bluuebunny/crossref_metadata_2025_split huggingface dataset:
Well Placement Optimization Using Simulated Annealing and Genetic Algorithm
Authors: Tukur Aisha Diggi , Nzerem Petrus , Nsan Nhoyidi , Okafor Ikechukwu Stanley , Gimba Abdullahi , Ogolo Oghenerume , Oluwaseun Alonge , Andrew Okafor 
Published: July 2019

Abstract
The general success ratio of wells drilled lies at 1:4, which highlights the difficulty in properly ascertaining sweetspots. well placement location selection is one of the most important processes to ensure optimal recovery of hydrocarbons. Conventionally, a subjective decision is based on the visualization of the HUPHISO (a product of net-to-gross, porosity and oil saturation) map. While this approach identifies regions of high HUPHISO regarded as sweetspots in the reservoir; it lacks consideration for neighbouring regions of the sweetspot. This sometimes lead to placement of wells in a sweetspot but near an adjoining aquifer; giving rise to early water breakthrough - low hydrocarbon recovery. Recently, heuristic optimization techniques. Genetic algorithm (GA) and simulated annealing (SA) has received attention as methods of selection of well-placement locations. This project developed and implemented GA and SA well-placement algorithms and compared the reservoir performance outputs to that of conventional method. Firstly, a reservoir performance model was built using a reservoir flow simulator. In the base case, the wells were placed based on a subjective selection of gridblocks upon the visualization of the HUPHISO map. Thereafter, JAVA routines of GA and SA well-placement algorithms were developed. The numeric data (ASCII format) underlying the map were then exported to the routines.
Finally, the performance model was updated with new well locations as selected based on the GA and SA-based approach and the results were compared to the base case. The Comparison of the results showed that both GA and SA-based approach resulted to an increased recovery and time before water breakthrough.
Use of Radial Basis Function Networks for Efficient Well Production Allocation
Authors: Zubarev Maxim , Zubarev Denis 
Published: July 2019

Abstract
Well production allocation is the cornerstone of reservoir surveillance and sound reservoir management. The apparent simplicity of the allocation process often results in an underestimation of its critical importance. However, the accuracy of the production rates allocation has an overwhelming impact on the company's ability to use sound data and perform model-driven analytics. As a result, the reliability of production forecasts, reserves estimates, and production system optimization efforts are affected by the selected allocation approach.
A common approach to well production allocation is based on the use of well tests closest in time to the point of interest. It assumes stable operating conditions and gradual changes in fractions of produced fluids. These assumptions rarely reflect reality and therefore lead to large allocation errors. Use of more sophisticated solutions, such as data-driven and model-driven integrated well-reservoir tools pose different challenges due to the constant need for time-consuming updates.
In this paper, we present a quick and efficient approach for production data allocation based on single layer Radial Basis Function Network - a variation of Artificial Neural Network. The procedure takes advantage of full well test dataset and can be effectively used in real time. We show that this approach does not suffer from the limitations of the more common approaches while delivering improved results.
Improved Water Based Mud Using Solanum Tuberosum Formulated Biopolymer and Application of Artificial Neural Network in Predicting Mud Rheological Properties
Authors: Tomiwa Oguntade , Oluwatosin Rotimi , Temiloluwa Ojo , Oluwasanmi Olabode , Joy Idaka 
Published: July 2019

Abstract
Drilling fluids are the most important materials in drilling operations, therefore improving the properties of these fluids are very essential in order to meet up with the increase in demands and required standards. In this experimental study, Solanum tuberosum formulated biopolymer was used to improve the water based mud rheological properties and artificial neural network predicted data for (PV) plastic viscosity, (AP) apparent viscosity and (YP) yield point. Artificial neural network (ANN) was used to train the rheological properties of the formulated mud and the network developed predicted the rheological properties of an untrained combination of bentonite and modified biopolymer. The main target is to regenerate or predict the rheological properties of the formulated mud; (AP) apparent viscosity, (YP) yield point and (PV) plastic viscosity generated originally from experimental procedures but this time using the ANN. The mean average error target was set to around 5-10%. As a model for choosing the best ANN architecture for predicting target value, two statistical parameters, mean squared error (MSE) and correlation coefficient (R2) were utilized. A system with the lower estimations of MSE and the higher estimations of R2 gives more precise forecasts. Three different network were created and the two statistical parameters were used to determine the best number of neurons in the hidden layer. The developed neural network with best prediction has Root Mean Square Error (MSE) of 1.25221 and overall correlation coefficient (R2) of 0.99373 for the predicted plastic viscosity, yield point and apparent viscosity
Predictive Models on Viable Options for Liquefied Petroleum Gas LPG Distribution: Case for a Small and Medium Scale Enterprise SME Commodity in Nigeria
Authors: Neeka Jacob B. , Ikoku Uche , Iyalla Ere , Joel Ogbonna , Ikiensikimama Sunday 
Published: July 2019

Abstract
Liquefied Petroleum Gas (LPG), a product of natural gas processing is a mixture of hydrocarbon gases mainly propane, butane, butylene and impurities such as Sulphur compounds. The production of LPG depends largely on available natural gas. Fortunately, Nigeria has proven gas reserves of over 189.27 Trillion Cubit Feet (TCF). However, LPG production in the country and its distribution especially in an emerging economy appeared to have limited growth over the last three decades. In this study, a stochastic model is applied to secondary historical and predictive data from 1994 – 2020, essentially on the production, consumption and streamline distribution pattern for the country. Certain assumptions were made including changes in the various stages in the production value chains (production, storage, distribution, pipeline infrastructure, and supply chains in-country.). Linear regression and correlation approaches were adopted using the models which agreed favorably with the plots from established data. It indicated that LPG consumption increases rapidly from 2016 upward following increases in infrastructural surplus, investment and awareness enlightenment initiatives. The results obtained indicated a strong correlation between demand-supply bond driven by market forces in the urban and suburban cities in-country. These indicators are reliable parameters for sustainable strategic planning, policy development and implementation for rapid economic recovery.
Production Optimization of Liquid Loading Problem in Offshore Niger Delta Gas Condensate Field
Authors: Abdullahi Mohammed Bashir , Sulaiman A. D. , Abdulkadir Usman , Salaudeen Ibraheem , Shehu Bashir Umar 
Published: July 2019

Abstract
In a natural gas field development plan, determining the life of the field and deciding the best-optimized production strategy as well as meeting the economic viability are the most important considerations to sustain gas production. Development optimization can increase the net present value by maximizing the hydrocarbon recovery and reducing the operating cost. Optimizing gas condensate bearing reservoirs below dew point exhibit complexities due to the hydrocarbon condensation and many times, an in-situ oil phase may result to reduce gas well productivity. Liquid loading can be a serious problem in gas-bearing condensate wells near the end of their production life. As the pressure in the drainage area is depleted below the dew point, the condensate will start to build up and the gas velocity in the production tubing falls below the critical rate resulting in inadequate energy to lift the entire condensate hydrocarbon out of the wellbore. The condensate liquid migrates down the tubing and accumulates at the bottom of the completion, increasing the bottom hole flowing pressure, thereby, reducing the production rate. Liquid loading phenomenon can be encountered in low productivity gas condensate wells. Preventive actions need to be considered for predicting and monitoring of liquid loading issue before it becomes a serious problem in production system form a reservoir to the surface facilities. This study focuses on optimizing gas production strategy in a field development plan of gas condensate well. Sensitivity analysis was implemented on the Bara well-1 through optimizing the operating parameters such as tubing sizes, wellhead pressures, skin factors, condensate gas ratio, water gas ratio and surface chokes sizes by using Niger-Delta field data and PROSPER dynamic simulator in order to select best well model construction that promote high gas deliverability and low condensate production. The reservoir GIIP has been estimated to 370 Bscf from both geological and dynamic simulation models. From the dynamic nodal analysis result, 5.5in tubing size promotes the highest optimum gas rate and low erosional velocity based on the investigated operating conditions.
Application of Artificial Intelligence in Well Screening and Production Optimisation in Oredo Oilfields, Niger Delta, Nigeria
Authors: Akanji Lateef T. , Dala Joshua , Bello Kelani , Olalekan Olafuyi , Jadhawar Prashant 
Published: July 2019

Abstract
An enhanced neuro-fuzzy technique is deployed in production optimisation and fluid flow analysis for wells drilled and completed in Oredo oilfields Niger delta Nigeria. The impact of historical production data, reservoir rock and fluid properties, well geometry, architecture, completion profile and surface data on overall well deliverability is incorporated in the model. The artificial intelligence training process is complete at the point a minimum quantifiable error is obtained or when a value less than the set tolerance limit is reached. Production data obtained from the short and long-strings for wells completed in Oredo field was processed, analysed and input into the enhanced neuro-fuzzy algorithm. The adopted enhanced neuro-fuzzy system is capable of modelling the direct approach of Mamdani and that of Sugeno in a five-layer feed-forward neural network and fuzzy logic process designed and implemented in a C/C++ numerical computation objected oriented platform. This study highlights the significance of data analytics and artificial intelligence in well performance prediction and cost reduction and optimisation in oil producing wells.
Modelling historical variability of phosphorus and organic carbon fluxes to the Mackenzie River, Canada
Authors: Shrestha Rajesh R. , Prowse Terry D. , Tso Lois 
Published: July 2019

AbstractThis study provides an improved statistical modelling framework for understanding historical variability and trends in water constituent fluxes in subarctic western Canada. We evaluated total phosphorus (TP) and dissolved organic carbon (DOC) fluxes for the Hay, Liard and Peel tributaries of the Mackenzie River. The TP and DOC concentrations primarily exhibit chemodynamic relationships with discharge, with the exception of the chemostatic relationship between DOC and discharge for the Hay River. With this understanding, we explored a number of enhancements in the load estimation model that included the use of (i) linear regression and logarithmic models, (ii) air-temperature as an alternate input variable and (iii) quantile mapping for bias-correction. Further, we evaluated uncertainties in the simulation of fluxes and trends by using a bootstrapping method. The modelled TP and DOC fluxes show considerable seasonal and interannual variability that generally follow the runoff dynamics. The annual and seasonal trends are mostly small and insignificant, with the largest significant increases occurring in the winter months. These trends are amplified compared with discharge, suggesting the possibility of pronounced changes with large changes in discharge. Additionally, the results provide evidence that directly using limited water constituent samples for trend analysis can be problematic.
Postmortem Degradation of Desmin and Dystrophin in Breast Muscles from Capons and Cockerels
Authors: Wojtysiak Dorota , Calik Jolanta , Krawczyk Józefa , Wojciechowska-Puchałka Joanna , Obrzut Joanna , Nahajło Karolina 
Published: July 2019

Abstract
In recent years, consumers have increasingly sought niche food products with specific aroma and flavour, and rich in nutrients. With a growing demand for quality poultry products, there is an opportunity to increase production of capons, which are more and more often marketed as high quality products, because their meat is more delicate, tender and juicy. Therefore the objective of this study was to compare meat quality parameters and rate of protein degradation between capon and cockerel breast muscle during postmortem aging. Fibre type diameter, intact desmin and dystrophin contents at 15 min, 24 h, and 48 h postmortem and the following technological parameters of breast meat were also determined: pH15, pH24, pH48, drip loss, shear force. The study was carried out on hybrids between Rhode Island Red cockerels (R-11) and Yellowleg Partridge hens (Ż-33) aged 24 weeks. The current findings indicate that compared with cockerel breast muscles, the capon breast muscles had significantly higher pH15 (P≤0.01), and lower drip loss (P≤0.01) and shear force values (P≤0.05). Additionally, the intensity of intact desmin and dystrophin in capon breast samples at 24 h and 48 h postmortem was significantly lower (P≤0.05) than that in the cockerel breast sample. In turn, the lower rate of desmin and dystrophin degradation (P≤0.05), along with higher drip loss in cockerel compared to capon breast muscles, may account for their lower muscle fibre diameters at 24 h and 48 h postmortem. Moreover, the rate of early postmortem pH decline can partly explain the variation of desmin and dystrophin degradation.
Pain in the cervico-facial pathology: elements of etiopathogenesis, diagnosis and therapeutic principles
Authors: Cobzeanu Bogdan Mihail , Palade Dragos Octavian , Rosu Andrei , Vonica Patricia Sonia , Martu Cristian , Radulescu Luminita , Rusu Daniela Carmen , Cobzeanu Luiza Maria , Cobzeanu Mihail Dan 
Published: July 2019

Abstract
The authors conduct a review of the etiopathogenesis, the main diagnostic methods and the treatment principles in cervico-facial pain. Pain in otorhinolaryngology is a multifactorial symptom, based on the rich innervation and vascularisation of the cephalic extremity. Pain can be of central or peripheral origin, acute and chronic. With the diversification of methods for exploring pain-generating lesions, different treatment protocols could also be achieved.
The association of absolute eosinophil count, serum immunoglobulin E and spirometry with co-morbid bronchial asthma in patients with allergic rhinitis
Authors: Vijayan Neelima , Karthikeyan Padmanabhan , Venkataramanujam Nirmal Coumare , Kaipuzha Ramiya Ramachandran , Pulimoottil Davis Thomas 
Published: July 2019

Abstract

OBJECTIVE. This study aimed to analyse the association of absolute eosinophil count (AEC), serum IgE and spirometry with co-morbid bronchial asthma in patients with allergic rhinitis.

MATERIAL AND METHODS. This study involved 50 patients with signs and symptoms of allergic rhinitis who underwent a clinical examination and various tests, including spirometry, and were followed up regularly. Patients found to have bronchial asthma or nasal polyposis were treated accordingly.

RESULTS. The study found the prevalence of bronchial asthma in patients with allergic rhinitis to be 58% and that the severity of bronchial asthma was reduced significantly, with lesser acute attacks and reduced hospitalizations with the effective treatment of allergic rhinitis (p=0.064).

CONCLUSION. This study showed that elevated AEC and serum IgE were significantly associated with co-existing allergic rhinitis and bronchial asthma and increased the chance of co-existence of these two pathologies. Spirometry is a useful tool for observing the response to treatment.
UJI TOKSISITAS LIMBAH CAIR TAHU TERHADAP KUTU AIR TAWAR (DAPHNIA MAGNA)
Authors: Wulandari0 Annisa , Fitria Laili 
Published: July 2019

ABSTRAKLimbah cair industri tahu yang dibuang ke badan air penerima tanpa pengolahan merupakan salah satu sumber pencemar di perairan yang menyebabkan kematian biota akuatik sehingga perlu dilakukan uji toksisitas akut. Penelitian ini bertujuan untuk mengetahui nilai LC50 limbah cair dari industri tahu yang terdapat di Kota Pontianak. Uji toksisitas akut dilakukan dengan metode statis dalam waktu 48 jam menggunakan hewan uji kutu air tawar (Daphnia magna). Konsentrasi rata-rata parameter limbah cair dari industri tahu yang didapatkan yaitu BOD sebesar 532,46 mg/L, COD 1870,20 mg/L, TSS 747 mg/L, amonia 432,50 mg/L, pH 5,58 dan suhu 32 oC. Nilai parameter limbah cair tahu tersebut melewati baku mutu KEP/MENLH/ No.5 Tahun 2014 tentang Baku Mutu Air Limbah bagi Usaha dan/atau Kegiatan Pengolahan Kedelai dan KEP/MENLH/ No.3 Tahun 2010 2010 tentang Baku Mutu Air Limbah bagi Kawasan Industri. Nilai LC50 rata-rata dari limbah cair tahu sebesar 3,56%. Peningkatan nilai BOD, COD, TSS, amonia dan pH akan menyebabkan peningkatan mortalitas hewan uji..Kata Kunci : LC50-48 jam, toksisitas, limbah cair tahu, kutu air tawar (Daphnia magna)
KAJIAN ANGKUTAN SEDIMEN LAYANG PADA SUNGAI JAWI KOTA PONTIANAK
Authors: Zul Pratomo Dicky Reno , Nurhayati Nurhayati , Fitria Laili 
Published: July 2019

ABSTRAKSungai Jawi merupakan salah satu saluran primer yang ada di Kota Pontianak. Aliran Sungai Jawi berada di Kecamatan Pontianak Barat, Sungai Jawi berfungsi tidak hanya untuk menampung dan mengalirkan limpasan air hujan, tetapi juga untuk menampung dan mengalirkan air limbah domestik dan menyediakan air bagi kebutuhan rumah tangga. Kondisi Sungai Jawi akhir-akhir ini semakin memburuk, air permukaan Sungai Jawi semakin keruh, dan terjadi pendangkalan di beberapa tempat terutama tempat-tempat yang memiliki aktivitas seperti di depan Pasar Dahlia dan di pertemuan saluran dari RS Antonius dengan Sungai Jawi, dan limbah hasil buangan yang berupa limbah cair yang mengandung lumpur ini akan terbawa aliran sungai yang seiring perubahan waktu, perjalanan aliran yang membawa lumpur (sedimen) ini akan masuk ke Sungai Jawi dan bermuara di Sungai Kapuas. Penelitian ini bertujuan untuk mengidentifikasi kadar sedimen layang (suspended load) di Sungai Jawi Kota Pontianak serta mengetahui dan mengidentifikasi pola angkutan sedimen di Sungai Jawi yang dipengaruhi pasang surut. Metode pengambilan sampe­­l­­ air menggunaan grab sampling sedangkan pemeriksaan sampel air dilakukan pada 3 titik pengambilan pada titik pengambilan sampel. Berdasarkan pengukuran elevasi muka air di muara Sungai Jawi selama 3 hari disimpulkan bahwa Sungai Jawi memiliki periode 1 kali dan 1 kali surut dalam 24 jam yang tergolong tipe pasang surut harian tunggal (diurnal tide). Konsentrasi sedimen tertinggi pada titik 1 sebesar 50 mg/l dimana titik 1 merupakan titik yang terdekat dengan muara sehingga terjadi akumulasi sedimen. Laju sedimen layang tertinggi terletak pada titik 2 segmen tengah dengan nilai laju sedimen layang (suspended load) sebesar 173,02 ton/ hari atau 63.152,54 ton/tahun. Laju sedimen terendah pada titik 3 segmen kanan dengan laju sedimen layang 8,67 ton/ hari atau 3.163,45 ton/tahun. Rata–rata laju sedimen layang di setiap titik 50,74 ton/ hari atau 18.519,49 ton/tahun.Kata Kunci : Sungai Jawi, pasang surut , sedimen layang, TSS.
Pemanfaatan Arang Aktif Ampas Kopi Sebagai Adsorben Kadmium Pada Air Sumur (The Usage of Coffee Waste Actived Charcoal as Adsorbent of Cadmium in Well Water)
Authors: Moelyaningrum Anita Dewi 
Published: July 2019

Logam berat masih banyak ditemukan mencemari lingkungan. Cadmium adalah logam berat yang bisa ditemukan didalam air disekitar tempat pembuangan sampah. Penelitian ini bertujuan untuk menganalisis arang aktif ampas kopi dalam menurunkan kadar Cd dalam air. Metode penelitian ini adalah true eksperimental dengan desain Rancangan Acak Lengkap. Tahap pertama adalah pembuatan arang kemudian diaktivasi dengan HCl. Hasil Uji kualitas arang aktif ampas kopi meliputi rendemen (98,5%), kadar air (7%), kadar abu (4%) dan daya serap idoin (687,96 mg/g). Terdapat empat kelompok yaitu tanpa perlakuan 0 gr/l (P0), perlakuan dengan 5 gr/ l (P1), 8 gr/l (P2) dan 10g/l (P3), dimana masing-masing kelompok terdiri dari 6 replikasi. Kelompok yang diberi perlakuan dikontakkan dengan arang aktif ampas kopi selama 2 jam. Selanjutnya dilakukan analisa kadar Cd dalam air dengan metode Spektrofotometri Serapan Atom. Hasil penelitian dilakukan uji normalitas kemudian dilakukan uji one way anova menggunakan SPSS. Hasil menunjukkan terdapat perbedaan secara signifikan sebesar 0,000 dengan interval kepercayaan 95% antara kelompok kontrol dan perlakuan. Arang aktif ampas kopi secara significant dapat mengikat kadar cadmium dalam air. Heavy metal cadmium (Cd) is still polluted the environment. It can be found in the wells around the landfill. This study aimed to analyze the active charcoal coffee ground to adsorb the cadmium in the water. This research method is the true experimental design with Completely Randomized Design. The first stage is making charcoal and then activated with HCl. There are four groups 0 gram/littre (P0), perlakuan dengan 5 gram/littre (P1), 8 gram/littre (P2) dan 10 gram/littre (P3) with each group consisting of 6 replication. Treatement group contacted with active charcoal coffee around 2 hours. Results of research normality test later conducted ANOVA test. The test results informed that there is 0,000 difference significanly with 95% confidence intervals. The active charcoal coffee had significant to adsorb cadmium in the water.
Conductivity and Activation Energy in Polymers Synthesized by Plasmas of Thiophene
Authors: Olayo Ma. Guadalupe , Cruz Guillermo J. , López Salvador , Morales Juan , Olayo Roberto 
Published: July 2019

The electric conductivity, activation energy and morphology of polythiophene synthesized by radiofrequency resistive plasmas are studied in this work. The continuous collisions of particles in the plasma induce the polymerization of thiophene but also break some of the monomer molecules producing complex polymers with thiophene rings and aliphatic hydrocarbon segments. These multidirectional chemical reactions are more marked at longer reaction times in which the morphology of the polymers evolved from smooth surfaces, at low exposure time, to spherical particles with diameter in the 300-1000 nm interval. Between both morphologies, some bubbles are formed on the surface. The intrinsic conductivity of plasma polymers of thiophene synthesized in this way varied in the range of 10-10 to 10-8 S/m; however, the conductivity resulted very sensitive to the water content in the polymers, which produced variations of up to 5 magnitude orders. The activation energy of the intrinsic conductivity was between 0.56 and 1.41 eV, increasing with the reaction time.

Plasma, Polymerization, Polythiophene, Conductivity, Activation Energy