bluuebunny/crossref_metadata_2025_split huggingface dataset:
Flow-Based Upscaling of Fractured Porous Media Using a Discrete Fracture and Matrix Model and a Fracture Merging Algorithm
Authors: Maier Christine , Oliveira Gonçalo , Schiozer Denis José 
Published: June 2023

Abstract
Many geo-energy related applications involve predicting the behavior of fluid flow in fractured subsurface reservoirs. Naturally fractured carbonate reservoirs are particularly important for being a major source of the world's hydrocarbon production. These reservoirs are also currently being considered as potential CO2 storage sites that will support net zero emissions goal. Simulation of flow in fractured reservoirs is a challenging task that typically involves upscaling the effective permeability of the fracture network and matrix into continuum models that consider the reservoir scale. The most accurate way to obtain such upscaled permeability for fracture networks is to perform single-phase flow simulations in statistical realizations of the fracture network using three-dimensional unstructured grids and explicit modelling of fractures. This step can be computationally challenging for highly dense fracture networks due to the difficulty in meshing the fractures and the rock matrix. Here, we present a method to reduce the complexity of the fracture network while still preserving the behavior of its effective permeability. Our approach involves a fracture merging algorithm that reduces the number of fractures allowing for faster meshing and upscaling. The fracture merging algorithm uses three different similarity metrics: fracture orientation, fracture area and distance between fractures. These metrics are used to identify similar fractures that can be merged into one single fracture with increased permeability. The upscaling algorithm to obtain the effective permeability of a grid cell containing a fracture network relies on flow simulations in three-dimensional unstructured meshes. We applied our method to different sub-networks extracted from a stochastically generated fracture network of a Brazilian Pre-Salt carbonate reservoir. We found that the average permeability of all fractures of the resulting fracture network increases with merging intensity, i.e., with decreasing the number of fractures, while the resulting upscaled effective permeability for the network remains in the same order of magnitude. This shows that the flow-based upscaling workflow including the merging algorithm leads to a significant reduction of complexity of fracture networks and consequently their 3D unstructured meshes while maintaining the structural and topological features that account for the fracture network effective permeability. Our proposed method is simple to implement and relies only on geometrical properties of the fractures. Other machine-learning based models have been proposed to achieve similar simplification of fracture networks, however, they are not easily incorporated into existing reservoir simulation tools and codes like the method presented in this work. Moreover, such previously published approaches do not consider flow in matrix and thus haven't been tested in scenarios where the matrix also contributes to flow.
Well Performance Metrics Suitable for Automated Monitoring
Authors: Shchipanov Anton , Namazova Gyunay , Muradov Khafiz 
Published: June 2023

Abstract
Automated well operations is a rapidly growing area with recent progress in automated drilling extending now into automated well monitoring and control during production operations. In reservoir engineering, although the industry continues to guide decision making processes mainly based on physics-based models and simulations, the focus of further developments of the industrial workflows has shifted towards hybrid solutions incorporating machine learning and big data analytics. Development of such solutions requires new approaches to integrate the reservoir physics into the workflows suitable for machine learning and big data analytics.
In this paper, we apply and test new metrics for permanent well monitoring developed based on time-lapse pressure transient analysis, called PTA-metrics. These metrics, inheriting reservoir mechanics gained from PTA, remain comparatively simple and suitable for automated workflows. The metrics have been tested on real well data from sandstone and carbonate fields, including slanted injection and horizontal production and injection wells. The testing has confirmed its capabilities in well monitoring separating reservoir from well-reservoir connection contributions to well performance. Application of the metrics enables on-the-fly well monitoring and alarming on well performance issues highlighting the issue origin: either a reservoir or a well-reservoir connection. At the same time, the testing also revealed that reliable application of the metrics depends on the patterns developed by time-lapse pressure transient responses and their Bourdet derivatives. It was shown that the PTA-metrics give reliable results for stable patterns, while change in the pattern may reduce their reliability. The paper concludes with a discussion of ways for application of the metrics in every-day well and reservoir monitoring practice as well as their integration in automated data interpretation workflows developed in the industry.
Potential of Deep Eutectic Solvents in the Upstream Oil and Gas Industry
Authors: Hamdi Zakaria , Koshekov Shaberdi , Bataee Mahmood 
Published: June 2023

Abstract
Oil and gas will be the main part of our future energy sources, despite of emerging and expanding of renewable energies. Enhanced Oil Recovery (EOR) plays an important role in the future oil and gas industry as the conventional oil reserves will shrink. Heavy oil reservoirs will be the main target of EOR methods because of the high number of existing heavy oil reservoirs. Surfactants are the most efficient chemical EOR method for many unconventional reservoirs as previous studies suggest. The problem with this EOR method is that these projects have high costs and raised environmental concerns. Ionic liquids (ILs) are introduced as an alternative material to surfactants, however, the cost of their synthesis and purification processes are high. Besides, some of them are toxic and have non-biodegradable properties which limit their commercial usage. Recently, a new form of ILs produced and called Deep Eutectic Solvents (DESs). The discovered material is more affordable and environmentally friendly and hence, it is considered to be an alternative material for existing conventional ILs. DESs are cheap, easy to produce, non-toxic, reusable, bio-degradable, and environmentally friendly. These materials consist of two or more cheap and safe components which will form a eutectic mixture. The melting point of the final mixture is lower than its components. In this study, the effectiveness of DESs in the EOR is analysed and evaluated to consider it as a new injection material for chemical EOR. This material has specific properties which improve the efficiency of EOR processes. Some of the favourable properties are stable emulsion between phases, interfacial tension (IFT) reduction, wettability change, recovery enhancement, and avoiding formation damage which is discussed and analysed in this paper. Moreover, the cost of the process is hugely reduced compared with other chemical injection methods. As the result, the main factor for the recovery enhancement is wettability alteration and the chance of viscosity. Besides, only malonic and acid-based DESs formed emulsions with oil, and the other types of DESs did not show emulsification properties. The IFT value increased for heavy oil reservoirs, while for reservoirs with light/medium oil IFT was reduced. Furthermore, DESs did not show formation damage which is a bonus point for this method. As the final result, Choline Chloride Glycerol showed the best recovery with an extra 30% to the original production.
The Role of Diffusion on the Reservoir Performance in Underground Hydrogen Storage
Authors: Arekhov Vladislav , Clemens Torsten , Wegner Jonas , Abdelmoula Mohamed , Manai Taoufik 
Published: June 2023

Abstract
For large scale seasonal storage, Underground Hydrogen Storage (UHS) can be used to balance fluctuating sustainable energy generation and energy demand. Similar to underground natural gas storage, depleted gas fields potentially allow for cost-efficient hydrogen storage. One of the major cost factors in UHS is the amount of cushion gas required and the purity of the hydrogen produced during the production cycle.
The hydrocarbon gas remaining in the reservoir can be used as cushion gas to significantly reduce UHS costs. To evaluate the composition of the gas produced during the production cycle of UHS, numerical simulation was applied. One of the important processes in UHS is molecular diffusion within the reservoir. The hydrogen recovery factor and methane to hydrogen production ratio were compared for cases with and without diffusive mass flux. Furthermore, a sensitivity analysis was carried out to identify important factors for UHS. The following parameters were investigated: permeability contrast, vertical to horizontal permeability ratio, reservoir heterogeneity, binary diffusion coefficient, and pressure dependent diffusion. In addition, the effects of numerical dispersion on the results were evaluated and are discussed.
The results of numerical simulation show the importance of diffusion on hydrogen storage in depleted gas reservoirs. Molecular diffusion plays a major role in case of heterogeneous reservoirs and large permeability contrasts. In low permeability zones, the diffusive mass transport becomes dominant over advective flux. Hydrogen propagates further into the low permeable layers of the reservoir when diffusion effects are considered compared with the cases neglecting diffusion. Similar effects are observed during the production cycle. Hydrocarbon gas in low permeability zones becomes more mobile due to diffusive transport. Thus, a larger amount of methane is back-produced with hydrogen for the cases when diffusion is simulated. It is shown that if molecular diffusion is ignored, the hydrogen recovery factor can be overestimated by up to 9% during the first production cycle and the onset of methane contamination can be underestimated by half of the back production cycle. Simulating pressure dependent diffusion might be important for specific configurations and should be covered in a sensitivity.
The results show that molecular diffusion within the reservoir has an impact on the onset of methane contamination when hydrocarbon gas is used as cushion gas in UHS. Also, the total amount of hydrogen produced is overestimated. For UHS operations, both, the composition and amount of hydrogen is important to design facilities and to determine the economics of UHS and hence diffusion should be evaluated in UHS simulation studies.
Fluid Modeling of Underground Hydrogen Storage in a Depleted Natural Gas Field
Authors: Nielsen Markus Hays , Arekhov Vladislav , Whitson Curtis Hays , Clemens Torsten , Zhainakov Timur , Wegner Jonas 
Published: June 2023

Abstract
Underground Hydrogen Storage (UHS) allows the storage of energy that is generated by fluctuating renewable energy sources such as solar and wind. Depleted hydrocarbon fields can be used to store hydrogen. The remaining hydrocarbon gas can be used as cushion gas. To engineer the UHS process, accurate phase, volumetric and transport behavior ("PVT") of hydrogen-hydrocarbon mixtures is required. In this paper, we develop an EOS and viscosity model to describe the operating envelope of a UHS operation in Austria.
Constant Composition Expansion (CCE) experiments were performed using a customized visual HPHT PVT set-up minimizing volume and density errors to ensure high accuracy of the measurements involving hydrogen. Viscosity experiments were performed using a capillary rheometer. Both experimental setups show a total measurement uncertainty of less than 2%. Experiments were performed for various hydrogen- hydrocarbon mixtures to cover the full range of the depleted gas field which is considered. The composition of hydrocarbon-hydrogen mixtures was confirmed using gas chromatography. The results were used to develop an EOS for the hydrogen-hydrocarbon system and to "tune" reduced density corresponding state models to match measured viscosity data.
The measured PVT and viscosity data of hydrogen-hydrocarbon mixtures measured in this study deviate somewhat from the default fluid models used in most commercial simulators. In this paper, a fluid model was developed using the Peng-Robinson EOS with volume shifts, and a reduced density corresponding state LBC viscosity model [1]. The fluid model was matched to (1) hydrogen-hydrocarbon gas laboratory measurements presented in this paper, (2) measured hydrogen-methane binary data (density and viscosity) taken from the literature, and (3) REFPROP (NIST) [2] calculated density and viscosity data for the hydrogen-hydrocarbon gas, hydrogen-methane binary system, and pure components. The required alteration (tuning) of the parameters in the fluid model development is discussed.
The impact of hydrogen content on gas mixture viscosity is studied based on a large number of literature studies for the hydrogen-methane binary system, and the hydrogen-hydrocarbon gas system presented in this paper for relevant operating conditions. Some literature data for hydrogen-methane systems show an anomalous, near-constant gas viscosity behavior at constant pressure and temperature with increasing hydrogen content, until a critical hydrogen content is reached (&gt;50 mole%). Similar behavior is also seen in the hydrogen-hydrocarbon gas mixture presented in this paper.
Modelling of Hydraulic Fracturing Risk on Cement Sheath Integrity
Authors: Cerasi Pierre Rolf , Todorovic Jelena 
Published: June 2023

Abstract
Finite element simulations investigate the effect of cement sheath length and proximity to perforations, varying the spacing of these and their length. The motivation is to assess the well integrity risk in fracturing operations, typical in shale gas or tight sandstone stimulation operations. Other applications are de-risking of injection operations in CO2 or H2 storage. Simplified simulations highlight unwanted associated fracturing in hydraulic fracturing operations, or as additional consequences of unplanned fracturing occurring due to injectivity impairment. Several cases are simulated: 1. Cased, cemented and perforated horizontal well interval; 2. Open hole perforated horizontal well interval; 3. Vertical cased and cemented interval. Results show that under some circumstances, fracturing may be expected in the well's cement sheath. These are locations where simulations show a possible fracturing scenario which could lead to unwanted pressure communication. However, the simulations all agree that there is no induced fracturing at more distant cement sheath sections. The major risk shown here is fracture initiation close to the perforated interval, suggesting that propagation along the cement sheath, although possible, is less likely.
Transient Pressure Interference During CO2 Injection in Saline Aquifers
Authors: Zeidouni Mehdi 
Published: June 2023

Abstract
CO2 injection in subsurface geological formations (e.g. deep saline aquifers) causes pressure perturbations over a large area surrounding the injection well. Observation wells are widely considered in geologic CO2 storage (GCS) projects where the pressure perturbation induced by CO2 injection is measured. In this work, we use analytical and numerical modeling tools along with field data to examine the pressure behavior in GCS projects before and after CO2 arrival at an observation well. Prior to CO2 arrival, a baseline pressure trend is established which corresponds to single-phase brine flow across the observation well (approximated by Theis solution). Therefore, analysis of early-time pressure data is straightforward, provides the single-phase flow characteristics (mobility and storativity), and helps establishing a baseline pressure change that can be extended beyond the single-phase flow period at the observation well.
Upon CO2 arrival, a departure from this baseline trend is expected. For the pressure to detect the CO2 arrival at an observation well, the departure from baseline pressure behavior must be significant and well above the background noise levels. We use existing analytical models to determine the strength of the expected pressure departure signal from the baseline trend upon CO2 arrival. The strength of the expected pressure departure is found to be directly proportional to the mobility ratio. Accordingly, we establish a criterion to determine whether the pressure at an observation well can detect the CO2 arrival. We present an analysis approach through application to synthetic and field data and show the characteristic pressure behavior before and after CO2 arrival. We show that while generally the pressure can be either above or below the expected baseline pressure trend, it would be likely above the baseline upon CO2 arrival. This is because the mobility ratio becomes less than unity after CO2 arrival. We show that depending on the reservoir characteristics, changes in the pressure trend may or may not be sufficient to detect the CO2 arrival.
Ising Meson Spectroscopy on a Noisy Digital Quantum Simulator
Authors: Roy Ananda , Lamb Christopher , Tang Yicheng , Davis Robert 
Published: June 2023

Abstract

Quantum simulation has the potential to be an indispensable technique for the investigation of non-perturbative phenomena in strongly-interacting quantum field theories (QFTs). In the modern quantum era, with Noisy Intermediate Scale Quantum (NISQ) simulators widely available and larger-scale quantum machines on the horizon, it is natural to ask: what non-perturbative QFT problems can be solved with the existing quantum hardware? We show that existing noisy quantum machines can be used to analyze the energy spectrum of a large family of strongly-interacting 1+1D QFTs. The latter exhibit a wide-range of non-perturbative effects like ‘quark confinement’ and ‘false vacuum decay’ which are typically associated with higher-dimensional QFTs of elementary particles. We perform quench experiments on IBM’s ibmq_mumbai quantum simulator to compute the energy spectrum of 1+1D quantum Ising model with a longitudinal field. The latter model is particularly interesting due to the formation of mesonic bound states arising from a confining potential for the Ising domain-walls, reminiscent of t’Hooft’s model of two-dimensional quantum chromodynamics. Our results demonstrate that digital quantum simulation in the NISQ era has the potential to be a viable alternative to numerical techniques such as density matrix renormalization group or the truncated conformal space methods for analyzing QFTs.
Reservoir operation method based on surrogate model and dynamic reservoir capacity
Authors: Zhu Sipeng , Qin Hui , Liu Huaiyuan , Qin Chao , Huang Jingwei , Wu Songlin , Niu Xinqiang 
Published: June 2023

Abstract
In recent years, more and more attention has been paid to the refined operation of reservoirs. Precise operation of reservoirs requires accurate calculation of reservoir capacity. Although hydrodynamic models can accurately calculate dynamic storage capacity, they cannot be used in reservoir operation models due to computational efficiency. This study uses a hydrodynamic model based on ELM to guide the training of PSTA-TCN as a proxy model. The dynamic storage capacity of the reservoir is included in the calculation when generating training data. The experimental results show that the proxy model can be used as a method to accurately calculate the reservoir capacity during the refined reservoir operation.
Voice activity detection for piano online teaching based on digital network system
Authors: Xiao Yayun 
Published: June 2023

Abstract
The purpose of this paper is to build a dedicated network dedicated to a complete digital network. So we investigated the necessity of network construction and digital and communication. After a lot of digital network research and detailed analysis of the system, the use plan of the report and further analysis. The purpose of the piano network system design is to solve traditional face-to-face education problems such as economy, time-consuming, physics, transportation, etc., and to make effective use of rapid development. In particular, it integrates all aspects of society with the network piano itself as learning Platform. By designing the resources and network system platform for effective piano learning, it can not only save social resources, but also provide convenience for students and teachers. This article first explains the basic principles related to voice activity detection, expounds the voice signal model, discusses the higher ratio of parameters used in conventional voice activity detection activities, and promotes simulation-related experiments to verify it. With the advent of the era of big data and the increase in network bandwidth, the previously limited network bandwidth resources have been improved, allowing users to perform a large number of online management. For example, piano online teaching technology based on broadband Internet, remote Internet in the field of information transmission, control technology, and piano, especially the Internet-based piano online teaching system, are all important industries in the era of big data.
Assessing the global impact of targeted conservation actions on species abundance
Authors: Blackburn Tim , Dove Shawn , Geldmann Jonas , Gregory Richard , Hoffmann Michael , McRae Louise , Visconti Piero , Jellesmark Sean 
Published: June 2023

Abstract
Globally, vertebrate abundance has declined, and species’ extinction rates have increased, at unprecedented rates over recent decades 1,2. In response, targeted species interventions, such as conservation breeding programmes, legislative measures or species-specific habitat management, have been used to help address population declines and reduce and reverse the loss of biodiversity 3,4. Until now, assessments of conservation actions have focused on the extent to which they reduce extinction risk or focus on the impact of protected areas 4–9. Here, we extend our knowledge of conservation efficacy by quantifying the impact of targeted conservation actions on vertebrate abundance, analyzing data from 26,904 vertebrate populations across 4,629 species worldwide. Using a counterfactual approach to represent population trends in the absence of conservation, we show that targeted actions have delivered substantial positive effects on the abundance of recipient vertebrate populations worldwide. Positive trends were especially observed in vertebrate populations subject to species or habitat management. Our results provide compelling evidence that, with sufficient and sustained resourcing and commitment, successful implementation of Target 4 of the recently adopted Kunming-Montreal Global Biodiversity Framework can readily help reverse global biodiversity loss and put nature on a path to recovery.