bluuebunny/crossref_metadata_2025_split huggingface dataset:
Revival of an Offshore Gas Field: Case Study of a Fractured Basement Reservoir, PY-1
Authors: Kumar Arun , Srinivasan V , Kavle R , Sharma R , Gariya B. C. , Panda D 
Published: April 2019

Abstract
PY-1 is one of the few fields in India producing hydrocarbons from Fractured Basement Reservoir. The field was developed with nine slot unmanned platform with gas exported through a 56 km 4" multiphase pipeline to landfall point at Pillaperumalnallur. Field was put on production in November 2009 with three extended reach wells.
The production performance of the field had some surprise and declined earlier than expected. As a result, based on the conclusions drawn from an integrated subsurface study, a two wells re-entry campaign to side track wells Mercury and Earth was planned to be executed in Q1 2018.
The objectives of this paper are twofold:Review the production performance of a granitic basement gas field and share learnings which may be useful for similar fields being developed elsewhere.Share the fit-for-purpose modelling workflow adopted to identify the opportunities and estimate reserves

Methods, procedures, process
The workflow consisted of following:Key uncertainties impacting GIIP and recovery were ascertained through subsurface and production data analysisAnalytical reservoir engineering tools such as material balance was used to estimate GIIP from production and pressure analysis. Importance of having PDG installed in offshore wells with unmanned platforms are highlighted.The uncertain petrophysical parameters such as porosity and was constrained based on GIIP estimates from material balanceProsper models were used to understand and predict the well performance and optimal tubing size to avoid liquid loadingFit-for-purpose simulation models were constructed to quantify impact of key uncertainties on production forecast and recovery
In order to mitigate the operational risks, drilling services were outsourced as a turnkey project to an industry leading service provider.
Automated Core Fracture Characterization by Computer Vision and Image Analytics of CT Images
Authors: Antle Ryan 
Published: April 2019

Abstract
Computer vision (CV) techniques were applied to X-ray computed tomographic (CT) images of reservoir cores to evaluate their potential for rapidly identifying fractures and other lithologic/geologic characteristics. The analyses utilized feature-labeled CT cross sectional images, themselves distributed submillimeter voxels of density- and atomic number-sensitive CT Numbers, as inputs to a Fully Convolutional Neural Network (FCN) for semantic segmentation of reservoir core features. In FCN, an image is interrogated using a series of sliding windows at various scales to create weighted filters to reduce error between classes in training images. These networks of filter layers were used to assign probabilities of classes, which were upscaled back to the original image dimensions resulting in probabilistic class assignments onto each pixel. FCN model accuracy, defined by its ability to replicate manually-assigned labels in the raw (unannotated) training image stack, was at least 80% and generally improved with the size of the training set. Once the labels were assigned, the underlying feature frequency, orientation, and size were measured in 3D volume reconstructions using algorithms modified from standard image analysis software. This method allowed users to endow a classification model with subject matter knowledge for further, autonomous label prediction. Thus, while initial image annotation was labor intensive, subsequent images were rapidly classified once the model was built. The classified labels were analyzed for abundance, orientation, and size of fractures were calculated to characterize spatial information of these features. FCN combined with fracture labeling improved knowledge capture and automation of fracture identification. Models trained by high quality 3D datasets can greatly reduce the time needed to describe subsequent core. The method demonstrated is not limited to fractures, other lithologic/geologic features could be trained using the same method, which may result in additional efficiencies.
Gas Huff and Puff Process in Eagle Ford Shale: Recovery Mechanism Study and Optimization
Authors: Wang Leizheng , Yu Wei 
Published: April 2019

Abstract
US unconventional resource production has developed tremendously in the past decade. Currently, the unconventional operators are trying many strategies such as refracturing, infill drillings and well spacing optimization to improve recovery factor of primary production. They are also employing big data and machine learning to explore the existed production data and geology information to screen the sweet spot from geology point of view. However, current recovery factor of most unconventional reservoirs is still very low (4~10%). A quick production rate decline pushes US operator to pursue gas EOR for unconventional reservoirs, lifting the ultimate recovery factor to another higher level. The goal of this work is to improve oil recovery by implementing gas Huff and Puff process and optimizing injection pattern for one of the US major tight oil reservoirs - Eagle Ford basin. Gas diffusion is regarded as critical for gas Huff and Puff process of tight oil reservoirs. Utilizing the dual permeability model, gas diffusion effect is systematically analyzed and compared with the widely used single porosity model to justify its importance. Transport in natural fractures is proved to be dominated recovery mechanism using dual permeability model. Uncertainty studies about reservoir heterogeneity and nature fracture permeability are performed to understand their influences on well productivity and gas EOR effectiveness. Moreover, three alternative gas injectant compositions including rich gas, lean gas and nitrogen are investigated in gas Huff and Puff processes for Eagle Ford tight oil fractured reservoir. The brief economic evaluation of Huff and Puff project is conducted for black oil region of the Eagle Ford basin.
Improved Rod-Pump Run Time in Sandy Wells Two Stages Filtration
Authors: VanNatta John , Logan Phillip , Stieg Alyssa , Gonzalez Gustavo , Guanacas Luis 
Published: April 2019

Abstract
Failures due to solid particles flowing with the production fluid is one of the main causes of interventions in wells with beam pumping systems. When this problem is accompanied with chemical deposition like scale, leads to a very common intervention during well operation. This paper proposes an analytical methodology that consists of evaluation of the particle size distribution, viability for the use of sand screens and centrifugal separation systems for sand control management in wells with short run time. These systems have proven effective for failure wells that requires a sand control management system when if not addressed increase the lifting costs leading many projects to be infeasible from an economic standpoint. All the technical considerations are explained focusing on the information required and the parameters analyzed to recommend the most accurate design for sand control; selected approaches and models that have been developed to improve the run time due to sand issues are shown in this paper.
A case study is showed in a well with average run time of 27 days indicating that identification of particle size distribution was a key factor to provide the right solution for sand control management. These novel applications help operators to reduced OPEX (operating expense), by minimizing well Interventions, decreasing failures in the pump; stabilizing the production and reducing the unforeseen interruption.
Reservoir Characterization Using NMR Data in Absence of Core - Breakthrough in NMR Data Utilization
Authors: Vij Jitesh , Nandi Anindya , Singh Sachit , Majumdar Chandan , Haldia Bhopal Kumar , Chaturvedi Praveen Chandra , Sarkar Sutanu 
Published: April 2019

Abstract
Considering the modern oil price environment, oil companies are more pressured than ever to reduce costs. This need affects tools used for reservoir characterization. Coring is important but expensive and is usually not available for the entire length of the well. A novel methodology is presented to perform reservoir characterization from wireline nuclear magnetic resonance (NMR) data, in the absence of any core, in offshore gas-bearing wells. This includes computing T2 cutoff, hydrocarbon saturation, permeability, and poro-fluid sand facies determination.
NMR is a shallow measurement and using wireline NMR measurements is even more challenging due to higher time after bit and increased mud filtrate invasion. Consequently, its use is restricted to quantifying porosity, and even the basic assessment of bound/free fluid require correct T2 cutoff to be determined from cores. Traditional formation evaluation methods use various equations like Archie’s, dual water, Waxman Smits, etc. to determine hydrocarbon saturation, all of which have many variables which, again, must be determined from cores. This makes it imperative to have core measurements to get precise results.
In this paper, we present the results of successful implementation of the proposed methodology, which functions without core data. It employs NMR data along with modern processing techniques like factor analysis and fluid substitution, and integrates density data to evaluate reservoir by 1) minimizing the mud signal, 2) using the virgin zone data to extract dominant peaks and repeated patterns on T2 distribution to divide the entire reservoir section into different poro-fluid types, 3) obtaining the T2 cutoffs for various poro-fluids facies, 4) calculating density magnetic resonance porosity (DMRP) and adopting it to drive fluid substitution, 5) obtaining original water equivalent porosity which is divided by DMRP to get water saturation, 6) employing the fluid substituted (water-only equivalent) T2 distribution along with the T2 cutoff determined by factor analysis to calculate permeability using the Timur-Coates equation.
Correlating the Performance of Friction Reducers with Source Water Chemistry
Authors: Hazra Suchandra , Madrid Vanessa , Luzan Tatiana , Van Domelen Mark , Copeland Chase 
Published: April 2019

Abstract
This paper provides a detailed evaluation of the impact that field source water chemistry has on the performance of friction reducers being used for hydraulic fracturing. In this research, correlations are established between friction reducer performance and source water chemical composition, allowing operators to shorten the learning curve within their fracturing operations, use the most appropriate fluid systems, and potentially mitigate job failures.
Extensive testing has been conducted to evaluate friction reducer performance in the presence of different ionic components such as calcium, magnesium, iron and chloride. Performance testing was determined by varying individual ions, as well as using source waters from multiple field locations having total dissolved solid (TDS) levels of well over 100,000 ppm. Testing parameters included friction reduction, hydration rate via viscosity, and rheological characterization for viscosifying-type friction reducers. Principal component analysis was used as statistical tool to characterize the variation in water chemistry and to establish its relationship with friction reducer performance.
Extension of Oil Well Economic Life by Simultaneous Production of Oil and Electricity
Authors: Wang Kai , Wu Xingru 
Published: April 2019

Abstract
Oil production decline and excessive water production are prevalent in mature fields and unconventional plays, which significantly impact the profitability of the wells and result in costly water treatment and disposal. To seek for a sustainable development of those wells, reducing the operation cost and extending their economic lives, this paper presents a method of synergistic production of hydrocarbon and electricity, which could harvest the unexploited geothermal energy from the produced water and transfer heat to electricity in the wellbore. Such method is cost-effective, since it does not require any surface power plant facility, and it is replicable in numerous wells including both vertical wells and horizontal wells. By simultaneous coproduction of oil and electricity, the value of existing assets could be fully developed, operation cost could be offset, and the economic life of the well could be extended.
This recently proposed method incorporated thermoelectric power generation technology and oil production. In this method, electricity could be produced by thermoelectric generator (TEG) mounted outside of the tubing wall under temperature gradient created by produced fluid and injected fluids. The aim of this paper is to illustrate the economic practicability of oil-electricity coproduction by using thermoelectric technology in oil wells based on previously proposed design. We examined the technical data of high water-cut oil wells in North Dakota and collected required information with respect to performance thermoelectric power generations. Special emphasis was placed on the key parameters related to project economics, such as thermoelectric material, length of TEG and injection rate. Sensitive studies were carried out to characterize the impact of the key parameters on project profits. We showed that by simultaneously production of oil and electricity, $234,480 of additional value could be generated without interfering with oil production.
The proposed method capitalizes on the unexploited value of produced water and generates additional benefits. This study could provide a workflow for oil and gas operators to evaluate an oil-electricity coproduction project and could act as a guidance to perform and commercialize such project to balance parts of the operation cost and extend the life of the existing assets.
Accelerated Completion Optimization with Uncertainty Reduction Through Coupled Data and Physics Based Hybrid Models
Authors: Liu Guoxiang , Stephenson Hayley , Shahkarami Alireza , Murrell Glen , Klenner Robert , Iyer Naresh , Barr Brian , Virani Nurali 
Published: April 2019

Abstract
Optimization problems, such as optimal well-spacing or completion design, can be resolved rapidly via surrogate proxy models, and these models can be built using either data-based or physics-based methods. Each approach has its strengths and weaknesses with respect to management of uncertainty, data quality or validation. This paper explores how data- and physics-based proxy models can be used together to create a workflow that combines the strengths of each approach and delivers an improved representation of the overall system. This paper presents use cases that display reduced simulation computational costs and/or reduced uncertainty in the outcomes of the models. A Bayesian calibration technique is used to improve predictability by combining numerical simulations with data regressions. Discrepancies between observations and surrogate outcomes are then observed to calibrate the model and improve the prediction quality and further reduce uncertainty. Furthermore, Gaussian Process Regression is used to locate global minima/maxima, with a minimal number of samples. To demonstrate the methodology, a reservoir model involving two wells in a drill space unit (DSU) in the Bakken Formation was constructed using publicly available data. This reservoir model was tuned by history matching the production data for the two wells. A data-based regression model was constructed based on machine learning technologies using the same dataset. Both models were coupled in a system to build a hybrid model to test the proposed process of data and physics coupling for completion optimization and uncertainty reduction. Subsequently, Gaussian Process Model was used to explore optimization scenarios outside of the data region of confidence and to exploit the hybrid model to further reduce uncertainty and prediction. Overall, both the computation time to identify optimal completion scenarios and uncertainty were reduced. This technique creates a robust framework to improve operational efficiency and drive completion optimization in an optimal timeframe. The hybrid modeling workflow has also been piloted in other applications such as completion design, well placement and optimization, parent-child well interference analysis, and well performance analysis.
Comparison between Wedge Resection and Segmentectomy for Ground Glass Opacity-dominant Early Stage Non-Small Cell Lung Cancer (TSCI 002): Study protocol for a randomized controlled trial
Authors: Liao Hu , Pang Long , Ma Lin , Liu Chengwu , Pu Qiang , Mei Jiandong , Lin Feng , Liu Lunxu 
Published: April 2019

Abstract
Background: Currently, there are no universally recognized criteria to choose between segmentectomy and wedge resection. However, compared with segmentectomy, wedge resection is more accessible, less invasive, preserves more pulmonary tissues and presents a faster post-operative recovery process, which in turn, result in a higher quality of life. We hypothesize that wedge resection could be a potential alternative to anatomic segmentectomy for patients with very early non-small cell lung cancer (NSCLC), and we plan to conduct the first randomized trial comparing the effectiveness and safety of wedge resection and segmentectomy to guide the surgical decision.
Methods: We plan to conduct a prospective, multicentre, randomized, open, parallel control and non-inferiority verification adopted study. Patients from 21 sites of China who satisfy all the inclusion criteria and do not fall into any of the exclusion criteria are qualified to be included in this study. They will then be randomly allocated into two groups: lung wedge resection + hilar and mediastinal lymph node resection / sampling (study group) and segmentectomy + hilar and mediastinal lymph node resection/sampling (control group). A recruitment period of no more than two years is anticipated. The primary endpoint of the study is 5-year disease-free survival (DFS) between the two groups. The secondary endpoints are 3-year DFS, 5-year overall survival （OS）, 30-day morbidity and mortality rates, and pulmonary function.
Discussion: This is a multi-centre, randomized, open, parallel control, and non-inferiority verification adopted study to evaluate whether lung wedge resection and segmentectomy are equivalent in long-term oncological efficacy in patients with ground glass opacity (GGO)-dominant early stage peripheral non-small cell lung cancer.
In vitro biofilm formation and antimicrobial susceptibility patterns of bacteria isolated from suspected external ocular infected patients attending Jimma University Medical Center eye clinic, southwest Ethiopia
Authors: Diriba Kuma , Kassa Tesfaye , Alemu Yared , Bekele Sisay 
Published: April 2019

Abstract
Background: Ocular disease with its complications is a major public health problem which significantly impacts on quality of life in developing countries. An ocular infection due to microbial agents, can lead to reduced vision and blindness. This study was aimed to assess the antimicrobial susceptibility pattern and biofilm forming potential of bacteria isolated from suspected external ocular infected patients attending Jimma University Medical Center (JUMC).
Method: A cross sectional facility based study was conducted on 319 suspect patients with external ocular infections from March 2017 to June 2017 at JUMC in Southwest Ethiopia. External ocular specimens were collected and standard operating procedures were followed to handle and culture throughout the study period. Antimicrobial susceptibility pattern of the isolates was determined by disk diffusion method according to CLSI 2015. Microtiter (96 wells) plate method was used to screen biofilm formation by measuring optical density at 570nm.
Result: Out of 319 study participants with external ocular infection, the prevalence of bacterial pathogens was 46.1%. The predominant bacterial isolates were Coagulase negative staphylococcus (CoNS) (27.7%) followed by Staphylococcus aureus (19.7%). Among Gram negatives, Pseudomonas aeroginosa (6.8%) was the leading isolate. Increased antimicrobial resistance was observed for tetracycline (64%), erthromycin (66.7%) and penicillin (77.1%). Amoxicillin-clavulanic acid, ciprofloxacin and gentamicin were the most effective drugs for both Gram negative and Gram positive ranging from about 70 to 100% with the later two drugs for external ocular infections. Methicillin resistant S. aureus (MRSA) accounted for 13.8% of S. aureus isolates.. Multidrug resistance (MDR) accounted for 68.7%. The overall biofilm formation rate of bacterial ocular pathogens was 66.1%; with P. aeruginosa (40%), CoNS (34.1%) and S. aureus (31%) formed strong biofilm phenotype.
Conclusion: The prevalence of bacterial isolates among external ocular infection was high. Almost all bacterial isolates were resistant to atleast one or more drugs. MDR pathogens were observed increasingly among biofilm formers or vice versa. Therefore, antimicrobial susceptibility testing should be practiced to guide treatment of external ocular cases and to control the emergence of drug resistant bacteria.
Interplay between Infarction Volume and Location to Mediate the Occurrence of Vertigo in patients with Vertebrobasilar Stroke
Authors: Elhfnawy Ahmed Mohamed , Elsalamawy Doaa , Volkmann Jens , Fluri Felix , El-Raouf Mervat Abd 
Published: April 2019

Abstract
Background

Vertigo is a common presentation of cerebellar or dorsal brain stem infarctions. However, the relation between infarction volume and the development of vertigo in patients with vertebrobasilar stroke was never investigated. In this study, we aimed to examine the interaction between the infarction size and location on the development of vertigo in patients with vertebrobasilar stroke.

Methods

Fifty-nine consecutive patients presenting with vertebrobasilar stroke were recruited and stratified into the presence or absence of vertigo. National institute of health stroke scale (NIHSS) on admission as well as modified Rankin Scale (mRS) and Barthel-index on discharge were used as clinical scales. The infarction location and volume were assessed in the diffusion-weighted images of magnetic resonance imaging (MRI).

Results

The infarction volume did not correlate with NIHSS-score on admission (ρ=0.077, p=0.56) but correlated with mRS (Spearman ρ=0.37, p=0.004) and Barthel index on discharge (ρ=0.33, p=0.011), serum levels of HbA1c (ρ=0.3, p=0.02) as well as white blood cells (ρ=0.34, p=0.008). Patients with vertigo had less male predominance (53.1% versus 77.8%, p=0.049) and were less likely to have focal neurological manifestations (65.6% versus 96.3%, p=0.004) in comparison to those without vertigo. The median of the total infarction volumes were statistically significant larger among patients with vertigo (5.6 versus 0.42 cm3, p=0.008). In an age and sex adjusted multivariate binary logistic regression model, an infarction location either in the cerebellum or dorsal midbrain and a total infarction volume of >0.48 cm3 were found to have an OR (95% CI) of 16.97 (3.1-92.95), p=0.001 and 4.4 (1.05-18.58), p=0.043, respectively to be associated with vertigo.

Conclusion

In addition to the infarction location in the cerebellum and/or dorsal brain stem, it seems that the infarction volume plays a role in the development of vertigo among patients with vertebrobasilar stroke. In patients with vertebrobasilar stroke, increased serum levels of HbA1c and leukocytosis seems to mediate the development of large infarctions.