阅读说明：本技术 一种核磁共振数据反演方法、装置、存储介质及设备 (Nuclear magnetic resonance data inversion method, device, storage medium and equipment ) 是由 郭江峰 谢然红 肖立志 徐陈昱 谷明宣 吴勃翰 于 2019-09-02 设计创作，主要内容包括：本申请实施方式公开了一种核磁共振数据反演方法、装置、存储介质及设备。所述方法包括：获取核磁共振回波数据；基于向量的Lp范数,建立目标函数；其中,所述向量满足预设的约束方程,所述约束方程通过所述核磁共振回波数据确定,所述Lp范数中的参数p的取值范围为大于等于0且小于等于1；根据所述目标函数的解,生成所述核磁共振回波数据的反演谱。本申请可以提高核磁共振反演谱的分辨率。(The embodiment of the application discloses a nuclear magnetic resonance data inversion method, a nuclear magnetic resonance data inversion device, a nuclear magnetic resonance data storage medium and nuclear magnetic resonance data storage equipment. The method comprises the following steps: acquiring nuclear magnetic resonance echo data; establishing an objective function based on the Lp norm of the vector; the vector meets a preset constraint equation, the constraint equation is determined through the nuclear magnetic resonance echo data, and the value range of a parameter p in the Lp norm is more than or equal to 0 and less than or equal to 1; and generating an inversion spectrum of the nuclear magnetic resonance echo data according to the solution of the target function. The resolution of the nuclear magnetic resonance inversion spectrum can be improved.)

1. A method for inversion of nuclear magnetic resonance data, comprising:

acquiring nuclear magnetic resonance echo data;

establishing an objective function based on the Lp norm of the vector; the vector meets a preset constraint equation, the constraint equation is determined through the nuclear magnetic resonance echo data, and the value range of a parameter p in the Lp norm is more than or equal to 0 and less than or equal to 1;

and generating an inversion spectrum of the nuclear magnetic resonance echo data according to the solution of the target function.

2. The method of claim 1, wherein the objective function is:

wherein the content of the first and second substances,is the Lp norm of the vector; the vector s is a solution of the objective function, and all elements in the vector s are more than or equal to 0; p is a parameter of Lp norm;

the constraint equation is:

Ks＝y

the vector y is a vector formed by echo amplitudes at different moments, and the echo amplitudes at the different moments are obtained through the nuclear magnetic resonance echo data; k is a kernel matrix, and elements in the kernel matrix K are as follows:

where T is the echo amplitude decay time, T₂Is the transverse relaxation time.

3. The method of claim 2, wherein the solution to the objective function is obtained by:

setting parameters epsilon, threshold tol, parameter p in Lp norm and maximum iteration number it_maxSetting the initial value of the iteration number it as 1; the value ranges of the parameter epsilon and the threshold tol are more than 0;

calculating the vector s⁽⁰⁾K \ y and determines the vector s⁽⁰⁾The number of elements n;

calculating initial residual error

Performing an it iterative computation, wherein the it iterative computation comprises: calculating the solution s after the it iteration^(it)And the residual r after the it iteration^(it)(ii) a The solution s after the it iteration^(it)And the residual r after the it iteration^(it)Obtained by the following method:

s^(it)＝WK^T/(KWK^T)y

wherein, the diagonal matrix W is diag (1./W), and the vector W is W₁,w₂,…w_i,…w_n]，At the time of the 1 st iteration,is the vector s⁽⁰⁾The ith element in (1); when the value of the number of iterations it is equal to or greater than 2,for the solution s after the previous iteration^(it-1)The ith element in (1);

at | r^(it)-r | < tol; or, | r^(it)-r | ≧ tol and it ═ it_maxIn the case of (1), let s be s^(it)And obtaining the vector s.

4. The method of claim 3, further comprising:

at | r^(it)-r | > tol and it < it_maxIn the case of (1), let s be s^(it)、r＝r^(it)；

And (5) after the iteration number it is increased by 1, carrying out the ith iteration calculation.

5. The method of claim 3, wherein s-s^(it)And obtaining a vector s, comprising:

let s be s^(it)；

And if the vector s contains elements smaller than 0, setting the elements smaller than 0 as 0 to obtain the vector s.

6. An apparatus for inverting nuclear magnetic resonance data, comprising:

the echo data acquisition module is used for acquiring nuclear magnetic resonance echo data;

the target function establishing module is used for establishing a target function based on the Lp norm of the vector; the vector meets a preset constraint equation, the constraint equation is determined through the nuclear magnetic resonance echo data, and the value range of a parameter p in the Lp norm is more than or equal to 0 and less than or equal to 1;

and the inversion spectrum generation module is used for generating the inversion spectrum of the nuclear magnetic resonance echo data according to the solution of the target function.

7. The apparatus of claim 6, wherein the inverted spectrum generation module comprises:

a parameter setting unit for setting parameters epsilon, threshold tol, parameter p in Lp norm and maximum iteration number it_maxSetting the initial value of the iteration number it as 1; said parameterThe value ranges of epsilon and the threshold tol are more than 0;

an initial solution calculation unit for calculating a vector s⁽⁰⁾K \ y and determines the vector s⁽⁰⁾The number of elements n;

an initial residual calculation unit for calculating an initial residual

The iterative computation unit is used for carrying out the it iterative computation, and the it iterative computation comprises the following steps: calculating the solution s after the it iteration^(it)And the residual r after the it iteration^(it)(ii) a The solution s after the it iteration^(it)And the residual r after the it iteration^(it)Obtained by the following method:

s^(it)＝WK^T/(KWK^T)y

wherein, the diagonal matrix W is diag (1./W), and the vector W is W₁,w₂,…w_i,…w_n]，At the time of the 1 st iteration,is the vector s⁽⁰⁾The ith element in (1); when the value of the number of iterations it is equal to or greater than 2,for the solution s after the previous iteration^(it-1)The ith element in (1);

a first determination unit for determining the absolute value of r^(it)-r | < tol; or, | r^(it)-r | ≧ tol and it ═ it_maxIn the case of (1), let s be s^(it)And obtaining the vector s.

8. The apparatus of claim 7, wherein the inverted spectrum generation module further comprises:

a second determination unit for determining the absolute value of r^(it)-r | > tol and it < it_maxIn the case of (1), let s be s^(it)、r＝r^(it)(ii) a And after the iteration number it is increased by 1, the ith iteration calculation is carried out.

9. A computer device comprising a processor and a memory for storing processor-executable instructions which, when executed by the processor, implement the steps of the method of any one of claims 1 to 5.

10. A computer readable storage medium having stored thereon computer instructions which, when executed, implement the steps of the method of any one of claims 1-5.

Technical Field

The application relates to the technical field of nuclear magnetic resonance logging data processing in oil and gas exploration, in particular to a nuclear magnetic resonance data inversion method, a nuclear magnetic resonance data inversion device, a nuclear magnetic resonance data storage medium and nuclear magnetic resonance data storage equipment.

Background

The nuclear magnetic resonance logging realizes the observation of underground oil and gas reservoir information by utilizing the resonance phenomenon generated by the interaction of hydrogen nuclei and a magnetic field, and is an effective method for detecting the physical properties of rocks. The original data of the nuclear magnetic resonance logging formation is an echo string consisting of thousands of echoes, and the measured echo string is generally used for inverting the nuclear magnetic resonance spectrum to be used for calculating the rock physical parameters of the reservoir, so that the accuracy of the inverted nuclear magnetic resonance spectrum is directly related to the accuracy of the calculated rock physical parameters. Therefore, it is very important to study the high-precision inversion method of nuclear magnetic resonance data.

At present, the existing nuclear magnetic resonance data inversion methods include a regularization method, an iteration method and an intelligent optimization method. When the methods are used for inverting nuclear magnetic resonance data, target functions all comprise a norm of residual error L2, so that sparsity of solutions obtained through inversion is poor, and resolution of an obtained nuclear magnetic resonance inversion spectrum is low. Therefore, a nuclear magnetic resonance data inversion method is needed to improve the resolution of nuclear magnetic resonance inversion spectra.

Disclosure of Invention

An object of the embodiments of the present application is to provide a nuclear magnetic resonance data inversion method, apparatus, storage medium, and device, so as to improve resolution of nuclear magnetic resonance inversion spectra.

In order to achieve the above object, an embodiment of the present application provides a nuclear magnetic resonance data inversion method, including:

acquiring nuclear magnetic resonance echo data;

establishing an objective function based on the Lp norm of the vector; the vector meets a preset constraint equation, the constraint equation is determined through the nuclear magnetic resonance echo data, and the value range of a parameter p in the Lp norm is more than or equal to 0 and less than or equal to 1;

and generating an inversion spectrum of the nuclear magnetic resonance echo data according to the solution of the target function.

In one embodiment, the objective function is:

wherein the content of the first and second substances,is the Lp norm of the vector; the vector s is a solution of the objective function, and all elements in the vector s are more than or equal to 0; p is a parameter of Lp norm;

the constraint equation is:

Ks＝y

the vector y is a vector formed by echo amplitudes at different moments, and the echo amplitudes at the different moments are obtained through the nuclear magnetic resonance echo data; k is a kernel matrix, and elements in the kernel matrix K are as follows:

where T is the echo amplitude decay time, T₂Is the transverse relaxation time.

In one embodiment, the solution to the objective function is obtained using the following steps:

setting parameters epsilon, threshold tol, parameter p in Lp norm and maximum iteration number it_maxSetting the initial value of the iteration number it as 1; the value ranges of the parameter epsilon and the threshold tol are more than 0;

calculating the vector s⁽⁰⁾K \ y and determines the vector s⁽⁰⁾The number of elements n;

calculating initial residual error

Performing an it iterative computation, wherein the it iterative computation comprises: calculating the solution s after the it iteration^(it)And the residual r after the it iteration^(it)(ii) a The solution s after the it iteration^(it)And the residue after the it iterationDifference r^(it)Obtained by the following method:

s^(it)＝WK^T/(KWK^T)y

wherein, the diagonal matrix W is diag (1./W), and the vector W is W₁,w₂,…w_i,…w_n]，At the time of the 1 st iteration,is the vector s⁽⁰⁾The ith element in (1); when the value of the number of iterations it is equal to or greater than 2,for the solution s after the previous iteration^(it-1)The ith element in (1);

at | r^(it)-r | < tol; or, | r^(it)-r | ≧ tol and it ═ it_maxIn the case of (1), let s be s^(it)And obtaining the vector s.

In one embodiment, further comprising:

at | r^(it)-r | > tol and it < it_maxIn the case of (1), let s be s^(it)、r＝r^(it)；

And (5) after the iteration number it is increased by 1, carrying out the ith iteration calculation.

In one embodiment, the order s ═ s^(it)And obtaining a vector s, comprising:

let s be s^(it)；

And if the vector s contains elements smaller than 0, setting the elements smaller than 0 as 0 to obtain the vector s.

The embodiment of the present application further provides a nuclear magnetic resonance data inversion apparatus, the apparatus includes:

the echo data acquisition module is used for acquiring nuclear magnetic resonance echo data;

the target function establishing module is used for establishing a target function based on the Lp norm of the vector; the vector meets a preset constraint equation, the constraint equation is determined through the nuclear magnetic resonance echo data, and the value range of a parameter p in the Lp norm is more than or equal to 0 and less than or equal to 1;

and the inversion spectrum generation module is used for generating the inversion spectrum of the nuclear magnetic resonance echo data according to the solution of the target function.

In one embodiment, the inverted spectrum generation module includes:

a parameter setting unit for setting parameters epsilon, threshold tol, parameter p in Lp norm and maximum iteration number it_maxSetting the initial value of the iteration number it as 1; the value ranges of the parameter epsilon and the threshold tol are more than 0;

an initial solution calculation unit for calculating a vector s⁽⁰⁾K \ y, and determining a vector s: (⁰) The number of elements n;

an initial residual calculation unit for calculating an initial residual

The iterative computation unit is used for carrying out the it iterative computation, and the it iterative computation comprises the following steps: calculating the solution s after the it iteration^(it)And the residual r after the it iteration^(it)(ii) a The solution s after the it iteration^(it)And the residual r after the it iteration^(it)Obtained by the following method:

s^(it)＝WK^T/(KWK^T)y

wherein, the diagonal matrix W is diag (1./W), and the vector W is W₁,w₂,…w_i,…w_n]，At the time of the 1 st iteration,is the vector s⁽⁰⁾The ith element in (1); when the value of the number of iterations it is equal to or greater than 2,for the solution s after the previous iteration^(it-1)The ith element in (1);

a first determination unit for determining the absolute value of r^(it)-r | < tol; or, | r^(it)-r | ≧ tol and it ═ it_maxIn the case of (1), let s be s^(it)And obtaining the vector s.

In one embodiment, the inverted spectrum generation module further comprises:

a second determination unit for determining the absolute value of r^(it)-r | > tol and it < it_maxIn the case of (1), let s be s^(it)、r＝r^(it)(ii) a And after the iteration number it is increased by 1, the ith iteration calculation is carried out.

The embodiment of the present application further provides a computer device, which includes a processor and a memory for storing processor-executable instructions, where the processor executes the instructions to implement the steps of the nuclear magnetic resonance data inversion method in any of the above embodiments.

Embodiments of the present application further provide a computer-readable storage medium, on which computer instructions are stored, and when executed, the instructions implement the steps of the nuclear magnetic resonance data inversion method in any of the above embodiments.

As can be seen from the technical solutions provided in the embodiments of the present application, the objective function in the present application only contains the Lp norm (the value range of the parameter p in the Lp norm is greater than or equal to 0 and less than or equal to 1), and does not contain the residual L2 norm, so that by using the nuclear magnetic resonance data inversion method provided in the present application, the solution sparsity of inversion is good, and the resolution of the obtained inversion spectrum is high.

Drawings

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 flowchart of a nuclear magnetic resonance data inversion method provided in an embodiment of the present application;

FIG. 2 shows a T containing two peaks according to the present application₂A spectral model graph;

fig. 3 is an echo train with a forward echo interval of 0.15ms, an echo number of 3000, and a signal-to-noise ratio of 150 according to the embodiment of the present application;

fig. 4 is an echo train with a forward echo interval of 0.15ms, an echo number of 3000, and a signal-to-noise ratio of 50 according to the embodiment of the present application;

fig. 5 is an echo train with a forward echo interval of 0.15ms, an echo number of 3000, and a signal-to-noise ratio of 10 provided in the embodiment of the present application;

FIG. 6 shows a nuclear magnetic resonance T obtained by processing the compressed echo data in FIG. 3 by three different inversion methods provided in an embodiment of the present application₂Comparing the spectrum with the model to obtain a result graph;

FIG. 7 shows a nuclear magnetic resonance T obtained by processing the compressed echo data in FIG. 4 by three different inversion methods provided in an embodiment of the present application₂Comparing the spectrum with the model to obtain a result graph;

FIG. 8 shows a nuclear magnetic resonance T obtained by processing the compressed echo data in FIG. 5 by three different inversion methods provided in an embodiment of the present application₂Comparing the spectrum with the model to obtain a result graph;

FIG. 9 is a block diagram of an apparatus for inverting nuclear magnetic resonance data according to an embodiment of the present disclosure;

fig. 10 is a schematic diagram of a computer device provided in an embodiment of the present application.

Detailed Description

The embodiment of the application provides a nuclear magnetic resonance data inversion method, a nuclear magnetic resonance data inversion device, a storage medium and equipment.

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 obtained by a person of ordinary skill in the art without any inventive work based on the embodiments in the present application shall fall within the scope of protection of the present application.

Referring to fig. 1, a flowchart of a nuclear magnetic resonance data inversion method provided in an embodiment of the present application may include the following steps:

s101: nuclear magnetic resonance echo data is acquired.

S102: establishing an objective function based on the Lp norm of the vector; the vector meets a preset constraint equation, the constraint equation is determined through the nuclear magnetic resonance echo data, and the value range of the parameter p in the Lp norm is greater than or equal to 0 and less than or equal to 1.

The problem of inversion of one-dimensional NMR data can be understood as solving s (T) in the integral equation shown in the following formula₂) The formula is as follows:

where y (T) is the echo amplitude at time T, T is the echo amplitude decay time, s (T)₂) For pending nuclear magnetic resonance T₂Spectrum, i.e. nuclear magnetic resonance inversion spectrum.

The above formula can be expressed in the form of a matrix equation as follows:

y＝Ks

the vector y is a vector formed by echo amplitudes at different moments, and the echo amplitudes at the different moments are obtained through the nuclear magnetic resonance echo data; k is a kernel matrix, and elements in the kernel matrix K are as follows:

where T is the echo amplitude decay time, T₂Is the transverse relaxation time.

The above matrix equation may be used as a constraint condition, that is, a constraint equation, to constrain a solution of the nuclear magnetic resonance inversion, and further, an objective function for the nuclear magnetic resonance inversion is established based on the Lp norm, and a solution that makes the objective function take a minimum value is solved, where the objective function is in the following form:

wherein the content of the first and second substances,is the Lp norm of the vector; the vector s is a solution of the objective function, and all elements in the vector s are more than or equal to 0; and p is a parameter of Lp norm.

S103: and obtaining an inversion spectrum of the nuclear magnetic resonance echo data based on the solution of the target function.

After the objective function is obtained, it is also required to perform iterative solution, specifically, an IRLS (iterative weighted Least Squares) algorithm may be used for solution, including the following steps:

setting a parameter epsilon (epsilon is more than 0), a threshold tol, a parameter p (p is more than or equal to 0 and less than or equal to 1) of Lp norm and a maximum iteration time it_maxSetting the initial value of the iteration number it as 1;

calculating the vector s⁽⁰⁾K \ y and determines the vector s⁽⁰⁾The number of elements n;

calculating initial residual error

Performing an it iterative computation, wherein the it iterative computation comprises: calculating the solution s after the it iteration^(it)And the residual r after the it iteration^(it)(ii) a The solution s after the it iteration^(it)And the residual r after the it iteration^(it)Obtained by the following method:

s^(it)＝WK^T/(KWK^T)y

wherein, the diagonal matrix W is diag (1./W), and the vector W is W₁,w₂,…w_i,…w_n]，At the time of the 1 st iteration,is the vector s⁽⁰⁾The ith element in (1); when the value of the number of iterations it is equal to or greater than 2,for the solution s after the previous iteration^(it-1)The ith element in (1);

at | r^(it)-r | < tol; or, | r^(it)-r | ≧ tol and it ═ it_maxIn the case of (1), let s be s^(it)If the vector s contains elements smaller than 0, setting the elements smaller than 0 to be 0, thereby obtaining the vector s.

At | r^(it)-r | > tol and it < it_maxIn the case of (1), let s be s^(it)、r＝r^(it)(ii) a And (5) after the iteration number it is increased by 1, carrying out the ith iteration calculation.

Through the iterative solution, the optimal solution of the target function, namely a vector s is obtained, and T formed by the vector s and the preselected transverse relaxation time is utilized₂Vector, the inverse spectrum of the nuclear magnetic resonance can be obtained in logarithmic coordinates.

Following nuclear magnetic resonance T₂Taking spectral data inversion as an example, a numerical simulation experiment is performed to verify the effectiveness of the nuclear magnetic resonance data inversion method provided by the embodiment of the specificationAnd (5) fruit.

FIG. 2 shows a numerical simulation model with a bimodal T₂Spectrum, T corresponding to two peaks₂The values are respectively 5ms and 100ms, then certain white Gaussian noise is added into the forward modeling result, and echo string data with different signal-to-noise ratios (SNR) are obtained through simulation.

Fig. 3, 4, and 5 are echo train data in forward operation, where in fig. 3, the echo interval is 0.15ms, the number of echoes is 3000, and the SNR is 150; in fig. 4, the echo interval is 0.15ms, the number of echoes is 3000, and the SNR is 50; in fig. 5, the echo interval is 0.15ms, the number of echoes is 3000, and the SNR is 10. The number of echo data in fig. 3, 4 and 5 is compressed to 7, and then the compressed echo data is processed by using a Truncated Singular Value Decomposition (TSVD) method, a Butler-streams-dawson (brd) method and the IRLS method provided by the present application, so as to obtain the nuclear magnetic resonance T corresponding to different signal-to-noise ratio data₂Spectra, as shown in fig. 6, 7 and 8, fig. 6 shows the nuclear magnetic resonance T obtained by processing the echo data in fig. 3 after compression by three different inversion methods₂A spectrum comparison result graph; FIG. 7 is a nuclear magnetic resonance T obtained by processing the echo data of FIG. 4 after compression by three different inversion methods₂A spectrum comparison result graph; FIG. 8 is a nuclear magnetic resonance T obtained by processing the compressed echo data of FIG. 5 by three different inversion methods₂And (5) comparing the spectrums to obtain a result graph.

As can be seen from fig. 6, 7 and 8, as the signal-to-noise ratio increases, the accuracy of the inversion result of the IRLS method provided by the present application is higher and higher, and the inversion result is superior to the inversion results of the currently commonly used TSVD method and BRD method, and especially when the signal-to-noise ratio is low, the T obtained by the inversion of the IRLS method provided by the present application is very low₂The spectral amplitude is higher and closer to the model.

As can be seen from the embodiments provided in the present specification, the following technical effects can be achieved:

in one embodiment provided in the present specification, the established target function does not contain the residual L2 norm, which improves the sparsity of the solution of the target function, thereby improving the resolution of the inverted spectrum;

in an embodiment provided by the present specification, the target function does not contain a regularization term, so that no regularization parameter needs to be obtained in the inversion process, and the inversion step is simplified.

As shown in fig. 9, an embodiment of the present application further provides an apparatus for inverting nuclear magnetic resonance data, including:

an echo data acquisition module 10, configured to acquire nuclear magnetic resonance echo data;

an objective function establishing module 20, configured to establish an objective function based on the Lp norm of the vector; the vector meets a preset constraint equation, the constraint equation is determined through the nuclear magnetic resonance echo data, and the value range of a parameter p in the Lp norm is more than or equal to 0 and less than or equal to 1;

and an inversion spectrum generation module 30, configured to obtain an inversion spectrum of the nuclear magnetic resonance echo data based on the solution of the target function.

Wherein the inverted spectrum generating module 30 includes:

a parameter setting unit 301, configured to set a parameter epsilon (epsilon > 0), a threshold tol, a parameter p (p is greater than or equal to 0 and less than or equal to 1) of Lp norm, and a maximum iteration number it_maxSetting the initial value of the iteration number it as 1;

an initial solution calculation unit 302 for calculating a vector s⁽⁰⁾K \ y and determines the vector s⁽⁰⁾The number of elements n;

an initial residual calculation unit 303 for calculating an initial residual

An iterative computation unit 304, configured to perform an it-th iterative computation, where the it-th iterative computation includes: calculating the solution s after the it iteration^(it)And the residual r after the it iteration^(it)(ii) a The solution s after the it iteration^(it)And the residual r after the it iteration^(it)Obtained by the following method:

s^(it)＝WK^T/(KWK^T)y

wherein, the diagonal matrix W is diag (1./W), and the vector W is W₁,w₂,…w_i,…w_n]，At the time of the 1 st iteration,is the vector s⁽⁰⁾The ith element in (1); when the value of the number of iterations it is equal to or greater than 2,for the solution s after the previous iteration^(it-1)The ith element in (1);

a first determination unit 305 for determining the absolute value of r^(it)-r | < tol; or, | r^(it)-r | ≧ tol and it ═ it_maxIn the case of (1), let s be s^(it)And obtaining the vector s.

A second determination unit 306 for determining the absolute value of | r^(it)-r | > tol and it < it_maxIn the case of (1), let s be s^(it)、r＝r^(it)(ii) a And after the iteration number it is increased by 1, the ith iteration calculation is carried out.

As shown in fig. 10, an embodiment of the present application further provides a computer device, which includes a processor and a memory for storing processor-executable instructions, where the processor executes the instructions to implement the steps of the nuclear magnetic resonance data inversion method in any of the embodiments described above.

Embodiments of the present application further provide a computer-readable storage medium, on which computer instructions are stored, and when executed, the instructions implement the steps of the nuclear magnetic resonance data inversion method in any of the above embodiments.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Language Description Language), traffic, pl (core unified Programming Language), HDCal, JHDL (Java Hardware Description Language), langue, Lola, HDL, laspam, hardsradware (Hardware Description Language), vhjhd (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

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 thus be considered 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 apparatuses and modules illustrated in the above embodiments may be implemented by a computer chip or an entity, or 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, the functionality of the various modules may be implemented in the same one or more software and/or hardware implementations as the present application.

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. With this understanding in mind, the present solution, or portions thereof that contribute to the prior art, may be embodied in the form of a software product, which in a typical configuration includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory. The computer software product may include instructions for causing a computing device (which may be a personal computer, a server, or a network device, etc.) to perform the methods described in the various embodiments or portions of embodiments of the present application. The computer software product may be stored in a memory, which may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium. Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include transitory computer readable media (transient media), such as modulated data signals and carrier waves.

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, as for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

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 consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.

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, 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.

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 spirit of the application.