Natural Resources Research最新文献

Groundwater is a vital renewable natural resource that largely supports the agriculture sector, especially in semi-arid climate of hard rock. However, the over-exploitation and inadequate recharge of groundwater in crystalline granitic terrains have depleted the shallow aquifer systems constraining the groundwater to be sporadically distributed in deep fractures. Therefore, tracing bedrock fractures becomes important, but the overlying thick pile of unsaturated saprolite layer presents a challenge to map them due to geophysical ambiguity. Currently, most studies have been done at laboratory scale, while bedrock fractures at natural field conditions are rarely attended as evidenced by numerous failures of borehole drillings in semi-arid hard rock terrain. To trace saturated bedrock fractures at natural field sites, we performed a multi-disciplinary experiment comprising hydro-geological insights, social information, remote sensing, gradient resistivity profile (GRP), vertical electrical sounding (VES) and electrical resistivity tomography (ERT) followed by exploratory borehole drillings, and hydro-chemical source speciation in a semi-arid, crystalline granitic terrain in southern India. The results showed (1) GRP as a precursor records the signatures of saturated bedrock fractures qualitatively, (2) least square inversion models of ERT demarcate distinct litho-units and saturated bedrock fractures, (3) exploratory borehole drilling shows saturated bedrock fractures at 49–54 m and 63–67 m depth designated with high yield (Q = 3382 lph), which compare well with electrical imaging results, and (4) hydro-chemical source speciation with dominated alkali-feldspar (albite) weathering confirmed groundwater from bedrock fractures, which supplemented the geophysical anomalies. These observations led to a practical step-by-step field guide for tracing deep-seated bedrock fractures in geologically similar semi-arid regions.

In the context of mining exploration, local earthquake tomography serves as a valuable complementary tool, applicable across varying scales from greenfield to brownfield projects. Nevertheless, interpreting body-wave velocity anomalies within tomographies poses a significant challenge, which largely depends on the expertise of the analyst and the availability of information. Addressing this challenge, this paper proposes a geostatistical analysis to effectively compare and enhance the information extracted from tomographies ranging from lower to higher resolutions. The data utilized in this study correspond to the tomographic inversion values of Mantos Rojos (MR) and Radomiro Tomic (RT) porphyry copper deposits situated within the Chuquicamata District in northern Chile. MR has a resolution of 2 × 2 km², comparatively lower than RT’s resolution of 1 × 1 km², yet both share the same spatial zone. This study evaluated the discernment capabilities of lower-resolution tomography (MR) in comparison to its higher-resolution counterpart (RT) using turning bands simulation. The simulated Vp/Vs values of MR were compared against RT seismic tomography data. Visual validation revealed that simulated Vp/Vs values from P- and S-wave velocity values of MR can identify the low Vp/Vs anomalies (< 1.7). Moreover, spatial analysis compared the experimental variograms for MR realizations and for RT values in preferential directions for Vp/Vs ratios, finding a correspondence between both spatial tools. Finally, geological validation was carried out by comparing the simulation results with geological maps of the study area and copper grades obtained through drilling campaigns provided by CODELCO, where spatial patterns indicative of mineralization and larger-scale geological features like the West Fault were identified. Our research has practical implications because, through geostatistical simulations, the grid dimensions of seismic tomography of MR can be reduced and still identify low Vp/Vs anomalies within the area of study, being consistent with the lower-resolution validation grid of RT. Our findings demonstrate the efficacy of geostatistical methods in enhancing exploration decision-making by providing insights into subsurface geological features and their relationship to mineralization. This approach not only improves the efficiency and success rate of mineral exploration projects but also minimizes environmental impact by allowing for more targeted and informed exploration activities.

As mining depth increases, the temperature of coal seams increases gradually, which increases the risk of spontaneous coal combustion in goaf areas. This paper uses a programmed temperature rise experiment to analyze the oxidation combustion characteristics of high ground temperature coal and calculates the oxidation kinetic parameters and limit characteristic parameters. The results show that, above 100 °C, the ratios C₃H₈/C₂H₆ and C₂H₄/C₂H₆ change with the same trend. The CO and CO₂ release rates, oxygen consumption rate, heating rate and heat release intensity are positively correlated with the ground temperature. There is a good exponential relationship between the release rate of CO and CO₂ and the coal temperature. The activation energy increases and then decreases as the oxidation temperature increases (above 100 °C). In the later stage of low-temperature oxidation, the higher the ground temperature is, the lower the activation energy, the more active the organic active groups and the more violent the oxidation reaction. As the oxidation temperature increases, the lower-limit oxygen concentration (C_min) and the minimum floating coal thickness (h_min) increase and then decrease, and the high ground temperature reduces the temperature at which the maximum is reached. With increasing ground temperature, h_min and C_min increase, and the maximum air leakage intensity decreases. The research results provide a theoretical basis for the prevention and control of spontaneous coal combustion in high ground temperature coal seam mining in deep mines.

The pore–fracture structure of deep coal deposits is highly important for the potential evaluation, investigation, and utilization of deep coalbed methane resources. This study used methods such as low-pressure CO₂ adsorption, low-temperature N₂ adsorption, high-pressure mercury intrusion porosimetry, scanning electron microscopy, and optical microscopy to describe the pore–fracture structure of deep coal reservoirs at multiple scales and to discuss the development features, complexity, and influence on permeability of the pore–fracture structure of coal reservoirs. The results showed that there were significant differences in the pore volume and specific surface area (SSA) of the coal specimens with respect to the distribution of pore diameters. The micropore volume and SSA accounted for the largest proportions (85.93% and 98.63%, respectively). The more moisture and fixed carbon content there were in coal, the larger the micropore volume was. The higher the yields of ash and volatile matter were, the smaller the micropore volume was. The larger the pore radius in coal was, the greater the fractal dimension was. Besides, within their respective pore size sections, as the fractal dimension increased, the pore volume gradually decreased. As the vitrinite content increased, the fracture aperture and surface density gradually increased. As the fracture aperture increased, the fracture fractal dimension decreased, while the fracture tortuosity increased. Compared with shallow coal seams, the fracture aperture of deep coal seams showed a decreasing trend, while the pore volume showed an increasing trend.

Witwatersrand-type gold deposits in South Africa are generally amenable to cyanidation due to their free-milling nature. However, the relatively easy-to-process gold ores have been mostly depleted, and the remaining ores are of low-grade combined with semi-refractory properties. Here, we use an integrated approach to understand the mineralogical and textural characteristics of the Witwatersrand-type gold ores and to explore the effectiveness of glycine-leaching gold recovery. Analysis of sulfide minerals using 3D micro-X-ray computed tomography data shows these minerals can be used as predictive indicators for feed gold grade as they either co-exist and/or encapsulate gold. Primary experimental results demonstrate that alkaline glycine can recover > 80% Au in 100 hours at ambient temperatures. Glycine thus holds promise for gold recovery of low-grade free-milling and semi-refractory Witwatersrand-type gold ores. We also note that the presence of carbonaceous matter in ores, such as in the Black Reef orebody, adversely affects gold recovery. Ore blending may therefore be a suitable option to remediate poor gold recovery. Lastly, we demonstrate that stochastic simulations and data analytics can help augment primary experimental data to estimate uncertainty, providing a better understanding of experimental results, and thus providing future research directions.

Lithological mapping is an effective tool for geological surveys and mineral exploration. However, it faces challenges in identifying complex rock types and improving classification accuracy. We mapped lithological units in the Karamaili ophiolite-mélange belt of Xinjiang using integrated machine learning algorithms, including artificial neural network (ANN), Mahalanobis distance (MD), support vector machine (SVM), and random forest (RF). These algorithms were utilized to process remote sensing datasets acquired by the Sustainable Development Science Satellite 1 Thermal Infrared Spectrometer (SDGSAT-1 TIS), Landsat-8 Operational Land Imager (OLI), and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER-GDEM). The results indicated that the overall accuracies of ANN, MD, SVM, and RF were 68.87%, 78.98%, 93.4%, and 98.36%, respectively. The SVM and RF effectively mapped the lithological units. The SDGSAT-1 TIS data helped to identify mafic–ultramafic and feldspar-rich rocks, while Landsat-8 OLI helped to successfully delineate granitoid and complex lithologies. The ASTER-GDEM data helped improve mapping accuracy by providing detailed topographic information. Thus, this study confirmed the efficacy of the implemented approaches to delineate mineralization zones and to discriminate lithological units. This study provides detailed geological data for lithological mapping and serves as a significant reference for geological surveys and environmental monitoring.

Geophysical exploration for disseminated chromite deposits has always been challenging because the ore body does not exhibit significant geophysical anomalies. An understanding of petrophysical rock parameters can make the interpretation of geophysical data more accurate. The spectral induced polarization (SIP) method emerged as a promising technique to understand the electrical and petrophysical properties of rocks. In the present study, we tried to acquire the low frequency (0.01–1 kHz) spectral nature of chromite host rock samples, including harzburgite, dunite, and serpentinite, to understand their petrophysical properties. A double Cole–Cole (CC) model was adapted for the interpretation of SIP data. The results confirmed that the chargeability (m) and relaxation time (τ) for ferrochromite were (0.61) and (2.42 s), respectively, and for serpentinized rocks (0.40) and (1.86 s). These values were sufficient to produce anomalies with respect to background. Further, ferrochromite samples exhibited higher resistivity (~500,000 Ω m) with respect to harzburgite, dunite, and serpentinite. The serpentinized rocks showed the highest magnetic susceptibility (3.5 × 10⁻³ SI) followed by harzburgite (2.93 × 10⁻³ SI), ferrochromite (2.60 × 10⁻³ SI) and dunite (0.96 × 10⁻³ SI). The ferrochromite rocks showed the highest density (3.9 g/cm³), followed by harzburgite (3.5 g/cm³), dunite (3.02 g/cm³), and serpentinized rocks (2.7 g/cm³). Acquired results can be considered while using geophysical data to increase accuracy. This study contributes to understanding the electrical and petrophysical parameters of chromite deposits and their host rocks.

Accurate assessment of in situ fluid occurrence and content in complex shale reservoirs is crucial for effective resource evaluation and shale oil extraction. Laboratory tests on placed samples often lead to misestimations due to movable fluid loss. Low-field nuclear magnetic resonance (NMR) technology, which eliminates the need to crush cores for pyrolysis experiments, is emerging as a vital tool for studying shale pore fluids. Simultaneously, mobile full-diameter core (MFDC) NMR at wellsite is advancing rapidly, allowing for the first-time testing of cores immediately after extraction. However, research in this field remains limited. This study employed an innovative laboratory oil–water restoration technique alongside two-dimensional (2D) transverse (T₁) – longitudinal relaxation time (T₂) NMR and wellsite MFDC to evaluate the in situ fluid content in the lower first member of Cretaceous Tengger (K₁bt₁) and Aershan (K₁ba) Formations of the Wuliyasitai Depression, Erlian Basin. Our findings demonstrate that the 2D T₁–T₂ NMR technique effectively detected various hydrogen-containing components in shale oil reservoirs. Combined with quantitative analysis, it revealed the dynamic characteristics of oil–water signals during restoration, establishing a reliable method for assessing shale oil–water content. The multistage Rock-Eval (MRE) pyrolysis method strongly correlated with the 2D NMR results, confirming the reliability of NMR. Due to maturity-related variation in shale oil composition, the MRE pyrolysis results of the lower K₁bt₁ and K₁ba shales exhibited a different linear correlation with the 2D NMR data of as-received (AR) state shale, prompting adjustments to the NMR calibration coefficients for lower K₁bt₁ shale. The total oil content of the in situ fluid state shale was calculated to be 1.9582 and 3.2489 times greater than that of the AR state for the lower K₁bt₁ and K₁ba formations, respectively. The laboratory-measured oil content of the in situ state shale aligned well with MFDC NMR results, indicating that integrating laboratory oil–water restoration techniques with NMR provides a more effective and accurate representation of in situ fluid occurrence and content. Furthermore, the empirical S₁-corrected model developed for lower K₁bt₁ and K₁ba shales in the Erlian Basin holds potential for broader application in shale oil operations. Our research offers valuable insights into evaluating in situ fluids in shale oil reservoirs.

The Pokiok Plutonic Suite (PPS) lies within the southern segment of New Brunswick's Central Plutonic Belt, Canada. The PPS exhibits significant Devonian intrusive events, including four main phases, namely the Hartfield Tonalite, the Hawkshaw Granite, the Skiff Lake Granite, and the Allandale Granite, hosting notable intrusion-related W–Mo–Sb–Au deposits. This study aimed to identify potential exploration targets for intrusion-related W–Mo–Sb–Au deposits using knowledge-driven mineral prospectivity mapping (MPM) techniques. Model- and judgment-related uncertainties undermine the reliability of knowledge-driven MPM. This study adopted a multifaceted approach, combining the mineral systems approach, parsimonious weighting methods, Monte Carlo simulation (MCS), and a risk–return analysis, to mitigate the effects of these uncertainties on MPM. We employed three multi-criteria decision-making systems, namely MCS-based Best Worst Method (BWM) with Measurement Alternatives and Ranking according to the Compromise Solution (MARCOS) (MCS–BWM–MARCOS), MCS-based Full Consistency Method (FUCOM) with MARCOS (MCS–FUCOM–MARCOS), and MCS-based Level Based Weight Assessment (LBWA) with MARCOS (MCS–LBWA–MARCOS), for MPM, with MCS–LBWA–MARCOS exhibiting the highest accuracy. The risk–return analysis was employed to interpret the results of our models. Low-risk, high-return cells reduced the search space for mineral exploration by ~ 15%, while predicting ~ 73% of the known intrusion-related W–Mo–Sb–Au occurrences. The methodology applied herein allows for a more confident selection of exploration targets using knowledge-driven MPM.

Coalbed methane primarily exists as adsorbed gas within the microscopic pores and fractures of coal. However, the complex pore structure of deep coal seams and its quantitative relationship with methane adsorption capacity remain unclear. This study investigated nine samples from a coal seam in the Ningwu Basin, representing different burial depths, including five middle-shallow and four deep burials. This was accomplished through a series of experiments, including high-pressure mercury injection (HPMI), low-temperature nitrogen adsorption (LTGA–N₂), low-pressure carbon dioxide adsorption (LPGA–CO₂), and high-pressure (30 MPa) methane isothermal adsorption (HPGA–CH₄). The study revealed the characteristics of the pore structure in deep coal seams and their differences compared to those in middle-shallow coal seams. Moreover, it clarified the mechanism by which the pore structure influences CH₄ adsorption capacity. Given the differences in methane adsorption mechanisms at various pore scales, a novel method for quantitatively assessing the methane adsorption capacity using pore structure parameters is proposed. The results showed that the micropore pore volume and specific surface area of the deep coal seam were significantly higher than those of the middle-shallow coal seams. In contrast, the development of mesopores and macropores was relatively limited. The CH₄ adsorption capacity of a coal seam was calculated using pore structure parameters across multiple scales, considering the coexistence of two-dimensional “filling adsorption” and three-dimensional “monolayer adsorption” mechanisms. The calculated capacity V_L’ closely matched the measured value of V_L, with error of less than 10%. The degree of micropore development is the main factor influencing the accuracy of this method. Therefore, using pore structure parameters at different scales to calculate methane adsorption capacity is effective and feasible for deep coal seams with extensive micropore development. This study established a connection between microscopic pore structure and macroscopic methane adsorption capacity, offering a novel method to determine the methane adsorption capacity of deep coal seams.