bluuebunny/crossref_metadata_2025 huggingface dataset:
The Curated Food System: A Limiting Aspirational Vision of What Constitutes “Good” Food
Authors: Andress Lauri , Byker Shanks Carmen , Hardison Moody Annie , Prewitt T. Elaine , Kinder Paul , Haynes-Maslow Lindsey
Published: July 2020

We seek to elucidate an aspirational vision for the food system and explore whether the characteristics of such a system inadvertently set unattainable standards for rural, low wealth communities. We apply discourse analysis to the following qualitative datasets: (1) interviews with food experts and advocates, (2) scholarly and grey literature, (3) industry websites, and (4) email exchanges between food advocates. The analysis revealed eight aspirational food system discourses: Production, Distribution, and Infrastructure; Healthy, Organic, Local Food; Behavioral Health and Education; Sustainability; Finance and Investment; Huger Relief; Demand Side Preferences; Romanticized, Community Led Transformations. Study findings reveal that of eight discourses only three encompass the experiences of rural, low wealth residents. This aspirational food system may result in the disempowerment of the needs of rural, low wealth groups; a perpetuation of the failure of groups who will be unable to reach the aspirational food vision; silencing of discourses that might question those that play a role in the inequitable distribution of income while sanctioning discourses that focus on personal or community solutions; and the absence of other policy-based solutions that address issues located within the food system. Further research is needed to inform policies and programs to mitigate food insecurity in rural, low wealth populations.
Recent Experiments Support an Emulsion Origin of Plasma Membrane Domains: Dependence of Domain Size on Physical Parameters
Authors: Allender David W. , Schick M.
Published: July 2020

It is widely, but not universally, believed that the lipids of the plasma membrane are not uniformly distributed, but that "rafts'' of sphingolipids and cholesterol float in a "sea'' of unsaturated lipids. The physical origin of such heterogeneities is often attributed to a phase coexistence between the two different domains. We argue that this explanation is untenable for several reasons. Further we note that the results of recent experiments are inconsistent with this picture. However they are quite consistent with an alternate explanation, namely that the plasma membrane is an emulsion of the two kinds of regions. To show this, we briefly review a simplified version of this theory and its phase diagram. We also explicate the dependence of the predicted domain size on four physical parameters. Among them are the spontaneous curvature of the membrane and its bending modulus and surface tension. Taking values of the latter two from experiment, we obtain domain sizes for several different cell types that vary from 58 to 88 nm.
Substance Use Disorder in the COVID-19 Pandemic: A Systematic Review of Vulnerabilities and Complications
Authors: Wei Yufeng , Shah Rameen
Published: July 2020

As the world endures the coronavirus disease 2019 (COVID-19) pandemic, conditions of 35 million vulnerable individuals struggling with substance use disorders (SUDs) worldwide have not received sufficient attention for their special health and medical needs. Many of these individuals are complicated by underlying health conditions, such as cardiovascular and lung diseases and undermined immune systems. During the pandemic, access to the healthcare systems and support groups is greatly diminished. Current research on COVID-19 has not addressed the unique challenges facing individuals with SUDs, including the heightened vulnerability and susceptibility to the disease. In this systematic review, we will discuss the pathogenesis and pathology of COVID-19, and highlight potential risk factors and complications to these individuals. We will also provide insights and considerations for COVID-19 treatment and prevention in patients with SUDs.
Air Transportation Income and Price Elasticities in Remote Areas: The Case of Brazilian Amazon Region
Authors: Vieira Ventura Rodrigo , Cabo Manoela , Caixeta Rafael , Fernandes Elton , Fernandes Vicente A.
Published: July 2020

The literature, aimed at understanding the income-price elasticity of air passenger demand, bases its analysis on airport movement. The diversity of studies regarding the casualty between air transportation and economic growth are examples. Some studies covering this link, estimate the income-price relationship with the demand considering international traffic. Considering a domestic setting, where this traffic is significant in Brazil, studies related to remote regions are scarce, and the existing ones focus on governmental policies and subsidies. In addition, empirical studies on the theme consenter themselves in developed regions, such as Europe, North America, and Australia. For Brazil, where we find the Amazon region, there are no empirical researches. This paper analyses the price-income elasticity of the demand regarding domestic passengers in air links from remote cities of the Brazilian Amazon. This study uses panel data regression analysis method on a database of domestic scheduled flights of Brazil´s National Civil Aviation Agency. The results show that air passengers involving remote region flights present a lower sensitiveness regarding local income and airline´s price variations than those in flights among capitals. The higher difference is in income-elasticity of the remote city of origin, which is lower than that of the air traffic among capitals.
Wheat Yield Forecasting Based on Landsat NDVI and SAVI Time Series
Authors: Adeniyi Odunayo David , Szabo Andrea , Tamás János , Nagy Attila
Published: July 2020

Due to increase demand of food grain in the world, assessment of yield before actual production is important in making policies and decisions in agricultural production system. For a large area, forecast models developed from vegetation indices derived from remote sensing satellite data possesses the potential to give quantitative and timely information on crops over large areas. Different vegetation indices are being made used for this purpose, however, their efficiency in estimating crop yield is needed to be certainly tested. In this study, wheat yield forecast was derived by regressing ground truthing yield data against time series of spatial vegetation indices for the 2013 to 2019 growing seasons. These spatial vegetation indices derived from Landsat 8 image data: Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) were compared to evaluate the most appropriate index that performs better in forecasting wheat production at Karcag, Kunhegyes and Ecsegfalva settlements in Jász-Nagykun-Szolnok county, in the Northern Great Plain region of central Hungary. The best time for making wheat yield prediction with Landsat 8- SAVI and NDVI was found to be the beginning of ripening period (160th day of the year) with higher correlation between the vegetation indices and the wheat yield. The validation results revealed that the model from SAVI provides more consistent and accurate forecasts yield compared to NDVI. The SAVI model forecast yield for the validation years, 2018 and 2019 were within 6.00% and 4.41% of the final reported values while that of NDVI model were within 8.31% and 6.27%. Nash-Sutcliffe efficiency index is positive with E1= 0.99 for the model from SAVI and for NDVI, E1=0.57, which connote that the forecasting method developed and evaluated performs acceptable forecast efficiency.
A Rapid Extraction Method of Regional Scale Agricultural Disasters Based on Google Earth Engine
Authors: Liu Zhengrong , Liu Huanjun , Luo Chong , Yang Haoxuan , Ju Yongchol , Guo Dong
Published: July 2020

Remote sensing has been used as an important tool for disaster monitoring and disaster scope extraction, especially for the analysis of temporal and spatial disasters patterns of large-scale long time series. In order to find out a rapid and effective method to monitor disaster in a wide range, based on the Google Earth Engine cloud platform, this study used MODIS vegetation index products of 250 meter spatial resolution synthesized in 16 days during the year 2005-2019 and three kinds of disaster monitoring and scope extraction models are proposed: normalized vegetation index median time standardization (RNDVI_TM(i)) model, the normalized vegetation index median phenology Standardization(RNDVI_AM(i)(j)) model, normalized vegetation index median spatiotemporal Standardization (RNDVI_ZM(i)(j)) model. The optimal threshold of disaster extraction for each model in different time phases was determined by Otsu method, and the extraction results were verified by Medium resolution image and ground measured data of the same or quasi-same period. Finally, the disaster scope of cultivated land in Heilongjiang province from 2010 to 2019 was extracted and the temporal and spatial pattern of disasters was analyzed based on the meteorological data. It shows that the three above-mentioned models have high disaster monitoring and range extraction capabilities with the verification accuracy of RNDVI_TM(i) 97.46%, RNDVI_AM(i)(j) 96.90%, and RNDVI_ZM(i)(j) 96.67% respectively. The spatial and temporal distribution of disasters is consistent with the disaster of the insured plots and meteorological data in the whole province. Meanwhile, it turns out that different monitoring and extraction methods are used in different disasters, among which wind hazard and insect disasters often need to be delayed for 16 days to observe. Each model also has various sensitivity and applicability to different disasters. Compared with other methods, this method is fast, and convenient, which allows it to be used for large-scale agricultural disaster monitoring and is easy to be applied into other research areas. The research provides a new idea for large-scale agricultural disaster monitoring.
All-$t_{2g}$ Electronic Orbital Reconstruction of Monoclinic MoO$_2$ Battery Material
Authors: Craco Luis , Leoni Stefano
Published: July 2020

Motivated by experiments, we undertake an investigation of electronic structure reconstruction and its link to electrodynamic responses of monoclinic MoO$_2$. Using a combination of LDA band structure with DMFT for the subspace defined by the physically most relevant Mo $4d$-bands, we unearth the importance of multi-orbital electron interactions to MoO$_2$ parent compound. Supported by a microscopic description of quantum capacity we identify the implications of many-particle orbital reconstruction to understanding and evaluating voltage-capacity profiles intrinsic to MoO$_2$ battery material. Therein, we underline the importance of the dielectric function and optical conductivity in the characterisation of existing and candidate battery materials.
Current Challenges of Cold Brew Coffee – Roasting, Extraction, Flavor Profile, Contamination, and Food Safety
Authors: Kwok Raven , Lee Wee Ting Kenny , Schwarz Steffen , Claassen Linda , Lachenmeier Dirk W.
Published: July 2020

Cold brew coffee has emerged as a new trend during the last decade. However, “cold brew” is an extraction style of ground roasted coffee with water at less than body temperature (typically 8°C or room temperature) rather than a beverage per se. Cold brew extraction poses several challenges including the need of specific optimization depending on the multivariate influences of coffee variety and processing, roast degree, grinding, dosage, water composition, turbulence, brew system (drip, immersion etc.), time and temperature. While cold brew is typically characterized by a floral sweetness, over-extraction may lead to abundant acidity and bitterness. To avoid this, an extraction degree of 70% was suggested using rather shorter times (i.e. 2 h at 15°C with 80 g/L coffee with optimized medium roast profiles). Due to the lack of sterilizing temperatures during preparation, cold brew is special in the coffee sector because hygiene and food safety aspects pose specific challenges for food industry. To avoid microbiological contamination and spoilage, cold brew should be as freshly prepared as possible and shelf-life should be minimized.
Data Driven Analytics for Personalized Medical Decision Making
Authors: Melnykova Nataliia , Shakhovska Nataliya , Gregus Michal , Melnykov Volodymyr , Zakharchuk Mariana , Vovk Olena
Published: July 2020

The study was conducted on applying machine learning and data mining methods to personalizing the treatment. This allows investigating individual patient characteristics. Personalization is built on the clustering method and associative rules. It was suggested to determine the average distance between instances for optimal performance metrics finding. The formalization of the medical data pre-processing stage for finding personalized solutions based on current standards and pharmaceutical protocols is proposed. The model of patient data is built. The paper presents the novel approach to clustering built on ensemble of cluster algorithm with better than k-means algorithm Hopkins metrics. The personalized treatment usually is based on decision tree. Such approach requires a lot of computation time and cannot be paralyzed. Therefore, it is proposed to classify persons by conditions, to determine deviations of parameters from the normative parameters of the group, as well as the average parameters. This made it possible to create a personalized approach to treatment for each patient based on long-term monitoring. According to the results of the analysis, it becomes possible to predict the optimal conditions for a particular patient and to find the medicaments treatment according to personal characteristics.
The COVID-19 Spread in India and Its Dependence on Temperature and Relative Humidity
Authors: Vinoj Velu , Gopinath Nandini , Landu Kiranmayi , Behera Bijayini , Mishra Baijayantimala
Published: July 2020

The coronavirus disease 2019 (COVID-19), the pandemic is an unprecedented health emergency never seen in the recorded history of humankind due to its sheer scale, rapid spread, and subsequent shock to the global economy. The past respiratory viral pandemics of the 21st century (SARS-CoV-2 in 2003, Influenza AH1N1 in 2009) have revealed seasonality in environmental factors to play a role in the dynamics of their spread. Here, we report the observed state-level relationship between environmental factors such as temperature (T), relative humidity (RH), specific humidity (SH), and solar radiation (SR) on the COVID-19 spread over the Indian region. The results show that T and RH have a significant impact on the disease growth rate and doubling time. Every degree rise in temperature corresponds to a 0.99 % decrease in the number of cases and an increase in doubling time by ~ 1.13 days implying a slowing down of spread. A similar analysis for RH reveals that more moisture leads to a higher growth rate and reduced doubling time. Lower SH and higher surface-reaching SR are found to reduce the spread and increase the doubling time similar to that of temperature. The range of average state-level T (RH) encountered during this period was between 24 and 35oC (30 and 87%) which implies that environmental impact is still effective at all these T (RH) and is not limited to specific T (RH) ranges. The progression of the season towards monsoon, post-monsoon, and thereafter winter with a continuous reduction in temperature will prove a major challenge for health workers and policymakers attempting to enforce mitigation and control measures.
Impact of COVID-19 on Performance of Pakistan Stock Exchange
Authors: Ahmed Shehar Yar
Published: July 2020

The objective of this study is to determine the impact of COVID-19 on the performance of Pakistani Stock Market. This study uses the data of COVID-19 related positive cases, fatalities, recovers and the closing prices of PSX 100 index of the first half of 2020. The findings of the study suggest that only COVID-19 recoveries are influencing the performance of the index and the daily positive cases and fatalities are insignificantly related to the performance. Further studies can be performed by incorporating other variables such as economic growth, interest rate and inflation rate along with the COVID-19 related variables at a cross-country level.
Montmorillonite K10: An Efficient Organo- Heterogeneous Catalyst for Synthesis of Benzimidazole Derivatives
Authors: Bonacci Sonia , Iriti Giuseppe , Mancuso Stefano , Novelli Paolo , Paonessa Rosina , Tallarico Sofia , Nardi Monica
Published: July 2020

The use of alternative synthetic methods, in the face of traditional processes that do not conform to the principles of Green Chemistry, represent a problem in the pharmaceutical industry. The procedures for the synthesis of benzimidazole derivatives have become a focus in synthetic organic chemistry, as they are building blocks of strong interest for the synthesis of compounds with pharmacological activity. Various benzimidazole derivatives have found very strong application in medicine and their synthesis is reported in the literature. A simple and environmental Montmorillonite K10 (MK10) catalyzed method for the synthesis of benzimidazole derivatives has been developed. The use of MK10 as heterogeneous catalysis provides various advantages in terms of yields, in the work up procedure of the reaction, selectivity and the possible recycle of catalyst without waste formation. The reactions were carried out in solvent free condition and in short reaction time using an inexpensive and environmentally friendly heterogeneous catalysis and it has been shown that the reaction process is applicable in the industrial field.
The Good among the Bad and the Ugly: The Unsung Heroes in ER Stress, GPCR and EMT
Authors: Gundamaraju Rohit , Lu Wenying , Eri Rajaraman
Published: July 2020

The majority of cellular responses to external stimuli are mediated by receptors such as G protein-coupled receptors (GPCRs) and systems including endoplasmic reticular stress (ER stress). Since GPCR signalling is pivotal in numerous malignant pathologies, they are targeted by a number of clinically used drugs. Cancer cells often negatively modulate GPCRs in order to survive, proliferate and to disseminate. Similarly, numerous branches of the unfolded protein response (UPR) act as pro-survival mediators and are involved in promoting cancer progression via mechanisms such as epithelial mesenchymal transition (EMT). However, there are a few proteins among these groups which impede deleterious effects by orchestrating the pro-apoptotic phenomenon and paving a therapeutic pathway. The present review exposes and discusses such critical mechanisms and some of the key processes involved in carcinogenesis.
Mechanism of Vascular Endothelial Dysfunction Causing Arteriosclerosis: Vascular Endothelial Glycocalyx
Authors: Yamaoka-Tojo Minako
Published: July 2020

In atherosclerosis patients, vascular endothelial dysfunction is commonly observed with damage of vascular endothelial glycocalyx, an extracellular matrix-bound to and encapsulating the endothelial cell lining the blood vessel wall. Unfavorable lifestyle; smoking and physical inactivity, also induces glycocalyx degradation. Moreover, the vascular endothelial glycocalyx is damaged by various unfavorable disease conditions like as dehydration, acute infectious disease, trauma, sepsis, ARDS, Kawasaki disease, preeclampsia, gestational diabetes mellitus, hypertension, diabetes, chronic kidney disease, atherosclerosis, stroke, dementia, microvascular angina, acute coronary syndrome, and heart failure. The vascular endothelial glycocalyx has been shown to be important not only as a physical cytoprotective barrier for vascular endothelial cells but also as a mechanism that regulates intracellular cell signaling. Therefore, vascular endothelial glycocalyx has great potential to explore new strategies for assessing the benefit conditions of our healthy vasculature.
Trends in Antibiotic Resistance of Major Uropathogens
Authors: AL-Khikani Falah Hasan Obayes
Published: July 2020

Around the world, there is no population clear from urinary tract infection (UTI), particularly among women. UTI is considered the most predominant bacterial infection. This study aimed to detect the incidence of the most common major uropathogens in patients severe from urinary tract infection with antibiotic sensitivity tests that assist urologist doctors for appropriate antimicrobial empirical therapy.Methods: This study was carried in a private laboratory in Babil city, Iraq from May 2019 to May 2020. Totally 70 individuals suffering from clear symptoms of UTI, as well as, 20 healthy persons participated in this study as a control group. Then, the standard microbiological methods carried out to isolate and identify bacterial species. Antimicrobial susceptibility tests were performed using different antimicrobial discs by applying the Kirby–Bauer disc diffusion method.Results: Totally, 90 specimens were obtained from them 20 control group, 19 with no growth, and 51 patients with bacterial growth distributed as 43 (83%) females and 8 (17%) males. E. coli were the most common predominant organisms. All isolates were showed a high rate of resistance to evaluated cephalosporins 100% and 82% to cefotaxime and ceftriaxone respectively, while very low resistance recorded in Aminoglycosides 20% and 13% to Gentamicin and amikacin respectively. Most age group infected with UTI was 21-40 years old.Conclusion: The current study showed an increasing burden of urinary tract infection caused by various bacteria implicated in UTI that causes changeable sensitivity to various antimicrobial agents. Therefore, in clinical use appropriate medications should be selected based on the data obtained from antimicrobial susceptibility tests.
PERAN PROMOSI PENJUALAN MELALUI INSTAGRAM TERHADAP PENJUALAN SAYUR ORGANIK DI PO. SAYUR ORGANIK MERBABU (SOM)
Authors: Andes Rafael Jeksen , Sunaryanto Lasmono Tri
Published: July 2020

AbstrakPO. Sayur Organik Merbabu, dikenal sebagai SOM, adalah salah satu perusahaan perseorangan yang bergerak di bidang pertanian sayur organik yang terletak di dekat Kota Salatiga Jawa Tengah. Instagram adalah satu media sosial yang digunakan oleh SOM dalam pemasaran produk sayur organiknya. Penelitian ini bertujuan: 1) untuk mengetahui peranan promosi penjualan produk sayur organik melalui Instagram di SOM; dan 2) untuk mengetahui tanggapan kosumen mengenai peran promosi penjualan melalui Instagram di SOM. Pemilihan lokasi penelitian dilakukan secara sengaja (purposive) dengan pertimbangan bahwa SOM memiliki usaha penjualan produk melalui instagram. Penelitian ini menggunakan metode kualitatif dengan pengamatan pada peranan promosi penjualan dan tanggapan konsumen terhadap promosi penjualan melalui Instagram. Hasil penelitian menunjukan promosi melalui instagram mampu meningkatkan penjualan sayur organik. Konsumen menilai bahwa instagram lebih mudah dan praktis dalam menyediakan informasi produk yang diinginkan. Implikasi kebijakan dari penelitian ini diperlukan peran perusahaan dalam pengelolan Instagram agar lebih efektif dan mendukung pemasaran sayur organik.Kata kunci: Instagram, Media Sosial, Penjualan, Promosi, SOM.
Assumptions and risks of a dystopian constitutionalism: reflections based on Philip K. Dick
Authors: Pinheiro Douglas Antônio Rocha
Published: July 2020

This article is based on the Law and Literature methodology. It analyzes the shortage of contemporary utopian narratives. The object of analysis are the characteristics of constitutionalism in light of literary categories from dystopian literature – especially regarding Philip K. Dick’s “Minority Report”. Thus, this paper examines to what extent the contemporary paranoia – both subjective and systemic – has strengthened court decisions based on pretentious illicit conspirations, as well as institutional solutions justified by the prospective use of automated processes, supposedly neutral and efficient. This paper also discusses the incorporation of a certain time paradigm of contemporary cultures, which is linear and unidirectional, with a rigid differentiation between past, present and future. Such conception creates temporal ghettos, besides imposing a dominant social rhythm that frustrates the very protective trait of constitutionalism, regarding the life projects of vulnerable minorities. Thus, this work reflects upon the fragility of the argumentative integrity seen in certain judicial sentences which are justified by consequentialist lines of thought, and which, by projecting future catastrophic effects for possible decisions, end up legitimizing opposite outcomes. In conclusion, the need for overcoming fear as the fundamental feeling in the social, institutional power is discussed.
Successful Strategy for Waterflooding Project Implementation in an Extra Heavy Oil Field
Authors: Niño Luz , Bonilla Fernando , Gil Layonel , Henao William , Reina John , Jimenez Edith , Vivas Pedro
Published: July 2020

Chichimene is the third most important field of Colombia, with an original oil in place of USD 3.1 million barrels, producing an extra heavy oil of around 8 API, characterized by high viscosity and reduced mobility. The estimated recovery factor was around 3%, and the reservoir pressure was declining drastically; because of this, it was necessary to urgently implement an enhanced oil recovery project, since without immediate intervention, the reservoir and field production would be seriously affected.

A thorough screening process was performed among diverse EOR options, and waterflooding was selected as the best alternative for maintaining reservoir pressure and increasing the recovery factor. The main challenge was to have a rapid implementation for the entire reservoir, considering that this region has reported community issues derived mainly from water management disagreements and inconformity with stringent labor requirements. Additionally, lengthy environmental permits and high deployment expenditures were factors that affected field development plans.

The research of an effective technology for the field-specific conditions and a low deployment cost indicated dumpflood as the best alternative, since it enabled injection from a deeper water formation to an upper production target zone through a smart BHA, substantially reducing injection facilities investment and operational costs. Time savings were identified, eliminating additional requirements for environmental permits. The main concern was that this technology has never been implemented for extra heavy oils.

Simulations in a steady state simulator validated the feasibility of the dumpflood technique in the field. Models of the production and injection zones evidenced the pressure needs and the necessary BHA adjustments to meet the target rates and to define the completion model with the specific equipment to perform the operation.

Implementation started in the South West area of the field and was deployed with three waterflooding patterns in a record time of three months. After nine months of operation, the reservoir pressure augmented in the surrounding wells, and the failure indicator of the electrical submersible pumps was reduced by a factor of 20%. As a major milestone, the average field production climbed by approximately 10,000 bbl/d. Considering the successful results, the project was extended to 20 waterflooding patterns in other areas of the field, the waterflooding project was approved and sanctioned one year after the pilot startup and therefore over 20,000 barrels of oil equivalent were incorporated to the proved reserve balance.
A New Approach for Geomechanical Evaluations with Modified Pickett Plots
Authors: Malaieri Mohammadreza , Matoorian Raya , Aguilera Roberto
Published: July 2020

A Pickett plot is a powerful graphical technique for petrophysical analysis of well logs, which was developed initially to represent Archie's equation visually. Pickett plots rely on pattern recognition on a log-log scale observable on a set of porosities and the corresponding true resistivities taken from well logs. The analyses of these plots have been used in the past, primarily for the determination of water saturation. However, throughout the past years, Pickett plots have been extended and modified for the evaluation of other reservoir parameters of interest, such as permeability, process/delivery speed, bulk volume water, and pore throat apertures.

In some recent works, applications of the Pickett plot have been extended from representing only a snapshot on time to describing and explaining several millions of years of burial, compaction, maturation trajectories, and petroleum generation. The word ‘petroleum’ as used in this paper includes oil, gas, and natural gas liquids.

In this study, the Pickett plot has been modified and extended to include geomechanical parameters such as Vp/Vs, Poisson's ratio, Young's modulus, Shear modulus, bulk modulus, friction angle and Unconfined Compressive Strength (UCS). A better understanding of these parameters helps to minimize risks associated with drilling, stimulation, and wellbore stability problems. Geomechanical characterization is vital to understand fracture creation and propagation. Hydraulic fractures are more likely to be generated in brittle zones with lower tensile strength, lesser Poison's ratio, and higher Young's modulus.

Mechanical properties are usually measured in laboratory experiments such as Triaxial Compression Tests carried out on core samples. But cores are not always available for testing; therefore, the original contribution of this paper is the construction of a modified Pickett plot that can help to perform quick and reasonable evaluations of geomechanical properties while at the same time carrying out standard petrophysical analysis of petroleum reservoirs. This type of integrated petrophysical-geomechanical interpretation on a single plot is not currently available in the literature.
Ultra-High Density Oil-Based Drilling Fluids and its Applications in Ultra-Deep Petroleum Systems
Authors: Li Qinghui , Li Shaoxuan
Published: July 2020

Global energy demand has driven petroleum industry to develop hydrocarbon resources from extremely harsh formations. Ultra-high density drilling fluids are critical to successful drilling and completion practices in all of these wells. In this paper, potential weighting materials were systematically evaluated and screened to accomplish an ultra-high density oil-based drilling fluid system (19.62 to 22.12lb/gal) aimed to utilize in ultra HPHT conditions (>30000psi and >410°F). Potential high-density weighting materials were evaluated. Properties (pure density, particle size/distribution, surface area etc.) were evaluated and compared. Special treatment was conducted to optimize properties of weighting materials. HPHT filtration tests under static and dynamic conditions were conducted at higher than 410°F and 300 psi. Real cores with an average porosity of 19% and an average permeability of 50 md were used in the filtration tests. Rheological properties, sag tendency, the volume of filtrate, and the filtrate cake characterization was measured before and after heating at 410°F for 16 hours.

Results revealed that ultra-micro manganese and ilmenite complex after suitable surface treatment could act as an ideal weighting material than ultra-pure barite or other materials, which could fail in rheology and sag measurement with such high temperature and density. Viscosity and filtration analysis confirmed the stability and reliability of this novel ultra-high density oil-based drilling fluid.

This study developed a challenged drilling fluid system under critical conditions, as well as established a systematical laboratory evaluation and screening procedure of weighting materials and contributed recommendations on how to utilize it in the fields.
Migration of Liquid Hydrocarbons in Organic-Rich Reservoirs Based on Geochemical and Well Log Analysis Explained with the use of New Practical Model
Authors: Piedrahita Jaime , Aguilera Roberto
Published: July 2020

This paper develops a new conceptual liquid-hydrocarbons migration model for practical application in organic-rich mudstone reservoirs. The method uses a combination of well log formation evaluation data, micro-resistivity image logs, nuclear magnetic resonance, and geochemical measurements obtained from either drill-cuttings or core data.

In the method proposed in this paper, organic matter (OM) geochemical indicators from organic petrography (thin sections), vitrinite reflectance, TOC from Leco analyzer, Rock-Eval pyrolysis including S1, S2, and Tmax are integrated with triple-combo and NMR logs so that both lean and organic-rich intervals can be identified. The addition of natural fracture intensity to the interpretation package makes the methodology quite unique. After applying cut-offs for each individual parameter, two types of migrations are identified that could take place in these source-rock reservoirs: primary and secondary migration.

The model is applied in a wildcat vertical well that penetrated several stacked organic-rich mudstones. The formation gross thickness of the evaluated section is around of 2800 ft-TVD divided into six main formations composed mainly by siliciclastic minerals with a moderate carbonate content, and low presence of clay minerals. The source-rock reservoirs penetrated by the well can be sub-divided into (1) naturally-fractured, (2) tight and (3) hybrid reservoirs. Reservoirs in sub-division (1) are very important because they might be able to produce oil without the need of hydraulic fracturing. Reservoirs in sub-division (2) have natural fractures but their scale is very small to allow any oil production. Consequently, they must always be hydraulically fractured. Reservoirs in sub-division (3) might or might not need hydraulic fracturing.

Intervals with high organic carbon content, S1, oil saturation index, and geochemical index but low natural fracture intensity indicate tight reservoirs, and they likely correspond to the hydrocarbon source that charged the juxtaposed naturally fractured or hybrid reservoirs. On the other hand, several intervals that present poor TOC, are highly brittle and naturally-fractured, and are connected with tight organic-rich intervals. Thus, the potential of these naturally fractured intervals to produce oil is quite significant.

The novelty of the method developed in this paper permits analyzing primary and secondary migration in the source rock. The method further permits identifying the type of reservoir (naturally fractured, tight and/or hybrid) penetrated by the exploratory wells. This allows ranking the most prospective intervals as well as optimum landing zones for future horizontal or geosteered wells to be drilled in neighboring areas.
An Open-Source Enabled Drilling Simulation Consortium for Academic and Commercial Applications
Authors: Losoya Enrique Zarate , Gildin Eduardo , Noynaert Samuel F , Medina-Zetina Zenon , Crain Tim , Stewart Shaun , Hicks Jimmy
Published: July 2020

Simulation of drilling processes involves the seamless integration of strongly coupled physics, numeric, and economic models. Operators desire advanced drilling simulation software that can mimic reality and yet be practical for daily operations. At the same time, academic researchers are devoting time and effort to develop robust and accurate models of every module of an integrated drilling environment but are challenged with translating their original contributions into the operational setting. We seek to solve both of these issues through a distinctive collaboration consortium based on an open-source paradigm. We describe and propose an advanced drilling simulation developed through a joint industry consortium at Texas A&M University. The simulator provides free access to sophisticated and reliable drilling dynamics solvers. This includes drill string dynamics, torque and drag analysis, geologic modeling, hydraulics, and wellbore pressure modeling, visualization, and operator interfaces. The simulator is written in C++ and is built on top of high-performance open source libraries that leverages parallel computing, GPU acceleration, multibody, and computational fluid dynamics solvers as well as other tools (see figure for further details). We will assist industry and academic users to employ our open-source tool. In addition, we will help said parties further develop our framework into proprietary and protected business software via the addition of custom functionality. The simulator core was successfully developed and has been used to model horizontal drilling, while providing near real-time performance. The framework has been used in several applications successfully, including modeling shallow horizontal jetting, rock drilling, and steering; as well as reconstructing spatial data from high fidelity downhole signals for borehole evaluation, and the development of improved downhole navigation algorithms. We believe that a collaborative development effort between academia and industry will bring solutions to complex modeling needs faster and more economically than any individual endeavor. To this end, the authors will also show how one can partner with Texas A&M University to obtain access to the open-source enabled drilling simulation framework and platform to collaborate, improve and create solutions for new and existing problems.
New Method for Overburden Modeling to Improve Geopressures Calculations
Authors: Velázquez-Cruz David , Espinosa-Castañeda Gustavo , Morquecho-Robles Adalberto
Published: July 2020

This paper showing that using rock-density measurement from well-logs affect the calculation of overburden stress because "environmental effects" caused by borehole conditions, overpressures, gas content, high mud filtrates, formation fluid saturation and rock mineralogy. Those effects influence the rock-density measurements and consequently both the overburden stress and geopressures computations; furthermore, the lack of rock-density well-logs in the first drilling stages also affect the overburden stress determinations. However, we consider that the most important bias-effect in the overburden stress calculation is that the overburden must be determined exclusively using the rock-density due to normal compaction of sediments. Hence, we are proposing a new method and model to compute the overburden stress that utilize a power law approach to reproduce rock density values instead to use log-density measurements. The new method is based on the theory of consolidation of clays described by Terzagui and Peck in 1948 which considers that rock-porosity reduction because of compaction when sediments burial increases. This rock-porosity reduction or rock-density increment can be modeled by a power law approach and use its results to calculate overburden instead rock-density measurements from well-logs. Here, we describe how establish the normal compaction trend for rock-density and its integration into overburden equation. This modified overburden model is showed and some examples are presented to permit readers to use the method with their own data. The examples compare the overburden stress calculated with new method against those using rock-density measurements from well-logs. The results show better overburden estimations using the power law model and how the use of rock-density readings from well-logs impact in the geopressures results because mislead of the overburden stress. The results allow to conclude that the overburden stress must be calculated using rock-density due to normal compaction of sediments and avoid the use of density-log readings that are influenced by "borehole environmental effects".
Application of Torque and Drag Models to Prevent Real-Time Operational Problems
Authors: Rodrigues G. da Silva Fabio , De Souza Cruz Marcelo , Newmar Donatti Carlos , P. Moreira de Mello Otávio , Leibsohn Martins Andrá , Gandra Percy Joseir , Max de A. Panisset Curt
Published: July 2020

Real-time drilling data is an essential tool to increase performance and operational safety, especially when operating in challenging environments. In this scenario, it is highly attractive to use new tools that can anticipate possible risks to the operation, aiding in decision making in order to guarantee operational efficiency and safety. The present work aims to present the new technologies developed in a real-time monitoring software (GANDELMAN ET AL., 2013), which automatic diagnosis drilling problem, from the calculations of loads alongthe drill string and the contact of the column with the borehole wall.

Torque and drag models are used to support well planning. The aim is to ensure the feasibility of theoperation and to assist in the prediction and prevention of operational problems during drilling. Directional wells require even more attention, since, as their inclination increases, additional forces are observed due to the enhanced contact of the drill string with the borehole wall.

Since these forces are cumulative, the deeper the well, the larger will be the contact forces and, consequently, the torque and drag values. A comprehensive torque and drag model was implemented to estimate the wear level on the casing, in real-time, due its contact with the drillstring. The purpose of this development is to automatically warn when the calculated wear approaches the expected and / or permitted wear.

Still using the T&D model implemented in the real-time monitoring software (GANDELMAN ET AL., 2013), a module was developed for a more accurate detection of the tubular element that is passing through each of the BOP (blowout preventer) rams when drilling from floating vessels. The main objective of this new technology is to assist the operation in a possible emergency disconnection. The main focus would be to precisely define the moment to actuate a RAM, minimizing the risk of reaching a non-shearable component of the drillstring. Therefore, a logic of tracking each element of the column in front of the BOP rams was created, which takes into account the effect of axial elongation due to real-time tension and compression.
Incorporating Biot Poroelastic Coefficient on Pickett Plots
Authors: Olusola Bukola K. , Aguilera Roberto , Cinco Ley Heber
Published: July 2020

A method is presented for incorporating Biot poroelastic coefficient on Pickett plots. The method allows integration of petrophysical parameters such as water saturation, porosity and permeability with geomechanics through Biot coefficient.

Pattern recognition in Pickett plots have been used historically for quick petrophysical evaluation, particularly for determination of water saturation. The procedure involves a crossplot of porosity vs. true resistivity on log-log coordinates. The method presented in this paper allows determination of Biot coefficient from the Pickett plot in addition to determination of standard petrophysical parameters. The method uses a correlation developed for estimating Biot poroelastic coefficient as a function of process speed (the ratio of permeability and porosity) and pore throat aperture (rp35).

Results indicate that the proposed Pickett plots permits quick simultaneous estimation of different parameters of interest for a given interval including water saturation, porosity, permeability, pore throat aperture and Biot coefficient. The Biot coefficient correlation works for various lithologies including limestone, sandstone, shales, source rock, marble, granite, unconsolidated and oil sand reservoirs. Thus, the method has application in the case of both conventional and unconventional reservoirs.

Key observations based on the proposed Pickett plot include: (1) there is a general tendency for Biot coefficient to decrease as water saturation increases, (2) there is a general tendency for Biot coefficient to increase as porosity, permeability, process speed and pore throat aperture (rp35) increase.

It is concluded that the integration of petrophysical parameters and Biot coefficient provides a new valuable tool to assist in the solution of petroleum engineering problems such as hydraulic fracturing and estimation of in-situ closure stress on proppant.

The novelty of this work is the development for the first time of an integrated Pickett plot that incorporates petrophysical analysis and Biot poroelastic coefficient.
Bayesian Deconvolution of Rate Pressure Data Using Regularizing Priors
Authors: Ravikumar Arjun , Lee John
Published: July 2020

The constant pressure production behavior of a reservoir system is a key component of reservoir diagnostics and production forecasting. Rate-pressure deconvolution is a technique that uses production data from variable rate-variable pressure production to calculate this constant pressure behavior. Regularization techniques are used to mitigate the instability inherent in the deconvolved result. In this work, we describe rate-pressure deconvolution in the time domain within the framework of Bayesian statistics, and obtain the deconvolved result by interpreting the posterior distribution.

We strategically parametrize the problem in terms of derivatives of the deconvolved solution to exploit the monotonic nature of the constant pressure behavior. We achieve regularization of the deconvolved solution using regularizing priors instead of conventional regularization methods. The regularizing prior is a probability distribution of the solution constructed using the prior knowledge of reservoir and fluid parameters from a variety of sources such as fluid samples, analogs, experience, and common sense. Finally, we obtain the deconvolved result using Markov chain Monte Carlo methods.

We show that conventional regularizing methods are a subset of the regularizing prior approach, by proving that, for specific choices of the prior, our method is equivalent to conventional regularization techniques. We establish the validity of our method using synthetic data with noise added. We analyze the sensitivity of the solution to the regularizing prior and discuss procedures for choosing an appropriate prior. We discuss methods to make the inference robust to outliers in the data. Finally, we demonstrate our deconvolution algorithm with field cases.

The constant pressure behavior of a reservoir is crucial to diagnostic and forecasting methods such as flow regime identification and decline curve analysis. Existing rate-pressure deconvolution techniques have no mechanism for including prior knowledge of the reservoir in the solution. Our framing of the problem incorporates this knowledge into the problem systematically. Our Bayesian approach also enables us to infer the uncertainty of the deconvolved solution directly from the posterior distribution.