1237 results about "Petrology" patented technology

The invention belongs to the technical field of mineral exploration, and particularly discloses a copper ore prospecting method based on three-dimensional geological modeling. The method comprises the following steps: acquiring geological data of a target area; after extreme values in the geological data are recognized and removed through a box plot, the geological data are mapped to an interval of [0, 1], and the geological data are divided into terrain data, stratum data and mineral resource data; adopting Kalman filtering to enable the data to form fusion data, and generating a thematic map comprising a geological map, a mineralization anomaly map and a topographic slope map; based on the data and the thematic map, constructing a three-dimensional geologic model by a finite element method, and performing mining path planning by adopting a specific path planning algorithm formula; exploring by the mining equipment according to the planned path, acquiring geological data, comparing the geological data with the predicted data, re-planning the path and continuing exploring if the path is blocked, the resource recovery is out of tolerance and new mineralization is abnormal, otherwise continuing exploring according to the planned path. The method has the advantages of being high in exploration efficiency and data precision, low in comprehensive cost and high in adaptability.

The invention provides a cement paste system with high strength, elasticity and toughness and application of the cement paste system in deep coal bed gas horizontal well cementation, and the cement paste system is prepared from the following raw materials in parts by mass: 40-70 parts of oil well cement, 13-40 parts of fly ash, 15-45 parts of slag, 5.0-20.0 parts of water-based organic silicon resin, 0.1-0.5 part of ultra-high performance polyethylene fiber, 3.0-8.0 parts of calcium oxide and 2.0-5.0 parts of calcium sulfate whisker. 1.0-8.0 parts of nano silicon dioxide, 1.0-6.0 parts of a fluid loss agent, 0.5-2.0 parts of a drag reducer, 0.2-1 part of a defoaming agent and 50-80 parts of water. The cement paste system disclosed by the invention has the characteristics of remarkable low-temperature quick setting and high early strength, also has the advantages of low water loss, controllable thickening, simple preparation operation and the like, and set cement is high in compressive strength, high in breaking strength and very excellent in elastic and tough mechanical properties.

The invention provides an ore leaching property analysis method, and belongs to the field of process mineralogy, and the method comprises the following steps: taking a to-be-detected sample, carrying out ore grinding treatment, and carrying out ore washing and desliming to obtain a pretreated sample; mixing the pretreated sample with graphite to prepare an automatic mineralogical analysis sample, measuring the content of a target mineral and the content of a target element through automatic mineralogical analysis, and calculating the average content of the target mineral; adding an agent into the pretreated sample to carry out leaching reaction, carrying out solid-liquid separation to obtain mineral residues, and calculating the mass ratio of the mineral residues to the pretreated sample before reaction; mixing mineral residues with graphite to prepare an automatic mineralogical analysis sample, analyzing the sample, measuring the content of residual target minerals and the content of residual target elements, and calculating the average content of the residual target minerals; and calculating a mineral leaching coefficient and an ore leaching coefficient based on the obtained data. The in-situ leaching recovery rate prediction method based on mineralogical analysis is suitable for development and evaluation of low-grade and complex ore bodies.

The invention relates to the technical field of reservoir numerical simulation, and discloses a polymer flooding reservoir rapid simulation optimization method considering sedimentary facies constraints, which comprises the following steps: identifying sedimentary facies boundaries according to distribution characteristics of sedimentary facies, and establishing a connected network model considering the sedimentary facies constraints on the basis of the sedimentary facies boundaries, well positions and various sedimentary facies attributes; carrying out one-dimensional grid division on the connected network model, converting the connected network model into a grid connection format of a universal simulator, and solving the connected network model by adopting the universal simulator to obtain pressure and saturation solutions; establishing an automatic historical fitting mathematical model based on sedimentary facies and oil reservoir constraint conditions; the economic net present value is used as an index, the water injection rate, the liquid production rate and the polymer injection rate of each well are used as optimization variables, the differential evolution algorithm is used, the total polymer injection amount and the oil reservoir pressure are restrained, and an oil reservoir injection and production optimization mathematical model is established. According to the method, the oil reservoir is optimized by comprehensively considering the characteristics of the oil reservoir after water flooding is converted into polymer flooding, so that rapid decision-making of the oil field and guidance of oil field construction are realized.

The invention relates to the technical field of oil and gas geological exploration, in particular to an over-mature hydrocarbon source rock parent material type distinguishing method and system.The method comprises the following steps that regional deposition characteristics are studied, an over-mature hydrocarbon source rock deposition environment is recognized, principal elements and microelements are extracted in combination with a geological background, and component relevance is judged; and sorting representative sedimentary environment elements, and establishing a sedimentary environment associated element set. According to the method, accurate recognition of the sedimentary environment is achieved by extracting major elements and trace elements, representative elements are screened, proportional analysis is combined with the macerals, distribution characteristics of saprolite groups, exinite groups and the like are determined, the ratio relation between the macerals and inorganic elements is recognized, a ratio operation set is constructed, and the relation between the macerals and the elements is analyzed in a multi-dimensional mode. The relationship between parent material types and maceral characteristics is disclosed, a maceral type index model is constructed, hydrocarbon source rock parent material type division precision and sedimentary environment analysis systematicness are improved, and a scientific basis is provided for oil and gas resource exploration.

The invention discloses an intelligent analysis method for geomechanical conditions of coal seam surrounding rocks, and belongs to the field of intelligent analysis of the geomechanical conditions of the coal seam surrounding rocks. The intelligent analysis method comprises the following steps: performing time sequence matching processing on historical geological data and real-time monitoring information by adopting a dynamic data integration technology according to a preliminary integration result of multi-source data; determining a unified feature set after multi-source data fusion; acquiring geomechanical condition related data of the unmined area according to the initial prediction model parameters, and performing simulation analysis on the surrounding rock stability to obtain stability prediction distribution of the unmined area; according to the stability prediction distribution of the unmined area, combining a dynamic data integration result, carrying out local correction on the prediction distribution, and determining a final stability prediction result; and for a final stability prediction result, generating a geomechanical condition risk distribution diagram of the unmined area through an intelligent prediction technology, obtaining distribution characteristics of a potential risk area, and completing output of a prediction model.

The invention discloses a deep anisotropic coal and rock mass in-situ stress recovery test method. The method comprises the following steps: step 1, preparing an anisotropic coal and rock mass sample; 2, carrying out an initial stress loading test; step 3, stress recovery test; and step 4, construction of a deep coal and rock mass anisotropy mechanical model. The method can solve the problem that the anisotropic characteristics and in-situ stress recovery process of the deep coal and rock mass cannot be accurately simulated in the prior art, and can accurately restore the mechanical behaviors of the deep coal and rock mass under different stress paths by combining an indoor test and a numerical simulation technology. And a scientific basis is provided for deep mine engineering design and disaster prevention and control.

The invention discloses a dust raising prevention sampling device and method for geological mineral exploration, and particularly relates to the technical field of geological exploration, the device comprises a drilling assembly, a drilling pipe assembly, a sampling inner pipe and an extraction rod, the drilling assembly comprises a drilling machine and a feeding driving frame, the drilling pipe assembly comprises a section of primary drilling pipe and a plurality of sections of secondary drilling pipes, the sampling inner pipe is arranged in the primary drill pipe, a plurality of groups of elastic pressing strips are arranged at the bottom end of the sampling inner pipe, and a tightening controller is further arranged on the outer side of the bottom of the sampling inner pipe. When the sampling inner pipe is lifted, the tightening controller extrudes the bottom end areas of the elastic pressing strips, so that all the elastic pressing strips are bent and deformed inwards, a soil sample entering the sampling inner pipe is extruded to a certain extent, and the carrying capacity of the soil sample is improved; furthermore, the soil sample in the sampling inner pipe can be effectively taken out when the sampling inner pipe ascends, and the sampling integrity and accuracy are greatly improved.

The present invention belongs to the technical field of oil and gas engineering. Disclosed are an artificially-assisted packing method for sand control and water control in a fractured reservoir, and a packing effect evaluation method. The artificially-assisted packing method for sand control and water control in a fractured reservoir comprises the following steps: S11, calculating a fracture occurrence evaluation index F for a fractured reservoir; S12, calculating an artificially-assisted packing process implementation feasibility index G; and S13, on the basis of the fracture occurrence evaluation index F obtained in step S11 and the artificially-assisted packing process implementation feasibility index G obtained in step S12, selecting one of a natural micro-saturated packing process, an artificially-assisted squeezing supersaturated packing process and an artificially-assisted fracturing strong-saturated packing process for packing. By means of the packing method in the present invention, an appropriate packing mode is correspondingly selected on the basis of the structure of a natural fracture in a reservoir, and the matching degree between the natural fracture and an available proppant, thereby "making the remedy suit the case" and effectively ensuring the effect of sand control and water control.

The invention provides a method for measuring a structure coefficient, and belongs to the field of process mineralogy, and the method comprises the following steps: selecting a representative ore sample, and preparing an automatic mineralogy analysis sample; performing automatic mineralogical analysis on the automatic mineralogical analysis sample, measuring the area of a target mineral and the content of a target element, and calculating a structural distribution coefficient, an edge structural distribution coefficient and a far-end structural content of the target mineral in combination with the density of the target mineral; and based on the target mineral structure content, the edge structure content and the far-end structure content, a target mineral structure coefficient, an edge structure coefficient and a far-end structure coefficient are calculated respectively, and an ore structure coefficient is obtained through weighted summation. According to the method, a special calculation method is set, the structural characteristics of the ore are comprehensively represented by the target mineral structure, the edge structure and the far-end structure, and the structural characteristics of the ore can be measured; through analysis of ore characteristic structures, structure coefficients are calculated so as to represent the influence of the structures on the permeability of the ore.

A deep learning-based rock microcrack identification and detection method belongs to the technical field of rock microcrack detection and identification in geological resources and geological engineering, and greatly improves the detection precision of rock microcracks by integrating a multi-scale feature pre-extraction module (MFP), an encoder space cascade coding path (ESCE) and a decoder input SE module. The conditions of false detection and missing detection are reduced, and the precision and the stability of micro-crack detection in the rock are remarkably improved. According to the method, through a reasonably designed network structure, the calculation amount of the network is reduced, the detection process is made to be more lightweight, and the method is suitable for rapid processing and real-time application of a large-scale data set. According to the method, the requirement for manual participation is greatly reduced, automatic detection and classification of the microcracks in the rock are achieved through the deep learning algorithm, the reliability and efficiency of rock integrity and mechanical property evaluation are improved, and the method has wide geological engineering application prospects.

The invention discloses a deep shale brittleness evaluation method based on energy evolution, electronic equipment and a medium. The method comprises the following steps: collecting basic parameters of a target stratum, and determining key parameters; carrying out a total stress-strain triaxial compression experiment according to the key parameters to obtain a total stress-strain curve of the rock core; dividing the total stress-strain curve, and respectively calculating the strain energy density related to the rock; and calculating the mineral brittleness index of the rock according to the key parameters and the strain energy density. According to the method, mineral components and energy evolution in the whole rock deformation-damage process are considered at the same time, and the brittleness characteristics of deep shale can be better reflected.

The invention discloses a water-rich composite stratum tunnel surrounding rock deformation identification method, and relates to the technical field of tunnel engineering, and the method comprises the following steps: collecting stratum information and hydrological data in a geological exploration stage, and on-site monitoring data in a construction stage, carrying out the cleaning and normalization processing of the data, constructing a training set of a random forest model, and carrying out the recognition of the deformation of the tunnel surrounding rock. Training a random forest model by using the training set to obtain a trained surrounding rock deformation classification model; and by means of the trained surrounding rock deformation classification model, current to-be-identified surrounding rock data are analyzed, first deformation data are obtained, and the first deformation data represent the preliminary tendency of surrounding rock deformation. Through the strong classification capability of the random forest model, the preliminary judgment of the surrounding rock deformation tendency is realized, the judgment accuracy and efficiency are improved, the weighted scoring method and the Bayesian network algorithm are adopted to carry out preliminary judgment and detailed judgment, the multi-source data are effectively integrated, and the judgment precision is improved.

The invention discloses a compact glutenite reservoir evaluation method based on a lithofacies-pore throat structure and application. The method comprises the following steps: step 1, establishing a lithofacies division scheme in a compact glutenite reservoir; 2, determining the reservoir performance of different lithofacies in the compact glutenite reservoir; 3, determining reservoir space types and features of different lithofacies in the compact glutenite reservoir; 4, analyzing pore throat structure characteristics of different lithofacies in the compact glutenite reservoir to obtain multi-type pore throat structure parameters; 5, establishing a reservoir performance and pore throat structure parameter database of different lithofacies in the compact glutenite reservoir; step 6, carrying out compact glutenite reservoir clustering by utilizing a Ward system clustering method; and step 7, in combination with productivity conditions and physical characteristics of different lithofacies in the compact glutenite reservoir, proofreading and perfecting a reservoir clustering result, and finally establishing a compact glutenite reservoir classification evaluation scheme. The invention further discloses application of the method in oil exploitation.

The invention discloses a horizontal well injection-vertical well extraction well pattern arrangement and mining method for in-situ leaching uranium mining, and relates to the field of mining engineering. The main method for arranging the well pattern comprises the steps that a horizontal liquid injection well is arranged in the middle of an ore bed in the trend of the ore bed, vertical liquid pumping wells with the same number are arranged on the two sides of the horizontal liquid injection well, the distances between the adjacent vertical liquid pumping wells on the same side of the horizontal liquid injection well are equal, and the vertical distances between the vertical liquid pumping wells and the horizontal liquid injection well are equal and are half of the distances between the adjacent vertical liquid pumping wells; the horizontal distance between the peripheral vertical liquid extraction wells and the end point of the horizontal well is half of the distance between every two adjacent vertical liquid extraction wells, and a similar determinant arrangement is formed. The mining method can overcome the defects of extraction and injection of traditional vertical liquid extraction wells, the leaching range of in-situ leaching uranium mining is expanded, and the leaching efficiency of in-situ leaching uranium mining is improved. Uranium mine mining nonuniformity caused by nonuniform flow distribution of the leaching liquid is reduced, and the uranium mine mining efficiency and the resource utilization rate are improved.

The invention discloses a natural caving method-based mining ore rock caving simulation system and method, relates to the technical field of ore rock caving simulation, and aims to solve the problems that the traditional ore rock caving simulation only focuses on acquisition of macroscopic geological data and rock mechanical parameters in the aspect of data acquisition, and the existing simulation system only focuses on acquisition of macroscopic geological data and rock mechanical parameters in the aspect of analysis methods during microstructure analysis. The algorithm is relatively single and rough, so that the simulation result cannot accurately reflect the real caving condition of the ore rock in the actual mining process. According to the invention, the data acquisition module comprehensively acquires macro and micro data and scientifically processes the macro and micro data, the microstructure analysis module accurately analyzes a microstructure by using multiple advanced algorithms and constructs a prediction model, the macro mechanical analysis module combines multiple algorithms to accurately analyze mechanical behaviors, and the data fusion calculation module ingeniously fuses the data to improve the prediction accuracy. Mining risks are effectively reduced, and safe and efficient mining operation is guaranteed.

The invention relates to the technical field of mineral exploration, and discloses a method for determining a heat source center of a gold and copper ore area containing alunite minerals, which comprises the following steps of: determining a to-be-detected area of a target mining area, sampling surface rocks according to a preset grid or section, and acquiring a plurality of rock samples and corresponding original acquisition points; carrying out mineral component analysis on the plurality of rock samples, screening the alunite-containing samples to obtain a plurality of alunite-containing samples, and screening effective samples; performing elemental component analysis on the effective sample, and extracting elements and contents related to gold mineralization or copper mineralization in the effective sample; setting a potential heat source center, calculating the distance between each effective sample and the potential heat source center, introducing a distance attenuation index, establishing an objective function of the element content and the distance, and adopting a gradient descent method to perform inversion solution by minimizing the objective function to obtain coordinates of the potential heat source center, namely the determined heat source center of the gold ore or the copper ore; the method improves the accuracy of gold and copper ore area heat source center exploration.

The invention discloses a compressed air energy storage underground lining cavern optimization design method and system, and belongs to the technical field of compressed air energy storage. The method comprises the steps that numerical simulation is conducted according to obtained rock mass parameters and given structural design parameters of the compressed air energy storage underground lining cavern, and the burial depth range of the compressed air energy storage underground lining cavern is determined; according to the buried depth range of the compressed air energy storage underground lining cavern, physical and mechanical parameters of surrounding rock of the stratum where the cavern is located are determined, and the load borne by the compressed air energy storage underground lining cavern structure is calculated; according to the load borne under the compressed air energy storage underground lining cavern structure, the limit burial depth of the compressed air energy storage underground lining cavern is obtained based on a limit equilibrium analysis method; and carrying out stability analysis on the limit burial depth of the compressed air energy storage underground lining cavern. According to the method, through steel lining-concrete lining-surrounding rock collaborative bearing mechanism analysis, inter-structure load distribution is quantified, the conservative property of traditional burial depth design is broken through, and stability optimization of the cavern is achieved.

The invention provides a method for predicting ground subsidence caused by ground stress change in geothermal exploitation, which comprises the following steps: collecting geological survey data of a target geothermal exploitation area, and constructing a three-dimensional geomechanical model; based on the constructed three-dimensional geomechanical model, simulating crustal stress evolution processes in different mining stages by adopting a numerical simulation method to obtain crustal stress tensor time sequence change data; inputting the crustal stress tensor time sequence change data into a three-dimensional geomechanical model as a boundary condition, and calculating the deformation of each rock stratum in the vertical direction to obtain a ground surface settlement estimated value; constructing a crustal stress-settlement prediction model based on the nonlinear mapping relationship between the crustal stress tensor time sequence change data and the settlement estimated value, and training; and inputting subsequent terrestrial heat exploitation scheme parameters, and predicting a future ground surface settlement trend by using the trained ground stress-settlement prediction model. The method is wide in application range and can be suitable for ground subsidence prediction of the geothermal exploitation area under different geological conditions.

The invention relates to a lithium ore prospecting prediction method and system, and relates to the technical field of mineral exploration. According to the lithium ore prospecting prediction method and system, the prediction accuracy of ore body identification is high, the exploration period can be shortened, and the exploration cost can be reduced. According to the method, the multi-dimensional data fusion is combined with the intelligent algorithm, the three-dimensional mineralization probability is output through the prediction neural network model, the prediction accuracy of ore body recognition is high, the exploration period can be shortened, and the exploration cost can be reduced.

The invention relates to the technical field of in-situ leaching mining of low-permeability sandstone type uranium ore, in particular to a prediction method for the in-situ leaching effect of the low-permeability sandstone type uranium ore. And constructing a single-hole blasting physical model, and simulating the change of the radiuses of the crushed region and the fractured region of the uranium mine by updating a non-coupling coefficient. Thirdly, constructing a multi-physics field coupling model, including a geometric model, rock parameter definition, initial and boundary condition setting, introduction of a fracture geometric model, and simulation of in-situ leaching uranium concentration and uranium recovery rate change curves after blasting permeation enhancement; the multi-physical field model covers a dilute material transfer field, a Darcy seepage field and a chemical field. And based on the uncoupling coefficients corresponding to the uranium concentration and the uranium recovery rate peak value, determining the optimal uncoupling coefficient, further constructing an HJC field scale blasting model, adjusting blasting parameters, and optimizing the uranium mine crack expansion condition and the in-situ leaching effect. And finally, in combination with the optimal blasting parameter, analyzing the influence of different in-situ leaching parameters on the in-situ leaching process, and optimizing the reaction rate, so that the whole process optimization is realized, and the in-situ leaching efficiency is improved.

The invention belongs to the technical field of vanadium enrichment mechanisms of phosphorus vanadium ores, and discloses a research method of a vanadium enrichment mechanism in a diagenetic stage of phosphorus vanadium ores, which comprises the following steps: S1, sample collection and treatment; s2, rock ore identification and mineral composition analysis; s3, analyzing the occurrence state and microcell morphology of vanadium; s4, performing geochemical analysis on the whole rock; s5, in-situ microcell geochemical analysis is carried out; s6, phosphorus nodule analysis; s7, comprehensive analysis and mineralization model establishment; according to the method, mineralogy, total rock geochemistry, micro-area surface scanning and other multi-scale and multi-means research methods are comprehensively utilized, and the vanadium occurrence state, the ore-forming fluid evolution and the phosphorus-vanadium coupling relation are finely described; in-situ microcell geochemical analysis is introduced into phosphorus nodule analysis, the internal structure, the growth sequence and element distribution of the phosphorus nodule are directly revealed, obvious frontier and systematicness are achieved, and reliable theoretical support is provided for accurate exploration of vanadium ore resources and green and efficient dressing and smelting process research and development.

The invention discloses a fracture-vug type carbonate rock fracture-vug reservoir reasoning method and device based on a knowledge graph. The device comprises an ontology construction module, a knowledge extraction module, a knowledge fusion module, a business rule module, a reasoning model module and a reservoir comprehensive evaluation model. Wherein the business rules comprise an oil reservoir analysis rule, a reservoir physical property rule, a logging interpretation rule and the like, the calculation model is a carbonate reservoir comprehensive reasoning model, and comprehensive reasoning analysis is performed on each fracture-cavity reservoir by combining the business rules of the business rule module with a carbonate fracture-cavity reservoir comprehensive reasoning method. And generating a carbonate rock fracture-cavity reservoir optimization scheme. According to the method, the exploration target optimization working efficiency of the carbonate fractured-vuggy reservoir can be improved, the pertinence, accuracy and timeliness of exploration decision making are improved, the exploration risk is reduced, and the decision making efficiency is improved.

The invention relates to the technical field of oil-gas exploration, in particular to a hydrocarbon generation potential evaluation method for marine hydrocarbon source rocks. On the basis of determining terrestrial source and sea source organic matter proportions of marine facies hydrocarbon source rocks in different sedimentary areas, marine facies hydrocarbon source rock thermal simulation experiments of different terrestrial source / sea source organic matter proportions are carried out, and gaseous hydrocarbon yields of the marine facies hydrocarbon source rocks of different terrestrial source / sea source organic matter proportions and isotope characteristics and activation energy of gaseous hydrocarbons of different maturity degrees are determined; according to generation, storage and cover layer parameters of a research area, selecting a suitable model and giving suitable parameter values, performing numerical simulation on hydrocarbon source rocks with different terrestrial / sea source organic matter proportions, and finally quantitatively determining hydrocarbon generation potential of hydrocarbon source rocks with different sedimentary areas and different terrestrial / sea source organic matter proportions in the research area by combining burial-thermal history evolution of the research area. And obtaining a hydrocarbon generation and expulsion period and a charging process, and determining a main reservoir forming period. Compared with the prior art, the hydrocarbon generation potential evaluation accuracy of the marine hydrocarbon source rock can be greatly improved.

The invention belongs to the field of petroleum and natural gas engineering, particularly relates to a method and a system for converting XRF logging elements and mineral content, and aims to solve the problems of long time for judging the mineral content by XRD and low cost performance. The method comprises the steps that XRF logging element and XRD mineral content detection is conducted on a coring sample according to the well depth, and XRF logging element detection data and XRD mineral content detection data are obtained; classifying minerals corresponding to the coring samples to obtain mineral types, extracting elements of the mineral types, and screening the elements to obtain characteristic elements; performing linear regression analysis on the XRF logging element detection data corresponding to the characteristic elements and the XRD mineral content detection data corresponding to the characteristic elements to obtain mineral content models of different mineral types; and substituting XRF logging element data of any well depth into the model to obtain the mineral type content of the well depth. According to the method, the mineral type content can be judged according to the XRF logging elements.

Methods and systems are disclosed. The method may include obtaining a first plurality of hydrocarbon source rock samples from a first well and a second plurality of hydrocarbon source rock samples from a second well, each well penetrating a portion of a subterranean region. For each of the first and second plurality of samples obtaining a set of kinetic parameter values, including a discrete distribution of activation energy and a common frequency factor and determining a weighted average activation energy value from the distribution. The method may further include identifying a first chemostratigraphic segment of the first well and a second chemostratigraphic segment of the second well, each based on the weighted average activation values; determining a correlated stratigraphic unit and mapping organofacies based on the first the second chemostratigraphic segments; and predicting hydrocarbon generation, retention and expulsion and determining a drilling target within the correlated stratigraphic unit.

The invention discloses a mineral resource prediction model construction method based on a complex geological background, and relates to the technical field of mineral resource prediction, a three-dimensional ideal geological background field without mineralization interference is constructed based on the geological background of an unknown mining area, and the three-dimensional ideal geological background field is used for displaying the mining field of a non-mineralization area; constructing a three-dimensional real geological field based on the exploration data, and comparing the three-dimensional real geological field with the three-dimensional ideal geological background field to obtain first difference distribution data; extracting geologic features of the known mineralization area, and generating interference factors based on the geologic features; introducing the interference factor into the ideal geological background field to generate an interference coupling background field, and extracting the difference between the interference coupling background field and the ideal geological background field as second difference distribution data; the mineral resource prediction model is constructed based on the first difference distribution data and the second difference distribution data, the method can adapt to prediction requirements of different geological backgrounds, and the intelligent level and application flexibility of a mineral resource prediction system are remarkably improved.

The invention discloses a salt lake carbonate rock multi-parameter quantitative classification and reservoir evaluation method, and relates to the technical field of oil-gas exploration. The method comprises the following steps: selecting a key well in an exploration block, collecting a plurality of salt lake carbonate rock samples, preparing an analysis sample under an anhydrous condition, quantitatively measuring a salinity parameter, a mixing index and a diagenesis strength parameter by utilizing the analysis sample, and determining a salinity code, a mixing code and a diagenesis phase code. And naming the salt lake carbonate rock based on the salinity code, the mixed product code and the lithogenous phase code, directly evaluating the salt lake carbonate rock reservoir according to a naming result, and performing single well comprehensive evaluation on the salt lake carbonate rock reservoir. According to the method, the influence of salinity, mixed accumulation and diagenesis strength on formation and evolution of the salt lake carbonate rocks is fully considered, accurate division of the types of the salt lake carbonate rocks is achieved, the reservoir naming result is directly associated with reservoir evaluation, and technical support is provided for standardized evaluation of the salt lake carbonate reservoir.

The invention relates to the field of oil and gas field exploration and development, in particular to a shale oil dessert well logging evaluation method and device based on source-reservoir coupling characteristics, and the method comprises the steps: determining the reservoir quality according to the effective porosity and effective thickness of a shale oil reservoir in a research area; the effective porosity is greater than a preset porosity lower limit threshold; evaluating the quality of each hydrocarbon source rock stratum section according to the effective points of the total organic carbon content of the kerogen in the research area, the effective thickness of the layer section corresponding to each effective point and the total organic carbon content of the kerogen of the effective point; according to the coupling relation between the reservoir quality and the quality of the hydrocarbon source rock stratum section within the estimated longitudinal distance range of the position of the effective point of the total organic carbon content of the kerogen; according to the coupling relation, shale oil desserts within the longitudinal distance range are evaluated and estimated. On the basis of hydrocarbon source rock quality classification, reservoir quality classification and a source-reservoir coupling relationship, a foundation is laid for accurate classification evaluation of shale oil dessert development sections.

The present description relates to the field of oil and gas field exploration and development, and in particular, to a shale oil sweet spot logging evaluation method and apparatus based on source-reservoir coupling characteristics. The method comprises: on the basis of the effective porosity and effective thickness of a shale oil reservoir in a research area, determining reservoir quality, wherein the effective porosity is greater than a preset porosity lower threshold; on the basis of effective points of kerogen total organic carbon content in the research area, the effective thickness of an interval corresponding to each effective point, and the kerogen total organic carbon content of each effective point, evaluating the quality of source rock intervals; on the basis of an estimated longitudinal distance range of the positions where the effective points of kerogen total organic carbon content are located, determining a coupling relationship between the reservoir quality and the quality of the source rock intervals; and on the basis of the coupling relationship, evaluating a shale oil sweet spot within the estimated longitudinal distance range.