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An integrated interpretation of processed 3D seismic data, a suite of well logs, biostratigraphic data and core photographs of AMO Field, deep offshore Niger Delta is carried out for the sequence stratigraphic analysis of strata penetrated by wells. Lithologic and key stratigraphic surfaces, that is the maximum flooding surfaces (MFSs) and sequence boundaries (SBs), are identified based on bioevents and log motifs. Biostratigraphic data help the delineation of MFSs and SBs, as well as dating, determination of depositional environment and paleobathymetry. The sequence stratigraphic study reveals seven MFSs (of 13.0 Ma, 11.0 Ma, 9.5 Ma, 7.4 Ma, 5.8 Ma, 5.0 Ma and 2.7 Ma) and six SBs (of 12.1 Ma, 10.3 Ma, 8.5 Ma, 6.3 Ma, 5.5 Ma and 4.2 Ma). The key stratigraphic surfaces identified involve three depositional sequences characterized by lowstand, transgressive and highstand system tracts respectively. The studied section is deposited in a deepwater environment ranging from Lower to Upper Bathyal and can be dated back to the Middle Miocene - Middle Pliocene in age. Seven faults and two horizons (corresponding to reservoir units) are identified and mapped across the seismic data volume to establish a continuity of the reservoir to areas lacking well control. The established sequence stratigraphic framework displays successions of sediments (system tracts) where the reservoir sand units of the lowstand and highstand system tracts are of hydrocarbon prospective units in the field.

Magnetite-bearing granophyre and quartz dolerite are the evolved fractions of differentiated dolerite (diabase) sills and are an important host to Archean gold deposits because they are chemical traps for orogenic fluids. Despite their economic importance, there is a poor understanding of how melt composition, crystal fractionation, sill geometry, and depth of emplacement increase the volume of host rock that is most favorable for gold precipitation during orogenesis. We use drill core logging, whole-rock geochemistry, magnetic susceptibility, gold assay, and thermodynamic modeling data from 11 mineralized and unmineralized ca. 2.7 Ga differentiated dolerites in the Eastern Goldfields superterrane (Yilgarn craton, Western Australia) to better understand the influence of igneous and emplacement processes on gold prospectivity. Orogenic gold favors differentiated dolerites, derived from iron-rich parental magmas, that crystallize large volumes of magnetite-bearing quartz dolerite (>25% total thickness). Mineralized sills are commonly >150 m thick and hosted by thick and broadly coeval sedimentary sequences. Sill thickness is an important predictor for gold prospectivity, as it largely controls cooling rate and hence fractionation. The parental melts of gold-mineralized sills fractionated large amounts of clinopyroxene and plagioclase (possibly up to 50%) at depth before emplacement in the shallow crust. A second fractionation event at shallow levels (

The application of deep learning algorithms in mineral prospectivity mapping (MPM) is a hot topic in mineral exploration. However, few studies have focused on recurrent neural networks (RNNs) in terms of integrating different evidential layers to map mineral potential. In this study, a gated recurrent unit (GRU) model was employed for MPM using a case study on the Baguio District of Philippines. To generate sufficient training samples for GRU, data augmentation with geological constraints was employed. To explore the influence of different orders of evidence layers, as inputs of RNN, a total permutation of the evidence layers was built. Meanwhile, a nonlinear controlling function was used to capture the spatial relationships between known mineral deposits and geological controlling factors and assign the value for each pixel of evidence layers. The obtained results demonstrated the excellent performance of GRU in MPM. The delineated high-anomaly areas show close spatial relationships with known mineral deposits and therefore can provide significant clues for the next round of mineral exploration in the study area.

The Sonakhan greenstone belt in Central India is under-explored with respect to gold in spite of its similarity to auriferous greenstone belts in general, which prompted a prospectivity analysis. The workflow involved adoption of a conceptual mineral systems model, recognizing indicative spatial proxies, processing exploration datasets, generating evidence maps and integrating into GIS-based mineral prospectivity mapping. Available geological information such as key lithologic units and their contacts was combined with geochemical anomalies of selected pathfinder elements, geophysical data (aeromagnetic anomaly and K/Th ratio map) and satellite digital image data (ASTER and Landsat 7 ETM +), leading to generation of 17 evidential layers. The lack of a significant number of known mineral occurrences in the study area precludes the use of data-driven prospectivity modeling techniques. Therefore, knowledge-driven approaches such as binary and multiclass index overlay, fuzzy logic and fuzzy AHP (analytic hierarchy process) were adopted to integrate the evidential layers resulting in four prospectivity maps. The variation of cumulative prospectivity with respect to cumulative area in each model was used to determine threshold to produce binary prospectivity maps separating high and low prospectivity zones. An approach based on the unique conditions of the binary prospectivity maps was used to illustrate the combined results of different models. In order to quantify the intuitive uncertainty in exploration targeting that arose due to different model outputs, a modulated predictive model was generated taking the mean prospectivity values at each pixel. The pixels having mean values above 95th percentile were grouped and the area delineated as potential exploration targets for gold that comprises merely 5% of the study area. The estimated uncertainty and confidence values for each pixel were used in the risk analysis that returned 1.95% and 3.05% of the study area as low- and high-risk exploration targets, respectively.

To integrate the evidential signatures into a mineral prospective map, it is necessary to model the observed data of metallogenic predictors with complex relationships. In this paper, a methodology was developed for gold prospectivity modeling by combining Laplacian eigenmaps (LEMS) and the least angle regression (LARS). LEMS were used to transform metallogenic predictors into Laplacian spectra to enhance the data classification ability, and the Laplacian spectra were used in LARS for gold prospectivity modeling. The Jinchanggouliang area, an important gold metallogenic district in China, was taken as the study area. Based on the geological and geochemical survey data of the study area, the LARS model, the combination of LEMS and LARS (LEMS–LARS) model, the logistic regression (LGR) model and the one-class support vector machine (OCSVM) model were each established for gold prospectivity modeling in the study area. The performances of these four models were measured using different performance evaluation methods. The receiver operating characteristic (ROC) analysis reveals that the LEMS–LARS model, the LGR model and the OCSVM model yield comparable performances and were superior to the LARS model, for gold prospectivity modeling in the study area. The prediction–area (P–A) plots of the four models show that the LEMS–LARS model, the LGR model and the OCSVM model each predicted about 20% of the study area as gold prospective areas, which contain about 80% of the known gold deposit locations. However, the performance of the LARS model was difficult to evaluate by the P-A plot because its prediction curve overlaps with its area curve, forming a straight-line segment, in the P-A plot. The gold prospective areas delineated optimally separately by the LEMS–LARS model, the LGR model and the OCSVM model are associated spatially with areas having favorable metallogenic conditions. The case study illustrates that the LEMS–LARS model can be used as a data-driven mineral prospectivity method, and its performance, in gold prospectivity modeling in the study area, is comparable to that of the LGR method and OCSVM method.

The Xiadian orogenic deposit with ~ 100 t of gold resources, located in the Jiaodong Peninsula, Eastern China, shows an economically attractive gold mineralization that is spatially associated with the Zhaoping detachment fault. This study presents a combination of field investigation, 3D modeling, spatial analysis of models, and prospectivity modeling using a multi-layer perceptron deep neural network to understand the association between gold mineralization and structural deformation and to identify targets for deep exploration. The principal gold mineralization at Xiadian occurs as disseminated ore associated with strongly fractured rocks. Spatial analysis determined that gold mineralization is located primarily in convex segments (0–50 m) of the fault footwall within 150 m of the fault buffer where the dip is gentle (~ 35° to 55°). Sulfide vein ore with high Au grades is, by contrast, typically sited within steeply dipping fracture-fill distal to the Zhaoping detachment (150–250 m), consistently in areas with NE-strike and associated with steep segments of the detachment fault. The distribution of the orebodies is attributed to brittle–ductile deformation proximal to the detachment and distal brittle extension. Given the characteristics of syn-deformation mineralization and the stress regime (NW σ3, NE σ2, and vertical σ1), the NE-plunging ore shoots were interpreted as the result of auriferous fluid flow into oblique dilation zones formed by the coupled normal and dextral strike-slip movement of the Zhaoping fault. Six potential gold targets were identified sub-horizontal to, and NE-trending from, known orebodies. This study highlights the utility of 3D prospectivity modeling as a robust tool for understanding orogenic gold spatial distribution and related structural controls.

While performing various steps for exploration and exploitation of geothermal resources, the applications of geochemical methods are pivotal for reservoir characteristics evaluation. It is used concurrently with geological and hydro-geological appraisals to supplement available information regarding the prospectively of the region of investigation at the relatively low cost compared to geophysical methods or drilling. Temperature range of 40 °C to 47 °C is demonstrated by the study area comprising of several thermal water manifestations. Studies from existing wells and surveys have suggested the presence of a sizable low enthalpy geothermal resource in the field. One of the most prominent uses of geochemical sampling is the determination of subsurface temperatures using Geothermometry. In this study, commonly accepted concepts of cationic and Silica Geothermometry have been applied to understand conditions in the reservoir. Interpretation of the data has given us some input on the reservoir characteristics like reservoir temperature, mixing process and multiple fluid origins. In Dholera geothermal field for determination of variation in hydrochemical facies and understanding of the advancement of the hydrochemical forms, the current research additionally imagines the significance of graphical portrayals like Piper chart, Scholler and so forth individually. The seawater intrudes the composition of water shows the reservoir. The physio-chemical properties of the water also influence exploitation strategies.

Natural hydrogen seeps called fairy circles have been identified in Mali, Brazil, Russia, and United-States. Natural hydrogen is produced from a field in Mali for 7 years. The natural hydrogen system is still poorly understood and needs to be studied in new geological contexts as to streamline hypotheses on the system dynamics and elements into concepts. In Australia, numerous circular surface features, commonly called salt lakes or swaps, are visible from the sky but no existing work shows nor quantifies any hydrogen content in those features. In this study, we reviewed the existing literature on fairy circles as to determine and directly test with soil-gas measurements if hydrogen surface-emitting features are present in Australia. We determined best candidates to test with a multi-disciplinary approach linking geology, multi-physical imaging, and seismic interpretation. Soil-gas measurements showed persistent hydrogen concentration localized in the external ring of circular depressions aligned along the Darling Fault, a major crustal boundary between the granitic, mafic and ultramafic rocks of the Yilgarn Craton from the sedimentary rocks of the Perth Basin. This work is the proof that fairy circles, in the meaning of H2 emitting structures, are present in Australia and opens the door to new prospectivity pathways by evaluating original hypotheses on natural hydrogen generation, migration pathways and entrapment. This geological setting promotes deep serpentinization of ultramafic rocks as well as oxidation of iron-rich Archean rocks and mafic dikes as potential hydrogen sources that are both of massive potential economic value. This hydrogen can circulate and be entrapped as aqueous hydrogen in low-salinity aquifers or migrate in gaseous phase in fault zones up to intermediate structural reservoir or to the surface.

The traditional convolutional neural networks applied in mineral prospectivity mapping usually extract features from only one scale at each iteration, resulting in plain features. To combat this limitation, this study utilized a convolutional neural network based on GoogLeNet to predict prospectivity for gold deposits in the Fengxian study area, China. The GoogLeNet adopted four groups of convolution kernels to extract and integrate features from multiple scales, obtaining abundant and comprehensive features related to mineralization. According to a multi-source geoinformation analysis, we selected 11 exploration criteria, including three geological factors (NW-trending brittle-ductile faults, NE-trending brittle faults, and anticline axes) and eight geochemical exploration data layers (Au, Ag, As, Hg, Pb, Zn, Cu, and Sb). Then, we created predictor samples to train the models to mine evidential features. Following to a comprehensive analysis, we formed a fusion model of GoogLeNet for mineral prospectivity modeling. The results demonstrated that the fusion model achieved an optimized predictive accuracy of 93.1% and an area under curve of 0.968. This fusion model outperformed the other models with superior success rate and prediction area rate performances, capturing 72% of the known gold deposits in just 27.3% of the research area. The results indicate the effectiveness of GoogLeNet in mineral prospectivity mapping. Finally, we classified the Fengxian district into three areas according to their different mineral prospectivity. The high-prospectivity areas provide significant implications for further exploration of gold deposits in the study area.

Studies of near-seabed datasets show that salt tectonics controls the distribution and architecture of deep-water reservoirs in many salt-influenced basins. It is typically difficult, however, to study the distribution and stratigraphic evolution of depositional systems preserved at deeper, economically significant depths, reflecting poor seismic imaging of steeply dipping strata flanking high-relief salt structures. 3D seismic and borehole data from the Santos Basin, offshore Brazil allow us to identify a range of depositional elements that form the building blocks of three main tectono-stratigraphic phases. During the first phase, channel systems and lobes were confined within updip minibasins and to the hangingwalls of salt-detached faults. During the second phase, channel systems and lobes filled updip minibasins to bypass sediment downslope, with coarse clastic deposition then occurring in downdip minibasins, >100 km from the coeval shelf margin. Syndepositional seafloor relief caused: (i) channel system deflection and diversion around salt-cored highs; (ii) channel system uplift and rotation on the flanks of rising salt structures; (iii) lateral and frontal confinement of channel systems. During the final phase, rising salt walls dissected previously deposited deep-water systems, with MTCs deposition becoming increasingly important. Our results have important implications for post-salt prospectivity in the Santos Basin and other salt-influenced sedimentary basins, with a range of reservoirs and trapping styles present in this underexplored interval. More specifically, we show that large volumes of clastic sediment were not trapped behind the ‘Albian Gap’, a salt-controlled depocenter dominating the north-western basin margin, but were instead delivered further basinward.

The Zhongdian arc is an important mineral province in southwest China that hosts significant Cu- and Mo-rich ore deposits. These are mainly present as Late Triassic porphyry Cu ± Mo-Au and Late Cretaceous porphyry Mo deposits, both with surrounding base metal enrichments in associated skarn, greisen, and vein occurrences. To help assess Mo resource potential in the arc-related magmatic–hydrothermal systems, we evaluated geochemical data from 1831 stream sediment samples that were collected at a density of one sample per 2 km2 during the Chinese National Geochemical Mapping Program. Singularity analyses were combined with factor analysis and singularity-quantile methods to interpret distribution patterns for 18 ore-related elements and to define geochemical signatures in the stream sediment data related to areas of high favorability for the presence of Cu- and Mo-dominant ores in the Zhongdian arc. The known mineral occurrences in the arc show spatial-frequency singularity. Spatial patterns in the sediment data indicate the Triassic Cu-dominant systems are associated with intrusions emplaced along a northwest-trending system of faults, whereas the Cretaceous Mo-rich ore systems are related to north–south striking structures. The patterns indicate locations of high favorability for new discoveries of Mo occurrences in the central part of the arc where many deposits are already known, as well as in the southwestern part of the arc that presently lacks abundant known occurrences. Factor analysis results show that the areas favorable for the Mo porphyries are best defined by a Mo–W–Bi–Pb–Ag signature in the sediment data. These can be distinguished from areas most likely to contain older Cu-rich systems that are marked by sediments with Cu, Zn, and Au anomalies. The singularity analysis, in combination with factor analysis and singularity-quantile, was able to successfully separate anomalies in the sediment samples that were representative of the Late Triassic and Late Cretaceous mineral systems, despite elements such as Mo, Pb, and Ag being enriched in ores of both ages.

Sedimentary basins in south Egypt, in particular Komombo and Nuqra basins, have been paid more attention during the last few decades, due to their hydrocarbon prospectivity. The present article is an integrated seismic and petrophysical study aiming at evaluating the hydrocarbon potentiality of the Cretaceous sedimentary sequence in these two basins. Data of four drilled wells including a conventional core, and well log data, in addition to 20 2D seismic profiles (ten for each basin), were studied in detail. The study indicates that the sedimentary sequence in the two basins is represented by the Nubia Sandstone, which is subdivided (from base to top) into Komombo, Six Hills, Abu Ballas, Sabaya, and Maghrabi formations. This sequence in both basins is dissected by a set of NW–SE-trending faults, in addition to a younger set of NNE–SSW to NE–SW trending. The present study indicates that the Komombo Formation is characterized by a good oil potentiality of a net pay thickness up to 65 ft (1 ft = 0.3048 m) in the Komombo basin. The Six Hills Formation may also be prospective, especially near the depocenters of the Komombo and Nuqra basins, due to its wide extension, good thickness (up to 4150 ft), and presence of some oil shows. However, the reservoir of the studied sequence may be of low quality due to cementation with silica, compaction, and the presence of high shale content. Two reservoir rock types (RRTs) were assigned to the Six Hills Formation: RRT1 (clean siliceous sandstone) with good reservoir quality and RRT2 (argillaceous sandstone) with low reservoir quality.

Successful delineation of high potential targets for exploration in maturely-explored orefields is still a tough challenge. A reliable prediction model achieved by integration of various ore-related geological factors and exploration information in the 3D space is an effective approach to deal with this challenge. The Anqing orefield has been intensively exploited for decades, and thereby the possible potential left must be at depth. The accumulated abundant data of exploration and research provide us a possibility for carrying out machine learning-based 3D modeling. The 3D block models of the main geological bodies, resistivity and volumetric strain field in this orefield were used as multi-resource geological data to construct prediction models by using weight-of-evidence and machine learning methods. Through performance evaluation and comparison, the following conclusions were obtained: (1) it is more scientific and reasonable to use all the geological prospecting factors concurrently for mineral prospectivity mapping (MPM) rather than use one or a part of them; (2) random forest (RF) algorithm seems capable of MPM because of its high accuracy and reliability in prediction; and (3) rational selection of training and learning samples, especially, those from actual geological objects and exploration engineering, plays a more critical role in MPM than algorithm and methods themselves. Two different RF prediction models were obtained for MPM in the east and the surrounding part of this orefield based on the outcome of geophysical prospecting. The spaces with prediction probabilities higher than 0.508 in the east part and 0.501 in the surroundings take up only 3.71% volume of the whole orefield, but contain 95.92% of the mineralized blocks. The high potential targets are most likely parts of the above spaces with high prediction probabilities that have not been drilled yet up to now.

Rare earth element and yttrium (REY) deposits are important strategic resources widely used in high-tech applications, such as solar cells and wind turbines. This paper summarises the temporal-spat...

Mafic-ultramafic subvolcanic intrusive complexes, at the 1–10-km scale, constitute favorable environments for the formation of orthomagmatic Ni-Cu-PGE sulfide deposits. Within 100–1000-km scale large igneous provinces (LIPs), the most favorable economic target areas may be difficult to identify using a traditional regional exploration approach. We report results of field and laboratory studies focused on an integrated geochemical-architectural model for the Ni-Cu-PGE sulfide potential of the High Arctic large igneous province (HALIP) of Canada, the largest and best-exposed portion of this circum-arctic LIP. Previous lithogeochemical studies of the Canadian HALIP (130–80 Ma) concluded that subalkaline mafic units located on Axel Heiberg Island were more prospective than younger, alkalic igneous rocks (alkaline basalts to basanites) exposed on northern Ellesmere Island. Mapping carried out for this study revealed the presence of abundant subalkaline igneous rocks on western Ellesmere Island. We interpret these units as an extension of the Schei Sills, a stratigraphically bound sequence of intrusions exposed along a ~ N-S belt on eastern Axel Heiberg Island. Samples from the Schei Sills and from the Middle Fiord Intrusive Complex (~ 20 km2, central Axel Heiberg Island) show Cu/Zr values above and below unity, consistent with complementary sulfide enrichment and removal, respectively, within these intrusive systems. The spatial association of the Schei Sills with the post-emplacement Eocene Stolz Thrust is noteworthy, as later thrusting associated with the Paleogene Eurekan Orogeny caused the uplift of deeper parts of the HALIP subvolcanic feeder system and associated wall-rock stratigraphy. Absolute Ir-group PGE contents are low throughout the HALIP; however, Pt-group PGE contents range widely among analyzed tholeiitic intrusive rocks. For example, relatively elevated Pt + Pd values of 10–30 ppb in samples from the Middle Fiord Intrusive Complex and the Schei Sills suggest heightened prospectivity in these two areas. In contrast, tholeiitic flood basalts in the Strand Fiord Formation and associated intrusions exposed in western Axel Heiberg Island (~ 95 Ma) exhibit Cu/Zr

This study illustrates the application of a geometric average integration of aeromagnetic, radiometric and satellite imagery data over a region prone to Cu‐bearing mineralization at Chahargonbad area in Kerman province of Iran. Processing aeromagnetic, radiometric and Advanced Spaceborne Thermal Emission and Reflection Radiometer satellite data can provide exploratory insights about favourable zones in association with porphyry‐type ore occurrences, which can be synthesized through a combination of knowledge‐ and data‐driven approaches as a geometric average and be represented in a mineral prospectivity map. The existence of known deposits in a prospect region can facilitate the investigation of significant exploratory footprints extracted from airborne data by calculating each indicator layer's weight by plotting a prediction–area curve accompanied by a concentration–area fractal curve. Among various indicators, the most important ones are determined based on derived weights from the prediction–area plots to be synthesized in a single Cu favorability map. To fulfil this aim, indicator layers from airborne geophysics (magmatic bodies, magnetic lineaments and potassium radiometry) and remote‐sensing data (alterations such as argillic, phyllic, propylitic and iron oxide along with geological lineaments) were prepared and evaluated using the known porphyry Cu mineralization by the simultaneous plot of the concentration–area fractal model and the prediction–area curve to attain the ore prediction rate and the relevant occupied area of each map for weight assignment of indicators. The geometric average prospectivity model was applied to synthesize the leading indicators, and the result was compared with a multi‐class index overlay map. This study's significance lies in improvement of the performance of the mineral prospectivity/potential mapping after running a geometric average by a higher ore prediction rate of 79%, which has occupied 21% of the area as potential zones for further mining investigations.

In this paper, we explore unsupervised cluster analysis to aid mineral prospectivity mapping (MPM) in two aspects: (1) to cluster geochemical data for MPM based on detailed analysis of evidence maps and (2) to explore coherence of spatial signatures at/around mineralized locations as well as outliers of geochemical data. To do so, a systematic procedure is proposed based on the Iterative Self-organizing Data Analysis Techniques Algorithm (ISODATA). Through this procedure, the detailed analysis of evidence maps in Hezuo–Meiwu district, Gansu Province, China, which portray five selected geochemical elements, showed that clusters with and without mineralized locations provide insight to weighing of each evidence. Finally, through the integration of evidence maps, the favorability score map yielded high AUC (> 0.80) for delineating various mineralized locations in the study area, which proves the efficacy of unsupervised cluster analysis as an aid to MPM. Moreover, the coherence of spatial signatures of known mineralized locations, which comprise a training dataset, is vital to data-driven MPM. Groupings of mineralized locations based on the ISODATA and visual inspection supported by PCs from principal component analysis imply that different deposit types may share the same or similar spatial signature and outliers in geochemical data may be potential training samples used for data-driven MPM. Mineralized locations of the same deposit type may show significant dissimilarity. However, this provides insights into selecting mineralized/non-mineralized locations for creation of training datasets. Interestingly, in the study area, major mineralized locations in zones divided by regional fault are clustered separately into two groups. This result not only proves that cluster analysis is effective for exploring the coherence of spatial signatures at/around mineralized locations, but it also justified our previous study, whereby we performed MPM by zones using machine learning algorithms.

The Yilgarn Craton, Western Australia is endowed with significant gold, nickel‑copper, Cu-Pb-Zn volcanic-hosted massive sulphide (VHMS) and iron ore deposits. Detailed knowledge of the spatial relationships between mineral systems and the crustal framework of the Yilgarn Craton may be powerful tools in the predictive exploration of undiscovered mineral systems. Both Nd and Hf isotopes have the potential to image crustal residence, mantle tapping structures, and juvenile input over both space and time. This study uses a recent compilation of Hf (1236 zircon analyses) and Nd (462 whole rock analyses) isotopes to image the architecture of the crust and compare this to the distribution of gold, nickel‑copper-platinum group elements (Ni-Cu-PGEs), Cu-Pb-Zn VHMS and iron ore deposits. Spatial correlation plots reveal a statistically significant relationship between Nd and Hf isotopic domains and the occurrence of gold, Ni-Cu-PGE, base metals, and iron confirmed by the coefficient of determination (R2) which measures how differences in metal occurrences can be explained by differences in the isotopic signature. Nickel occurrences show the strongest antithetic spatial correlation (R2 = 0.80) with Hf model ages, followed by gold (R2 = 0.58) and base metals (R2 = 0.35), which implies higher metal endowment in areas of more juvenile crust. In contrast, there is a significant positive spatial correlation (R2 = 0.49) between iron ore occurrence and older model ages. Isotopic data can also be plotted as Hf or Nd time-slices, where the strongest spatial correlation between gold, nickel, and base metal occurrence and juvenile input occurs at ca. 2700–2550 Ma. Generally, a model can be proposed where (1) base metals are more prevalent in juvenile crust because of its thinner nature, greater mantle input, high-heat flow, increased water-magma interaction; (2) iron ore is concentrated in regions of old, mature, and stable crust; (3) komatiite-hosted Ni-Cu-PGE systems are focused in juvenile rift zones at the edge of old crustal blocks; and (4) gold is also localised in juvenile crust at craton edges where several factors are localised, including orogenesis, occurrence of previously fertilised crust (i.e. Fe-rich lithologies, sanukitoids), favourable structures (potential inversion of rift structures), and ‘late’ alkaline magmatism. In gold, Ni-Cu-PGE, and base metal mineral systems, the ability of magmas to access higher crustal levels unimpeded appears vital in regional prospectivity and is itself a function of crustal configuration.

This paper reports an application of uncertainty visualisation of a regional scale (1:50 000) 3D geological geometry model to be involved in GIS-based 3D mineral potential assessment of the Xiangxibei lead-zinc mineral concentration area in northwestern Hunan District, China. Three-dimensional (3D) geological modelling is a process of interpretation that combines a set of input measurements in geometry. Today, technology has become a necessary part of GIS-based deep prospecting. However, issues of sparse data and imperfect understanding exist in the process so that there are several uncertainties in 3D geological modelling. And these uncertainties are inevitably transmitted into the post-processing applications, such as model-based mineral resource assessment. Thus, in this paper, first, a big-data-based method was used to estimate the uncertainty of a 3D geological model; second, a group of expectations of geological geometry uncertainty were calculated and integrated into ore-bearing stratoisohypse modelling, which is one of the major favourable parameters of assessment for Lead-Zinc (Pb-Zn) deep prospectivity mapping in northwestern Hunan; and finally, prospecting targets were improved.

Today’s era of big data is witnessing a gradual increase in the amount of data, more correlations between data, as well as growth in their spatial dimension. Conventional linear statistical models applied to mineral prospectivity mapping (MPM) perform poorly because of the random and nonlinear nature of metallogenic processes. To overcome this performance degradation, deep learning models have been introduced in 3D MPM. In this study, taking the Huayuan sedimentary Mn deposit in Hunan Province as an example, we construct a 3D digital model of this deposit based on the prospectivity model of the study area. In this approach, 3D predictor layers are converted from the conceptual model and employed in a 3D convolutional neural network (3D CNN). The characteristics of the spatial distribution are extracted by the 3D CNN. Subsequently, we divide the 22 extracted ore-controlling variables into six groups for contrast experiments based on various combinations and further apply the 3D CNN model and weight of evidence (WofE) method on each group. The predictive model is trained on the basis of the coupling correlation between the spatial distributions of the variables and the underground occurrence space of the Mn orebodies, and the correlation between different ore-controlling factors. The analysis of 12 factors indicates that the 3D CNN model performs well in the 3D MPM, achieving a promising accuracy of up to 100% and a loss value below 0.001. A comparison shows that the 3D CNN model outperforms the WofE model in terms of predictive evaluation indexes, namely the success rate and ore-controlling rate. In particular, the 1–12 ore-controlling factors selected in experiment 5 provide a significantly better prediction effect than the other factors. Consequently, we conclude that the Mn deposit in the study area is not only related to the stratum and interlaminar anomalous bodies but also to the spatial distribution of the faults. The experimental results confirm that the proposed 3D CNN is promising for 3D MPM as it eliminates the interference factors.

With the decrease in surface and shallow ore deposits, mineral exploration has focused on deeply buried ore bodies, and large-scale metallogenic prediction presents new opportunities and challenges. This paper adopts the predictive thinking method in this era of big data combined with specific research on the special exploration and exploitation of deep-earth resources. Four basic theoretical models of large-scale deep mineralization prediction and evaluation are explored: mineral prediction geological model theory, multidisciplinary information correlation theory, mineral regional trend analysis theory, and mineral prediction geological differentiation theory. The main workflow of large-scale deep resource prediction in the digital and information age is summarized, including construction of ore prospecting models of metallogenic systems, multiscale 3D geological modeling, and 3D quantitative prediction of deep resources. Taking the Lala copper mine in Sichuan Province as an example, this paper carries out deep 3D quantitative prediction of mineral resources and makes a positive contribution to the future prediction and evaluation of mineral resources.

This paper demonstrates knowledge-guided fuzzy logic modeling of regional-scale surficial uranium (U) prospectivity in British Columbia (Canada). The deposits/occurrences of surficial U in this region vary from those in Western Australia and Namibia; thus, requiring innovative and carefully-thought techniques of spatial evidence generation and integration. As novelty, this papers introduces a new weighted fuzzy algebraic sum operator to combine certain spatial evidence layers. The analysis trialed several layers of spatial evidence based on conceptual mineral system model of surficial U in British Columbia (Canada) as well as tested various models of evidence integration. Non-linear weighted functions of (a) spatial closeness to U-enriched felsic igneous rocks was employed as U-source spatial evidence, (b) spatial closeness to paleochannels as fluid pathways spatial evidence, and (c) surface water U content as chemical trap spatial evidence. The best models of prospectivity created by integrating the layers of spatial evidence for U-source, pathways and traps predicted at least 85% of the known surficial U deposits/occurrences in >10% of the study region with the highest prospectivity fuzzy scores. The results of analyses demonstrate that, employing the known deposits/occurrences of surficial U for scrutinizing the spatial evidence layers and the final models of prospectivity can pinpoint the most suitable critical processes and models of data integration to reduce bias in the analysis of mineral prospectivity.

The renewed quest to boost Nigeria’s dwindling reserves through aggressive search for oil and gas deposits in Cretaceous sedimentary basins has re-ignited the need to re-evaluate the hydrocarbon potentials of the Dahomey Basin. Aeromagnetic data are a low-cost geophysical tool deployed in mapping regional basement structures and determination of basement depths and sedimentary thickness in frontier basin exploration. In this study, high-resolution aeromagnetic (HRAM) data covering the Dahomey Basin Nigeria have been interpreted to map the basement structural configuration and to identify mini-basins favorable for hydrocarbon prospectivity. The total magnetic intensity grid was reduced to the equator (RTE) and edge detection filters including first vertical derivative (FVD), total horizontal derivative (THDR), tilt derivative (TDR) and total horizontal derivative of upward continuation (THDR_UC)) were applied to the RTE grid to locate the edges and contacts of geological structures in the basin. Depth to magnetic sources were estimated using the source parameter imaging (SPI) method. Data interpretation results revealed shallow and deep-seated linear features trending in the NNE-SSW, NE-SW, NW-SE and WNW-ESE directions. The SPI map showed a rugged basement topography which depicted a horst-graben architecture on 2D forward models along some selected profiles. Two mini-basins ranging in basement depths between 4.5 – 6.3km were mapped offshore of the study area. It appears the offshore Dahomey Basin holds greater promises for hydrocarbon occurrence due to the presence of thicker succession of sedimentary deposits in the identified mini-basins.

Rock properties in the subsurface are of major importance for evaluating the petroleum prospectivity of a sedimentary basin. The key rock properties to understand are porosity, density, temperature, effective stress, and pore pressure. These rock properties can be obtained or calculated when borehole data are available. However, borehole data are usually sparse, especially in frontier basins. We propose some simple rock-physics transforms for converting P-wave velocity to other rock properties. We found that these rock-physics transforms are predictive in the east and west sides of Campeche Basin. The proposed rock-physics transforms can be used to obtain laterally varying rock properties based on information derived from seismic data.

In recent years, various geological activities and different mineral prospecting and exploration programs have been intensified along the Red Sea hills in order to elucidate the geological maps and to evaluate the mineral potentials. This study is therefore aimed at testing the viability of using remote sensing and geographic information system (GIS) techniques for geological mapping and prospecting for gold mineralization in the area. The study area is located in northeast Sudan and covers an area of about 1379 km2. Different digital image processing techniques were applied to Landsat 8 Operational Land Imager image in order to increase the discrimination between various lithological units and to delineate wall rock alteration which represents target zones for gold mineralization. Image sharpening was performed to enhance the spatial resolution of the images for more detailed information. Contrast stretching was applied after the various digital processing procedures to produce more interpretable images. The principal component analysis transformations yielded saturated images and resulted in more interpretable images than the original data. Several ratio images were prepared, combined together and displayed in RGB color composite ratio images. This process revealed the existence of alteration zones in the study area. These zones extend from the northeast to the southwest in the acid meta-volcanic and silica barite rocks. The enhanced satellite images were implemented in the GIS environment to facilitate the final production of the geological map at scale 1:400,000. X-ray fluorescence analyses prove that selected samples taken from the wall rock alteration zones are gold-bearing.

This paper investigates the long-term dispersal of trace metals and their impact on the environment long after mine closure in the French Alps. Three statistical methods derived from modern mining (Exploratory Data Analysis, fractals and Sediment Quality Index) were applied to geochemical analyses of streambed sediments to produce mineral prospectivity maps. About 5% of the samples have a poor or marginal quality and may have an effect on biota. Positive anomalies are either related to the geological background (lithology, major tectonic contacts) or to ancient mining sites. The local impact of former mining was investigated on a medieval Pb–Ag district (Brandes; Pbmax ~8 000 mg kg−1), a small district mined during the 17th–19th c. (Peisey-Nancroix; Pbmax = 583 mg kg−1), and a major modern Pb–Ag mine (Macot-La Plagne; Pbmax ~ 3 200 mg kg−1).The mining heritage is still traceable in the northern French Alps. The anomalies observed at local scale are related to the volume of extracted ore rather than to the timing and duration of mining, suggesting that old mining sites still release trace metals over centuries and up to a thousand years. The statistical methods used provide a strong tool for archaeological prospection and environmental studies.

The North West Shelf (NWS) of Australia is a prolific hydrocarbon province hosting significant volumes of hydrocarbons, primarily derived from Jurassic and Cretaceous targets. A new regional, integrated geoscience study has been undertaken to develop insights into the paleogeography and petroleum systems of Late Permian to Triassic successions, which have been underexplored historically in favor of Jurassic to Cretaceous targets. Within the NWS study area, graben and half-graben depocenters developed in response to intracratonic rifting that preceded later fragmentation and northward rifting of small continental blocks. This, coupled with contemporaneous cycles of rising sea levels, brought about the development of large embayments and shallow, epeiric seas between the Australian continental landmass and outlying continental fragments in the early stages of divergence. Key elements of the study results discussed herein include the study methodology, the paleogeographic and gross depositional environment mapping, and the reservoir and source kitchen modeling. The study results highlight the presence of depocenters that developed within oblique rift zones due to regional Permo-Triassic strike-slip tectonics that bear compelling similarities to modern-day analogues. These intracratonic rift zones are well-known and prominent tectonic features resulting from mantle upwelling and weakening of overlying lithospheric crust, initiating the development of divergent intraplate depocenters. The comprehensive analysis of these depocenters from a paleogeographic and petroleum system perspective provides a basin evaluation tool for Triassic prospectivity.

Major mineral discoveries have declined in recent decades, and the natural resource industry is in the process of adapting and incorporating novel technologies such as machine learning and artificial intelligence to help guide the next generation of exploration. One such development is an artificial intelligence architecture called VNet that uses deep learning and convolutional neural networks. This method is designed specifically for use with geoscience data and is suitable for a multitude of exploration applications. One such application is mineral prospectivity in which the machine is tasked with identifying the complex pattern between many layers of geoscience data and a particular commodity of interest, such as gold. The VNet algorithm is designed to recognize patterns at different spatial scales, which lends itself well to the mineral prospectivity problem of there often being local and regional trends that affect where mineralization occurs. We test this approach on an orogenic gold greenstone belt setting in the Canadian Arctic where the algorithm uses gold values from sparse drill holes for training purposes to predict gold mineralization elsewhere in the region. The prospectivity results highlight new target areas, and one such target was followed up with a direct-current induced polarization survey. A chargeability anomaly was discovered wherein the VNet had predicted gold mineralization, and subsequent drilling encountered a 6 g/t Au intercept within 10 m of drilling that averaged more than 1.0 g/t Au. Although most of the prospectivity targets generated from VNet were not drill tested, this first intercept helps validate the approach. We believe this method can help maximize the use of existing geoscience data for successful and efficient exploration programs in the future.

The lower Silurian Qusaiba Shale is one of the major source rocks for Paleozoic oil/gas reservoirs in Saudi Arabia and recently considered a potential unconventional shale gas resource. The study aims to evaluate the reservoir heterogeneity and production potential of Qusaiba Shale through the integration of geological, geomechanical and fractures characteristics. Three lithofacies were identified in Qusaiba shale. Mineralogical composition resulted in variable amounts of quartz ranging from 39 to 40, 45–55 and 60–78% for Lithofacies-I, II and III, respectively. Inter-granular porosity of these lithofacies is very low; however, fractures along laminations, at angle with laminations, and few micro-faults enhance porosity up to 5–6, 2–3, and

With the depletion of mineral resources on land, seafloor massive sulfide deposits have the potential to become as important for exploration, development and mining as those on land. However, it is difficult to investigate the ocean environment where seafloor massive sulfide deposits are located. Thus, improving prospecting efficiency by reducing the exploration search space through mineral prospectivity mapping (MPM) is desirable. MPM has been used in the exploration for seafloor deposits on regional scales, e.g., the Mid-Atlantic Ridge and Arctic Ridge. However, studies of MPM on ultraslow-spreading ridges on segment scales to aid exploration for seafloor massive sulfide have not been carried out to date. Here, data of water depth, geology and hydrothermal plume anomalies were analyzed and the weights-of-evidence method was used to study the metallogenic regularity and to predict the potential area for seafloor massive sulfide exploration in 48.7°–50.5° E segments on the ultraslow spreading Southwest Indian Ridge. Based on spatial analysis, 11 predictive maps were selected to establish a mineral potential model. Weight values indicate that the location of seafloor massive sulfide deposits is correlated mainly with mode-E faults and oceanic crust thickness in the study area, which correspond with documented ore-controlling factors on other studied ultraslow-spreading ridges. In addition, the detachment fault and ridge axis, which reflect the deep hydrothermal circulation channel and magmatic activities, also play an important role. Based on the posterior probability values, 3 level A, 2 level B and 2 level C areas were identified as targets for further study. The MPM results were helpful for narrowing the search space and have implications for investigating and evaluating seafloor massive sulfide resources in the study area and on other ultraslow-spreading ridges.

Recognition and mapping of mineralization-related patterns in geochemical data is a key computational analysis to achieve a predictive model of prospectivity for mineral deposit occurrence. This contribution describes a spatio-geologically informed fuzzy classification (SGIFC) for portraying the spatial-frequency distribution of mineralization through integration of geochemical concentrations, 3D spatial properties, and geological knowledge contained in surface samples. A spatio-geological interaction model (SGIM) was defined to constitute an SGIFC by modulating fuzzy memberships in each iteration of standard fuzzy c-means (FCM) according to the incorporation of both spatial and geological inter-sample similarities. This strategy was adapted to the compositional nature of multi-elemental data and implemented by programming over packages supplied within the R language environment. A comparative experiment on soil samples collected in a porphyry Cu–Au system was subjected to understand how the SGIM affects standard memberships spatially, statistically, and geostatistically. Spatial autocorrelation analysis of fuzzy memberships through Moran’s I calculation and Monte Carlo simulation indicated that SGIFC leads to more robust spatially connected patterns compared to FCM models. Moreover, variogram analysis illustrated that SGIM orients the spatial continuity of mineralization-related memberships along the diffusion bearing of hydrothermal fluids across geological structures of the study area. Rock samples collected along trenches, as well as Cu volumetric productivities, were used as benchmarks to evaluate the integrity of the derived predictive models. The results reveal that the distribution pattern of mineralization-related memberships for SGIFC, compared to that of FCM, is more consistent with sub-outcropping and deep metallogenic realities and describes a more significant quantitative association with subsurface mineral content within the study region. The incorporation of SGIM into fuzzy classification has demonstrated the sufficiency to synthesize the comprehensive information of samples to predict effectively potential targets for follow-up exploration.

Investigating the timing, structural style, and development of multiphase extensional fault systems is essential for understanding rift basin evolution and for assessment of structural trap integrity. Borehole-controlled interpretation and analysis of two-dimensional and three-dimensional seismic data sets from the eastern Dampier subbasin indicate that a northeast-trending basement weakness zone was subjected to west-northwest–east-southeast oblique extension in the latest Triassic–late Middle Jurassic, resulting in systematic segmentation of the Rosemary fault system (RFS). Temporal stress change during Cretaceous north-south extension produced complex fault systems along the RFS, including (1) east-west–trending isolated faults with maximum displacement close to their center; (2) east-west–trending abutting faults, which initially nucleated as isolated faults, later abutted against the main structure, showing large displacement accruement on the composite fault; and (3) northeast-southwest–trending splay faults characterized by systematic left-stepping segmentation, with maximum displacement occurring at the point where the splay faults deviate from the main structure. In the Miocene, the RFS was locally reactivated by northwest-southeast compression in the northeastern part of the fault system, developing a compressive fault-propagation fold at the upper tip of the inverted extensional fault. This study suggests that the style of basin boundary fault reactivation depends largely on preexisting structures and temporal stress changes. The fault reactivation style is also a significant factor in influencing basin architecture, sediment distribution, fault linkage processes, and petroleum basin prospectivity.

Azerbaijan is one of the oldest oil and gas provinces, where more than 2 bln tons of oil have been extracted over more than a century. At present, the oil production is declining and mainly determined by production from the Azeri-Chirag-Guneshli offshore block (AChG). Compared to oil, the opportunities for further growing natural gas reserves and production are very promising. For the latest years, a number of large gas condensate fields have been discovered in the deep-water part of South Caspian Sea, such as Shakh-Deniz, Apsheron, Umid. There are a number of prospects that have not yet been drilled in this part of the sea basin. The paper assesses their prospectivity, substantiates the priority exploration targets and, on the basis of the statistical analysis of the quantitative gas/oil ratio data for many other Azerbaijanian and world basins, an attempt is made to assess the reserves in the prospects. The total recoverable oil reserves in Azerbaijan are estimated at 3.5 bln tons, of which slightly above 2 bln tons have already been extracted. Based on the statistically estimated ratio between the volumes of gas and oil in various basins of the world, including Azerbaijan, the total possible natural gas reserves in Azerbaijan are estimated at about 4 trillion m3 . This is in agreement with the other available estimates. Of this volume of natural gas, 0.85 trillion m3 has already been extracted, and the approved geological reserves are estimated at 2.55 trillion m3 . Almost 83% of the extracted natural gas belonged to offshore fields. This trend will continue in the future, and, moreover, will be strengthened due to large volumes of gas condensate accumulations in the deepwater part of the basin. In this part of the basin, the most attractive prospects are Mashal, Shafag, and Israfil Huseynov, total reserves of which are expected at 0.6 trillion m3 of natural gas.

Basing on generalization of large actual material on complex investigation of diamond its characteristic in Upper Paleozoic and Mesozoic sedimentary thick layers of the Siberian platform is provided. Special attention is paid to the Central-Siberian sub-province, where it is convincingly shown that the area of development of individual diamond macro-associations is limited by a specific diamondiferous region, within which complexes of different in age terrigenous and coastal Upper Paleozoic and Mesozoic sediments are developed. Identified in some diamondiferous regions proximity of typomorphic features of diamonds in sedimentary thick layers of these ages testifies about formation of these collectors due to washout of more ancient productive layers or Middle Paleozoic primary sources. Polygeny of mineralogical associations of diamonds from different in age placers within some diamondiferous regions was noted, which may be successfully used when forecasting and prospecting primary sources of the mineral. Diamond and its tipomorphic features are one of the main criteria for forecasting and searching for root sources Materials on heterogeneity of the Viljujsko-Marhinska zone of deep faults with respect to productive kimberlite magmatism, which is associated with areals of the hard consolidated basement of the Archean age (Botuobinskij and Tjungskij cratons) obtained in the framework of medium scale forecast and search studies of typomophic features of diamonds have an important practical conclusion. The results of a study of the typomorphic features of diamonds from the most well-studied kimberlite bodies indicatle heterogeneities in the structure of the upper mantle even within the Central Siberian diamondiferous subprovince, especially with respect to the distributionof focirly rare coloured crystals (II, III and IV varieties) presumably of ecbgite genesis, associated with deep diamandiferous xenoliths of various composition. These varieties of diamonds are rare and accessory in kimberlite bodies, however their findings in rashes even in a single amount, can serve as a basis for localizing the territory of the search for indigenous sources. The analysis of typomorphic features of diamonds indicates the high prospectivity of placer oceurrences of the Central Siberian diamondiferous pronnce for the discovety of new highly productive kimberlite pipes.

Neoproterozoic sedimentary basins are increasingly gaining hydrocarbon exploration attention globally following results of significant discoveries in these basins as a result of long, consistent and focused research and exploration efforts. The hydrocarbon prospectivity of the unexplored Mesoproterozoic–Early Paleozoic Voltaian basin is reviewed relative to global Neoproterozoic basins. Like the Voltaian basin of Ghana, global Neoproterozoic basins have experienced similar geological event of glaciation with accompanying deposition of marginal–shallow marine carbonates and associated siliciclastic argillaceous sediments. These carbonates and argillaceous sediments coupled with deep anoxic depositional environments, favored the preservation of organic matter in these sediments and carbonates globally making them source rocks and in some cases the reservoir rocks as well, to hydrocarbon occurrence. The hydrocarbon prospectivity of the Voltaian is highly probable with Neoproterozoic basins of similar geologic analogies, Amadeus basin, Illizi basin, the Tindouf and Taoudeni basins of the WAC, having proven and active petroleum systems with some listed as world class oil/gas producing basins together with other Neoproterozoic basins like South Salt Oman basin, Barnett shales and giant gas reserves of southwestern Sichuan basin of China.

We have determined the potential geothermal prospectivity of clean sandstones in the Tubbergen Formation (Late Carboniferous) of the Twente area (eastern Netherlands). We were motivated by the prevailing paradigm that in the Netherlands geothermal power can only be harvested economically through large, expensive installations producing high volumes from high-quality aquifers located between approximately 1500 and 2500 m. No such aquifers are present in Twente. We found that heat production is economically feasible from the Tubbergen Formation sandstones by producing smaller volumes from smaller, highly efficient installations that can be developed at considerably lower cost. Our reinterpretation of publicly available seismic and well data shows that potentially suitable sandstones occur over the whole area with thicknesses of up to 50 m, porosities reaching 20%, and permeabilities reaching 300 mD. The Tubbergen Formation is approximately 400–700 m thick in the study area and contains approximately 60% sandstone. The top reservoir reaches an approximate 1500 m depth in the southwest, and the base reaches some 4300 m in the northeast of the study area. The temperature is expected to range between 60°C and 140°C depending on the depth. The Carboniferous is densely faulted with a block size of approximately 3 × 4 km, each block being a potential target for geothermal development. To determine the economic feasibility, we performed an economic screening for a hypothetical location north of the city of Enschede and backed this up by reservoir simulations. The geologic risks of the Tubbergen Formation are the lack of permeability, reservoir thickness, and lateral extent of the reservoirs. In our judgment, the chance of economic success for this site is 50% or more. Upside potential is present in numerous fault blocks in the study area and in adjacent areas where suitable sandstones with similar porosity and permeability at greater depth and higher temperatures are expected.

North China (NC) is a region recording a long and complex geological history spanning from the Archaean to Cenozoic. This included magmatism, sedimentation, metamorphism, and deformation, demonstra...

The Palaeozoic basin of Jordan and Iraq occupies the NW part of the Arabian Plate. The Lower Palaeozoic succession is the most under-explored succession in Iraq, particularly in western Iraq where it is considered the most promising target for future exploration. The western Iraqi subsurface and Jordan geology are characterized by similar major chrono-stratigraphic rock units. In western Iraq, the Akkas-1 well is the only gas and condensate discovery in sandstone reservoirs of Early Silurian and Late Ordovician age. Lower Silurian sandstones of the Akkas Formation are an oil reservoir characterized by a mean porosity of 6.5% and permeability of 0.2mD. Underlying Upper Ordovician sandstones of the upper part of the Khabour Formation are also reservoir, but for sweet gas and condensate. The latter are comparable to both the Risha and Wadi Sirhan discoveries in Jordan. Several deeper potential sandstone reservoirs (of older Ordovician and Cambrian ages) are also present across the region. Equivalent Ordovician age Jordanian reservoirs are primarily developed in homogeneous, highly mature quartz arenites of storm-dominated clastic-shelf stratigraphies. Within the Risha Field and the Wadi Sirhan area, are also end-Ordovician (Hirnantian) glaciogenic and periglacial sandstones with more variable reservoir quality characteristics compared to the underlying quartz arenites. These often comprise highly immature arkoses (as diamictites) that provide a mineralogically much less stable assemblage in which there is a possibility of developing secondary porosity. Sedimentological and XRD mineralogical studies suggest that diagenesis is an important factor in developing of reservoir quality. Nevertheless, reservoir quality is a major exploration risk where burial was significant that led to quartz overgrowth and clay cementation. It is notable that some sandstone reservoirs have chlorite-clay coatings, which prevented formation of the quartz overgrowth and preserved good reservoir quality. The widespread occurrence of associated source and seal rocks together with the proven and potential reservoirs, suggests that Lower Palaeozoic prospects below the deserts of western Iraq are promising targets for future hydrocarbon exploration.

Tanzania, like other East African countries, is seeking to increase its hydrocarbon discoveries from both onshore and offshore sedimentary basins. Although the Tanga onshore basin has the potential of adding to the hydrocarbon reserve of the country, it has very scanty literature to guide preliminary investigations into the basin prospectivity. This review seeks to highlight the petroleum system elements within the basin and how worthy it is exploring for its hydrocarbons potential. The general geology of the basin seems to have characteristics of a complete petroleum system with dolomitic limestone as source rocks and an obvious shale source rock and evidences of fossils and oil seepage around Kivundo River, although further research is needed to validate this assumption. Feldspathic sandstones are present to serve as a reservoir to economic hydrocarbon reserves. The basin has suitable thickness to provide the needed temperature and pressure for thermal maturity of any existing organic matter (OM) and to expel them from their various ‘kitchens’. Brittle structures are available to facilitate the migration of expelled kerogens. Structural straps are available via micro-folds and faults, to ensure accumulation of economic quantities that could be explored and exploited at profit. Also, the Tanga onshore basin has geological analogies that are similar to other basins’ hydrocarbon discoveries including that in Rovuma, Morondava and Songo Songo basins which are to the south of Tanga onshore basin.

Актуальность. Абшеронский нефтегазоносный район, где были проведены исследования, является одним из продуктивных в Азербайджане. Цель поисково-разведочных работ в основном заключается в увеличении добычи углеводородов, а это достигается выявлением новых нефтегазоносных объектов. С этой точки зрения в антиклинальном поясе Хали‒Нефт Дашлары в разрезе палеоген-миоценовых отложений выявление залежей, связанных с антиклинальными и неантиклинальными типами ловушками, имеет важную практическую особенность и это однозначно сыграет немаловажную роль в повышении добычи нефти и газа в республике. Наши исследования были проведены по определяющим нефтегазоносность критериям: геотермическим, литофациальным, тектоническим, палеотектоническим и т. д., по стратиграфическому разрезу палеоген-миоцен и плиоцена для определения новых объектов. Цель: определить с геотермической точки зрения в какой зоне нефтегазообразования в настоящее время находятся отложения продуктивной толщи и, в соответствии с этим, уточнить перспективность зоны, а также исследовать распространенность неантиклинальных ловушек в связи с палеотктоническими особенностями и конседиментационным развитием зоны. Объекты: отдельные структуры, представляющие антиклинальную зону Хали‒Нефт Дашлары, свиты нижнего отдела продуктивной толщи. Методы. Изменения общей мощности и песчанистости отложений продуктивной толщи в исследуемых структурах были проанализированы в локальном и региональном направлениях, были построены соответствующие диаграммы, отражающие закономерности изменения мощности и песчанистости по свитам. Наряду с этим были построены палеопрофили, отражающие палеотектоническое развитие структур антиклинальной зоны Хали‒Нефт Дашлары. Результаты. Построение графика скорости осадконакопления и, в связи с этим, анализ данных, изучение палеотемпературных условий Пираллахи-Келькорской впадины и проведенный анализ позволяют определить время нахождения отложений как продуктивной толщи, так и нижележащих отложений миоцена, палеогена и мезозоя в главной зоне нефтегазообразования, а также сопоставить главные этапы миграции со временем образования структур в пределах данной территории. Результаты всех исследований, проведенных в этом направлении, позволяют утверждать, что область исследований и ее окрестности также являются перспективными с точки зрения нефтегазоносности. Relevance. The study was carried out in Absheron oil and gas region, which is one of the productive in Azerbaijan. The aim of implemented researches consists in increasing hydrocarbon production which is achieved by identifying new oil and gas reservoirs within deposit. From this point of view reservoirs associated with anticlinal and non-anticlinal types of traps within the Khali‒Neft Dashlari anticlinal belt were identified. The approach was based on section Paleogene-Miocene sediments, the identification of reservoirs was associated with anticlinal and non-anticlinal types of traps. Such approach has an important practical feature and this will definitely play an important role in increasing oil and gas production in the republic. Our studies were carried out according to the criteria determining oil and gas potential, such as geothermal, lithofacial, tectonic, paleotectonic, etc. Estimations and attempts to identify new reservoirs were carried out along the stratigraphic profile of the Paleogene-Miocene and Pliocene ages. The main aim of the research is to determine, from geothermal aspect, present location of the productive series deposits within the oil and gas generation zone and, in this relation, clarify prospectivity of the zone, as well as to investigate the prevalence of non-anticline traps in association with paleotectonic properties and syndepositional evolution of the zone. The main aim of the research is to determine, from geothermal aspect, present location of the productive series deposits within the oil and gas generation zone and, in this relation, clarify prospectivity of the zone, as well as to investigate the prevalence of non-anticline traps in association with paleotectonic properties and syndepositional evolution of the zone. Research area: individual structures representing Khali‒Neft Dashlari anticline zone, Lower productive series suites. Methods. Changes in total thickness and sandiness of the productive series deposits within the structures under investigation were analyzed at local and regional scales, the corresponding diagrams reflecting the patterns of changes in thickness and sandiness of individual suites were plotted. Paleoprofiles reflecting the paleotectonic evolution of the structures of the Khali‒Neft Dashlari anticline zone were constructed. Results. Construction of the deposition rate diagram and, in this regard, the data analysis, study of the paleotemperature environment of the Pirallahi-Kelkor depression and the analysis performed allow us to determine the terms of staying of both the productive series and the underlying Miocene, Paleogene and Mesozoic sediments within the main oil and gas formation zone, as well as to compare the major migration stages with the structure formation periods within a given territory. The results of all studies carried out in this direction allow us to state that the research area and its environs are also promising from the point of view of oil and gas potential.

Geochemical exploration for rare metals, specifically lithium, is essential on a regional scale based on their demand and consumption in recent years. The main objective of this study was to delineate lithium anomalies in regional exploration utilizing the geochemical mapping prospectivity index (GMPI), staged factor analysis (SFA), and a concentration-number (C-N) fractal model based on stream sediments. The case study area is 26000 km2 and is located in the Khorasan Razavi province (NE Iran). In addition, rock samples were used to validate the Li anomalies identified. Results derived via the SFA show that Li was located on a factor denoted as F1-3 with Be, Cs, F, Nb, Sn, Th, U and W, which was used for calculation of the GMPI values. The GMPI data were classified by the C-N fractal method for determination of the Li anomalies. The main anomalies with GMPI ≥ 0.7 and Li ≥ 48 ppm were situated in the SE, SW, north and south parts of the study region. Li grades of rock samples were categorized by the C-N fractal technique for validation of F2-2 anomalies using a log-ratio matrix. The main anomalies were correlated with related lithological units of Li mineralization types. This correlation indicates that the main GMPI–Li anomalies are associated with granitic–pegmatitic units in the central and SE parts, and overlap with clay minerals in the northern and southern sectors of this region. There is good potential for Li mineralization as demonstrated by this hybrid method.

This paper introduces the concept of geodata science-based mineral prospectivity mapping (GSMPM), which is based on analyzing the spatial associations between geological prospecting big data (GPBD) and locations of known mineralization. Geodata science reveals the inter-correlations between GPBD and mineralization, converts GPBD into mappable criteria, and combines multiple mappable criteria into a mineral potential map. A workflow of the GSMPM is proposed and compared with the traditional workflow of mineral prospectivity mapping. More specifically, each component in such a workflow is explained in detail to demonstrate how geodata science serves mineral prospectivity mapping by deriving geoinformation from geoscience data, generating geo-knowledge from geoinformation, and allowing spatial decision-making by integrating geoinformation and geo-knowledge on the formation of mineral deposits. This review also presents several research directions for GSMPM in the future.

Exploration success at Breagh demonstrates that western parts of the Mid North Sea High area are prospective despite the absence of an Upper Permian (Rotliegend Group) Leman Sandstone Formation reservoir and source rocks belonging to the Upper Carboniferous Westphalian Coal Measures Group. Detailed seismic and well interpretation shows that the Breagh trap was a long-lived footwall high, the prospectivity of which was enhanced by Variscan folding and uplift, leading to the truncation (subcrop) of Lower Carboniferous reservoirs beneath the Base Permian Unconformity. Its drape (supra-crop) by Upper Permian (Zechstein Super Group) evaporites creates the seal. The complexity of its overburden means that an accurate picture of the Breagh structure only emerges after accurate depth-conversion that takes the effects of the Mesozoic graben into account. Pronounced easterly tilting during the Cenozoic affected the area and controlled gas migration into the structure from palaeostructures lying to the east. However, evidence that Breagh is not filled to spill point (underfill) suggests that charge limitation remained an issue. The study demonstrates that a poorly-documented and under-explored Lower Carboniferous play exists in Southern North Sea, which relies upon careful structural mapping and basin modelling to be undertaken for the play to be understood and its further potential to be realized. Thematic collection: This article is part of the Under-explored plays and frontier basins of the UK continental shelf collection available at: https://www.lyellcollection.org/cc/under-explored-plays-and-frontier-basins-of-the-uk-continental-shelf

The UK Rockall, located to the west of Scotland and the Hebrides, is a frontier petroleum-bearing basin. Exploratory drilling in the basin took place over a quarter of a century (1980–2006), during which time a total of 12 wells were drilled, leading to the discovery of a single, subcommercial gas accumulation. We argue that the basin, which has seen no drilling activity for more than a decade, has not been sufficiently tested by the existing well stock. We examine the reasons for the absence of key Jurassic source rocks in the UK Rockall wells, which are widely distributed elsewhere on the UK Continental Shelf (UKCS), and argue that their absence in the wells does not preclude their existence in the basin at large. An evaluation of the Permian–Early Eocene successions, based upon the seismic interpretation of new 2D seismic data, has been integrated with legacy data and regional evidence to establish the potential for source, reservoir and sealing elements within each interval. Finally, we look at the future for exploration in the UK Rockall and suggest a way forward in the drilling of a new joint governmental–industry test well that may help to unlock the exploration potential of this under-explored, yet prospective, basin. Thematic collection: This article is part of the Under-explored plays and frontier basins of the UK continental shelf collection available at: https://www.lyellcollection.org/cc/under-explored-plays-and-frontier-basins-of-the-uk-continental-shelf