Sandstone type uranium mine CSAMT data processing flow and data interpretation method

Abstract

The application provides a sandstone type uranium mine CSAMT data processing flow and data interpretation method, which collects, counts and analyzes drilling and logging resistivity data, and then establishes an initial geoelectric model; according to the geoelectric model, forward calculation is carried out, then data inversion processing is carried out, finally, the inversion model and the inversion coefficient are determined, then the measured original data is edited, and static displacement correction, transition zone correction and terrain correction are completed, finally, inversion mapping is carried out, according to known geological data, formation, lithology and fault structure interpretation marks are established, and finally, data interpretation and comprehensive analysis are completed according to the interpretation marks. The application establishes a systematic sandstone type uranium mine CSAMT processing flow and data interpretation method, can accurately determine the inversion initial model and the inversion coefficient, realizes fine data processing, and according to known geological data, establishes interpretation marks, finely interprets data, and accurately guides sandstone type uranium mine drilling engineering deployment.

Description

Technical Field

[0001] The present invention relates to a data processing flow and a data interpretation method, in particular to a CSAMT data processing flow and a data interpretation method for sandstone-type uranium deposits. Background Art

[0002] Sandstone-type uranium deposits in Mesozoic and Cenozoic basins are one of the most important uranium deposit types in my country and are currently the primary focus of uranium prospecting. Sandstone-type uranium deposits are mostly concealed ore bodies with few outcrops of the target strata. They exhibit a "mud-sand-mud" reservoir structure, with faults playing a dominant role in controlling the basin's structural pattern, the spatial distribution of the target strata, and the conduction of deep reducing fluids and groundwater drainage. Due to the extensive Quaternary coverage of the surface, geophysical methods are urgently needed to ascertain the deep stratigraphic structure and the development of fault structures to provide a basis for planning drilling projects for sandstone-type uranium exploration.

[0003] Controlled-source audio frequency magnetotelluric (CSAMT) measurements offer high lateral resolution, robust interference immunity, and high efficiency. CSAMT surveys conducted in basins have provided objective insights into the stratigraphic structure, fault structure, target strata, and sandbody development characteristics of sandstone-type uranium deposits, guiding the deployment of drilling projects for sandstone-type uranium deposits. This requires sufficient precision in CSAMT data processing and interpretation.

[0004] Currently, CSAMT data processing and interpretation often lack a systematic process, primarily due to a lack of collection, analysis, and statistics of borehole and logging resistivity data in the survey area. This makes it impossible to accurately determine the initial model and inversion coefficients for inversion processing, resulting in inaccurate buried depths and thicknesses of electrical layers in the inverted resistivity cross-section. Furthermore, the lack of established stratigraphic, lithologic, and fault structure interpretation markers results in large errors in the stratigraphic structure, lithologic, and fault structure of sandstone-type uranium deposits interpreted by CSAMT, which cannot reflect the true geological conditions and ultimately cannot accurately guide drilling project deployment. Summary of the Invention

[0005] The purpose of the present invention is to provide a CSAMT data processing flow and data interpretation method for sandstone-type uranium deposits.

[0006] The present invention is implemented as follows: a CSAMT data processing flow and data interpretation method for sandstone-type uranium deposits, comprising the following steps:

[0007] a. Collect, compile and analyze the borehole and logging resistivity data in the survey area to obtain the borehole geoelectric structure and logging resistivity curve in the survey area;

[0008] b. Determine the measuring point spacing, electric dipole moment, acquisition frequency, acquisition mode, and the number, thickness, and burial depth of electrical layers based on the geoelectric structure and logging resistivity curve, and establish an initial geoelectric model;

[0009] c. Perform forward calculation on the established initial geoelectric model to generate data files that can be inverted;

[0010] d. Using several inversion models provided by the inversion software, perform inversion calculations on the generated invertible data files to obtain several inversion resistivity cross-sections;

[0011] e. Compare the drawn inversion resistivity cross-sections with the established initial geoelectric model, and select the inversion model of the inversion resistivity cross-section that is closest to the initial geoelectric model as the final inversion model;

[0012] f. Selecting a number of inversion coefficients based on the drilling data, substituting the inversion coefficients into the inversion model obtained above for inversion calculation, and comparing the calculation results with the borehole and logging resistivity curves of the survey area to determine the inversion coefficients of the inversion model; the inversion coefficients include the first layer thickness and smoothing coefficient of the model;

[0013] g. Edit the original data of sandstone-type uranium deposits measured by the CSAMT method;

[0014] h. Perform static displacement correction, transition zone correction, and terrain correction on the edited original data in sequence;

[0015] i. Using the final inversion model and inversion coefficients determined in steps e and f, perform final inversion processing on the data obtained in the previous step to generate a final resistivity cross-section diagram;

[0016] j. Select relatively typical areas in the exploration area to establish an inversion resistivity section for sandstone-type uranium deposits, and establish interpretation marks for the strata, lithology, and fault structures in the inversion resistivity section diagram of the typical area based on known geological data;

[0017] k. Based on the interpretation marks established in step j, interpret and comprehensively analyze the inversion resistivity section stratigraphic structure, lithology and fault structure within the entire exploration area obtained in step i.

[0018] In step f, the selected first layer thickness and smoothing coefficient are substituted into the inversion model in step e, and the inversion calculation is performed on the inversion data in step c. Then, the inversion result is compared and analyzed with the borehole and logging resistivity curves of the survey area to determine whether the selected first layer thickness and smoothing coefficient are reasonable. If the selected first layer thickness and smoothing coefficient are reasonable, proceed to step g; if not, reselect and verify.

[0019] The initial geoelectric model described in step b is established by the forward modeling software em2d.exe, and forward modeling calculations are performed by the software to generate a data file that can be inverted.

[0020] The inversion software used in step d is SCS2D inversion software.

[0021] In step h, the edited original data is subjected to static displacement correction using the Astatic.exe software, and terrain correction is performed using the terrain correction software.

[0022] The present invention establishes a systematic CSAMT processing flow and data interpretation method for sandstone-type uranium deposits, which can accurately determine the inversion initial model and inversion coefficients, realize refined data processing, establish interpretation markers based on known geological data, and perform fine interpretation of the data, thereby accurately guiding the deployment of sandstone-type uranium deposit drilling projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flow chart of the present invention.

[0024] Figure 2 It is the drilling data and logging resistivity map collected in the embodiment of the present invention.

[0025] Figure 3 This is the initial geoelectric model diagram in the embodiment of the present invention.

[0026] Figure 4 3 is a comparison diagram of initial model selection in an embodiment of the present invention.

[0027] Figure 5 This is a comparison chart of the thickness selection of the first layer of the inversion coefficient in an embodiment of the present invention.

[0028] Figure 6 3 is a comparison diagram of the inversion coefficient smoothing coefficient in the embodiment of the present invention.

[0029] Figure 7 This is a comparison diagram of the forward modeling results and the drilling and logging resistivity curves of the survey area in the embodiment of the present invention.

[0030] Figure 8 This is the final inversion resistivity cross-section diagram of the survey area according to the embodiment of the present invention.

[0031] Figure 9 This is a typical example of an embodiment of the present invention for establishing an inversion resistivity cross-section interpretation landmark map for a sandstone-type uranium deposit exploration area.

[0032] Figure 10 The embodiment of the present invention establishes an inversion resistivity section interpretation landmark map of a sandstone-type uranium deposit exploration area in the entire exploration area. DETAILED DESCRIPTION

[0033] The present invention provides a CSAMT data processing flow and data interpretation method for sandstone-type uranium deposits, which includes the following steps:

[0034] S1. Collect, count, and analyze the borehole and logging resistivity data of the survey area to obtain the geoelectric structure of the borehole and the logging resistivity curve of the survey area. In this embodiment, the ZKY1-7 hole in the Yingen area is taken as an example. The borehole and logging hole in the survey area are located in the Zhagai depression, 4.0 km northeast of the B22K06 line. The borehole data and logging resistivity map at this location are as follows: Figure 2 As shown, from Figure 2 The following information was revealed in the survey area:

[0035] (1) The hole depth is 0-25 m, and the apparent resistivity is 10-18 Ω·m, which is a relatively low-medium resistivity feature. It is a reflection of the mudstone and siltstone of the Bayingebi Formation of the Lower Cretaceous with thin layers of gravelly mudstone.

[0036] (2) The hole depth is 25 to 160 m, the apparent resistivity is 20 to 40 Ω·m, and the curve is serrated, with relatively medium resistivity, reflecting the sandy conglomerate interbedded with thin mudstone of the Bayingebi Formation of the Lower Cretaceous.

[0037] (3) The hole depth is 160-560 m, the apparent resistivity is 5-20 Ω·m, the curve is relatively smooth, and the relatively low resistivity characteristics are a reflection of the mudstone and siltstone of the Bayingebi Formation of the Lower Cretaceous.

[0038] (4) The hole depth is 560-588 m, the apparent resistivity is 30-80 Ω·m, and the curve is serrated, with relatively medium-high resistivity, reflecting the metamorphic sandstone of the Amushan Formation of the Lower Carboniferous.

[0039] S2. Determine the distance between measuring points, electric dipole moment, acquisition frequency, acquisition mode, number of electrical layers, thickness, and burial depth based on the resistivity curve, and use the forward modeling software em2d.exe provided by Zonge to establish the initial geoelectrical model, such as Figure 3 The forward model parameters in this embodiment are as follows: the measurement point distance is 200 m, the electric dipole moment is 100 m, the frequency is 8192-1 Hz, and some parameter information.

[0040] (1) The first layer of the model is distributed horizontally from 0 to 2000 m, with a thickness of 25 m and a resistivity of 15 Ω·m. It corresponds to the mudstone and siltstone of the Bayingebi Formation of the Lower Cretaceous with thin layers of gravelly mudstone.

[0041] (2) The second layer of the model is distributed from 0 to 2000 m laterally, with a thickness of 135 m and a resistivity of 25 Ω·m. It corresponds to the sandy conglomerate of the Bayingebi Formation of the Lower Cretaceous with thin layers of mudstone.

[0042] (3) The third layer of the model has a horizontal distribution of 0 to 2000 m, a thickness of 400 m, and a resistivity of 10 Ω·m, corresponding to the mudstone and siltstone of the Bayingebi Formation of the Lower Cretaceous.

[0043] (4) The fourth layer of the model has a horizontal distribution of 0 to 2000 m, a thickness of 240 m, and a resistivity of 50 Ω·m, corresponding to the metamorphic sandstone of the Amushan Formation of the Lower Carboniferous.

[0044] S3. Use the forward modeling software em2d.exe provided by Zonge to perform forward calculations on the established initial geoelectric model and generate a data file that can be inverted.

[0045] S4. Use several inversion models provided by the inversion software to perform inversion calculations on the generated invertible data files to obtain several inversion resistivity cross-section diagrams. This step uses SCS2D inversion software for calculation, which provides four inversion models: 2D Moving average of data, 2D Moving avg Bostick of resistivity, 2D Moving average of 1D model, and uniform resistivity. Figure 4 The inversion resistivity cross-sections obtained by inversion calculation for the above four different inversion models. The inversion parameters of the four models in this step are all system default parameters.

[0046] S5. Compare the resistivity cross-sections under the four different inversion models obtained in the previous step with Figure 3 The initial geoelectric model in the . Figure 4 It can be seen from the figure that the electrical structure inverted by the four initial background models is generally a four-layer structure, and the electrical characteristics are similar to Figure 3 The initial geoelectric model in the results is basically consistent. Combined with the analysis of drilling data, it can be seen that the inversion results of different models in this embodiment more objectively reflect the geoelectric characteristics of the survey area, which is consistent with the results of ZKY1-7 borehole ( Figure 2 Comparison of the revealed results: The thickness of the second electrical layer inverted by the 2D Moving average of data and the 2D Moving average of resistivity models differed significantly from the thickness revealed by the drill hole. The thickness of the third electrical layer inverted by the uniform resistivity model also differed significantly from the thickness revealed by the drill hole. The electrical layer inverted by the 2D Moving average of 1D model was more consistent with the drill hole revealed results. Therefore, the 2D Moving average of 1D model was selected as the final inversion model for this initial model.

[0047] S6. Determine the inversion coefficients of the inversion model. The inversion coefficients of the inversion model include the first layer thickness and the smoothing coefficient.

[0048] The value of the first layer thickness in the inversion model will affect the buried depth and thickness of the electrical layer. At the same time, certain geological information will be amplified and smoothed due to different values, which will affect the accuracy of geological inference and interpretation. The value of the first layer thickness should be selected based on drilling data.

[0049] In order to reasonably select the thickness of the first layer of the model, the forward modeling data next to the known borehole ZKY1-7 was selected in the processing, and the values ​​of the first layer thickness of the inversion model were inverted and compared. The final 2DMoving average of data inversion model was used for parameter selection. Five first layer thickness values ​​of 10m, 25m, 50m, 75m and 100m were selected based on the geological data. The comparison chart is shown in the figure below. Figure 5 shown.

[0050] Depend on Figure 5 Analysis of the resistivity cross-sections inverted for different first-layer thicknesses reveals that the electrical characteristics closely match the drilling data, with no decrease or increase in the number of electrical layers. Vertically, the structure appears to be four layers, with a medium-high resistivity, medium resistivity, low resistivity, and medium resistivity distribution. However, significant differences in the depth and thickness of the electrical layers in the resistivity cross-sections inverted for different first-layer thicknesses are observed. These differences are as follows: ① When the first layer thickness is 10 m and 25 m, the first electrical layer thickness increases, significantly differing from the geological conditions revealed by the drill hole. ② When the first layer thickness is 75 m, the shallow first and second electrical layers merge, and the third electrical layer shifts upward. ③ When the first layer thickness is 100 m, the first and second electrical layers merge, and a localized high-resistivity layer appears at shallow depth. ④ When the first layer thickness is 50 m, the depth and thickness of each electrical layer closely match the drill hole exposure. Therefore, based on the experimental results, a 50 m first layer thickness was selected for the data processing model.

[0051] The smoothing coefficient controls the relationship between the data fit and the roughness of the inversion model. If the value is too large, the data fit is too small, the model is smooth, and some geological information may be filtered out. If the value is too small, the data fit is too good, the model is rough, and there is a possibility of introducing false geological information. To select an appropriate smoothing coefficient, before data inversion, forward modeling data near known drill holes in the area (holes YZK1-7) were selected and compared with the smoothing coefficient values. Based on the drilling data, the smoothing coefficients selected were 0.1, 0.2, 0.3, 0.4, and 0.5, respectively. Figure 6 The inversion comparison test results when the smoothness coefficient values ​​are 0.1, 0.2, 0.3, 0.4, and 0.5 for the forward modeling data of borehole YZK1-7 are selected respectively.

[0052] Depend on Figure 6 As can be seen, the inversion results of the cross-sections are basically consistent, showing four electrical layers with a distribution of medium-high resistivity, medium resistivity, low resistivity, and medium resistivity. The stratification results are basically the same, but there are significant differences in the inverted resistivity values, contour density, and morphology of the electrical layers. These differences are mainly manifested in the following ways: ① When the smoothing coefficient is 0.1 or 0.2, due to the high data fit, the inverted resistivity contours are dense and clumped, and some inverted resistivity values ​​appear overall high. ② When the smoothing coefficient is equal to 0.4 or 0.5, the deep inverted resistivity contours are sparse, the inverted resistivity values ​​are large, and the deep electrical layer stratification is not obvious, which cannot objectively reflect the geological conditions of the area. ③ When the smoothing coefficient is 0.3, it is basically consistent with the stratum, lithology depth, and thickness revealed by drilling. The inverted resistivity cross-section diagram has clear stratification, which is consistent with the geological conditions and accurately reflects the geoelectric structure of the area. Therefore, based on the test results, the final smoothing coefficient for the data processing of the work area is 0.3.

[0053] Substitute the first layer thickness value of 50 m and the smoothing coefficient of 0.3 into the selected 2D Moving average of 1D model, perform inversion calculation on the inversion data obtained in step S3, and obtain the inversion resistivity cross-section diagram. Compare the inversion resistivity cross-section diagram with the resistivity curves of the drilling and logging in the survey area, as shown in Figure 2. Figure 7 As shown. Figure 7 As can be seen from the figure, the inversion resistivity cross-section diagram obtained using the first layer thickness and smoothing coefficient values ​​selected in this embodiment is generally consistent with the strata, lithology depth, and thickness revealed by drilling. The inversion resistivity cross-section diagram is clearly layered and well consistent with the geological conditions. Therefore, the first layer thickness and smoothing coefficient values ​​selected in this embodiment are reasonable.

[0054] S7. Edit the original data of sandstone-type uranium deposits in the survey area measured by the CSAMT method. Data editing is mainly to check the error and noise of the original data and edit it to prepare for the next step of data processing. Its content mainly includes the following aspects:

[0055] (1) Check whether the original field records and the data header records are consistent. If they are inconsistent, find the cause and correct it.

[0056] (2) Based on the possible sounding curve shape caused by the regional geological conditions and the data deviation (SEM) of the original records, the flying point data are eliminated and the original data are processed.

[0057] (3) The data of different working days of the same profile are spliced ​​together to prepare for the processing of the entire profile.

[0058] (4) Edit the corresponding terrain files based on the original field records to prepare for terrain inversion.

[0059] (5) Use Zonge's SHRED and AMTAVG software to preprocess the raw data.

[0060] (6) Use HSMOOTH software to perform sliding average filtering on the magnetic amplitude.

[0061] S8. Perform static displacement correction, transition zone correction, and terrain correction based on the edited original data;

[0062] (1) Static correction

[0063] When there are electrical differences in the horizontal direction of shallow geological bodies, the distribution of surface charges of these inhomogeneous bodies can cause abnormal changes in the electric field amplitude, and this change is independent of the frequency. It is manifested as a corresponding up and down translation of the Cania resistivity curve on the vertical axis of the double logarithmic coordinates, while the phase does not change. This phenomenon is called the static effect.

[0064] This time, we used Astatic.exe software provided by Zonge and the commonly used FLMA (fixed-length smoothing) method to correct static effects on the raw data from the entire area. This method calculates the average impedance of the entire survey line to estimate the static correction value of the apparent resistivity at the reference frequency.

[0065] (2) Transition zone correction

[0066] Used to correct the distortion of the Carnia resistivity in the transition region due to non-plane wave effects. Effective correction methods can be selected according to work needs.

[0067] (3) Terrain correction

[0068] Terrain correction is performed using the terrain correction software of Zonge Company in the United States. This software only needs to edit and generate terrain files before inversion, and the corresponding terrain files can be loaded during the inversion process.

[0069] The principle of terrain correction is to construct a grid model of the actual terrain by dividing the grid into a specific proportion based on the actual elevations at different measuring points along the survey line. When dividing the grid, the shallow grid of the model is subdivided as much as possible. Then, combined with the surface resistivity, a two-dimensional geoelectric model with terrain is constructed. This model is used as the starting point for a two-dimensional inversion calculation, indirectly eliminating the effects of terrain.

[0070] S9, using the final inversion model and inversion coefficient determined in steps e and f, perform final inversion processing on the data obtained in the previous step to generate the final resistivity cross-section diagram, such as Figure 8 shown.

[0071] S10. Select a relatively typical area in the exploration area to establish an inversion resistivity section of the sandstone-type uranium deposit exploration area, and interpret the stratigraphy, lithology, and fault structure in the inversion resistivity section diagram of the typical area based on known geological data, such as Figure 9 shown.

[0072] S11, according to the interpretation mark established in step S10, establish the inversion resistivity cross section of the sandstone type uranium deposit exploration area in the entire exploration area ( Figure 8 ) in the stratigraphic structure, lithology and fault structure, and finally obtain Figure 10 .

[0073] The staff used this method to conduct exploration experiments in the sandstone-type uranium deposit exploration area. Figure 10 This is the data interpretation map obtained using this method within the survey area. Based on the final data interpretation and comprehensive analysis, the drilling project deployment for sandstone-type uranium deposits was determined. The drilling findings are consistent with the inferred interpretation results of this method, and mineralization information was revealed, achieving good exploration results. Therefore, the CSAMT data processing process and data interpretation method for sandstone-type uranium deposits can provide a basis and reference for drilling project deployment in sandstone-type uranium exploration areas.

Claims

1. A CSAMT data processing flow and data interpretation method for sandstone-type uranium deposits, characterized by: The following steps are involved: a. Collect, compile and analyze the borehole and logging resistivity data in the survey area to obtain the borehole geoelectric structure and logging resistivity curve in the survey area; b. Determine the measuring point spacing, electric dipole moment, acquisition frequency, acquisition mode, and the number, thickness, and burial depth of electrical layers based on the geoelectric structure and logging resistivity curve, and establish an initial geoelectric model; c. Perform forward calculation on the established initial geoelectric model to generate invertible data files; d. Using several inversion models provided by the inversion software, perform inversion calculations on the generated invertible data files to obtain several inversion resistivity cross-sections; e. Compare the drawn inversion resistivity cross-sections with the established initial geoelectric model, and select the inversion model of the inversion resistivity cross-section that is closest to the initial geoelectric model as the final inversion model; f. Selecting a number of inversion coefficients based on the drilling data, substituting the inversion coefficients into the inversion model obtained above for inversion calculation, and comparing the calculation results with the borehole and logging resistivity curves of the survey area to determine the inversion coefficients of the inversion model; the inversion coefficients include the first layer thickness and smoothing coefficient of the model; g. Edit the original data of sandstone-type uranium deposits measured by the CSAMT method; h. Perform static displacement correction, transition zone correction, and terrain correction on the edited original data in sequence; i. Using the final inversion model and inversion coefficients determined in steps e and f, perform final inversion processing on the data obtained in the previous step to generate a final resistivity cross-section diagram; j. Select relatively typical areas in the exploration area to establish an inversion resistivity section for sandstone-type uranium deposits, and establish interpretation marks for the strata, lithology, and fault structures in the inversion resistivity section diagram of the typical area based on known geological data; k. Based on the interpretation marks established in step j, interpret and comprehensively analyze the inversion resistivity section stratigraphic structure, lithology and fault structure within the entire exploration area obtained in step i.

2. The CSAMT data processing flow and data interpretation method for sandstone-type uranium deposits according to claim 1 is characterized by: In step f, the selected first layer thickness and smoothing coefficient are substituted into the inversion model in step e, and the inversion calculation is performed on the inversion data in step c. Then, the inversion result is compared and analyzed with the borehole and logging resistivity curves of the survey area to determine whether the selected first layer thickness and smoothing coefficient are reasonable. If the selected first layer thickness and smoothing coefficient are reasonable, proceed to step g; if not, reselect and verify.

3. The CSAMT data processing flow and data interpretation method for sandstone-type uranium deposits according to claim 1 is characterized by: The initial geoelectric model described in step b is established by the forward modeling software em2d.exe, and forward modeling calculations are performed by the software to generate a data file that can be inverted.

4. The CSAMT data processing flow and data interpretation method for sandstone-type uranium deposits according to claim 1 is characterized by: The inversion software used in step d is SCS2D inversion software.

5. The CSAMT data processing flow and data interpretation method for sandstone-type uranium deposits according to claim 1 is characterized by: In step h, the edited original data is subjected to static displacement correction using the Astatic.exe software, and terrain correction is performed using the terrain correction software.

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