CN110753224A - Data rearrangement method and system for measurement while drilling data compression - Google Patents
Data rearrangement method and system for measurement while drilling data compression Download PDFInfo
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Abstract
The invention discloses a data rearrangement method for imaging data compression while drilling, which comprises the following steps: obtaining a data sequence comprising N arranged in a one-dimensional data sequence2Rearranging original measurement data of each element into a sequence arranged in a matrix form of N x N according to a sequence i of each element by utilizing a correlation constraint condition and generating a plurality of corresponding two-dimensional data rearrangement paths; and screening the optimal data rearrangement path with the shortest rearrangement element distance from the two-dimensional data rearrangement path according to the distance of the two-dimensional data rearrangement path to determine a two-dimensional matrix data sequence corresponding to the optimal data rearrangement path and provide input data with optimal correlation between non-adjacent data for data compression processing. The invention keeps the phase between the adjacent data in the one-dimensional sequence under the premise of lower calculation amountThe method has the advantages of improving the relevance between non-adjacent data, improving the efficiency of data compression and prolonging the storage time of downhole data.
Description
Technical Field
The invention relates to the technical field of logging while drilling, in particular to a data rearrangement method and a data rearrangement system for compression of measurement while drilling data.
Background
Logging While Drilling (LWD) utilizes Logging instruments arranged in a drill collar to measure rock physical parameters in real time during Drilling, and transmits the measurement results to the ground for processing in real time by means of a data remote measurement system, and the LWD is mainly applied to Drilling engineering optimization and stratum evaluation. When the drilling-following instrument works, various logging instruments such as sound waves, resistivity, nuclear magnetism, gamma rays and the like are hung in the drill collar, and the accuracy of stratum evaluation can be improved by joint interpretation of logging results of the various instruments. With the development of the LWD technology, downhole sensors are increasingly abundant, the amount of acquired data is gradually increased, the capacity of a downhole memory is limited, and long-term storage of the data cannot be realized, but the conventional mud pulse telemetry system has a low data transmission rate and cannot realize real-time transmission of a large amount of LWD data. Therefore, long-term storage and real-time transmission of downhole data become key problems restricting development of the LWD technology, and the data compression technology provides an effective way for solving the problems.
In order to improve the transmission efficiency of measurement while drilling data, data compression technology and information transmission technology have been introduced into the field of geosteering drilling in developed countries. Mature products are available abroad in the aspect of efficient compression of downhole data, but the technical details of the products still belong to trade secrets. For example, schlumberger transmits borehole imaging data to the ground in real time after 50 times of compression by using an image compression technology, thereby solving the problem of insufficient transmission capability of a channel. The domestic research on the compression method of logging-while-drilling data is relatively few, and the method mainly comprises the following four types: (1) the compression method of logging while drilling data based on the LZW (Lempel Ziv Welch) algorithm is slow in speed and poor in timeliness, but a dictionary needs to be continuously inquired in the LZW compression process and compression codes are sequentially output; (2) the method reduces the complexity of the SPIHT algorithm, improves the running speed of the algorithm, designs a parallel realization structure of the algorithm, but the wavelet transformation has reversible transformation only when the wavelet transformation meets the tolerance condition of the wavelet function, and has limitation; (3) a logging while drilling data compression method based on Discrete Cosine Transform (DCT) achieves a higher compression ratio; (4) a logging-while-drilling data compression method based on predictive coding (DPCM) and a mixed coding method based on DPCM and DCT transformation are applied to the imaging-while-drilling data compression, the method obtains a higher compression ratio, and meanwhile, the algorithm has low operation complexity and is suitable for being used in downhole instruments.
The compression principle and performance of the method are different, but one-dimensional raw measurement data are directly processed. The data obtained by the logging instrument in the actual engineering operation process has spatial correlation, namely when one-dimensional data is adopted for representation, strong correlation exists between the current data and the data far away from the current data, the correlation is destroyed by the one-dimensional representation form, and the correlation between the data is not fully utilized in the existing method.
Disclosure of Invention
In order to solve the technical problem, an embodiment of the present invention provides a data rearrangement method for measurement while drilling data compression, where the method includes the following steps: dimension conversion step, obtaining one dimension numberArranged in a sequence comprising N2Rearranging original measurement data of each element into a sequence arranged in a matrix form of N x N according to a sequence order i of each element by utilizing a correlation constraint condition and generating a plurality of corresponding two-dimensional data rearrangement paths; and a path screening step, namely screening an optimal data rearrangement path with the shortest rearrangement element distance from the two-dimensional data rearrangement path according to the distance of the two-dimensional data rearrangement path to determine a two-dimensional matrix data sequence corresponding to the optimal data rearrangement path, and providing input data with optimal correlation between non-adjacent data for data compression processing.
Preferably, the dimension conversion step includes: listing all original rearrangement paths of the one-dimensional data sequence rearranged into an N x N matrix sequence according to the sequence i of each element in the one-dimensional data sequence; placing the elements with the sequence order of 1 in the one-dimensional data sequence at a preset starting point in the N x N matrix sequence, and screening paths meeting the correlation constraint condition from the original rearrangement paths by using the correlation constraint condition to obtain all two-dimensional data rearrangement paths, wherein the correlation constraint condition comprises: the arrangement paths of the elements in the original rearrangement path are continuous and have no intersection, and the elements which are adjacent in sequence order are kept adjacent.
Preferably, the path screening step includes: step one, starting from the condition that a sequence order i is 2, calculating the ith rearrangement element distance of each two-dimensional data rearrangement path with the shortest ith-1 rearrangement element distance, wherein the ith rearrangement element distance is the distance between an element with the sequence order 1 and an element with the sequence order i; step two, comparing each calculated ith rearrangement element distance, and determining the number of the two-dimensional data rearrangement paths with the shortest ith rearrangement element distance; and step three, if the number of the two-dimensional data rearrangement paths with the shortest ith rearrangement element distance is 1, taking the path as the optimal data rearrangement path.
Preferably, in the path screening step, the third step further includes: if the two-dimensional data rearrangement paths with the shortest ith rearrangement element distance are included, increasing the sequence order i by 1, and continuing to execute the first step and the second step under the condition of the increased sequence order, and so on until the optimal data rearrangement path is screened out.
Preferably, if a plurality of the two-dimensional data rearrangement paths with the shortest ith distance are included, where i ═ N2Then, one of the two-dimensional data rearrangement paths is arbitrarily selected and used as the optimal data rearrangement path.
In another aspect, a data rearrangement system for measurement-while-drilling data compression is provided, the system comprising the following modules: a dimension conversion module configured to acquire a data sequence comprising N arranged in a one-dimensional data sequence2Rearranging original measurement data of each element into a sequence arranged in a matrix form of N x N according to a sequence order i of each element by utilizing a correlation constraint condition and generating a plurality of corresponding two-dimensional data rearrangement paths; and the path screening module is configured to screen an optimal data rearrangement path with the shortest rearrangement element distance from the two-dimensional data rearrangement paths according to the distance of the two-dimensional data rearrangement paths, so as to determine a two-dimensional matrix data sequence corresponding to the optimal data rearrangement path, and provide input data with optimal correlation between non-adjacent data for data compression processing.
Preferably, the dimension conversion module includes: an original path generating unit configured to list all original rearrangement paths in which the one-dimensional data sequence is rearranged into an N × N matrix sequence, in accordance with a sequence order i of each element in the one-dimensional data sequence; a correlation keeping unit configured to place an element with a sequence order of 1 in the one-dimensional data sequence at a preset starting point in the N × N matrix sequence, and screen a path satisfying the correlation constraint condition from the original rearrangement paths by using a correlation constraint condition to obtain all two-dimensional data rearrangement paths, wherein the correlation constraint condition includes: the arrangement paths of the elements in the original rearrangement path are continuous and have no intersection, and the elements which are adjacent in sequence order are kept adjacent.
Preferably, the path screening module includes: an element distance generating unit configured to calculate an ith rearrangement element distance, which is a distance between an element in the sequence order 1 and an element in the sequence order i, of two-dimensional data rearrangement paths each having the shortest i-1 th rearrangement element distance, from a case in which the sequence order i is 2; a rearrangement path optimizing unit configured to compare the calculated i-th rearrangement element distances and determine the number of the two-dimensional data rearrangement paths having the shortest i-th rearrangement element distance; and an optimal path selecting unit configured to take the path as an optimal data rearrangement path if the number of two-dimensional data rearrangement paths having the shortest i-th rearrangement element distance is 1.
Preferably, in the path screening module, the optimal path selecting unit further includes: the method is configured to, if a plurality of two-dimensional data rearrangement paths having the shortest i-th rearrangement element distance are included, increase the sequence order i by 1, and continue to execute the element distance generation unit and the rearrangement path optimization unit in the case of the increased sequence order, and so on until the optimal data rearrangement path is screened out.
Preferably, in the optimal path selecting unit, if a plurality of two-dimensional data rearrangement paths with the shortest ith distance are included, where i ═ N2Then, one of the two-dimensional data rearrangement paths is arbitrarily selected and used as the optimal data rearrangement path.
Compared with the prior art, one or more embodiments in the above scheme can have the following advantages or beneficial effects:
the invention provides a data recombination method and a data recombination system, which take the rearrangement element distance as an optimization criterion, take the data rearrangement path continuity, no intersection and data adjacency maintenance as constraint conditions, and recombine the obtained one-dimensional data into a two-dimensional matrix. The method and the system keep the correlation between the adjacent data in the original one-dimensional sequence to the maximum extent on the premise of lower calculation amount, enhance the correlation between the non-adjacent data, improve the efficiency of data compression processing, prolong the storage time of the underground data and improve the data remote transmission efficiency.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a diagram illustrating steps of a data rearrangement method for MWD data compression according to an embodiment of the present invention.
Fig. 2 is a specific flowchart of a data rearrangement method for measurement-while-drilling data compression according to an embodiment of the present application.
Fig. 3 is a schematic diagram of a specific example of a data rearrangement method for measurement-while-drilling data compression according to an embodiment of the present application.
FIG. 4 is a flowchart of a data rearrangement method for compression of measurement-while-drilling data based on DPCM and DCT hybrid coding of the method for compression of imaging-while-drilling data according to an embodiment of the present application.
FIG. 5 is a comparison graph of compression effects of an imaging-while-drilling data compression method based on DPCM and DCT mixed coding without applying the data rearrangement method for measurement-while-drilling data compression of the embodiment of the present application.
FIG. 6 is a comparison graph of compression effects of a data compression method for measurement-while-drilling data compression based on DPCM and DCT mixed coding, to which the data rearrangement method for measurement-while-drilling data compression of the embodiment of the present application is applied.
FIG. 7 is a block diagram of a data reordering system for measurement-while-drilling data compression according to an embodiment of the present application.
Detailed Description
The following detailed description of the embodiments of the present invention will be provided with reference to the drawings and examples, so that how to apply the technical means to solve the technical problems and achieve the technical effects can be fully understood and implemented. It should be noted that, as long as there is no conflict, the embodiments and the features of the embodiments of the present invention may be combined with each other, and the technical solutions formed are within the scope of the present invention.
In order to improve the transmission efficiency of measurement while drilling data, the compression method of measurement while drilling data in the prior art is mainly based on an LZW (Lempel Ziv Welch) algorithm, a wavelet transform, a discrete cosine transform, a predictive coding algorithm and other algorithms. However, the compression principle and performance of the above methods are different, and one-dimensional raw measurement data are directly processed, and data obtained by a logging instrument in the actual engineering operation process have spatial correlation among the data, that is, when one-dimensional data is used for representation, strong correlation exists between the current data and the data far away from the current data, and the correlation is destroyed by the one-dimensional representation form, and the correlation among the data is not fully utilized in the existing method.
Therefore, the embodiment of the application provides a data rearrangement method and a system for measurement-while-drilling data compression, the method and the system take the average distance of rearrangement elements as an optimization criterion, take the data rearrangement path as a constraint condition that the data rearrangement path is continuous and has no cross and data adjacency is kept, recombine the input original one-dimensional data into a two-dimensional matrix, and enhance the correlation between non-adjacent data and improve the efficiency of data compression while keeping the correlation between the adjacent data.
FIG. 1 is a diagram illustrating steps of a data rearrangement method for MWD data compression according to an embodiment of the present invention. As shown in fig. 1, first, a dimension conversion operation needs to be performed on the acquired one-dimensional data sequence. Further, (step S110) in the dimension conversion step, N-containing data acquired by the measurement-while-drilling instrument and arranged in the form of a one-dimensional data sequence is acquired2Rearranging the original measurement data of each (sector) element according to the sequence order i of each element by utilizing a correlation constraint condition to obtain a corresponding N x N matrix sequence, and generating a plurality of (all) two-dimensional data rearrangement paths of the N x N matrix sequence so as to maintain the phase between non-adjacent (sector) dataAnd (4) turning off. Wherein N is2Indicates the total number of (sector) elements, and i indicates the sequence order number of the elements.
In one embodiment, N is preset around the well2Each sector (i.e. the collected area has N)2And the measurement-while-drilling instrument collects a group of (individual) measurement data from each sector and arranges each measurement data as one (sector) element into a one-dimensional data sequence according to the sequence of the (sector) elements. Wherein the (sector) element data of the one-dimensional data sequence is also N2Therefore, in order to facilitate the conversion of raw measurement data from the form of a one-dimensional data sequence to the form of a matrix that can more accurately represent the data correlation, the number of (sector) elements is set to N2，N2The data is related to the measurement precision of the measurement while drilling and the measurement precision of the instrument, and the technical personnel in the field can set the data according to the actual requirement, and the value of N in the invention is not particularly limited.
Further, fig. 2 is a specific flowchart of a data rearrangement method for measurement-while-drilling data compression according to an embodiment of the present application. With reference to fig. 2, a specific flow of the above dimension conversion step is explained below. First, all the original rearrangement paths included in the one-dimensional data sequence that can be rearranged into the N × N matrix sequence are listed according to the sequence order i of each (sector) element in the one-dimensional data sequence. The original rearrangement path is formed by encoding each (sector) element according to a natural sequence of (sectors), respectively placing the elements at each position point in an N x N matrix, and then connecting each (sector) element according to the sequence of each (sector) element. Note that, for having N2One-dimensional data sequence of individual (sector) elements, the original rearrangement path of which has an N! A strip path.
Then, the (sector) elements with the sequence order of 1 in the one-dimensional data sequence are placed at a preset starting point in the N x N matrix sequence, and paths meeting the correlation constraint condition are screened from the original rearrangement paths by utilizing the correlation constraint condition to obtain all two-dimensional data rearrangement paths. Wherein the relevance constraints include: the arrangement path of each (sector) element in the original rearrangement path keeps the characteristics of continuity, no discontinuity and no intersection, and each (sector) element adjacent in sequence order keeps adjacent. In this way, the correlation between different data is enhanced such that data that are not adjacent different (sector) elements but have strong correlation (e.g., the data within a sector element may be imaging data) are correlated in the form of a matrix path.
It should be noted that the preset starting point may be set to the positions of four corners in the N × N matrix, that is, the upper left corner, the upper right corner, the lower left corner, and the lower right corner.
Fig. 3 is a schematic diagram of a specific example of a data rearrangement method for measurement-while-drilling data compression according to an embodiment of the present application. As shown in fig. 3, the one-dimensional data sequences X1 and X2 … … X16 screen out two-dimensional data rearrangement paths satisfying the correlation constraint condition according to the correlation constraint condition, as shown in (a) matrix and (b) matrix in fig. 3.
Referring to fig. 1 and fig. 2 again, after the dimension conversion of the (sector) element data is completed, the screened two-dimensional data rearrangement path needs to be optimized, and an optimal data rearrangement path is selected. Further, in step S120 (route filtering step), the route distances of the routes are rearranged based on the two-dimensional data to rearrange the element distances diTaking an optimization criterion (wherein i is a natural number of 1-15) as the optimization criterion according to d1、d2… …, screening out the optimal data rearrangement path with the shortest rearrangement element distance from the two-dimensional data rearrangement paths, finally determining the two-dimensional matrix data sequence corresponding to the optimal data rearrangement path, and taking the two-dimensional matrix data sequence as the input data of the subsequent data compression processing, further providing the input data with the best correlation between non-adjacent data for the data compression processing, thereby improving the data compression efficiency, prolonging the storage time of the downhole data, and improving the data remote transmission efficiency.
According to the data rearrangement mode, each measurement data is kept adjacent to the most relevant data which is directly adjacent to the measurement data in the original one-dimensional sequence in rows or columns, and the correlation between the adjacent data in the original one-dimensional sequence is kept to the maximum extent. In addition, in the data rearrangement mode, the average distance of the rearrangement elements is minimum, the fluctuation of the rearranged data is reduced to the maximum extent, and the correlation between non-adjacent data is enhanced.
Specifically, first, the ith rearrangement element distance in each two-dimensional data rearrangement path having the shortest ith-1 rearrangement element distance is calculated from the case where the sequence order i is 2 (refer to fig. 2), where the ith rearrangement element distance diDistance d of (sector) element with sequence order 1 and (sector) element with sequence order ii-1Distance d of (sector) element with sequence order of 1 and (sector) element with sequence order of i-1i-1The minimum two-dimensional data rearrangement path is the two-dimensional data rearrangement path with the shortest i-1 th rearrangement element distance. It should be noted that, when i is 2, since the distance of the 1 st rearrangement element in each two-dimensional data rearrangement path is 0 (i.e. the distance between the element with the sequence order of 1 and the starting point), the distance d of the 2 nd rearrangement element in each two-dimensional data rearrangement path needs to be calculated in this step2. Then, each of the ith rearrangement element distances calculated above is compared, and the number of two-dimensional data rearrangement paths having the shortest ith rearrangement element distance is determined. And then, if the number of the two-dimensional data rearrangement paths with the shortest ith rearrangement element distance is 1, taking the path as an optimal data rearrangement path to determine a two-dimensional matrix data sequence corresponding to the optimal data rearrangement path.
Further, if the two-dimensional data rearrangement path comprises a plurality of two-dimensional data rearrangement paths with the shortest ith rearrangement element distance, increasing the sequence order i by 1, and continuing to implement the first step and the second step under the condition of the increased sequence order, and so on until an optimal data rearrangement path is screened out to determine the two-dimensional matrix data sequence corresponding to the optimal data rearrangement path.
In one embodiment, starting from the case where the sequence order i is 2, the element with the sequence order of 2 in each two-dimensional data reordering path is calculatedDistance d of element from element (starting point) with sequence order 12Will have the smallest d2The path is determined as the optimal data rearrangement path, and is used for determining the two-dimensional matrix data sequence corresponding to the optimal data rearrangement path.
In another embodiment, the distance d between the element of the sequence order 2 and the element of the sequence order 1 (starting point) in each two-dimensional data rearrangement path is calculated from the case where the sequence order i is 22. Furthermore, if there are multiple two-dimensional data rearrangement paths corresponding to the distance d2If they are the same, then calculate that the strips have the same d2In the path (d), the distance d between the element with the sequence order of 3 and the element with the sequence order of 1 (starting point)3At this time, d3And the smaller the rearrangement performance of the two-dimensional data rearrangement path to which the two-dimensional data rearrangement path belongs is, the better the rearrangement performance is, and so on, until an optimal data rearrangement path with the best performance is screened out to determine the two-dimensional matrix data sequence corresponding to the optimal data rearrangement path.
In the sequence order i, N2In the case of (1), if the calculated path corresponding to the ith rearrangement element distance still includes a plurality of two-dimensional data rearrangement paths having the shortest ith rearrangement element distance, one of the two-dimensional data rearrangement paths having the shortest ith rearrangement element distance is arbitrarily selected and used as the optimal data rearrangement path for the subsequent data compression processing. Referring to fig. 3, the rearrangement element distance d of two data rearrangement paths shown in matrix (a) and matrix (b)1、d2… …, it is found through experiments that the results of the two rearrangement paths are equivalent for the next measurement data compression process, and therefore, one of the paths needs to be selected as the optimal data rearrangement path for the subsequent measurement data compression process.
In addition, the data rearrangement method for compression of imaging data while drilling described above is applied to the data rearrangement method by taking a mixed coding method of DPCM and DCT as an example, and the effects of the data rearrangement method according to the present invention will be described.
First, a description will be given of a flow of a data compression method in which the data rearrangement method in the embodiment of the present invention is applied to hybrid coding of DPCM and DCT transform. FIG. 4 is a flowchart of a data rearrangement method for compression of measurement-while-drilling data based on DPCM and DCT hybrid coding of the method for compression of imaging-while-drilling data according to an embodiment of the present application.
As shown in FIG. 4, first, N is included and acquired by measurement-while-drilling instrument2And carrying out predictive coding on the original measurement data to obtain a one-dimensional (differential) data sequence which represents a predictive coding result and contains each (sector) element around the well. Then, the method in the embodiment of the present invention is used to perform data compression processing on the obtained one-dimensional (differential) data sequence subjected to the prediction coding differential processing, and according to the data reassembly method described above, the input one-dimensional (differential) data sequence is converted into a two-dimensional matrix data sequence having an optimal data rearrangement path. Then, DCT transformation, uniform quantization and entropy coding processing are sequentially carried out on the two-dimensional matrix data sequence, so that compression of original measurement data with strong correlation among different (sectors) is completed. Further, the compressed original measurement data is decompressed according to a similar method, which is not described herein again.
Example 1:
in the actual logging while drilling process, in order to ensure real-time performance of data transmission, compression processing is usually performed by taking a plurality of sector data acquired within one well circumference as a unit, and taking imaging while drilling data of 16 sectors as an example, compression processing is performed on 16 acquired imaging while drilling data once according to the flow shown in fig. 4. Wherein, the data reorganization process comprises:
(1) for a one-dimensional (differential) data sequence of 16 elements acquired in each well cycle, all rearrangement paths are listed which can rearrange the data sequence into a 4 x 4 matrix data sequence, which is 16! Seed growing;
(2) screening out all data rearrangement paths meeting the conditions by using two conditions that a first element in a one-dimensional data sequence is placed at the upper left corner of a 4 x 4 matrix and data rearrangement paths are continuous and have no cross and data adjacency is kept as constraints;
(3) at a rearrangement element distance diAs an optimization criterion, according to d1、d2… …, the selected data rearrangement method is optimally selected. From d1Start, d1The smaller the data rearrangement method is, the better the performance of the data rearrangement method is; for both data rearrangement methods, if d1When the same is true, then d2The smaller the rearrangement method is, the better the performance of the rearrangement method is, and so on, the data rearrangement method with the best performance is finally obtained, as shown in fig. 3.
Example 2:
in the actual logging while drilling process, in order to ensure the real-time performance of data transmission, the data of 256 sectors continuously acquired in 16 cycles is used for compression, the data of 16 sectors in one cycle is used as a unit for compression, and the 16 times of data compression is completed according to the flow shown in fig. 4. Wherein, the data reorganization process comprises:
(1) for a one-dimensional (differential) data sequence containing 16 elements acquired in each well cycle, all data rearrangement methods that can rearrange the data sequence into a 4 x 4 matrix data sequence are listed, which is 16! Seed growing;
(2) screening out all data rearrangement methods which meet the conditions by using two conditions that a first element in a one-dimensional data sequence is placed at the upper left corner of a 4 x 4 matrix and a data rearrangement path is continuous and non-crossed and data adjacency is kept as constraints;
(3) by average distance d of rearranged elementsiAs an optimization criterion, according to d1、d2… …, the selected data rearrangement method is optimally selected. From d1Start, d1The smaller the data rearrangement method is, the better the performance of the data rearrangement method is; for both data rearrangement methods, if d1When the same is true, then d2The smaller the rearrangement method is, the better the performance of the rearrangement method is, and so on, the data rearrangement method with the best performance is finally obtained, as shown in fig. 3.
Further, fig. 5 is a comparison graph of compression effects of the imaging while drilling data compression method based on DPCM and DCT hybrid coding without applying the data rearrangement method for measurement while drilling data compression of the embodiment of the present application. Fig. 5 shows a comparison between a reconstructed data curve obtained by data compression without the data rearrangement method of the present invention and an original data curve at a compression ratio of 1.5:1 and a relative error of about 6.7%. FIG. 6 is a comparison graph of compression effects of a data compression method for measurement-while-drilling data compression based on DPCM and DCT mixed coding, to which the data rearrangement method for measurement-while-drilling data compression of the embodiment of the present application is applied. Fig. 6 shows a comparison between a reconstructed data curve obtained by data compression using the data rearrangement method of the present invention and an original data curve at a compression ratio of 3.39:1 and a relative error of about 1.08%. As can be seen from fig. 5 and fig. 6, after the data rearrangement method provided by the present invention is adopted, the compression ratio is significantly improved by 1.26 times.
In addition, aiming at the data rearrangement method, the invention also provides a data rearrangement system for the compression of the imaging data while drilling. FIG. 7 is a block diagram of a data reordering system for measurement-while-drilling data compression according to an embodiment of the present application. As shown in fig. 7, the system includes: a dimension conversion module 71 and a path filtering module 72. The dimension conversion module 71 is implemented according to the method in step S110, and is capable of acquiring the data acquired by the measurement-while-drilling instrument, which is arranged in a one-dimensional data sequence and contains N2The original measurement data of each (sector) element is obtained by utilizing a correlation constraint condition and according to the sequence order i of each element, the original measurement data contains N2The one-dimensional data sequences of the individual (sector) elements are rearranged to obtain corresponding sequences in the form of N x N matrices, and all two-dimensional data rearrangement paths of the N x N matrix sequences are generated to maintain the correlation between different (sector) data. Wherein N is2Indicates the total number of (sector) elements, and i indicates the sequence order number of the elements.
Specifically, the dimension conversion module 71 further includes: an original path generating unit 711 and a correlation holding unit 712. Further, the original path generating unit 711 lists all original rearrangement paths included in the one-dimensional data sequence that can be rearranged into an N × N matrix sequence, according to the sequence order i of each (sector) element in the obtained one-dimensional data sequence. Then, the correlation keeping unit 712 places (sector) elements with sequence order of 1 in the one-dimensional data sequence at a preset starting point in the N × N matrix sequence, and screens out paths satisfying the correlation constraint condition from the original rearrangement paths by using the correlation constraint condition, so as to obtain all two-dimensional data rearrangement paths. The relevance constraints include: the arrangement path of each (sector) element in the original rearrangement path keeps the characteristics of continuity, no discontinuity and no intersection, and each (sector) element adjacent in sequence order keeps adjacent.
Next, the path screening module 72 will be explained. The path screening module 72 is implemented according to the method in step S120, and can screen an optimal data rearrangement path with the shortest rearrangement element distance from the two-dimensional data rearrangement paths according to the distance of the two-dimensional data rearrangement path, finally determine a two-dimensional matrix data sequence corresponding to the optimal data rearrangement path, and use the two-dimensional matrix data sequence as input data for subsequent data compression processing, so as to further provide input data with optimal correlation between non-adjacent data for data compression processing.
Specifically, the path screening module 72 further includes: an element distance generating unit 721, a rearrangement path optimizing unit 722, and an optimal path selecting unit 723. Further, the element distance generating unit 721 needs to calculate the ith rearrangement element distance in each two-dimensional data rearrangement path having the shortest i-1 th rearrangement element distance, where the ith rearrangement element distance d is calculated, from the case where the sequence order i is 2iDistance d of (sector) element with sequence order 1 and (sector) element with sequence order ii-1Distance d of (sector) element with sequence order of 1 and (sector) element with sequence order of i-1i-1The minimum two-dimensional data rearrangement path is the two-dimensional data rearrangement path with the shortest i-1 th rearrangement element distance. It should be noted that, when i is 2, since the distance of the 1 st rearrangement element in each two-dimensional data rearrangement path is 0 (i.e. the distance between the element with the sequence order of 1 and the starting point), the distance d of the 2 nd rearrangement element in each two-dimensional data rearrangement path needs to be calculated in this step2. Next, each of the element distances calculated by the element distance generating unit 721 is compared by the rearrangement path optimizing unit 722And determining the number of two-dimensional data rearrangement paths with the shortest ith rearrangement element distance. Then, the optimal path selecting unit 723 screens the optimized two-dimensional data rearrangement paths, and if the unit 723 determines that the number of the two-dimensional data rearrangement paths having the shortest ith rearrangement element distance is 1, the path is used as the optimal data rearrangement path to determine a two-dimensional matrix data sequence corresponding to the optimal data rearrangement path.
In addition, if the optimal path selecting unit 723 determines that the two-dimensional data rearrangement path includes a plurality of two-dimensional data rearrangement paths having the shortest i-th rearrangement element distance, the sequence order i is increased by 1, and the two-dimensional data rearrangement path continues to return to the element distance generating unit 721 and the rearrangement path optimizing unit 722 for implementation in the case of the increased sequence order, and so on, until the optimal data rearrangement path is screened out, so as to determine the two-dimensional matrix data sequence corresponding to the optimal data rearrangement path.
Further, the optimal path selecting unit 723 determines that the two-dimensional data rearrangement path includes a plurality of shortest i-th rearrangement element distances, where i is N2And then, one of the two-dimensional data rearrangement paths with the shortest ith rearrangement element distance is arbitrarily selected and used as an optimal data rearrangement path to determine a two-dimensional matrix data sequence corresponding to the optimal data rearrangement path, and the two-dimensional matrix data is further used as input data of subsequent data compression processing.
The embodiment of the invention provides a data rearrangement method and a data rearrangement system for measurement while drilling data compression. The method and the system take the rearrangement element distance as an optimization criterion, take the data rearrangement path which is continuous and has no cross and keeps the data adjacency as a constraint condition, recombine the obtained one-dimensional data into a two-dimensional matrix, enhance the relevance between non-adjacent data, improve the efficiency of the transform coding decorrelation redundancy, prolong the storage time of the underground data and improve the data remote transmission efficiency on the premise of keeping the relevance between the adjacent data and lower calculation amount.
Although the embodiments of the present invention have been described above, the above descriptions are only for the convenience of understanding the present invention, and are not intended to limit the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A data reordering method for measurement-while-drilling data compression, the method comprising the steps of:
dimension conversion step, obtaining N arranged in one-dimensional data sequence2Rearranging original measurement data of each element into a sequence arranged in a matrix form of N x N according to a sequence order i of each element by utilizing a correlation constraint condition and generating a plurality of corresponding two-dimensional data rearrangement paths;
and a path screening step, namely screening an optimal data rearrangement path with the shortest rearrangement element distance from the two-dimensional data rearrangement path according to the distance of the two-dimensional data rearrangement path to determine a two-dimensional matrix data sequence corresponding to the optimal data rearrangement path, and providing input data with optimal correlation between non-adjacent data for data compression processing.
2. The data rearrangement method according to claim 1, wherein the dimension conversion step comprises:
listing all original rearrangement paths of the one-dimensional data sequence rearranged into an N x N matrix sequence according to the sequence i of each element in the one-dimensional data sequence;
placing the elements with the sequence order of 1 in the one-dimensional data sequence at a preset starting point in the N x N matrix sequence, and screening paths meeting the correlation constraint condition from the original rearrangement paths by using the correlation constraint condition to obtain all two-dimensional data rearrangement paths, wherein the correlation constraint condition comprises: the arrangement paths of the elements in the original rearrangement path are continuous and have no intersection, and the elements which are adjacent in sequence order are kept adjacent.
3. The data rearrangement method according to claim 1 or 2, wherein the path filtering step comprises:
step one, starting from the condition that a sequence order i is 2, calculating the ith rearrangement element distance of each two-dimensional data rearrangement path with the shortest ith-1 rearrangement element distance, wherein the ith rearrangement element distance is the distance between an element with the sequence order 1 and an element with the sequence order i;
step two, comparing each calculated ith rearrangement element distance, and determining the number of the two-dimensional data rearrangement paths with the shortest ith rearrangement element distance;
and step three, if the number of the two-dimensional data rearrangement paths with the shortest ith rearrangement element distance is 1, taking the path as the optimal data rearrangement path.
4. The data rearrangement method according to claim 3, wherein in the path filtering step, the third step further comprises:
if the two-dimensional data rearrangement paths with the shortest ith rearrangement element distance are included, increasing the sequence order i by 1, and continuing to execute the first step and the second step under the condition of the increased sequence order, and so on until the optimal data rearrangement path is screened out.
5. The method according to claim 4, wherein the data rearrangement method further comprises a plurality of the two-dimensional data rearrangement paths having the shortest ith distance, wherein i ═ N2，
One of the two-dimensional data rearrangement paths is arbitrarily selected and set as the optimal data rearrangement path.
6. A data reordering system for measurement-while-drilling data compression, the system comprising the following modules:
a dimension conversion module configured to acquire a data sequence in one dimensionOf formula (I) arranged comprising N2Rearranging original measurement data of each element into a sequence arranged in a matrix form of N x N according to a sequence order i of each element by utilizing a correlation constraint condition and generating a plurality of corresponding two-dimensional data rearrangement paths;
and the path screening module is configured to screen an optimal data rearrangement path with the shortest rearrangement element distance from the two-dimensional data rearrangement paths according to the distance of the two-dimensional data rearrangement paths, so as to determine a two-dimensional matrix data sequence corresponding to the optimal data rearrangement path, and provide input data with optimal correlation between non-adjacent data for data compression processing.
7. The data reordering system of claim 6 wherein said dimension conversion module comprises:
an original path generating unit configured to list all original rearrangement paths in which the one-dimensional data sequence is rearranged into an N × N matrix sequence, in accordance with a sequence order i of each element in the one-dimensional data sequence;
a correlation keeping unit configured to place an element with a sequence order of 1 in the one-dimensional data sequence at a preset starting point in the N × N matrix sequence, and screen a path satisfying the correlation constraint condition from the original rearrangement paths by using a correlation constraint condition to obtain all two-dimensional data rearrangement paths, wherein the correlation constraint condition includes: the arrangement paths of the elements in the original rearrangement path are continuous and have no intersection, and the elements which are adjacent in sequence order are kept adjacent.
8. The data reordering system of claim 6 or 7 wherein the path filtering module comprises:
an element distance generating unit configured to calculate an ith rearrangement element distance, which is a distance between an element in the sequence order 1 and an element in the sequence order i, of two-dimensional data rearrangement paths each having the shortest i-1 th rearrangement element distance, from a case in which the sequence order i is 2;
a rearrangement path optimizing unit configured to compare the calculated i-th rearrangement element distances and determine the number of the two-dimensional data rearrangement paths having the shortest i-th rearrangement element distance;
and an optimal path selecting unit configured to take the path as an optimal data rearrangement path if the number of two-dimensional data rearrangement paths having the shortest i-th rearrangement element distance is 1.
9. The data reordering system of claim 8 wherein in the path filtering module, the optimal path selecting unit further comprises:
the method is configured to, if a plurality of two-dimensional data rearrangement paths having the shortest i-th rearrangement element distance are included, increase the sequence order i by 1, and continue to execute the element distance generation unit and the rearrangement path optimization unit in the case of the increased sequence order, and so on until the optimal data rearrangement path is screened out.
10. The data reordering system of claim 9 wherein the optimal path selecting unit comprises a plurality of two-dimensional data reordering paths with the shortest ith distance, wherein i-N2，
One of the two-dimensional data rearrangement paths is arbitrarily selected and set as the optimal data rearrangement path.
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