Rock Parameters Research Articles (Page 1)

Hydrocarbons have a vital role as a driver of the global economy, which causes demand to continue to increase. To achieve production targets, oil and gas companies try to conduct exploration using efficient and accurate methods to obtain optimal hydrocarbon reserves. One approach in hydrocarbon exploration is to use geostatistical analysis to understand the characteristics of petrophysical parameters of reservoir rocks (e.g. porosity, permeability, water saturation and facies). This study aims to characterize reservoirs in the NE Java Basin using a geostatistical approach that Sequential Gaussian Simulation (SGSIM) to produce random realizations that can be adjusted and validated through geostatistical analysis of data before and after the simulation. The dataset used in this study consist of well data, seismic line, and core data. The results shows the petrophysical properties distribution from the simulation reveals the dominance of carbonate sandstone reservoirs in the central part of the study area with a thinning slope towards the northwest and southeast, while sandstone reservoirs are only dominant in the southeast direction of the study area. This research provides important insights in understanding reservoir characteristics and can be a basis for efficient decision making in the exploration of hydrocarbon resources in this area.

Abstract. The transition from strong to weak mechanical behavior in the Earth's continental middle crust is always caused by an initiation of viscous deformation. Microstructural evidence from field examples indicates that viscously deforming polymineralic shear zones represent the weakest zones in the crust and may dominate mid-crustal rheology. The results of recent experiments (as in Part 1, Nevskaya et al., 2025) demonstrate that the observed weak behavior is due to the activation of dissolution–precipitation creep (DPC). Formation of fine-grained material and efficient pinning of grain growth are important prerequisites for the formation of a stable deforming microstructure. However, available rheological parameters for fine-grained polymineralic rocks deforming by DPC are insufficient. A series of three types of experiments was conducted on a granitoid fine-grained ultramylonite to different strains at 650–725 °C, 1.2 GPa, with strain rates varying from 10−3 to 10−6 s−1. Type I and II experiments are solid natural samples, providing key microstructural evidence for DPC. Type III experiments are general shear experiments performed on coarse- and fine-grained ultramylonite powder. All experiments were combined to estimate rheological parameters for such polymineralic shear zones. A stress exponent n≈1.5 and grain size exponent m≈-1.66, with uncertainties, were estimated and coupled with microstructural observations. Extrapolations indicate that, at slow natural strain rates, DPC in polymineralic granitoid fault rocks can occur at lower temperatures than monomineralic quartz. A deformation mechanism map is proposed, indicating a transition in the deformation mechanism from dislocation creep in monomineralic quartz to DPC in weaker polymineralic fine-grained granitoids, based on strain rate and grain size. Most importantly, the polymineralic composition is the determining factor in achieving the fine grain sizes necessary for DPC to become activated. This is due to the presence of additional chemical driving potentials and phase mixing, both of which are absent in monomineralic systems.

The Cerchar Abrasiveness Index (CAI) is a vital parameter in geotechnical engineering, especially when it comes to tunneling and mechanized excavations. The study employed a comprehensive dataset of 163 samples representing various rock types, including igneous, sedimentary, and metamorphic formations. The methodology included three base algorithms (XGBoost, LightGBM, and Random Forest), improved by three distinct metaheuristic techniques: Arithmetic Optimization Algorithm (AOA), Reptile Search Optimization (RSO), and Harris Hawks Optimization (HHO). The Brazilian tensile strength (BTS), uniaxial compressive strength (UCS), equivalent quartz content (EQC), and brittleness index (BI) were the four main rock parameters used to make the predictive models. The model was further evaluated by splitting the data into 80% training and 20% testing sets. Subsequently, the model was compared to 17 real-world hard rock TBM projects in different countries and geological conditions. The AOA-optimized versions performed nicely, with AOA-LightGBM doing the best on the held-out test set (R² = 0.952, RMSE = 0.290, MAE = 0.208, VAF = 0.952). External validation showed that AOA-XGBoost performed properly, with the highest correlation coefficient of 0.8308 compared to field measurements from international tunneling projects. Also, the AOA-XGBoost did well on tests with R² = 0.951, RMSE = 0.296, MAE = 0.223, and VAF = 0.951. Using SHAP values to examine feature importance revealed unique parameter influence signatures. EQC was the most important parameter in XGBoost models, while UCS had the greatest impact in LightGBM and Random Forest-based models. The new method described here is an important advancement in CAI prediction methodology. It is more accurate and efficient than traditional experimental testing methods, and it works well on different types of rock. Its engineering applicability has been proven through real-world operational scenarios.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-22098-9.

Research on rock slope stability, particularly considering joints and creep parameters, plays an important role. In this paper, the authors present an experimental procedure for determining the instantaneous mechanical parameters of rock using uniaxial compression and Brazilian tests, as well as for identifying creep parameters through three - point bending tests on beam - shaped rock specimens. The creep parameters obtained from laboratory tests were converted for use in numerical simulations. The Itasca 3DEC software was then employed to evaluate slope stability, incorporating both joint structures and the creep behavior of rock masses

Abstract Conventional slope stability analyses often rely on two-dimensional models, which neglect local geological heterogeneity and spatial distribution of materials. This simplification can lead to inaccuracies in evaluating slope safety. Additionally, traditional strength reduction methods (SRMs) uniformly reduce the parameters of rock and soil, failing to represent the actual degradation process during progressive failure. This study aims to improve the accuracy of slope stability analysis by developing a method that better captures the spatial variability of geological conditions and the nonsynchronous degradation of shear strength. A three-dimensional (3D) geological model was constructed to restore the actual stratigraphic structure of the slope. Based on the shear strength degradation mechanism, a nonsynchronous coordinated reduction (NSCR) method was proposed, incorporating advanced reduction steps (n) and a correlation factor (λ). This method simulates progressive slope failure more realistically. An engineering case study demonstrated that the 3D NSCR method obtained a safety factor of Fs = 1.265, which is very close to that of the most critical two-dimensional limit equilibrium method section (with a difference of about 1%), whereas the traditional SRM and the two-dimensional coordinated reduction method show relatively larger errors. The 3D analysis revealed the overall dangerous slip surface, providing enhanced insight into slope instability mechanisms. The proposed NSCR method, supported by 3D geological modeling, improves the accuracy of slope stability analysis by better representing progressive failure. It is a feasible and effective tool for engineering applications involving complex slope conditions.

ABSTRACTOwing to deposition, weathering, and historical loading variations, the mechanical properties of underground rock and soil masses demonstrate significant spatial variability and stratified distribution. This study investigates the influence of multi‐layer soil spatial variability on ground settlement and tunnel reliability during shield tunnel construction by developing a refined stochastic finite element model. The CPSO‐TLOOA‐Stacking hybrid intelligent algorithm optimizes the inversion of multi‐stratum mechanical parameters based on the measured surface settlement data from tunnel engineering and the Conditional Tabular GAN (CTGAN) data extension framework. Utilizing the Karhunen–Loève (K‐L) series expansion method and random field theory, a joint analysis framework of stochastic finite element and probability statistics is constructed to evaluate the impact of spatial random field parameters of different soil layers on formation deformation and failure probability. Coupled with the Hamiltonian Monte Carlo‐Subset Simulation algorithm, the reliability of tunnel deformation under conditions of cross‐correlated random fields with multiple surrounding rock parameters is effectively assessed. The results indicate that the R2 value of the expanded dataset fitted by the CPSO‐TLOOA‐Stacking hybrid intelligent algorithm is 99.46%, and the relative error between the dataset and the measured value is 0.7%. The Hamiltonian Monte Carlo‐Subset Simulation algorithm significantly enhances the calculation efficiency of tunnel deformation reliability and provides valuable guidance for shield tunnel construction and design.

Due to inherent geological uncertainties, slope stability is a critical factor in open-pit mining operations. These uncertainties affect stability assessments, including spatial variability, weathering, and human factors. The quarry in Vilonya, Hungary, excavates dolomite rock, characterized by fragmentation and variable joint conditions. Post-mining, stability is assessed to determine whether slopes can maintain steeper angles than the standard 45°. This study evaluates the stability of slopes in the Vilonya dolomite quarry using probabilistic methods to account for geotechnical variability and to assess the feasibility of steeper slope angles. A combination of field measurements, laboratory tests, and computational analyses were employed. Joint orientations and roughness were determined through photogrammetry and Barton comb measurements. Statistical analysis of rock parameters were done by software like Analytic Solver. Stability was analyzed using Rocscience software (Dips, RocPlane, SWedge, Slide2) for various failure mechanisms, including planar and wedge sliding, as well as global stability. Kinematic analyses identified critical joint sets that may contribute to slope failure. Probabilistic assessments showed that some joint intersections present failure probabilities as high as 67.42% for wedge failure, while planar sliding risks were negligible. Global stability analysis indicated no critical failures, with safety factors consistently above 1.35 across all slopes. Probabilistic methods reveal significant insights into slope stability that deterministic approaches may overlook. The study confirms the feasibility of maintaining steeper slope angles under controlled risk, optimizing extraction while ensuring stability. Incorporating probabilistic analysis is recommended for reliable slope design in similar geological settings.

This paper explores the mechanisms of energy transfer and failure zones in rock mass blasting. By combining theoretical derivation with numerical simulation, we examine the deformation, failure features, and source parameters of rock subjected to spherical charge blasting. Using the Mohr–Coulomb yield criterion, we classify the rock failure process into four zones: the cavity zone, fracture zone, radial fracture zone, and vibration zone. Additionally, we establish a dynamic partitioned model that considers explosion cavity expansion, compression wave propagation, and energy dissipation. Applying elastic failure conditions, we develop a calculation model for vibration parameters in each zone and use MATLAB programming to find numerical solutions for the radius of the failure zone, elastic potential energy, and the interface pressure over time. Verification with a granite underground blasting project in Qingdao shows the ratio of the spherical cavity radius to the charge radius is 1.49, and the crushing zone radius to the charge radius is 2.85. Theoretical results are consistent with the approximate method in magnitude and value, confirming the model’s reliability. The interface pressure sharply peaks and then decays exponentially. The growth of the fracture zone depends heavily on initial pressure, rock strength, and Poisson’s ratio. These findings support blasting engineering design and seismic effect assessment.

Anisotropic properties of fracture zone in sandstone inferred from seismic moment tensors of acoustic emissions.

ABSTRACT Slope stability is one of the key factors for the safe operation of large-scale hydropower projects. Based on the deformation monitoring data of a hydropower station bank slope, Particle Swarm Optimization (PSO) is employed to improve the Gaussian Process Regression (GPR) method for intelligent inversion of rock and soil mechanical parameters. This approach overcomes the limitations of traditional inversion methods, such as low computational efficiency and strong multi-solution nature. The error between the inversion and measurement does not exceed 35% and normalised RMSE is 0.384, which verifies the reliability of the algorithm. Based on the inverted parameters, the limit equilibrium method is used to calculate the slope safety factor and the potential sliding blocks are determined with 6 blocks on the left side and 7 blocks on the right side. Safety factors of these potential sliding slopes are all larger than 1.25, which means that no more support system is needed. This research not only provides a novel method for calibrating geo-mechanical parameters but also establishes an integrated inversion-analysis technical framework. This framework offers theoretical support for safety warnings and reinforcement decisions of similar hydropower slopes, demonstrating significant engineering value for ensuring the whole life-cycle safety of major infrastructure.

The applicability of similar materials is a key factor affecting the results of geomechanical model tests. In order to investigate the multi-physical field evolution mechanism of surrounding rocks during water inrush disasters in tunnels crossing fault zones, based on the similarity theory of geomechanical model tests, the physical-mechanical parameters of a prototype rock's mass were first analyzed for similarity, and the target values of similar materials were determined. Secondly, using sand as coarse aggregate, talcum powder as fine aggregate, gypsum and clay as binders, and Vaseline as a regulator, a fault-simulating material suitable for model tests was developed through extensive laboratory experiments. Finally, with material deformation characteristics and strength failure characteristics as key control indicators, parameters such as uniaxial compressive strength, permeability coefficient, unit weight, and elastic modulus are synergistically regulated to determine the influence of different component ratios on material properties. The experimental results show that the uniaxial compressive strength and permeability coefficient of similar materials are mainly controlled by gypsum and Vaseline. Cohesion is mainly controlled by clay and Vaseline. The application of this similar material in the model test of the tunnel fault water inrush disaster successfully reproduced the disaster evolution process of fault water inrush, meeting the requirements of the model test for similar materials of faults. Furthermore, it provides valuable guidance for the selection of similar materials and the optimization of mix proportions for fault disaster model tests involving similar characteristics.

Abstract Reaction‐driven cracking has been discussed for decades. One mechanism is the extension of a microcrack resulting from precipitation. This mechanism can create porosity, permeability and reactive surface area in low‐permeability rock. We model this problem as a fracture loaded over a fraction of its length by a vein. The loading causes crack propagation when the stress intensity factor reaches its critical value. We calculate the conditions for the onset of crack growth, the time required, pressure distribution around the vein, and the crack surface displacements. These results are relevant to many problems. One application is to geological storage of by mineralization. Results depend strongly on rock parameters but using representative values from experiments, our calculations suggest an initiation time within tens of years at low temperature and dilute fluid conditions. Lower critical stress intensity factor, higher reaction rate, and greater carbonate filling ratio reduce the time to initiation.

ABSTRACTThe Yin‐E Basin, located at the junction of the Siberian, Kazakhstan, and Tarim blocks and the North China Craton, has experienced complex tectonic activities and remains one of the underexplored onshore sedimentary basins in China. The Upper Palaeozoic is an important stratigraphic interval for oil and gas exploration, but its source rock thermal evolution lacks systematic research, thus hindering exploration progress. Addressing the frontier topic of very low‐grade metamorphism's role in organic maturation, we studied the clay mineralogy (illite crystallinity: 0.42°–0.25° Δ2θ), illite polymorphism (predominantly 2 M1), and cell parameters (b0: 9.0024–9.0204 Å) of the Upper Palaeozoic source rocks (wells YBC1, BD1 and YBN1) in the Suhongtu Depression, revealing the palaeogeothermal field of the Upper Palaeozoic. These data were combined with basin modelling to quantitatively constrain the thermal evolution history. The results indicate that the Upper Palaeozoic strata primarily underwent prehnite‐pumpellyite‐facies of very low‐grade metamorphism under medium‐low pressure, corresponding to peak temperatures of 211.94°C–226.32°C. The reconstructed palaeotemperature reached 210°C–220°C. By the end of the Permian, all source rocks had reached their maximum thermal maturity (vitrinite reflectance, Ro: 1.42%–2.42%), with the Ba'nan Sag showing significantly higher maturity (Ro: 1.57%–2.42%). This study provides key constraints on the thermal evolution and hydrocarbon generation potential of Upper Palaeozoic source rocks, supporting future exploration in the Yin‐E Basin and adjacent areas.

Fluid factor plays a crucial role in seismic fluid discrimination, but it is influenced by the complex petrophysical properties of reservoir rocks, which also leads to the statistical diversity of reservoir parameters. In this study, the commonly used Russell fluid factor is first investigated using the inclusion-based rock-physics theory. Rock-physics analysis reveals that the Russell fluid factor is constrained by lithology and a dry rock parameter that is difficult to determine for real reservoirs. To address these limitations, a new fluid factor is developed. Theoretical analysis and field data application illustrate its wide applicability. In addition, to reduce the prediction bias caused by the complex petrophysical properties, a generalized mixture prior considering the lithology contribution is developed. This innovative approach enables the characterization of the lithology-based probabilistic statistical distributions of different reservoir parameters. Field data tests, such as well-logging and seismic data, demonstrate the advantages of our approach, which is helpful in identifying the hydrocarbon-bearing zones in complex reservoirs.

The deformation characteristics of the surrounding rock in tunnel groups are considered critical for the design of support structures and the assurance of the long-term safety of deep-buried diversion tunnels. The deformation behavior of surrounding rock in tunnel groups was investigated to guide structural support design. Field tests and numerical simulations were performed to analyze the distribution of ground stress and the ground reaction curve under varying conditions, including rock type, tunnel spacing, and burial depth. A solid unit–structural unit coupled simulation approach was adopted to derive the two-liner support characteristic curve and to examine the propagation behavior of concrete cracks. The influences of surrounding rock strength, reinforcement ratio, and secondary lining thickness on the bearing capacity of the secondary lining were systematically evaluated. The following findings were obtained: (1) The tunnel group effect was found to be negligible when the spacing (D) was ≥65 m and the burial depth was 1600 m. (2) Both P0.3 and Pmax of the secondary lining increased linearly with reinforcement ratio and thickness. (3) For surrounding rock of grade III (IV), 95% ulim and 90% ulim were found to be optimal support timings, with secondary lining forces remaining well below the cracking stress during construction. (4) For surrounding rock of grade V in tunnels with a burial depth of 200 m, 90% ulim is recommended as the initial support timing. Support timings for tunnels with burial depths between 400 m and 800 m are 40 cm, 50 cm, and 60 cm, respectively. Design parameters should be adjusted based on grouting effects and monitoring data. Additional reinforcement is recommended for tunnels with burial depths between 1000 m and 2000 m to improve bearing capacity, with measures to enhance impermeability and reduce external water pressure. These findings contribute to the safe and reliable design of support structures for deep-buried diversion tunnels, providing technical support for design optimization and long-term operation.

Background. The modern oil industry is paying more and more attention to increasing the oil recovery of hard-to-recover reserves. The results of a few field tests without application of geological and technical measures for flow stimulation limit the possibility of substantiating criteria for selecting promising areas for development and pilot operations. The study of the rock features of the Khadum Formation (Р3hd) of the East Pre-Caucasian oil and gas region was carried out using data from core samples with ultralow filtration and capacitance properties. It is proposed to substantiate and use certain geochemical properties of rocks and organic matter and pyrolytic parameters as indicators of oil content. Objective. To study the variability of the geochemical properties of the Khadum deposits and identify the dependencies between them for the subsequent identification of the most promising oil and gas zones according to a group of geological and geochemical criteria. Materials and methods. The paper presents the geochemical characteristics and comparison of the main pyrolytic parameters for rocks of the Khadum Formation. Pyrolysis data (by the Rock-Eval method) from core and field information from oil fields were used. Results. The predominance of two types of kerogen was established and two types of rocks with different hydrocarbon potential were identified. The distribution schemes of the main geochemical characteristics of the Khadum Formation and the distribution of established rock types with different hydrocarbon potential within the Eastern Pre-Caucasus are compiled. Conclusions. A new approach to identifying the most promising oil- and gas-bearing areas within the Khadum Formation on the basis of geochemical criteria is proposed, based on the identification of two types of reservoir rocks with different hydrocarbon potential in terms of S1, S2, Тmax, HI and OSI parameters.

Micro-fracturing technology is a key approach to enhancing the flow capacity of oil sands reservoirs and improving Steam-Assisted Gravity Drainage (SAGD) performance, whereas heterogeneity in reservoir physical properties significantly impacts stimulation effectiveness. This study systematically investigates the coupling mechanisms of asphaltene content, clay content, and heavy oil viscosity on micro-fracturing stimulation effectiveness, based on the oil sands reservoir in Block Zhong-18 of the Fengcheng Oilfield. By establishing an extended Drucker–Prager constitutive model, Kozeny–Poiseuille permeability model, and hydro-mechanical coupling numerical simulation, this study quantitatively reveals the controlling effects of reservoir properties on key rock parameters (e.g., elastic modulus, Poisson’s ratio, and permeability), integrating experimental data with literature review. The results demonstrate that increasing clay content significantly reduces reservoir permeability and stimulated volume, whereas elevated asphaltene content inhibits stimulation efficiency by weakening rock strength. Additionally, the thermal sensitivity of heavy oil viscosity indirectly affects geomechanical responses, with low-viscosity fluids under high-temperature conditions being more conducive to effective stimulation. Based on the quantitative relationship between cumulative injection volume and stimulation parameters, a classification-based optimization model for oil sands reservoir operations was developed, predicting over 70% reduction in preheating duration. This study provides both theoretical foundations and practical guidelines for micro-fracturing parameter design in complex oil sands reservoirs.

A specific energy and penetration interaction-based method for optimizing TBM operational parameters in hard rock

A succesful petrophysical evaluation of shaly-sand formations requieres: 1) the availability of high quality well log data and, 2) a petrophysical model that successfully represents the geological conditions of the rocks. Unfortunately, it is not always possible to fulfill these conditions, and in many cases the set of well logs is incomplete. To determine petrophysical parameters (i.e., volumes of laminar, structural and disperse shale) in clastic rocks from incomplete well log data we followed three approaches which are based on a hierarchical model, and on a joint inversion technique: 1) Available well log data (excluding the incomplete well log) are used to train machine learning algorithms to generate a predictive model; 2) the first step of the second approach machine learning algorithms are used to generate the missing data which are subsequently included a joint inversion; 3) in the third approach, machine learning process is used to estimate the missing data which are subsequently included in the prediction of the petrophysical properties. The supervised learning paradigm we used was in a joint based on different regression models (linear, decision trees, and kernel). A performance analysis of the three approaches is conducted with synthetic data (representing real conditions of clastic formations from an oil field in southern Mexico). We simulated gamma ray, deep resistivity, P-wave travel time, bulk density and neutron porosity logs by means of a hierarchical petrophysical model for clastic rock to accomplish a controlled analysis. The three different approaches were applied without P-wave travel time data to analyze the impact of the missing information. In general, the results indicate an adequate petrophysical parameter determination in each of the approaches. Metric evaluations indicate that the best performance was obtained by the second approach followed by approaches one and three. The correct estimation of the volumes of shale distribution could not be correctly resolved by any of the three applied methods but the total shale content could accurately be predicted which suggests that there is a non-uniqueness problem.

Underground longwall mining conducted in the vicinity of the barrier pillars in the KWK ROW Ruch Marcel mine has led to volume changes in the rock mass. As the longwalls progressed, a gradual increase in stress occurred in the goaf overburden, as a result of which this part of the rock mass increased in density in relation to the surrounding strata. Seismic events occurring during mining as a result of elastic energy accumulation led to the relaxation of the medium and local decreases in its bulk density. The microgravimetric method is sensitive to variations in this physical parameter of rock. The most transparent effects of the differences in rock mass density can be observed by performing periodic local gravity field surveys and analysing their spatial and temporal variability. This paper analyses the relationship between ground deformations and the spatial and temporal gravity field distribution changes observed on the surface in the context of the safety of barrier pillars F1 and F2 in Marklowice (the GSB-GFO testing ground of project EPOS-PL+). Relative gravimetric surveys, referenced to the determined absolute values of g, were performed in 7 series over the period of 2021–2023. The collected data made it possible to chart differential maps of gravity field changes and anomalies with Bouguer reduction. The differential anomaly distributions between successive survey series and the reference series were analysed. This served as the basis for assessing the safety of the barrier pillars maintained by the mine and the possibility of ground deformation occurrence on the surface.