bluuebunny/crossref_metadata_2025 huggingface dataset:
Damage Evolution of Sandstone Under Cyclic Loading for Underground Gas Storage
Authors: Zhang Wenhong , Tian Shouceng , Weng Jintao , Sheng Mao , Wang Tianyu , Ma Zhengchao
Published: August 2024

Underground gas storage plays an important component of emergency gas supply and peak shaving capabilities in winter. It plays a vital role in ensuring the security of natural gas supply. Pressure variations and frequency changes in gas storage can easily cause fatigue damage to formation rocks. The M reservoir is currently in the initial phases of development, and conducting a thorough analysis of reservoir damage deformation under various storage conditions, including storage frequency and fluid pressure fluctuations, is crucial for ensuring safe and efficient operation. In this study, uniaxial compression tests and cyclic loading mechanical experiments are conducted on sandstone samples from M gas storage in Junggar Basin. These experiments combined with the operational data of M gas storage investigate the influence of different frequencies and amplitudes by stress-strain curves and hysteresis loop. Damage variables D are introduced to quantitatively analyze the damage behavior of sandstone at different frequencies and amplitudes. The results show that the compressive strength of sandstone is affected by amplitude and frequency. On the one hand, the higher the amplitude, the lower the rock strength, the fuller the hysteretic loop. On the other hand, the lower the frequency, the lower the rock strength. From the point of view of damage variable, the increase of amplitude prolongs the development cycle of inelastic strain. The higher the amplitude, the greater the final damage. When the amplitude is constant, the increase in frequency reduces the interaction time between the stone particles and the degree of rock damage decreases. The study provides a reference for the construction and safe operation of gas storage reservoirs.

1. INTRODUCTION

Underground gas storage is an important infrastructure for the storage of natural gas resources and the peaking of natural gas supply and demand(He,A., Ma,Q., Pang,Y. et al., 2023). Around the world, there are four main types of gas reservoirs: porous reservoirs, salt caverns, caverns, and depleted reservoirs. Depleted reservoir type gas storage is the most dominant type, with over 80% of the total volume ratio dedicated to working gas. By 2023, China had built 28 gas storage reservoirs with a peaking capacity of 165×109 m3. However, their working capacity only represents 4.4% of China's natural gas consumption, which is far below the minimum requirement of 12% set by the International Gas Union(Changyin, D, Chen, C, Lizhi, W, 2022). Thus, the conversion of depleted gas reservoirs into gas storage has been identified as a highly promising tool. The attention of academic institutions, governments, and oil companies has been drawn to accelerating the construction of gas storage.
Strength Characterization and Empirical Correlations for Carbonate Rocks from the Brazilian Pre-Salt Reservoirs
Authors: Sampaio R. V. , Righetto G. L. , Fontoura S. A. B. , Lima C. , Naumann M.
Published: August 2024

The pre-salt regions in Brazil, especially the Campos and Santos Basins, are responsible for most of the country's hydrocarbon production. Although there has been much discussion about the geological and petrophysical aspects of the carbonate reservoirs found in these areas, information about their mechanical properties is still limited. This study aims to help fill this gap by characterizing the strength of well plugs from four different wells located in the Santos Basin and developing empirical correlations. The samples are lacustrine carbonates of varying lithologies from the Barra Velha Formation, with porosity ranging between 0.7% and 20.5%, and permeability ranging from near-zero to 22.1 mD. The results showed cohesion (c') varying from 11.1 to 43.1 MPa, internal friction angle (φ') between 12.7° and 39.2°, and UCS between 29.2 and 171.7 MPa. The average Poisson's ratio (ν50) was 0.26 ± 0.1, and the Young's modulus (E50) results were between 8.7 and 72.4 GPa. The established empirical correlations between porosity and E50, UCS, c', and φ' were exponential and power equations that provided suitable fitting of the data and could be applied to other carbonates from the Barra Velha Formation.

1. INTRODUCTION

The worldwide exploration and production of carbonate reservoirs for oil and gas have been a significant driving force for the study of these rocks. In the offshore basins of Southeastern Brazil, the lacustrine carbonates are a major challenge for the industry. These rocks are known for being complex and heterogeneous, requiring a wide understanding of the interplay of their geological, petrophysical, and mechanical aspects. Even though most of the country's production comes from pre-salt reservoirs, obtaining well samples for mechanical characterization is expensive and, therefore, rare. Thus, there is a lack of information about the mechanical behavior of these lacustrine carbonates.

Considering this scenario, many authors have been addressing their efforts to develop empirical correlations to be used with parameters such as porosity, sonic wave's transit time, and density, which are easily obtained from well logs. Some of these correlations available in the literature were gathered by Santos and Ferreira (2010). However, due to the complexity of these carbonate rocks, it is important to verify the suitability of the correlations. In this paper, some well plugs from Santos Basin were used in triaxial tests to obtain the Mohr-Coulomb failure envelopes and elastic parameters. In addition, empirical correlations were developed based on the tests' results and the porosity of the specimens.
Shear Strength and 1D Compressibility Characteristics of a Plastic and Non-Plastic Soil Exposed to Wet-Dry Weathering
Authors: Tohm Calvin , Lingwall Bret
Published: August 2024

Seasonal weathering cycles such as wet-dry desiccation weathering can alter geomaterial (weak rock to soil) structure, particle arrangement (i.e. fabric), shear strength, 1D compressibility, and other engineering properties. During the drying and rehydration process associated with wet-dry weathering cycles geomaterial intra-particle forces are altered. These micro-scale changes to rock structure and soil fabric facilitate macro-scale responses in the soils engineering properties. As the number of wetting-drying cycles increases its expected to see the geomaterial mass become fragmented and disjointed due to the formation of drying tensile cracks. Upon rewetting the tensile cracks within the soil mass may partially recover but will still result in altered soil properties. This study sought to investigate how this phenomenon alters a soils shear strength and 1D compressibility properties. To accomplish this a plastic (MH) weathered shale residual and non-plastic (SC) soil was molded at its optimum moisture content (OMC) in accordance with ASTM D698 then exposed to 0, 1, 2, and 10 wetting-drying cycles. It was found that the wetting-drying cycles had a large impact on the MH material. This is most likely a result of the higher swelling clay content in the MH material, resulting in larger amounts of shrink swell that occurring during drying and rehydration of the samples. The SC soil contained relatively little amounts of swelling clay which resulted in smaller amounts of sample alteration that occurred during the weathering cycles.

1. INTRODCUTION

Seasonally driven weathering cycles act as external environmentally driven stresses on near surface soil, rock and intermediary geomaterial (IGM) masses. Seasonal weathering cycles gradually alter geomaterial engineering properties by gradually degrading the material fabric. Seasonal weathering cycles (freeze-thaw and wetting-drying desiccation) interact with the topmost layer of soil or rock in the upper 2 to 5-m and develop an active zone in this depth range in the slope as the degree of weathering over time increase. This ultimately results in degraded soil, weak rock or IGM that becomes fragmented and disjointed at the degree of degradation increases unless repaired through mechanical compaction, grouting, or anchoring.
High-Performance Modeling of Coupled Hydro-Mechanical Behavior with Graphical Processing Units
Authors: Bondarenko N. , Makhnenko R. , Podladchikov Y.
Published: August 2024

Proper consideration of the complexity of coupled processes is essential for accurate assessment of outcomes of geoenergy projects. The potential applications include evaluation of the sealing capacity of caprock, storage potential of the reservoir formation, fluid transport, and induced seismicity risks. The numerical implementation of the governing equations for thermo-hydro-mechanical-chemical response is challenging due to the substantial contrast between the characteristic times of coupled processes. Furthermore, addressing the heterogeneity and anisotropy of geological formations requires development of representative three-dimensional models, which can reach billions of grid points. These challenges are addressed by implementation of pseudo-transient iterative method with the use of graphical processing units (GPU) to achieve low-level parallelization. The implemented numerical codes are formulated in consistent modular structure allowing to enable modules based on the desired applications and are presented for the case of hydro-mechanical coupling. Hydro module handles single- and two-phase flow coupled with the mechanical component. The foundational constitutive framework of mechanical response is Biot's poroelasticity that can be expanded to incorporate viscous- and plastic-deformation. Resolving the governing equations of coupled hydro-mechanical (HM) response with high resolution is a bandwidth-limited problem, highlighting that effective management of memory access is essential for scalability of parallel computations. All the modules are implemented in the single executable file, allowing to limit unnecessary memory access, and resulting in up to 50x performance increase in single-GPU implementation compared to single CPU. The accuracy of HM solver is benchmarked with known analytical solutions for uncoupled and coupled processes.

1. INTRODUCTION

The complex environment of the subsurface frequently involves non-equilibrium mechanical (M), hydraulic (H), and other processes. These processes are inherently interrelated, and their independent consideration requires specific conditions. Precise control over the environmental conditions preserved in laboratory experiments opens way for measurements of material properties required for characterization of the coupled processes. However, laboratory approaches are usually limited in spatial- and temporal-scales, failing to directly address the material response at field scales and potential heterogeneity of geological formations.
Mechanical Upscaling in Highly Heterogeneous Rock Masses: Impact on Anisotropy and Subsurface Stress Prediction in the Bone Spring and Wolfcamp Formations of the Delaware Basin, USA
Authors: Cheng L. , Crawford B. R. , Chen H. , Macquaker J. H. , McLendon D.
Published: August 2024

The unconventional Bone Spring and Wolfcamp Formations are the development focus in the Delaware Basin. However, the high heterogeneity of the reservoir rocks challenges the selection of landing zones and increases the uncertainty of well performance. Estimating faithful elastic properties and predicting stress profiles along the wellbores are key to improve production and stimulation design. We acquire over 3,000 feet of continuous cores from five wells in New Mexico, Delaware Basin. We combine a variety of high-resolution, whole core-based characterization techniques that include hyperspectral and dual energy computed tomography imaging, ultrasonic velocities, and scratch index profiling, to quantify intrinsic, fine-scale variability in vertical transversely isotropic elastic properties indicating Young's modulus and Poisson's ratio perpendicular and parallel to bedding. Geomechanical averaging of this thinly bedded medium is then upscaled to a petro-mechanical facies scale for geological modeling and stress prediction. Elastic anisotropy as an emergent property of the upscaling process is contrasted with the anisotropy determined from the traditional core-plug based approach. Implications for stress profile prediction are discussed.

1. INTRODUCTION

The Permian Basin of west Texas and southeast New Mexico constitutes the largest oil reserve and the highest producing oil field in the United States. The component Delaware Basin to the west incorporates significant development in the Bone Spring and Wolfcamp Formations. The Bone Spring Formation represents a mixed siliciclastic-carbonate succession deposited as sediment gravity flows under cyclical sea level fluctuations (Montgomery, 1997; Blake, 2020). Due to the cyclic sedimentation associated with changing sea level, the Bone Spring Formation can be subdivided into 1st, 2nd, and 3rd Bone Spring carbonates followed by sand units. The underlying Wolfcamp Formation records deepwater deposition of organic-rich mudstones interbedded with calcareous mudstones, calcareous siltstones, carbonates, and argillaceous mudstones that were deposited within mixed carbonate-siliciclastic fan systems (Yeap, 2021). In general, the Wolfcamp Formation can further be separated into A, B, C, and D units (Gaswirth, 2017). Both formations consist of mixed sediment gravity flow and suspension sedimentation deposits which often exhibit thin beds and facies resulting in high heterogeneity (Bievenour and Sonnenberg, 2019). Thin bed analysis is critical for reservoir property characterization but can be challenging when heterogeneity regularly exists at length scales below wireline log resolution (2 – 3 feet). Therefore, acquiring high-resolution measurements can significantly assist in identifying and quantifying thin-bed heterogeneity and properties assignment.
Optimizing Overall Slope Angle and Net Present Value (NPV) Through the Utilization of Ground-Based Pit Wall Monitoring Data
Authors: Quansah E. A. , Anani A. , Adewuyi S.
Published: August 2024

In open pit mining operations, the decision to select the ultimate pit slope angle is critical due to its significant impact on safety and economic outcomes like net present value, mine life, operational costs, and safety risks. Recognizing the variability in rock properties and the discrepancies between planned and actual conditions, this paper introduces a robust framework that aligns the monitoring of pit wall conditions with optimizing pit slope angles. We proposed the use of data from the geotechnical model to conduct stability analysis with Rocscience software, combining real-time radar and prism system data. This adaptive approach aims to enhance the stability and safety of mines while optimizing economic returns. Additionally, it utilizes the Whittle software for determining the optimal pit slope angle, balancing safety requirements with operational cost efficiencies. This comprehensive framework promises substantial benefits, including reduced risk of slope failure, extended mine life, and decreased mining costs. Ultimately, by incorporating this methodology into the mining operation decision making process, significant improvement will be seen in safety and economic profitability, marking a significant advancement in open-pit mining management. This paper highlights the importance of adaptive, data-informed decisions in enhancing both the economic viability and safety of mining operations.

1. INTRODUCTION

Rock slope failure is one of the main hazards in open-pit mines. This causes about 14% of injuries and deaths of workers at various mines around the world (Aleotti & Chowdhury, 1999). This highlights the critical need for continuous innovative research and solutions aimed at mitigating such risks. It also suggests the need to keep safety a top priority for safe ore production and profitability. While working under safe conditions, it is also germane to consider improved ore recovery for profit maximization. In either way, optimizing pit angle may improve slope stability and increase profit by reducing stripping (Read & Stacey, 2010). However, this task necessitates a comprehensive understanding of the geotechnical parameters and the dynamics of slope movement.
Sub-Level Caving Blast Modelling to Determine the Impact of Blast Design Parameters and Rock Mass Characteristics on Fragmentation
Authors: Khodayari A. R. , Xu C. , Dowd P. , Dare-Bryan P. C. , Metcalfe A.
Published: August 2024

Sub-level caving (SLC) is a mass mining method that relies on the gravitational flow of blasted ore and the collapse of waste rock. The fine end and the coarse end of blasted particles impact material flow through sublevel interval. Improving blast induced fragmentation has the potential to improve ore recovery, reduce dilution and improve productivity by reducing the remediation of ground support and providing more efficient draw point extraction, while also improving the efficiency of downstream hauling, crushing, and grinding processes. Numerical simulations were conducted using a hybrid finite/discrete element compute engine coupled with a non-ideal detonation model. The model geometries take into consideration the uneven distribution of explosives within each blast due to the fan-shaped rings of blast holes, and the complex environment of blasting into broken ground. The modelling used existing field data from the Ernest Henry Mine to define the blast design, characterize the rock mass, and compare field and modelled fragmentation across a range of explosive densities and burden sizes. Further modelling investigated the influence of discontinuity density in the rock mass on fragmentation.

1. INTRODUCTION

The initial step in the comminution process in metalliferous mining involves the fragmentation of the rock mass containing ore. Typically, this is achieved through methods such as drilling and blasting. The fragmentation size distribution after blasting can have a significant impact on the efficiency of downstream processes such as the hauling of the ore, crushing and grinding (Grant et al., 1995), (Campbell & Thurley, 2017), (Jimeno et al., 1995), (Hamdi et al., 2001), (Aler et al., 1996). Within a sub-level caving operation (Figure 1) finer ore is more mobile and flows faster to the draw point, but it can produce sticky mud or slurry in damp circumstances. While larger fragments or boulders can block the flow of material and produce hang-ups, which are a safety hazard and lead to poor ore recovery (Campbell & Thurley, 2017). Determining the optimal fragment size presents a challenge due to the complex interplay of multiple factors associated with blasting parameters, rock characteristics, and operational conditions.
MultiFracSimPPM: A Data-Driven Probabilistic Predictive Model for Hydraulic Fracture Growth from Uniformly and Non-Uniformly-Spaced Perforation Clusters
Authors: Michael Andreas , Kalu Chukwuemeka , Bouabdallah Nassim
Published: August 2024

The thrust of this study is the assessment of using non-uniform-spaced perforation-clusters (as opposed to uniformly-spaced perforation clusters) in order to promote improved multi-frac growth geometries, by reducing stress-induced interference during simultaneous-HF growth. A probabilistic predictive model (PPM) that integrates empirical data obtained from laboratory-scale experiments is overviewed. MultifracSimPPM employs published results from multi-frac growth experiments on transparent gelatin blocks with single-phased perforations and various perforations-spacing arrays. A realistic and dependable expectation for multi-frac geometry was generated through the implementation of a Monte-Carlo simulation scheme, assessing such "limited-entry" technique. Statistical bias is introduced into random probabilistic distributions using this empirical dataset by MultifracSimPPM, resulting in geometric profiles that correspond to experimental findings that disprove the initial hypothesis (non-uniformly-spaced perforation clusters did not perform better than uniformly-spaced perforation clusters). Integrating economic principles could further enhance HF-treatment design, leading to higher post-stimulation hydrocarbon production and improved economics.

1. INTRODUCTION

Multistage hydraulic fracturing (HF) operations in horizontal wells enables hydrocarbon production from unconventional, low-permeability shale formations. The key element of HF modelling remains the prediction of the generated HF growth. When it comes to reservoir stimulation using multistage HF treatments, where many HFs are being "pumped" simultaneously within each frac stage, the problem's complexity increases exponentially. Standard treatment design software do not incorporate "real-world" phenomena, such as dominant HF creation and inactive perforation clusters (Michael, 2022). This work presents a probabilistic predictive model (PPM) that incorporates empirical inputs from laboratory-scale experiments. HF geometry is arguably the most critical element of HF-treatment design, with a number of considerations made for influencing multi-frac growth to optimize production and economics.

Employing random sampling, the algorithm, which is executed in MATLAB, populates output arrays that contain vectors of the expected HF heights and lengths. The statistical probability of occurrence of the corresponding HF-growth dimensions (length and height) in our laboratory experiments is utilized to populate these input arrays. The width of each HF is determined using the "Perkins-Kern-Nordgren" (PKN) geometry model.

Subsequently, the calculated HF length, height, and width are applied to the formation of semi-ellipsoid-shaped HF-growth profiles that illustrate the anticipated final multiple-HF-growth geometry. The homogeneity of multiple-HF growth is likewise quantified by using our novel fracture-geometric-homogeneity index (FGHI), as a metric.
Case Study: Investigation, Analysis and Mitigation of Rock Instability for a Potential Slope Failure in Highly Weathered Granite at Pinto Valley Mine in Arizona
Authors: Ureel S. D.
Published: August 2024

In the mining and civil engineering industries, slope stability issues have become essential problems to avoid ensuring site safety, maximum ore extraction and limited interruptions in production. Slope failures in mining operations are a cause for concern when dealing with potential safety hazards, accidents and injuries for mining personnel and damage to equipment. Predicting, monitoring and investigating slope failures are pertinent for safe working conditions and should be inspected continuously. A high wall composed of a small top layer of alluvium underlined by highly weathered granite at the Pinto Valley Mine in Arizona expressed warning signs such as rockfall, talus/debris retained on lower benches, tension cracks and displacements on the slope stability radar (SSR) during production adjacent to the slope. Detailed inspections, monitoring and mitigation were immediately initiated following these signs of instability.

If the area of interest is not critical to production, the easiest plan of action would be to leave the material in place and let the slope fail naturally as long it will not cause any safety hazards; however, this is not the case for failure researched in this paper. Mine blasting and production need to continue below the failure due to high grade ore in the vicinity. This can only happen if the failure mechanism is well understood and the rate of displacement is low. This study was performed to understand the mechanisms that triggered the failure, the rock conditions before and after the failure and to show how to proceed with controlled mining procedures in organized manner. This study will show observations before, during and after the slope instability as well as successful mitigation efforts and analyses. The results acquired illustrated that slope instability can be predicted from SSR, the SRR exhibited real time monitoring and provided initiation for mining safety protocols and procedures.

1. INTRODUCTION

Slope stability plays an important role in rock engineering. During the design, construction and post design phases of rock slope stability, engineers and geologists need to pay close attention to the rock conditions within the rock slope to prevent slope failures, protect employees and maintain economic profit. Slope geometry, material properties, and insitu stress conditions need to be investigated in order to understand the potential for rock slides, wedge failures, and other instabilities.
Investigation of the Frost-Induced Shallow Alpine Rockfall Process Using 3D FDEM
Authors: Sun Lei , Grasselli Giovanni
Published: August 2024

Increasing rockfall activities in alpine areas have been observed under the global climate change circumstance. One widely accepted explanation of the alpine rockfall is that the warming and thawing of ice-rich bedrock permafrost decreases effective shear strength and destabilizes rock substrates in unusual hot summers. However, small but frequent shallow collapses are also widely observed in mountainous areas when the temperature decreases in late autumn or cold winter. The research work presented herein proposes a numerical framework for simulating the frost heaving/cracking process and revealing the related shallow alpine rockfall mechanism, based on the three-dimensional (3D) combined finite discrete element method (FDEM), where complex coupled thermal-mechanical processes at low-temperature are considered, e.g., the heat transfer, water-ice transition, ice-rock interaction, and cracking. Results suggest that shallow collapses are observed when the temperature decreases in late autumn or cold winter. Cracks initiate and propagate in the rock mass, driven by the ice-rock interaction in cold seasons, deteriorate the structure stability and induce shallow rockfall. Knowledge of long-term thermal/water evolution of a rock slope therefore provides valuable insight into progressive rock deformation and related alpine rockfall hazards.

1. BACKGROUND

Increasing rockfall activities in alpine areas have been observed under the global climate change circumstance (Harris et al. 2009; Ravanel and Deline 2011), and are linked to the frost heaving/cracking behavior (Hallet 2006; Draebing and Krautblatter 2019). One wildly accepted explanation of the alpine rockfall is that the warming and thawing of ice-rich bedrock permafrost decreases effective shear strength and destabilize rock substrates in unusual hot summers (Gruber et al. 2004; Hasler et al. 2012). However, small but frequent shallow collapses are also widely observed in mountainous areas when the temperature decreases in late autumn or cold winter (Gruber and Haeberli 2007; Wu et al. 2021). Frost cracking is hypothesized to play an important role in the destabilization of steep permafrost (Matsuoka and Murton 2008), which can be inferred from the evidence that ice is common in fractures of bedrock and the fresh detachment scars of rockfall. Therefore, understanding the frost heaving/cracking mechanism is critical to shallow rockfall disasters in cold regions. To address this knowledge gap, a 3D numerical framework is developed to study the frost heaving and cracking process in fractured rock masses and further investigate the shallow rockfall mechanism based on the 3D FDEM (Munjiza 2004), which takes the advantage of simulating both continuum and discontinuum behavior.
An Investigation of Fault Geometric Effects on Fault Activation Mechanisms in CO2 Storage
Authors: Mortazavi A. , Maratov T.
Published: August 2024

In response to the escalating greenhouse gas emissions and climate change problem, promising solutions have emerged in the form of Carbon Capture and Storage (CCS) projects, offering potential avenues for mitigating environmental impact. This study explores the behavior of CO2 storage reservoirs and associated fault reactivation mechanisms using three-dimensional (3D) numerical modeling using Distinct Element Code (3DEC). The critical role of the reservoir-caprock interface is highlighted by the vertical displacement measurements from numerical simulation. Proximity to the reservoir-seal contact point correlates with maximum deformation magnitudes of 0.052 m, while the surface level (Z = 0 m) is subject to less significant deformation (0.01 m), indicating favorable reservoir stability. Aligning closely with previous 2D analyses, further parametric studies with real-world data and prolonged observations would be beneficial for validating modeling assumptions.

1. BACKGROUND

For the past couple of decades, CO2 Capture and Storage (CCS) has been consistently recommended and employed in response to the intensified greenhouse gases emission problem. In practice, in a CO2 reservoir, increasing pressure resulting from injection can lead to crack propagation and damage to borehole and seal rock through various mechanisms (Rutqvist, 2012; Zoback & Gorelick, 2012). As pressure builds within the reservoir due to CO2 injection, it can induce stresses in the surrounding rock mass, potentially exceeding the rock's strength. This can lead to the initiation and propagation of fractures, particularly in zones of pre-existing weaknesses such as faults or joints. Large amounts of pressure can cause deformation and compaction of the reservoir rock, leading to subsidence or heave around the borehole. This can result in borehole instability, including casing failure, collapse, or even blowouts. Furthermore, if the seal rock (caprock) above the reservoir is not sufficiently impermeable or strong, increased pressure from CO2 injection can cause it to fracture or deform, compromising its ability to contain the injected CO2. This can lead to CO2 leakage pathways, allowing the gas to migrate towards the surface or into underground rock layers, posing environmental and safety risks. Hence, such a promising solution in the form of CCS requires a safe and efficient storage site design to avoid above-described injection- or sequestration-induced damage that may ultimately lead to the gas leakage.
A Unified Computational Framework for Modelling Rock Failure Evolution: From Progressive Degradation to Catastrophic Rupture and Avalanche
Authors: Wang Liang , Lei Qinghua
Published: August 2024

In this study, we develop a novel unified computational framework for modelling the evolutionary behaviour of fractured rocks from progressive damage to catastrophic rupture and runout. In this framework, physical laws are coupled with failure criteria to describe the combined effects of time-dependent degradation and strain-driven processes; heterogeneities are considered by the representation of pre-existing fractures and statistical distribution of elasticity in rocks; an implicit time integration scheme is adopted to capture the deformational behaviour across multiple time scales; the particle finite element technique is applied to track the large deformation of rock masses. We demonstrate this computational framework for investigating rock failure evolution in both natural settings and engineering configurations, i.e. weathering-induced rock slope failures and tunnelling-induced rockbursts. We show that the model can realistically capture the complex responses of fractured rocks prior to failure, diverse rupture patterns during the failure, and various mass movement dynamics after the failure. Numerical simulations also indicate the strong control of geological heterogeneities on rock failure evolution. This unified computational framework can serve as a robust and powerful tool to unravel the origin of catastrophic rock failures, assess the risks related to potential extreme geohazards, and develop physics-based early warning systems in practice.

1. INTRODUCTION

The entire history of rock mass failure involves long-term destabilisation processes (Amitrano & Helmstetter, 2006), the formation of ‘system-sized’ fractures (Main, 2000), and the avalanche of failed materials, which are strongly coupled over the space and time domains. More specifically, destabilisation processes could lead to various failure patterns and dynamics, which may further affect the post-failure runout characteristics (L. Wang & Lei, 2023). Therefore, understanding the evolutionary behaviour of geomaterials across multiple time and length scales is of central importance for predicting the timing and magnitude of failure events (Ö. Aydan et al., 1996; Eberhardt, 2008). However, the involved material and geometric nonlinearities have posed a great challenge to developing numerical models for rock mass failures.
Analysis of Machine Learning Models for Prediction of Petrophysical Data
Authors: Vega-Ortiz C. , Palash P. , Edelman E. , McPherson B. J. , Maxwell G. , List D.
Published: August 2024

The growing need for better reservoir characterization methods in unconventional hydrocarbon extraction, geothermal energy production, and carbon sequestration has led to a demand for more accurate and reliable petrophysical data prediction techniques. However, data standardization across multiple wells in an area of interest is a challenging task, but essential for effective reservoir characterization. Petrophysical data is often statistically erratic due to the use of multiple service providers and logging tools, as well as the natural variability of the reservoir lithology. The article underscores the potential of the RTM, ANN and GPR ML models to generate accurate predictions of petrophysical properties, such as density and total organic carbon (TOC), even in the face of incomplete data sets. Such predictions are not merely academic but have practical implications, with ML-derived pseudo-curves aiding in the fine-tuning of reservoir models. By providing detailed case studies, the article offers insights into the successful application of ML models for pseudo-curves generation, which not only enhances the accuracy of reservoir simulations but also mitigates the risks associated with reservoir development and management. In conclusion, it encourages a shift from traditional empirical modeling to data-driven, algorithmic approaches, which promise to redefine the standards for accuracy and reliability in reservoir analysis and development.

1. INTRODUCTION

The historical approach in the oil and gas industry applies conventional models to establish correlations for generating pseudo-data. However, these models often fall short due to their reliance on region-specific petrophysical assumptions and the problematic generalization of constants or variables, leading to inaccurate estimations. To circumvent these limitations, ML regression models are increasingly employed. By leveraging existing petrophysical measurements—such as gamma ray, density, porosity, acoustic, and resistivity logs—as training datasets, ML models can infer the complex relationships between these measurements and reservoir characteristics. This training data encapsulates critical lithological information reflecting the interactions of minerals, fluids, and specific environmental conditions within the reservoir, providing a nuanced understanding that underpins the prediction process.
Numerical Simulation of Gas Leakage During Controlled Retracting Injection Point Process for Underground Coal Gasification
Authors: Wang Tianduoyi , Shi Juntai , Wu Keliu , Chen Zhangxin
Published: August 2024

In order to study the specific influence of various factors on gas leakage during the underground coal gasification (UCG), a numerical model of the Controlled Retracting Injection Point (CRIP) process for UCG was established by the computer modeling group software. Considering the geomechanical effect, the gas distribution characteristics during the CRIP process are explored, as well as the effects of gasification pressure difference, production pressure, gasified-gas pressure, reservoir permeability, and water energy on gas migration. Moreover, an assessment system of gas leakage during the UCG process was established based on dominant factors to provide the possibility for quick judgment of gas leakage. The results showed that the relative magnitude of gasifier pressure and initial coalbed pressure determines whether gas leakage occurs. The highest point of gasifier pressure occurs at a distance of 75 meters from the production well in the direction of the gas injection retreat. Gasifier pressure, gasification pressure difference, and permeability were the main factors, which form a complete gas leakage evaluation system. The gas leakage class was divided by 10 degrees, and Class 1 to Class 5 should enhance leak prevention measures.

1. INTRODUCTION

The energy sector is a primary field for achieving carbon neutrality and peak carbon emissions. Since the beginning of this century, the world has been gradually transitioning towards a low-carbon energy structure. A new wave of industrial and technological revolutions has sparked a surge in the low-carbon revolution, new energy revolution, and intelligent revolution (Zou et al., 2019). Coal resources play a crucial role in global energy supply, at least for the next quarter-century. However, the environmental issues associated with its combustion partially offset its value (Takyi et al., 2023). Approximately 80% of the coal mined in China is burned directly on the surface for purposes such as power generation and heating (Imran et al., 2014). This utilization of coal resources will bring serious environmental pollution.
Modeling of Immiscible Fluid Flow in Mixed-Wetted Porous Media Using the Lattice Boltzmann Method
Authors: Zhang Shengting , Li Jing , Wang Tianduoyi , Zhu Qingyuan , Wu Keliu , Chen Zhangxin , Chen Zhangxin
Published: August 2024

The phenomenon of immiscible fluid flow in mixed-wetted porous media has long fascinated researchers due to its prevalence in unconventional oil reservoirs and its profound implications for the spreading behavior of fracturing fluids during invasion and flowback processes. In this study, we employed the multi-component Shan-Chen lattice Boltzmann method (LBM) to investigate the complex dynamics of immiscible fluid flow within these media. To validate our numerical approach, we simulated the forced imbibition dynamics in parallel double wettability pores and compared the results with theoretical models. Our findings reveal that wetting fluids tend to preferentially invade regions of stronger wettability in porous media, especially at low capillary numbers. In contrast, subsequent fluid injection fails to invade weak-wettable areas once a breakthrough occurs in strongly wettable zones. Additionally, we identified a critical capillary number that determines the ability of injected fluids to overcome capillary resistance and flow into weakly wetted regions, thereby enhancing fluid displacement. These insights offer valuable understanding for optimizing fluid flow in unconventional reservoirs and designing more efficient porous media systems, ultimately contributing to more sustainable and effective oil recovery techniques.

1. INTRODUCTION

Understanding the immiscible fluid flow processes (including imbibition and drainage) of multi-component systems, such as oil-water, in porous media is of paramount importance across diverse industrial and technological domains. These processes are involved in enhanced oil recovery (EOR) (Singh et al., 2019), geologic storage of CO2 (Bachu, 2008), and proton exchange membrane fuel cells (PEMFC) (Anderson et al., 2010), among other applications. The key influencing factors in these processes encompass wettability, capillary number, fluid viscosity, and pore-throat structure (Holtzman & Segre, 2015). In particular, wettability is critical in governing slow imbibition/drainage dynamics within porous media (Bakhshian et al., 2020). During imbibition processes in predominantly hydrophilic rocks, the corner flow and wetting film phenomena are commonly observed (Zhao et al., 2016). Conversely, in the case of hydrophobic rocks, typical occurrences during drainage include the Haines jump and snap-off sensations (Alpak et al., 2019). However, it is imperative to acknowledge that reservoir rocks rarely exhibit uniform wettability; rather, they often manifest a mixed-wetting state, characterized by the coexistence of both hydrophilic and hydrophobic rock surfaces (AlRatrout et al., 2018). Therefore, to comprehend microscopic mechanisms like EOR through water flooding and the spreading behavior of fracturing fluids throughout the invasion and flowback processes requires studying the impact of mixed-wettability on two-phase flow patterns.
A Coal Pillar Burst Assessment Index Based on Numerical and Analytical Tools
Authors: Cardenas-Triana C. , Androulakis V. , Agioutantis Z.
Published: August 2024

Coal bursts are challenging to predict due to their highly complex and dynamic nature. In recent years, efforts to integrate established indices, such as Burst Potential Index (BPI), Energy Storage Rate (ESR), and Strain Energy Density (SED), with numerical computation modeling have shown potential. This study aims to develop a novel burst risk assessment tool for individual coal pillars in a longwall gate-road system (LGS). A modified pillar-specific BPI (mBPI) is proposed and couples analytical indices with numerical modeling. The modified index expands the classic BPI by removing the limitations stemming from considering only the elastic region of the material constitutive model and the stress-strain behavior under uniaxial loading. The effect of various geometrical and geomechanical parameters on the mBPI is evaluated through a parametric analysis. A total of 47 numerical models were generated to calculate the mBPI of an LGS pillar for different conditions. The results indicate that coal strength and coal stiffness, in-situ horizontal stresses, overburden depth, and pillar width have a substantial effect on the mBPI, while the width of the LGS yield pillar has a minimal impact on the mBPI.

1. INTRODUCTION

Coal bursts remain a longstanding, disrupting phenomenon in underground coal mines that can lead to high safety risks and have the potential to cause fatal injuries. Coal bursts are described by Zhang et al. (2017) as "dynamic rock failure involving a sudden release of strain energy stored within the rock mass". Since 1872, there have been more than 1,200 reported cases worldwide (i.e., in the United States, Germany, Czech Republic, Russia, China, and India), causing more than 1,000 fatalities (Sabapathy et al., 2019). It is evident that coal bursts present a substantial hazard in deep-mining coal operations, as they can cause serious damage to equipment and facilities, as well as loss of life.

Despite the extensive database of coal burst incidents available, a comprehensive scientific understanding of this phenomenon still eludes the international mining community. The causes and failure mechanisms of coal bursts constitute an extremely complex and dynamic engineering problem. Geotechnical engineering revolves around rock mass behavior, which cannot be fully described mathematically because of the multiple, and/or potentially impossible-to-determine factors involved. The discontinuous nature of the rock masses, the inherently heterogeneous and anisotropic engineering properties, the presence of bedding planes, faults, joints, folds, micro-fractures, the varying field stress conditions and pore pressure conditions, and other conditions allow only for approximate estimations of the rock mass behavior.
Dynamic and Static Biot's Coefficient of Transversely Isotropic Longmaxi Shale
Authors: Jia Lichun , Deng Hu , Xu Qicong , Xu Wen , Li Lei , Li Luchun
Published: August 2024

In this work, the dynamic and static Biot's coefficients and elastic parameters of Longmaxi black shale are investigated by using acoustic measurement and triaxial compression tests. The results firstly show that the dynamic and static elastic stiffness, Young's modulus both increase with confining pressure, and the dynamic results is higher than the corresponding static values. The Young's modulus parallel to bedding is higher than that of perpendicular to bedding. However, the Poisson's ratio has no significant rule with confining pressure and bedding direction. Secondly, the dynamic and static Biot's coefficients decrease with confining pressure. And the Biot's coefficients perpendicular to bedding are higher than those parallel to bedding. Moreover, the static Biot's coefficients are higher than the dynamic results. Finally, there is a linear relationship between dynamic and static Biot's coefficients and Young's modulus, respectively. The anisotropic Biot's coefficient and the dynamic to static conversion could improve the accuracy of geomechanical analysis in Longmaxi shale.

1. INTRODUCTION

The Biot's coefficient, or effective stress coefficient, is a key parameter in poro-elasticity, which could reflect the contribution of pore pressure to effective stress (Alam et al., 2009; Asadollahpour et al., 2021). This coefficient is widely used in petroleum geomechanics, wellbore stability analysis, fracturing design, reservoir sensitivity analysis and productivity prediction, rock physics and other research fields (Valdes et al., 2016; Aderibigbe et al., 2019). Hence, it is of great practical significance for accurately and efficiently obtaining the Biot's coefficient.

The Biot's coefficient can be determined from the subtraction of rock bulk modulus to rock matrix's bulk modulus ratio from one (Alam et al., 2009; Asadollahpour et al., 2021; Vorobiev et al., 2022). In the direct laboratory approach, the bulk modulus is obtained while pore pressure is zero in the jacketed test while the rock matrix's modulus is measured by doing the unjacketed test in which the values of the pore pressure and confining pressure are the same (Ling, et al., 2016; Zhou and Ghassemi, 2019). Moreover, the Biot's coefficient also could be calculated by compressibility, permeability and wave velocity or sonic well logs (Luo et al., 2015; He et al., 2016; Amiri et al., 2019; Nolte et al., 2021; Vorobiev et al., 2022). Commonly, the result calculated from the wave velocity is named as dynamic Biot's coefficient (Asadollahpour et al., 2021; Azadpour et al., 2022). Compared to dynamic Biot's coefficient, the unjacketed and drained hydrostatic compression tests are expensive and laborious while the core samples are mostly unavailable. But the dynamic Biot's coefficient needs to be converted into a static value before using for engineering analysis (Crawford et al., 2020).