bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Damage Mechanics Challenge Results: Participant Predictions Compared with Experiment
Authors: Morris J. P. , Pyrak-Nolte L. J. , Yoon H. , Bobet A. , Jiang L. 
Published: September 2023

ABSTRACT
We present results from a recent exercise where participating organizations were asked to provide model-based blind predictions of damage evolution in 3D-printed geomaterial analogue test articles. Participants were provided with a range of data characterizing both the undamaged state (e.g.: ultrasonic measurements) and damage evolution (e.g.: 3-point bending, unconfined compression, and Brazilian testing) of the material. In this paper, we focus on comparisons between the participants’ predictions and the previously secret challenge problem experimental observations. We present valuable lessons learned for the application of numerical methods to deformation and failure in brittle-ductile materials. The exercise also allows us to identify which specific types of calibration data were of most utility to the participants in developing their predictions. Further, we identify additional data that would have been useful for participants to improve the confidence of their predictions. Consequently, this work improves our understanding of how to better characterize a material to enable accurate prediction of damage and failure propagation in natural and engineered brittle-ductile materials.

INTRODUCTION
Understanding the failure of materials is particularly relevant today with the current interest in aging infrastructure and in enhanced geothermal systems which require a network of fractures to optimize production. As more and more sensors are used to monitor infrastructure and the subsurface, methods are required to detect anomalous signals in data and link these signals to the underlying physics and mechanics of failure to determine if failure is imminent. This requires robust computational methods that capture the physics of failure and identify the measurable signatures of failures. While there are many computational approaches for simulating damage evolution in materials, few have been ground-truth tested with either known experimental data or with blind data sets.
The Fracture Challenge concept (e.g.: Boyce et al., 2014) has demonstrated that valuable lessons can be learned by comparing computational methods and workflow approaches taken by different teams in the blind prediction of controlled fracturing experiments. Previous challenges have focused upon failure in metals. Here, we present results from a recent challenge that considered damage evolution in additively manufactured samples where the mechanical response is similar to the brittle-ductile response of rock, yet highly reproducible from one test article to another by virtue of the 3D printing process.
Experimental Investigation of Fracture Orientation in Rocks Using Shear Wave Splitting
Authors: Kholy S. M. , Lee Hunjoo P. 
Published: September 2023

ABSTRACT
The understanding of the orientation of pre-existing discontinuities is crucial for subsurface engineering applications, such as drilling, well completion, and hydraulic fracturing. A variety of methods have been developed to identify fracture orientation, including wellbore imaging and monitoring of microseismic events in reservoirs. Recent research has utilized shear waves to evaluate fracture orientation and density in porous media by analyzing the shear wave splitting (SWS). The aim of this study is to assess the fracture orientation in two rock types, synthetic Hydrostone and Eagle Ford shale, under triaxial loading conditions using the SWS phenomenon. Shear wave velocities were measured using two orthogonal transducers at each end of the fractured sample for transmitting and receiving shear wave travel times. The results showed that SWS, the velocity difference between the two shear waves, was the highest at fracture orientations of 0° and 90°, when one of the transducers was parallel with the fracture. Whereas SWS was the lowest for the sample with fracture at 45°, when the split shear waves attenuated during re-orientation with their preferred propagation directions. The findings of this study could help identify fracture orientation near the wellbore and contribute to minimizing various drilling and completion issues.

INTRODUCTION
Natural fractures are abundant mechanical structures that exist in most rock types, especially in carbonates and shale (Moore and Wade, 2013). These pre-existing discontinuities could cause several drilling issues including mud losses (Razavi et al., 2017) and drilling breaks (Narr et al., 2006). In production engineering, the presence of natural fractures may enhance the local permeability, and hence the production rate (Luffel et al., 1993; Sakhaee-Pour and Bryant, 2011; Ben et al., 2012; Al-Rubaye et al., 2020). However, in the meantime, it can also increase the gas-oil ratio and water cut impairing the hydrocarbon productivity (Aguilera, 1980; Wennberg et al., 2016). Furthermore, in hydraulic fracturing applications, these natural fractures are known to have significant impact on the hydraulic fracture trajectory and the Stimulated Reservoir Volume (SRV) depending on their relative orientation to the hydraulic fracture propagation direction (Gale, et al., 2007; Zhou et al., 2008; Bahorich et al., 2012; Lee et al., 2015).
The orientation of natural fractures is determined by the paleo-stress field of the most active tectonic period (Maerten and Maerten, 2006; Zhang et al., 2022). Nevertheless, this orientation may not always align with the current stress field (Abul Khair et al., 2013; Abul Khair et al., 2015; Likrama et al., 2019). Thus, characterizing the orientation of natural fractures is crucial for effective design of various subsurface engineering applications.
Numerical Study of Hydrogen Storage in Lined Rock Cavern and Implications of Hydrogen Embrittlement
Authors: Sun Zhuang , Wu Jingtian , Salazar-Tio Rafael , Fager Andrew , Crouse Bernd 
Published: September 2023

ABSTRACT
Underground hydrogen storage could provide buffer capacity to store the excess energy from renewable resources. A lined rock cavern (LRC) is one of the hydrogen geologic storage site options. It offers great flexibility because it does not rely on the existence of salt caverns, aquifer formations or depleted hydrocarbon reservoir fields. However, many important aspects have to be studied before its full-scale implementation, among them (1) the effect of spatial variation of rock mass properties and (2) hydrogen embrittlement on the steel lining. We present a numerical study on these two aspects by simulating field tests at a pilot LRC project. For the effect of rock heterogeneity, we assign a spatial variation of elastic properties based on the Gaussian covariance model. The results show a good agreement with the field measurements. The spatial correlation length of rock mass elastic properties only has a minor impact on the cavern surface deformation. Regarding hydrogen embrittlement, our simulations predict a significant hydrogen diffusion in the welded low alloy steel (S355) lining after ∼2 months of operation, which may cause hydrogen leakage and facilitate the hydrogen embrittlement. We show that advanced numerical models are powerful tools to ensure the safety of hydrogen storage in a LRC.

INTRODUCTION
Energy production from renewable sources such as wind turbines and solar cells has gained lots of attraction to reduce emissions of greenhouse gases and mitigate global warming (Pörtner et al., 2022). However, electricity from such energy sources has a strongly fluctuating nature, therefore requires storage options at sufficient scale to fulfil demand requirements (Osman et al., 2022). With the help of electrolyzer technology, the surplus electricity can be used to produce hydrogen that can be stored and used as a fuel when needed. Underground geologic storage of hydrogen enables significant storage cost reductions as well as buffer capacity to store this surplus energy generated from renewable resources (Hassanpouryouzband et al., 2021; Liebscher et al., 2016; Ozarslan, 2012; Tarkowski, 2019). The underground hydrogen storage also provides opportunities for its commercial usage in industry and transport (Lord et al., 2014).
Developing Methods to Assess Changes in Mechanical Properties of Shale Modified by Engineered Mineral Precipitation
Authors: Bedey K. , Cunningham A. B. , Phillips A. J. , Kirkland C. M. , Willett M. R. , Dobeck L. , Eldring J. , Crandall D. , Rutqvist J. 
Published: September 2023

ABSTRACT
Fractures in subsurface shale formations serve multiple purposes, for example, in the recovery of resources in hydraulic fracturing or as potential harmful leakage passages through caprocks that may contribute undesired fluids to the atmosphere or functional groundwater aquifers. A proposed method to seal or influence fracture properties is Ureolysis-Induced Calcium Carbonate Precipitation (UICP), a bio-mineralization technology driven by the enzymatic hydrolysis of urea, resulting in the formation of calcium carbonate. The resulting calcium carbonate can bridge the gaps in fractured shale and reduce fluid flow through fractures. This study represents the first step toward determining the influence of UICP treatment on shale material and its subsequent mechanical strength properties. The goal of this preliminary work is twofold: first, we aim to identify a method to test tensile strength along a core axis and second, we seek to assess the effect of temperature on the tensile strength of intact, unfractured shale cores (2.54 cm (1 in) diameter, 5.08 cm (2 in) long for comparison with future fractured and UICP-treated cores. A modified Brazilian indirect tensile strength test successfully measured splitting tensile strength of shale cores from Eagle Ford and Wolfcamp formations at room temperature and 60°C.

INTRODUCTION
Hydraulic fracturing coupled with horizontal drilling has been an instrumental technology for extraction of natural gas reserves in subsurface rock formations such as sandstone and shale. Shale gas is the natural gas trapped within subsurface shale formations and has become a crucial unconventional energy source amid an evolving energy landscape. Hydraulic fracturing and horizontal drilling stimulated energy independence, lowered fuel prices, and promoted job creation in the United States (Q. Wang et al., 2014). While hydraulic fracturing created many positive economic impacts, it has also generated undesirable environmental effects. This research is aims at offsetting environmental costs by sealing fractured subsurface shale using a sustainable bio-mineralization technology known as Ureolysis-induced calcium carbonate precipitation (UICP) (Kirkland et al., 2021). If UICP can bridge the gap in fractured shale, and prove strong enough to seal fractures, UICP treatments may be used at the field scale to limit fracture propagation, better store carbon dioxide, and extend the life and efficiency of existing and future wells.
Impact of Proppant Distribution in Hydraulic Fracture on the Productivity of the Multi-Stage Fractured Marcellus Shale Horizontal Wells
Authors: El Sgher Mohamed , Aminian Kashy , Sattari Arya , Samuel Ameri 
Published: September 2023

ABSTRACT
The impact of the proppant distribution within the hydraulic fracture on the productivity of the multi-stage fractured Marcellus shale horizontal well has been investigated. The available data from a Marcellus Shale horizontal well were compiled, analyzed using a fracture model to determine the fracture properties, and used to develop a reservoir model. Multipliers for permeability and conductivity were incorporated in the model to account for the dynamic net stress changes during the production. The model predictions were found to be in close agreement with the well production. The impact of the non-uniform fracture conductivity and stage spacing on gas production were then investigated. The non-uniform fracture conductivity has a significant impact on the initial gas production. Therefore, it is important to consider the impact of the non-uniform fracture conductivity in optimizing hydraulic fracturing treatments in Marcellus shale.

INTRODUCTION
The application of the horizontal drilling and hydraulic fracturing techniques have unlocked, significant natural gas reserves from shale gas reservoirs. Marcellus Shale is one of the most prolific and largest unconventional gas resources in US. There are approximately 95,000 square miles of Marcellus shale in Ohio, West Virginia, and Pennsylvania as well as areas in New York, Kentucky, Tennessee, and Maryland. Marcellus shale varies in thickness from 50 to 200 ft. The depth of the shale ranges from 4,000 to 8,500 ft. The average temperature of the Marcellus shale is 150°F. The total organic carbon (TOC) ranges from 2 to 20 percent in Marcellus Shale (Boyce et al., 2010).
Hydraulic fracture treatment involves injecting fluid into the wellbore in order to increase the downhole pressure to a level in excess of the fracturing pressure of the formation. In response to this increase in pressure, the formation cracks, allowing the injected fluid to enter and extend the crack further into the formation. To keep the crack open after injection, a solid proppant, such as sand, is mixed with the injected fluid. Proppant plays an important role in stopping fractures from closing under in-situ formation stress and maintaining the fracture conductivity. There is a greater degree of closure in the unpropped areas, and their conductivity is poorer than in the propped areas. The distribution of proppant within the fracture can significantly affect the productivity of the well. The Marcellus Shale is typically treated with 2,500 to 20,000 barrels of water and 25,000 to 75,000 pounds of sand proppant at a rate of 25 to 100 barrels per minute (Bruner and Smosna, 2011).
Enabling CO2 Plume Geothermal: Key Geological, Reservoir, and Operational Considerations
Authors: Okoroafor E. R. , Kang Y. , Elsayed T. , Indro A. 
Published: September 2023

ABSTRACT
To investigate ways of advancing CO2 plume geothermal (CPG), we have examined key geological, reservoir, geomechanical, and operational considerations. We use a three-dimensional numerical reservoir simulator to model the impact of each parameter studied on the injectivity and productivity indices for CO2 plume geothermal systems. In addition, we use a coupled thermohydromechanical model to understand if the process might induce fracturing or seismicity. The result showed that the top of the reservoir, the formation porosity, and the formation thickness are the top three factors impacting the productivity index and injectivity index of CPG systems. We also note that produced CO2 is less than the injected CO2 due to trapping mechanisms and bypassed CO2. Lower permeability and anisotropy were more favorable for the given reservoir and well configuration. From a geological perspective, sensitivity analyses reveal the influence of dip on CO2 extraction and the need for optimal well placement. Elastic-brittle analysis suggests that reservoir fracturing and microseismicity may not occur during injection. However, microseismicity may occur during production, thus providing some guidance on how operators may want to optimize monitoring strategies.

INTRODUCTION
The apparent high cost and lack of economic attractiveness of carbon capture utilization and storage (CCUS) projects have been perceived as a challenge for the large-scale deployment of numerous CO2 capture projects (Shen et al. 2022 and Gibbins et al. 2008). Budinis et al. (2018) suggest that the ability to utilize and sequester captured CO2 could enhance the economic viability of CCUS. Researchers such as Brown (2000), Pruess (2006), Luo and Jiang (2014), and Okoroafor et al. (2022) have investigated the thermal performance of an enhanced geothermal system (EGS) using supercritical CO2, which has shown promise for heat mining due to the favorable thermophysical properties of CO2 in its supercritical state. However, unlike the complex fracture system of the EGS model, the CO2 plume geothermal system takes advantage of CO2's greater compressibility, expansibility, and lower viscosity when injected into sedimentary rocks. Fluid loss in the system indirectly serves the purpose of CO2 geological storage, as Randolph et al. (2010, 2011) observed.
Machine Learning Based Predictive Models for UCS and Young's Modulus of the Dakota Sand Using Schmidt Hammer Rebound
Authors: Chellal H. A. K. , Egenhoff S. , Latrach A. , Bakelli O. 
Published: September 2023

ABSTRACT
The Inyan Kara formation is a fluvial sandstone saline aquifer in the Williston basin that gained a lot of interest in the recent years due to it being the main saltwater disposal formation and one of the most promising CO2 storage formations in the basin. However very little is known about the geomechanical properties of this formation given the limited number of cored wells and other necessary data through this interval. Therefore, this study used a combination of well log data, routine geomechanical core data experiments and Schmidt hammer measurements to create a robust machine learning model that accurately predicts the deformability and strength of the Inyan Kara formation (i.e., the uniaxial confined stress (UCS) and Young's modulus) from Schmidt hammer rebound. The model performance was then compared to published empirical correlations and proved to be very accurate with near perfect predictions. Our model uses data from the Williston basin and therefore would be more suitable and perform much better on data from the same basin than the existing empirical relationships.

INTRODUCTION
The Inyan Kara formation in the Williston basin has gained a lot of interest in the recent years given the rising Drilling problems caused by the saltwater disposal activity in this formation (Basu et al., 2019) and the interest in this formation as a potential CO2 storage formation. However, this formation is a saline aquifer located at an average depth ranging between 4000 to 6000 feet with no potential hydrocarbon resources. Therefore, wireline logs and core data in this formation are very scarce (Basu et al., 2020) and this is the primary motivation for this study which aims to generate a machine learning model that correlates the Schmidt hammer rebound to the young's modulus and unconfined compressive strength of the different lithologies in this formation which are parameters usually measured through destructive laboratory tests. Given the importance of the mechanical properties of the rocks for geomechanical modeling (Chellal et al., 2022) as it relates to CO2 geological storage, wellbore stability and other problems related to saltwater disposal. This highlights the importance of finding a machine learning model that rely on non-destructive testing methods like the Schmidt hammer rebound to estimate the deformability and strength of the rock defined by young's modulus (YM) and unconfined compressive strength (UCS) (Malki et al., 2023).
Blast Movement Simulation Through a Hybrid Approach of Continuum, Discontinuum, and Machine Learning Modeling
Authors: Fu Wei , Furtney Jason , Valencia Jorge 
Published: September 2023

ABSTRACT
Estimating and optimizing rock movement during blasting is important to prevent unnecessary material handling, reduce ore loss and dilution, and minimize environmental footprint. It has been challenging and computationally burdensome to model the whole dynamic process because rock blasting consists of a complex process that generally involves explosive detonation, gas expansion, stress wave propagation, rock fragmentation and throw, and muckpile formation. In this regard, we propose a hybrid approach that captures the first-order impacts on the rock movement due to blasting while achieving accelerated simulation. Specifically, a small-scale continuum model is established to represent an annulus of rock, with explosive in the center and gas pressure resulting from the detonation applied to the borehole surface, which reduces as the borehole deforms. The continuum model simulates the early-stage, near-field rock blasting process and forms a synthetic dataset based on realistic explosive data to train a machine learning model. Key parameters, such as expanded hole diameter, burden velocity, and time-dependent gas pressure, are readily obtained from the constructed machine learning model. Informed by the machine learning model, the subsequent discontinuum model simulates the dynamic rock movement and predicts the muckpile formation in the far field using the rolling resistance contact model. Our results demonstrate the efficacy of the proposed approach to capture the key physics of blast-induced rock movement and realize accelerated blast design optimization aided by machine learning.

INTRODUCTION
Rock blasting is a highly effective technique employed for fracturing and moving rock mass with extensive applications in various fields such as mining, quarrying, tunneling, and civil engineering industries. The understanding of rock behaviors during blasting is critical for optimizing blasting design, reducing material loss and/or dilution, as well as minimizing environmental impact and safety hazards. While it is difficult to quantify rock blasting experimentally, numerical simulation approaches have been developed over the years to model the process. However, simulating rock blasting is still a challenging and computationally demanding task. One of the main challenges lies in the complex physical processes that occur during blasting, including non-ideal detonation, near-field rock crushing, fracturing, vibration, ore/waste movement, and muckpile formation. Simulating rock blasting movement is further complicated by the intrinsic heterogeneity of rock materials and variability in blasting conditions, which result in highly nonlinear and discontinuous behaviors. Moreover, the wide range of length and time scales involved in these sub-processes presents a significant computational burden.