CN107229075A - Method and device for determining depth domain seismic wavelets - Google Patents
Method and device for determining depth domain seismic wavelets Download PDFInfo
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Abstract
The embodiment of the application provides a method and a device for determining depth domain seismic wavelets, wherein the method comprises the following steps: acquiring acoustic logging data, and respectively determining a depth domain reflection coefficient sequence and depth domain imaging data of a well position according to the acoustic logging data; and determining depth domain seismic wavelets according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well position. According to the scheme, a matrix equation is constructed according to the depth domain reflection coefficient sequence and the depth domain imaging data, the depth domain imaging data are used as expected output, and the optimal matching operator based on the depth domain reflection coefficient sequence is used as the depth domain seismic wavelet. Therefore, the technical problems that the depth domain seismic wavelet cannot be directly solved, the determining process is complex, and the determined depth domain seismic wavelet is poor in accuracy in the existing depth domain seismic wavelet determining method are solved, and the technical effect of accurately, simply and conveniently determining the depth domain seismic wavelet is achieved.
Description
Technical Field
The application relates to the technical field of oil and gas exploration, in particular to a method and a device for determining depth domain seismic wavelets.
Background
Seismic wavelets, and in particular depth domain seismic wavelets, are an important type of seismic data in oil and gas exploration. In general, a seismic wavelet refers to a piece of signal that has a certain start time, is finite in energy, and has a certain duration. Which is the basic unit in seismic recording. It is generally considered that the seismic wave generated by the seismic source excitation is only a sharp pulse with extremely short duration, and as the sharp pulse propagates in a viscoelastic medium, the high-frequency component of the sharp pulse is attenuated quickly, and the waveform grows, so that a seismic wavelet is formed and then propagates underground in the form of the seismic wavelet. Due to the above-mentioned characteristics of seismic wavelets, it is often desirable to use depth-domain seismic wavelets in implementations. For example, in the analysis of forward problems, it is necessary to generate simulation data by combining a wave equation or convolution model with depth domain seismic wavelets, so as to obtain a synthetic record, and the synthetic record is used as a guide to perform specific oil and gas exploration or reservoir prediction. Therefore, how to accurately determine the depth domain seismic wavelets has been a concern.
The existing depth domain seismic wavelet determining method cannot directly extract depth domain seismic wavelets, and usually the time domain seismic wavelets are obtained firstly and then converted into the depth domain seismic wavelets according to the convolution theorem. However, in practical implementation, the convolution of the depth domain seismic wavelet and the reflection coefficient does not satisfy the convolution theorem, that is, the characteristic that the wavelet is changed with the depth gradually cannot be satisfied. Therefore, when the existing depth domain seismic wavelet determining method is implemented specifically, the technical problems that the depth domain seismic wavelet cannot be directly determined, the accuracy of the determined depth domain seismic wavelet is poor, and the determining process is complex often exist.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the application provides a method and a device for determining depth domain seismic wavelets, and aims to solve the technical problems that the depth domain seismic wavelets cannot be directly determined, the accuracy of the determined depth domain seismic wavelets is poor, and the determination process is complex in the existing method for determining the depth domain seismic wavelets.
The embodiment of the application provides a method for determining depth domain seismic wavelets, which comprises the following steps:
acquiring acoustic logging data of a region to be measured;
determining a depth domain reflection coefficient sequence and depth domain imaging data of a well position according to the acoustic logging data;
and determining depth domain seismic wavelets according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well position.
In one embodiment, determining a depth domain reflection coefficient sequence from sonic logging data comprises:
acquiring speed field data and density field data according to the acoustic logging data;
and determining the depth domain reflection coefficient sequence according to the speed field data and the density field data.
In one embodiment, determining the sequence of depth domain reflection coefficients from the velocity field data and the density field data comprises: determining the depth domain reflection coefficient sequence according to the following formula:
wherein R isd(zi) Depth domain reflection coefficient, upsilon (z) of the ith sampling point in the depth domain reflection coefficient sequencei) Velocity field data for the ith sample point in the velocity field data, ρ (z)i) Density field data for the ith sample point in the density field data, ziThe depth value of the ith sampling point in the logging data is shown, and i is the number of the sampling point in the depth direction in the logging data.
In one embodiment, determining a depth domain seismic wavelet from the sequence of depth domain reflection coefficients and depth domain imaging data for the well location comprises:
determining an autocorrelation parameter of the depth domain reflection coefficient sequence according to the depth domain reflection coefficient sequence;
determining a cross-correlation parameter of the depth domain reflection coefficient sequence and the depth domain imaging data according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well position;
and determining a matching operator according to the autocorrelation parameters and the cross-correlation parameters, and taking the matching operator as the depth domain seismic wavelets.
In one embodiment, determining the autocorrelation parameter of the depth-domain reflection coefficient sequence based on the depth-domain reflection coefficient sequence comprises: the autocorrelation parameters are determined according to the following formula:
wherein,is the autocorrelation parameter, R, of the ith sample pointd(n) is the depth domain reflection coefficient at depth n, Rd(n+zi) The depth domain reflection coefficient when the depth is the sum of the depth of the ith sampling point and n, wherein n is a depth variable and is a natural number in the range of 1 to l, and z isiIs the depth value of the ith sampling point in the logging data, and l is the length of the operator.
In one embodiment, determining a cross-correlation parameter for a depth domain reflection coefficient sequence and depth domain imaging data from the depth domain reflection coefficient sequence and depth domain imaging data for the well location comprises: determining the cross-correlation parameter according to the following formula:
wherein, muRx(zi) Is the cross-correlation parameter, x, of the ith sample pointd(n) is imaging data at depth n, Rd(n + z) is a depth domain reflection coefficient when the depth is the sum of the depth of the ith sampling point and n, n is a depth variable and is a natural number with the value ranging from 1 to l, and z isiIs the depth value of the ith sampling point in the logging data, and l is the length of the operator.
In one embodiment, determining a match operator from the autocorrelation parameters and the cross-correlation parameters comprises:
constructing a solving matrix equation according to the autocorrelation parameters and the cross-correlation parameters;
and determining the matching operator by solving the solving matrix equation.
In one embodiment, constructing a solution matrix equation based on the autocorrelation parameters and the cross-correlation parameters comprises:
according to the autocorrelation parameters and the cross-correlation parameters, the following equations are constructed as the solving matrix equation:
wherein,is an autocorrelation parameter at a depth of z, muRx(z) is the cross-correlation parameter at depth z, wd(z) is a matching operator when the depth is z, l is the length of the matching operator, z is the depth, and the value of z is a natural number in the range of 0 to l.
In one embodiment, after determining the depth domain seismic wavelet, the method further comprises:
according to the depth domain seismic wavelets, inversion processing is carried out on prestack depth migration data to obtain a processing result;
and carrying out oil and gas exploration according to the processing result.
Based on the same inventive concept, the embodiment of the present application further provides a device for determining depth domain seismic wavelets, including:
the acquisition module is used for acquiring acoustic logging data of a region to be measured;
the first determination module is used for determining a depth domain reflection coefficient sequence and depth domain imaging data of a well position according to the acoustic logging data;
and the second determination module is used for determining the depth domain seismic wavelet according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well position.
In one embodiment, the first determining module comprises:
the acquisition unit is used for acquiring speed field data and density field data according to the acoustic logging data;
a first determination unit to determine the depth domain reflection coefficient sequence and depth domain imaging data of the well location from the velocity field data and the density field data.
In one embodiment, the second determining module comprises:
a second determining unit, configured to determine an autocorrelation parameter of the depth-domain reflection coefficient sequence according to the depth-domain reflection coefficient sequence;
a third determining unit, configured to determine, according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well location, a cross-correlation parameter between the depth domain reflection coefficient sequence and the depth domain imaging data;
and the fourth determining unit is used for determining a matching operator according to the autocorrelation parameter and the cross-correlation parameter, and taking the matching operator as the depth domain seismic wavelet.
In the embodiment of the application, a depth domain reflection coefficient sequence and depth domain imaging data of a well position are respectively determined through acoustic logging data; and further determining depth domain seismic wavelets according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well position. Therefore, the technical problems that the depth domain seismic wavelet cannot be directly solved, the determining process is complex, and the determined depth domain seismic wavelet is poor in accuracy in the existing depth domain seismic wavelet determining method are solved, and the technical effect of accurately and simply determining the depth domain seismic wavelet is achieved.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort.
FIG. 1 is a process flow diagram of a method of determining depth domain seismic wavelets in accordance with an embodiment of the present application;
FIG. 2 is a block diagram of the components of a depth domain seismic wavelet determination apparatus according to an embodiment of the present application;
FIG. 3 is a graphical illustration of depth domain reflection coefficients from well data acquired in one example scenario;
FIG. 4 is a schematic diagram of time domain imaging acquired in one example of a scene;
FIG. 5 is a schematic diagram of a depth domain wavelet obtained in an example scenario;
FIG. 6 is a schematic diagram of a depth domain equivalent wavelet synthetic record obtained in one example scenario;
FIG. 7 is a schematic diagram of a comparison of a depth domain equivalent wavelet synthesis record and a time-depth transition record obtained in one example scenario.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Considering that the existing depth domain seismic wavelet determination method generally acquires the time domain seismic wavelet first and then converts the time domain seismic wavelet into the depth domain seismic wavelet. However, the convolution of the wavelet and the reflection coefficient does not satisfy the convolution theorem. Therefore, when the method for converting the time domain seismic wavelet into the depth domain seismic wavelet is implemented, the technical problems that the depth domain seismic wavelet cannot be directly obtained, the determining process is complex, and the accuracy of the determined depth domain seismic wavelet is poor often exist. Aiming at the root cause of the technical problems, the depth domain reflection coefficient sequence and the depth domain imaging data can be obtained firstly according to the logging data, and then the matching operator is obtained as the depth domain seismic wavelet according to the depth domain reflection coefficient sequence and the depth domain imaging data. Namely, the depth domain seismic wavelets can be determined directly from the depth domain seismic data. Therefore, the technical problems that the depth domain seismic wavelet cannot be directly solved, the determining process is complex, and the determined depth domain seismic wavelet is poor in accuracy in the existing depth domain seismic wavelet determining method are solved, and the technical effect of accurately and simply determining the depth domain seismic wavelet is achieved.
Based on the thought, the embodiment of the application provides a method for determining depth domain seismic wavelets. Please refer to fig. 1, which is a flowchart illustrating a method for determining depth-domain seismic wavelets according to an embodiment of the present application. The method for determining the depth domain seismic wavelet provided by the embodiment of the application specifically comprises the following steps.
Step 101: and acquiring acoustic logging data of the area to be measured.
In this embodiment, the acoustic logging data may be one of logging data. In particular, the sonic logging data may further include: velocity field data and density field data, etc.
Step 102: and determining a depth domain reflection coefficient sequence and depth domain imaging data of the well position according to the acoustic logging data.
In one embodiment, in order to be able to determine the depth domain imaging data of the depth domain reflection coefficient sequence and the well location separately, the following steps may be performed in practice.
S102-1: and determining a depth domain reflection coefficient sequence according to the acoustic logging data.
In one embodiment, to obtain the depth domain reflection coefficient sequence, the depth domain reflection coefficient sequence may be determined by determining each depth domain reflection coefficient in the following manner.
S102-1-1: acquiring speed field data and density field data according to the acoustic logging data;
s102-1-2: and determining the depth domain reflection coefficient sequence according to the speed field data and the density field data.
In one embodiment, in implementation, the depth-domain reflection coefficients may be determined by determining each depth-domain reflection coefficient from the velocity field data and the density field data according to the following formula, and further determining the depth-domain reflection coefficient sequence.
Wherein R isd(zi) Depth domain reflection coefficient, upsilon (z) of the ith sampling point in the depth domain reflection coefficient sequencei) Velocity field data for the ith sample point in the velocity field data, ρ (z)i) Density field data for the ith sample point in the density field data, ziThe depth value of the ith sampling point in the logging data is shown, and i is the number of the sampling point in the depth direction in the logging data.
In the present embodiment, after obtaining the reflection coefficients of each depth domain according to the above formula, the obtained reflection coefficients of a plurality of depth domains are combined into a depth domain reflection coefficient sequence. The depth domain reflection coefficient sequence may be specifically represented by the following manner: rd(z)，z＝z1,z2...zi...znWherein z isiIs the corresponding depth.
In the embodiment, the number of the sampling points can be flexibly set according to specific conditions and construction requirements. For example, the depth direction of the log is 3000 meters, and every 4 meters can be used as a sampling interval. Thus, there are a total of 750 sampling points, i.e., i can be a natural number from 1 to 750.
S102-2: from the sonic logging data, depth domain imaging data of the well location is determined.
In one embodiment, when implemented, depth domain imaging data for a well location may be determined from well log data. Wherein, the well can be a well arranged on the site during specific construction. Correspondingly, the well position is the position of the well determined after the well is set on the site during specific construction. The depth field imaging data of the well location may be specifically represented in the following manner: x is the number ofd(z)，z＝z1,z2...zi...znWherein z isiIs the corresponding depth.
Step 103: and determining depth domain seismic wavelets according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well position.
In one embodiment, in order to avoid an error caused by determining a time domain seismic wavelet first and then converting the time domain seismic wavelet into a depth domain seismic wavelet, the present application provides that the depth domain seismic wavelet may be directly determined according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well location. In specific implementation, the method can be performed according to the following steps.
S103-1: and determining the autocorrelation parameters of the depth domain reflection coefficient sequence according to the depth domain reflection coefficient sequence.
In one embodiment, in order to determine the autocorrelation parameter of the depth domain reflection coefficient sequence, in particular, the autocorrelation parameter of the reflection coefficient sequence may be calculated according to the following formula:
wherein,is the autocorrelation parameter, R, of the ith sample pointd(n) is the depth domain reflection coefficient at depth n, Rd(n+zi) The depth domain reflection coefficient when the depth is the sum of the depth of the ith sampling point and n, wherein n is a depth variable and takes a natural number (including 1 and l) in a range from 1 to l, and ziIs the depth value of the ith sampling point in the logging data, and l is the length of the operator.
S103-2: and determining the cross-correlation parameters of the depth domain reflection coefficient sequence and the depth domain imaging data according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well position.
In an embodiment, in order to determine the cross-correlation parameter between the depth-domain reflection coefficient sequence and the depth-domain imaging data, in a specific implementation, the cross-correlation parameter between the depth-domain reflection coefficient sequence and the depth-domain imaging data may be calculated according to the following formula:
wherein, muRx(zi) Is the cross-correlation parameter, x, of the ith sample pointd(n) is imaging data at depth n, Rd(n + z) is a depth domain reflection coefficient when the depth is the sum of the depth of the ith sampling point and n, n is a depth variable and is a natural number (including 1 and l) in the range of 1 to l, and z isiIs the depth value of the ith sampling point in the logging data, and l is the length of the operator.
S103-3: and determining a matching operator according to the autocorrelation parameters and the cross-correlation parameters, and taking the matching operator as the depth domain seismic wavelets.
In one embodiment, in order to directly determine the depth domain seismic wavelet, in a specific implementation, an optimal matching operator of the depth domain reflection coefficient sequence based on the well data and taking the depth domain imaging data as an expected output may be obtained according to the calculated autocorrelation parameter of the depth domain reflection coefficient sequence, the calculated depth domain reflection coefficient sequence, and the cross-correlation parameter of the depth domain imaging data. I.e., depth domain seismic wavelets are determined directly from depth domain data. Wherein the operator can be regarded as a depth domain equivalent wavelet in the least squares sense. Thus, this operator may be treated as the depth domain seismic wavelet described above. It should be noted that, in the determination method provided in the embodiment of the present application, based on an optimal matching algorithm, a wavelet obtained by convolving a wavelet with a reflection coefficient under an optimal matching condition with a depth domain seismic trace is used as an optimal depth domain seismic wavelet. Therefore, the obtained seismic domain wavelet can be better suitable for synthesis and recording in the later period to make synthetic inversion, namely the depth domain seismic wavelet can be used for obtaining a more accurate processing result.
In an embodiment, in order to determine the matching operator, when implemented, the following steps may be performed:
s103-3-1: constructing a solving matrix equation according to the autocorrelation parameters and the cross-correlation parameters;
s103-3-2: and determining the matching operator by solving the solving matrix equation.
In an embodiment, constructing a solution matrix equation according to the autocorrelation parameter and the cross-correlation parameter may specifically include the following:
according to the autocorrelation parameters and the cross-correlation parameters, the following equations are constructed as the solving matrix equation:
wherein,is an autocorrelation parameter at a depth of z, muRx(z) is the cross-correlation parameter at depth z, wdAnd (z) is a matching operator when the depth is z, l is the length of the matching operator (namely the depth domain seismic wavelet wavelength), z is the depth, and the value of z is a natural number in the range of 0 to l.
In one embodiment, after the solution matrix equation is constructed, in order to improve the solution rate, the purpose of rapidly solving the equation to determine the corresponding matching operator is achieved. In specific implementation, the solving matrix equation can be solved by calculation methods such as a recursion algorithm and the like. Specifically, for example, the solved matrix equation may be solved by a levenson (Levinson) fast recursion algorithm, and the matching operator may be obtained as the depth domain seismic wavelet. Of course, in the specific implementation, an algorithm other than the levenson algorithm listed above may be selected to solve the above equation according to the specific situation and implementation conditions. The present application is not limited thereto.
In one embodiment, after the depth domain seismic wavelets are determined, the hydrocarbon survey may be further conducted. In specific implementation, the method may further include the following steps.
S104-1: according to the depth domain seismic wavelets, inversion processing is carried out on prestack depth migration data to obtain a processing result;
s104-2: and carrying out oil and gas exploration according to the processing result.
In the embodiment, after the pre-stack depth migration data is inverted according to the depth domain seismic wavelet to obtain the processing result, the processing result can be used as a guide basis for oil and gas exploration, and the processing result can be used as a reference basis for concrete construction such as reservoir prediction.
In the embodiment of the application, compared with the existing method, the depth domain reflection coefficient sequence and the depth domain imaging data of the well position are respectively determined according to the acoustic logging data; and further determining depth domain seismic wavelets according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well position. Namely, the depth domain seismic wavelets are determined directly according to the depth domain seismic data. Therefore, the technical problems that the depth domain seismic wavelet cannot be directly solved, the determining process is complex, and the determined depth domain seismic wavelet is poor in accuracy in the existing depth domain seismic wavelet determining method are solved, and the technical effect of accurately and simply determining the depth domain seismic wavelet is achieved.
Based on the same inventive concept, the embodiment of the invention also provides a device for determining the depth domain seismic wavelet, which is described in the following embodiment. Because the principle of solving the problems by the device is similar to the method for determining the depth domain seismic wavelets, the implementation of the device can refer to the implementation of the method for determining the depth domain seismic wavelets, and repeated parts are not repeated. As used hereinafter, the term "unit" or "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated. Referring to fig. 2, a structural diagram of an apparatus for determining depth domain seismic wavelets according to an embodiment of the present application may specifically include: the acquiring module 201, the first determining module 202, and the second determining module 203, which will be described in detail below.
The acquiring module 201 may be specifically configured to acquire acoustic logging data of an area to be measured;
the first determining module 202 may be specifically configured to determine a depth domain reflection coefficient sequence and depth domain imaging data of a well location according to the acoustic logging data;
the second determining module 203 may be specifically configured to determine a depth domain seismic wavelet according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well location.
In an embodiment, in order to determine the depth domain reflection coefficient sequence, in a specific implementation, the first determining module 202 may specifically include the following units.
The acquisition unit is specifically used for acquiring speed field data and density field data according to the acoustic logging data;
the first determination unit may be specifically configured to determine the depth domain reflection coefficient sequence and the depth domain imaging data of the well location from the velocity field data and the density field data.
In one embodiment, in order to determine the depth-domain seismic wavelet according to the depth-domain seismic data, in a specific implementation, the second determining module 203 may specifically include the following units.
The second determining unit may be specifically configured to determine an autocorrelation parameter of the depth-domain reflection coefficient sequence according to the depth-domain reflection coefficient sequence;
a third determining unit, which may be specifically configured to determine, according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well location, a cross-correlation parameter between the depth domain reflection coefficient sequence and the depth domain imaging data;
the fourth determining unit may be specifically configured to determine a matching operator according to the autocorrelation parameter and the cross-correlation parameter, and use the matching operator as the depth-domain seismic wavelet.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
It should be noted that, the systems, devices, modules or units described in the above embodiments may be implemented by a computer chip or an entity, or implemented by a product with certain functions. For convenience of description, in the present specification, the above devices are described as being divided into various units by functions, and are described separately. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing the present application.
Moreover, in the subject specification, adjectives such as first and second may only be used to distinguish one element or action from another element or action without necessarily requiring or implying any actual such relationship or order. References to an element or component or step (etc.) should not be construed as limited to only one of the element, component, or step, but rather to one or more of the element, component, or step, etc., where the context permits.
From the above description, it can be seen that the depth domain seismic wavelet determining method and apparatus provided by the embodiment of the present application respectively determine a depth domain reflection coefficient sequence and depth domain imaging data of a well position according to acoustic logging data; and further determining depth domain seismic wavelets according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well position. Therefore, the technical problems that the depth domain seismic wavelet cannot be directly solved, the determining process is complex, and the determined depth domain seismic wavelet is poor in accuracy in the existing depth domain seismic wavelet determining method are solved, and the technical effect of accurately and simply determining the depth domain seismic wavelet is achieved. And the matching operator is solved by utilizing the Levenson recursion algorithm, so that the solving speed is improved, and the technical effect of quickly and simply solving the depth domain seismic wavelet is achieved.
In a specific implementation scenario, the depth domain seismic wavelet determination method/device provided by the application is used for extracting the depth domain seismic wavelet of a certain area. Specific implementations can be performed with reference to the following.
Step (1): calculating a depth domain reflection coefficient sequence based on the well data by using the velocity field data v (z) and the density field data rho (z) of the acoustic logging data:Rd(z),z＝z1,z2,…,znwherein z represents depth. And in particular to the depth domain reflection coefficient plot of figure 3 derived from well data acquired in one example scenario.
Step (2): selecting depth domain imaging data at the well location: x is the number ofd(z),z＝z1,z2,…,zn。
And (3): calculating a depth domain reflection coefficient sequence Rd(z) the auto-correlation of the (z),(i.e. the autocorrelation parameters of the depth-domain sequence of reflection coefficients).
And (4): calculating a depth domain reflection coefficient sequence Rd(z) and depth domain imaging data xd(z) cross correlation μRx(0),μRx(1),…,μRx(l) (i.e., the cross-correlation parameter of the depth-domain sequence of reflection coefficients with the depth-domain imaging data).
And (5): in specific implementation, the autocorrelation of the depth domain reflection coefficient sequence calculated in step (3) can be further usedCross-correlating mu with the depth domain reflection coefficient sequence and the depth domain imaging data calculated in step (4)Rx(0),μRx(1),…,μRx(l) Finding out depth-domain imaging data xd(z) a depth domain reflection coefficient sequence R based on well data for a desired outputd(z) best match operator wd(z), the operator is the depth domain equivalent wavelet under the least square meaning, namely the depth domain seismic wavelet.
During the specific construction, the steel plate is placed in a steel plate,
the calculation method of the step (1) is as follows:
depth ziCoefficient of reflection Rd(zi) Can be calculated from the velocity field v (z) and the density field ρ (z)To, it is expressed as:
the calculation method of the step (3) is as follows:
depth domain reflection coefficient sequence RdThe autocorrelation calculation of (z) can be expressed as:
the calculation method of the step (4) is as follows:
depth domain reflection coefficient sequence Rd(z) and depth domain imaging data xdThe cross-correlation calculation of (z) can be expressed as:
the calculation method of the step (5) is as follows:
for solving the depth domain equivalent wavelet w in the least square sensed(z) obtained by the steps (3) and (4)And muRx(z) constructing a matrix equation expression as follows:
it should be noted that the above matrix equation can be solved by a Levinson fast recursion algorithmdAnd (z) obtaining the depth seismic wavelet, wherein the wave length of the depth domain seismic wavelet is l. And the time domain seismic wavelets extracted by the prior art method, see FIG. 4 for acquisition in one scenario exampleThe time domain imaging schematic diagram of (1) is compared with the depth domain seismic wavelet determined by the depth domain seismic wavelet determining method/device of the present embodiment, with reference to the depth domain wavelet schematic diagram of fig. 5 obtained in one scene example, and it is found that the waveforms of the two are not the same. Further, a depth domain seismic wavelet synthetic record may be determined from the depth domain seismic wavelets, see FIG. 6 for a depth domain equivalent wavelet synthetic record obtained in one scenario example. See FIG. 7 for a schematic comparison of a depth domain equivalent wavelet synthetic record obtained in one scenario example with a time-depth conversion record, compared to a synthetic record via time domain seismic wavelets. The synthetic recordings determined from the depth domain seismic wavelets are more accurate.
Therefore, by the above scene example, it is verified that the method and the device for determining depth domain seismic wavelets provided by the embodiment of the present application can indeed solve the technical problems that the depth domain seismic wavelets cannot be directly obtained, the determination process is complex, and the accuracy of the determined depth domain seismic wavelets is poor in the existing method for determining depth domain seismic wavelets, and achieve the technical effect of accurately and simply determining depth domain seismic wavelets. The method has the advantages that the seismic wavelets can be directly extracted in the depth domain, the problem that the wavelets cannot be extracted from the seismic data in the depth domain is solved, and a foundation is laid for the direct application of the prestack depth domain data in the inversion aspect.
Although the present application refers to a method or apparatus for determining seismic waves in different depth domains, the present application is not limited to the cases described in the industry standards or examples, and the like, and some industry standards or implementations slightly modified based on the implementations described in the custom manner or examples may also achieve the same, equivalent or similar implementations, or the implementations expected after modification. Embodiments employing such modified or transformed data acquisition, processing, output, determination, etc., may still fall within the scope of alternative embodiments of the present application.
Although the present application provides method steps as described in an embodiment or flowchart, more or fewer steps may be included based on conventional or non-inventive means. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an apparatus or client product in practice executes, it may execute sequentially or in parallel (e.g., in a parallel processor or multithreaded processing environment, or even in a distributed data processing environment) according to the embodiments or methods shown in the figures. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the presence of additional identical or equivalent elements in a process, method, article, or apparatus that comprises the recited elements is not excluded.
The devices or modules and the like explained in the above embodiments may be specifically implemented by a computer chip or an entity, or implemented by a product with certain functions. For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, in implementing the present application, the functions of each module may be implemented in one or more pieces of software and/or hardware, or a module that implements the same function may be implemented by a combination of a plurality of sub-modules, and the like. The above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical division, and other divisions may be realized in practice, for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not executed.
Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may therefore be considered as a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, classes, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
From the above description of the embodiments, it is clear to those skilled in the art that the present application can be implemented by software plus necessary general hardware platform. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, or the like, and includes several instructions for enabling a computer device (which may be a personal computer, a mobile terminal, a server, or a network device) to execute the method according to the embodiments or some parts of the embodiments of the present application.
The embodiments in the present specification are described in a progressive manner, and the same or similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. The application is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
While the present application has been described with examples, those of ordinary skill in the art will appreciate that there are numerous variations and permutations of the present application without departing from the spirit of the application, and it is intended that the appended claims encompass such variations and permutations without departing from the present application.
Claims (12)
1. A method for determining depth-domain seismic wavelets, comprising:
acquiring acoustic logging data of a region to be measured;
determining a depth domain reflection coefficient sequence and depth domain imaging data of a well position according to the acoustic logging data;
and determining depth domain seismic wavelets according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well position.
2. The method of claim 1, wherein determining a depth domain reflection coefficient sequence from sonic logging data comprises:
acquiring speed field data and density field data according to the acoustic logging data;
and determining the depth domain reflection coefficient sequence according to the speed field data and the density field data.
3. The method of claim 2, wherein determining the sequence of depth domain reflection coefficients from the velocity field data and the density field data comprises:
determining the depth domain reflection coefficient sequence according to the following formula:
<mrow> <msup> <mi>R</mi> <mi>d</mi> </msup> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>&rho;</mi> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mi>&upsi;</mi> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>-</mo> <mi>&rho;</mi> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mrow> <mi>i</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> <mo>)</mo> </mrow> <mi>&upsi;</mi> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mrow> <mi>i</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> <mo>)</mo> </mrow> </mrow> <mrow> <mi>&rho;</mi> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mi>&upsi;</mi> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>+</mo> <mi>&rho;</mi> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mrow> <mi>i</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> <mo>)</mo> </mrow> <mi>&upsi;</mi> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mrow> <mi>i</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> </mrow>
wherein R isd(zi) Depth domain reflection coefficient, upsilon (z) of the ith sampling point in the depth domain reflection coefficient sequencei) Velocity field data for the ith sample point in the velocity field data, ρ (z)i) Density field data for the ith sample point in the density field data, ziThe depth value of the ith sampling point in the logging data is shown, and i is the number of the sampling point in the depth direction in the logging data.
4. The method of claim 1, wherein determining depth domain seismic wavelets from the sequence of depth domain reflection coefficients and depth domain imaging data for the well location comprises:
determining an autocorrelation parameter of the depth domain reflection coefficient sequence according to the depth domain reflection coefficient sequence;
determining a cross-correlation parameter of the depth domain reflection coefficient sequence and the depth domain imaging data according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well position;
and determining a matching operator according to the autocorrelation parameters and the cross-correlation parameters, and taking the matching operator as the depth domain seismic wavelets.
5. The method according to claim 4, wherein determining the autocorrelation parameters of the depth-domain sequence of reflection coefficients from the depth-domain sequence of reflection coefficients comprises: the autocorrelation parameters are determined according to the following formula:
wherein,is the autocorrelation parameter, R, of the ith sample pointd(n) is the depth domain reflection coefficient at depth n, Rd(n+zi) The depth domain reflection coefficient when the depth is the sum of the depth of the ith sampling point and n, wherein n is a depth variable and is a natural number in the range of 1 to l, and z isiIs the depth value of the ith sampling point in the logging data, and l is the length of the operator.
6. The method of claim 4, wherein determining cross-correlation parameters for the depth domain reflection coefficient sequence and depth domain imaging data from the depth domain reflection coefficient sequence and depth domain imaging data for the well location comprises: determining the cross-correlation parameter according to the following formula:
<mrow> <msub> <mi>&mu;</mi> <mrow> <mi>R</mi> <mi>x</mi> </mrow> </msub> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>=</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>n</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>l</mi> </munderover> <msup> <mi>x</mi> <mi>d</mi> </msup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <msup> <mi>R</mi> <mi>d</mi> </msup> <mrow> <mo>(</mo> <mi>n</mi> <mo>+</mo> <msub> <mi>z</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> </mrow>
wherein, muRx(zi) Is the cross-correlation parameter, x, of the ith sample pointd(n) is imaging data at depth n, Rd(n + z) is a depth domain reflection coefficient when the depth is the sum of the depth of the ith sampling point and n, n is a depth variable and is a natural number with the value ranging from 1 to l, and z isiIs the depth value of the ith sampling point in the logging data, and l is the length of the operator.
7. The method of claim 4, wherein determining a match operator from the autocorrelation parameters and the cross-correlation parameters comprises:
constructing a solving matrix equation according to the autocorrelation parameters and the cross-correlation parameters;
and determining the matching operator by solving the solving matrix equation.
8. The method of claim 7, wherein constructing a solution matrix equation from the autocorrelation parameters and the cross-correlation parameters comprises:
according to the autocorrelation parameters and the cross-correlation parameters, the following equations are constructed as the solving matrix equation:
wherein,is an autocorrelation parameter at a depth of z, muRx(z) is the cross-correlation parameter at depth z, wd(z) is a matching operator when the depth is z, l is the length of the matching operator, z is the depth, and the value of z is a natural number in the range of 0 to l.
9. The method of claim 1, wherein after determining the depth domain seismic wavelet, the method further comprises:
according to the depth domain seismic wavelets, inversion processing is carried out on prestack depth migration data to obtain a processing result;
and carrying out oil and gas exploration according to the processing result.
10. An apparatus for determining depth domain seismic wavelets, comprising:
the acquisition module is used for acquiring acoustic logging data of a region to be measured;
the first determination module is used for determining a depth domain reflection coefficient sequence and depth domain imaging data of a well position according to the acoustic logging data;
and the second determination module is used for determining the depth domain seismic wavelet according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well position.
11. The apparatus of claim 10, wherein the first determining module comprises:
the acquisition unit is used for acquiring speed field data and density field data according to the acoustic logging data;
a first determination unit to determine the depth domain reflection coefficient sequence and depth domain imaging data of the well location from the velocity field data and the density field data.
12. The apparatus of claim 10, wherein the second determining module comprises:
a second determining unit, configured to determine an autocorrelation parameter of the depth-domain reflection coefficient sequence according to the depth-domain reflection coefficient sequence;
a third determining unit, configured to determine, according to the depth domain reflection coefficient sequence and the depth domain imaging data of the well location, a cross-correlation parameter between the depth domain reflection coefficient sequence and the depth domain imaging data;
and the fourth determining unit is used for determining a matching operator according to the autocorrelation parameter and the cross-correlation parameter, and taking the matching operator as the depth domain seismic wavelet.
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