Geological Conditions Research Articles

Copper deposit development potential on the Qinghai-Xizang Plateau in China based on the pressure-state-response framework

The Qinghai-Xizang Plateau (QXP) in China is a geological treasure trove known for its complex structures and rich mineral resources. Among these, copper stands out as a critical metal for economic development. However, the exploitation of these resources is not without challenges, particularly in balancing the need for economic growth with the preservation of the plateau’s delicate ecosystem. In this study, we take into account the intricate interplay between human activities, environmental conditions, and economic strategies. By applying a pressure-state-response (PSR) framework and innovatively establishing a comprehensive potential evaluation index, we are able to quantify the development potential of copper deposits on the QXP and to identify key factors influencing the development potential. The results indicate a varied landscape of copper deposit development potential across the QXP. The state layer in the PSR model represents the most significant obstacle to the development potential of copper resources on the QXP. Certain areas, specifically central Xizang, eastern Xizang, and northwestern Yunnan, show high development potential for copper deposits due to favorable geological conditions and policy environments, and strong infrastructure.

Audio-frequency magnetotelluric data inversion method based on adaptive binary structure constraint and its application in geothermal exploration

Audio-frequency magnetotelluric (AMT) inversion technology plays a crucial role in the exploration of deep resources, especially in the detection of deep geothermal resources. Although AMT inversion technology has significant advantages in vertical resolution, the inversion process still faces serious challenges of non-uniqueness. To improve the accuracy and reliability of inversion, this paper proposes an AMT data inversion method based on adaptive binary structure constraint. This method incorporates adaptive extraction techniques to conduct a cluster analysis of the resistivity model generated in each iteration, thereby intelligently identifying and distinguishing the target and background areas in the model. These target areas are then used as prior structural information for the next iteration, guiding the refined reconstruction of the resistivity model. During the iteration process, the AMT inversion algorithm focuses on calculating the target areas, while the resistivity values of the background areas remain unchanged. This strategy effectively reduces the degrees of freedom in the inversion problem, lowers the dimension of the solution, thereby improving the computational efficiency and accuracy of the inversion. Model tests show that compared with traditional smoothing constrained AMT inversion method (S-AMT), the adaptive binary structure-constrained AMT inversion method (ABS-AMT) can reconstruct high-resolution refined resistivity models, significantly reducing the uncertainty of inversion. Furthermore, the ABS-AMT method not only reduces the dependence on prior knowledge but also enhances the algorithm's adaptability to different geological conditions. Practical application in the geothermal area of Laosandui in Linjiang City, Jilin Province, China, fully demonstrates the method's effectiveness and significant superiority in actual geothermal exploration through comparative analysis with known geothermal target areas.

LITHOLOGY UNITS WANAJAYA AREA AND SURROUNDING, BUAHDUA SUBDISTRICT, SUMEDANG DISTRICT, WEST JAVA PROVINCE

The research site is located in Wanajaya Village, Buahdua Subdistrict, Gunung Kidul Regency, West Java Province. Accessibility to the research location using a motorbike. The purpose of this study is to determine the geological conditions of the study area in terms of lithological units and stratigraphic order. The lithological unit of the study area is divided into 4 lithological units, namely the Mudstone Unit, the Andesite Intrusion Unit, the Volcanic Breccia Unit and the Andesite Lava Unit, namely the naming of rock units based on observable physical characteristics, including rock type, uniformity of lithological symptoms and stratigraphic position. The geological history of the first research site in the Late Miocene to Early Pliocene time was deposited by the mudstone unit. In the late Pliocene to Pleistocene volcanism activity occurred due to the displacement of the volcanic centre from the south to the centre of Java (Martodjojo, 1984) which caused the formation of the wanajaya fold and continued with the formation of the wanajaya ascending fault. As a result of the weak fault zone, the andesite intrusion unit appeared, which was the beginning of the activity of the old volcano. In Pleistocene time, namely deposition of Volcanic Breccia Unit and continued by the deposition of andesite lava unit due to volcanism activity of Tampomas volcano issued pyroclastic material.

Numerical Investigation of Transmission and Sealing Characteristics of Salt Rock, Limestone, and Sandstone for Hydrogen Underground Energy Storage in Ontario, Canada

With the accelerating global transition to clean energy, underground hydrogen storage (UHS) has gained significant attention as a flexible and renewable energy storage technology. Ontario, Canada, as a pioneer in energy transition, offers substantial underground storage potential, with its geological conditions of salt, limestone, and sandstone providing diverse options for hydrogen storage. However, the hydrogen transport characteristics of different rock media significantly affect the feasibility and safety of energy storage projects, warranting in-depth research. This study simulates the hydrogen flow and transport characteristics in typical energy storage digital rock core models (salt rock, limestone, and sandstone) from Ontario using the improved quartet structure generation set (I-QSGS) and the lattice Boltzmann method (LBM). The study systematically investigates the distribution of flow velocity fields, directional characteristics, and permeability differences, covering the impact of hydraulic changes on storage capacity and the mesoscopic flow behavior of hydrogen in porous media. The results show that salt rock, due to its dense structure, has the lowest permeability and airtightness, with extremely low hydrogen transport velocity that is minimally affected by pressure differences. The microfracture structure of limestone provides uneven transport pathways, exhibiting moderate permeability and fracture-dominated transport characteristics. Sandstone, with its higher porosity and good connectivity, has a significantly higher transport rate compared to the other two media, showing local high-velocity preferential flow paths. Directional analysis reveals that salt rock and sandstone exhibit significant anisotropy, while limestone’s transport characteristics are more uniform. Based on these findings, salt rock, with its superior sealing ability, demonstrates the best hydrogen storage performance, while limestone and sandstone also exhibit potential for storage under specific conditions, though further optimization and validation are required. This study provides a theoretical basis for site selection and operational parameter optimization for underground hydrogen storage in Ontario and offers valuable insights for energy storage projects in similar geological settings globally.

Pre-Stack Nonlinear Direct Exact Inversion of Fracture Parameters in Deep Shale Reservoirs

A conventional linear pre-stack inversion method under the conventional stationary convolution model is limited by the assumptions of weak formation contrast change and small angle incidence and fails to take into account the amplitude attenuation of seismic wave propagation. Meanwhile, the resolution and precision of oil and gas evaluation and fracture characterization of shale reservoirs under complex geological conditions are low because the compaction and non-connectivity characteristics of deep shale reservoirs are not fully considered. Therefore, porous rock pores are divided into connected pores and disconnected pores. Combined with the effect of compaction on dry rock skeleton, a petrophysical model considering the compaction and pore dysconnectivity of deep shale reservoir is developed. The quantitative relationship between transverse isotropy with a vertical axis of symmetry (VTI) stiffness matrix, rock physical properties, and fracture parameters is established in this model. It provides a more accurate scheme for the original physical modeling of deep shale. This relationship is incorporated into the exact VTI reflection coefficient equation, and a nonstationary convolution operator is derived by using the attenuation theory of seismic wave propagation. A nonstationary pre-stack nonlinear direct inversion method of fracture parameters of shale reservoirs with horizontal fractures is proposed, which Improves the resolution and accuracy of shale reservoir gas bearing and fracture characteristics prediction. It provides a new way to accurately characterize the fracture development and oil-bearing property of shale reservoirs. A model test and field data test verify the effectiveness of this method.

Hydrogeological analysis of topography-driven groundwater flow in a low temperature geothermal aquifer system in the Julian Alps, Slovenia

Abstract Groundwater flow and heat distribution was investigated in the regional karstic-fissured aquifer-aquitard system near Lake Bled in the Slovenian, eastern Julian Alps. The area features thermal springs with temperatures of 19–23 °C which are exploited by abstraction wells. The occurrence of low-temperature geothermal systems, which are common in the Alps, are associated with specific hydrogeological conditions, such as vertical hydraulic connectivity between different geological formations, relatively large elevation differences along flow paths, and the concentrated upwelling of geothermal water to the surface. The occurrence of the low-temperature geothermal field is explained by the presence of a hydraulically conductive fault along with a regional groundwater flow pattern that supports deep groundwater circulation. Hydraulic measurements and temperature data were collected from springs and wells in the area to support the analysis of flow patterns, together with the construction of a basin-scale 2D numerical flow and heat transport simulation. The diverse topographic and geological conditions result in a multi-scale groundwater flow system. The discharge of thermal waters in the Lake Bled area is a consequence of the upwelling of deep groundwater induced by a combination of the ~ 650 m difference in hydraulic head and hydrogeological heterogeneity and anisotropy, related to faulting of the geological formations. In addition, individual flow subsystems were found to significantly affect the natural heat distribution and travel times within the basin-scale system. The study highlights the combination of a basin scale approach taking into consideration local to regional-scale heterogeneities and faults in order to better understand the hydrogeological behaviour of Alpine groundwater systems.

Revising the coal mining CH4 emission factor based on multiple inventories and atmospheric inversion approach at one of the world's largest coal production areas: Shanxi province, China.

Methane (CH4) emissions from the coal industry represent a substantial portion of anthropogenic CH4 emissions from energy-related activities. China ranks as the world's largest coal producer, where Shanxi Province is one of its major coal production regions and accounts for 20.7% of the national total coal production. The inherent variability in coal properties, geological conditions, and mining techniques across coal mines introduces significant fluctuations in CH4 emission characteristics and emission factors (EFs), creating considerable uncertainty when estimating CH4 emissions in this major coal mining region using traditional emission inventories, thereby introducing large bias in estimating national total CH4 emissions of China. In this study, we applied a top-down approach to estimate CH4 emissions in the Taiyuan-Jinzhong Metropolitan (TJM) area of Shanxi Province, using atmospheric CH4 concentration observed from a 30-meter tower between March 2018 and February 2019. Building upon our previous work, we integrated five emission inventories-EDGAR, GFEI-coal, PRO-coal, GFEI-fuel, and a satellite-based CH4 emission product-with two inversion methods. Additionally, satellite xCH4 data were utilized to identify significant emission outliers, which were then calibrated when estimating the CH4 emission and EF for the region. Our results revealed notable disparities in the magnitude of CH4 emissions among the five inventories for the TJM region. After applying the MSF and SFBI methods to constrain the prior emission inventories, the posterior CH4 emissions for the TJM region were estimated at 1.1×106t, 1.0×106t, 1.1×106t, 1.3×106t, and 1.5×106t, respectively, across the five inventories. The derived coal mine CH4 EF for the TJM region was 9.6 (±1.35) m3/t, significantly lower than the previously reported value of 23.2 (±4.9) m3/t, highlighting the substantial impact of emission outliers on posterior CH4 emissions. A comparative analysis with EFs from other studies demonstrated that this value closely aligns with the EF values for coal with low CH4 content. However, it is important to note that substantial regional variability of coal mining activities can result in significant uncertainty in EFs across different areas. Therefore, we underscore the necessity of establishing a more extensive atmospheric CH4 observation network to enhance the assessment of regional variations in CH4 EFs and emissions from coal mining activities.

MFIEN: multi-scale feature interactive enhancement network for seismic data denoising in desert areas

Due to complex acquisition environments and geological conditions, in desert seismic data, the background noise is always intense and overlaps with the frequency range of the seismic signals. This severely blurs the seismic signals, bringing challenges to accurately extract desired reflection information. Effectively suppressing random noise and significantly optimizing the signal-to-noise ratio (SNR) is emerging as a key issue in seismic data processing. A Multi-scale Feature Interaction Enhancement Network (MFIEN) for intense background seismic noise attenuation in desert areas is proposed in this paper to address this problem. In general, MFIEN has a multi-scale feature interaction structure that combines feature information from different layers and captures distinct features through effective information integration. Furthermore, a fusion feature enhancement module (FFEM), incorporating dilated convolutions and convolutions with different kernel sizes, is proposed. This expands the receptive field without changing the size of the feature maps, thereby preserving the structural features of seismic records more effectively. Both synthetic and field desert data denoising results indicate that MFIEN can accurately suppress intense background noise and effectively recover weak signals, significantly enhancing the quality of seismic data.

Enhancing Long-Term Viability of Energy Pile with Heat Sink Systems in Tropical Monsoon Climates: Implementation Strategies and Performance Analysis

Enhancing Long-Term Viability of Energy Pile with Heat Sink Systems in Tropical Monsoon Climates: Implementation Strategies and Performance Analysis

Biogenic hydrogen production from oil hydrocarbons at geological carbon storage conditions

Biogenic hydrogen production from oil hydrocarbons at geological carbon storage conditions

Identifying predictors of spatiotemporal variations in residential radon concentrations across North Carolina using machine learning analytics.

Radon is a naturally occurring radioactive gas derived from the decay of uranium in the Earth's crust. Radon exposure is the leading cause of lung cancer among non-smokers in the US. Radon infiltrates homes through soil and building foundations. This study advances methodologies for assessing residential radon exposure by leveraging a comprehensive dataset of 126,382 short-term (2-7 days) radon test results collected across North Carolina from 2010 to 2020. Employing a combination of linear regression and advanced machine learning techniques, including random forest models. Analysis through linear regression, linear mixed-effects models (LME), and generalized additive models (GAM) using the first-time tested radon levels reveals that elevation, proximity to geological faults, and soil moisture are pivotal in determining radon concentration. Specifically, elevation consistently shows a positive relationship with radon levels across models (linear regression: β=0.12, p<0.001; LME: β=0.17, p<0.001; GAM: β=0.11, p<0.001). Conversely, the distance to geological faults negatively correlates with radon concentration (linear regression: β=-0.11, p<0.001; LME: β=-0.06, p<0.001; GAM: β=-0.07, p<0.001), indicating lower radon levels further from faults. Using the random forest model, our study identifies the most influential environmental predictors of first-time tested radon levels. Elevation is the most influential variable, followed by median instantaneous surface pressure and soil moisture in the upper 10cm layer, illustrating the significant role of geological and immediate surface conditions. Additional important factors include precipitation, mean temperature, and deeper soil moisture levels (40-200cm), which underscores the influence of climate on radon variability. Root zone soil moisture and the Normalized Difference Vegetation Index (NDVI) also contribute to predicting radon levels, reflecting the importance of soil and vegetation dynamics in radon emanation. By integrating multiple statistical models, this research provides a nuanced understanding of the predictors of radon concentration, enhancing predictive accuracy and reliability.

Experiment research on the control method of automatically retained entry by roof cutting pressure relief within thick hard main roof longwall top coal caving panel

Experiment research on the control method of automatically retained entry by roof cutting pressure relief within thick hard main roof longwall top coal caving panel

The effects of rain and drought on incidence of enteric disease in Pennsylvania (2010-2019).

Campylobacter, nontyphoidal Salmonella, Cryptosporidium, and Giardia cause an estimated 1 million cases of domestically acquired waterborne diseases annually in the United States. Acute symptoms can include diarrhea and vomiting; however, these illnesses can result in longer term complications such as reactive arthritis, Guillan Barré syndrome and death, particularly in immunocompromised individuals. Precipitation and drought can plausibly increase the risk of enteric infections, but consensus in the literature is lacking. To determine the effects of rain and drought on weekly counts of reportable enteric illness (due to Salmonella, Campylobacter, Giardia, or Cryptosporidium) in Pennsylvania, US between 2010 and 2019. We obtained 10-years of data on confirmed illness from 66 Pennsylvania counties due to: Salmonella (9,924), Campylobacter (15,854), Giardia (4,537), and Cryptosporidium (4,017). A zero-inflated negative binomial model with random-intercept for county was used to assess the relationship between illnesses caused by these pathogens between 2010 and 2019, and weekly rain (cm) and Palmer Drought Severity Index (PDSI) values from the National Weather Service. The lag times that were tested, between illness and weather event, were chosen by calculating the cross correlation between the statewide average weekly rain and the statewide number of weekly cases. A positive association was found between rain and counts of campylobacteriosis, salmonellosis, and giardiasis. An increase in prior wetness (PDSI value) was associated with increased incidence rates of cryptosporidiosis and campylobacteriosis. The relationship between rain and PDSI and illness varied by organism type. Complex relationships exist between enteric disease and precipitation and prior environmental wetness. Our findings suggest that rainfall may be contributing to increased waterborne exposure. Further investigation is needed to explore these relationships with factors such as drinking water source, local geological conditions, presence of combined sewer overflows and agricultural activities, recreational water use and irrigation water sources to better elucidate important waterborne transmission pathways.

The Environmental Evaluation of the Sp. Opi – Babatan Saudagar – Srijabo Road

The Public Works Agency for Highways and Spatial Planning of South Sumatra Province has the task of deconcentration in the field of roads and has authority over 88 roads with a length of 1,779.27 km spread across 17 districts and cities in South Sumatra Province. Not all provincial roads have an environmental evaluation document. The objective of the current research was to evaluate the environmental impact resulting from road operational activities in South Sumatra Province by taking data on ongoing activities, geological and topographic conditions, flora and fauna, socio-economic and cultural activities in the area, as well as measuring quality standards, which include air quality standards, noise, vibration, and water quality standards on the Sp. OPI - Babatan Saudagar - Srijabo Road. The conclusion of the current research shows that the ambient air quality, noise intensity, and vibration are still good and meet quality standards. The potential hydrogen (pH) and dissolved oxygen (DO) parameters in the Ogan River branch at the time of sampling for surface water quality did not meet the quality standards due to the type of soil, which tends to be acidic. Furthermore, the results of groundwater quality analysis show that the pH of groundwater measured in all locations is less than 6.5 or does not meet quality standards, which can cause an unpleasant taste when consumed, so processing is needed to increase the pH of groundwater.

Strong wind is one of the important factors that trigger landslides

Landslides, causing significant loss of life and property, are traditionally attributed to heavy rainfall and geological or topographical factors, often overlooking strong winds. In landslide-prone forest regions, typhoon-induced strong winds can uproot trees and destabilize their root systems, potentially triggering shallow landslides. In this study, a data-driven approach revealed that strong wind is one of the important factors that may trigger landslides, particularly strong wind lasting for hours. The significance of the combined rain–wind influence on landslides is examined using Mann–Whitney U test and 3D histogram, and a Random Forest machine learning model is constructed to predict the occurrences of landslides based on factors, such as heavy rain, strong winds, traditional geological conditions, and topographical factors. The models with wind factors have better performance than models without wind factors. These findings infer that both strong winds and heavy rainfall during typhoons may trigger or increase the risk of landslides.

Study on the Influence of Complicated Geological Condition Permeability in Coal Reservoirs on Horizontal Well Drainage and Production

Study on the Influence of Complicated Geological Condition Permeability in Coal Reservoirs on Horizontal Well Drainage and Production

A Physical Model Test of Coal-Mining-Induced Deformation Mechanisms in a Canal

The route of the South-to-North Water Diversion channel strides across part of the coal mine goaf in Yuzhou County, Henan Province, China, and long-term deformation due to coal seam recovery poses a threat to the safe operation of the main canal. Therefore, the study of the deformation mechanisms induced by coal seam recovery is of great significance to the canal’s safe operation, as well as to deformation monitoring and to the development of early warnings. The geologic model was established based on the geological engineering conditions of the Yuzhou Gongmao mining area, spanning the main canal of the South-to-North Water Diversion Project; then, the physical model test was carried out according to similar theories. The deformation characteristics of the rock overlay and the channel above the goaf were analyzed, and failure criteria for overburdened rock and the channel were proposed. The results showed that horizontal fissures were gradually observed in the overlying rock as the coal mining progressed, extending and widening. When the goaf was excavated to 76 cm, the overlying rock body suddenly collapsed as a whole, and the channel collapsed and was destroyed. During the formation of the goaf, there was a critical span ratio (R): When the height-to-span ratio was greater than 0.039, the collapse of overlying rock occurred only within a certain range above the goaf. When the height-to-span ratio was less than 0.039, the overlying rock body collapsed in a wide area, and the soil on both sides of the channel collapsed to the center of the channel, presenting a “V” glyph collapse. The sediment in the center of the channel measured 22 mm, and there were multiple tensile cracks on both sides of the embankment, with a width of 5–10 mm. The vertical deformation of the channel went through three stages, namely, the initial deformation stage, the deceleration deformation stage, and the stability stage. This study can provide scientific guidance for early warnings of channel deformation and safe operation across the goaf.

Key Technologies for Horizontal Well Development in Deep Tight Sandstone Reservoirs

ABSTRACTDeep tight sandstone oil and gas reservoirs are exerting an increasingly crucial role in the augmentation of fossil energy reserves and the provision of energy. On account of the intricate geological conditions and the deficiency of a comprehensive set of exploration and development engineering technologies as well as supporting processes, the present development of deep tight sandstone oil and gas reservoirs remains in its nascent stage. Through the analysis and generalization of the horizontal well development technology for deep tight sandstone oil and gas reservoirs, a series of technologies have been established, encompassing reservoir geological evaluation and modeling, horizontal well development reservoir engineering validation, horizontal well geological design, and enhanced oil recovery processes. By taking the C 6 reservoir in Ordos basin, China as the research subject, in light of the research outcomes regarding the damage mechanisms and potential damage factors of tight sandstone oil and gas reservoirs, a geological evaluation approach based on the well log response characteristics was constructed, clarifying the porosity and permeability features of the C 6 reservoir, establishing the numerical model of the oil reservoir, and further elaborating the methods for dividing the development layers, selecting the development well pattern, and determining the development well density. The design parameters of horizontal well‐segmented hydraulic fracturing were meticulously optimized, resulting in a minimum cluster spacing of 7 m and a maximum cluster spacing of 20 m. Given the influence of horizontal stress differences, the optimum fracturing density was ascertained to be 16 perforations per meter, and the optimal fracturing fluid volume was identified through simulation to range from 12 to 25 m3/m. The crucial technologies for the development of tight sandstone oil and gas reservoirs in horizontal wells have been clearly identified, offering theoretical direction for the efficient exploitation of deep tight sandstone oil and gas reservoirs.

Study on subsidence evolution induced by coal mining under highway based on finite element simulation

Accurate estimation of overlying strata subsidence and surface deformation caused by coal extraction is crucial for assessing the impact of mining activities on surface infrastructure. In this study, we investigated the subsidence evolution of overlying strata and ground surface induced by underground mining using finite element simulation and focus on a mining district in the Yu-Heng mining area of the central Ordos Basin and then, the influence of underground longwall mining on the surface roads was evaluated. A three-dimensional geological model of the mining district was constructed, considering the actual stratum structures and the deterioration effect of water on rock mechanical properties. The whole coal mining process was simulated to predict the evolution of the subsidence basin at different mining stages, and the surface deformation characteristics caused by coal mining were calculated. Results showed that the subsidence characteristics by numerical simulation were highly consistent with the records of surface subsidence in the adjacent areas, indicating that the constructed geological model can accurately reflect the actual geological conditions and the deformation behaviors of overlying strata. A comparative study revealed that the mechanical properties of the generalized layers determined by processing the mechanical parameters of dry core samples will be much higher than those of the natural strata under the in situ water-saturated condition, and then the subsidence caused by coal mining will be significantly underestimated. Thus, the water-induced mechanical property deterioration of overlying strata must be fully considered when constructing geological models.

Analysis and Evaluation of a TCO2 Electrothermal Energy Storage System with Integration of CO2 Geological Storage

The goal to reduce greenhouse gas emissions necessitates the increase in RES utilization. To accomplish this goal, energy storage solutions are required. This study investigates the performance of an electrothermal energy storage system, the CEEGS, which consists of an above-surface energy storage system and a below-surface geological system. The focus is set initially on the analysis of the above-surface system to gain insight into its operation. Then, steady-state optimization is utilized to identify the operating conditions that maximize the system performance, before investigating the below-surface system integration and the effect that the geological conditions have on system performance. For the above-surface system, efficiency (ηR-T) up to 46.89% is calculated. For systems integrated with CO2 geological storage, two case studies are examined, presenting higher ηR-T compared to the above-surface system (Case study 1: 50.37%, Case study 2: 67.39%). The optimal ηR-T for Case study 2 is achieved for higher injection/production pressures and temperatures conditions and minimal ΔP and ΔT between injection and production. In conclusion, it is the selection of the geological storage conditions that contribute the most to the optimal ηR-T; thus, the selection of the appropriate geological storage formation is imperative.