bluuebunny/crossref_metadata_2025_split huggingface dataset:
Emerging Techniques in Measuring Capillary Pressure and Permeability Using NMR and AI
Authors: Ghamdi Ahmed , Isah Abubakar , Elsayed Mahmoud , Garadi Kareem , Abdulraheem Abdulazeez 
Published: December 2021

Abstract
Measurement of Special Core Analysis (SCAL) parameters is a costly and time-intensive process. Some of the disadvantages of the current techniques are that they are not performed in-situ, and can destroy the core plugs, e.g., mercury injection capillary pressure (MICP). The objective of this paper is to introduce and investigate the emerging techniques in measuring SCAL parameters using Nuclear Magnetic Resonance (NMR) and Artificial Intelligence (Al).
The conventional methods for measuring SCAL parameters are well understood and are an industry standard. Yet, NMR and Al - which are revolutionizing the way petroleum engineers and scientists describe rock/fluid properties - have yet to be utilized to their full potential in reservoir description. In addition, integration of the two tools will open a greater opportunity in the field of reservoir description, where measurement of in-situ SCAL parameters could be achieved. This paper shows the results of NMR lab experiments and Al analytics for measuring capillary pressures and permeability.
The data set was divided into 70% for training and 30% for validation. Artificial Neural Network (ANN) was used and the developed model compared well with the permeability and capillary pressure data measured from the conventional methods. Specifically, the model predicted permeability 10% error. Similarly, for the capillary pressures, the model was able to achieve an excellent match. This active research area of prediction of capillary pressure, permeability and other rock properties is a promising emerging technique that capitalizes on NMR/AI analytics. There is significant potential is being able to evaluate wettability in-situ. Core-plugs undergoing Amott-Harvey experiment with NMR measurements in the process can be used as a building block for an NMR/AI wettability determination technique. This potential aspect of NMR/AI analytics can have significant implications on field development and EOR projects
The developed NMR-Al model is an excellent start to measure permeability and capillary pressure in-situ. This novel approach coupled with ongoing research for better handling of in-situ wettability measurement will provide the industry with enormous insight into the in-situ SCAL measurements which are currently considered as an elusive measurement with no robust logging technique to evaluate them in-situ.
Micromechanics of Drilling: A Laboratory Investigation of Formation Evaluation at the Bit
Authors: Koulidis Alexis , Mohamed Fahd , Ahmed Shehab 
Published: December 2021

Abstract
Challenging drilling applications and low oil prices have created a new emphasis on innovation in the industry. This research investigates the value of drill bit based force sensing at the rock-cutter interface. For this purpose, a laboratory-based mini-rig has been built in order to recreate a scaled drilling process. The work aims to build a better understanding of the collected force and torque data despite the semi-continuous drilling process. This data is then used to estimate the formation strength.
A scaled drill bit with two cutters was designed with sensors integrated into the drill bit cutter, drill string and the mini-rig structure. The mini-rig design allowed the accurate control of depth of cut by utilizing a comprehensive data acquisition and control system during the experiments. Initially, fifty-five samples were prepared with various water/gypsum ratios for a uniaxial compression test, scratch test, and for testing in the mini-rig. Prior to the mini-rig experiments, the results of the uniaxial compression and scratch tests were used as a benchmark to extract rock properties and the state of stress behavior.
The experiments under atmospheric conditions revealed that the mini-rig could accurately estimate formation strength from a few rotations. The force data at the bit-rock interface was correlated with the torque measurements, and the results indicate that the tangential force has similar trends and relatively similar values.
The groove created by the drill bit's rotating trajectory has a 14.45 cm circumference. This allows for a significant amount of data to be captured from a single rotation. The circular cutter geometry's influence is crucial for a continuous process since the active cutting area is continuously changing due to the pre-cut groove. The performed depth of cuts ranged from 0.1 to 1 mm in the same groove, and thus the active cutting area can be accurately calculated in real-time while conducting the experiments.
Tangential and normal force data from the scratch test was analyzed in order to provide insights for correlation with the mini-rig data. The analysis shows that both tests give similar trends to the force measurements from the mini-rig. Moreover, the benchmark value of formation strength that was obtained from the uniaxial compression test was also in the same range. This illustrates the potential viability of drill bit based formation strength measurement due to the similarity between mini-rig test results and those using more classical testing practices.
The experimental setup can provide a continuous cutting process that allows an accurate estimation of formation strength during a semi-continuous drilling operation with analogous application in the field. This can lead to an in-depth understanding of drilled formation properties while drilling and possibly assist in evaluating cutter wear state in-situ.
Intelligent Rotary Steerable System, Coupled with an Instrumented Bit, Delivers Section Plan in Deepwater GOM Project
Authors: Snyder John , Salmon Graeme 
Published: December 2021

Abstract
The challenging offshore drilling environment has increased the need for cost-effective operations to deliver accurate well placement, high borehole quality, and shoe-to-shoe drilling performance. As well construction complexity continues to develop, the need for an improved systems approach to delivering integrated performance is critical.
Complex bottom hole assemblies (BHA) used in deepwater operations will include additional sensors and capabilities than in the past. These BHAs consist of multiple cutting structures (bit/reamer), gamma, resistivity, density, porosity, sonic, formation pressure testing/sampling capabilities, as well as drilling dynamics systems and onboard diagnostic sensors. Rock cutting structure design primarily relied on data capture at the surface. An instrumented sensor package within the drill bit provides dynamic measurements allowing for better understanding of BHA performance, creating a more efficient system for all drilling conditions. The addition of intelligent systems that monitor and control these complex BHAs, makes it possible to implement autonomous steering of directional drilling assemblies in the offshore environment.
In the Deepwater Gulf of Mexico (GOM), this case study documents the introduction of a new automated drilling service and Intelligent Rotary Steerable System (iRSS) with an instrumented bit. Utilizing these complex BHAs, the system can provide real-time (RT) steering decisions automatically given the downhole tool configuration, planned well path, and RT sensor information received. The 6-3/4-inch nominal diameter system, coupled with the instrumented bit, successfully completed the first 5,400-foot (1,650m) section while enlarging the 8-1/2-inch (216mm) borehole to 9-7/8 inches (250mm). The system delivered a high-quality wellbore with low tortuosity and minimal vibration, while keeping to the planned well path. The system achieved all performance objectives and captured dynamic drilling responses for use in an additional applications.
This fast sampling iRSS maintains continuous and faster steering control at high rates of penetration (ROP) providing accurate well path directional control. The system-matched polycrystalline diamond (PDC) bit is engineered to deliver greater side cutting efficiency with enhanced cutting structure improving the iRSS performance. Included within the bit is an instrumentation package that tracks drilling dynamics at the bit. The bit dynamics data is then used to improve bit designs and optimize drilling parameters.
Research On Energy Distribution and Solidification Characteristics During Laser Cladding Based On Numerical Simulation
Authors: Yang Wenhui , Cheng Yanhai , Zhang Yipeng , Yang Jinyong , Liang Xiubing 
Published: December 2021

Abstract
Laser cladding as an emerging surface modification technology can be widely adopted for surface modification. In this study, 27SiMn was selected as the substrate, the powder was a self-made iron-based alloy, and the thermophysical properties of the material were predicted by the CALPHAD algorithm. The numerical model of the laser cladding process is established by setting reasonable hypothetical condition, initial condition, boundary condition, and solver parameters. In order to verify the accuracy of the numerical model, 10 sets of experiments have been carried out, and the agreement between the model calculation results and the experimental results reached 92%. Through the study of energy distribution in the laser cladding process, it is found that about 10% of the laser energy is used to heat the substrate to form a melt-pool, and at least 53% of the energy is radiated into the environment. Finally, the effects of temperature gradient and solidification rate on the microstructure of the cladding layer were explored.
Genome Wide Identification and Characterization of Mitogen Activated Protein Kinase (MAPK) Genes Reveals Their Potential in Enhancing Drought and Salt Stress Tolerance in Gossypium Hirsutum
Authors: Salisu Sadau Bello , Mehari Teame Gereziher , Ahmad Adeel , Tajo Sani Muhammad , Ibrahim Sani , Iqbal Muhammad Shahid , Elasad Mohammed , Zhang Jingjing , Wei Hengling , Yu Shuxun 
Published: December 2021

Abstract
Background: Cotton crop is universally considered as protein and edible oil source besides the major contributor of natural fiber and is grown all around the globe. Unpredicted environmental stresses are becoming a significant threat to sustainable cotton production, ultimately leading to a substantial irreversible economic loss. Mitogen-activated protein kinase (MAPK), generally considered essential for recognizing environmental stresses through phosphorylating downstream signal pathways.Results: In the current study, we have identified 74 MAPK genes across cotton, 41 from G. hirsutum, 19 from G. raimondii, whereas 14 have been identified through G. arboreum. The MAPK gene-proteins have been further interrogated to determine their physicochemical characteristics and other essential features. In this perspective, characterization, phylogenetic relationship, chromosomal mapping, gene motif, cis-regulatory element, and subcellular localization were carried out. Based on phylogenetic analysis, the MAPK family in cotton is usually categorized as A, B, C, D, and E clades. Seven GHMAPK genes (GH_A07G1527, GH_D02G1138, GH_D03G0121, GH_D03G1517, GH_D05G1003, GH_D11G0040, and GH_D12G2528) were selected, and specific tissue expression and profiling were performed across drought and salt stress.Conclusions : RNA sequence and qPCR results represented genes as differentially expressed across both vegetative and reproductive plant parts. Similarly, the qPCR analysis showed that six genes had been upregulated substantially through drought treatment while all the genes were upregulated across salt treatment.
"Hand as Foot Teaching Method" Application in Upper Cervical Anatomy and Common Diseases
Authors: Hao Haijing , Xu Lu , Wang Haohui , Wang Zhe , Liu Xingyu , Wang Pengpeng , Liu Xiaoqi 
Published: December 2021

Abstract
Background“Hand as Foot teaching method” has been applied to the clinical teaching of various orthopaedic subspecialties and achieved good results, but it has not been carried out in the specialized teaching of spine surgery, especially the upper cervical spine. The orthopedics teaching team of the Second Affiliated Hospital of Harbin Medical University applied this teaching method to the clinical teaching of atlantoaxial anatomical relationships and common atlantoaxial diseases.MethodsThe "Hand as Foot Teaching Method" was used to teach key and difficult points for master students of osteology in the Second Affiliated Hospital of Harbin Medical University, supplemented by PPT + anatomical specimens to assist the teaching process.Results"Hand as Foot Teaching Method" can concretize the complex anatomical structure of upper cervical vertebra, thus deepening students' understanding and memory of difficult points, enhancing teacher-student interaction and activating the teaching atmosphere.Conclusion"Hand as Foot Teaching Method" can be applied to the clinical teaching of atlantoaxial knowledge. Compared with the simple application of PPT + model teaching, this teaching method is more helpful for students to grasp difficulties quickly and in three dimensions, significantly improve the teaching quality, and can even be applied to preoperative doctor-patient communication. It has application and promotion value in clinical teaching of spinal surgery.
Projection of Droughts in Amu Darya River Basin for Shared Socioeconomic Pathways
Authors: Salehie Obaidullah , Hamed Mohammed Magdy , Ismail Tarmizi bin , Shahid Shamsuddin 
Published: December 2021

Abstract
Droughts significantly affect socioeconomic and the environment primarily by decreasing the water availability of a region. This study aims to assess the changes in drought characteristics in Central Asia's transboundary Amu Darya river basin for four shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The precipitation, maximum and minimum temperature (Pr, Tmx and Tmn) simulations of 19 global climate models (GCMs) of the coupled model intercomparison project phase 6 (CMIP6) were used to select the best models to prepare the multimodel ensemble (MME). The standard precipitation evapotranspiration index (SPEI) was used to estimate droughts for multiple timescales from Pr and potential evapotranspiration (PET) derived from Tmx and Tmn. The changes in the frequency and spatial distribution of droughts for different severities and timescales were evaluated for the two future periods, 2020–2059 and 2060-2099, compared to the base period of 1975-2014. The study revealed four GCMs, AWI-CM-1-1-MR, CMCC-ESM2, INM-CM4-8 and MPI-ESM1-2-LR, as most suitable for projections of droughts in the study area. The multimodel ensemble (MME) mean of the selected GCMs showed a decrease in Pr by -3 to 12% in the near future and a change in the range of 3 to -9% in the far future in most parts of the basin for different SSPs. The PET showed almost no change in most parts of the basin in the near future and an increase in the range of 10 to 70% in the far future. The change (%) in projected drought occurrence showed to noticeably decrease in the near future, particularly for moderate droughts by up to ≤-50% for SSP5-8.5 and an increase in the far future by up to ≥30% for SSP3-7.0. The increase in all severities of droughts was projected mostly in the center and northwest of the basin. Overall, the results showed a drought shift from the east to the northwest of the basin in the future.
Dynamic Two-sided Matching Group Decision-making Model with Multi-form Preference Information for Configuring Tasks and Resources in Cloud Manufacturing
Authors: Zhang Xuejiao , Yang Yu 
Published: December 2021

Abstract
Enterprises have been faced with the problem of how to optimize resource allocation in an uncertain environment by the expanding of manufacturing informatization. In the process of cloud manufacturing matching, group decision making organizations may provide uncertain preference information. However, preference information at various points have led to differing impacts of the final matching decision. it is necessary to study the dynamic two-sided matching. In this paper, the dynamic two-sided matching problem under the multi-form preference information was studied. Primarily, the problem of two-sided matching is described, then through group decision-making and uncertain preference information, an ordinal vector matrix is constructed. Afterwards, the comprehensive satisfaction matrix is calculated by using dynamic time-series weight and matching competition degree. Further, by introducing stable matching constraints, a multi-objective optimization model considering the satisfaction, fairness and stability of matching is constructed. Then the optimal matching result is obtained by solving the model. In addition, the presented method was verified through a case of cloud manufacturing. At the end, advantages of the presented model were demonstrated by comparison. Research results of this paper enrich the theoretical research of two-sided matching and provide an effective solution for cloud manufacturing matching in uncertain environments.
Complex Drivers of Riparian Soil Oxygen Variability Revealed Using Self-Organizing Maps
Authors: Lancellotti Brittany Victoria , Underwood Kristen , Perdrial Julia , Adair Carol , Schroth Andrew , Roy Eric 
Published: December 2021

Abstract
Oxygen (O2) is a key regulator of soil reduction-oxidation processes and therefore modulates biogeochemical cycles. The difficulties associated with accurately characterizing soil O2 variability have prompted the use of soil moisture as a proxy for soil O2, based on the low solubility of O2 in water. Due to seasonal shifts in soil O2 depletion mechanisms, the use of soil moisture alone as a proxy measurement could result in inaccurate O2 estimations. For example, soil O2 may remain high during cool months when soil respiration rates are low. We analyzed high-frequency sensor data (e.g., soil moisture, temperature, CO2, O2) with a machine learning technique, the Self-Organizing Map, to pinpoint suites of soil conditions that are associated with contrasting O2 regimes. At two low-lying riparian sites in contrasting land use and topographic settings of northern Vermont, we found that soil O2 levels varied seasonally, and with soil moisture. For example, forty-seven percent of low O2 levels were associated with cool and wet soil conditions, whereas 32% were associated with warm and dry conditions. Contrastingly, the majority (62%) of high O2 conditions occurred under warm and dry conditions. High soil moisture levels did not always lead to low O2, however, as 38% of high O2 values occurred under cool and wet conditions. Our results highlight challenges associated with predicting soil O2 solely based on soil moisture, as variable combinations of soil and site-specific hydrologic conditions can complicate the relationship between soil water content and O2. This indicates that process-based ecosystem and denitrification models that rely solely on soil moisture to estimate O2 availability will, in some cases, need to incorporate other site and climate-specific drivers to accurately predict soil O2.
Syphilis Trigram: a domain-specific visualisation to combat syphilis epidemic and improve the quality of maternal and child health in Brazil
Authors: Morais Cleber Matos , Teixeira Igor Vitor , Endo Patricia Takako , Kelner Judith 
Published: December 2021

Abstract
Background: The Brazilian health system is a large and complex system, especially considering its mixed public and private funding. The number of syphilis cases has been increasing greatly in the last four years, even though it has a cheap and simple treatment. Syphilis notification is compulsory by law, and public health surveillance pays great importance to syphilis notification during pregnancy. Syphilis infection can cause severe newborn conditions, premature births, and abortions. Methods: The Action Research methodology was applied to deal with the complex syphilis surveillance reality in Pernambuco, Brazil. Iterative learning cycles were used, totalling six cycles with a formal validation of an operational version of the Syphilis Trigram visualisation at the end of the process. The original data source was analysed and prepared for use without any new data or changes in the ordinary procedure of the current system. Results: The main result of this study is the Syphilis Trigram, a domain-specific infographic for presenting gestational and birth data. The second contribution of this study is the Average Trigram, an organised pie chart which synthesises the Syphilis Trigram relationship in an aggregated manner. Both visualisations are presented in an Infographic User Interface, a tool that gathers an infographic broad visualisation sense for data visualisation. These interfaces also gather selection and filter tools to assist and refine the presented information. The user can experience a specific case-by-case view and an aggregated perspective by any city monitored by the system. Conclusions: The proposed domain-specific visualisation amplifies the understanding of each syphilis case and the overall case characteristics of a city. This new information produced by the Trigram can clarify the reinfection/relapse cases, optimise resource allocation, and enhance syphilis healthcare policies without any new data. Therefore, health surveillance professionals can see the broad tendency, understand the key patterns through visualisation, and take action in a feasible time.
Combining a Locally Restricted Anisotropic Spatial Kernel with an ETAS Incomplete Model for Better Forecasts of the 2019 Ridgecrest Sequence
Authors: Grimm Christian , Hainzl Sebastian , Käser Martin , Küchenhoff Helmut 
Published: December 2021

Abstract
Strong earthquakes cause aftershock sequences that are clustered in time according to a power decay law, and in space along their extended rupture, shaping a typically elongate pattern of aftershock locations. A widely used approach to model seismic clustering is the Epidemic Type Aftershock Sequence (ETAS) model, that shows three major biases: First, the conventional ETAS approach assumes isotropic spatial triggering, which stands in conflict with observations and geophysical arguments for strong earthquakes. Second, the spatial kernel has unlimited extent, allowing smaller events to exert disproportionate trigger potential over an unrealistically large area. Third, the ETAS model assumes complete event records and neglects inevitable short-term aftershock incompleteness as a consequence of overlapping coda waves. These three effects can substantially bias the parameter estimation and particularly lead to underestimated cluster sizes. In this article, we combine the approach of Grimm (2021), which introduced a generalized anisotropic and locally restricted spatial kernel, with the ETAS-Incomplete (ETASI) time model of Hainzl (2021), to define an ETASI space-time model with flexible spatial kernel that solves the abovementioned shortcomings. We apply different model versions to a triad of forecasting experiments of the 2019 Ridgecrest sequence, and evaluate the prediction quality with respect to cluster size, largest aftershock magnitude and spatial distribution. The new model provides the potential of more realistic simulations of on-going aftershock activity, e.g.~allowing better predictions of the probability and location of a strong, damaging aftershock, which might be beneficial for short term risk assessment and desaster response.