Arabian Journal of Geosciences最新文献

Pressure on land is a consequence of population expansion, increased food consumption, and competition between land uses. Soils play a crucial role in supporting food production and providing ecosystem services. The demand for timely and relevant soil information that can support decision-making at different scales is increasing as efforts are made to ensure sustainable use of soil resources. Digital soil mapping (DSM) has become increasingly popular in various ecosystems, including arid, semi-arid, and humid regions, as well as rangelands and forests, due to its ability to overcome associated constraints to traditional methods of soil mapping. DSM offers a more efficient way to provide soil information in terms of time and cost, while improving map accuracy and providing quantified estimates of uncertainty. DSM involves the construction of soil spatial information systems using numerical models to analyze spatial and temporal variations in soil types and attributes based on soil observations, knowledge, and associated environmental factors. The main objective of this article is to present an overview of advances in thematic soil mapping in relation to advances in remote sensing (RS). First, we provide a brief summary of common tools used in DSM. Subsequently, we discuss advances in historical soil data, environmental variables, and applications of DSM tools. Finally, we present the major developments and future perspectives suggested by existing research. In conclusion, although DSM is becoming increasingly sophisticated to meet diverse soil information requirements, there are still issues to be addressed, particularly in highly heterogeneous and human-impacted environments. These issues require the development of new methodologies and applications of the DSM.

Determining the permeability of the reservoir in the absence of well logs and core analysis data is a challenge in the oil and gas industry. Even though correlations such as Winland and Pittman exist, they often fail to provide an accurate permeability value. This study utilized the mercury injection capillary pressure data from published literature to determine the permeability in sandstone reservoirs. The dataset included parameters such as pore throat radius at various mercury saturations (25%, 35%, 50%, and 75%), along with permeability and porosity determined through laboratory experiments. Different machine learning techniques, namely, LASSO regression, ridge regression, support vector regression (SVR), random forest (RF) regression, decision tree (DT) regression, K-nearest neighbor (KNN) regression, gradient boosting, Ada Boost, and multilayered perceptron (MLP) were used to determine permeability values form porosity, pore throat radii, and pore throat sorting data. Sixty-three samples were randomly divided into training and test sets, out of which 75% were used for training both the models while 25% were used to test them. The regression coefficients suggested that pore throat radius at 75% saturation (r75) had the highest influence on the permeability values, followed by porosity (phi) and r50. It was noted that as the learning rate increased, the root mean squared error (RMSE) gradually reduced from 48.9208 to 47.2889 for ridge and LASSO-normal, while for ridge and LASSO-polynomial 99.97 to 52.2629. Various models and correlations have been developed in previous studies; however, the lithological characteristics of reservoir rock vary with location and subsurface factors. The novelty of this study lies in its integration of machine learning models with mercury injection capillary data for accurate permeability predictions, addressing the limitations of traditional correlations and offering a reliable method for characterizing sandstone reservoirs in the absence of well log data and evaluating the flow behavior of reservoir fluids within the porous media.

A great number of variables (such as rock properties, in-situ stresses, drilling fluid, inclination etc.) are effective on wellbore stability and the combined effect of those variables determines the stability condition of wellbore. The main aim of this study is to analyse the combined effect of drilling fluid, stress state and inclination angle considering that there is no comprehensive study conducted on the topic. In this study, three stress conditions (normal faulting stress condition, reverse faulting stress condition and strike slip faulting stress condition), three drilling fluids (bentonite based, KCl based and polymer based), three inclination angles (0, 45 and 90°) and two depths (2800 and 5000 ft) were considered to evaluate the effect of those parameters on wellbore stability. The results of analyses showed that the number of instabilitity zones around the wellbore increases as the inclination angle increases under normal fault stress state However, number of instability zones are higher for low inclination angle values under reverse and strike slip fault stress states. While the best stability condition was obtained with polymer drilling fluids due to limited decrement on strength properties, the worst stability condition was satisfied with bentonite drilling fluids due to considerable decrement on strength properties as a result of interaction with drilling fluid.

In view of the gas flow problem in the hydraulic fracturing engineering of L-type horizontal well and in the process of gas production in coalbed methane development, the permeability stress test of single fracture coal-rock combination was carried out. The permeability evolution law of fractured coal-rock combination under axial compression, confining compression, and gas pressure is analyzed. The axial compression has little effect on the permeability of coal-rock combination with fractures, and the permeability has no obvious change. Taking 0.25 MPa gas pressure as an example, the permeability of N1 fluctuates between 0.004 and 0.005 mD, and the permeability of N2 and N3 samples fluctuates between 0.002 and 0.0035 mD. With the increase of confining compression, the permeability decreases with the increase of confining compression. Taking the N4 sample as an example, when the gas pressure is 0.50 MPa, the permeability of N4 rapidly decreases from 0.351 to 0.0025 mD. The permeability has decreased by 99.3%. With the increase of gas pressure, the permeability and stress sensitivity of fractured coal-rock combination decrease gradually. In the process of gas pressure loading, the permeability decreases greatly due to the existence of gas slippage effect in the low-pressure stage. When the gas pressure exceeds 1 MPa, the joint action of slip effect and velocity-sensitive effect makes the permeability almost unchanged. Taking the N4 sample as an example, when the axial and confining pressures are 6 MPa, the permeability decays from 1.298 to 0.382 mD, with a decay ratio of 70.6%. Finally, the permeability calculation model of single fracture coal-rock combination under in situ stress and gas pressure can well match the experimental data and clarify the influence of each permeability on the overall permeability. The permeability model shows that the overall permeability depends on the part of the smaller permeability, and the higher permeability only makes the overall permeability increase slightly.

Bakar (Arab J Geosci 14:763, 2021) presented a comprehensive study to answer some questions regarding the origin of cherts and selective silicification of Eocene and Messinian host rocks. Silicification is one of the most significant diagenetic processes influencing the evolution of sedimentary rocks, especially carbonates and evaporites, which makes this study interesting. A large number of sedimentologists, stratigraphers, petroleum geologists, and other related fields are interested in studying silicification owing to the potential information that study of silicification might provide on paleogeography, paleoceanography, stratigraphic correlations, the diagenetic history of carbonate rocks, and other topics. However, I have some comments on some points stated in the paper of Bakar (Arab J Geosci 14:763, 2021).

This study focuses on evaluating the quality of the Aouinet Wanin F3B sandstone as a potential hydrocarbon reservoir in Well A37, NC 169A, Wafa Field, Ghadamis Basin, northwest Libya. Capillary pressure data, a key indicator of pore throat size distribution and fluid percolation capability, is crucial for reservoir characterization. However, due to the high costs, time constraints, and environmental concerns associated with mercury injection capillary pressure testing, this study introduces an alternative approach. We utilize routine core analysis data specifically porosity and permeability to model synthetic drainage capillary pressure curves based on Pittman’s modified equations. Our results reveal three distinct rock types represent the reservoir intervals, categorized into mega-, macro-, and micro-pores. The uppermost zone of mega- and macro-pores demonstrates excellent to good reservoir qualities. The log–log plot of pore throat radius versus permeability using Pittman’s R50 equation yielded a 1 mD permeability cutoff, aligning with common reservoir benchmarks, while the Winland R35 equation produced a cutoff of 0.4 mD, slightly outside the acceptable range which is between 0.5 and 1 mD. These findings offer a cost-effective and reliable alternative for reservoir quality assessment.

Gels that initially exhibit low viscosity and later form a stable three-dimensional structure can be successfully employed in controlling fluid loss during drilling operations. Hybrid gels, composed of a cross-linked polymer gel as the continuous phase and an oil-based fluid as the internal phase, offer a more cost-effective and easily controllable solution than conventional polymer gels. This study investigates the performance of hybrid gels enhanced with nanoparticles (NPs) for controlling fluid loss during drilling operations. To evaluate the impact of environmentally friendly NPs (nano-silica (NS) and nano-bentonite (NB)) on gel behavior, several parameters, including initial and final gelation times (IGT and FGT), crosslinking rate (CR), and final viscosity (FV), were assessed under varying conditions of pH, temperature, and salinity. Additionally, gel stability over time, dynamic stability, and maximum sealing pressure were measured. To assess potential reservoir damage, gel degradation was evaluated in hydrochloric acid solutions with concentrations of 15 wt. % and 28 wt. %. Results demonstrate that NPs significantly enhance the performance of hybrid gels, improving sealing pressure by approximately 20% in fractured and highly permeable porous media. The gels exhibited enhanced stability, resistance to high pressures, and minimal reservoir damage. These findings highlight the potential of hybrid gels with NPs as a promising solution for combating fluid loss and improving drilling efficiency and safety.

Graphical Abstract

Expansive soils, known for their susceptibility to early damage due to their swelling and shrinkage properties, pose a significant technical challenge in geotechnical engineering. This study explores the optimization of microbial-induced improvement of these soils, emphasizing the pivotal role of temperature, pH, and time on both microbial growth dynamics and the soil’s swell-shrink behavior. A series of microbial growth and expansive soil swell-shrink tests were conducted, employing response surface methodology (RSM) to develop regression models that delineate the optimal conditions for microbial solution concentration and the free swelling ratio. The findings indicate that temperature and curing time exert a more pronounced influence on these parameters than pH. Notably, microbial solution concentration exhibits a peak with increasing temperature, while the free swelling ratio inversely declines. The curing time’s effect is characterized by an initial peak in microbial solution concentration followed by a gradual decrease, with the free swelling ratio of the soil consistently diminishing. The optimization analysis pinpoints the optimal conditions at 32 °C, pH 6.5, and a curing duration of 48 h, where the reduction in both microbial solution concentration and free swelling ratio is maximized. Under these conditions, microorganisms are used for improvement, the microbial solution’s OD₆₀₀ value peaks at 1.996, significantly reducing the expansive soil’s free swelling ratio from 169 to 64.3%.

This comprehensive study focuses on the evaluation and comparison of seismic hazard parameters in the Northeast Indian region, covering longitude 87°–98°E and latitude 20°–30°N, which is characterized by high seismicity and complex tectonic structures. The study aims to estimate seismicity parameters such as the magnitude-frequency distribution and Gutenberg-Richter a and b-values using maximum likelihood method (MLM) through the Zmap and the statistical approach proposed by Kijko. The study area is divided into six seismogenic source zones, and zone-wise seismicity parameters are estimated using the declustered catalog considering whole earthquake data and data within the completeness period. The study estimated seismicity parameters using completed catalogs. The results showed that the a value ranged from 2.85 to 5.06, and the b value ranged from 0.76 to 0.92 when using Zmap. Meanwhile, when using the Kijko approach, the estimated a value ranged from 2.70 to 4.65, and the b value ranged from 0.64 to 0.85. The estimated seismicity parameters are used to estimate the return periods and probabilities of earthquakes with different magnitudes for each zones. From the probability curve, it is observed that the probability of earthquake occurrences decreases exponentially with magnitude. For all zones, a high probability of occurrence is observed for earthquake magnitude 6 both in 50 and 100 years. The return periods for different magnitudes estimated from the Zmap and Kijko methods are consistent with some variations among the six source zones. Zmap estimates were lower for smaller magnitudes and higher for larger magnitudes than the Kijko method. The difference factor varied depending on the source zone and magnitude. In general, Zmap estimates were lower by a factor of 1.0 to 1.34 for lower magnitudes and higher by a factor of 1.01 to 1.35 for higher magnitudes.