CN111325834A - Modeling method and system based on digital image processing - Google Patents
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- 238000006243 chemical reaction Methods 0.000 claims description 7
- 238000009499 grossing Methods 0.000 claims description 7
- 238000003708 edge detection Methods 0.000 claims description 4
- 230000000877 morphologic effect Effects 0.000 claims description 3
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- 230000000007 visual effect Effects 0.000 abstract description 5
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/32—Transforming one recording into another or one representation into another
- G01V1/325—Transforming one representation into another
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/34—Displaying seismic recordings or visualisation of seismic data or attributes
- G01V1/345—Visualisation of seismic data or attributes, e.g. in 3D cubes
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/40—Filling a planar surface by adding surface attributes, e.g. colour or texture
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/04—Context-preserving transformations, e.g. by using an importance map
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/40—Transforming data representation
- G01V2210/48—Other transforms
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/66—Subsurface modeling
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/70—Other details related to processing
- G01V2210/74—Visualisation of seismic data
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Abstract
The invention relates to a modeling method and a system based on image processing, wherein the method comprises the steps of S1, converting data to be processed in a time-space domain into a digital image domain through a numerical value-color mapping pair; s2, processing the image converted into the digital image domain by using an image morphology processing technology; and S3, converting the processed image into a time-space domain through numerical value-color mapping, and completing modeling. The modeling method provided by the invention is simple to operate, is visual and clear, has high precision, and can efficiently and simply complete complex modeling work.
Description
Technical Field
The invention relates to a modeling method and a modeling system based on digital image processing, and relates to the technical field of seismic exploration.
Background
Along with the transformation of seismic exploration targets from conventional-structure oil and gas reservoirs to unconventional lithologic oil and gas reservoirs, the oil and gas-containing prediction and reservoir exploitation scheme design simultaneously needs geophysical specialties to provide quantitative prediction parameters with higher precision: porosity, saturation, permeability, brittleness index, etc., and therefore, put higher demands on modeling techniques. Three links of seismic data acquisition, processing and inversion are closely related to modeling. The method aims to acquire the information of the underground medium to the maximum extent, and the design of the acquisition and observation system is an important task of seismic data acquisition, so that the seismic data with the maximum information amount is acquired by adopting an economical and efficient observation system. The main dependence means of the design of the acquisition observation system is forward modeling which depends on a model, the higher the accuracy of the prediction model is, the closer the prediction data is to the actual situation, the higher the rationality of the designed observation system is, and the acquisition quality and the acquisition cost reach a reasonable balance. In the process of processing the seismic data, the velocity is a key parameter, a high-precision velocity model is obtained, the imaging quality of the seismic data can be greatly improved, and the method is also a key for realizing the fidelity and the amplitude of the seismic data. The seismic data inversion process is an inverse process from data to medium parameters, is an underdetermined problem in principle, and a low-frequency model is an indispensable factor in order to reduce the multi-solution and obtain a solution closer to the real underground situation. How to build an accurate low-frequency model is one of the core problems of seismic data inversion. Therefore, in order to meet the requirements of the transformation of seismic exploration targets and the quantitative prediction of oil and gas reservoirs with high precision, the search for a modeling method with high precision and convenient operation is still one of important research contents in the field of seismic exploration.
The existing modeling work is mainly divided into two stages, firstly, the acquisition of modeling elements mainly refers to horizons, velocity volumes, fault interpretation results and other direct or indirect results obtained from seismic data. Secondly, the modeling elements are combined together according to a certain rule in a time-space domain by utilizing a computer technology. The combination of modeling elements mainly depends on computer technology, and the result of striving for modeling is firstly visual effect, so that modeling personnel can obtain visual images through vision, and further judge modeling quality. The most challenging task in the conventional modeling process is human-computer interaction, and when an operator attempts to modify a certain element or a local feature of a certain element in a model, the modeling task is often extremely difficult. The reason for this is that interconversion between data and visual images requires too many rules and expertise in the computer field, making manipulation by geophysical personnel difficult. Therefore, modeling work in the field of oil and gas exploration is usually focused on simple combination of few modeling elements, and the requirements of production practice are difficult to meet.
In recent years, with the development of computer vision technology, in particular the development of deep learning technology, the processing of oil and gas exploration data based on images becomes possible. Based on conventional wisdom, seismic data is often transformed, for example by fourier transformation, from the time-space domain to the frequency domain, then processed and then transformed by inverse fourier transformation to the time-space domain. The conventional modeling techniques have the following disadvantages: the operation is complex, and the computer mapping technology needs to be mastered; it is difficult to control outliers and boundaries in the modeling elements; interoperation requires highly configured computer hardware (especially video memory).
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a modeling method and system based on digital image processing, which transform modeling elements into an image domain, process the modeling elements by using an image processing technique, and then inversely transform the processed image into a data domain, so that the method and system are high in precision and can efficiently and simply complete complex modeling work.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the present embodiment provides a modeling method based on digital image processing, including:
s1, converting the data to be processed in the time-space domain into a digital image domain through a numerical value-color mapping pair;
s2, processing the image converted into the digital image domain by using an image morphology processing technology;
and S3, converting the processed image into a time-space domain through numerical value-color mapping to finish modeling.
Further, the method also comprises the step of preprocessing the data to be processed in the time-space domain:
performing abnormal value processing on the obtained data S to enable the data value after the abnormal value processing to be in a set range, specifically:
wherein Y is new data obtained after processing, SupAnd SdownAn upper limit value and a lower limit value are set for the data S, respectively.
Further, a value-color mapping pair includes two types of value-color mapping pairs: one is to construct gray scale value-color mapping pairs, and the other is to construct color value-color mapping pairs.
Further, the processing of the image converted into the digital image domain by the above S2 includes an opening operation, a closing operation, and/or an edge detection smoothing process using an image morphology processing technique.
In a second aspect, the present embodiment further provides a modeling system based on digital image processing, the system including:
the domain conversion module is used for converting the data to be processed in the time-space domain into a digital image domain through a numerical value-color mapping pair;
the image processing module is used for processing the image converted into the digital image domain by utilizing an image morphological processing technology;
and the inverse conversion module is used for inversely converting the processed image into a time-space domain through a numerical value-color mapping.
Further, the abnormal value processing module is used for processing the abnormal value of the obtained data, so that the data value after the abnormal value processing is in a set range.
Due to the adoption of the technical scheme, the invention has the following advantages:
1. the invention provides a method for completing modeling work by utilizing image processing, which is simple to operate, does not need complex computer technology as a support, is more convenient when processing abnormal points and boundary problems in a model, does not need higher configured computer resources, is simple to operate, is visual and clear, has high precision, and can efficiently and simply complete complex modeling work.
2. Because the conventional modeling means is complex in operation, is difficult to process abnormal points and boundaries in modeling elements and has high requirements on computer hardware, the invention provides a method for solving the modeling problem in the digital image field based on the fact that the computer vision research field and the deep learning technology are rapidly developed in the image field, the modeling elements are converted into the digital image field, the problems of local abnormal points, boundary smoothness and the like in the modeling process are solved by using the common image processing technology, and then the modeling elements are converted into the data field;
in conclusion, the invention can be widely applied to seismic exploration.
Detailed Description
Exemplary embodiments of the present invention are described in more detail below, however, it should be understood that the present invention may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
It is to be understood that the terminology used herein is for the purpose of describing particular example embodiments only, and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" may be intended to include the plural forms as well, unless the context clearly indicates otherwise. The terms "comprises," "comprising," and "having" are inclusive and therefore specify the presence of stated features, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and/or groups thereof. The method steps, processes, and operations described herein are not to be construed as necessarily requiring their performance in the particular order described or illustrated, unless specifically identified as an order of performance. It should also be understood that additional or alternative steps may be used.
Example 1
The embodiment provides a modeling method based on digital image processing, which comprises the following steps:
s1, obtaining relevant data of earthquake, and removing abnormal value from earthquake data
In this embodiment, the seismic data or the related attribute data is denoted as S. Preprocessing the acquired seismic data S, for example, so that the data beyond the set range fall into the corresponding data range:
in the formula, SupAnd SdownRespectively is a reasonable upper limit value and a reasonable lower limit value of S, abnormal value removing processing is carried out on the seismic data through the formula, and new data Y is obtained after processing.
S2, constructing a data-to-image conversion value-color mapping pair:
the present embodiment can construct two types of numerical values-color mapping pairs according to actual needs: one is to construct gray scale value-color mapping pairs, and the other is to construct color value-color mapping pairs.
Specifically, the colors can be represented by three colors, red, green and blue (RGB), each of which varies from 0 to 255. Gray scale value-color mapping pairs total 255, i.e., three colors red, green, and blue equal, from 000, 111, 222 …. At most, 16777216 (24 times of 2) mapping pairs can exist in the color value-color mapping pairs, the number of the general oil and gas exploration fields does not exceed 1000, and the data body of the time-space domain can be converted into one picture of the digital image field by using the value-color mapping pairs constructed in the above way.
And S3, processing the converted image according to requirements, wherein the processing comprises opening operation, closing operation, edge detection smoothing processing and the like:
the opening operation is a process that the image is sequentially subjected to corrosion and expansion treatment, and after the image is corroded, abnormal points are removed, but the image is compressed. And then, the corroded image is subjected to expansion processing, so that abnormal points can be removed, and the original image is kept.
The closed operation is a process of sequentially performing expansion and corrosion treatment on the image. The image expands first and then erodes, which helps to remove outliers within a connected region, or outliers on the border of the region.
The edge smoothing processing may be performed by alternately performing an open operation and a close operation.
The above operation is essentially traversing the image with a convolution kernel of n × n, the size of n depending on the size of the outliers and the degree of edge smoothing.
S4, inversely transforming the processed image into a spatio-temporal data domain through a value-color mapping pair, that is: the processed picture is converted to the original data domain using the constructed value-color mapping pairs.
Example 2
The present embodiment provides a modeling system based on digital image processing, the system including:
and the abnormal value processing module is used for processing the abnormal value of the obtained data, so that the data value after the abnormal value processing is in a set range.
The domain conversion module is used for converting the data to be processed in the time-space domain into a digital image domain through a numerical value-color mapping pair;
the image processing module is used for processing the image converted into the digital image domain by utilizing an image morphological processing technology;
and the inverse conversion module is used for inversely converting the processed image into a time-space domain through a numerical value-color mapping.
Example 3
The embodiment provides a modeling process for carving igneous rocks on a three-dimensional seismic data body based on digital image processing, which comprises the following steps:
s1: removing abnormal values from the seismic data to enable the processed seismic data to be in a set range;
s2: defining numerical value-color mapping pairs, wherein the more the numerical value-color mapping pairs are, the higher the accuracy of converting the seismic data into the image is;
s3: using the numerical-color mapping pairs in S2, the seismic data may be converted into an image along the inline or crossline direction;
s4: editing the position of the igneous rock by using an image editing tool, such as a painting brush, an eraser and a color filling function in a drawing program carried by a windows system, editing the igneous rock into a single color, such as 244126120 for three colors of RGB, wherein the color is not contained in the value-color mapping pair defined in the step S2, and a value-color mapping pair is independently defined for the color and is supplemented into the value-color mapping pair defined in the step S2 to form a new value-color mapping pair;
s5: processing the igneous rock boundary in the S4 by using an image boundary processing tool, and mainly performing opening operation, closing operation and edge detection smoothing processing on the image, so that the igneous rock boundary is smoother and accords with geological understanding;
s6: and (5) carrying out inverse transformation on the image processed in the S5 by using the numerical value-color mapping in the S4 to obtain processed model data, thereby completing the engraving of the igneous rock.
Example 4
The embodiment provides a process for modeling a three-dimensional velocity volume based on a digital image processing method, wherein the velocity volume is an intermediate result of seismic data processing, and the modeling method comprises the following steps:
s1: removing abnormal values from the seismic data to enable the processed velocity value to be in a reasonable range;
s2: defining a speed value-color mapping pair, wherein the more the speed value-color mapping pair is, the higher the precision of converting a speed body into an image is;
s3: converting the velocity volume along the inline or crossline direction into an image (the Z direction is typically the depth or time direction) using the velocity value-color map pair in S2;
s4: eliminating small anomalies in the velocity volume by image opening operation, separating two velocity anomaly volumes at a fine point, and smoothing the boundary of a larger velocity volume without changing the area of the velocity anomaly volumes;
s5: filling a tiny hollow space in the velocity body by utilizing image closed operation, connecting the boundary of the adjacent velocity abnormal body and the smooth velocity abnormal body without changing the area of the boundary;
s6: processing the velocity volume boundary generated at S5 with an image boundary processing tool;
s7: the processed image in S6 is inversely transformed using the velocity value-color mapping pair in S2, and a processed velocity model is generated.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (6)
1. A modeling method based on digital image processing is characterized by comprising the following steps:
s1, converting the data to be processed in the time-space domain into a digital image domain through a numerical value-color mapping pair;
s2, processing the image converted into the digital image domain by using an image morphology processing technology;
and S3, converting the processed image into a time-space domain through numerical value-color mapping to finish modeling.
2. The modeling method based on digital image processing according to claim 1, further comprising the step of preprocessing the to-be-processed data of the spatio-temporal domain:
performing abnormal value processing on the obtained data S to enable the data value after the abnormal value processing to be in a set range, specifically:
wherein Y is new data obtained after processing, SupAnd SdownAn upper limit value and a lower limit value are set for the data S, respectively.
3. The digital image processing-based modeling method of claim 1, wherein the numerical-color mapping pairs comprise two types of numerical-color mapping pairs: one is to construct gray scale value-color mapping pairs, and the other is to construct color value-color mapping pairs.
4. The modeling method based on digital image processing according to any of claims 1 to 3, wherein the processing of the image converted into the digital image domain by S2 includes an opening operation, a closing operation and/or an edge detection smoothing process using an image morphology processing technique.
5. A modeling system based on digital image processing, the system comprising:
the domain conversion module is used for converting the data to be processed in the time-space domain into a digital image domain through a numerical value-color mapping pair;
the image processing module is used for processing the image converted into the digital image domain by utilizing an image morphological processing technology;
and the inverse conversion module is used for inversely converting the processed image into a time-space domain through a numerical value-color mapping.
6. The modeling system for digital image processing according to claim 5, further comprising an abnormal value processing module for performing abnormal value processing on the obtained data so that a data value after the abnormal value processing is within a set range.
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