CN111932654A - Automatic logging curve tracking method and device based on pixel optimization and electronic equipment - Google Patents
Automatic logging curve tracking method and device based on pixel optimization and electronic equipment Download PDFInfo
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- CN111932654A CN111932654A CN202010740028.4A CN202010740028A CN111932654A CN 111932654 A CN111932654 A CN 111932654A CN 202010740028 A CN202010740028 A CN 202010740028A CN 111932654 A CN111932654 A CN 111932654A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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Abstract
The embodiment of the invention discloses a method and a device for automatically tracking a logging curve based on pixel optimization and electronic equipment, wherein the method comprises the following steps: s1: acquiring pixel information of each pixel point in a logging image; s2: giving an initial tracking point on a logging curve in the logging image, and performing transverse tracking according to the initial tracking point, a given color threshold value and a given transverse tracking distance; s3: obtaining a current optimal point in a next row of pixels, and performing transverse tracking according to the current optimal point, the color threshold and the transverse tracking distance; s4: and repeating the step S3 until the distance between the starting tracking point and the current optimal point exceeds the given longitudinal tracking distance, and obtaining a final logging curve. The invention can automatically extract the logging curve from the logging image quickly and accurately, and has good anti-interference effect.
Description
Technical Field
The embodiment of the invention relates to the technical field of image processing, in particular to a method and a device for automatically tracking a logging curve based on pixel optimization and electronic equipment.
Background
The logging curve is a common carrier for recording logging information in the exploration and production processes of the oil field, and has important significance for guiding the development of the oil field. Due to the fact that measured parameters are numerous, various instruments of multiple companies are involved in the well logging process, well logging data are often given in the form of curves in pictures, and therefore the picture well logging curve data need to be extracted automatically.
Because a great amount of background grids and curves or curves and curves interweave in a logging curve drawing image, curve tracking is interrupted, manual connection is needed, and automatic curve extraction is very difficult.
Disclosure of Invention
The embodiment of the invention aims to provide a method, a device and electronic equipment for automatically tracking a logging curve based on pixel optimization, which are used for solving the problem that the existing logging curve is very difficult to automatically track.
In order to achieve the above object, the embodiments of the present invention mainly provide the following technical solutions:
in a first aspect, an embodiment of the present invention provides a log automatic tracking method based on pixel optimization, including: s1: acquiring pixel information of each pixel point in a logging image; s2: giving an initial tracking point on a logging curve in the logging image, and performing transverse tracking according to the initial tracking point, a given color threshold value and a given transverse tracking distance; s3: obtaining a current optimal point in a next row of pixels, and performing transverse tracking according to the current optimal point, the color threshold and the transverse tracking distance; s4: and repeating the step S3 until the distance between the starting tracking point and the current optimal point exceeds the given longitudinal tracking distance, and obtaining a final logging curve.
According to one embodiment of the invention, acquiring the current optimal point in the next row of pixels comprises: in the transverse tracking range of the next row of pixels, coordinate points and pixel values in the color threshold range are stored in an array from left to right; calculating the average value of the horizontal coordinates of all the pixel points in the array; obtaining coefficients of all pixel points in the array according to the average value and a coefficient calculation formula; and taking the point with the minimum coefficient in the coefficients of all the pixel points in the array as the current optimal point.
According to an embodiment of the present invention, the coefficient calculation formula is:
Ci＝(Hpi.Xi-AvgD)/AvgD*0.5+(Hpi.Vi-P.v)/P.v*0.5
wherein Ci is a coefficient of a pixel point Hpi (Xi, Yi, Vi), hpi.xi is an abscissa of the pixel point Hpi (Xi, Yi, Vi), AvgD is an average of abscissas of all pixel points in the array, hpi.vi is a pixel value of the pixel point Hpi (Xi, Yi, Vi), and P.v is a coordinate value of the initial tracking point.
According to an embodiment of the invention, the pixel information comprises RGB values of the pixel points.
In a second aspect, an embodiment of the present invention further provides a device for automatically tracking a log based on pixel optimization, including: the acquisition module is used for acquiring a logging image; the control processing module is used for acquiring pixel information of each pixel point in a logging image, giving an initial tracking point on a logging curve in the logging image, and performing transverse tracking according to the initial tracking point, a given color threshold value and a given transverse tracking distance; the control processing module is further used for obtaining a current optimal point in a next row of pixels and performing transverse tracking according to the optimal point, the color threshold and the transverse tracking distance; and the control processing module is also used for repeatedly acquiring the current optimal point to perform transverse tracking until the distance between the initial tracking point and the current optimal point exceeds a given longitudinal tracking distance, so as to obtain a final logging curve.
According to an embodiment of the present invention, the control processing module is configured to, within a horizontal tracking range in a next row of pixels, store coordinate points and pixel values within a color threshold range from left to right into an array, calculate an average value of abscissa of all pixel points in the array, obtain coefficients of all pixel points in the array according to the average value and a coefficient calculation formula, and take a point with a minimum coefficient among the coefficients of all pixel points in the array as a current optimal point.
According to an embodiment of the present invention, the coefficient calculation formula is:
Ci＝(Hpi.Xi-AvgD)/AvgD*0.5+(Hpi.Vi-P.v)/P.v*0.5
wherein Ci is a coefficient of a pixel point Hpi (Xi, Yi, Vi), hpi.xi is an abscissa of the pixel point Hpi (Xi, Yi, Vi), AvgD is an average of abscissas of all pixel points in the array, hpi.vi is a pixel value of the pixel point Hpi (Xi, Yi, Vi), and P.v is a coordinate value of the initial tracking point.
According to an embodiment of the invention, the pixel information comprises RGB values of the pixel points.
In a third aspect, an embodiment of the present invention further provides an electronic device, including: at least one processor and at least one memory; the memory is to store one or more program instructions; the processor is configured to execute one or more program instructions to perform the method for automatic pixel-based optimization tracing of a well log according to the first aspect.
In a fourth aspect, embodiments of the present invention further provide a computer-readable storage medium containing one or more program instructions for executing the pixel-based optimized automatic log tracking method according to the first aspect.
The technical scheme provided by the embodiment of the invention at least has the following advantages:
the automatic tracking method, the device and the electronic equipment for the logging curve based on the pixel optimization can quickly, accurately and automatically extract the logging curve from the logging image, and have good anti-interference effect.
Drawings
FIG. 1 is a flowchart of a method for automatic tracking of a log based on pixel optimization according to an embodiment of the present invention.
FIG. 2 is a graph of pixel information for each pixel point in a log image according to an example of the present invention.
FIG. 3 is a diagram of the solution of the optimal point Pc (x, y, v) for filtering the gridline disturbances in one example of the invention.
Fig. 4 is a schematic diagram of elimination curve interference for solving the optimal point Pc (x, y, v) in another example of the present invention.
FIG. 5 is a schematic illustration of automatic log tracking according to an example of the present invention.
Fig. 6 is a block diagram of an embodiment of an automatic log tracking device based on pixel optimization.
Detailed Description
The following description of the embodiments of the present invention is provided for illustrative purposes, and other advantages and effects of the present invention will become apparent to those skilled in the art from the present disclosure.
In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular system structures, interfaces, techniques, etc. in order to provide a thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In the description of the present invention, it is to be understood that the terms "central", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner" and "outer" and the like indicate orientations or positional relationships based on those shown in the drawings, and are used only for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
FIG. 1 is a flowchart of a method for automatic tracking of a log based on pixel optimization according to an embodiment of the present invention. As shown in fig. 1, a method for automatically tracking a log based on pixel optimization according to an embodiment of the present invention includes:
s1: and acquiring the pixel information of each pixel point in the logging image.
FIG. 2 is a graph of pixel information for each pixel point in a log image according to an example of the present invention. As shown in fig. 2, in one embodiment of the present invention, the pixel information includes RGB values of the pixel points.
S2: and giving a starting tracking point on a logging curve in the logging image, and performing transverse tracking according to the starting tracking point, a given color threshold value and a given transverse tracking distance.
Specifically, the present invention adopts a left-right tracking mode and then a downward tracking mode, so that the initial tracking point is the uppermost pixel point on the logging curve. It will be understood by those skilled in the art that when left-right tracking is performed first and then upward tracking is performed, the initial tracking point is a pixel point at the bottom of the log curve.
After the initial tracking point is obtained, left-right tracking is performed from the initial tracking point. In left-right tracking, tracking is performed according to a given color threshold and a lateral tracking distance. In one example of the invention, the log on the log image is black, the background image is white, the color threshold is a pixel value representing a solid black approximation, and the lateral tracking distance is 30 pixels. Because the logging curve has a large color difference with the background, the edge of the logging curve can be judged when the lateral tracking is carried out according to the color.
S3: and acquiring a current optimal point in the next row of pixels, and performing transverse tracking according to the current optimal point, the color threshold and the transverse tracking distance.
In one embodiment of the present invention, acquiring the current optimal point in the next row of pixels includes: in the transverse tracking range of the next row of pixels, coordinate points and pixel values in the color threshold range are stored in an array from left to right; calculating the average value of the horizontal coordinates of all the pixel points in the array; obtaining coefficients of all pixel points in the array according to the average value and a coefficient calculation formula; and taking the point with the minimum coefficient in the coefficients of all the pixel points in the array as the current optimal point.
FIG. 3 is a diagram of the solution of the optimal point Pc (x, y, v) for filtering the gridline disturbances in one example of the invention. As shown in fig. 3, P.x, P.y, and P.v are the abscissa, ordinate, and pixel value of the start tracking point P (x, y, v), respectively.
Coordinate points and pixel values within the color threshold range are saved from left to right into the array HPn (Xn, Yn, Vn) over the lateral tracking distance HL.
Obtaining the average distance AvgD of (Xn, Yn, Vn) according to the abscissa Xn of all the pixel points in the array, and obtaining the coefficient Ci of the Hpi (Xi, Yi, Vi) point according to the following formula:
Ci＝(Hpi.Xi-AvgD)/AvgD*0.5+(Hpi.Vi-P.v)/P.v*0.5
wherein Ci is the coefficient of the pixel point Hpi (Xi, Yi, Vi), Hpi.
The point Pc (x, y, v) with the minimum coefficient in the pixel point HPn (Xn, Yn, Vn) is taken as the optimal point and stored in the set VecP, the coefficient Ci is related to the pixel distance and the pixel value, and because the grid lines are generally thinner than the curve, and the optimal points with different colors and calculated by the formula can well avoid the interference of the grid lines.
Fig. 4 is a schematic diagram of elimination curve interference for solving the optimal point Pc (x, y, v) in another example of the present invention. . As shown in fig. 4, the shape trends of the curve are different due to the different colors of the curve and the curve, and the interference of the adjacent curve can be well eliminated by obtaining the optimal point through the formula.
S4: and repeating the step S3 until the distance between the initial tracking point and the current optimal point exceeds the given longitudinal tracking distance, and obtaining a final logging curve.
Specifically, the downward tracking is started from the current optimum point Pc (x, y, v), and the step S3 is repeated until the end of exceeding the longitudinal tracking range.
FIG. 5 is a schematic illustration of automatic log tracking according to an example of the present invention. As shown in fig. 5, the automatic tracking method for a logging curve based on pixel optimization provided in the embodiment of the present invention can automatically extract the logging curve from the logging image quickly and accurately, and has a good anti-interference effect.
Fig. 6 is a block diagram of an embodiment of an automatic log tracking device based on pixel optimization. As shown in fig. 6, the automatic tracking apparatus for a log based on pixel optimization according to an embodiment of the present invention includes: an acquisition module 100 and a control processing module 200.
The acquisition module 100 is used for acquiring a logging image. The control processing module 200 is configured to obtain pixel information of each pixel point in the log image, set an initial tracking point on a log curve in the log image, and perform lateral tracking according to the initial tracking point, a given color threshold, and a given lateral tracking distance. The control processing module 200 is further configured to obtain a current optimal point in a next row of pixels, and perform lateral tracking according to the optimal point, the color threshold, and the lateral tracking distance. The control processing module 200 is further configured to repeatedly acquire a current optimal point for performing lateral tracking until a distance between the initial tracking point and the current optimal point exceeds a given longitudinal tracking distance, so as to obtain a final logging curve.
In an embodiment of the present invention, the control processing module 200 is specifically configured to, within a horizontal tracking range in a next row of pixels, store coordinate points and pixel values within a color threshold range into an array from left to right, calculate an average value of abscissas of all pixel points in the array, obtain coefficients of all pixel points in the array according to an average value and coefficient calculation formula, and use a point with a minimum coefficient among the coefficients of all pixel points in the array as a current optimal point.
In one embodiment of the present invention, the coefficient calculation formula is:
Ci＝(Hpi.Xi-AvgD)/AvgD*0.5+(Hpi.Vi-P.v)/P.v*0.5
wherein Ci is a coefficient of the pixel point Hpi (Xi, Yi, Vi), hpi.xi is an abscissa of the pixel point Hpi (Xi, Yi, Vi), AvgD is an average of abscissas of all the pixel points in the array, hpi.vi is a pixel value of the pixel point Hpi (Xi, Yi, Vi), and P.v is a coordinate value of the initial tracking point.
In one embodiment of the present invention, the pixel information includes RGB values of the pixel points.
It should be noted that, a specific implementation of the device for automatically tracking a logging curve based on pixel optimization according to the embodiment of the present invention is similar to a specific implementation of the method for automatically tracking a logging curve based on pixel optimization according to the embodiment of the present invention, and specific reference is specifically made to the description of the method for automatically tracking a logging curve based on pixel optimization, and no further description is given for reducing redundancy.
In addition, other configurations and functions of the automatic tracking device for a log curve based on pixel optimization according to the embodiment of the present invention are known to those skilled in the art, and are not described in detail for reducing redundancy.
An embodiment of the present invention further provides an electronic device, including: at least one processor and at least one memory; the memory is to store one or more program instructions; the processor is configured to execute one or more program instructions to perform the method for automatic pixel-based optimization tracing of a well log according to the first aspect.
The embodiments disclosed herein provide a computer-readable storage medium having computer program instructions stored therein, which when run on a computer, cause the computer to perform the above-mentioned automatic tracing method for a well log based on pixel optimization.
In an embodiment of the invention, the processor may be an integrated circuit chip having signal processing capability. The Processor may be a general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component.
The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The processor reads the information in the storage medium and completes the steps of the method in combination with the hardware.
The storage medium may be a memory, for example, which may be volatile memory or nonvolatile memory, or which may include both volatile and nonvolatile memory.
The nonvolatile memory may be a Read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash memory.
The volatile Memory may be a Random Access Memory (RAM) which serves as an external cache. By way of example and not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (ddr Data Rate SDRAM), Enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM).
The storage media described in connection with the embodiments of the invention are intended to comprise, without being limited to, these and any other suitable types of memory.
Those skilled in the art will appreciate that the functionality described in the present invention may be implemented in a combination of hardware and software in one or more of the examples described above. When software is applied, the corresponding functionality may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
The above-mentioned embodiments, objects, technical solutions and advantages of the present invention are further described in detail, it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made on the basis of the technical solutions of the present invention should be included in the scope of the present invention.
Claims (10)
1. A log curve automatic tracking method based on pixel optimization is characterized by comprising the following steps:
s1: acquiring pixel information of each pixel point in a logging image;
s2: giving an initial tracking point on a logging curve in the logging image, and performing transverse tracking according to the initial tracking point, a given color threshold value and a given transverse tracking distance;
s3: obtaining a current optimal point in a next row of pixels, and performing transverse tracking according to the current optimal point, the color threshold and the transverse tracking distance;
s4: and repeating the step S3 until the distance between the starting tracking point and the current optimal point exceeds the given longitudinal tracking distance, and obtaining a final logging curve.
2. The method of claim 1, wherein obtaining a current optimal point in a next row of pixels comprises:
in the transverse tracking range of the next row of pixels, coordinate points and pixel values in the color threshold range are stored in an array from left to right;
calculating the average value of the horizontal coordinates of all the pixel points in the array;
obtaining coefficients of all pixel points in the array according to the average value and a coefficient calculation formula;
and taking the point with the minimum coefficient in the coefficients of all the pixel points in the array as the current optimal point.
3. The method of claim 2, wherein the coefficient calculation formula is:
Ci＝(Hpi.Xi-AvgD)/AvgD*0.5+(Hpi.Vi-P.v)/P.v*0.5
wherein Ci is a coefficient of a pixel point Hpi (Xi, Yi, Vi), hpi.xi is an abscissa of the pixel point Hpi (Xi, Yi, Vi), AvgD is an average of abscissas of all pixel points in the array, hpi.vi is a pixel value of the pixel point Hpi (Xi, Yi, Vi), and P.v is a coordinate value of the initial tracking point.
4. The method of claim 1, wherein the pixel information comprises RGB values of a pixel.
5. An automatic log tracking device based on pixel optimization, comprising:
the acquisition module is used for acquiring a logging image;
the control processing module is used for acquiring pixel information of each pixel point in a logging image, giving an initial tracking point on a logging curve in the logging image, and performing transverse tracking according to the initial tracking point, a given color threshold value and a given transverse tracking distance; the control processing module is further used for obtaining a current optimal point in a next row of pixels and performing transverse tracking according to the optimal point, the color threshold and the transverse tracking distance; and the control processing module is also used for repeatedly acquiring the current optimal point to perform transverse tracking until the distance between the initial tracking point and the current optimal point exceeds a given longitudinal tracking distance, so as to obtain a final logging curve.
6. The pixel-optimization-based automatic logging curve tracking device of claim 5, wherein the control processing module is configured to store coordinate points and pixel values within a color threshold range into an array from left to right within a horizontal tracking range in a next row of pixels, calculate an average value of abscissas of all pixel points in the array, obtain coefficients of all pixel points in the array according to the average value and coefficient calculation formula, and take a point with a smallest coefficient among the coefficients of all pixel points in the array as a current optimal point.
7. The device of claim 6, wherein the coefficient calculation formula is:
Ci＝(Hpi.Xi-AvgD)/AvgD*0.5+(Hpi.Vi-P.v)/P.v*0.5
wherein Ci is a coefficient of a pixel point Hpi (Xi, Yi, Vi), hpi.xi is an abscissa of the pixel point Hpi (Xi, Yi, Vi), AvgD is an average of abscissas of all pixel points in the array, hpi.vi is a pixel value of the pixel point Hpi (Xi, Yi, Vi), and P.v is a coordinate value of the initial tracking point.
8. The pixel-based optimization log curve automatic tracking device of claim 5, wherein the pixel information comprises RGB values of pixel points.
9. An electronic device, characterized in that the electronic device comprises: at least one processor and at least one memory;
the memory is to store one or more program instructions;
the processor, configured to execute one or more program instructions to perform the method for automatic pixel-based optimization log tracking according to any one of claims 1-4.
10. A computer readable storage medium having one or more program instructions embodied therein for performing the pixel-optimization-based automatic log tracking method of any of claims 1-4.
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