Speleogenetic Evolution and Geological Remote Sensing of the Gypsum Plain, Eddy County, New Mexico

Permian evaporites of the Gypsum Plain region of the Delaware Basin host extensive karst phenomena, as well as unique diagenetic alterations of host strata. Because of the complex, poorly understood hydrogeologic system, little has been established concerning the relation and evolution of the overprinted, modern and ancient karst manifestations within the Gypsum Plain, as a whole. Through a combination of traditional field studies and the development of improved remote sensing methodologies, this study established the speleogenetic evolution of the Gypsum Plain in relation to the greater tectonic, stratigraphic, hydrogeologic and climatic history of the Delaware Basin. Emphasis was focused on a 100 km2 area of the Gypsum Plain in Eddy County, New Mexico, for the presence of all characteristic evaporite karst manifestations previously reported for the region, including epikarst, epigene caves, hypogene caves, intrastratal brecciation, calcitization and sulfur oxidation. Late Miocene uplift and tilting of the Delaware Basin tectonic block initiated development of dissolution and collapse of Castile strata, inducing an early phase of hypogene karsting. Renewed uplift and tilting during the latest Miocene, combined with increasing regional geothermal gradients, enabled hydrocarbon maturation, evaporite calcitization and additional hypogene porosity development. Pleistocene climate fluctuations increased denudation and exposed Castile evaporites to epigene development, while migration of the Pecos River across the area during the late Eocene enhanced karst processes. Karsting slowed with the Holocene shift to the current warm, arid climate, but solutional processes remain active with the general eastward migration of the hydrogeologic system. Traditional karst studies such as this are often costly and require months, if not years, of physical fieldwork. Preliminary identification of areas of interest through the careful evaluation of geologic maps offers a more efficient approach. However, published geologic maps of the Gypsum Plain feature little to no detail of lithologic variability, a vital attribute when dealing with phenomena dm2 to tens of m2 in area. Therefore,50 centimeter spatial resolution geologic maps were created through the classification of reflectance values of color infrared imagery of the study area in order to better constrain spatial variability in karst processes. Multispectral data was used for this purpose due to the high spatial resolution commercially/publicly available over that of hyperspectral sensor’s higher spectral resolutions and band combinations, deemed unnecessary because of the contrasting reflectance values of surface strata across the Gypsum Plain. Coupling of an improved speleogenetic evolution of the area with more accurate geologic mapping enables the development of better land management practices for karsted terrains such as the Gypsum Plain

Mapeamento de óxidos de ferro usando imagens landsat-8/OLI e EO-1/hyperion nos depósitos ferríferos da Serra Norte, província mineral de Carajás, Brasil

FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOMapping methods for iron oxides and clay minerals, using Landsat-8/Operational Land Imager (OLI) and Earth Observing 1 (EO-1)/Hyperion imagery integrated with airborne geophysical data, were applied in the N4, N5, and N4WS iron deposits, Serra Norte, Carajás, Brazil. Band ratios were achieved on Landsat-8/OLI imagery, allowing the recognition of the main minerals from iron deposits. The Landsat-8/OLI imagery showed a robust performance for iron oxide exploration, even in vegetated shrub areas. Feature extraction and Spectral Angle Mapper hyperspectral classification methods were carried out on EO-1/Hyperion imagery with good results for mapping high-grade iron ore, the hematite-goethite ratio, and clay minerals from regolith. The EO-1/Hyperion imagery proved an excellent tool for fast remote mineral mapping in open-pit areas, as well as mapping waste and tailing disposal facilities. An unsupervised classification was carried out on a data set consisting of EO-1/Hyperion visible near-infrared 74 bands, Landsat-8/OLI-derived Normalized Difference Vegetation Index, Laser Imaging Detection and Ranging-derived Digital Terrain Model, and high-resolution airborne geophysical data (gamma ray spectrometry, Tzz component of gradiometric gravimetry data). This multisource classification proved to be an adequate alternative for mapping iron oxides in vegetated shrub areas and to enhance the geology of the regolith and mineralized areas463331349FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOsem informação307177/2014-9Métodos de mapeamento para óxidos de ferro e argilas, aplicados em imagens Landsat-8/Operational Land Imager (OLI) e Earth Observing 1 (EO-1)/Hyperion e integrados com dados aerogeofísicos, foram testados nos depósitos de ferro de N4, N5 e N4WS, Serra Norte, Carajás, Brasil. Razões de banda foram aplicadas à imagem Landsat-8/OLI, identificando os principais minerais dos depósitos de ferro de N4 e N5. As imagens Landsat-8/OLI mostraram um bom desempenho para a exploração de óxido de ferro, mesmo em áreas vegetadas. Extração de feições espectrais e o método de classificação hiperespectral Spectral Angle Mapper foram aplicados na imagem EO-1/Hyperion com bons resultados para o mapeamento de minério de ferro de alto teor, bem como da proporção de hematita-goethita do minério e de argilas nos regolitos. A imagem EO-1/Hyperion provou ser uma excelente ferramenta para o mapeamento remoto de minerais em áreas de mina a céu aberto, bem como no mapeamento das pilhas de minério. Uma classificação não supervisionada foi aplicada a dados de 74 bandas do visível e infravermelho próximo do EO-1/Hyperion, índice Normalized Difference Vegetation Index derivado do Landsat-8/OLI, Modelo Digital do Terreno derivado do Laser Imaging Detection and Ranging, e dados aerogeofísicos (gamaespectrometria e componente Tzz do dado gravimétrico gradiométrico). Essa classificação de dados multifonte mostrou ser uma alternativa para mapeamento de óxidos de ferro em áreas vegetadas, bem como da geologia do regolito e das áreas mineralizada

Recent advances in the application of mineral chemistry to exploration for porphyry copper–gold–molybdenum deposits: detecting the geochemical fingerprints and footprints of hypogene mineralization and alteration

In the past decade, significant research efforts have been devoted to mineral chemistrystudies to assist porphyry exploration. These activities can be divided into two majorfields of research: (1) porphyry indicator minerals (PIMs), which are used to identify thepresence of, or potential for, porphyry-style mineralization based on the chemistry ofmagmatic minerals such as zircon, plagioclase and apatite, or resistate hydrothermalminerals such as magnetite; and (2) porphyry vectoring and fertility tools (PVFTs),which use the chemical compositions of hydrothermal minerals such as epidote,chlorite and alunite to predict the likely direction and distance to mineralized centers,and the potential metal endowment of a mineral district. This new generation ofexploration tools has been enabled by advances in and increased access to laserablation-inductively coupled plasma mass spectrometry (LA-ICP-MS), short wavelength infrared (SWIR), visible near-infrared (VNIR) and hyperspectral technologies.PIMs and PVFTs show considerable promise for exploration and are starting to beapplied to the diversity of environments that host porphyry and epithermal depositsglobally. Industry has consistently supported development of these tools, in the case ofPVFTs encouraged by several successful blind tests where deposit centers havesuccessfully been predicted from distal propylitic settings. Industry adoption is steadilyincreasing but is restrained by a lack of the necessary analytical equipment andexpertise in commercial laboratories, and also by the on-going reliance on well-established geochemical exploration techniques (e.g., sediment, soil and rock-chipsampling) that have aided the discovery of near-surface resources over many decades, are now proving less effective in the search for deeply buried mineral resources, and for those concealed under cover

Lateritic palaeosols of N.E. Africa: a remote sensing study

Remote sensing data and image processing techniques are used increasingly to aid scientific investigation and address geological problems in areas that are difficult to map by conventional methods. This thesis explores how multi spectral satellite data, supported by traditional geological techniques, facilitate a study of lateritic palaeosols. The work centres on laterites, which are thin but important elements of the Phanerozoic stratigraphy of NE Africa. They immediately pre-date midOligocene flood basalts and, if mapped, can be used to delineate a flood basalt-Iaterite contact and define the pre-30 Ma African Surface and uplift patterns. They have important engineering properties and are key to understanding basement alteration and its associated mineralization. They affect agriculture and groundwater quality and retention - essential in Sub-Saharan Aflica where access to safe water is limited. They dominate the landscape, yet are unmapped and marginalised in the literature. Their geological context supports a laterite-focused remote sensing mapping strategy. A strategy for geologic mapping of laterites based on their simple mineralogy and spectral characteristics that distinguish them from other rocks is developed. Methods for mapping are presented using Earth Observation data. The outcome is a series of regional geological maps of Eritrea and Ethiopia. These reveal that laterite cover is more extensive than previously thought and enable further lines of research. The maps provide a means of regional dating of laterites, which, together with ages obtained for overlying flood basalts and new basement cooling ages, indicate a major planation during the Palaeozoic and constrain the timing of associated uplift and erosion. A regional review of Mesozoic-Cenozoic climatic, strati graphic and structural evolution is presented and a model of Neogene deformation of the lateriteflood basalt datum is produced. Finally, laterite maps, petrographic and geochemical evidence are used to access basic essentials of life: clean water, a safe environment and a sustainable economy

Porphyry Indicator Minerals (PIMS) and Porphyry Vectoring and Fertility Tools (PVFTS) – Indicators of Mineralization Styles and Recorders of Hypogene Geochemical Dispersion Halos

In the past decade, significant research efforts have been devoted to mineral chemistry studies to assist porphyry exploration. These activities can be divided into two major fields of research: (1) porphyry indicator minerals (PIMS), which aims to identify the presence of, or potential for, porphyry-style mineralization based on the chemistry of magmatic minerals such as plagioclase, zircon and apatite, or resistate hydrothermal minerals such as magnetite; and (2) porphyry vectoring and fertility tools (PVFTS), which use the chemical compositions of hydrothermal minerals such as epidote, chlorite and alunite to predict the likely direction and distance to mineralized centres, and the potential metal endowment of a mineral district. This new generation of exploration tools has been enabled by advances in laser ablation-inductively coupled plasma mass spectrometry, short wave length infrared data acquisition and data processing, and the increased availability of microanalytical techniques such as cathodoluminescence. PVFTS and PIMS show considerable promise for porphyry exploration, and are starting to be applied to the diversity of environments that host porphyry and epithermal deposits around the circum-Pacific region. Industry has consistently supported development of these tools, in the case of PVFTS encouraged by several successful “blind tests” where deposit centres have successfully been predicted from distal propylitic settings. Industry adoption is steadily increasing but is restrained by a lack of the necessary analytical equipment and expertise in commercial laboratories.Item freely available with no apparent Creative Commons License or copyright statement. The attached file is the published pdf

Quantitative Mapping of Soil Property Based on Laboratory and Airborne Hyperspectral Data Using Machine Learning

Soil visible and near-infrared spectroscopy provides a non-destructive, rapid and low-cost approach to quantify various soil physical and chemical properties based on their reflectance in the spectral range of 400–2500 nm. With an increasing number of large-scale soil spectral libraries established across the world and new space-borne hyperspectral sensors, there is a need to explore methods to extract informative features from reflectance spectra and produce accurate soil spectroscopic models using machine learning. Features generated from regional or large-scale soil spectral data play a key role in the quantitative spectroscopic model for soil properties. The Land Use/Land Cover Area Frame Survey (LUCAS) soil library was used to explore PLS-derived components and fractal features generated from soil spectra in this study. The gradient-boosting method performed well when coupled with extracted features on the estimation of several soil properties. Transfer learning based on convolutional neural networks (CNNs) was proposed to make the model developed from laboratory data transferable for airborne hyperspectral data. The soil clay map was successfully derived using HyMap imagery and the fine-tuned CNN model developed from LUCAS mineral soils, as deep learning has the potential to learn transferable features that generalise from the source domain to target domain. The external environmental factors like the presence of vegetation restrain the application of imaging spectroscopy. The reflectance data can be transformed into a vegetation suppressed domain with a force invariance approach, the performance of which was evaluated in an agricultural area using CASI airborne hyperspectral data. However, the relationship between vegetation and acquired spectra is complicated, and more efforts should put on removing the effects of external factors to make the model transferable from one sensor to another.:Abstract I Kurzfassung III Table of Contents V List of Figures IX List of Tables XIII List of Abbreviations XV 1 Introduction 1 1.1 Motivation 1 1.2 Soil spectra from different platforms 2 1.3 Soil property quantification using spectral data 4 1.4 Feature representation of soil spectra 5 1.5 Objectives 6 1.6 Thesis structure 7 2 Combining Partial Least Squares and the Gradient-Boosting Method for Soil Property Retrieval Using Visible Near-Infrared Shortwave Infrared Spectra 9 2.1 Abstract 10 2.2 Introduction 10 2.3 Materials and methods 13 2.3.1 The LUCAS soil spectral library 13 2.3.2 Partial least squares algorithm 15 2.3.3 Gradient-Boosted Decision Trees 15 2.3.4 Calculation of relative variable importance 16 2.3.5 Assessment 17 2.4 Results 17 2.4.1 Overview of the spectral measurement 17 2.4.2 Results of PLS regression for the estimation of soil properties 19 2.4.3 Results of PLS-GBDT for the estimation of soil properties 21 2.4.4 Relative important variables derived from PLS regression and the gradient-boosting method 24 2.5 Discussion 28 2.5.1 Dimension reduction for high-dimensional soil spectra 28 2.5.2 GBDT for quantitative soil spectroscopic modelling 29 2.6 Conclusions 30 3 Quantitative Retrieval of Organic Soil Properties from Visible Near-Infrared Shortwave Infrared Spectroscopy Using Fractal-Based Feature Extraction 31 3.1 Abstract 32 3.2 Introduction 32 3.3 Materials and Methods 35 3.3.1 The LUCAS topsoil dataset 35 3.3.2 Fractal feature extraction method 37 3.3.3 Gradient-boosting regression model 37 3.3.4 Evaluation 41 3.4 Results 42 3.4.1 Fractal features for soil spectroscopy 42 3.4.2 Effects of different step and window size on extracted fractal features 45 3.4.3 Modelling soil properties with fractal features 47 3.4.3 Comparison with PLS regression 49 3.5 Discussion 51 3.5.1 The importance of fractal dimension for soil spectra 51 3.5.2 Modelling soil properties with fractal features 52 3.6 Conclusions 53 4 Transfer Learning for Soil Spectroscopy Based on Convolutional Neural Networks and Its Application in Soil Clay Content Mapping Using Hyperspectral Imagery 55 4.1 Abstract 55 4.2 Introduction 56 4.3 Materials and Methods 59 4.3.1 Datasets 59 4.3.2 Methods 62 4.3.3 Assessment 67 4.4 Results and Discussion 67 4.4.1 Interpretation of mineral and organic soils from LUCAS dataset 67 4.4.2 1D-CNN and spectral index for LUCAS soil clay content estimation 69 4.4.3 Application of transfer learning for soil clay content mapping using the pre-trained 1D-CNN model 72 4.4.4 Comparison between spectral index and transfer learning 74 4.4.5 Large-scale soil spectral library for digital soil mapping at the local scale using hyperspectral imagery 75 4.5 Conclusions 75 5 A Case Study of Forced Invariance Approach for Soil Salinity Estimation in Vegetation-Covered Terrain Using Airborne Hyperspectral Imagery 77 5.1 Abstract 78 5.2 Introduction 78 5.3 Materials and Methods 81 5.3.1 Study area of Zhangye Oasis 81 5.3.2 Data description 82 5.3.3 Methods 83 5.3.3 Model performance assessment 85 5.4 Results and Discussion 86 5.4.1 The correlation between NDVI and soil salinity 86 5.4.2 Vegetation suppression performance using the Forced Invariance Approach 86 5.4.3 Estimation of soil properties using airborne hyperspectral data 88 5.5 Conclusions 90 6 Conclusions and Outlook 93 Bibliography 97 Acknowledgements 11

Integration of advanced remote sensing and geospatial methodologies to enhance mineral exploration: An example from the southern Gawler Ranges, South Australia

The world’s demand for metals is increasing and there is a growing need for mineral explorers to locate new ore deposits. Globally, discovery of economic mineral deposits is becoming more challenging due to the increasing depths where exploration is being conducted to discover mineral deposits. Most surficial deposits have been discovered, driving exploration into terrains with substantial weathered regolith cover, and requiring new exploration methods. Current traditional exploration methods including geophysics, high density soil sampling and geochemical analysis can be expensive, time consuming and limited in geographic extent. Although remote sensing methods have been applied to regional-scale mineral exploration, there is potential for them to be used more fully in regions where regolith is a continuing challenge. The overarching aim of this multidisciplinary thesis is to develop methods that integrate forms of remote sensing and geospatial information to reduce the risk and cost of exploration in weathered terrains by identifying and mapping surface alteration related to buried mineralisation. The study area used to develop and test these methodologies was the southern Gawler Ranges, South Australia, a region prospective for gold, porphyry-copper and epithermal-silver mineralisation. This semi-arid environment is moderately vegetated with limited geological exposures. Most basement rocks are overlain by approximately 100 m of weathered cover materials presenting challenges for both exploration and remote sensing methods. The broad research aim was addressed through three more specific objectives: 1. Development of an objective regolith-landform map using geospatial data and a repeatable methodology that can be used to guide the early stages of exploration potential assessment; 2. Characterisation of surface expressions of alteration mineralogy and interpretation of landscape processes using airborne hyperspectral imagery and mineralogical data; and 3. Integration of surface geochemistry, mineralogy and regolith-landform mapping to understand and map surface signatures of potential buried mineralisation. An unsupervised classification was applied to geospatial data layers including a Digital Elevation Model, Topographic Position Index and potassium, thorium and uranium gamma-ray radiometrics. This was clustered to generate an objective regolith-landform map representing the main regolith-landform types. This map captured many of the features typically mapped by traditional regolith-landform mapping as assessed by a statistical goodness of fit measure. While not a replacement for the resource-intensive traditional regolith maps derived from extensive field work, this method used freely available geospatial data an objective, repeatable methodology to produce a map that has potential to increase understanding of the landscape and assist targeting of areas of alteration and mineralisation for more detailed exploration. Airborne hyperspectral imagery was analysed by Spectral Feature Fitting, matching image spectra to reference spectra to identify alteration mineralogy. X-ray diffraction was used to independently validate mineralogy present in the landscape providing insight into unclear spatial distributions of some minerals and confirming the presence of key alteration minerals. Landscape processes were interpreted by integrating the spatial distribution of minerals with the objective regolith-landform map. Advanced argillic and argillic alteration were identified in the study area, focused around an exposed alunite breccia at Nankivel Hill. The results placed the central topographic feature, Nankivel Hill, proximal to potential porphyry mineralisation, with Peterlumbo Hill distal to mineralisation as possible chloritic alteration expressed at the surface in this region. Definition of lithologies from major element geochemistry identified ten rock and cover sequence types within the study area. A region-specific pathfinder element suite was defined using interpretation and thresholds of the Nankivel and Peterlumbo Hill rock exposures. The mineral hosts of these pathfinder elements were proposed from interpretation of semi-quantitative X-ray diffraction to determine the influence of weathering on dispersion of pathfinder elements from rock exposure to cover sequence materials. This suggested that most pathfinder elements were hosted in a variety of minerals including alunite, jarosite, microcline, muscovite, orthoclase and hematite in rock exposures and a broader range of feldspars, clays, micas, carbonates and iron oxides associated with cover sequence materials. Definitions of proximal and distal geochemical and mineralogical footprints of a porphyry deposit were delineated using the surface geochemistry, X-ray diffraction and hyperspectral mineralogical data. The landscape position of pathfinder elements was interpreted to recommend sample media with the most potential for identification of pathfinders at higher concentrations. The outcomes of this research demonstrate several encouraging approaches for use of land surface remote sensing and geospatial analysis in the context of mineral exploration in highly weathered and covered terrains. These methods can be integrated easily with more traditional methods and data to improve mineral exploration outcomes for the industry. The increasing need to explore terrains with extensive depths of cover in order to discover new ore deposits suggests that the industry would benefit from integrating these tools to enhance future exploration.Thesis (Ph.D.) -- University of Adelaide, School of Biological Sciences, 202

Assessing the role of EO in biodiversity monitoring: options for integrating in-situ observations with EO within the context of the EBONE concept

The European Biodiversity Observation Network (EBONE) is a European contribution on terrestrial monitoring to GEO BON, the Group on Earth Observations Biodiversity Observation Network. EBONE’s aims are to develop a system of biodiversity observation at regional, national and European levels by assessing existing approaches in terms of their validity and applicability starting in Europe, then expanding to regions in Africa. The objective of EBONE is to deliver: 1. A sound scientific basis for the production of statistical estimates of stock and change of key indicators; 2. The development of a system for estimating past changes and forecasting and testing policy options and management strategies for threatened ecosystems and species; 3. A proposal for a cost-effective biodiversity monitoring system. There is a consensus that Earth Observation (EO) has a role to play in monitoring biodiversity. With its capacity to observe detailed spatial patterns and variability across large areas at regular intervals, our instinct suggests that EO could deliver the type of spatial and temporal coverage that is beyond reach with in-situ efforts. Furthermore, when considering the emerging networks of in-situ observations, the prospect of enhancing the quality of the information whilst reducing cost through integration is compelling. This report gives a realistic assessment of the role of EO in biodiversity monitoring and the options for integrating in-situ observations with EO within the context of the EBONE concept (cfr. EBONE-ID1.4). The assessment is mainly based on a set of targeted pilot studies. Building on this assessment, the report then presents a series of recommendations on the best options for using EO in an effective, consistent and sustainable biodiversity monitoring scheme. The issues that we faced were many: 1. Integration can be interpreted in different ways. One possible interpretation is: the combined use of independent data sets to deliver a different but improved data set; another is: the use of one data set to complement another dataset. 2. The targeted improvement will vary with stakeholder group: some will seek for more efficiency, others for more reliable estimates (accuracy and/or precision); others for more detail in space and/or time or more of everything. 3. Integration requires a link between the datasets (EO and in-situ). The strength of the link between reflected electromagnetic radiation and the habitats and their biodiversity observed in-situ is function of many variables, for example: the spatial scale of the observations; timing of the observations; the adopted nomenclature for classification; the complexity of the landscape in terms of composition, spatial structure and the physical environment; the habitat and land cover types under consideration. 4. The type of the EO data available varies (function of e.g. budget, size and location of region, cloudiness, national and/or international investment in airborne campaigns or space technology) which determines its capability to deliver the required output. EO and in-situ could be combined in different ways, depending on the type of integration we wanted to achieve and the targeted improvement. We aimed for an improvement in accuracy (i.e. the reduction in error of our indicator estimate calculated for an environmental zone). Furthermore, EO would also provide the spatial patterns for correlated in-situ data. EBONE in its initial development, focused on three main indicators covering: (i) the extent and change of habitats of European interest in the context of a general habitat assessment; (ii) abundance and distribution of selected species (birds, butterflies and plants); and (iii) fragmentation of natural and semi-natural areas. For habitat extent, we decided that it did not matter how in-situ was integrated with EO as long as we could demonstrate that acceptable accuracies could be achieved and the precision could consistently be improved. The nomenclature used to map habitats in-situ was the General Habitat Classification. We considered the following options where the EO and in-situ play different roles: using in-situ samples to re-calibrate a habitat map independently derived from EO; improving the accuracy of in-situ sampled habitat statistics, by post-stratification with correlated EO data; and using in-situ samples to train the classification of EO data into habitat types where the EO data delivers full coverage or a larger number of samples. For some of the above cases we also considered the impact that the sampling strategy employed to deliver the samples would have on the accuracy and precision achieved. Restricted access to European wide species data prevented work on the indicator ‘abundance and distribution of species’. With respect to the indicator ‘fragmentation’, we investigated ways of delivering EO derived measures of habitat patterns that are meaningful to sampled in-situ observations

The influence of cap rock composition on hydrocarbon seep type in the Zagros oil fields, a study using Advanced Spaceborne Thermal Emission and Reflection Radiometer mineral map

The persistent natural hydrocarbon seepage in onshore basins challenges observation and exploration technologies, which are required to document and assess these valuable indications of the presence of oil and gas in the subsurface. This paper aims at demonstrating the relationship between the compositional variation of an evaporite cap rock and the types of seeps occurring at the surface. For this purpose, the multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data was utilized for mapping mineral variations of a petroleum system in the Zagros oil fields. Relative absorption-band depth (RBD), band rationing and the boosted regression trees (BRT) were applied to enhance and classify the mineral composition of evaporite, sandstone, and marly limestone formations. The gas seeps were associated with the areas of gypsum-bearing evaporite cap rock while oil seeps were mostly associated with calcite and clay zones within the cap rock, which was more prone to fracturing during the tectonic activities of the basin. It is suggested that the application of remote sensing in the oil and gas industry could be widened by detection of sleep-induced alteration to assess the efficiency of cap rock and to evaluate the productivity of reservoirs at a regional scale