined with the second average value and the third average value, and then fit to obtain a fitting relationship between the velocity relative value and the acceleration relative value of all the wells; the acceleration relative value represents a lateral velocity gradient; A seventh module is used to convert the second time-depth relationship into a third time-depth relationship based on the second time-depth relationship combined with the fitting relationship; The eighth module is used to obtain the lateral velocity gradient of each well based on the third time-depth relationship by using the time-depth data corresponding to the seismic horizon after horizon calibration; and to compile a lateral velocity gradient trend diagram according to the lateral velocity gradient corresponding to each well in the target oil field; The ninth module is used to substitute the single-layer reflection time of the seismic layer and the lateral velocity gradient trend diagram into the third time-depth relationship to convert and obtain a depth structure diagram of the target oil field.

10. A computer storage medium storing a program executable by a processor, characterized in that: The program executable by the processor is used to implement the method according to any one of claims 1 to 7 when executed by the processor.

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