Prospecting method, system and electronic equipment based on volcanic rock spatial distribution identification

Abstract

The application provides a kind of based on volcanic rock spatial distribution identification prospecting method, system and electronic equipment, it is related to volcanic rock cover spatial distribution identification field.The application includes: determining the buried depth of volcanic distribution point rock;Using the correspondence between volcanic rock distribution and residual gravity anomaly, determine the residual gravity anomaly value caused by volcanic rock and then determine the volcanic rock distribution characteristics on each profile;Build the distribution model of various geological bodies except volcanic rock on each profile;According to the volcanic rock spatial distribution characteristics on each profile and the spatial distribution model of various geological bodies except volcanic rock, determine the spatial distribution model of various geological bodies in the study area and then carry out prospecting work in the study area.The application identifies the spatial distribution of volcanic rock based on the principle that the density of volcanic rock strata at different depths is different, improving the identification accuracy of the spatial distribution of volcanic rock.

Description

Technical Field

[0001] This invention relates to the field of spatial distribution identification of volcanic rock caprock, and in particular to a mineral exploration method, system and electronic equipment based on spatial distribution identification of volcanic rocks. Background Technology

[0002] Volcanic rocks, also known as extrusive rocks, are rocks formed when magma carrying other rock fragments or crystals is ejected along volcanic conduits to the Earth's surface and cools. They include volcanic lava and pyroclastic rocks. Volcanic rocks play a crucial role in mineral formation and have always been a focus of geological prospecting. Taking the Luzong Basin in the middle and lower reaches of the Yangtze River as an example, volcanic rocks are widely distributed on the surface of this region. Deposits such as the Luohe iron mine, Hejiaxiaoling iron mine, and Jingbian copper mine are all located within volcanic rocks or at the contact zone between volcanic rocks and underlying intrusive rocks. However, surface volcanic rocks obscure human understanding of the underlying strata, structures, and igneous rocks, posing a challenge to geological prospecting beneath them. Therefore, the detection, identification, and stripping of the spatial distribution of volcanic rocks are not only helpful for prospecting within volcanic strata but also have significant practical value for prospecting at the contact between volcanic rocks and underlying strata, as well as for geological prospecting beneath volcanic rock cover.

[0003] Geophysical methods for detecting the spatial distribution of volcanic rocks are based on the physical properties of the rocks. Currently, the detection of the spatial distribution of volcanic rocks has not yielded satisfactory results, mainly due to two reasons: First, the unique lithological characteristics of volcanic strata (complex lithology and poor lateral continuity) result in strong shielding and attenuation of signals such as seismic exploration, thus limiting the effectiveness of seismic exploration in volcanic areas. Second, the variation of volcanic strata properties with burial depth is unclear, and our understanding of the differences in physical properties between volcanic strata and surrounding rocks is insufficient. Therefore, how to detect the spatial distribution of volcanic caprock remains a crucial factor restricting breakthroughs in mineral exploration in volcanic basins. Taking density as an example, the average density of volcanic rocks collected from the surface in the past is generally between 2.50 and 2.56 × 10⁻⁶. 3 kg·m -3 The density of intrusive rocks exposed at the surface is 2.58–2.64 × 10⁻⁶. 3 kg·m -3 The result showed that the density of intrusive rocks was slightly higher than that of volcanic rocks. Using this result as a basis for inferring the spatial distribution of volcanic rocks is one-sided, leading to a significant discrepancy between the detected results and the actual spatial distribution of volcanic rocks. The main reason is the lack of understanding of how rock properties change with increasing burial depth due to variations in environmental factors such as pressure. Summary of the Invention

[0004] The purpose of this invention is to provide a mineral exploration method, system, and electronic device based on the spatial distribution identification of volcanic rocks. The spatial distribution identification of volcanic rocks is based on the principle that the density of volcanic rock strata at different depths is different, thereby improving the accuracy of the spatial distribution identification of volcanic rocks.

[0005] To achieve the above objectives, the present invention provides the following solution:

[0006] A mineral exploration method based on spatial distribution identification of volcanic rocks, comprising:

[0007] Obtain the density values ​​of volcanic rocks at different depths in each borehole within the study area;

[0008] The depth-density variation curve of volcanic rocks in the study area was obtained by fitting the density values ​​of volcanic rocks at different depths of multiple boreholes.

[0009] The depth at which the boundary between volcanic and intrusive rocks is located in each borehole within the study area is determined as the burial depth of the volcanic distribution point in the corresponding borehole.

[0010] Acquire gravity data within the study area;

[0011] Extract the residual gravity anomalies from the gravity data;

[0012] Based on the burial depth of the volcanic rock distribution points and the residual gravity anomaly, the residual gravity anomaly value caused by the volcanic rock is determined using the correspondence between volcanic rock distribution and residual gravity anomaly.

[0013] Based on the depth-density variation curve of the volcanic rocks, the correspondence between the distribution of volcanic rocks and the residual gravity anomaly, and the residual gravity anomaly value caused by the volcanic rocks, multi-profile variable density volcanic rock modeling and forward and inverse modeling under borehole constraints are carried out in combination with the surface geology of the study area to determine the distribution characteristics of volcanic rocks on each profile.

[0014] Based on gravity data, magnetic data, electrical data and seismic exploration data of the study area, and on the basis of constructing the distribution of volcanic rocks in each profile, a distribution model of various geological bodies other than the volcanic rocks in each profile is constructed.

[0015] Based on the spatial distribution characteristics of volcanic rocks on each profile and the spatial distribution models of various geological bodies other than the volcanic rocks, the spatial distribution models of various types of geological bodies in the study area are determined.

[0016] Mineral exploration was conducted in the study area based on the spatial distribution model of the various types of geological bodies.

[0017] Optionally, based on the burial depth of the volcanic rock distribution points and the residual gravity anomaly, the residual gravity anomaly value caused by the volcanic rock is determined using the correspondence between volcanic rock distribution and residual gravity anomaly, including:

[0018] Select any borehole as the current borehole;

[0019] Determine any adjacent borehole of the current borehole as the current adjacent borehole;

[0020] Based on the residual gravity anomaly, determine the magnitude of the change in residual gravity anomaly value between the current borehole and its current adjacent borehole;

[0021] Determine the amplitude of the volcanic rock burial depth variation between the current borehole and its current adjacent borehole;

[0022] Based on the variation amplitude of the volcanic rock burial depth and the variation amplitude of the residual gravity anomaly value, determine whether the residual gravity anomaly value of the current borehole and the residual gravity anomaly value of the current adjacent borehole satisfy the correspondence relationship between volcanic rock distribution and residual gravity anomaly, and obtain the judgment result;

[0023] If the judgment result is yes, then it is determined that the currently extracted residual gravity anomaly value is caused by volcanic rock.

[0024] Optionally, after determining that the currently extracted residual gravity anomaly is caused by volcanic rock, the method further includes:

[0025] If the currently extracted residual gravity anomaly value does not satisfy the correspondence between the volcanic rock distribution and the residual gravity anomaly, then return to the step "Extract residual gravity anomaly value from the gravity data".

[0026] Optionally, the correspondence between the volcanic rock distribution and the residual gravity anomaly is as follows:

[0027] Wherein, ΔG is the variation amplitude of the residual gravity anomaly value at the locations of two adjacent boreholes; ΔX is the distance between two adjacent boreholes; κ is the proportionality coefficient; ΔH is the variation amplitude of the volcanic rock burial depth between two adjacent boreholes; the volcanic rock distribution and residual gravity anomaly between multiple adjacent boreholes all satisfy the volcanic rock distribution-residual gravity anomaly correspondence.

[0028] A mineral exploration system based on spatial distribution identification of volcanic rocks, comprising:

[0029] The volcanic rock density value acquisition module is used to acquire the volcanic rock density values ​​at different depths in each borehole within the study area;

[0030] The volcanic rock depth-density variation curve determination module is used to fit the volcanic rock density values ​​at different depths of multiple boreholes to obtain the volcanic rock depth-density variation curve of the study area.

[0031] The volcanic rock distribution point burial depth determination module is used to determine the depth of the boundary between volcanic rocks and intrusive rocks in each borehole in the study area as the burial depth of the volcanic rock distribution point in the corresponding borehole.

[0032] The gravity data acquisition module is used to acquire gravity data within the study area.

[0033] The residual gravity anomaly module is used to extract residual gravity anomalies from the gravity data;

[0034] The residual gravity anomaly determination module is used to determine the residual gravity anomaly value caused by volcanic rocks based on the burial depth of the volcanic rock distribution point and the residual gravity anomaly, using the correspondence between the burial depth of the volcanic rock distribution point and the residual gravity anomaly.

[0035] The volcanic rock profile distribution characteristic determination module is used to determine the volcanic rock distribution characteristics of each profile by performing multi-profile variable density volcanic rock modeling and forward and inverse modeling under borehole constraints based on the volcanic rock depth-density variation curve, the volcanic rock distribution-residual gravity anomaly correspondence, and the residual gravity anomaly value caused by the volcanic rock, combined with the surface geology of the study area.

[0036] The module for determining the distribution model of multiple geological bodies other than the volcanic rocks is used to construct the distribution model of multiple geological bodies other than the volcanic rocks on each profile based on the gravity data, magnetic data, electrical data and seismic exploration data of the study area, after the volcanic rock distribution of each profile has been constructed.

[0037] The module for determining the spatial distribution model of multiple geological bodies is used to determine the spatial distribution model of multiple geological bodies in the study area based on the distribution characteristics of volcanic rocks on each profile and the distribution model of multiple geological bodies other than the volcanic rocks.

[0038] The mineral exploration module is used to conduct mineral exploration work in the study area based on the spatial distribution model of the various types of geological bodies.

[0039] An electronic device includes a memory and a processor, the memory storing a computer program, and the processor running the computer program to enable the electronic device to perform a mineral exploration method based on the spatial distribution identification of volcanic rocks.

[0040] Optionally, the memory is a readable storage medium.

[0041] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0042] This invention provides a mineral exploration method, system, and electronic equipment based on the spatial distribution identification of volcanic rocks. The method involves: acquiring volcanic rock density values ​​at different depths in each borehole within a study area; fitting the volcanic rock density values ​​at different depths in multiple boreholes to obtain a depth-density variation curve of volcanic rocks in the study area; determining the depth of the boundary between volcanic rocks and intrusive rocks in each borehole as the burial depth of the corresponding volcanic distribution point; acquiring gravity data within the study area; extracting residual gravity anomalies from the gravity data; and determining the residual gravity anomaly values ​​caused by volcanic rocks based on the burial depth of the volcanic distribution point and the residual gravity anomaly, utilizing the correspondence between volcanic rock distribution and residual gravity anomaly; and finally, based on the depth-density variation curve of volcanic rocks... This invention establishes a correlation between volcanic rock distribution and residual gravity anomalies, and identifies residual gravity anomalies caused by volcanic rocks. Combined with surface geology of the study area, it conducts multi-section variable-density volcanic rock modeling and forward / inverse modeling under borehole constraints to determine the distribution characteristics of volcanic rocks on each section. Based on gravity, magnetic, electrical, and seismic data of the study area, it constructs distribution models for various geological bodies other than volcanic rocks on each section, building upon the existing volcanic rock distribution models. Based on the spatial distribution characteristics of volcanic rocks on each section and the spatial distribution models of various geological bodies other than volcanic rocks, it determines the spatial distribution models of various types of geological bodies in the study area. Mineral exploration is then conducted in the study area based on these spatial distribution models. This invention identifies the spatial distribution of volcanic rocks based on the principle of different densities in volcanic rock strata at different depths, improving the accuracy of volcanic rock spatial distribution identification. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a flowchart of the spatial distribution identification method for volcanic rocks in Embodiment 1 of the present invention;

[0045] Figure 2 This is a graph showing the change in density of volcanic rock with depth in Example 1 of the present invention;

[0046] Figure 3 is a diagram showing the relationship between the spatial distribution of volcanic rocks and the residual gravity anomaly in Example 1 of the present invention; Figure 3(a) is a schematic diagram of the gravity anomaly curve and the extracted residual gravity anomaly curve in Example 1 of the present invention; Figure 3(b) is a schematic diagram of the distribution points of volcanic rock burial depth in the borehole in Example 1 of the present invention.

[0047] Figure 4 This is a gravity anomaly fitting curve diagram in Embodiment 1 of the present invention;

[0048] Figure 5 This is a gravity-based forward and inverse model of volcanic rock distribution in Example 1 of the present invention;

[0049] Figure 6 This is a gravity and magnetic fitting curve diagram from Embodiment 1 of the present invention;

[0050] Figure 7 This is a seismic survey profile from Embodiment 1 of the present invention;

[0051] Figure 8 This is a diagram illustrating the forward and inverse gravity modeling in Embodiment 1 of the present invention.

[0052] Figure 9 This is a schematic diagram of a geological model with a polygonal cross-section in Embodiment 1 of the present invention;

[0053] Figure 10 This is a cross-sectional schematic diagram of a geological model with a polygonal cross-section in Embodiment 1 of the present invention;

[0054] Figure 11 This is a schematic diagram of the forward and inverse modeling results of the full cross-section in Embodiment 1 of the present invention;

[0055] Figure 12 This is a schematic diagram of the spatial distribution model of volcanic rocks in Embodiment 1 of the present invention;

[0056] Figure 13 This is a schematic diagram of the geological model in Embodiment 1 of the present invention. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] The purpose of this invention is to provide a mineral exploration method, system, and electronic device based on the spatial distribution identification of volcanic rocks. The spatial distribution identification of volcanic rocks is based on the principle that the density of volcanic rock strata at different depths is different, thereby improving the accuracy of the spatial distribution identification of volcanic rocks.

[0059] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0060] Example 1

[0061] like Figure 1 As shown, this embodiment provides a mineral exploration method based on the spatial distribution identification of volcanic rocks, including:

[0062] Step 101: Obtain the density values ​​of volcanic rocks at different depths in each borehole within the study area. That is, obtain the density difference at the interface between the volcanic rock and the underlying geological body (intrusive rock) in each borehole.

[0063] Step 102: The depth-density variation curve of volcanic rocks in the study area is obtained by fitting the density values ​​of volcanic rocks at different depths of multiple boreholes.

[0064] Rock samples were collected and analyzed from the study area, particularly the rock properties from boreholes. This analysis constructed an integrated model of surface and deep rock property (primarily density) variations, including the rate of density change at different depths and density differences at key density interfaces. For example, regarding the rate of density change, volcanic rocks showed the highest density increase rate from the surface to a depth of -400 meters, approximately 0.8 × 10⁻⁶. 3 kg·m -3 / km, the rate of increase slows down below -400 meters. The constructed density versus depth curves, the density versus density curve of a single volcanic rock, and the density versus depth curve of the intrusive rock beneath the volcanic rock are shown below. Figure 2 As shown.

[0065] Step 103: Determine the depth of the boundary between volcanic rocks and intrusive rocks in each borehole within the study area as the burial depth of the volcanic distribution point in the corresponding borehole.

[0066] Step 104: Obtain gravity data within the study area.

[0067] Step 105: Extract residual gravity outliers from the gravity data.

[0068] Step 106: Based on the burial depth of the volcanic rock distribution points and the residual gravity anomaly, determine the residual gravity anomaly value caused by the volcanic rock using the correspondence between volcanic rock distribution and residual gravity anomaly; the correspondence between volcanic rock distribution and residual gravity anomaly is as follows:

[0069] Wherein, ΔG represents the amplitude of the residual gravity anomaly between two adjacent boreholes; ΔX represents the distance between two adjacent boreholes; κ is the proportionality coefficient; and ΔH represents the amplitude of the volcanic rock burial depth between two adjacent boreholes. The distribution of volcanic rocks and residual gravity anomalies between multiple adjacent boreholes satisfy the correspondence between volcanic rock distribution and residual gravity anomaly. Boreholes in the study area were collected to establish the relationship between the borehole-controlled volcanic rock burial depth distribution and residual gravity anomalies. As shown in Figure 3, in Figure 3(a), the vertical axis represents the amplitude of gravity anomaly, and the horizontal axis represents distance. In Figure 3(b), the vertical axis represents burial depth, and the horizontal axis represents distance.

[0070] The spatial distribution of volcanic rocks and gravity data show a certain degree of mirror relationship, but not a complete mirror relationship (for example, the gravity anomaly at borehole numbered FZK01 is smaller than that of the Huangmeijian pluton outcrop at the western end of the profile). This is because the gravity data includes gravity anomalies caused by volcanic rocks and other geological bodies, forming a superimposed field, i.e., g = g 火山岩 +g0, where g0 represents the gravity field caused by geological bodies other than volcanic rocks. Therefore, this embodiment performs anomaly separation on the gravity field, extracting residual gravity anomalies so that the spatial distribution of volcanic rocks and the extracted residual gravity anomaly curve are mirror images of each other, that is, the rate of change of the thickness of the volcanic rocks controlled by the borehole (generally referring to a thickness > 400 meters) is linearly related to the rate of change of the extracted residual gravity anomaly. Thus, the extracted residual gravity anomaly is caused by volcanic rocks, i.e., g... 火山岩 In Figure 3, the upper line represents the extracted residual gravity anomaly data, which is a curve showing the change with borehole location (distance). The thicker the volcanic rock, the higher the residual gravity anomaly. Through borehole comparison and extraction, the gravity anomaly at borehole number FZK01 is slightly larger than that of the Huangmeijian rock mass outcrop at the western end of the profile, which is consistent with the actual geological conditions.

[0071] Using borehole location (distance) as the x-axis and depth as the y-axis, the variation in volcanic rock burial depth distribution on the profile is obtained based on multiple volcanic rock burial depth distribution points. Residual gravity anomalies are extracted from the gravity data. Using borehole location (distance) as the x-axis and gravity anomaly values ​​as the y-axis, residual gravity anomaly curves are extracted for the locations of the boreholes and the intervals between them. Based on the volcanic rock distribution curve and the gravity anomaly curve, the correspondence between volcanic rock burial depth distribution and residual gravity anomaly is determined. Whether the correspondence between the volcanic rock burial depth distribution and residual gravity anomaly curves is linear is used to determine whether the extracted residual gravity anomaly is caused by volcanic rock. If it is not linear, the residual gravity anomaly is re-extracted until the extracted residual gravity anomaly and the volcanic rock burial depth distribution satisfy the linearity requirement. This indicates that the extracted residual gravity anomaly is caused by volcanic rock strata, i.e., residual gravity anomaly = g 火山岩 .

[0072] Step 106 includes:

[0073] Step 1061: Determine any borehole as the current borehole.

[0074] Step 1062: Determine any adjacent borehole of the current borehole as the current adjacent borehole.

[0075] Step 1063: Based on the residual gravity anomaly, determine the amplitude of the change in residual gravity anomaly value between the current borehole and the current adjacent borehole.

[0076] Step 1064: Determine the amplitude of the volcanic rock burial depth variation between the current borehole and the current adjacent borehole.

[0077] Step 1065: Based on the variation amplitude of volcanic rock burial depth and the variation amplitude of residual gravity anomaly value, determine whether the residual gravity anomaly value of the current borehole and the residual gravity anomaly value of the current adjacent borehole satisfy the correspondence relationship between volcanic rock distribution and residual gravity anomaly, and obtain the judgment result.

[0078] Step 1066: If the judgment result is yes, then it is determined that the currently extracted residual gravity anomaly value is caused by volcanic rock.

[0079] Step 1067: If the currently extracted residual gravity anomaly value does not satisfy the correspondence between volcanic rock distribution and residual gravity anomaly, then return to step 105.

[0080] Step 107: Based on the volcanic rock depth-density variation curve, the correspondence between volcanic rock distribution and residual gravity anomaly, and the residual gravity anomaly value caused by volcanic rocks, and combined with the surface geology of the study area, multi-profile variable density volcanic rock modeling and forward and inverse modeling are carried out under borehole constraints to determine the volcanic rock distribution characteristics on each profile.

[0081] Based on the depth-density variation curve, the correspondence between the burial depth distribution of volcanic rocks and the residual gravity anomaly, and the residual gravity anomaly, forward and inverse modeling of multi-profile variable density volcanic rocks under borehole constraints is carried out to characterize the spatial distribution characteristics of volcanic rocks on each profile.

[0082] Residual gravity anomalies are used to conduct forward and inverse modeling of variable-density volcanic rocks across multiple profiles under borehole constraints, characterizing the spatial distribution features of volcanic rocks on each profile. In the profile modeling forward and inverse modeling process, if other reliable magnetic, electrical, and seismic exploration data are available, they should also be used as important bases for modeling forward and inverse modeling, which can further improve the accuracy of identification. The theoretical gravity anomaly g generated by the volcanic rock model constructed on the profile is considered as follows. 火山岩理论 The fitting error with the actual extracted residual gravity anomaly data is less than 5%, indicating that the model accurately reflects the distribution of volcanic rocks on the profile. The inversion results are as follows: Figure 5 .

[0083] The forward and inverse steps for volcanic rock modeling are as follows:

[0084] 1. Import profile data using gravity, magnetoelectricity, and forward modeling software. Figure 4 (Solid line in the middle) uses the separated residual gravity anomaly, namely the gravity anomaly of volcanic rocks.

[0085] 2. Construct a geological model with a polygonal cross-section (e.g., Figure 9 ), its cross-section (such as Figure 10 It can approximate the morphology of various geological bodies.

[0086] 3. Assign physical property parameters, such as density, to the constructed geological body, and perform forward modeling on the geological body using forward modeling formulas to obtain the theoretical gravity anomaly caused by the geological body. Figure 4 (middle dashed line).

[0087] 4. The theoretical gravity anomaly of the constructed geological body and the imported gravity anomaly ( Figure 4 If the values ​​and changes of the two lines are basically consistent, and the fitting error is less than 5%, then (e.g., solid lines) Figure 4 , Figure 4 If the horizontal axis represents distance and the vertical axis represents gravity amplitude, then the anomaly is considered to be caused by a constructed geological body. Figure 5 , Figure 5 (The horizontal axis represents distance; the vertical axis represents depth). Otherwise, adjust the geological body morphology until the fitting error meets the requirements.

[0088] The most significant difference between this gravity forward modeling work and existing technologies is the use of variable density. Previous gravity forward modeling studies assigned a uniform density to individual geological bodies based on measurements from surface samples. This resulted in significant discrepancies between the geological understanding gained through exploration and reality. This new approach, however, utilizes the obtained density variation patterns of volcanic rocks with depth to conduct variable density gravity forward modeling on this single geological body, greatly improving identification accuracy.

[0089] In a rectangular coordinate system, the gravity two-and-a-half-body forward modeling formula for a finite-length triangular prism is as follows:

[0090]

[0091] The forward modeling formula for the weight of a prism composed of multiple finite-length triangular prisms with polygonal cross-sections is as follows:

[0092]

[0093] Where: G is the gravitational constant, σ is the density, and s i Let (ξ, η, ζ) be the cross-section of the i-th finite-length triangular prism, (ξ, η, ζ) be the coordinates of a volume element within the finite-length triangular prism, and n be the number of polygons (cross-sections). η1 and η2 are the Y-coordinates of the cross-sections at the two ends of the finite-length triangular prism. Figure 9 (Y1, Y2), δg i Let denot be the theoretical gravity anomaly generated by the i-th finite-length triangular prism, and let Δg be the theoretical gravity anomaly generated by the prism with a polygonal cross-section.

[0094] Based on this, the constant density σ is replaced by a fitting formula for the change of borehole rock density with depth. In this case, a polynomial fitting is used, that is, the density of volcanic rock is:

[0095] σ=a+bh+ch 2 +dh 3 +eh 4 +...

[0096] Substituting this into the above gravity forward model, we get: Where h represents the depth of volcanic rock. Considering the density variation, the depth h of volcanic rock is divided into four intervals: 0-200m, 200-300m, 300-400m, and 400m and below. a = 2.4880578; b = -0.0008616964; c = -7.603712e-007; d = -1.5677937e-0101; e = 1.7057553e-014.

[0097] Step 108: Based on the gravity data, magnetic data, electrical data and seismic exploration data of the study area, construct the distribution model of various geological bodies other than volcanic rocks on each profile, building upon the existing volcanic rock distribution model.

[0098] Based on the multi-section characterization of volcanic rock distribution, and using gravity data, magnetic data, electrical data, and seismic exploration data (a combination of multiple geophysical data, meaning the inferred geological model must not only conform to the understanding of surface geology and boreholes, but also to the geological characteristics reflected by gravity, magnetism, and seismic activity, which inevitably improves the accuracy of exploration), comprehensive geophysical modeling and forward and inverse models are carried out to infer the distribution characteristics of other geological bodies in each section.

[0099] 1. Import profile data using gravity, magnetoelectricity, and forward modeling software. Figure 6 center solid line, Figure 6 The horizontal axis represents distance; the vertical axis represents gravity amplitude, including gravity data, magnetic data, and seismic data (such as...). Figure 7 )wait.

[0100] 2. Construct a geological model with a polygonal cross-section (e.g., Figure 9 ), its cross-section (such as Figure 10 By editing the vertices, one can approximate the shapes of various geological bodies.

[0101] 3. Assign physical properties to the geological body, such as density, and perform forward modeling using formulas to obtain the theoretical gravity anomaly caused by the geological body. Figure 6 (middle dashed line).

[0102] 4. Compare the theoretical gravity anomaly with the imported gravity anomaly. If the values ​​and changes of the two are basically consistent and the fitting error is less than 5%, then the anomaly is considered to be caused by the constructed geological body (e.g., Figure 8 , where the horizontal axis represents distance and the vertical axis represents depth, ), otherwise adjust the shape of the geological body until the fitting error meets the requirements. Figure 8 In the middle, F represents a fracture, and F1 represents the number of one of the fractures.

[0103] Step 108: Determine the spatial distribution characteristics of volcanic rocks and other geological bodies on multiple cross-sections (e.g., Figure 11 Using complex structural modeling techniques, spatial distribution models of volcanic rocks and other geological bodies are constructed, such as... Figure 12 ,13.

[0104] Complete the forward and inverse modeling of multiple full cross sections, such as... Figure 11 The distribution of volcanic rocks and other geological formations can be seen in the cross-section.

[0105] Based on spatial data of volcanic rock distribution across multiple profiles, a spatial distribution model of volcanic rocks is constructed (e.g., Figure 12 ), while constructing models of other geological bodies (such as Figure 13 ), serving basic geological research and mineral exploration.

[0106] What specific data are included in the spatial data of volcanic rock distribution across multiple profiles?

[0107] The main data consists of the planar coordinates and top and bottom depths of the corresponding geological bodies on each profile.

[0108] The steps for constructing the spatial distribution model of volcanic rocks and the geological model beneath them are as follows:

[0109] 1. Import the profile data into the 3D modeling software.

[0110] 2. Display the spatial distribution and modification of data.

[0111] 3. Model construction is carried out using complex structural modeling techniques.

[0112] 4. If the model is unreasonable, find the corresponding profile data and modify it. Then repeat the above steps until it is completed.

[0113] Step 109: Based on the spatial distribution characteristics of volcanic rocks on each profile and the spatial distribution models of various geological bodies other than volcanic rocks, determine the spatial distribution models of various types of geological bodies in the study area.

[0114] Step 1010: Conduct mineral exploration in the study area based on the spatial distribution model of various geological bodies.

[0115] The traditional forward and inverse modeling steps are as follows: First, based on the profile location, extract geophysical data such as gravity data, as well as surface geological and borehole data. Second, construct an initial model. The initial model is controlled by surface geological and borehole results. Third, based on the initial model, guided by geological theory, and according to the distribution characteristics of geophysical data (including gravity, magnetic, electrical, and seismic data), inferences and interpretations are made to construct a polygonal geological model whose cross-section can approximate various geological body morphologies. Fourth, assign varying physical property parameters to the inferred geological model, perform forward modeling using gravity, magnetic, and electrical methods, and analyze the relationship between the forward modeling results and the measured data. If the fitting error is less than 5%, the anomaly is considered to indicate that the constructed geological model conforms to geological and geophysical distribution laws, thus completing the process. This is essentially a model verification. The main difference in the variable density modeling and inverse modeling of this invention lies in the fourth step mentioned above. Previously, the same density was assigned to each individual geological body. This variable density method is based on the obtained density variation pattern with depth. The single geological body of volcanic rock is divided into multiple layers according to the sampling distance or density variation pattern of physical property samples in the borehole. Each layer is assigned a density, and gravity forward modeling is carried out to greatly improve the identification accuracy.

[0116] Example 2

[0117] In order to implement the method corresponding to Embodiment 1 above and achieve the corresponding functions and technical effects, a mineral exploration system based on the spatial distribution identification of volcanic rocks is provided below, including:

[0118] The volcanic rock density value acquisition module is used to obtain the volcanic rock density value at different depths of each borehole in the study area.

[0119] The volcanic rock depth-density variation curve determination module is used to fit the volcanic rock density values ​​at different depths in multiple boreholes to obtain the volcanic rock depth-density variation curve of the study area.

[0120] The volcanic rock distribution point burial depth determination module is used to determine the depth of the boundary between volcanic rocks and intrusive rocks in each borehole within the study area as the burial depth of the volcanic rock distribution point in the corresponding borehole.

[0121] The gravity data acquisition module is used to acquire gravity data within the study area.

[0122] The Residual Gravity Anomaly Module is used to extract residual gravity anomalies from gravity data.

[0123] The residual gravity anomaly determination module is used to determine the residual gravity anomaly value caused by volcanic rocks based on the burial depth of the volcanic rock distribution point and the residual gravity anomaly, using the correspondence between the burial depth of the volcanic rock distribution point and the residual gravity anomaly.

[0124] The volcanic rock profile distribution characteristic determination module is used to perform multi-profile variable density volcanic rock modeling and forward and inverse modeling under borehole constraints based on the volcanic rock depth-density variation curve, the correspondence between volcanic rock distribution and residual gravity anomaly, and the residual gravity anomaly value caused by volcanic rocks, combined with the surface geology of the study area, to determine the volcanic rock distribution characteristics on each profile.

[0125] The module for determining the distribution model of multiple geological bodies other than volcanic rocks is used to construct the distribution model of multiple geological bodies other than volcanic rocks on each profile based on gravity data, magnetic data, electrical data and seismic exploration data of the study area, after the volcanic rock distribution has been constructed.

[0126] The module for determining the spatial distribution model of various geological bodies is used to determine the spatial distribution model of various geological bodies in the study area based on the distribution characteristics of volcanic rocks on each profile and the distribution model of various geological bodies other than volcanic rocks.

[0127] The mineral exploration module is used to conduct mineral exploration in the study area based on spatial distribution models of various types of geological bodies.

[0128] Example 3

[0129] This embodiment provides an electronic device, including a memory and a processor. The memory stores a computer program, and the processor runs the computer program to enable the electronic device to perform a mineral exploration method based on the spatial distribution identification of volcanic rocks as described in Embodiment 1. The memory is a readable storage medium.

[0130] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0131] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for prospecting based on volcanic rock spatial distribution recognition, characterized in that, The method comprises the following steps: obtaining the density values of the volcanic rock at different depths in each drill hole in the study area; fitting the volcanic rock depth-density variation curve of the study area according to the density values of the volcanic rock at different depths in multiple drill holes; determining the depth of the boundary point between the volcanic rock and the intrusive rock in each drill hole in the study area as the volcanic rock distribution point burial depth of the corresponding drill hole; obtaining the gravity data in the study area; extracting the residual gravity anomaly values in the gravity data; determining the residual gravity anomaly values caused by the volcanic rock according to the volcanic rock distribution point burial depth and the residual gravity anomaly, and using the volcanic rock distribution-residual gravity anomaly correspondence relationship; based on the volcanic rock depth-density variation curve, the volcanic rock distribution-residual gravity anomaly correspondence relationship and the residual gravity anomaly values caused by the volcanic rock, combining the surface geology of the study area, performing multi-profile variable-density volcanic rock modeling and forward-inversion work under drill hole constraints, and determining the volcanic rock distribution characteristics on each profile; based on the gravity data, the magnetic method data, the electrical method data and the seismic exploration data in the study area, constructing the volcanic rock distribution on each profile, and constructing the distribution model of multiple geological bodies on each profile except the volcanic rock; determining the spatial distribution model of multiple types of geological bodies in the study area according to the spatial distribution characteristics of the volcanic rock on each profile and the spatial distribution model of multiple geological bodies except the volcanic rock; performing ore prospecting work in the study area according to the spatial distribution model of multiple types of geological bodies.

2. The method according to claim 1, characterized in that, According to the volcanic rock distribution point burial depth and the residual gravity anomaly, the residual gravity anomaly values caused by the volcanic rock are determined by using the volcanic rock distribution-residual gravity anomaly correspondence relationship, which comprises the following steps: determining any drill hole as a current drill hole; determining any adjacent drill hole of the current drill hole as a current adjacent drill hole; determining the residual gravity anomaly value variation amplitude between the current drill hole and the current adjacent drill hole according to the residual gravity anomaly; determining the volcanic rock burial depth variation amplitude between the current drill hole and the current adjacent drill hole; determining whether the residual gravity anomaly values of the current drill hole and the current adjacent drill hole satisfy the volcanic rock distribution-residual gravity anomaly correspondence relationship according to the volcanic rock burial depth variation amplitude and the residual gravity anomaly value variation amplitude, and obtaining a judgment result; if the judgment result is yes, it is determined that the current extracted residual gravity anomaly value is caused by the volcanic rock.

3. The method according to claim 2, characterized in that, After determining that the current extracted residual gravity anomaly value is caused by the volcanic rock, the method further comprises the following steps: if the current extracted residual gravity anomaly value does not satisfy the volcanic rock distribution-residual gravity anomaly correspondence relationship, returning to the step of extracting the residual gravity anomaly values in the gravity data.

4. The method according to claim 1, characterized in that, The volcanic rock distribution-residual gravity anomaly correspondence is: ; wherein, is a variation amplitude of the residual gravity anomaly value at the position of the two adjacent drill holes; is a distance between the two adjacent drill holes; is a proportional coefficient; is a variation amplitude of the volcanic rock buried depth between the two adjacent drill holes; the volcanic rock distribution and the residual gravity anomaly between the multiple adjacent drill holes satisfy the volcanic rock distribution-residual gravity anomaly correspondence.

5. A prospecting system based on volcanic rock spatial distribution recognition, characterized in that, The method comprises the following steps: a volcanic rock density value obtaining module is configured to obtain the density values of the volcanic rock at different depths in each drill hole in the study area; a volcanic rock depth-density variation curve determining module is configured to fit the volcanic rock depth-density variation curve of the study area according to the density values of the volcanic rock at different depths in multiple drill holes; a volcanic rock distribution point burial depth determining module is configured to determine the depth of the boundary point between the volcanic rock and the intrusive rock in each drill hole in the study area as the volcanic rock distribution point burial depth of the corresponding drill hole; a gravity data obtaining module is configured to obtain the gravity data in the study area; a residual gravity anomaly value module configured to extract residual gravity anomaly values from the gravity data; a residual gravity anomaly value cause determination module configured to determine residual gravity anomaly values caused by volcanic rocks based on the depths of volcanic rock distribution points and the residual gravity anomalies by using a depth of volcanic rock distribution point-residual gravity anomaly correspondence relationship; a volcanic rock profile distribution feature determination module configured to determine volcanic rock distribution features on each profile by combining multi-profile variable density volcanic rock modeling and forward and inverse work under borehole constraints based on the volcanic rock depth-density variation curve, the volcanic rock distribution-residual gravity anomaly correspondence relationship, and the residual gravity anomaly values caused by volcanic rocks, and in combination with the surface geology of the study area; a model of distribution of geological bodies other than the volcanic rocks on each profile determination module configured to construct a model of distribution of geological bodies other than the volcanic rocks on each profile based on gravity data, magnetic data, electrical data, and seismic exploration data of the study area, on the basis of the construction of the volcanic rock distribution on each profile; a spatial distribution model of various types of geological bodies determination module configured to determine a spatial distribution model of various types of geological bodies in the study area based on the volcanic rock distribution features on each profile and the model of distribution of geological bodies other than the volcanic rocks on each profile; a prospecting module configured to perform prospecting work in the study area based on the spatial distribution model of various types of geological bodies.

6. An electronic device, comprising: An electronic device comprising a memory and a processor, the memory being configured to store a computer program, and the processor being configured to execute the computer program to cause the electronic device to perform a method for prospecting based on volcanic rock spatial distribution identification according to any one of claims 1 to 4. The memory is a readable storage medium.

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