CN107843935B - XRMI electric imaging image automatic generation method - Google Patents
XRMI electric imaging image automatic generation method Download PDFInfo
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- CN107843935B CN107843935B CN201711002494.7A CN201711002494A CN107843935B CN 107843935 B CN107843935 B CN 107843935B CN 201711002494 A CN201711002494 A CN 201711002494A CN 107843935 B CN107843935 B CN 107843935B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
- G01V3/18—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation specially adapted for well-logging
- G01V3/26—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation specially adapted for well-logging operating with magnetic or electric fields produced or modified either by the surrounding earth formation or by the detecting device
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
- G01V3/18—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation specially adapted for well-logging
- G01V3/34—Transmitting data to recording or processing apparatus; Recording data
Abstract
The invention discloses an XRM I electrical imaging image automatic generation method, which comprises the following steps: (1) automatic selection judgment, loading and information identification of XRM I electrical imaging measurement data; (2) performing automatic statistical analysis judgment and data preprocessing on the quality performance of the data automatically selected and loaded in the step (1); (3) and automatically calibrating and processing the image according to the preprocessed data and automatically generating a display image according to the calibration and processing result. The method is simple to operate, and XRM I electrical imaging logging data can be automatically compiled and identified. In application, technicians only need to load XRM I electric imaging data, the software automatically performs data quality statistical analysis, data preprocessing, image processing and image display, various parameters do not need to be manually filled, and the error probability of manual operation is reduced, so that any person who is not in the well logging interpretation profession can quickly obtain XRM I electric imaging dynamic and static electric imaging effect diagrams.
Description
Technical Field
The invention relates to the technical field of geophysical petroleum geological logging, surveying and data analysis, in particular to an automatic image generation and processing method for processing XRMI electric imaging data to obtain a geological rock image, namely an automatic XRMI electric imaging image generation method
Background
The electric imaging well logging is an advanced well logging technology, has the characteristic of high resolution, can provide rich information of a well wall and the periphery of a well hole, can visually and qualitatively identify a bottom interface, a crack and a structural form from a well logging image, and can perform quantitative processing and analysis on the well logging image through an image processing method to extract parameters such as a stratum interface, a production condition and the like. The electric imaging well logging is widely applied to the aspects of exploration of complex oil and gas reservoirs, evaluation of heterogeneous reservoirs, analysis of ground stress and the like by virtue of the characteristics of high resolution and image intuition.
In the aspect of the electrical imaging logging image processing technology, more advanced electrical imaging processing interpretation software is developed abroad, mainly including Techog of Schlumberger corporation, eXpress of Atlas corporation and DPP of Harlibertn corporation. However, the software can only decode the home electronic imaging data format, and the software interface is in english, so the operation is complex, a large amount of professional knowledge is required, and the software is difficult to popularize and apply. The domestic electric imaging software mainly comprises FORWARD. However, in the process of generating the XRMI image, the software needs a large amount of manual judgment and data analysis, and needs to input various parameters manually, so that the operation is complex. And for non-professional well logging interpreters, it is difficult to process and generate an electrical imaging graph.
The applicant of the technical scheme is mainly technically engaged in development and use of petroleum logging and geological professional application software, researches on electrical imaging logging processing from 2001, and has more experience on electrical imaging logging image processing.
In the domestic work of electrical imaging logging, 65% of the work is done by a harebilton XRMI measurement instrument, while most technicians who use electrical imaging processing interpretation software for data analysis and image generation are not those who are professional in logging analysis. How to simplify the analysis, data processing and image analysis work of XRMI measurements is an important goal to alleviate the workload of the related technicians and to improve the work efficiency. Therefore, according to the characteristic of the XRMI measured electrical imaging data, the technical scheme of the XRMI measuring method can automatically decode logging data in different formats and automatically identify the measurement data of the XRMI electrical imaging instrument, so that an analyst can automatically obtain an electrical imaging result image and information only by guiding the XRMI measurement data by using the method.
Disclosure of Invention
In order to automatically realize the automatic image generation of XRMI electrical imaging measurement data, slow down the manual selection of various parameters by technicians and improve the efficiency of data analysis and image processing, the application provides the following automatic XRMI electrical imaging image generation method, which comprises the following steps:
(1) Automatic selection judgment, loading and information identification of XRMI electrical imaging measurement data;
(2) performing automatic statistical analysis judgment and data preprocessing on the quality performance of the data automatically selected and loaded in the step (1);
(3) And automatically calibrating and processing the image according to the preprocessed data and automatically generating a display image according to the calibration and processing result.
According to the technical scheme, automation is achieved on screening of data files, data loading and matching of corresponding data information, manual participation is not needed, statistics and analysis are automatically conducted on the integrity of the data and curve information contained in the data after the matched data are loaded, the data are corrected according to analysis results, and finally the corrected data are subjected to image processing to obtain a final XRMI electric imaging image; the whole method process is completely and automatically judged and analyzed, the data analysis efficiency and the image generation efficiency are improved, the workload of technicians is simplified, and the working efficiency is improved.
in the step (1) of the above method for automatically generating an XRMI electrical imaging image, when the XRMI electrical imaging measurement data is selected and judged, a data file package to be loaded is selected first, each data file in the data file package is read, the format of each data file is matched with different predefined well logging data format standards, if the data file contains 6 resistivity data sets with the length of 25 elements, and the data set names are XPAD1, XPAD2, XPAD3, XPAD4, XPAD5 and XPAD6, the data file is judged to belong to the XRMI electrical imaging measurement data file; if the measured data elements in the data file are all 1, determining the data as conventional logging data, and carrying out data correspondence and storage according to a conventional logging data dictionary; otherwise, data processing is exited and no XRMI electrical imaging measurement data is indicated in the data packet, and a selection of another data file packet is requested. In the method, after a user selects a data file package, a program reads each data file in the data file package, whether the file belongs to an XRMI electrical imaging measurement data file or conventional logging data is judged by using the method, and the two files can be accurately identified and screened by using the judging method. After the determination of the XRMI electrical imaging measurement data file is completed, the name and unit of the data are named according to the data dictionary according to the specification of the XRMI data dictionary. After the standard naming is carried out according to the data dictionary and the corresponding data file becomes a file with a standard format, the subsequent processing process can be carried out more conveniently.
In the information identification of XRMI electric imaging measurement data, measurement values of the top depth, the bottom depth and the drill diameter of a measurement well section are obtained from the data and automatically assigned, and operation parameters and conditions are provided for subsequent data processing and analysis.
In the step (2) of the above XRMI electrical imaging image automatic generation method, the statistical analysis, judgment and preprocessing of the quality performance of the XRMI electrical imaging measurement data includes the following steps: (a) judging whether the data comprise an electrical imaging curve, a well deviation azimuth curve, a well deviation angle curve, a drill bit radius curve and a relative azimuth curve, if any curve is lacked, quitting the processing process and prompting; (b) judging whether the data contain a Z-axis acceleration curve and a frame time curve, if so, performing acceleration correction on the data, otherwise, not performing acceleration correction; (c) judging whether the data contain a voltage curve, if so, performing voltage correction on the data, otherwise, not performing voltage correction; (d) and (4) judging whether the conventional logging data contain a shallow lateral curve, if so, performing shallow lateral calibration on the data, and otherwise, not performing shallow lateral calibration. Because the electrical imaging curve, the well deviation azimuth curve, the well deviation angle curve, the drill bit radius curve and the relative azimuth curve are necessary curves for data analysis and processing, and the absence of any curve can cause data processing errors, firstly, the existence of the 5 curves is judged, and then, the data is subjected to selective acceleration correction, voltage correction or shallow lateral calibration under the existence condition of the curves, so as to ensure that the data processing is finished.
In order to better consider the situation that the probe during measurement meets the card, the method judges whether the card is met during instrument detection through a Z-axis acceleration curve, namely, a card point exists, and then performs acceleration correction on the data according to the depth section of the card met by the instrument in the data, so as to further optimize and correct the data.
In the method for automatically generating the XRMI electrical imaging image, the step (2) of carrying out statistical analysis, judgment and pretreatment on the quality performance of the XRMI electrical imaging measurement data further comprises resistivity calibration, non-coplanar correction, electrical buckle depth alignment and amplitude normalization correction.
After the XRMI electric imaging data is processed and analyzed, the data is completely corrected, then image calibration before image generation is carried out, the calibration method comprises static color scale calibration and dynamic chromaticity calibration, and then filtering and image enhancement are carried out on the image to generate a static image and a dynamic image of a display image. In the image filtering, 3X3 cross filtering is adopted as a default, but filtering methods of 3X3 mean filtering, NXN mean filtering and NXN median filtering can be selected according to the filtered image effect to realize a clearer image; the image enhancement is carried out by adopting two methods of frequency domain enhancement and space enhancement.
The technical scheme of this application possesses following technological effect beneficial effect: (1) the whole method is simple to operate; (2) the method automatically compiles and identifies XRMI electric imaging logging data; (3) in the operation process of technicians, only XRMI electric imaging data is loaded, the software automatically performs data quality statistical analysis, data preprocessing, image processing and image display, various parameters do not need to be manually filled, and the error probability of manual operation is reduced; (4) by using the method, a person who is not a well logging interpretation professional can quickly obtain a dynamic and static electric imaging result picture.
Drawings
Fig. 1 is a flow chart diagram of an XRMI electrographic image automatic generation method.
Detailed Description
The method for automatically generating XRMI electric imaging images of the present invention is explained and illustrated in detail in the attached drawings.
As shown in fig. 1, the method of the present application includes three major steps: the method comprises the following steps: (1) automatic selection judgment, loading and information identification of XRMI electrical imaging measurement data; (2) performing automatic statistical analysis judgment and data preprocessing on the quality performance of the data automatically selected and loaded in the step (1); (3) and automatically calibrating and processing the image according to the preprocessed data and automatically generating a display image according to the calibration and processing result. Now separately described are the following: firstly, a user selects a data file packet to be loaded, reads each data file in the data file packet and matches the format of each data file with different predefined logging data format standards, the data with different formats comprises DLIS, LIS, XTF, CLS, LDF, TXT and the like, the logging data with different formats comprises a set of standards and specifications. And after the logging data are successfully matched, the software extracts the information of the data and then rewrites the data according to the defined data format. Thus, the logging data in different formats are loaded into the software and can be used for related analysis and calculation. XRMI differs from other electrical imaging log data by: the XRMI has six polar plates, the number of electric buckles of each polar plate is 25, if the measured data has 6 curves named as XPAD1, XPAD2, XPAD3, XPAD4, XPAD5 and XPAD6, and each element is 25, the data is used as the standard for judging the XRMI data. When the data is scanned, the scanned data meets the standard, and the data is judged to be XRMI electrical imaging data. The conventional logging data is characterized in that all elements of the logging curve are 1, and the conventional logging data can be used as a standard for judging the conventional curve, namely if the measured data elements in the data file are 1, the data is determined to be the conventional logging data, the data is corresponded and stored according to a conventional logging data dictionary, and the storage volume stored in the conventional logging curve is named as CONV. If the above-mentioned condition for determining XRMI electrical imaging measurement data is not satisfied, the data processing is exited and no XRMI electrical imaging measurement data is indicated in the data packet, and another data file packet is requested to be selected. After the determination of the XRMI electrical imaging measurement data file is completed, the name and unit of the data are named according to the data dictionary according to the specification of the XRMI data dictionary. After XRMI electrical imaging data are identified and confirmed, the depth range of 6 polar plate effective data with the name of 'XPAD (1-6)' of a logging curve is automatically counted, measured values of the top depth, the bottom depth and the diameter of a drill bit of a measured well section are automatically obtained from the data and assigned, and if the diameter of the drill bit has a plurality of values, the diameter value of the drill bit corresponding to the deepest depth of the well section is selected.
the step (2) of carrying out statistical analysis, judgment and pretreatment on the quality performance of XRMI electric imaging measurement data comprises the following steps: (a) judging whether the data comprise an electrical imaging curve, a well deviation azimuth curve, a well deviation angle curve, a drill bit radius curve and a relative azimuth curve, if any curve is lacked, quitting the processing process and prompting; (b) judging whether the data contain a Z-axis acceleration curve and a frame time curve, if so, performing acceleration correction on the data, otherwise, not performing acceleration correction; (c) judging whether the data contain a voltage curve, if so, performing voltage correction on the data, otherwise, not performing voltage correction; (d) and (4) judging whether the conventional logging data contain a shallow lateral curve, if so, performing shallow lateral calibration on the data, and otherwise, not performing shallow lateral calibration. The XRMI electrographic data list in the above determination is shown in table 1.
Table 1: XRMI electrical imaging data name list correspondence
And the process also comprises card encountering judgment, and if the card encountering is judged in the instrument detection through the Z-axis acceleration curve, namely a card point exists, the acceleration correction is carried out on the data according to the depth section of the card encountering of the instrument in the data. The instrument jam determination is based on the fact that due to the elasticity of the cable, the velocity of the instrument cannot be kept constant over any interval of the well unless it is always equal to the cable velocity. Therefore, when the measured acceleration curve shows a straight line segment in a certain time window and is close to a zero value, and the predicted speed of the instrument at the starting point of the time window is far less than the speed of the wellhead cable, the instrument can be basically judged to encounter the jam. In addition, when the acceleration curve meets the card, damping vibration can occur, a negative value appears at the moment of card stopping, a great straight line appears during recovery, and meanwhile, the cable tension curve is gradually increased when the card meets. The detection method comprises the following steps: when the minimum variation of the gravity acceleration is smaller than the detection lower limit, the instrument is considered to be blocked, and the default value of the detection lower limit is 0.01; and after the instrument meets the card, when the change of the gravity acceleration is larger than a certain value, the instrument is considered to be unlocked. The measuring data recording instrument sends the depth section of the card to be detected to the preprocessing for acceleration correction. The statistical analysis, judgment and pretreatment of the quality performance of the XRMI electrical imaging measurement data further comprise resistivity calibration, non-coplanar correction, electrical buckle depth alignment and amplitude normalization correction. The specific implementation of each correction is as follows:
(1) And voltage correction, namely performing voltage correction when a prompt of 'voltage correction' is received. Because the electrical property change range of some strata is large, in order to record the slight change condition of local strata as much as possible, the voltage measurement range needs to be changed in real time, so that the same current value recorded in different well sections possibly represents different stratum properties, and therefore, the voltage correction needs to be carried out on the whole well section in the pretreatment process, and the recorded current or conductivity can reflect the electrical property of the strata which is consistent. When voltage correction is performed, the correction factor is EMMRmaxEMMR, because EMMR reaches a maximum value when the electrical buckle response is the weakest, the correction factor is close to 1, and weak signals are not influenced by the correction factor too much, thereby being close to the conductivity of the stratum. The calibration method is as follows, the measured current I of each buckle is divided by the EMMR supply voltage VEMMRMultiplying by a correction factor to obtain the apparent conductivity C of each electric bucklei：Wherein: k is the correction factor EMMRmax/EMMR，IiIs the measured value of each electric buckle.
2) And (3) resistivity calibration, namely if the data recorded by field data acquisition is original data and is not converted into the resistivity or the conductivity of each scanning electric button, performing the resistivity calibration. The resistivity scales of different instruments are different, and the resistivity scale formula of the XRMI instrument is as follows: ri,j＝ρ×EMEX(i)/(xi,j×0.3452×12.5×10-6)+10-6Wherein: ρ is the scale factor, EMEX (i) is the voltage value recorded for each depth point, xi,jMeasured electricity for each electric buckleFlow value, Ri,jResistivity after each electrical snap-off calibration.
(3) And (4) performing electric imaging acceleration correction, and performing acceleration correction on the whole well section after receiving the prompt of performing acceleration correction. And after receiving the depth section of the instrument encountering the card, performing acceleration correction again in the depth section. The instrument does non-uniform motion in the borehole, particularly the instrument encounters jamming, jam release or short stay in the borehole, and the wellhead cable still shows the uniform motion, so that the real depth of the instrument has non-systematic deviation with the depth of the wellhead cable, and the corresponding relation between the curve sampling value and the real depth is influenced. The acceleration correction is to recover the true depth corresponding to the sampling data and eliminate curve deformation caused by non-uniform motion of the instrument. The velocity correction (i.e., acceleration correction) equation is as follows: v ═ a ═ Δ t, h ═ V ^ Δ t, V is the cable speed, h is the true depth of the sampled data, a is the instrument motion acceleration, and Δ t is the sampling time.
(4) The non-coplanar correction, XRMI electric imaging logger is pushed against the borehole wall to measure, and the 6 pushing arms of the logger can move independently to independently carry out the hole diameter calibration and measurement. The flexible pushing arm can ensure that each polar plate can be tightly attached to the well arm under the condition of complex well hole conditions, and a reliable measuring result is obtained. If a plurality of polar plates of the XRMI electric imaging logging instrument are not on the same plane when folded, namely the opening angle of each electrode arm is different, the measuring point of each electrode is not at the same depth at the moment and does not belong to the same geometric plane, and the response depth of the electrode is corrected when the situation occurs, namely the non-coplanar correction is performed.
(5) The depth of the electric buckles is aligned, two rows of electrodes are arranged on each electrode of the XRMI electric imaging logging instrument, a fixed distance exists between different rows of electrodes in the longitudinal direction, meanwhile, a certain depth difference also exists between adjacent polar plates in the longitudinal direction, and data recorded by the electric buckles of different rows of each polar plate reflect different depths of the well wall, so that the electric buckles of different rows of each polar plate must be aligned in depth. The distance between the upper row of electric buckles and the lower row of electric buckles of the XRMI polar plate is 0.3 inch, the vertical distance between the polar plate and the corresponding electric buckles of the polar plate is 2.4 inches, the odd polar plate is provided with 12 electric buckles in the first row and 13 electric buckles in the second row, the even polar plate is just opposite, and the odd polar plate and the even polar plate are arranged in a staggered mode. The depth alignment method of the electric buckles adopted by the software takes the second row (the lowest row) of the odd pole plates as a reference, and moves other rows of electrodes to finish depth correction, and the method comprises the following specific steps: (1) odd number buckles of the odd pole plate are taken as the measuring reference: in the process of aligning the electric buckles, the polar plates of other rows move corresponding distances to be aligned with the electric buckles in the row; (2) aligning the electric buckles in the polar plates: even numbered pole button data of the same pole plate recorded simultaneously with the reference pole button is actually measured at a depth of 0.3 inches vertically above the reference pole button, so the even numbered pole button data needs to be moved up by 0.3 inches. Typical XRMI has a sampling spacing of 0.1 inch, i.e., 3 sampling intervals shifted up; (3) similarly, the dipole plate dipole buttons move up 2.4 inches, i.e., 24 sampling intervals; (4) similarly, the dipole plate odd electrical clasp is moved up 2.7 inches, i.e., 27 sampling intervals.
(6) Amplitude normalization, the electrical imaging XRMI, with 150 electrical taps, varied in contact with the borehole wall, and the electrode sensitivities were not identical, so that all electrodes had substantially the same average response over a longer interval. In the logging process, random factors such as a mud film, an oil film or other pollutants formed on the surface of each electric buckle continuously change, so that for stratums with the same conductivity, data acquired by each electric buckle electrode are different, and the response characteristics are difficult to be consistent. Curve normalization is to have all electrodes have substantially the same average response over a longer interval.
(7) And (3) shallow lateral calibration, which is to scale the electric buckle measurement value of the micro-resistivity scanning imaging logging into the resistivity or the conductivity of the stratum by means of shallow lateral logging, and aims to use the imaging image after the scaling for predicting the porosity of the crack and the high-resolution electric buckle resistivity curve after the scaling for thin layer analysis and the like.
After the correction process is completed, image calibration and processing are finally carried out, and a display image is automatically generated according to the calibration and processing result. The method comprises the following steps: (1) and (4) image calibration, namely establishing a corresponding relation between the amplitude of a scanning curve and gray scale or chroma by using a static color scale calibration method and a dynamic chroma calibration method, and calibrating chroma according to the principle that each chroma or gray scale occupies equal frequency.
And (4) calibrating a static color code, wherein the purpose of the static color code calibration is to perform lithology identification and formation comparison in the whole treatment well section. The method is to make one-time frequency statistics on the whole treatment interval or target interval and carry out chromaticity calibration according to the principle that each chromaticity or gray level accounts for equal frequency, so that the overall change characteristic of the conductivity in the well section can be kept, and the fine change of the conductivity can be reflected to a certain extent. The specific operation steps are as follows: (1) counting the maximum value V of the polar plate data of the whole well sectionmin、Vmax(ii) a (2) According to the maximum value V of the polar plate datamin、VmaxAnd color code Cmin、CmaxTo calculate the scale factor S, Voffset：S＝(Cmax-Cmin)/(Vmax-Vmin)，Voffset＝Cmin-VminX S; (3) and linearly scaling the polar plate data into a color code value to finish static color code calibration. Vpixel＝Vi×S+VoffsetWherein V isiThe value of the current measured for each button, VpixelThe color scale value after calibration.
And (3) dynamic color scale calibration, wherein when the change range of the measured formation conductivity value is large, a dynamic colorimetric calibration method is adopted in order to clearly display small conductivity contrast in an image. I.e. within a small depth, a static chromaticity calibration is made for the sliding window length (typically less than 3ft) according to the user's requirements. There is a partial overlap between adjacent window lengths. This, while losing the overall change in conductivity characteristic within the treatment interval, highlights the local change in conductivity characteristic in greater detail.
image filtering, which comprises the following four methods: 3X3 mean filtering, 3X3 cross filtering, NXN mean filtering, NXN median filtering.
And the image enhancement adopts two methods of frequency domain enhancement and space enhancement.
Frequency domain enhancement, also known as contrast enhancement, can make the original low-contrast image undergo the enhancement of a frequency domain enhancement transform function (linear or non-linear) to make certain features more obvious. For linear contrast enhancement, the log is extended to the 0-255 gray scale range to fully utilize the gray scale that can be displayed by the display. For example: in both mudstone and non-mudstone intervals, XRMI log values are split into two groups, with the low value groups (non-mudstone intervals) being enhanced linearly and the high value groups being assigned 255. The high value groups are classified into mudstones and not subdivided. The low value set is linearly graded from 0 to 255, highlighting the enhancement of the image of the non-mudstone formation.
Spatial enhancement, the basic method of which is spatial filtering; the amount of change in the gray value per unit distance for any part of an image is called the spatial frequency. The spatial filtering is performed at spatial frequencies. When the spatial frequency is zero, the image is a picture with unchanged gray scale; when the spatial frequency is low, the gray scale in the image is smoothly changed. The high spatial frequency corresponds to the image gray scale which changes rapidly, and the spatial frequency of the black and white picture is the highest. In order to carry out spatial filtering, a weighting matrix is firstly designed, and the gray scale of a central point is replaced by the gray scale weighted average value of each point in the neighborhood, so that the spatial frequency of the image can be changed.
And image generation, including static image generation and dynamic image generation, wherein imaging logging data is subjected to data preprocessing and color scale calibration, and then an imaging color spectrum generated by mapping is used for obtaining a color matrix of each polar plate, the azimuth position of each polar plate measuring electric buckle is calculated according to an azimuth curve determined by the three magnetic flux data, and finally the color matrix is drawn on a computer screen according to the azimuth position.
the above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and simplifications made in the spirit of the present invention are intended to be included in the scope of the present invention.
Claims (7)
- An XRMI electrographic image automatic generation method, the method comprising the steps of:(1) Automatic selection judgment, loading and information identification of XRMI electrical imaging measurement data; when the XRMI electrical imaging measurement data is selected and judged, firstly, a data file package needing to be loaded is selected, each data file in the data file package is read, the format of each data file is matched with different predefined logging data format standards, if the data file contains 6 resistivity data groups with the length of 25 elements, and the data group names are XPAD1, XPAD2, XPAD3, XPAD4, XPAD5 and XPAD6, the data file is judged to belong to the XRMI electrical imaging measurement data file; if the measured data elements in the data file are all 1, determining the data as conventional logging data, and carrying out data correspondence and storage according to a conventional logging data dictionary; otherwise, quitting data processing and indicating that no XRMI electric imaging measurement data exists in the data file packet, and requesting to select other data file packets;(2) And (2) carrying out automatic statistical analysis judgment and data preprocessing on the quality performance of the data automatically selected and loaded in the step (1), wherein the method specifically comprises the following steps: (a) judging whether the data comprise an electrical imaging curve, a well deviation azimuth curve, a well deviation angle curve, a drill bit radius curve and a relative azimuth curve, if any curve is lacked, quitting the processing process and prompting; (b) judging whether the data contain a Z-axis acceleration curve and a frame time curve, if so, performing acceleration correction on the data, otherwise, not performing acceleration correction; (c) judging whether the data contain a voltage curve, if so, performing voltage correction on the data, otherwise, not performing voltage correction; (d) judging whether the conventional logging data contain shallow lateral curves, if so, performing shallow lateral calibration on the data, otherwise, not performing shallow lateral calibration;(3) And automatically calibrating and processing the image according to the preprocessed data and automatically generating a display image according to the calibration and processing result.
- 2. the method of claim 1, wherein upon completion of the determination of the XRMI electrical imaging measurement data file, the data is subjected to canonical naming of names and units according to the XRMI data dictionary.
- 3. The method of claim 1 or claim 2, wherein the information identifying the XRMI electrogram measurement data comprises obtaining and automatically assigning measurements of top depth, bottom depth, and bit diameter of the measured well section from the data.
- 4. the method of claim 1, wherein if the occurrence of an instrument jam during instrument detection is determined by the Z-axis acceleration curve, i.e., if a jam point exists, then performing acceleration correction on the data according to the depth segment of the instrument jam in the data.
- 5. The method of claim 3, wherein the step (2) of statistically analyzing, determining and preprocessing the quality of the XRMI electrographic measurement data further comprises resistivity calibration, non-coplanarity correction, electrical snap depth alignment, and amplitude normalization correction.
- 6. The method of claim 1, wherein the image scaling in step (3) includes static color scale scaling and dynamic chrominance scaling, and the image processing includes image filtering and image enhancement, and generates the static image and the dynamic image of the display image.
- 7. The method of claim 6, wherein the image filtering defaults to 3X3 cross filtering while preserving filtering methods employing 3X3 mean filtering, NXN median filtering; the image enhancement is carried out by adopting two methods of frequency domain enhancement and space enhancement.
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