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CN-122017998-A - Method and application for correcting logging sound wave speed to VSP speed trend based on automatic segmentation

CN122017998ACN 122017998 ACN122017998 ACN 122017998ACN-122017998-A

Abstract

The invention provides a method for correcting a logging sound wave speed to a VSP speed trend based on automatic segmentation and application thereof, and relates to the technical field of oil and gas exploration. The method comprises the steps of collecting logging sound wave speed data, VSP data and geological stratification data, preprocessing and calibrating, analyzing the obtained VSP data, identifying a main speed change horizon or speed trend, constructing the change rate of the VSP speed, automatically segmenting the logging sound wave speed data by utilizing an automatic algorithm according to the VSP speed trend and stratum characteristics, fitting the logging sound wave speed in each segment by utilizing a mathematical function to obtain a correction factor or a correction curve, and correcting the logging sound wave speed, quality control and result output. The method not only improves exploration efficiency and accuracy, reduces cost, but also enhances the interpretability of data, and provides powerful support for oil and gas exploration and development.

Inventors

  • WANG CHAO
  • LI ZONGJIE
  • LIU WENKUI
  • HAN JUN
  • LI GUOYUAN
  • CHAI MINGRUI

Assignees

  • 中国石油化工股份有限公司
  • 中国石油化工股份有限公司西北油田分公司

Dates

Publication Date
20260512
Application Date
20241111

Claims (18)

  1. 1. A method for correcting a logging acoustic velocity to a VSP velocity trend based on automatic segmentation, comprising the steps of: Step 1, data preparation, namely collecting logging sound wave velocity data, VSP data and geological stratification data; Step 2, preprocessing the data, namely preprocessing logging sound wave velocity data and VSP data, and then calibrating; Analyzing the VSP data obtained in the step 2, identifying a main speed change horizon or speed trend, and constructing the change rate of the VSP speed; Step 4, automatically segmenting logging sound wave speed data by utilizing an automatic algorithm according to VSP speed trend and stratum characteristics; Step 5, fitting the logging sound wave speed in each section by using a mathematical function to obtain a correction factor or a correction curve; Correcting the logging sound wave speed, namely correcting the original logging sound wave speed according to a correction factor or a correction curve obtained by fitting; Step 7, quality control, namely performing quality check on the corrected logging sound wave speed to ensure that unreasonable speed change or abnormal value is not introduced in the correction process; and 8, outputting a result, namely outputting corrected data.
  2. 2. The method of claim 1, wherein in step 1, the logging sonic velocity data comprises target well and adjacent well depth, sonic logging velocity, the VSP data comprises target well and adjacent well depth, VSP logging velocity, and the geologic stratification data comprises well depth and horizon information.
  3. 3. The method of claim 1, wherein in step 2, the preprocessing comprises at least one of cleaning, filtering, denoising, and rejecting outliers, missing values, or erroneous data.
  4. 4. The method according to claim 1, wherein in step 2, the calibration comprises a depth and/or time calibration.
  5. 5. The method according to claim 1, wherein the step 3 comprises the steps of: 3-1, data preparation, namely ensuring the accuracy and the integrity of data and preprocessing missing or abnormal data; 3-2, analyzing the speed change along with the depth, namely identifying a horizon or interval of which the speed is obviously changed along with the depth; 3-3, identifying main speed change horizons or trends, namely analyzing the geological significance of the speed change horizons or trends by combining geological background information; 3-4, checking abnormal values, namely checking whether abnormal values exist in the speed data, and marking and recording the abnormal values; 3-5, calculating speed parameters, namely calculating average speed, layer speed and root mean square speed; 3-6, abnormal value processing of the speed parameter, namely checking the obtained abnormal value of the speed parameter, and removing and/or recalculating the abnormal value; 3-7, selecting the VSP resolving speed, namely selecting the average speed as the VSP resolving speed in the next step after the abnormal value processing.
  6. 6. The method of claim 5, wherein in 3-5, the average speed is calculated as: Wherein V a is the average velocity, representing the average propagation velocity of the acoustic wave in the particular wellbore section; hd i is the depth of the observation point, calculated from the ground surface; t i /2 vertical single pass time, from the surface.
  7. 7. The method of claim 5, wherein in 3-5, the layer speed calculation formula: Wherein, the V ni is the layer speed; hd i is the depth of the observation point, calculated from the ground surface; t i /2 vertical single pass time, from the surface.
  8. 8. The method of claim 5, wherein in 3-5, the root mean square velocity calculation formula: Wherein, the Is root mean square velocity; t i is the time value of the ith measurement point; V i is the speed value of the i-th measurement point; n is the total number of measurement points.
  9. 9. The method of claim 1, wherein in step 4, the automated algorithm comprises at least one of cluster analysis, dynamic programming, and sliding window.
  10. 10. The method according to claim 1, wherein the step 4 comprises the specific steps of: 4-1, data preparation: importing a database, and loading logging sound wave speed data and corresponding depth or time data; 4-2, threshold setting: setting an initial threshold value for identifying a significant change point in the sonic velocity data; 4-3, automatic segmentation algorithm: Defining a function find breakpoints that accepts as inputs sonic velocity data, a threshold value, and a minimum length; inside the function, calculating the difference between adjacent speed values; Indexes with absolute values of difference values larger than a threshold value correspond to possible segmentation points; Traversing all possible segmentation points, and adding the current segmentation point into a segmentation point list if the current segmentation point is a previous segmentation point or if the number of data points between the two points is greater than the minimum length; ensuring that the last segment point is set correctly; if the distance between the last segmentation point and the end of the data is greater than the minimum length minus one, the end of the data is taken as a segmentation point; 4-4, segment point filtration: Initializing a new list to store the filtered segmentation points, the first point always remaining; Traversing the segmented point list, checking whether the difference value between the current point and the previous point is larger than or equal to a preset value, if the current point depth is smaller than a specified value and the current point is satisfied, adding the current point into the filtered segmented point list; 4-5, acquiring the actual segmentation point positions: Acquiring a corresponding actual segmentation point position from the x_data by using the filtered segmentation point index; 4-6, output: And outputting the filtered segmentation point positions.
  11. 11. The method according to claim 1, wherein the step 5 comprises the specific steps of: 5-1, data segmentation: based on the segmentation points obtained in the step 4, dividing x_data and y_data into a plurality of subsequences by using an np-split function; 5-2, defining a fitting function: Selecting a proper fitting function to describe the relationship between the sound wave speed and the depth or the time; 5-3, segment fitting: fitting each segment by using a cut_fit function to obtain fitting parameters; 5-4, output and visualization: After each segment fitting is completed, outputting fitting parameters; the original data and the fitting result are intuitively displayed through a visual means.
  12. 12. The method according to claim 1, wherein the step 6 comprises the specific steps of: Initializing an array corrected_y with the same size as the original y data to store the corrected sound wave velocity value; 6-2, traversing the segments, namely determining an x value range corresponding to each segment and finding a corresponding y value for each segment; 6-3, applying fitting parameters, namely calculating a corrected y value through a fitting function by using the fitting parameters of the current segment; 6-4, storing the correction value, namely storing the calculated corrected y value in a corresponding position in the corrected y array; 6-5, processing boundary conditions, namely ensuring proper processing at the segment boundary and the start/end points of the data so as to avoid data loss or repetition; And 6-6, verifying the correction effect, namely comparing and analyzing the corrected sound wave speed data with the VSP speed data to evaluate the accuracy and the effectiveness of the correction method.
  13. 13. The method of claim 1, wherein the quality check of step 7 comprises at least one of a data integrity check, a fit quality assessment, a parameter rationality check, and a boundary condition processing.
  14. 14. The method according to claim 1, wherein the step 7 comprises the following specific steps: 7-1, data integrity check: Checking the integrity of the original logging sound wave speed data and depth or time data, ensuring that no missing value or abnormal value exists; 7-2, fitting quality evaluation: for each segment, evaluating the quality of the fitting result, and evaluating the fitting quality by checking the fitting residual error; 7-3, checking parameter rationality: Checking rationality of fitting parameters; if unreasonable parameter values are found, further inspection of the data and fitting process is required to determine the cause of the problem; 7-4, boundary condition processing: Ensuring proper processing at segment boundaries and start/end points of data, avoiding data loss or duplication, and ensuring continuity of correction results.
  15. 15. The method of claim 1, wherein the content of the output of step 8 comprises corrected data, fitting parameters, quality control reports, and visualization data.
  16. 16. The method according to claim 1, wherein the step 8 comprises the specific steps of: 8-1, corrected data output: Outputting corrected logging sound wave speed data in a proper format; The output file should include an index or depth/time value of the original data to correspond to and compare with the original data; 8-2, fitting parameter output: outputting fitting parameters of each segment for subsequent analysis and verification; 8-3, quality control report: Generating a quality control report, and summarizing the results of data integrity check, fitting quality evaluation, parameter rationality check and boundary condition processing; 8-4, visual output: The data before and after correction and the fitting curve can be displayed by visual means such as charts, images and the like, so that a user can more intuitively know the correction effect.
  17. 17. The method of claim 16, wherein the visual output comprises at least one of a raw data scatter plot, a fitted plot, and a residual plot.
  18. 18. Use of the method of any one of claims 1-17 in oil and gas exploration and development, geophysical data processing and analysis and mineral resource exploration in the northbound region of the tarius basin.

Description

Method and application for correcting logging sound wave speed to VSP speed trend based on automatic segmentation Technical Field The invention relates to the technical field of oil and gas exploration, in particular to a method for correcting a logging sound wave speed to a VSP speed trend based on automatic segmentation and application thereof. Background The Tarim basin is located in Xinjiang region in northwest of China, is the largest inland basin in China, and is one of the regions with the most abundant oil and gas resources in the world. The oil and gas resources in the basin are rich, but the exploration and development difficulty is extremely high, mainly because the geological conditions in the region are complex, and the oil and gas reservoirs have the characteristics of ultra-deep, ultra-high temperature, ultra-high pressure and the like. Logging is a downhole oil and gas exploration method used for finding oil and gas reservoirs, evaluating oil and gas reserves and their production, and it also has wide application in oil and gas field development and drilling engineering. The logging technology is an indispensable means for accurately finding out the hydrocarbon reservoir and finely describing the hydrocarbon reservoir, and is an important scientific basis for calculation of hydrocarbon reservoir parameters, evaluation of productivity and formulation and adjustment of development schemes. Logging is a vast array of methods, electrical, acoustic, and radioactive are three basic methods. Sonic velocity logging is the most commonly used logging method (e.g., chinese patent CN102866435A, chinese patent CN1621860a, etc.) for calculating and determining formation porosity, lithology and pore fluid properties by measuring the time difference Δt of the formation sliding wave (reciprocal of formation longitudinal wave velocity) according to the propagation velocity of the sonic wave in the formation. The vertical seismic profile technology (VSP) realizes underground through the ground excitation and well receiving modes, and is widely applied to finely describing well Zhou Fuza structures, reservoirs, fluid space spreading and the like, is an indispensable bridge for connecting ground earthquakes, well logging and geological information, and improves reservoir target imaging precision due to the fact that the VSP technology has more direct reservoir description (absorption attenuation, speed, anisotropism and the like) capability, better time-depth calibration capability and resolution capability higher than ground earthquakes. However, because of economic benefit, part of the well is only subjected to acoustic logging, but not VSP logging. The VSP observation mode enables the seismic waves to pass through the low-speed zone of the earth surface only once, so that the attenuation of the seismic wave energy, particularly the loss of high-frequency components, is reduced. The geophone is placed along the well bore, and receives seismic waves in the stratum, so that the geophone can be positioned at the target depth underground more accurately, the accuracy of speed analysis is improved, the geophone of the VSP is closer to the target layer, therefore, the received seismic signals are less interfered, the amplitude information distortion is smaller, and the data are more real and reliable. VSP and acoustic logging trends have extremely high trend similarity, well data, particularly more VSP speeds, are needed in well control anisotropic seismic data processing, and control points in well control anisotropic seismic data processing can be better realized by correcting the traditional logging acoustic speeds to the VSP speed trends. In the field of oil exploration and development, correction of logging acoustic velocity to VSP (vertical seismic profile) velocity trend is a key technical link. The traditional correction method mainly depends on manual segmentation and manual adjustment, and is low in efficiency, and is easily affected by human factors, so that the accuracy and reliability of a correction result are difficult to guarantee. In recent years, with the continuous development of computer technology, some automatic correction methods such as neural networks and curve fitting have been proposed and applied gradually. However, these methods still have certain limitations in dealing with complex geological conditions. Therefore, the development of a novel logging sound wave velocity correction technology has important significance for improving the efficiency and accuracy of the oil exploration and development of the Tarim basin. Disclosure of Invention Aiming at the problems, the invention provides a method for correcting the logging acoustic wave velocity to the VSP velocity trend based on automatic segmentation, and by introducing an advanced automatic segmentation algorithm, the automatic analysis and processing of logging acoustic wave data can be realized, so that the characteristics of differe