bluuebunny/crossref_metadata_2025_split huggingface dataset:
Horizontal Well Casing Design Optimization & Implementation Case Study: Vibrations Management Through Enhanced Bottom Hole Assembly Design
Authors: Abaltusov Nikolay , Ryabov Anton , Dankov Aleksandr , Zaripov Elvir , Grishin Dmitriy , Teregulov Oleg 
Published: October 2019

Abstract
The objective of pilot testing was to optimize horizontal well construction cycle by decreasing the number of casing strings. The testing involved drilling of 13 wells, in which only production casing was run in hole instead of intermediate casing and a liner.
The key issue during drilling was failure of measurement tools due to high vibration. This paper covers decisions and actions being made to get a well with new casing design successfully drilled.
To mitigate the issues, the bottom hole assembly (BHA) behavior was modeled using a proprietary software for static and vibration analysis. Relevant diameters of stabilizers and drilling modes were selected. The interpreted computations were successfully used for drilling further wells.
For comprehensive approach, an optimal bit design was selected vibration mitigation wise.
Three-axis vibration sensors installed in the BHA enabled selecting of optimal drilling modes in real time.
Drilling of triple casing wells showed reduction in actual well construction time compared to quadruple casing by 20% on the average.
The record-setting well was drilled in 8.6 less days compared to a similar 4-string well. Furthermore, BHA with mud motor was used, which is less expensive compared to a BHA with Rotary Steerable System (RSS).
The three-string design was used at the fields in question for the first time.
The accumulated experience makes it possible to use this technology at other fields, where horizontal wells are drilled.
Well Placement Optimization with an Artificial Intelligence Method Applied to Brugge Field
Authors: Bruyelle Jérémie , Guérillot Dominique 
Published: October 2019

Abstract
Planning the position of a new well is an essential task to increase hydrocarbon production. However, trying to capture the uncertainty related to the geological properties, an ensemble of geological realizations of the models must be considered. The objective can be to identify the locations of the new wells that maximize the average oil recovery or Net Present Value (NPV), for an ensemble of geological models. Also, considering an ensemble of geological models, an objective can be to minimize the standard deviation of the NPV (or cumulative oil recovery). Reducing the uncertainty on the NPV leads to reduce the risk for the placement of the new wells. These two objectives can be defined with a "mean-standard deviation" formulation of the objective function. Following the weight given to each objective, the placement of the wells is not the same. To know all the well-placement possibilities and associated risk, many optimization problems must be done. Such as procedures, require the use of optimization method and reservoirs simulations on each reservoir model. This optimization problem leads to a high number of reservoir simulation to determine the appropriate location and can be expensive in computation time. To reduce the computation time, a method consists in to substitute the reservoir simulator by a meta-model. In this paper, the use of an artificial neural network as a proxy model is considered. The objective is to propose a method to speed up the well-placement optimization process using a proxy model based on an artificial intelligence technique to replace the reservoir simulator. The proposed methodology considers an ensemble of realization and aims to provide an overview of solutions in an economic point of view inspired by portfolio optimization problems. An application of the methodology is presented for the Brugge field.
Flow Characteristics Through Gas Alternating Gas Injection During Enhanced Gas Recovery
Authors: Mohammed Nuhu , Abubakar Abbas Jibrin , Enyi Godpower Chimagwu , Ghavami Ghasem Nasr 
Published: October 2019

Abstract
Gas and liquid flooding using carbon dioxide (CO2), nitrogen (N2), or brine solution have become one of the promising enhanced gas (EGR) and oil recovery (EOR) technologies for residual hydrocarbons (HCs) enhancement in conventional oil and gas reservoir respectively. However, the flow mechanism between the displacing and displaced fluids are not yet clear, especially for the novel gas alternating gas injection method adopted in this study. This experimental study investigates the flow mechanism of N2-CO2-CH4 through gas alternating gas injection techniques in consolidated rocks during EGR. The research presents a better flow behaviour characteristic using a novel N2 alternating CO2 during EGR. These values were used in determining the optimum injection rate with the minimum in situ mixing and high displacement front. An experimental laboratory core flooding, experiment was done to imitate a detailed process of an unsteady state N2-CO2-CH4 displacement in Bandera grey core sample at 35-40°C of temperature, 1500 psig of pressure, and at 0.2, 0.4, 0.6, 0.8 and 1.0 ml/min N2 alternating CO2 injection rates to evaluate the displacement flow characteristics, such as diffusion coefficient, dispersion coefficient, density and viscosity, mobility ratio, and dispersivity. The CO2 was injected after 4-5 cm3 of N2 injection throughout the runs at the experimental condition. The findings indicated that gas alternating gas injection technique presents a better flow behaviour characteristic compared to that of individual CO2 or N2 injection. Such prominent behaviour was observed at 0.4 ml/min injection, with higher displacement front and longer CO2 breakthrough time. The mobility ratio of N2-CO2-CH4 was lower compared to that of N2-CH4 and CO2-CH4. This was due to the inclusion of nitrogen which acts as a barrier between the CO2 and displaced CH4. The later contributed significantly for the delayed in CO2 breakthrough especially at lower injection rates (0.2-0.4 ml/min) during the gas alternating gas EGR process. The overall molecular diffusion coefficients were found to be 22.99, 18.48 and 17.33 ×10-8 m2/s for N2-CH4, CO2-CH4, and CO2-N2 binary interaction respectively at the test condition. The dispersion coefficient increases with an increase in the injection rate due to rise in the interstitial velocity as the CO2 plume traverses through the core sample during the EGR process.
Understanding O/G Shale Reservoir Tortuosity by Imaging Characterizations
Authors: Sewailan Mohammad , Al-Bazzaz Waleed 
Published: October 2019

Abstract
A shale reservoir rock sample has been imaged successfully at 40X (millimeter scale), 400X (micrometer scale), and 4000X (nanometer scale). All captured images have been processed with morphological approach utilizing big data for porosity with pore size distribution as well as tortuosity. 1D, 2D and 3D pre-logic models are developed. And heterogeneity post-logic models are also developed. Nano pores are dominated in shale rock; as a result, the tortuous paths recognized are very complex yet very hopeful for many production scenarios.
The prepared shale rock samples in the form of rock fragments will be imaged and characterized for porosity morphology, pore size distributions, and tortuosity in 2D format utilizing SEM-BSE imaging techniques. The generated images will be quantified using pre-defined logic (10-classes of pore ranges, pore counts, pore frequency percent, and pore area). The data generated will be used to estimate tortuosity. Tortuosity investigations are set for different magnifications X40-millimeter scale, X400-micrometer scale, and X4000-nanometer scale, yielding the total formation/ sample experiments to become 3 magnifications X 1 sample = 3 experiment suites to ensure tortuosity representations for all shale pore magnification.
The overall objective is to increase shale reservoir knowledge and awareness of imaging characterizations that inherits increasingly sophisticated and unconventional technologies, which make the production of unconventional resources faster, accurate, and economically efficient. Another objective is to justify the exploitation of organically rich unconventional Oil and Gas (O&G) shale reservoirs that were always ignored by operators seeking easier production and faster returns on investments, as potential sources of significant natural gas and liquid reserves. The final objective is to introduce a reliable method to quantify tortuosity for unconventional reservoirs that seeks new physics in order to advance stimulation, advance reservoir characterization, and advance recovery efficiencies and production improvement.
Self-Healing PAM Composite Hydrogel for Water Shutoff at High Temperatures: Thermal and Rheological Investigations
Authors: Almohsin Ayman , Michal Feven , Alsharaeh Edreese , Bataweel Mohammed , Krishnan Mohan 
Published: October 2019

Abstract
Self-healing hydrogels have attracted much attention as they possess the ability to increase the lifetime of the materials and reduce the total cost during the process of long-term use. In this study, self-healing PAM-Zr(OH)4 hydrogel was prepared from acrylamide (AM) and Zr(OH)4 nanosheet filler using a free radical polymerization method. In addition, the polymerization of AM monomers was initiated by ammonium persulfate (APS) while tetramethylethylenediamine (TEMED) was used as a catalyst. The prepared composite hydrogel was cured at high temperature (i.e. 150°C) in order to simulate the conditions of the oil reservoirs. The thermal and rheological properties of the composite hydrogel were studied using thermogravimetric analyzer (TGA), differential scanning calorimetry (DSC) and dynamic mechanical analyzer (DMA). As observed from DSC, the free water (Wf) for PAM-Zr(OH)4 hydrogel was 0.39 and that of for neat-PAM was 0.34. The storage modulus (G′) and loss modulus (G″) for the PAM-Zr(OH)4 hydrogel were 2060 Pa and 644 Pa, whereas that of for neat PAM was 2000 Pa, 627 Pa respectively. From the results, incorporating fillers into the PAM matrix had significant improvements on the thermal and mechanical properties for PAM-Zr(OH)4 hydrogel in comparison to that of neat-PAM hydrogel. In addition, the composite hydrogel has demonstrated an excellent swelling behavior (i.e. swelling capacity up to 14,000%) while sustaining its gel strength (G′/G″). The kinetics of water absorption by the PAM-Zr(OH)4 hydrogel was pseudo-second-order with a second-order rate constant (k2) of 9.3×10−8 min g/g.
Enhanced Oil Recovery for Carbonate Oil Reservoir by Using Nano-Surfactant:Part II
Authors: Alhuraishawy Ali K. , Hamied Ramzy S. , Hammood Hajir A. , AL-Bazzaz Waleed Hussien 
Published: October 2019

Abstract
Excellent attempts have been made worldwide to improve oil recovery. Nano technology features in EOR have been the focus of attention over the past century. The introduction of nanotechnology began in the late 1980s and was created to synthesize fresh nano-materials by rearranging atoms and molecules. Based on the small partition size of NPs (1-100) nm, the optical, thermal, chemical and structural properties of the nanomaterial differ completely from those shown by either its atoms or bulk materials. It is also clear that surfactants contribute to the stability of nanoparticles and emulsions with the aim of reducing IFT and changing rock wettability to water-wet.
The main objective of this study is to investigate the effects of nano particles and surfactant on improving oil recovery in carbonate reservoirs. Two key parameters were examined: silica nano particles and silica nano particles with Sodium Dodecyl sulfate (SDS) as an anionic surfactant. Finally, flooding test showed that using 0.03wt% SiO2 with 0.158 wt% SDS can improve oil recovery by 15.1% and minimize residual oil saturation to 25.6%. X-ray powder diffraction (XRD) and field emission scanning electron microscope (FESEM) were also done for thin core samples and the results have been discussed.
The Interrelationship of Carbonate Reservoir Quality and Dynamic Characterization of Chemical Solutions for Potential of Enhanced Oil Recovery
Authors: Zhou Xianmin , Kamal Muhammad Shahzad 
Published: October 2019

AbstractUnderstanding complex variation in dynamic characterizations of chemical solutions on the surface of rock related to different carbonate reservoir quality is one of the most challenging subjects in the enhanced oil recovery process because pore distribution, pore structure and petrophysical properties of carbonate reservoir have many differences. Carbonate reservoirs usually have heterogeneity, a wide range of pore levels and petrophysical parameters. This research aims to investigate systematically and explain the interrelationship between reservoir quality indexes (RQI) or flow zone indicator (FZI) and dynamic characterization of chemical solutions. The interrelationship derived can be applied to enhanced oil recovery in carbonate reservoirs.Several laboratory studies were completed using carbonate core plugs and reservoir brine at reservoir conditions for dynamic characterization of chemical solutions for the potential application of enhanced oil recovery: 1). the evaluation of resistance factor (RF), residual resistance factor (RRF) and injectivity (I) of a sulfonated polymer; 2). dynamic adsorption and desorption of an amphoteric surfactant. The RQIs of carbonate core plugs are in the range of 0.74 to 1.91 µm.Based on the results of this study, we found that the dynamic characterizations of chemical solutions depend on the RQI. The results from a sulfonated polymer solution injection tests show that RF and RRF increase with a decrease in RQI for both solutions of 0.1 wt% and 0.2 wt% polymer. However, there is a critical frontal velocity for such a polymer solution of 0.2 wt%. When the frontal velocity is more than critical frontal velocity, RRF has similar values with increase in front velocity. Liquid permeability loss at a concentration of 0.2 wt% is higher than that in the case of 0.1 wt%.This paper provides a comprehensive overview of dynamic characterization of an amphoteric surfactant and sulfonated polymer for carbonate reservoir rocks with RQI and presents insights and large potential for application of chemically enhanced oil recovery in carbonate reservoirs.
Stuck Pipe Incidents Prediction Based On Data Analysis
Authors: Zhu Qi , Wang Zhaohui , Huang Jian 
Published: October 2019

Abstract
The process of oil and gas drilling is a complicated and uncertain field practice. Moreover, uncertainty and fuzziness of formation is also a threat to drilling safety. Due to inaccurate cognition of objective environment and decision-making errors of subjective consciousness, underground complex conditions and serious accidents are caused.
Stuck pipe is one kind of downhole accident with high probability, complex handling difficulty and cost of manpower and material resources in drilling engineering. To deal with the stuck pipe accident, workers on the well-site are often required to judge the geological conditions of formation drilled, to adjust drilling parameters, drilling fluid performance and other methods to avoid and remove. Without fixed reference basis and determination methods, it is difficult to provide early warnings.
Through the collection, while drilling in formation, such as geological lithology, designed well structure, real-time drilling fluid performance, rock physical properties of backflow cuttings, and drilling engineering parameter et,al. Artificial neural network learning model is used to predict the risk probability of stuck pipe.
In this paper, face to formation collapse stuck pipe, after collected and analyzed the physical and chemical properties of backflow cuttings, drilling fluid system performance, well-site drilling data and other well-site drilling parameters according to the influencing factors of collapse and stuck pipe, combined with computer intelligent technology, and predicted collapse stuck pipe risk probability in advance.
Through well-field data collected, the occurrence of stuck pipe is predicted successfully. Through accumulated database, the accuracy of prediction model is constantly improved and modified. Early warning mechanism, timely adjustment of drilling fluid additives, maintenance of drilling fluid system performance and improvement of drilling parameters for different formations, increase drilling speed and avoid unnecessary waiting time
Impact of AKAP6 Polymorphisms on Glioma Susceptibility and Prognosis
Authors: Zhang Ming , Zhao Yonglin , Zhao Junjie , Huang Tingqin , Wu Yuan 
Published: October 2019

Abstract
Purpose Glioma is the most common primary malignant brain tumor with high mortality and poor prognosis. Our aim was to clarify the correlation between AKAP6 gene polymorphisms and glioma susceptibility and prognosis in Chinese Han population. Methods Five single-nucleotide polymorphisms (SNPs) of AKAP6 were genotyped by Agena MassARRAY in 575 glioma patients and 500 healthy controls. Logistic regression model was utilized to calculate odds ratios (OR) and 95% confidence intervals (CI). The associations between polymorphisms and survival were assessed using the log-rank test, Kaplan-Meier analysis and Cox regression model. Results We found that rs2239647 polymorphism was strongly associated with an increased risk of glioma (OR = 1.90, p = 0.007) and a worse prognosis for glioma, especially in high-grade glioma (HR = 1.67, p = 0.034). Stratified analysis showed that rs2239647 increased the risk of glioma in female (OR = 1.62, p = 0.016). Whereas, rs4261436 (HR = 0.70, p = 0.045) and rs17522122 (HR = 0.75, p = 0.016) were associated with better prognosis of astrocytoma. In addition, we also found that surgical methods and chemotherapy are critical factors for the prognosis of glioma patients. Conclusions This study firstly provided evidence for the impact of AKAP6 polymorphisms on susceptibility and prognosis of glioma, suggesting AKAP6 variants might have potential roles in the etiology of glioma.
A phenomics-based approach for the detection and interpretation of shared genetic influences on 29 biochemical indices in Chinese south men
Authors: hu yanling , tan aihua , yu lei , hou chenyang , kuang haofa , wu qunying , sun Jinghan , zhou Qingniao , zhu yuanyuan , Zhang Chenqi , wei wei , li Lianfeng , li weidong , huang yuanjie , huang hongli , xie xing , lu tingxi , zhang haiying , yang xiaobo , gao yong , li tianyu , Jiang yonghua , mo zengnan 
Published: October 2019

Abstract
Background: Phenomics provides a new technologies and platforms as a systematic phenome-genome approach. However, few studies have reported on the system mining of shared genetics among clinical biochemical indices based on Phenomics methods, especially in China. This study aimed to apply phenomics to systematically explore shared genetics among 29 biochemical indices based on the Fangchenggang Area Male Health and Examination Survey cohort.
Result: A total of 1,999 subjects with 29 biochemical indices and 709,211 single nucleotide polymorphisms were subjected to phenomics analysis. Three bioinformatics methods, namely, Pearson test, Jaccard index, and linkage disequilibrium score regression , were used. Results showed that 29 biochemical indices were from a network. IgA, IgG, IgE, IgM, HCY, AFP and B12 were in the central community of 29 biochemical indices. Key genes and loci associated with metabolism traits were further identified, shared-genetics analysis showed that 29 SNPs (P < 10 -4 ) were associated with three or more traits. After integrating the SNPs related to two or more traits with the GWAS catalog, 31 SNPs were found to be associated with several diseases (P < 10 -8 ). Taking ALDH2 as an example to preliminarily explore its biological function, we also confirmed that rs671 (ALDH2) polymorphism affected multiple traits of osteogenesis and adipogenesis differentiation in 3T3-L1 preadipocytes.
Conclusion: All these findings indicated a network of shared genetics and 29 biochemical indices, which will helpfully understand the genetics participated in biochemical metabolism.
Prevalence and correlates of suicidal ideation in Korean Firefighters: a nationwide study
Authors: Park Heyeon , Kim Johanna Inhyang , Min Beom Jun , Oh Sohee , Kim Jeong-Hyun 
Published: October 2019

Abstract
Background: It is generally known that firefighters are at an increased risk of suicide. However, the prevalence or correlates of suicidal ideation in firefighters have not been thoroughly explained to date. The aim of this study was to measure the 1-year prevalence of suicidal ideation in firefighters and to investigate the correlates of past-year suicidal ideation among the demographic, occupational and clinical characteristics.
Method: A web-based survey was conducted using a self-reported questionnaire. A total of 45,698 Korean firefighters were included for analysis. Prevalence of suicidal ideation in the past year was calculated and its correlates were elucidated using a multivariable logistic regression analysis.
Results: The 1-year prevalence of suicidal ideation was 10.66% in Korean firefighters. Recent traumatic experience, high levels of occupational stress from physical work environment and emotional labor, as well as current duty of officer were significant correlates of suicidal ideation in the previous year, even after controlling the effect of PTSD and depressive symptoms. With respect to demographic factors, female gender, and divorced/separated/widowed marital status were associated with suicidal ideation in the previous year in firefighters.Conclusions: More firefighters experienced recent suicidal ideation than the general population and there were risk factors related to the role of firefighters in Korea. Intervention and policies that manage these risk factors are necessary for the prevention of suicide in firefighters.
CRISPR elements provide a new framework for the genealogy of the citrus canker pathogen Xanthomonas citri pv. citri
Authors: Jeong Kwanho , Muñoz-Bodnar Alejandra , Rojas Nathalia Arias , Poulin Lucie , Rodriguez-R Luis Miguel , Gagnevin Lionel , Vernière Christian , Pruvost Olivier , Koebnik Ralf 
Published: October 2019

Abstract
Background Xanthomonads are an important clade of Gram-negative bacteria infecting a plethora of economically important host plants, including citrus. Knowledge about the pathogen’s diversity and population structure are prerequisite for epidemiological surveillance and efficient disease management. Rapidly evolving genetic loci, such as Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), are of special interest to develop new molecular typing tools. Results We analyzed CRISPR loci of 56 Xanthomonas citri pv. citri strains of world-wide origin, a regulated pathogen causing Asiatic citrus canker in several regions of the world. With one exception, 23 unique sequences built up the repertoire of spacers, suggesting that this set of strains originated from a common ancestor that already harbored these 23 spacers. One isolate originating from Pakistan contained a string of 14 additional, probably more recently acquired spacers indicating that this genetic lineage has or had until recently the capacity to acquire new spacers. Comparison of CRISPR arrays with previously obtained molecular typing data, such as amplified fragment length polymorphisms (AFLP), variable-number of tandem-repeats (VNTR) and genome-wide single-nucleotide polymorphisms (SNP), demonstrated that these methods reveal similar evolutionary trajectories. Notably, genome analyses allowed to generate a model for CRISPR array evolution in X. citri pv. citri, which provides a new framework for the genealogy of the citrus canker pathogen. Conclusions CRISPR-based typing will further improve the accuracy of the genetic identification of X. citri pv. citri outbreak strains in molecular epidemiology analyses, especially when used concomitantly with another genotyping method.