Comprehensive modeling of mineral potential mapping by integration of multiset geosciences data

This work has evaluated the functionality of various fuzzy-based fusion methods in the mineral potential mapping (MPM), by which a multi-criteria decision-making problem was solved to design a layout for drilling complementary boreholes through a comprehensive analysis of geospatial datasets. The novel methods employed were fuzzy c-means clustering, fuzzy gamma operator, fuzzy inference system (FIS), fuzzy outranking, and fuzzy ordered weighted averaging (FOWA). Kahang porphyry Cu-Mo deposit in the Isfahan province of Iran was chosen as a case study to examine the performance of these fuzzy methods in MPM. Extracted geospatial indicator layers for assessing the potential of porphyry-type mineralization were derived from four criteria, namely geology (rock units and faults), remote sensing (alteration map), geochemistry (Cu, Mo, and factor maps), and geophysics (reduced to the pole and analytical signal of magnetic data). The concentration-area multifractal method was utilized to reclassify each synthesized fuzzy favorability map into five classes. To appraise and compare the efficiency of each employed method, a productivity measure assumed as a cumulative summation of Cu grade multiplied by its thickness above an economical cut-off value of 0.2% was calculated along with each drilling (totally 33 ones). According to fuzzy favorability maps derived from running all fuzzy methods, the FIS and FOWA had the highest efficiency with 80 and 78% of accuracy, respectively. Eventually, taking all fuzzy maps into account led to the delineation of some new favorable zones, whereby further exploratory investigations are envisioned for determining their mining potential.     

Framework and modeling structure of Exploration and Mining Cadastre system in Iran

In this paper we introduce a framework for developing the Exploration and Mining Cadastre System (EMCS), which involves all activities related to exploration areas, including registration and subsequent legal issues in a broader sense. It is built with two main purposes in mind: (1) enable necessary surveys, observe applicant’s reserved parcel, register the parcel online, and issue and follow up necessary permits/licenses in the field of exploration, (2) provide a mutual platform for data exchange among various service systems in the field of exploration and mining in Iran. The EMCS model is designed in Unified Modeling Language (UML) with three main sets of classes: (1) RegisterObject (2) ActivityLicense, and (3) Person. Other relevant features of the model are also specified at the class level. These include: conditional registered parcels, unregisterable areas such as prohibited or protected areas, legal borders around registered or serving parcels, reference documents such as legal survey results documents, responsibilities, and restrictions. The model also considers issues related to exploration cost, parcel code, tax, royalty, commodity, priorities, facilitations, evaluation, transfer of ownership, changing parameters, and temporal registration. The temporal aspects of the classes are also supported by the model to take care of the time periods that involve the general procedures in the registration of exploration and mining properties. We anticipate that the framework and model structure provide a platform for data storage, improve the supervision of exploration and mining process, change manual into online registration system, prevent administrative corruption, and reduce bureaucracy.     

Multiple data-type processing as applied to the selection of areas with high gold potential in French Guyana

As part of the Guyana Shield, the basement rocks of French Guyana, between latitudes 3° and 3°30′N, consist of greenstones belts of Proterozoic age (2.0–2.1 Ga) enclosed by anatectic granitoïds and migmatites, and of acid or basic intrusives.     

Dynamic data integration for structural modeling: model screening approach using a distance-based model parameterization

This paper proposes a novel history-matching method where reservoir structure is inverted from dynamic fluid flow response. The proposed workflow consists of searching for models that match production history from a large set of prior structural model realizations. This prior set represents the reservoir structural uncertainty because of interpretation uncertainty on seismic sections. To make such a search effective, we introduce a parameter space defined with a “similarity distance” for accommodating this large set of realizations. The inverse solutions are found using a stochastic search method. Realistic reservoir examples are presented to prove the applicability of the proposed method.     

A hybrid AHP-VIKOR approach for prospectivity modeling of porphyry Cu deposits in the Varzaghan District,NW Iran

Identifying highly favorable areas related to a particular mineralization type is the main objective of mineral prospectivity modeling (MPM). The northwestern portion of Ahar-Arasbaran porphyry copper belt (AAPCB) is situated within the Urumieh-Dokhtar magmatic belt (UDMB). Because of owning many worthwhile Cu-Mo and Cu-Au porphyry deposits, this area is entitled to incorporate diverse spatial evidence layers for the MPM. In this paper, a hybrid AHP-VIKOR, as an improved knowledge-driven MPM procedure has been proposed for integration of various exploration evidence layers. For this, the AHP is used to calculate important weights of spatial criteria while the VIKOR is applied to outline ultimate prospectivity model. Six effective spatial evidence layers pertaining to the Varzaghan District are selected: (1) multi-elemental geochemical layer of Cu-Mo-Bi-Au; (2) remotely sensed data of argillic, phyllic, and iron oxide alteration layers; and (3) geological and structural layers of Oligo-Miocene intrusions and fault. In addition, a fuzzy prospectivity model (γ?=?0.9) is implemented to assess the AHP-VIKOR approach. Two credible validation methods comprising normalized density index and success rate curve are adapted for quantitative evaluation of predictive models and enhancing the probability of exploration success. The achieved results proved the higher accuracy of the AHP-VIKOR model compared with the fuzzy model in delimiting the favorable areas.     

The Anarak, Jandaq and Posht-e-Badam metamorphic complexes in central Iran: New geological data, relationships and tectonic implications

The Anarak, Jandaq and Posht-e-Badam metamorphic complexes occupy the NW part of the Central-East Iranian Microcontinent and are juxtaposed with the Great Kavir block and Sanandaj-Sirjan zone. Our recent findings redefine the origin of these complexes, so far attributed to the Precambrian–Early Paleozoic orogenic episodes, and now directly related to the tectonic evolution of the Paleo-Tethys Ocean. This tectonic evolution was initiated by Late Ordovician–Early Devonian rifting events and terminated in the Triassic by the Eocimmerian collision event due to the docking of the Cimmerian blocks with the Asiatic Turan block.

The “Variscan accretionary complex” is a new name we proposed for the most widely distributed metamorphic rocks connected to the Anarak and Jandaq complexes. This accretionary complex exposed from SW of Jandaq to the Anarak and Kabudan areas is a thick and fine grain siliciclastic sequence accompanied by marginal-sea ophiolitic remnants, including gabbro-basalts with a supra-subduction-geochemical signature. New ⁴⁰Ar/³⁹Ar ages are obtained as 333–320 Ma for the metamorphism of this sequence under greenschist to amphibolite facies. Moreover, the limy intercalations in the volcano-sedimentary part of this complex in Godar-e-Siah yielded Upper Devonian–Tournaisian conodonts. The northeastern part of this complex in the Jandaq area was intruded by 215 ± 15 Ma arc to collisional granite and pegmatites dated by ID-TIMS and its metamorphic rocks are characterized by some ⁴⁰Ar/³⁹Ar radiometric ages of 163–156 Ma.

The “Variscan” accretionary complex was northwardly accreted to the Airekan granitic terrane dated at 549 ± 15 Ma. Later, from the Late Carboniferous to Triassic, huge amounts of oceanic material were accreted to its southern side and penetrated by several seamounts such as the Anarak and Kabudan. This new period of accretion is supported by the 280–230 Ma ⁴⁰Ar/³⁹Ar ages for the Anarak mild high-pressure metamorphic rocks and a 262 Ma U–Pb age for the trondhjemite–rhyolite association of that area. The Triassic Bayazeh flysch filled the foreland basin during the final closure of the Paleo-Tethys Ocean and was partly deposited and/or thrusted onto the Cimmerian Yazd block.

The Paleo-Tethys magmatic arc products have been well-preserved in the Late Devonian–Carboniferous Godar-e-Siah intra-arc deposits and the Triassic Nakhlak fore-arc succession. On the passive margin of the Cimmerian block, in the Yazd region, the nearly continuous Upper Paleozoic platform-type deposition was totally interrupted during the Middle to Late Triassic. Local erosion, down to Lower Paleozoic levels, may be related to flexural bulge erosion. The platform was finally unconformably covered by Liassic continental molassic deposits of the Shemshak.

One of the extensional periods related to Neo-Tethyan back-arc rifting in Late Cretaceous time finally separated parts of the Eocimmerian collisional domain from the Eurasian Turan domain. The opening and closing of this new ocean, characterized by the Nain and Sabzevar ophiolitic mélanges, finally transported the Anarak–Jandaq composite terrane to Central Iran, accompanied by large scale rotation of the Central-East Iranian Microcontinent (CEIM). Due to many similarities between the Posht-e-Badam metamorphic complex and the Anarak–Jandaq composite terrane, the former could be part of the latter, if it was transported further south during Tertiary time.     

A comprehensive VIKOR method for integration of various exploratory data in mineral potential mapping

The central Iranian volcanic-sedimentary belt in Kerman province of Iran that is located within the Urumieh-Dokhtar magmatic arc zone is chosen to integrate diverse evidential layers for mineral potential mapping. The studied area has high potential of mineral occurrences especially porphyry copper, and the prepared potential maps aim to outline new prospect zones for further investigation. Two evidential layers including the downward continued map and the analytic signal of filtered magnetic data are generated to be used as geophysical plausible traces of porphyry copper occurrences. The low values of the resistivity layer acquired from airborne frequency domain electromagnetic data are also used as an electrical criterion in this study. Four remote sensing evidential layers including argillic, phyllic, propylitic, and hydroxyl alterations are extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images in order to map the altered areas associated with porphyry copper deposits. The Enhanced Thematic Mapper Plus (ETM+) images are used as well to prepare iron oxide layer. Since potassic alteration is generally the mainstay of copper ore mineralization, the airborne potassium radiometry data is used to explore both phyllic and potassic alteration. Finally, the geochemical layers of Cu/B/Pb/Zn elements and the main geochemical component responsible for ore mineralization extracted from principal component analysis are included in the integration process to prepare final potential maps. The conventional and the extended version of VIKOR method (as a well-known algorithm in multi-criteria decision making problems) produced two mineral potential maps, and the results were compared with the ones acquired from prevalent methods of the index overlay and fuzzy logic operators of sum and gamma. The final mineral potential maps based upon desired geo-data set indicate adequately matching of high potential zones with previous working and active mines of copper deposits.     

Factor analysis applied to regional geochemical data: problems and possibilities

A large regional geochemical data set of C-horizon podzol samples from a 188,000 km² area in the European Arctic, analysed for more than 50 elements, was used to test the influence of different variants of factor analysis on the results extracted. Due to the nature of regional geochemical data (neither normal nor log-normal, strongly skewed, often multi-modal data distributions), the simplest methods of factor analysis with the least statistical assumptions perform best. As a result of this test it can generally be suggested to use principal factor analysis with an orthogonal rotation for such data. Selecting the number of factors to extract is difficult, however, the scree plot provides some useful help. For the test data, a low number of extracted factors gave the most informative results. Deleting or adding just 1 element in the input matrix can drastically change the results of factor analysis. Given that selection of elements is often rather based on availability of analytical packages (or detection limits) than on geochemical reasoning this is a disturbing result. Factor analysis revealed the most interesting data structures when a low number of variables were entered. A graphical presentation of the loadings and a simple, automated mapping technique allows extraction of the most interesting results of different factor analyses in one glance. Results presented here underline the importance of careful univariate data analysis prior to entering factor analysis. Outliers should be removed from the dataset and different populations present in the data should be treated separately. Factor analysis can be used to explore a large data set for hidden multivariate data structures.     

Cluster analysis applied to regional geochemical data: Problems and possibilities

Cluster analysis can be used to group samples and to develop ideas about the multivariate geochemistry of the data set at hand. Due to the complex nature of regional geochemical data (neither normal nor log-normal, strongly skewed, often multi-modal data distributions, data closure), cluster analysis results often strongly depend on the preparation of the data (e.g. choice of the transformation) and on the clustering algorithm selected. Different variants of cluster analysis can lead to surprisingly different cluster centroids, cluster sizes and classifications even when using exactly the same input data. Cluster analysis should not be misused as a statistical “proof” of certain relationships in the data. The use of cluster analysis as an exploratory data analysis tool requires a powerful program system to test different data preparation, processing and clustering methods, including the ability to present the results in a number of easy to grasp graphics. Such a tool has been developed as a package for the R statistical software. Two example data sets from geochemistry are used to demonstrate how the results change with different data preparation and clustering methods. A data set from S-Norway with a known number of clusters and cluster membership is used to test the performance of different clustering and data preparation techniques. For a complex data set from the Kola Peninsula, cluster analysis is applied to explore regional data structures.     

Groundwater modeling applied to production well management in a contaminated aquifer

A study was conducted to evaluate production strategies for a well field system near a source of groundwater contamination. Numerical modeling of groundwater flow was employed to generate hydraulic head configurations for different production scenarios. For a given scenario, an evaluation of contamination susceptibility was made by comparing head distributions in two aquifer units to the positions of the contaminant source and discharging water supply wells. The results of this study suggest that groundwater flow modeling can be a useful technique for planning the production of water supply wells in aquifers at risk of contamination from anthropogenic pollution sources.     

Determination of sand dune characteristics through geomorphometry and wind data analysis in central Iran (Kashan Erg)

The combination of wind measurements and remotely sensed geomorphometry indices provides a valuable resource in the study of desert landforms, because arduous desert environments are difficult to access. In this research, we couple wind data and geomorphometry to separate and classify different sand dunes in Kashan Erg in central Iran. Additionally, the effect of sand-fixing projects on sand dune morphology was assessed using geomorphometry indices (roughness, curvature, surface area, dune spacing and dune height). Results showed that a Digital Elevation Model of the National Cartographic Center of Iran (NCC DEM) with 10-m resolution and accuracy of 54% could discriminate geomorphometry parameters better than the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data with 30-m resolution and Shuttle Radar Topography Mission (SRTM) data with 90-m resolution and 45.2 and 1.6% accuracy, respectively. Low classification of SRTM DEM was associated with too many non-value points found in the DEM. Accuracy assessment of comparison ground control points revealed that ASTER DEM (RMSE = 4.25) has higher accuracy than SRTM and NCC DEMs in this region. Study of curvature showed that transverse and linear sand dunes were formed in concave topography rather than convex. Reduced slopes in fixed sand dunes were established due to wind erosion control projects. Measurements of dune height and spacing show that there is significant correlation in compound dunes (R ² = 0.546), linear dunes (R ² = 0.228) and fixed dunes (R ² = 0.129). In general, the height of dunes in Kashan Erg increases from the margin of the field to the center of the field with a maximum height of 120 m in star dunes. Analysis of wind data showed that sand drift potential is in low-medium class in Kashan Erg. Linear sand dunes in Kashan Erg show that they are following a global trend in forming of these. Finally, established of geomorphometry method in dune classification will help researchers to identify priority of land management and performance assessment of sand dunes fixing projects in arid arduous environment.     

Physicochemical modeling as applied to study of sulfoarsenide complexes in hydrothermal solutions

System As–Na–S–Cl–H–O was studied. The research was carried out in three stages: (1) selection of the most likely complexes resulting from arsenic sulfide dissolution, (2) calculation of their thermodynamic constants, and (3) comparison of calculated data with thermodynamic database obtained in tests with the solution of inverse thermodynamic problems using the Selektor program complex. The system As–Na–S–Cl–H–O included more than 230 dependent components, which were divided into two groups, base and functional. The former group includes components of the solution (NaCl, NaOH, Na₂S, NaHS, HCl, H₂S, H₂SO₄, sulfates, H₂SO₃, sulfites, thiosulfates, Na⁺, Cl⁻,HS⁻, S²⁻), gas phase (43 components), and solid phase (orpiment, red arsenic, arsenolite, claudetite, arsenic, sulfur, sodium salts). Thermodynamic constants of the base components are contained in the Selektor database (they were borrowed from reference-books). The latter group includes 77 complexes labile in the solution but determining the solubility of arsenic and stability of its solid phases. Physicochemical modeling was performed in H₂S (≥0.01 m, pH = 1–10), Na₂S, and NaHS solutions at 25–250 °C and saturated-vapor pressure. It has been established that the dissolution of arsenic sulfide mineral phases in subneutral and alkaline solutions at low oxidation potential is favored by the formation of sulfoarsenides, which are more stable than arsenides and arsenates. Thermodynamic constants of functional complexes determining the orpiment solubility were calculated within the experimental error. It is shown that in hydrothermal iron-free systems with a low oxidation potential, the concentration of As in the solution decreases on cooling and with acidity increase.     

Interpretative matrices approach to ranking lake sub-basin pollution potential: an applied study in Brazil

In 2005 a Cylindrospermopsis raciborskii bloom occurred in the Rio Verde Lake Basin (Brazil). To address this concern, a field analysis was performed to measure physicochemical variables and flows in 14 sub-basins, between 2008 and 2009. Measurements of mean total P (0.039 mg/L ± 0.018 mean SD), mean total Kjeldahl N (0.260 mg/L ± 0.226 mean SD), and mean BOD (1.2 mg/L ± 0.4 mean SD) concentrations were low in most streams, while COD reached a high of 27.1 mg/L (±4.9 mean SD). One tributary was responsible for 85 % of TP load, 77.1 % of TKN load, 78 % of t-BOD load, and 79 % of t-COD load. These concentrations and loads were used to develop the pollution potential assessment matrix (2PAM), which considered three different perspectives: stream water quality, reservoir ecosystem equilibrium, and sub-basin management. Each factor (TP, TKN, BOD and COD) was weighted based on concentration, total load and unit-area load. Pollution potential differed depending on which perspective was considered. The matrix developed, 2PAM, provides a new way to analyze concentrations and loads, enabling basin managers to prioritize action plans according to desired use within the basin.     

A hybrid finite element-spectral boundary integral approach: Applications to dynamic rupture modeling in unbounded domains

The finite element method (FEM) and the spectral boundary integral method (SBI) have both been widely used in the study of dynamic rupture simulations along a weak interface. In this paper, we present a hybrid method that combines FEM and SBI through the consistent exchange of displacement and traction boundary conditions, thereby benefiting from the flexibility of FEM in handling problems with nonlinearities or small-scale heterogeneities and from the superior performance and accuracy of SBI. We validate the hybrid method using a benchmark problem from the Southern California Earthquake Center's dynamic rupture simulation validation exercises.We further demonstrate the capability and computational efficiency of the hybrid scheme for resolving off-fault heterogeneities by studying a 2D in-plane shear crack in two different settings: one where the crack is embedded in a high-velocity zone and another where it is embedded in a low-velocity zone. Finally, we discuss the potential of the hybrid method for addressing a wide range of problems in geophysics and engineering.     

矿产资源潜力评价数据模型研发、应用与数据集成方法技术体系

全国矿产资源潜力评价工作（2006—2013年）是目前中国最系统、最全面、最权威的一次矿产资源国情调查,形成了大量创新性成果。通过研发矿产资源潜力评价数据模型、应用软件及关键方法技术,全程提供现代信息技术支撑,使该项矿产资源国情调查全程信息数字化、预测处理GIS化、预测结果定量化、预测定位精准化、成果规范化与集成化,建立了矿产资源潜力评价数据模型研制、开发、应用与数据集成的方法技术体系。简要介绍该方法技术体系的主要内容,与同行交流,使之进一步发展完善。     

松辽盆地中央坳陷及邻区三维地热地质建模与地热资源靶区优选

三维地热地质建模能够直观反映地质体温度场分布格局, 有助于圈定地热资源有利靶区。本文利用地球物理及钻孔资料、岩石热物性数据对松辽盆地中央坳陷区进行三维地质建模及温度场模拟, 通过钻孔测温和实测大地热流数据, 验证了地热地质模型的可靠性。结果表明, 中央坳陷在1.0~4.0 km深度的温度分别为30.3℃~62.8℃、68.2℃~120.2℃、110.5℃~166.7℃、158.4℃~214.2℃。4.0 km深度内地温梯度介于36.9℃/km~57.4℃/km之间, 平均地温梯度为48.4℃/km。嫩江组、姚家组二段-三段、青山口组二段-三段和泉三段-四段4套主力热储底板温度分别介于15.8℃~71.4℃、23.6℃~88.6℃、31.8℃~107.4℃和48.9℃~133.4℃, 其中华字井阶地、大庆长垣、宾县王府凹陷为热储温度高值区。研究区现今地温场主要受基底起伏的控制, 基底和沉积层热导率的差异引起的热流"折射"效应促进了浅部热量的再分配, 形成了凹凸相间的地温场分布格局; 此外, 断裂构造对地温场高异常区的分布也有显著影响。结合热源、通道和储盖组合特征, 圈定大庆长垣中部地区泉头组三段-四段为松辽盆地中央坳陷地热资源开发有利靶区。     

大数据科学从信息化、模式化到智能化:现代地球化学应用研究的新范式

地球科学领域处在信息科学与信息化社会时代,基于大数据战略驱动的现代地球科学正在蓬勃兴起.诞生于近代的地球化学具有天然的结构化信息科学属性.提出建立从信息化、模式化到智能化的地球化学大数据信息科学应用研究总体思路,即基于地球化学大数据首先建立信息化系统,运用地球系统科学方法理论建立成矿地球化学分带富集模式与生态地球化学累...     

Geostatistical modeling of salinity as a basis for irrigation management and crop selection—A case study in central Tunisia

Spatial distribution of the salinity in groundwater used for irrigation and irrigated soil was investigated on Gammouda Plain, an important agricultural area in central Tunisia. Samples from 188 wells and irrigated fields were obtained in November 1988. Groundwater salinity ranges from 2 to 30 dS/m, and 50 percent of the sampled wells have a salinity higher than 3.5 dS/m. In most cases the soil samples have a salinity higher than 4 dS/m. Maps of salinity and leaching were produced by a geostatistical interpolation method based on ordinary kriging. In a great part of the plain, the estimated salinity levels indicate that there is a considerable risk for reduced yield potential for several of the most important crops grown. A rough estimation of the leaching fraction was computed from the soil and water salinity. Computer-based models of salinity ought to facilitate the general planning of irrigation management and crop selection.