Uranium-bearing sandstone layer and redox transition zone identification method
Through the deep processing of hyperspectral remote sensing data and spectral feature separation technology, the problem of interference of the Quaternary thick cover layer was solved, and the rapid and accurate identification of uranium-containing sandstone layers and redox transition zones were achieved, reducing exploration costs and improving efficiency.
Patent Information
- Application Number
- CN202411902323.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-23
- Publication Date
- 2025-05-02
AI Technical Summary
In sedimentary basins, the Quaternary thick cover interferes with the identification of the underlying uranium-containing sandstone layers and redox transition zones by remote sensing technology. The existing exploration methods are costly, long periods and limited coverage.
Through the deep processing of hyperspectral remote sensing data, the spectral characteristics of the Quaternary thick cover layer and the target strata are extracted, combined with spectral feature separation and multi-source data fusion, the cover layer interference is eliminated, and the uranium-containing sandstone layer and redox transition zone are accurately identified.
It has achieved rapid and accurate identification of the locations of the underlying uranium-containing sandstone layers and redox transition zones, reduced exploration costs, improved efficiency, and provided economic and practical technical means for efficient exploration of sandstone-type uranium ores.
Abstract
Description
Technical Field
[0001] The invention belongs to the technical field of mineral resource exploration, and in particular relates to a method for identifying a uranium-containing sandstone layer and a redox transition zone. Background Art
[0002] Sandstone uranium deposits are one of the most important types of uranium resources in the world. They are mainly found in uranium-bearing sandstone layers or redox transition zones in sedimentary basins. Their formation is closely related to the sedimentary environment, stratigraphic structure and redox conditions. However, in many sedimentary basins (such as the Qaidam Basin and the Junggar Basin), the Quaternary thick cover layers are widely distributed, including deserts, alluvial fans, and lake sediments. The thickness of these cover layers can reach tens to hundreds of meters, which seriously interferes with the identification of the underlying uranium-bearing sandstone layers and redox transition zones by remote sensing technology.
[0003] Existing sandstone-type uranium exploration methods mainly rely on geological mapping, drilling and geophysical exploration. Although these methods are highly accurate, they are expensive, have a long cycle and have limited coverage. Hyperspectral remote sensing technology, with its advantage of high spectral resolution, can extract the spectral characteristics of minerals and rocks from the surface spectrum, and is a fast and economical exploration method. However, how to effectively eliminate the interference of the thick Quaternary cover layer and accurately extract the spectral characteristics of the underlying uranium-bearing sandstone layer and the redox transition zone is still a technical difficulty in this field. Summary of the invention
[0004] The purpose of the present invention is to provide a method for identifying uranium-containing sandstone layers and redox transition zones. The method can effectively eliminate the interference of Quaternary thick covering layers (such as deserts, alluvial deposits, lake sediments, etc.) in sedimentary basins, quickly and accurately extract the spectral characteristics of underlying uranium-containing sandstone layers and redox transition zones, and provide a scientific basis for the exploration of sandstone-type uranium deposits.
[0005] The technical solution to achieve the purpose of the present invention is:
[0006] A method for identifying a uranium-containing sandstone layer and a redox transition zone, the method comprising:
[0007] Step 1: Acquisition and preprocessing of hyperspectral remote sensing data;
[0008] Step 2: Extraction of spectral features of the Quaternary thick cover layer;
[0009] Step 3: Extracting spectral features of target strata (uranium-containing sandstone layer and redox transition zone);
[0010] Step 4: Eliminate interference from the Quaternary thick cover layer and extract spectral anomalies from the target stratum;
[0011] Step 5: Multi-source data fusion and verification.
[0012] The hyperspectral remote sensing data obtained in step 1 has a band range of 0.4-2.5 μm, a spatial resolution of 10-30 meters, and a spectral resolution of nanometers.
[0013] The hyperspectral remote sensing data preprocessing in step 1 includes: radiation correction, atmospheric correction, geometric correction, terrain correction, noise removal, and band selection.
[0014] The step 2 comprises:
[0015] Step 2.1, spectral characteristics analysis of the Quaternary cover layer: using hyperspectral remote sensing data, extract the typical spectral characteristics of the Quaternary cover layer;
[0016] Step 2.2, sampling and construction of cover layer spectral feature library: Select typical Quaternary cover layer samples in the study area, measure their spectral curves using a ground-based hyperspectral instrument, and establish a cover layer spectral feature library;
[0017] Step 2.3: Cover layer spectral classification: Identify the cover layer type in the hyperspectral remote sensing data through the classification algorithm and generate a cover layer distribution map.
[0018] The typical spectral characteristics of the Quaternary cover layer in step 2.1 include: reflectivity, band range, and absorption peak of desert cover layer, lake sediment, and salt sediment.
[0019] The step 3 comprises:
[0020] Step 3.1, Geological background analysis: Collect geological data of the study area, clarify the occurrence conditions of uranium-bearing sandstone layers, and summarize the mineral composition and typical spectral characteristics of the target strata;
[0021] Step 3.2, target formation spectrum measurement: perform ground spectrum measurement on the collected uranium-bearing sandstone samples and redox transition zone samples, record their continuous spectrum curves, and extract key absorption peak positions and reflection characteristics;
[0022] Step 3.3, constructing a spectral feature library of target strata: entering the measured spectral features of uranium-bearing sandstone layers and redox transition zone samples into the database as a reference template for target strata identification.
[0023] The elimination of interference from the Quaternary thick overburden in step 4 includes:
[0024] Step 4.1.1, separation of spectral features of the covering layer: separation of spectral features of the covering layer through spectral angle matching, spectral demixing analysis, and band ratio method;
[0025] Step 4.1.2, Generate the cover layer distribution map: Generate the cover layer distribution map based on spectral angle matching, spectral demixing analysis, and band ratio method, and mark the spatial distribution range and type of the cover layer.
[0026] The target stratum spectral anomaly extraction in step 4 includes:
[0027] Step 4.2.1, target stratum spectrum matching: match the target stratum spectrum through spectral angle matching, spectral correlation analysis, and band index method to generate a target stratum distribution map;
[0028] Step 4.2.2, spectral anomaly area extraction: use the principal component analysis method to circle possible spectral anomaly areas, calculate the spectral anomaly index related to the target formation, and extract the area with high anomaly values in the spectral anomaly index map;
[0029] Step 4.2.3, generating a spectrum anomaly distribution map: annotate the distribution range of the spectrum anomaly area in the form of an image to generate a spectrum anomaly distribution map.
[0030] The step 5 comprises:
[0031] Step 5.1, data fusion: superimpose and analyze the abnormal area extracted by hyperspectral with geological data, geophysical data and geochemical data to screen out reliable uranium target areas;
[0032] Step 5.2: Field verification: Conduct field verification in the hyperspectral anomaly area and confirm the distribution and uranium content of the target strata through drilling, sampling and laboratory analysis.
[0033] The beneficial technical effects of the present invention are:
[0034] The present invention provides a method for identifying uranium-containing sandstone layers and redox transition zones, which solves the problem of interference of thick Quaternary covering layers (such as deserts, alluvial deposits, lacustrine sediments, etc.) in sedimentary basins with the spectral identification of uranium-containing sandstone layers and redox transition zones. By using hyperspectral remote sensing data to extract the spectral characteristics of the covering layer and the target stratum, combined with interference elimination technology, the location of the underlying uranium-containing sandstone layer and the redox transition zone can be quickly and accurately identified, providing an economical and practical technical means for the efficient exploration of sandstone-type uranium deposits.
[0035] (1) Eliminating interference from overburden: For the first time, a method based on hyperspectral remote sensing data combined with a spectral shielding algorithm and a band ratio method was proposed to accurately eliminate the interference of the Quaternary thick overburden on sandstone-type uranium deposit exploration.
[0036] (2) Accurately identify target strata: A spectral feature library of the overburden layer was constructed, and the spectral demixing algorithm of hyperspectral data was used to shield the interference of the overburden layer, so as to quickly and accurately locate the distribution area of uranium-bearing sandstone layers and redox transition zones.
[0037] (3) Improve exploration efficiency: Compared with traditional geological exploration methods (such as drilling and geophysical exploration), the method of the present invention has low cost, wide coverage, and high efficiency. It can quickly screen uranium-bearing sandstone layers and redox transition zones over a large area, providing a low-cost and high-efficiency technical means for sandstone-type uranium mine exploration.
[0038] (4) Wide applicability: It is suitable for sandstone uranium exploration in similar sedimentary basins around the world and has wide application value. DETAILED DESCRIPTION
[0039] The present invention is further described in detail below in conjunction with embodiments.
[0040] The present invention provides a method for identifying uranium-containing sandstone layers and redox transition zones. Through deep processing of hyperspectral remote sensing data, combined with spectral feature analysis, interference shielding algorithm and multi-source data fusion, the interference of the Quaternary thick cover layer is successfully eliminated, and the spectral features of uranium-containing sandstone layers and redox transition zones are accurately extracted, providing an innovative and practical technical method for the rapid exploration of sandstone-type uranium deposits. The specific steps are as follows:
[0041] Step 1: Hyperspectral remote sensing data acquisition and preprocessing
[0042] Step 1.1: Hyperspectral remote sensing data acquisition
[0043] Hyperspectral remote sensing data (such as ASTER, Landsat 8, Hyperion or domestic hyperspectral satellite data) are selected to cover the target sedimentary basin area. The band range is 0.4-2.5μm, the spatial resolution is 10-30 meters, and the spectral resolution is nanometer level.
[0044] Step 1.2: Hyperspectral remote sensing data preprocessing
[0045] Radiation correction: Convert the original hyperspectral data into surface reflectance data to eliminate the effects of atmosphere and water vapor absorption.
[0046] Atmospheric correction: Use FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes) or 6S model to perform atmospheric correction on remote sensing images to eliminate the effects of atmospheric scattering and absorption.
[0047] Geometric correction: Geometrically align the data to ensure accurate superposition with topographic and geological maps.
[0048] Terrain correction: Combined with digital elevation model (DEM) data, the influence of terrain undulation on spectral reflectance is eliminated to ensure the authenticity of spectral characteristics.
[0049] Noise removal: Use principal component analysis (PCA) or band denoising algorithm to remove noise bands (such as water vapor absorption bands) in hyperspectral data.
[0050] Band selection: According to the spectral characteristics of the target stratum (such as uranium-bearing sandstone layer), key bands (such as the iron oxide absorption peak at 0.5-0.6μm, the clay mineral absorption peak at 2.2μm, etc.) are selected for subsequent analysis.
[0051] Step 2: Extraction of spectral features of the Quaternary thick cover layer
[0052] Step 2.1: Analysis of spectral characteristics of the Quaternary cover layer
[0053] Using hyperspectral remote sensing data, typical spectral characteristics of the Quaternary cover layer are extracted, including:
[0054] Desert cover: High reflectivity, especially in the visible and near-infrared bands (0.4-1.3μm).
[0055] Lake sediments: low reflectivity, manifested as a flat spectral curve.
[0056] Salt sediments: have an obvious absorption peak in the 2.0-2.5μm band.
[0057] Step 2.2: Sampling and overlay spectral feature library construction
[0058] Typical Quaternary cover layer samples (such as desert sediments, alluvial deposits, lake sediments, etc.) were selected in the study area, and their spectral curves were measured using a ground-based hyperspectral instrument (such as ASD FieldSpec) to establish a cover layer spectral feature library. The typical spectral features of the cover layer were recorded, such as the high reflectivity of desert sediments (0.6-0.8μm band) and the specific absorption peak of salt sediments (1.9μm band).
[0059] Step 2.3: Cover layer spectrum classification
[0060] Through classification algorithms such as spectral angle matching (SAM) and support vector machine (SVM), the cover type in hyperspectral remote sensing data is identified and the cover distribution map is generated.
[0061] Step 3: Extraction of spectral features of target strata (uranium-containing sandstone layer and redox transition zone)
[0062] Step 3.1: Geological background analysis
[0063] Collect geological data of the study area and clarify the occurrence conditions of uranium-bearing sandstone layers (such as sedimentary environment, formation thickness, distribution characteristics of redox transition zones, etc.).
[0064] Summarize the mineral composition of the target formation (such as iron oxides, clay minerals, carbonates, etc.) and their typical spectral characteristics.
[0065] Step 3.2: Spectral measurement of target formation
[0066] Ground spectral measurements were carried out on the collected uranium-bearing sandstone samples and redox transition zone samples, their continuous spectral curves were recorded, and the key absorption peak positions and reflection characteristics were extracted.
[0067] For example, iron oxide has an absorption peak at 0.5-0.6 μm, clay minerals have an absorption peak at 2.2 μm, and carbonates have an absorption peak around 2.3 μm.
[0068] Step 3.3: Construction of target formation spectral feature library
[0069] The measured spectral characteristics of uranium-bearing sandstone layers and redox transition zone samples are entered into the database as a reference template for target stratum identification.
[0070] Step 4: Elimination of interference from the Quaternary thick cover layer and extraction of spectral anomalies of the target stratum
[0071] Step 4.1: Elimination of interference from the Quaternary thick cover layer
[0072] Step 4.1.1: Separation of cover layer spectral features
[0073] Since the Quaternary thick cover layer (such as desert sediments, alluvial deposits, lake sediments, etc.) has a strong spectral reflectance characteristic, its spectral signal will cover or mix the spectral characteristics of the underlying target stratum (uranium-containing sandstone layer), so it is necessary to eliminate the interference of the cover layer through the following methods:
[0074] Spectral Angle Matching (SAM): Match the pixel spectra in the hyperspectral data with the overlay spectral library, calculate the spectral angles, and identify areas with similar spectra to the overlay.
[0075] Spectral Unmixing: Decompose the spectral signal of each pixel into the spectral contribution ratios of various ground objects (such as overburden layer and target layer), and separate the spectral components of the overburden layer.
[0076] Band ratio method: Utilize the specific band reflection characteristics of the covering layer (such as the high reflection band of desert sediments) to calculate the band ratio map and shield the influence of the covering layer.
[0077] Step 4.1.2: Generate the coverage distribution map
[0078] Based on the above method, a cover layer distribution map is generated to mark the spatial distribution range and type of the cover layer, providing a reference for the subsequent identification of the target stratum.
[0079] Through overlay analysis, the spectral signal of the overburden layer is shielded and the spectral characteristics of the underlying target stratum are enhanced.
[0080] Step 4.2: Extraction of spectral anomalies of target formation
[0081] Step 4.2.1: Spectral matching of target formation
[0082] (1) Spectral Angle Matching (SAM): The hyperspectral data is matched pixel by pixel with the spectral feature library of the target formation, the spectral angle is calculated, and the area that best matches the spectrum of the target formation is extracted.
[0083] (2) Spectral correlation analysis: Calculate the correlation coefficient between the hyperspectral data and the target spectral features and identify the high correlation areas.
[0084] (3) Band index method: Based on the spectral characteristics of the target stratum, the index of a specific band (such as iron oxide index, clay mineral index) is calculated to generate a distribution map of the target stratum.
[0085] Step 4.2.2: Extraction of spectral abnormal regions
[0086] (1) Principal Component Analysis (PCA)
[0087] The principal component analysis method is used to extract the main spectral change features from the hyperspectral data, highlighting the spectral anomaly information of the target stratum. By analyzing the principal component image, possible spectral anomaly areas are circled.
[0088] (2) Calculation of spectral anomaly index
[0089] Calculate the spectral anomaly index related to the target formation, such as:
[0090] Iron oxide index: (R 0.5 -R 0.6 ) / (R 0.5 +R 0.6 );
[0091] In the formula, R 0.5 It is the reflectivity at a wavelength of 0.5 microns (500 nanometers), indicating the intensity of reflected light from a target object (such as soil or vegetation) at a wavelength of 500 nanometers. This band is usually associated with the spectral characteristics of vegetation, minerals or iron oxides. 0.6 It is the reflectivity at a wavelength of 0.6 microns (600 nanometers), indicating the intensity of reflected light from the target object at a wavelength of 600 nanometers. This band is often used to detect the spectral characteristics of iron oxides because the reflectivity of iron oxides in this band is usually low.
[0092] Clay mineral index: (R 2.2 -R 1.8 ) / (R2.2 +R 1.8 ).
[0093] In the formula, R 2.2 It is the reflectivity at a wavelength of 2.2 microns (2200 nanometers), indicating the intensity of reflected light from a target object (such as soil or rock) at a wavelength of 2200 nanometers. This band is an important band near the characteristic absorption peak of clay minerals (such as kaolinite, montmorillonite, illite, etc.), and clay minerals usually have strong absorption characteristics in this band. 1.8 It is the reflectivity at a wavelength of 1.8 microns (1800 nanometers), which indicates the intensity of reflected light from the target object at a wavelength of 1800 nanometers. This band is usually used as a reference band because the absorption characteristics of clay minerals in this band are relatively weak.
[0094] In the spectral anomaly index map, the areas with high outlier values are extracted.
[0095] Step 4.2.3: Generate spectral anomaly distribution map
[0096] The distribution range of the spectral anomaly area is marked in the form of an image to generate a spectral anomaly distribution map, providing a target area for subsequent exploration.
[0097] Step 5: Multi-source data fusion and verification
[0098] Step 5.1: Data fusion
[0099] The abnormal areas extracted by hyperspectral analysis are superimposed with geological data (such as stratigraphic distribution maps, structural maps), geophysical data (such as radioactivity measurements, gravity and magnetic measurements) and geochemical data (such as abnormal distribution of uranium elements) to screen out reliable uranium mine targets.
[0100] Step 5.2: Field verification
[0101] Field verification is carried out in the hyperspectral anomaly area, and the distribution and uranium content of the target strata are confirmed through drilling, sampling and laboratory analysis.
[0102] The present invention is described in detail above in conjunction with the embodiments, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of ordinary technicians in the field without departing from the purpose of the present invention. The contents not described in detail in the present invention can adopt the existing technology.
Claims
1. A method for identifying uranium-containing sandstone layers and redox transition zones, characterized in that: The method comprises: Step 1: Acquisition and preprocessing of hyperspectral remote sensing data; Step 2: Extraction of spectral features of the Quaternary thick cover layer; Step 3: Extracting spectral features of target strata; Step 4: Eliminate interference from the Quaternary thick cover layer and extract spectral anomalies from the target stratum; Step 5: Multi-source data fusion and verification.
2. The method for identifying uranium-containing sandstone layers and redox transition zones according to claim 1, characterized in that: The hyperspectral remote sensing data obtained in step 1 has a band range of 0.4-2.5 μm, a spatial resolution of 10-30 meters, and a spectral resolution of nanometers.
3. The method for identifying uranium-containing sandstone layers and redox transition zones according to claim 1, characterized in that: The hyperspectral remote sensing data preprocessing in step 1 includes: radiation correction, atmospheric correction, geometric correction, terrain correction, noise removal, and band selection.
4. The method for identifying uranium-containing sandstone layers and redox transition zones according to claim 1, characterized in that: The step 2 comprises: Step 2.1, spectral characteristics analysis of the Quaternary cover layer: using hyperspectral remote sensing data, extract the typical spectral characteristics of the Quaternary cover layer; Step 2.2, sampling and construction of cover layer spectral feature library: Select typical Quaternary cover layer samples in the study area, measure their spectral curves using a ground-based hyperspectral instrument, and establish a cover layer spectral feature library; Step 2.3: Cover layer spectral classification: Identify the cover layer type in the hyperspectral remote sensing data through the classification algorithm and generate a cover layer distribution map.
5. The method for identifying uranium-containing sandstone layers and redox transition zones according to claim 4, characterized in that: The typical spectral characteristics of the Quaternary cover layer in step 2.1 include: reflectivity, band range, and absorption peak of desert cover layer, lake sediment, and salt sediment.
6. The method for identifying uranium-containing sandstone layers and redox transition zones according to claim 1, characterized in that: The step 3 comprises: Step 3.1, Geological background analysis: Collect geological data of the study area, clarify the occurrence conditions of uranium-bearing sandstone layers, and summarize the mineral composition and typical spectral characteristics of the target strata; Step 3.2, target formation spectrum measurement: perform ground spectrum measurement on the collected uranium-bearing sandstone samples and redox transition zone samples, record their continuous spectrum curves, and extract key absorption peak positions and reflection characteristics; Step 3.3, constructing a spectral feature library of target strata: entering the measured spectral features of uranium-bearing sandstone layers and redox transition zone samples into the database as a reference template for target strata identification.
7. The method for identifying uranium-containing sandstone layers and redox transition zones according to claim 1, characterized in that: The elimination of interference from the Quaternary thick overburden in step 4 includes: Step 4.1.1, separation of spectral features of the covering layer: separation of spectral features of the covering layer through spectral angle matching, spectral demixing analysis, and band ratio method; Step 4.1.2, Generate the cover layer distribution map: Generate the cover layer distribution map based on spectral angle matching, spectral demixing analysis, and band ratio method, and mark the spatial distribution range and type of the cover layer.
8. The method for identifying uranium-containing sandstone layers and redox transition zones according to claim 1, characterized in that: The target stratum spectral anomaly extraction in step 4 includes: Step 4.2.1, target stratum spectrum matching: match the target stratum spectrum through spectral angle matching, spectral correlation analysis, and band index method to generate a target stratum distribution map; Step 4.2.2, spectral anomaly area extraction: use the principal component analysis method to circle possible spectral anomaly areas, calculate the spectral anomaly index related to the target formation, and extract the area with high anomaly values in the spectral anomaly index map; Step 4.2.3, generating a spectrum anomaly distribution map: annotate the distribution range of the spectrum anomaly area in the form of an image to generate a spectrum anomaly distribution map.
9. The method for identifying uranium-containing sandstone layers and redox transition zones according to claim 1, characterized in that: The step 5 comprises: Step 5.1, data fusion: superimpose and analyze the abnormal area extracted by hyperspectral with geological data, geophysical data and geochemical data to screen out reliable uranium target areas; Step 5.2: Field verification: Conduct field verification in the hyperspectral anomaly area and confirm the distribution and uranium content of the target strata through drilling, sampling and laboratory analysis.