bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

ABSTRACT:
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

ABSTRACT:
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

ABSTRACT:
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

ABSTRACT:
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

ABSTRACT:
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).
Assessment of Ground-Support Interaction Using Continuum Grain-Based Models
Authors: Sinha S. , Walton G. , Shirole D. 
Published: August 2024

ABSTRACT:
Spalling of pillar ribs is a major hazard in the mining industry. Developing effective support guidelines requires an understanding of pillar damage mechanisms as well as the rock-support interaction. Bonded Block Models (BBMs) represent a convenient tool for this purpose, as they can reproduce the rock fracturing process reasonably well, but it is not known whether all variants of this modeling technique can replicate the impact of reinforcement (bolts) on otherwise unsupported ground. Broadly speaking, BBMs can be sub-divided into two groups: true discontinuum (implemented in DEM software) and pseudo-discontinuum (implemented in FEM software). Previous research by the authors has demonstrated the ability of DEM-based BBMs to reproduce rock-support interaction very well using real mining case studies. The current study is focused on evaluating the capability of FEM-based BBMs to replicate pillar damage mechanisms and rock-support interaction. Specifically, the stress-strain curves from BBMs developed in RS2 for three different width to height (W/H) ratio unsupported pillars (W/H = 1, 2, 3) were calibrated to match the macroscopic behavior of BBMs developed in UDEC, followed by analyzing the influence of rockbolt patterns in these models. Model outputs like stress-strain behavior, block and joint yield, and failure patterns were analyzed. With this, differences and similarities in the behavior of the two model variants have been discussed, considering their applicability in practical support design.

1. INTRODUCTION
Pillars are an integral load bearing member in underground mines and play an essential role in upholding the functional integrity of the mine openings. As mining continues to progress deeper, these pillars are subjected to ever higher stresses, which increases the incidence and severity of ground control issues, including, but not limited to spalling, buckling, pillar bursting, etc. (Kaiser et al., 1996; Diederichs, 2007). From a macroscopic failure standpoint, the design of pillars is well-studied (Hedley and Grant, 1972; Krauland and Soder, 1987; Potvin et al., 1989; Lunder and Pakalnis, 1997; Martin and Maybee, 2000). On the contrary, design of surficial supports (e.g. rockbolts, wire meshes etc.) for controlling stress-induced failures at the pillar periphery remains a topic of research, primarily because of the complex interaction between support elements and unsupported ground undergoing stress-induced damage.
LSTM Recurrent Neural Network Based Method for Identification of Drilling Operating Conditions and its Application
Authors: Chen Changchang , Ji Guodong , Zhang Hongyuan , Sun Yuqi , Wu Qiang , Lv Zehao 
Published: August 2024

ABSTRACT:
Polycrystalline Diamond Compact (PDC) bit underground operating conditions identification is one of the difficulties during the drilling operation. It is of great significant for the drilling improvement and accurate construction formation to accurately identify the complex operating conditions during drilling the operation such as PDC bit wearing and stick-slip vibration, etc. In this paper, data of relationship between torque, rate of penetration (ROP) signal and weight on bit (WOB), rev were obtained through lab simulation experiment, after which, a relationship database of torque, ROP signal and WOB, rev was established, a single-layer Long Short Term Memory (LSTM) recurrent neural network (LSTM) was constructed, the number of neurons, batch size and optimizer type of LSTM layer were optimized. With BPTT algorithm, LSTM model was trained and tested on the training set containing 6000 groups of data, and achieved the goal of identifying the bit operation conditions against the input of WOB, torque, rev and ROP signal parameters. Based on this model, the PDC bit underground operating conditions identification software was compiled, and was connected to the logging unit to realize real-time identification of bit underground operating conditions, and field test application was successfully carried out in Mahu 1 Well Region. The research showed that the convergence speed was fast and the time cost was at the lowest when the number of neurons of LSTM model was 50, and that the optimized Adam optimizer model could meet the requirements of convergence speed and prediction accuracy with the lowest loss value. The classification accuracy of this model on the test set reached 94% and the accuracy of the prediction method was also verified by field test application.

1. INTRODUCTION
During the drilling, complex underground conditions such as PDC bit wearing and stick slip may a impact the drilling cycle and drilling cost directly, in that bit wearing reduces the rock breaking efficiency. Either too early or too late pulling out of the hole(POOH) can affect the drilling effectiveness. After the bit stick-slip vibration, the cutting teeth can not effectively eat the rock, hence reducing the rock breaking efficiency. Serious bit stick-slip vibration may cause accidents such as increase of drill string torque and even breaking of drilling tool[1-3]. Therefore, real-time and accurate prediction of underground operating conditions of PDC bit and accurate guidance of tripping operation can effectively improve the mechanical ROP, reduce NPT and shorten the well construction cycle[4].
Effect of Cyclic Freezing and Thawing on Permeability and Mechanical Properties of Red Sandstone Under Triaxial Compression Condition
Authors: Liu B. , He Y. Q. , Han Y. H. , Li W. H. , Zeng J. Y. 
Published: August 2024

ABSTRACT:
During the construction of coal mines in western China, many boreholes are drilled through artificially frozen Cretaceous and Jurassic formations. After experiencing one freeze-thaw cycle, these water-rich and weakly cemented rocks generally demonstrate significant changes in permeability and mechanical properties, leading to frequent occurrences of water intrusion and flooding accidents. In this study, triaxial compression test and permeability test were conducted on red sandstone under conditions of both no freeze-thaw cycle and one freeze-thaw cycle. The variation of permeability and mechanical characteristics of red sandstone induced by one freeze-thaw cycle was investigated for different confining pressures. The results indicated that, after one freeze-thaw cycle, the peak strength and elastic modulus of the red sandstone decreased but the Poisson's ratio increased. Under low confining pressures (4 and 6 MPa), the permeability of red sandstone exhibited staging characteristics. Enhanced by the freezing-thawing cycle, the permeability of red sandstone significantly increased before the onset of crack initiation. Under high confining pressures (8 and 10 MPa), the permeability showed a continuous decreasing trend, as the expansion of vertical fractures was suppressed by the high confining pressure. The test results from this work are helpful to stability analysis of the mine shaft and pre-control of seepage damage after the thawing treatment of the frozen coal mines.

1. INTRODUCTION
During the construction of coal mines using artificial freezing method in western China, the frozen boreholes often pass through the Cretaceous and Jurassic formations. These water-rich and weakly cemented rocks are characterized as late diagenesis, poor cementation, low strength, and easy to become mud when encountering water (Zheng et al., 2011; Ma et al. 2018; Weng et al.2021). After experiencing artificial freezing and natural melting process, the permeability and mechanical properties of the rock further weaken, leading to frequent occurrences of water intrusion and flooding accidents (Deng et al. 2010; Huang et al. 2022; Xiong et al. 2023). Ultimately, it can cause significant losses of economy and threaten the safety of lives and property of humans.