CN117250658B - Method for creating seismic dataset of investigation region - Google Patents
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- CN117250658B CN117250658B CN202311540263.7A CN202311540263A CN117250658B CN 117250658 B CN117250658 B CN 117250658B CN 202311540263 A CN202311540263 A CN 202311540263A CN 117250658 B CN117250658 B CN 117250658B
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- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000011835 investigation Methods 0.000 title claims description 19
- 238000011160 research Methods 0.000 claims abstract description 27
- 239000011435 rock Substances 0.000 claims abstract description 15
- 238000001308 synthesis method Methods 0.000 claims abstract description 7
- 238000006243 chemical reaction Methods 0.000 claims abstract description 6
- 230000015572 biosynthetic process Effects 0.000 claims description 31
- 238000005553 drilling Methods 0.000 claims description 17
- 239000004576 sand Substances 0.000 claims description 13
- 230000002093 peripheral effect Effects 0.000 claims description 3
- 238000012549 training Methods 0.000 abstract description 6
- 238000001514 detection method Methods 0.000 abstract description 2
- 238000005755 formation reaction Methods 0.000 description 26
- 239000000523 sample Substances 0.000 description 10
- 229910052770 Uranium Inorganic materials 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- JFALSRSLKYAFGM-UHFFFAOYSA-N uranium(0) Chemical compound [U] JFALSRSLKYAFGM-UHFFFAOYSA-N 0.000 description 5
- 238000005070 sampling Methods 0.000 description 4
- 238000013473 artificial intelligence Methods 0.000 description 3
- 230000008901 benefit Effects 0.000 description 3
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- 238000005259 measurement Methods 0.000 description 3
- 235000005881 Calendula officinalis Nutrition 0.000 description 2
- 241000736851 Tagetes Species 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000013075 data extraction Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 238000001739 density measurement Methods 0.000 description 1
- 238000001035 drying Methods 0.000 description 1
- 239000002360 explosive Substances 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000013517 stratification Methods 0.000 description 1
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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
- G01V1/282—Application of seismic models, synthetic seismograms
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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
- G01V1/003—Seismic data acquisition in general, e.g. survey design
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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
- G01V1/30—Analysis
- G01V1/303—Analysis for determining velocity profiles or travel times
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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
- G01V1/30—Analysis
- G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
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Abstract
The embodiment of the invention relates to seismic or acoustic exploration or detection, and particularly discloses a method for establishing a seismic data set of a research area, which mainly comprises the following steps: measuring drill cores with different depths at preset intervals to obtain longitudinal wave speed, transverse wave speed and density of the cores; establishing a rock physical model according to lithology information, longitudinal wave speed, transverse wave speed and density of the rock core; changing parameters of the petrophysical model according to preset conditions to obtain a new petrophysical model; determining a plurality of simulated seismic data according to the plurality of petrophysical models and the simulated seismic data synthesis method; performing time-depth conversion on lithology information, and converting from a depth domain to a time domain; according to the time information, lithology information is given to the simulated seismic data, and a simulated seismic data set with lithology information is obtained. The seismic data obtained by the method provided by the invention can be used for training the lithology prediction model so as to improve the prediction accuracy of the lithology prediction model.
Description
Technical Field
Embodiments of the present invention relate to seismic or acoustic exploration or detection, and in particular to methods of creating a seismic dataset of a region of interest.
Background
The sandstone type uranium deposit exploration practice shows that identifying lithology information of deep strata of sandstone type uranium deposit can effectively guide exploration of uranium deposit of deep strata.
The research finds that the lithology information of the deep stratum has certain relativity with the seismic data, and the lithology information of the stratum with unknown lithology information can be predicted by establishing a prediction model of the seismic data and the lithology information. However, since there is less measured seismic data, the prediction model cannot be trained sufficiently, so that the prediction result obtained by performing prediction by the above prediction model has a large deviation from the actual situation.
Disclosure of Invention
To address at least one aspect of the above problems, the present invention provides a method of creating a seismic dataset of a region of interest, comprising the steps of:
drilling, logging and logging are carried out on a research area, and lithology information of the research area is obtained; acquiring drill cores of different stratum depths of a preset depth interval of a research area, and measuring the cores to obtain longitudinal wave speed, transverse wave speed and density of the cores; according to lithology information, longitudinal wave speed, transverse wave speed and density of the rock core, establishing a petrophysical model of the research area in a stratum depth range; changing parameters of the petrophysical model according to preset conditions to obtain a plurality of new petrophysical models; determining a plurality of simulated seismic data by using a simulated seismic data synthesis method according to the plurality of petrophysical models; performing time-depth conversion on lithology information, and converting the lithology information from depth domain data into time domain data; according to the time information, lithology information of a time domain is endowed to a plurality of simulated seismic data, and the simulated seismic data with lithology information are obtained, wherein the set of the data is a seismic data set of a research area.
According to the method provided by the invention, a sufficient amount of seismic data can be obtained, and the seismic data is used for carrying out artificial intelligence training on the established lithology prediction model, so that the prediction accuracy of the lithology prediction model is improved.
Drawings
Other objects and advantages of the present invention will become apparent from the following description of embodiments of the present invention, which is to be read in connection with the accompanying drawings, and may assist in a comprehensive understanding of the present invention.
FIG. 1 is a flow chart of a method of creating a seismic dataset for a region of interest provided by an embodiment of the invention.
FIG. 2 is a flow chart of measuring longitudinal wave velocity, transverse wave velocity and density of a core sample according to an embodiment of the present invention.
FIG. 3 is a petrophysical model schematic of an example well of an embodiment of the present invention.
FIG. 4 is a seismic data extraction schematic of an embodiment of the invention.
FIG. 5 is a schematic diagram of simulated versus measured seismic data in accordance with an embodiment of the invention.
Detailed Description
For the purposes, technical solutions and advantages of the present application, the technical solutions of the present application will be clearly and completely described below with reference to the drawings of the embodiments of the present application. It will be apparent that the described embodiments are one embodiment of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without the benefit of the present disclosure, are intended to be within the scope of the present application based on the described embodiments.
It is to be noted that unless otherwise defined, technical or scientific terms used herein should be taken in a general sense as understood by one of ordinary skill in the art to which this application belongs. If, throughout, reference is made to "first," "second," etc., the description of "first," "second," etc., is used merely for distinguishing between similar objects and not for understanding as indicating or implying a relative importance, order, or implicitly indicating the number of technical features indicated, it being understood that the data of "first," "second," etc., may be interchanged where appropriate. If "and/or" is present throughout, it is meant to include three side-by-side schemes, for example, "A and/or B" including the A scheme, or the B scheme, or the scheme where A and B are satisfied simultaneously. Furthermore, for ease of description, spatially relative terms, such as "above," "below," "top," "bottom," and the like, may be used herein merely to describe the spatial positional relationship of one device or feature to another device or feature as illustrated in the figures, and should be understood to encompass different orientations in use or operation in addition to the orientation depicted in the figures.
The inventor of the application finds that lithology can be identified by using a prediction model in practical research, and in order to improve the accuracy of prediction of the prediction model, the prediction model needs to be trained, but actual measurement seismic data aiming at a research area is less, so that the data volume of a seismic data set for training cannot meet the training requirement. Therefore, the embodiment of the invention provides a method for establishing a seismic data set of a research area, which can obtain enough seismic data, wherein the seismic data are used for carrying out artificial intelligence training on an established lithology prediction model, so that the prediction accuracy of the lithology prediction model is improved.
FIG. 1 shows a flow chart of a method of creating a seismic dataset of a region of interest provided in accordance with an embodiment of the present invention, the method of creating a seismic dataset of a region of interest provided in accordance with the present invention comprising the following steps.
In step S1, drilling, logging and logging are carried out on the research area, and lithology information of the research area is obtained.
In step S2, drill cores of different stratum depths of a preset depth interval of a research area are obtained, and the drill cores are measured to obtain the longitudinal wave speed, the transverse wave speed and the density of the drill cores.
In the step S3, a petrophysical model of the research area in the stratum depth range is established according to lithology information and the longitudinal wave speed, the transverse wave speed and the density of the rock core.
In step S4, parameters of the petrophysical model are changed according to predetermined conditions to obtain a plurality of new petrophysical models.
In step S5, a plurality of simulated seismic data are determined from the plurality of petrophysical models using a simulated seismic data synthesis method.
In step S6, the lithology information is subjected to time-depth conversion, and lithology information simulation seismic data is converted from depth domain data to time domain data.
In step S7, according to the time information, lithology information in the time domain is given to a plurality of simulated seismic data, so as to obtain simulated seismic data with lithology information, and the set of the data is a seismic data set of the research area. The method can obtain enough seismic data, and the seismic data are used for carrying out artificial intelligence training on the established model for carrying out lithology prediction, so that the prediction accuracy of the lithology prediction model is improved.
In step S1, drilling, logging and logging are performed on the investigation region to obtain lithology information of the investigation region. In some embodiments of the present application, drilling is performed within a research area, after drilling is completed, logging may be performed using a logging tool, formation parameters such as borehole diameter, natural potential, resistivity, natural gamma, sonic time difference, density, etc. are acquired in the well, while data is acquired using the logging tool, a parameter probe of the logging tool may be used to slide downhole, one data being determined at each predetermined interval, which may be 0.05m, for example. Further, drilling is cored, the lithology of the obtained sample is observed, geological stratification is determined in combination with regional formation characteristics and lithology histograms are drawn, i.e. logging is performed.
Lithology information of the study area refers to mudstone, mud-containing fine sand, muddy silt, fine sand, silty silt rock, medium sand, calcareous gravel, muddy silt, medium sand (containing ore), muddy fine sand (containing ore), and the like. In some embodiments, different depth intervals of the well of the investigation region are sampled, the formation, sampling depth and lithology information of which are shown in Table 1 below.
Table 1 sample information for a zone of interest of an example well
In step S2, cores of wells drilled at different formation depths of a predetermined depth interval of the investigation region are obtained, and the cores are measured to obtain a longitudinal wave velocity, a transverse wave velocity and a density of the cores.
In some embodiments of the present application, drilling is performed at a target layer of a study area to obtain core samples of different formation depths, the samples should meet a diameter > 3cm and a length > 5cm, the depth range of the samples covers the entire target layer, and the sampling is performed at predetermined depth intervals. The predetermined depth interval may be increased/decreased during sampling according to the change in lithology. For example, in a depth range where lithology changes are relatively stable, 50m samples may be taken at depth intervals; and in the depth range of the stratum with more frequent lithology change, the sampling can be performed at the depth interval of 10 m.
In some embodiments of the present application, after obtaining core samples for drilling at different formation depths, the longitudinal and transverse wave velocities of the core samples may be measured using an ultrasonic pulse transmission method, and the density of the core samples may be measured using a volumetric method. In the case of measuring a core sample, the steps may be as shown in fig. 2, and mainly include: in step S21, drilling and coring are performed on the target layer, so as to obtain a core sample; in step S22, cleaning and drying the core sample taken out; in step S23, measuring the density of the core sample by a volume method; in step S24, measuring the longitudinal wave velocity and the transverse wave velocity of the core sample at high temperature, high pressure, normal temperature and normal pressure by using an ultrasonic pulse transmission method; in step S25, the measurement result is checked. In these examples, the longitudinal wave velocity, transverse wave velocity and density measurements of a portion of the sample are shown in table 2 below.
TABLE 2 measurement results of longitudinal wave speed, transverse wave speed and Density of partial samples
In step S3, a petrophysical model of the investigation region within the formation depth range is established according to the lithology information and the longitudinal wave velocity, the transverse wave velocity and the density of the core.
In some embodiments of the present application, lithology is that of a majority of the formations within a predetermined depth range of the sampled formation of the core in a petrophysical model step of establishing a region of interest within the depth range of the formation based on lithology information and longitudinal wave velocity, transverse wave velocity, and density of the core. Such as the simultaneous presence of mudstone, fine sand, and middle sand within the 475-480m formation thickness cell, where the mudstone thickness is greater, the formation thickness cell lithology is determined to be mudstone.
In some embodiments of the present application, the lithology of the formation may be divided into 5 of mudstone, silt, fine sand, middlings, and gravel. For example, lithology of the uranium deposit of marigold and its corresponding compressional, shear and density are shown in table 3 below.
TABLE 3 lithology of the uranium deposit of marigold and its corresponding longitudinal wave velocity, transverse wave velocity and density
In some embodiments of the present application, in the step of building a petrophysical model of the investigation region within the formation depth range based on lithology information and the longitudinal wave velocity, the transverse wave velocity and the density of the core, the longitudinal wave velocity is determined by an interval consisting of a median value, a maximum value and a minimum value of the longitudinal wave velocity, the transverse wave velocity is determined by an interval consisting of a median value, a maximum value and a minimum value of the transverse wave velocity, and the density is determined by an interval consisting of a median value, a maximum value and a minimum value of the density. For example, in a depth range of the target zone of the example well, where the rock longitudinal wave velocity has an intermediate value of 2819m/s and the maximum, minimum and intermediate values are each 150m/s different, the rock longitudinal wave velocity in that depth range is 2819±150m/s.
In some embodiments of the present application, in the step of building a petrophysical model of the investigation region within the formation depth range according to lithology information and longitudinal wave velocity, transverse wave velocity and density of the core, the petrophysical model is built at predetermined depth intervals, the predetermined depth intervals are 5m, and the predetermined depth intervals are 5m as one formation thickness unit.
In some embodiments of the present application, the petrophysical model may be expressed in tabular form. For example, the target layer petrophysical model of an example well may be as shown in table 4 below.
Table 4 petrophysical model of the destination layer of example well
In other embodiments of the present application, the petrophysical model may be expressed in the form of a data map. For example, a schematic diagram of a petrophysical model of a destination layer of an example well may be shown in FIG. 3. The model clearly and intuitively shows the lithology 31 of each thickness unit of the target layer, the longitudinal wave velocity 32 of each thickness unit of the target layer, the transverse wave velocity 33 of each thickness unit of the target layer and the density 34 of each thickness unit of the target layer in the form of pictures.
In step S4, parameters of the petrophysical model are changed according to predetermined conditions, and a plurality of new petrophysical models are obtained.
In some embodiments of the present application, the petrophysical model comprises lithology information of a region of the core of a predetermined formation depth, longitudinal wave velocity, transverse wave velocity, and density of the core, the lithology information corresponding to the longitudinal wave velocity, transverse wave velocity, and density.
In some embodiments of the present application, lithology information may be changed to obtain a new petrophysical model. For example, a certain formation lithology of the physical model of raw rock is sandstone, which can be transformed into mudstone, and the corresponding longitudinal wave velocity, transverse wave velocity and density of sandstone are transformed into those of mudstone.
In other embodiments of the present application, any of the compressional wave velocity, shear wave velocity, and density may be varied to obtain a new petrophysical model. For example, a certain stratum of the original rock physical model has a longitudinal wave speed of 2850m/s, a transverse wave speed of 1650m/s and a density of 2.1g/cm 3, and the longitudinal wave speed is finely tuned to 2900m/s within the parameter range of the rock physical model under the condition of not changing lithology, and other parameters are kept unchanged, so that a new rock physical model is obtained.
In other embodiments of the present application, the formation depth of the acquired core may be changed to obtain a new petrophysical model. For example, a certain stratum thickness of the original rock physical model is 30m, and the stratum thickness can be converted into 28m or 32m to obtain a new rock physical model.
In some embodiments of the present application, changing parameters of the petrophysical model according to predetermined conditions means that parameter adjustments of the petrophysical model are to follow certain rules, to adjust within a certain range, and not to be done at will. For example, when changing the formation thickness of an example well, the values of the formation thickness after the change should be within the range of formation thicknesses shown by the regional geological data, and the values of the longitudinal wave velocity, the transverse wave velocity, and the density of the changed formation should be within the range of longitudinal wave velocity, transverse wave velocity, and the density of the petrophysical model established in table 4.
In step S5, a plurality of simulated seismic data are determined from the plurality of petrophysical models using a simulated seismic data synthesis method.
In some embodiments of the present application, a skilled artisan may synthesize simulated seismic data from a petrophysical model of an example well using convolution calculations of reflection coefficients of formations and seismic wavelets. For example, a skilled artisan may utilize commercial software or programming to synthesize simulated seismic data, such as seismic data processing software such as CGG, omega, and the like.
In some embodiments of the present application, seismic data for a well of a study area may be acquired, from which the accuracy of the data of the seismic dataset of the study area is determined. Acquiring seismic data of the well drilling of the investigation region may be accomplished by acquiring seismic field measured data via a seismometer. When the seismograph is used for collecting data, the selected observation system surface element is not more than 10m multiplied by 10m, the coverage times are not less than 48 times, the maximum offset is not less than the survey depth multiplied by 1.5, and the main frequency of the detector is not higher than 10Hz. In some embodiments, the source may be a vibroseis source. Alternatively, in other embodiments, the source may be an explosive source.
In the step of acquiring seismic data of the well bore of the investigation region, the seismic acquisition range should be determined from the range of the pre-survey and the full coverage area range of the acquired seismic data should be greater than the range of the pre-survey. After acquiring the seismic data of the well drilling of the investigation region, the acquired seismic data needs to be processed. The seismic data processing is to perform high-resolution processing on field seismic data by using seismic data processing software so as to obtain seismic pre-stack and post-stack pure wave data volumes. In some embodiments, the seismic data processing may be implemented by commercial software, e.g., the seismic data processing may be implemented by CGG, omega, etc. software. Alternatively, in other embodiments, seismic data processing may be accomplished by self-programming.
In the step of acquiring the seismic data of the well of the investigation region and determining the accuracy of the data of the seismic dataset of the investigation region from the seismic data, further comprising: acquiring peripheral well side channel seismic data of well drilling of a research area; the accuracy of the data of the studied seismic dataset is determined from the seismic data and the well side channel seismic data.
In some embodiments of the present application, acquiring the seismic data of the side channel of the well of the research area refers to extracting the single channel seismic data corresponding to the position and the single channel seismic data of 8 orientations around the well according to the coordinate position of the well, and extracting 9 channels of seismic data in total, where a seismic data extraction schematic diagram is shown in fig. 4. Peripheral well bypass seismic data for the well is obtained by extracting single trace 49 seismic data and well bypass 41-48 seismic data for the well coordinate locations. The distance between the coordinate position of the drilling well and the coordinate position of the extracted well side channel seismic data is 7.5m, and the distance between the two coordinate positions of the extracted well side channel seismic data is 7.5m.
After acquiring the well drilling seismic data and the surrounding well bypass seismic data of the investigation region, determining the accuracy of the data of the studied seismic data set is determined by comparing the simulated seismic data with the obtained well drilling seismic data and surrounding well bypass seismic data of the investigation region.
In some embodiments of the present application, based on the acoustic velocity curve 51 of the example well and the density curve 52 of the example well, simulated seismic data 53 is synthesized by a simulated seismic data synthesis method, and the simulated seismic data is compared with measured seismic data 54 of the well side channel, and the obtained comparison result is schematically shown in fig. 5. As can be seen from FIG. 5, in the objective interval, the correlation degree between the simulated seismic data and the measured seismic data reaches 0.84, which shows that the simulated seismic data synthesized by the simulated seismic data synthesis method is accurate and reliable.
In step S6, the lithology information is subjected to time-depth conversion, and the lithology information is converted from the depth domain data to the time domain data.
In some embodiments of the present application, the time-depth transformation of lithology information may be referenced to acoustic curves in the log data, which may represent formation velocities of the respective formations, from which time-depth transformation relationships may be obtained. Lithology information can be converted from depth domain data to time domain data through a time-depth conversion relationship. The lithology information is converted from the depth domain to the time domain data in order to establish a correspondence with the seismic data as the time domain data.
In step S7, lithology information in a time domain is assigned to a plurality of simulated seismic data according to the time information, and simulated seismic data having lithology information is obtained, and the set of data is a seismic data set of a study area.
In some embodiments of the present application, obtaining simulated seismic data with lithology information includes: firstly, according to the coordinate positions, seismic data ordered according to a time sequence and lithology data ordered according to the time sequence are in one-to-one correspondence, and 1 channel of seismic data corresponds to 1 channel of lithology data; and carrying out one-to-one correspondence on the same channel of seismic data according to a time sequence, thereby obtaining the time domain simulated seismic data with lithology information, wherein the time domain simulated seismic data with lithology information is collected into a seismic data set of a research area.
It should also be noted that, in the embodiments of the present invention, the features of the embodiments of the present invention and the features of the embodiments of the present invention may be combined with each other to obtain new embodiments without conflict.
The present invention is not limited to the above embodiments, but the scope of the invention is defined by the claims.
Claims (9)
1. A method of creating a seismic dataset of a region of interest, comprising the steps of:
drilling, logging and logging are carried out on a research area, and lithology information of the research area is obtained;
acquiring drill cores of the wells with different stratum depths at preset depth intervals of the research area, and measuring the drill cores to obtain longitudinal wave speed, transverse wave speed and density of the drill cores;
establishing a petrophysical model of the research area in a stratum depth range according to the lithology information and the longitudinal wave speed, the transverse wave speed and the density of the rock core;
changing parameters of the petrophysical model according to preset conditions to obtain a plurality of new petrophysical models;
determining a plurality of simulated seismic data by using a simulated seismic data synthesis method according to the plurality of new petrophysical models;
performing time-depth conversion on the lithology information, and converting the lithology information from depth domain data into time domain data;
according to the time information, lithology information of the time domain is endowed to the plurality of simulated seismic data, so that simulated seismic data with lithology information are obtained, and the data set is a seismic data set of a research area;
changing parameters of the petrophysical model to obtain a plurality of new petrophysical models, comprising:
the petrophysical model comprises lithology information of a region of the core, which is used for obtaining a preset stratum depth, and longitudinal wave speed, transverse wave speed and density of the core, wherein the lithology information corresponds to the longitudinal wave speed, the transverse wave speed and the density;
the lithology information of the research area refers to mudstone, mud-containing fine sand, argillaceous silt, fine sand, silty silt rock, medium sand, calcareous gravel, argillaceous silt, medium sand containing ores and argillaceous fine sand containing ores.
2. The method of claim 1, wherein the lithology information is changed to obtain a new petrophysical model.
3. The method of claim 1, wherein any of the compressional wave velocity, shear wave velocity, and density are changed to obtain a new petrophysical model.
4. The method of claim 1, wherein a new petrophysical model is obtained by changing a formation depth at which the core is acquired.
5. The method of claim 1, wherein the predetermined depth interval is 5m.
6. The method of claim 1, wherein in the step of building a petrophysical model of the investigation region over a range of formation depths based on the lithology information and the longitudinal wave velocity, transverse wave velocity, and density of the core, the lithology is that of a majority of the formation within a predetermined depth range of the sampled formation of the core.
7. The method of claim 1, wherein in the step of building a petrophysical model of the investigation region over a formation depth range from the lithology information and the longitudinal wave velocity, the transverse wave velocity and the density of the core, the longitudinal wave velocity is determined from a section consisting of a median value, a maximum value and a minimum value of the longitudinal wave velocity, the transverse wave velocity is determined from a section consisting of a median value, a maximum value and a minimum value of the transverse wave velocity, and the density is determined from a section consisting of a median value, a maximum value and a minimum value of the density.
8. The method of any of claims 1-7, further comprising:
acquiring seismic data of a well of the investigation region;
and determining the accuracy of the data of the seismic data set of the research area according to the seismic data.
9. The method of claim 8, further comprising:
acquiring peripheral well side channel seismic data of the well drilling of the research area;
and determining the accuracy of the data of the studied seismic data set according to the seismic data and the well side channel seismic data.
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