CN111932654B - Automatic tracking method and device for logging curve based on pixel optimization and electronic equipment - Google Patents
Automatic tracking method and device for logging curve based on pixel optimization and electronic equipment Download PDFInfo
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- CN111932654B CN111932654B CN202010740028.4A CN202010740028A CN111932654B CN 111932654 B CN111932654 B CN 111932654B CN 202010740028 A CN202010740028 A CN 202010740028A CN 111932654 B CN111932654 B CN 111932654B
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- G06—COMPUTING; CALCULATING OR COUNTING
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Abstract
The embodiment of the invention discloses a logging curve automatic tracking method, a device and electronic equipment based on pixel optimization, 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 carrying out transverse tracking according to the initial tracking point, a given color threshold value and a given transverse tracking distance; s3: acquiring a current optimal point in the next row of pixels, and carrying out 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 initial tracking point and the current optimal point exceeds a given longitudinal tracking distance, and obtaining a final logging curve. The invention can automatically extract the well logging curve from the well logging image rapidly 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 oil field exploration and production process, and has important significance for guiding oil field development. Because of the numerous parameters measured, the logging process involves multiple instruments from multiple companies, and the logging data is often presented in the form of curves in the pictures, which requires automatic extraction of the picture log data.
Because of a large number of background grids and curves or curves interweaved with the curves in the log 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 conventional logging curve is very difficult to automatically track.
In order to achieve the above purpose, the embodiment of the present invention mainly provides the following technical solutions:
in a first aspect, an embodiment of the present invention provides a method for automatically tracking a log 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 carrying out transverse tracking according to the initial tracking point, a given color threshold value and a given transverse tracking distance; s3: acquiring a current optimal point in the next row of pixels, and carrying out 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 initial tracking point and the current optimal point exceeds a given longitudinal tracking distance, and obtaining a final logging curve.
According to one embodiment of the present invention, obtaining the current optimal point in the next row of pixels includes: in the transverse tracking range of the next row of pixels, storing coordinate points and pixel values in the color threshold range into an array from left to right; calculating the average value of the abscissa of all pixel points in the array; obtaining coefficients of all pixel points in the array according to the average value and the coefficient calculation formula; and taking the point with the smallest coefficient in the coefficients of all pixel points in the array as the current optimal point.
According to 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
where Ci is the coefficient of the pixel Hpi (Xi, yi, vi), hpi.xi is the abscissa of the pixel Hpi (Xi, yi, vi), avgD is the average value of the abscissas of all the pixels in the array, hpi.vi is the pixel value of the pixel Hpi (Xi, yi, vi), and P.v is the coordinate value of the start tracking point.
According to one embodiment of the invention, the pixel information includes RGB values of the pixel points.
In a second aspect, an embodiment of the present invention further provides an apparatus for automatically tracking a log based on pixel optimization, including: the acquisition module is used for acquiring the logging image; the control processing module is used for acquiring pixel information of each pixel point in the well logging image, giving an initial tracking point on a well logging curve in the well logging image, and carrying out transverse tracking according to the initial tracking point, a given color threshold value and a given transverse tracking distance; the control processing module is also used for acquiring the current optimal point in the next row of pixels and carrying out transverse tracking according to the optimal point, the color threshold and the transverse tracking distance; the control processing module is further used for repeatedly acquiring the current optimal point to carry out transverse tracking until the distance between the initial tracking point and the current optimal point exceeds a given longitudinal tracking distance, and a final logging curve is obtained.
According to one embodiment of the present invention, the control processing module is configured to store, from left to right, coordinate points and pixel values in a color threshold range into an array in a lateral tracking range in a next row of pixels, calculate an average value of abscissa coordinates 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 use a point with a minimum coefficient in coefficients of all pixel points in the array as a current optimal point.
According to 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
where Ci is the coefficient of the pixel Hpi (Xi, yi, vi), hpi.xi is the abscissa of the pixel Hpi (Xi, yi, vi), avgD is the average value of the abscissas of all the pixels in the array, hpi.vi is the pixel value of the pixel Hpi (Xi, yi, vi), and P.v is the coordinate value of the start tracking point.
According to one embodiment of the invention, the pixel information includes 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 used for storing one or more program instructions; the processor is configured to execute one or more program instructions configured to perform the method for automatically tracking a log based on pixel-optimization as described in the first aspect.
In a fourth aspect, embodiments of the present invention also provide a computer readable storage medium containing one or more program instructions for being executed with the pixel-based optimized log automatic tracking method according to the first aspect.
The technical scheme provided by the embodiment of the invention has at least the following advantages:
the method, the device and the electronic equipment for automatically tracking the logging curve based on pixel optimization provided by the embodiment of the invention can be used for automatically extracting the logging curve from the logging image rapidly and accurately, and have good anti-interference effect.
Drawings
FIG. 1 is a flowchart of an embodiment of an automatic tracking method of a log based on pixel optimization.
FIG. 2 is a diagram of pixel information for each pixel in a log image in accordance with one example of the present invention.
FIG. 3 is a schematic diagram of solving for the optimum Pc (x, y, v) filter grid line disturbance in one example of the invention.
Fig. 4 is a schematic diagram of solving the optimal point Pc (x, y, v) excluding curve interference in another example of the present invention.
FIG. 5 is a schematic diagram of automatic tracking of a log in accordance with one example of the present invention.
Fig. 6 is a block diagram of an embodiment of an automatic tracking device for a log based on pixel optimization.
Detailed Description
Further advantages and effects of the present invention will become apparent to those skilled in the art from the disclosure of the present invention, which is described by the following specific examples.
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, 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 should be understood that the terms "center", "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner" and "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific 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 an embodiment of an automatic tracking method of a log based on pixel optimization. As shown in fig. 1, the automatic tracking method of a logging curve based on pixel optimization according to an embodiment of the present invention includes:
s1: and acquiring pixel information of each pixel point in the well logging image.
FIG. 2 is a diagram of pixel information for each pixel in a log image in accordance with one 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 an initial tracking point on a logging curve in the logging image, and carrying out transverse tracking according to the initial tracking point, the given color threshold and the given transverse tracking distance.
Specifically, the invention adopts a mode of tracking left and right and then tracking downwards, so that the initial tracking point is the uppermost pixel point on the logging curve. It will be appreciated by those skilled in the art that when tracking left and right and then up is used, the initial tracking point is the lowest pixel point on the log.
After the initial tracking point is obtained, left and right tracking is performed from the initial tracking point. In the left-right tracking, tracking is performed according to a predetermined 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 phase, and the lateral tracking distance is 30 pixels. Because the color of the logging curve is greatly different from that of 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 the current optimal point in the next row of pixels, and carrying out transverse tracking according to the current optimal point, the color threshold value and the transverse tracking distance.
In one embodiment of the invention, the current optimal point in the next row of pixels is obtained, including: in the transverse tracking range of the next row of pixels, storing coordinate points and pixel values in the color threshold range into an array from left to right; calculating the average value of the abscissa of all pixel points in the array; obtaining coefficients of all pixel points in the array according to the average value and the coefficient calculation formula; and taking the point with the smallest coefficient in the coefficients of all pixel points in the array as the current optimal point.
FIG. 3 is a schematic diagram of solving for the optimum Pc (x, y, v) filter grid line disturbance in one example of the invention. As shown in fig. 3, P.x, P.y, and P.v are the abscissa, the ordinate, and the pixel value of the start tracking point P (x, y, v), respectively.
Coordinate points and pixel values within the color threshold range are saved into an array HPn (Xn, yn, vn) from left to right within the range of the lateral tracking distance HL.
According to the abscissa Xn of all pixel points in the array, the average distance AvgD of (Xn, yn, vn) is obtained, and the coefficient Ci of the Hpi (Xi, yi, vi) point is obtained according to the following formula:
Ci＝(Hpi.Xi-AvgD)/AvgD*0.5+(Hpi.Vi-P.v)/P.v*0.5
where Ci is the coefficient of the pixel point Hpi (Xi, yi, vi), hpi.xi is the abscissa of the pixel point Hpi (Xi, yi, vi), avgD is the average value of the abscissas of all the pixel points in the array, and hpi.vi is the pixel value of the pixel point Hpi (Xi, yi, vi).
The point Pc (x, y, v) with the smallest coefficient in the pixel points HPn (Xn, yn, vn) is stored into the VecP as the optimal point, the coefficient Ci is related to the pixel distance and the pixel value, and the interference of the grid lines can be well avoided due to the fact that the grid lines are generally thinner than the curve and the optimal points calculated through the formula are different in color.
Fig. 4 is a schematic diagram of solving the optimal point Pc (x, y, v) excluding curve interference in another example of the present invention. . As shown in FIG. 4, the curves and the curves have different morphological trends due to different colors, and the optimal point obtained by the formula can well eliminate the interference of adjacent curves.
S4: and (3) repeating the step (S3) until the distance between the initial tracking point and the current optimal point exceeds a given longitudinal tracking distance, and obtaining a final logging curve.
Specifically, tracking down from the current optimum point Pc (x, y, v), step S3 is repeated until the end of the out-of-longitudinal tracking range.
FIG. 5 is a schematic diagram of automatic tracking of a log in accordance with one example of the present invention. As shown in fig. 5, the method for automatically tracking the logging curve based on pixel optimization provided by the embodiment of the invention can be used for automatically extracting the logging curve from the logging image rapidly and accurately, and has good anti-interference effect.
Fig. 6 is a block diagram of an embodiment of an automatic tracking device for a log based on pixel optimization. As shown in fig. 6, the automatic log tracking device based on pixel optimization according to the embodiment of the invention includes: an acquisition module 100 and a control processing module 200.
Wherein 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 in the log image, and set a starting tracking point on a log curve in the log image, and perform lateral tracking according to the starting tracking point, the set color threshold, and the set lateral tracking distance. The control processing module 200 is further configured to obtain a current optimal point in the 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 the current optimal point for performing lateral tracking until the distance between the initial tracking point and the current optimal point exceeds the given longitudinal tracking distance, so as to obtain a final log.
In one embodiment of the present invention, the control processing module 200 is specifically configured to store, from left to right, coordinate points and pixel values in the color threshold range in the lateral tracking range in the next row of pixels, calculate an average value of abscissa coordinates 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 use a point with the smallest coefficient in the coefficients of all pixel points in the array as a current optimal point.
In one embodiment of the invention, the coefficient calculation formula is:
Ci＝(Hpi.Xi-AvgD)/AvgD*0.5+(Hpi.Vi-P.v)/P.v*0.5
where Ci is the coefficient of the pixel point Hpi (Xi, yi, vi), hpi.xi is the abscissa of the pixel point Hpi (Xi, yi, vi), avgD is the average value of the abscissas of all the pixel points in the array, hpi.vi is the pixel value of the pixel point Hpi (Xi, yi, vi), and P.v is the coordinate value of the start tracking point.
In one embodiment of the invention, the pixel information includes RGB values of the pixel points.
It should be noted that, the specific implementation manner of the automatic log tracking device based on pixel optimization in the embodiment of the present invention is similar to the specific implementation manner of the automatic log tracking method based on pixel optimization in the embodiment of the present invention, specifically refer to the description of the part of the automatic log tracking method based on pixel optimization, and in order to reduce redundancy, details are not repeated.
In addition, other configurations and functions of the automatic log tracking device based on pixel optimization according to the embodiments of the present invention are known to those skilled in the art, and are not described in detail for reducing redundancy.
The embodiment of the invention also provides electronic equipment, which comprises: at least one processor and at least one memory; the memory is used for storing one or more program instructions; the processor is configured to execute one or more program instructions configured to perform the method for automatically tracking a log based on pixel-optimization as described in the first aspect.
The disclosed embodiments provide a computer readable storage medium having stored therein computer program instructions that, when run on a computer, cause the computer to perform the above-described pixel-optimizing-based log automatic tracking method.
In the embodiment of the invention, the processor may be an integrated circuit chip with signal processing capability. The processor may be a general purpose processor, a digital signal processor (Digital Signal Processor, DSP for short), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), a field programmable gate array (FieldProgrammable GateArray, FPGA for short), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components.
The disclosed methods, steps, and logic blocks 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 embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The processor reads the information in the storage medium and, in combination with its hardware, performs the steps of the above method.
The storage medium may be memory, for example, may be volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory.
The nonvolatile memory may be Read-only memory (ROM), programmable ROM (PROM), erasable PROM (EPROM), electrically Erasable ROM (Electrically EPROM, EEPROM), or flash memory.
The volatile memory may be a random access memory (Random Access Memory, RAM for short) which acts as an external cache. By way of example, and not limitation, many forms of RAM are available, such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (Double Data Rate SDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), and direct memory bus RAM (Direct Rambus RAM, DRRAM).
The storage media described in embodiments of the present 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 in one or more of the examples described above, the functions described in the present invention may be implemented in a combination of hardware and software. When the software is applied, the corresponding functions may be stored in a computer-readable medium or transmitted as one or more instructions or code on the 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 foregoing embodiments have been provided for the purpose of illustrating the general principles of the present invention in further detail, and are not to be construed as limiting the scope of the invention, but are merely intended to cover any modifications, equivalents, improvements, etc. based on the teachings of the invention.
Claims (6)
1. The automatic tracking method of the logging curve based on pixel optimization is characterized by comprising the following steps of:
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 carrying out transverse tracking according to the initial tracking point, a given color threshold value and a given transverse tracking distance;
s3: acquiring a current optimal point in the next row of pixels, and carrying out transverse tracking according to the current optimal point, the color threshold and the transverse tracking distance;
s4: repeating the step S3 until the distance between the initial tracking point and the current optimal point exceeds a given longitudinal tracking distance, and obtaining a final logging curve;
acquiring the current optimal point in the next row of pixels comprises:
in the transverse tracking range of the next row of pixels, storing coordinate points and pixel values in the color threshold range into an array from left to right;
calculating the average value of the abscissa of all pixel points in the array;
obtaining coefficients of all pixel points in the array according to the average value and the coefficient calculation formula;
taking the point with the smallest coefficient in the coefficients of all pixel points in the array as the current optimal point;
the coefficient calculation formula is as follows:
Ci＝(Hpi.Xi-AvgD)/AvgD*0.5+(Hpi.Vi-P.v)/P.v*0.5
where Ci is the coefficient of the pixel Hpi (Xi, yi, vi), hpi.xi is the abscissa of the pixel Hpi (Xi, yi, vi), avgD is the average value of the abscissas of all the pixels in the array, hpi.vi is the pixel value of the pixel Hpi (Xi, yi, vi), and P.v is the coordinate value of the start tracking point.
2. The method of claim 1, wherein the pixel information comprises RGB values of the pixel points.
3. An automatic log tracking device based on pixel optimization, which is characterized by comprising:
the acquisition module is used for acquiring the logging image;
the control processing module is used for acquiring pixel information of each pixel point in the well logging image, giving an initial tracking point on a well logging curve in the well logging image, and carrying out 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 the next row of pixels and carrying out transverse tracking according to the current optimal point, the color threshold and the transverse tracking distance; the control processing module is also used for repeatedly acquiring the current optimal point to carry out 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;
the control processing module is used for storing coordinate points and pixel values in a color threshold range into an array from left to right in a transverse tracking range in the next row of pixels, calculating the average value of the abscissa of all the pixel points in the array, obtaining the coefficients of all the pixel points in the array according to the average value and a coefficient calculation formula, and taking the point with the smallest coefficient in the coefficients of all the pixel points in the array as the current optimal point;
the coefficient calculation formula is as follows:
Ci＝(Hpi.Xi-AvgD)/AvgD*0.5+(Hpi.Vi-P.v)/P.v*0.5
where Ci is the coefficient of the pixel Hpi (Xi, yi, vi), hpi.xi is the abscissa of the pixel Hpi (Xi, yi, vi), avgD is the average value of the abscissas of all the pixels in the array, hpi.vi is the pixel value of the pixel Hpi (Xi, yi, vi), and P.v is the coordinate value of the start tracking point.
4. The pixel-optimizing-based log automatic tracking device of claim 3, wherein the pixel information comprises RGB values of a pixel point.
5. An electronic device, the electronic device comprising: at least one processor and at least one memory;
the memory is used for storing one or more program instructions;
the processor configured to execute one or more program instructions to perform the pixel-based optimization well-logging curve auto-tracking method of any one of claims 1-2.
6. A computer readable storage medium having one or more program instructions embodied therein for performing the pixel-based optimization method of log auto-tracking as recited in any one of claims 1-2.
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