Geomechanical Properties Research Articles

Investigating the effect of nano-CaCO3 on the geomechanical properties of clay contaminated with waste leachate

Matrix acidizing impact on the geomechanical properties in carbonate rocks: an experimental approach using acetic acid at different contact times

Oil production from Achimov and Tyumen formations is steadily increasing. Productive zones are characterized by low reservoir properties. The presence of underlying water-saturated intervals and thin clay interlayers separating oil-saturated and water-saturated formations leads to high water cut of the well product when using hydraulic fracturing designs on cross-linked gel. Operation is carried out by horizontal wells with multi-stage hydraulic fracturing. To increase well productivity and reduce water cut, hybrid hydraulic fracturing designs are used using large proppant masses and volumes of process fluids. Calculations of such designs in the hydraulic fracturing simulator showed that the fractures are characterized by complex geometry and uneven distribution of proppant.Application of a uniform fracture design calculated in the reference well leads to a significant error in hydrodynamic calculations for heterogeneous reservoirs of the Achimov and Tyumen formations. To account for the heterogeneous structure and uneven distribution of properties in the pay zone and hydraulic fractures, a method for calculating well performance indicators has been proposed that improves the reliability of forecasting. At the first stage, a reference well is selected near the drilled area. Correlation relationships between static and dynamic geomechanical properties for construction of geomechanical model are restored by existing complex of well geophysical studies and core studies. This model is used to reconstruct correlation relationships between geomechanical properties and reservoir properties. When performing hydrodynamic calculations in the target horizontal well in the intervals of hydraulic fracturing ports, geomechanical properties are restored based on data from property cubes in the hydrodynamic model (porosity, permeability, lithology), and a geomechanical model is constructed. The model is fed into a hydraulic fracturing simulator, which calculates the design of each fracture. Based on the calculation results, maps of the distribution of reservoir properties in the fracture are built, which are imported into a hydrodynamic simulator to predict well performance indicators.Based on the results of hydrodynamic calculations, the effectiveness of the proposed method for predicting the performance of wells with hydraulic fracturing was confirmed in comparison with the standard forecasting approach.

ABSTRACT The growing challenges associated with the disposal of industrial wastes have compelled engineers to explore their utilisation in the construction sector. In this context, this study aims to explore the suitability of brick kiln waste (BKW) treated with some percentage of cement as a substitute for natural soil in various geotechnical engineering applications. A comprehensive experimental programme was carried out in which ordinary Portland cement (2%, 4%, 6%, 8% and 10% by dry weight of BKW) was added to assess its impact on the geomechanical properties of BKW. Strength improvement was assessed through unconfined compressive strength (UCS), split tensile strength (STS), direct shear (DST) and California bearing ratio (CBR) tests on samples cured for 7, 14 and 28 days. The results revealed a significant enhancement in strength with cement addition and curing, with UCS reaching 1435 kPa at 8% cement, cohesion increasing from 14.6 to 62.7 kN/m 2 , friction angle from 35.4 ∘ to 48.5 ∘ and CBR improving from 12.7% to 36.8% (unsoaked) and 7.1% to 23.4% (soaked). Microstructural analysis using XRD, FESEM and EDAX indicated morphological changes, reduction of voids and formation of a cohesive binding matrix. Thus, BKW utilisation not only addresses disposal issues but also provides a sustainable construction material.

Underground hydrogen storage (UHS) in underground geological reservoirs is a promising solution for large-scale energy storage. However, several challenges, particularly geomechanical ones, must be resolved before UHS can be widely and safely deployed. The interactions between hydrogen, brine, and reservoir rock, combined with the cyclic stresses resulting from hydrogen injection and withdrawal may affect the mechanical integrity of the reservoir, the caprock, as well as its surrounding formations. This is an experimental investigation into the geomechanical impact of a 6 month exposure of clay-rich sandstone (Yellow Felser) rocks to hydrogen and/or brine. Cm-scale samples were exposed to hydrogen-saturated brine at 150 bar and 100^{circ }hbox {C} in an autoclave for the period of six months. Afterwards, triaxial cyclic loading experiments were conducted on the samples under confining pressures of 10, 20, and 30 MPa. The results are compared with those from the reference samples, which have been exposed to brine only, for the same time period. Each mechanical test included eight stress cycles in the linear stress regime (below the brittle yield point), followed by loading to failure. The frequency, amplitude, and stress conditions were tailored to each confining pressure. The results showed that six months of hydrogen-saturated brine exposure had no noticeable effect on the failure envelope, elastic properties, inelastic strain, and acoustic properties of the Yellow Felser sandstone compared to exposure to brine alone. Internal friction, P-wave velocity, and Young’s modulus each showed a change of around 3%, which is on the same order as the repeatability and therefore indicating minimal geomechanical alteration. Complementary qualitative and quantitative scanning electron microscopy (SEM) analyses revealed negligible microstructural changes. When eight stress cycles were applied within the linear stress regime, the majority of inelastic strain occurred during the first cycle, with no progressive accumulation thereafter. A comparison with samples tested under monotonic loading to failure confirmed that cyclic loading under these conditions does not affect the rock strength of Yellow Felser sandstone. These findings provide new insights into the combined effects of cyclic stress and hydrogen/brine/rock interactions on the geomechanical behavior of clay-rich sandstones under reservoir-relevant pressure and temperature conditions.

Mauddud formation is one of the most prominent formations in Northeastern Iraq due to its significant hydrocarbon reserves, making accurate geomechanical characterization essential for safe drilling operations and informed development planning. This study constructs a calibrated post-drill one dimensional mechanical earth model (1D-MEM) for selected wells, levering Techlog software to integrate rock mechanical data, image logs, multi-arm caliper measurements, conventional well logs, drilling reports, and core analyses. The methodology provides a detailed workflow for estimating geomechanical properties from log and image analysis to model calibration. Validation of the 1-D MEM performed through cross-comparison with direct measurements, ensuring the reliability of the predicted stress and strength profile. Laboratory and field data including pore pressure measurements using DST method, destructive and non-destructive mechanical tests, scanning electron microscopy (SEM), thin section test (TS), X-ray diffraction test (XRD), and energy-dispersive X-ray spectroscopy (EDS) have all been used for analyzation and calibration process. These datasets enhance the MEM parameters and support the derivation of empirical correlation specific to the Mauddud Formation. Derived correlations include compressional-shear slowness velocity, slowness velocity- bulk density, compression slowness-unconfined compressive strength (UCS), and the Young's modulus to UCS correlation. Results show that mineralogical composition particularly porosity and calcite content have a dominant influence on formation strength with high porosity, low calcite intervals resulting in the lowest UCS values.

It is well known that drilling challenges, in addition to fluctuating oil prices and increasing competition for production, can contribute to unscheduled field expenditures exceeding one billion U.S. dollars annually. This study emphasizes the importance of integrating geomechanical principles into petroleum engineering, which includes reservoir, drilling, and production operations. A case study was conducted on one well in Rumaila oilfield, located in southern Iraq, to determine the geomechanical properties of carbonate, sandstone, and shale formations. Stress regimes, elastic, and rock strength properties were analyzed. The results showed the stress regime is a strike-slip regime from the Sadi to Zubair formations. The Tanuma formation exhibits low elasticity and strength properties, indicating optimized mud rheological properties for effective lifting capacity. The MishCR1 reservoir, as a producible formation with high rock mechanical stability, can resist compaction and fault reactivation. Other oil-producible reservoirs (MishMA, MishMB2, MishMB1, Zu1, and Zu2) have moderate geomechanical properties, requiring tailored production rates, pressure management, and enhanced recovery methods to mitigate deformation risks. For sandstone reservoirs (Zu1 and Zu2), gravel packing or chemical stabilization is recommended to sustain reservoir performance and enhance oil recovery. This study presents the need for geo-mechanical insights to optimize petroleum operations and mitigate production risks.

This paper presents a methodology for assessing the stability of stoping chambers and inter-chamber pillars (ICPs) during underground mining of ore bodies with varying dip angles. The objective is to determine optimal parameters for excavation elements (chamber width and pillar spacing) that ensure the stability of the mining system under fractured rock mass conditions. The Zhezkazgan deposit’s geomechanical properties were used as the modeling case study. The methodology includes geotechnical core mapping (with RQD, Q-system, and GSI classifications), laboratory strength testing, field–laboratory correlation, and numerical modeling using the finite element method. Particular focus is placed on the sensitivity of stability to variations in GSI, depth, and excavation geometry. The results indicate that increasing the dip angle significantly reduces the stability of both chambers and pillars. The novelty of this study lies in the comprehensive assessment of structural factors and excavation geometry on mass stability under site-specific geological conditions.

Because pore fluids have less influence on shear waves, S-wave velocity ([Formula: see text]) directly measures a rock frame’s stiffness. However, direct [Formula: see text] measurements are scarce in the vintage wells of the Delaware Basin. Although empirical and traditional machine-learning methods have been used to predict [Formula: see text] from conventional well logs, their estimates often depend on specific geologic formations or boundary conditions. In this study, we develop a self-attention, bidirectional long short-term memory (BiLSTM) model with depth-ordered sequences and automated hyperparameter optimization to overcome these limitations, requiring no prior geologic information. Trained on P-wave velocity, density, total porosity, and gamma-ray logs from 123 wells, the model captures nonlinear relationships in the data, achieving an [Formula: see text] of 0.85 and surpassing existing empirical and regression-based approaches. Further validation in blind tests with eight wells in different counties demonstrates accurate [Formula: see text] predictions throughout the basin where direct [Formula: see text] logs are missing. To interpret the model’s “black box,” we compute Shapley values to quantify each input’s contribution to [Formula: see text] predictions. In addition, the BiLSTM’s superior performance extends to geomechanical properties, such as bulk modulus ([Formula: see text]), shear modulus ([Formula: see text]), Young’s modulus ([Formula: see text]), and Poisson’s ratio ([Formula: see text]), highlighting its practical utility in seismic applications such as energy exploration and development, geothermal energy, carbon and hydrogen storage, and induced seismicity monitoring.

This study presents an expert system for assessing the stability of underground mine workings and automatically selecting rock bolt support schemes. The system integrates physically based calculations of roof compressive strength (Rc) and expected maximum displacement (Um) with rule-based decision logic grounded in engineering practice. Unlike empirical classifications and black-box AI models, the proposed approach ensures interpretable, reproducible, and context-aware engineering decisions. The architecture includes a numerical solver that computes Rc and Um based on excavation geometry, geomechanical properties, and mining conditions. The support scheme is selected using a knowledge base of formalized rules, while the specific support parameters are calculated within the solver. The system was validated across 51 underground excavations, with approximately 85% of its recommendations matching field-proven support solutions, and 12% suggesting reinforced schemes that could have prevented failures. The expert system is suitable for integration into digital mine management platforms and offers a foundation for developing digital twin solutions in geomechanically variable environments.

Construction industry commonly produces a significant amount of Quarry dust and hollow block powder as a by-product, posing challenges for its disposal due to limited space for storage and its fine nature. Previous studies have explored various avenues for ash reuse, including in cement, bricks, tiles, concrete, soil stabilization, raising ash dikes, backfilling low-lying areas, constructing roads and bridge abutments, and in agricultural applications. However, one less explored area is the reutilization of ash in developing Controlled Low Strength Material (CLSM), also known as flowable fill. CLSM is a self-compacting material consisting of fine aggregates, cement, water, and other recycled materials that flows like a liquid and hardens over time. Traditionally, river sand is the preferred backfill material due to its wide availability and favourable geotechnical properties. However, with the increasing demand and shortage of river sand, there is a need for alternative and cost-effective backfill materials that have minimal adverse effects on the environment, which can be fulfilled by CLSM. Additionally, due to its high flowability and self-compacting properties, CLSM can be used in locations where conventional backfill materials are not easily accessible or where compaction equipment cannot reach. Researchers have successfully developed CLSM using various recycling materials such as fly ash, quarry dust and GGBS. Industrial wastes can effectively partially replace cement and/or sand in CLSM, making it economical and environmentally sustainable. Key properties of CLSM to be evaluated include flowability, hardening time and compressive strength. This study focuses on evaluating different CLSM compositions using GGBS, FA, and BA partially replacing cement and Quarry dust to replace sand through experimental studies on flowability and compressive strength. The study aims to achieve maximum possible cement replacement with three different cementitious pozzolanic materials to make it more sustainable and to understand the effect of reducing cement content in CLSM properties.

Blasting is one of the most widely used and cost-effective techniques for rock excavation and fragmentation in open-pit mining, particularly for large-scale operations. However, repeated or poorly controlled blasting can generate excessive ground vibrations that threaten slope stability by causing structural damage, fracturing of the rock mass, and potential failure. Evaluating the effects of blast-induced vibrations is essential to ensure safe and sustainable mining operations. This study investigates the impact of blasting-induced vibrations on slope stability at the Saindak Copper-Gold Open-Pit Mine in Pakistan. A comprehensive dataset was compiled, including field-monitored ground vibration measurements—specifically peak particle velocity (PPV) and key blast design parameters such as spacing (S), burden (B), stemming length (SL), maximum charge per delay (MCPD), and distance from the blast point (D). Geomechanical properties of slope-forming rock units were validated through laboratory testing. Slope stability was analyzed using pseudo-static limit equilibrium methods (LEMs) based on the Mohr–Coulomb failure criterion, employing four approaches: Fellenius, Janbu, Bishop, and Spencer. Pearson and Spearman correlation analyses quantified the influence of blasting parameters on slope behavior, and sensitivity analysis determined the cumulative distribution of slope failure and dynamic response under increasing seismic loads. FoS values were calculated for both east and west pit slopes under static and dynamic conditions. Among all methods, Spencer consistently yielded the highest FoS values. Under static conditions, FoS was 1.502 for the east slope and 1.254 for the west. Under dynamic loading, FoS declined to 1.308 and 1.102, reductions of 12.9% and 11.3%, respectively, as calculated using the Spencer method. The east slope exhibited greater stability due to its gentler angle. Correlation analysis revealed that burden had a significant negative impact (r = −0.81) on stability. Sensitivity analysis showed that stability deteriorates notably when PPV exceeds 10.9 mm/s. Although daily blasting did not critically compromise stability, the west slope showed greater vulnerability, underscoring the need for stricter control of blasting energy to mitigate vibration-induced instability and promote long-term operational sustainability.

This paper presents the procedures and results of the numerical modelling and simulations performed to analyse an innovative method of advanced methane drainage employing underground long-reach directional drilling (LRDD) technology. The analysis involved the implementation of geomechanical and dynamic reservoir models to simulate processes in coal seams and the surrounding rocks during coal mining and concurrent methane drainage, in accordance with the proposed technology. The analysis aimed to quantitatively assess the effectiveness of the technology, evaluate its sensitivity to the geological and geomechanical properties of the rocks, and identify the potential for optimisation of its technological and operational parameters in the proposed strategy. The works presented in this paper include the following key tasks: the construction of a system of geological, geomechanical, and dynamic simulation models; the analysis of the geomechanical effects of various types and regions of occurrence; the implementation of the correlation between the geomechanical states of the rocks and their transport properties; and the performance of the effectively coupled geomechanical and reservoir fluid flow simulations. The proposed approach was applied to the specific conditions of the multi-seam Murcki–Staszic Coal Mine operated by Jastrzębska Spółka Węglowa, Poland.

Exploring Machine Learning Techniques for Open Stope Stability Prediction: A Comparative Study and Feature Importance Analysis

In the fields of blasting and geological exploration drilling, understanding the drilling speed at various times and depths is crucial. This speed can reveal valuable insights into the hardness and geomechanical properties of the soil and rock being drilled. The study at hand presents an innovative solution for determining and monitoring drilling speed through the integration of two advanced technologies: the Global Navigation Satellite System (GNSS) and the Inertial Measurement Unit (IMU). The IMU signals play a pivotal role in identifying the precise drilling times, while the GNSS-based elevation data are employed to obtain real-time measurements of drilling speed. By combining these technologies, the study aims to enhance the accuracy and efficiency of drilling operations. The experimental results are promising, indicating that the integrated GNSS RTK/IMU system can automatically monitor real-time drilling speed with remarkable precision, achieving millimeter-per-second accuracy. This approach not only improves the monitoring process but also provides a more detailed understanding of the subsurface conditions. The ability to accurately measure drilling speed in real-time allows for better decision-making and optimization of drilling strategies. Consequently, this integration of GNSS and IMU technologies represents a significant advancement in the field of geological exploration and blasting, offering a reliable and precise method for assessing the geomechanical properties of the soil and rock.

Facies-driven correlations based on rock porosity for the assessment of geomechanical properties of carbonate rocks in Santos Basin

Long-term effects of hydrogen and brine on the geomechanical properties of Berea sandstone– An experimental study

Wave velocity logs are vital in identifying reservoir lithology, physical properties, geomechanical properties, and fluids in geophysical exploration. However, direct measurement of wave velocities through well logs or core labs is often constrained by financial, technical issues, and site conditions. The novelty of this study lies in constructing new models of compressional and shear wave velocities across various scenarios. This paper proposes artificial neural networks and regression analysis techniques to estimate compressional and shear wave velocities. The proposed models were developed based on datasets from 11 wells drilled in the Rumaila oilfield, located in the southern region of Iraq. The raw datasets are composed of compressional wave, shear wave, formation depth, Neutron porosity, and bulk density. The key distinction between this study and previous literature is that it examines all possible instances of data scarcity that may arise in this field of interest, which in turn affects the determination of geomechanical rock properties. The models were developed based on either one parameter, two or three parameters. These models demonstrated a high R2 value of up to 0.974 and a low mean square error as low as 0.0016. A validation has been done using data from other two wells within the same field of interest as well as from one well in Halfaya oil field within Missan governorate in southern Iraq. The results underscored the efficiency and generalizability of the developed ANN models beyond the initial data sets that affirm the reliability in practical fields’ life.

The objective of this paper was to predict and geomechanically characterize the reservoirs in the JAY oil-fields (JAY-25, JAY-26, JAY-30, and JAY-33) in the Niger Delta Region of Nigeria using Probability Neural Network (PNN) and Multilayered Feed Forward Network (MLFN) machine learning algorithms which subsequently identified a reservoir of interest. By employing a combination of gamma ray, resistivity logs, volume of shale, porosity, and water saturation logs. Data obtained showed that the reservoir is porous with a high concentration of exploitable hydrocarbons. Well correlation analysis suggests good continuity of sand (reservoir) and shale (seal) packages in the field. Results from these two machine learning algorithms were compared to determine the more reliable technique to predict geomechanical properties for the field from seismic data. The feasibility study results for predicted Young's Modulus using Probabilistic Neural Network (PNN) outperformed Multilayer Feed forward Neural Network (MLFN), showing correlation coefficients of 0.99 and 0.98, respectively. Cross-validation correlations were 0.96 and 0.87 for PNN and MLFN, respectively. Similarly, PNN demonstrated higher performance in predicting Poisson ratio with correlation coefficients of 0.998 compared to MLFN's 0.996, and cross-validation correlations of 0.99 and 0.95 respectively. Therefore, the PNN technique is recommended for predicting both geomechanical properties from seismic in the field. These findings underscore the effectiveness of machine learning models in capturing geomechanical patterns, offering valuable insights for reservoir characterization and exploration in the Niger Delta

The transition to a sustainable energy future hinges on the development of reliable large-scale hydrogen storage solutions to balance the intermittency of renewable energy and decarbonize hard-to-abate industries. Underground hydrogen storage (UHS) in salt caverns emerged as a technically and economically viable strategy, leveraging the unique geomechanical properties of salt formations—including low permeability, self-healing capabilities, and chemical inertness—to ensure safe and high-purity hydrogen storage under cyclic loading conditions. This review provides a comprehensive analysis of the advantages of salt cavern hydrogen storage, such as rapid injection and extraction capabilities, cost-effectiveness compared to other storage methods (e.g., hydrogen storage in depleted oil and gas reservoirs, aquifers, and aboveground tanks), and minimal environmental impact. It also addresses critical challenges, including hydrogen embrittlement, microbial activity, and regulatory fragmentation. Through global case studies, best operational practices for risk mitigation in real-world applications are highlighted, such as adaptive solution mining techniques and microbial monitoring. Focusing on China’s regional potential, this study evaluates the hydrogen storage feasibility of stratified salt areas such as Jiangsu Jintan, Hubei Yunying, and Henan Pingdingshan. By integrating technological innovation, policy coordination, and cross-sector collaboration, salt cavern hydrogen storage is poised to play a pivotal role in realizing a resilient hydrogen economy, bridging the gap between renewable energy production and industrial decarbonization.