bluuebunny/crossref_metadata_2025_split huggingface dataset:
Occupational deaths from Similar Causes; Why?
Authors: Shittu Ganiyu Adio 
Published: July 2019

Abstract
Understanding why incidents re-occur from similar causes despite the previous experiences, lessons and available tools to ensure that they do not happen again has been a cause of concern for company management for years and different reasons have been attributed to this issue. In recent past, below are few examples of incidents from similar causes.
On 25 January 2012, during the pre-mob inspection of a pile load tester pump by a DIL pile rig operator (Mechanical-24yrs old) with his Supervisor, the unit was put under pressure three times successfully but there was no movement of the pump piston. The pump was put under pressure the fourth time with a declared pressure of 500 bars, the pile load tester flange suddenly gave way and caused several severe injuries to the operator. He was confirmed dead at around 18h30. The unit was brand new with test certificate; IP was trained for it and note that the design pressure of the pile load tester was 690bars. In addition, when the unit failed, the 25 out of 26 bolts of the flange cut off while the last one had its nut pulled out.
On 15 May 2017, a fatal accident occurred when an analyzer engineer removed the cover on an explosion-proof enclosure as part of the routine task for the day. The ~5.5kg weighing threaded cover and with a 14 inches in diameter was propelled forcefully from the enclosure as the Engineer unscrewed it inflicting a fatal head injury. The pressure inside the enclosure from leaking sample gas or instrument air components caused the forceful propulsion of the enclosure cover. There was no gauge or indicator on the enclosure to monitor the internal pressure inside the enclosure and there was no means to relieve internal pressure (http://www.safteng.net/images/2017_Posts_Pics/CVXIndustryAlertJune2017.pdf).
Modification of Hall-Yarborough Equation of State For Predicting Gas Compressibility Factors
Authors: Ayuba Ibrahim , Isehunwa S. O. , Adamu M. B. , Usman A. , Bello M. N. 
Published: July 2019

Abstract
This investigation demonstrates the use of acentric factor as the third parameter in a corresponding states correlation for compressibility factors and a discussion of their application to three different types of gas reservoir.
A correlation is presented which provides compressibility factors based on Hall – Yarborough equation of states for use in both two – phase and single-phase hydrocarbon systems. The modified Hall - Yarborough equation employs the acentric factor as an additional parameter to improve its accuracy. This modified equation is as simple as the original form, yet achieves substantially better prediction accuracy, especially at higher pressure.
The correlation is based on hydrocarbon compressibility determinations from twenty-two hydrocarbon samples taken from three different types of reservoir systems. Out of the data used 67 percent were from dew point or retrograde gas condensate and bubble point or dissolved gas reservoir, 33 percent were from single phase gas reservoir.
Results from the modified Hall – Yarborough equation, the original Hall – Yarborough equation and practically obtained were compared with natural gas components data for three different reservoirs to demonstrate its accuracy and increased application range. The improvement of the modified equation, over the original Hall – Yarborough equation ranges from 0.98% to 7.017% on the average.
Artificial Bee Colony ABC a Potential for Optimizing Well Placement – A Review
Authors: Okoro Emmanuel Emeka , Agwu Okorie E. , Olatunji David , Orodu Oyinkepreye David 
Published: July 2019

Abstract
Many optimization tools exist for well placement into reservoirs for maximum oil recovery. Conventional tools such as simulated annealing, response surface technology, gradient-based optimization, mixed integer programming etc. abound. However, artificial intelligence optimization tools have emerged over the years and are gaining ground. Artificial bee colony (ABC) has become one of the most common optimization methods in the domain of Artificial Intelligence since it was first conceived in the early nineties. As a result, avalanches of researches to its credit in well placement optimization exist. This paper therefore, highlighted conventional well placement optimization tools and also reviewed the artificial intelligence based optimization tools especially ABC and hybrids of ABC Algorithms formulated for well placement and compared them with each other using four basic criteria. The review has shown that ABC algorithms are very efficient in handling the placement of wells in reservoirs during well planning. This work therefore opens up a new vista in the area of well placement optimization and is therefore recommended to anyone looking for a pivot on the well placement optimization discussion.
A Geomodel for Pore Pressure Prediction Based on A Viscoelastic Compaction Law
Authors: Nwonodi Roland I. , Dosunmu Adewale 
Published: July 2019

Abstract
It is important to develop a model that simulates in situ pore pressure profile especially in an overpressured interval mainly because of wellbore instability, hydraulic fracturing treatment, lost circulation, kick, and blowout. The current methodology for predicting pore pressure depends on the Terzaghi's total stress but requires the accurate determination of the effective stress in the rock. The sedimentary processes occurring in a basin put the rock under compaction, which can be viscoelastic. The normal-compaction methods of predicting pore pressure consider only mechanical compaction, but viscous compaction is important to consider, especially beyond 2000 meters of the subsurface. In this study, a model for predicting pore pressure was developed by applying an effective stress law that considers viscoelastic compaction into the Terzaghi's stress equation. From the relationship defining effective stress and the rate of deformation, the author posed an expression for the total effective stress in terms of time. The applicable boundary condition was with respect to the transit time through the rock. Using transit time data for a Gulf Coast wellbore at 10,000 ft yielded a pressure gradient of 0.885 psi/ft, which compares to 0.863 psi/ft obtained from the modified Eaton's model and 0.9132 psi/ft obtained from the Zhang model. Another pressure required for a wellbore at 30,000 ft yielded a pressure gradient of 0.535 psi/ft, which compares with 0.52 psi/ft obtained from measured formation pressure. Thus, the results indicate that the viscoelastic compaction accurately defines the pore pressure profile in a rock. Furthermore, simulation results indicate that the most important variable affecting pore pressure is the overburden stress.
Magnetic Resonance: Says it as it is!
Authors: Oifoghe Stanley , Okowi Victor , Ibe Eziulo 
Published: July 2019

Abstract
Magnetic resonance (MR) is a very robust service that delivers several formation evaluation products. Both the wireline (WL) and logging-while-drilling (LWD) services deliver shale volume, porosity, permeability, viscosity, saturation and fluid typing. In addition to these, the WL service also delivers capillary pressure and grain size analysis.
Although WL and LWD MR Services have different modes of acquisition, the result is usually the same. WL MR uses multiple frequencies, but LWD MR uses a single frequency. Multiple frequencies provide multiple magnetic field gradients that provide for more flexible hydrocarbon typing acquisition sequences, unlike the LWD MR single frequency that supplies a single hydrocarbon acquisition sequence.
Dual Wait Time (DTW) analysis is the hydrocarbon typing technique for LWD MR, but the WL hydrocarbon typing has the flexibility to choose from a range of applications that includes two-dimensional MR mapping (2D MR), density multiple wait time (DMTW) analysis, multiple gradient inter-echo spacing (MGTE) analysis, simultaneous inversion of multiple echo trains (SIMET), and T1/T2 ratio (R-T2) analysis for gas reservoirs.
Light hydrocarbons (gas) and Kaolinitic shales compromise the use of neutron-density and gamma ray models as bulk shale volume indicators. However, MR shale volume computation using clay-bound water (CBW), which is unaffected by the presence of gas or Kaolinitic shales. MR Logs can accurately determine porosity in complex lithologies and thin beds. Irreducible water saturation from MR is used to determine reservoir quality and productivity.
In the industry today, MR logs are the most tolerant to environmental challenges. They are able to "say" the true state of the reservoir in the midst of environmental factors like the presence of gas, shales, and thin beds, which are known to adversely impact measurements from other conventional tools
Dynamic Production Forecasting using Artificial Neural Networks customized to historical well Key Flow Indicators
Authors: Nnamdi David N. , Adelaja Victor O. 
Published: July 2019

Abstract
The existing decline curve analysis (DCA) equations, some with valid theoretical justifications, cannot directly react to changes in operating conditions. Thus, they all assume constant operating conditions over the flowing life of a well. This however is an obvious oversimplification.
This paper begins by briefly reviewing Gilbert's equation for flowrate prediction and then the C-curve and Logistic growth model DCA theories. The above review serves to identify well key flow indicators (KFI) and performance drivers. Subsequently, a forecasting approach which involves building artificial neural network (ANN) frameworks and training them on well KFI data is presented.
Using trained ANNs, production forecasts were generated for three oil wells in the Niger-Delta producing from separate reservoirs under different flow regimes. The results were compared to forecasts from traditional DCA methods and material balance simulation, as well as with future production from the wells themselves. The results indicated that trained ANNs are capable of generating better performance curves than traditional DCA, with forecasts tying closely with results of material balance simulation and measured future well production rates. The ability of trained ANNs to evaluate the effect of changes in operating conditions (i.e. FTHP, GOR and water-cut) on production profiles and reserves drainable by wells, allows for scenario forecasting which is invaluable in field development planning. This is illustrated with field cases.
This paper also presents a novel approach to evaluating the optimal hyperparameter configuration (i.e. the number of layers, neuron count per layer, dropout, batch size and the learning rate) required to minimize the loss function whilst training an ANN on any given dataset. This should prove invaluable to engineers and geoscientists integrating deep learning into sub-surface analyses.
Single Trip Tubing Conveyed Perforations Across Multi-Lobed Differentially Depleted Reservoir Complexes In A Highly Deviated Well – Challenges, Lessons Learned & Best Practices
Authors: Agbo Ejimofor , Anyanwu Chinedu , Olowoyeye Oluwasola , Ini Titus , Emah Victor 
Published: July 2019

Abstract
This paper demonstrates how 280ft of oil column spread unevenly across multiple and differentially depleted reservoir units separated by shale layers of varying thicknesses in a highly deviated (62 deg.) well was perforated in a one trip system and how the project cost was minimized by achieving multiple perforations in a single trip whilst retaining capacity to effectively cure losses and mitigating post-perforation well control risks. Against the conventional perforation methodology where reservoir units are perforated individually, isolated before carrying out the next perforation in the subsequent reservoir. The one trip system was designed and deployed in one run targeting all the 6 separate carefully selected sand lobes in one run ensuring good standoff from the contact and zonal isolation behind casing. Successful execution was confirmed with all the expected physical outcomes which includes pipe vibration, brine loss as well inspection of the spent guns. A post perforation noise and production logging also confirmed flow across all planned perforation intervals. Perforation of a highly deviated well in differentially depleted multi-lobed reservoirs present significant operational risks. This paper illustrates how one can safely collapse multiple conventional perforation runs into a single trip with its attendant benefits on cost efficiency, crossflow and well control. This is the first of its kind in a swampy terrain, shallow offshore Niger Delta.
Integration of Rock Physics and Seismic Inversion for Net-To-Gross Estimation: Implication for Reservoir Modelling and Field Development in Offshore Niger Delta
Authors: Chudi Obinna , Iwegbu James , Tetegan Gerard , Ikwueze Obinna , Effiom Oghogho , Oke-Oghene Uruh , Ayodeji Babatunde , Opatewa Stephen , Oladipo Titi , Afolayan Tunbosun , Tonyi Amba-Ambaiowei , Osayande Francesca , Falade Oladipo , Kanu Magnus , Anaevune Austin , Emakpor Jake , Afulukwe Chuks , Pokima Sophie 
Published: July 2019

Abstract
This study highlights a technique adopted for predicting and mapping net-to-gross (NTG) away from well locations through a combination of rock physics and seismic inversion applied in the Baza Field. The Baza field is located offshore Nigeria, with reservoirs poorly to mildly consolidated that were originally deposited in a deep-water submarine canyon system. The field is a partially appraised green field with three well penetrations encountereing amalgamated channels and lobes within the canyon system of tuiditic origin. Of the three wells drilled to date, only one well penetrated the key reservoir of interest- the B4 sands. The paucity of well penetration posses a challenge for accurate reservoir property assessment, particularly net-to-gross that has direct impact on hydrocarbon volume computation and ultimately on field development.
Net-to-gross was predicted from seismic data based on a linear relationship observed from log derived P-impedance-AI (density × compressional velocity logs) and S-impedance-SI (density × shear velocity). Both properties when integrated can descrimate between sands and shales, and therefore serves as a proxy for calculating NTG. The linear relationship was applied to AI and SI seismic volumes built from simultaneous inversion of three sub-stack seismic data – the near (0-18), median (12-24) and far (24-45).
The seismically derived net-to gross computed from simultaneous inversion compares favorably with log derived net-to-gross at well locations. The net-to-gross model resulted in a robust static and dynamic model that ultimately formed the basis for selecting optimal locations for future development wells for the B4 reservoir.
Mathematical Modelling of Oil Viscosity at Bubble point Pressure and Dead Oil Viscosity of Nigerian Crude
Authors: Adeeyo Yisa 
Published: July 2019

Abstract
Traditionally, reservoir engineering fluid flow calculations use viscosity data. However, in the absence of lab/experimental data other available derived correlations are used to predict the PVT property. Limit on the number of available data, regional peculiarity of the fluid, several viscosity correlations in the literature have limited accuracy and applicability. This study has developed predictive models using more than 2020 unpublished PVT data sets from different locations in Nigeria in rigorous nonlinear regression modelling. Different nonlinear algorithms, modified Newton-Raphson nonlinear least-square data fitting approach; Levenberg-Marquardt algorithm were used to develop new models for the estimation of the viscosity at the bubblepoint pressure and dead oil viscosity. The results of the performance of the model for viscosity at the bubblepoint show that the model provides better prediction with average absolute relative error of 21.06 and coefficient of correlation of 0.98 and the dead oil viscosity model shows a substantial improvement with average absolute relative error of 30.06 and coefficient of correlation of 0.90 over published correlations.
Investigation of Sediment Migration From The Abakaliki Anticlinorium To The Anambra Basin - A Geostatistical Approach
Authors: Okiotor M. E. , Asuen G.O. 
Published: July 2019

Abstract
The present investigation focused on geochemical evaluation of shale sequences in The Lower Benue Trough using geostatistical approach Thirty two representative samples of shale sequences of The Asu River Group, Nkporo Group and Mamu Formation in The Lower Benue Trough were subjected to Multi-Parameter study in an attempt to present a model of the sediment provenance, and paleoenvironment diagenetic conditions.
The X-ray diffraction and Inductively Coupled Plasma Mass spectrometry (ICP-MS) techniques were employed to examine and establish qualitative and quantitative constituents of the Major oxides, Trace and Rare Earth elements. The major minerals determined include SiO2 (40.96%, 56.08% & 60.39%)2, Al2O3 (15.09%, 18.27% and 21.16%), TiO2 (0.75%, 1.73% and 1.63%) and Fe2O3 (9.66%, 2.78% & 2.85%), for Asu River Group, Nkporo Group and Mamu Formation respectively. The studies suggest high influx of sediments into both The Abakaliki Anticlinorium and the Anambra Basin. When tested with multivariate statistical techniques such as Factor, Principal Component, Correspondence and Cluster analyses, the hidden affinities within the sediments were revealed in terms of similarities and dissimilarities. Enrichment and depletion of biogenic indicators CaO (EF=1.87 − 0.01) and P2O5 (EF=1.58 − 0.33) in the studied Asu River Group and Anambra basin sediments indicate deep marine to marginal marine paleoevironment of deposition respectively. Chemical examination of the maturity indexes indicate that the Anambra basin sediments were more matured, indicating that most of the Anambra Basin sediments were reworked from the Abakaliki Anticlinorium.
Assessment of Vehicular Carbon Dioxide Emission at Major Road Intersections in Benin City, Edo State Nigeria
Authors: Iwuala Ikechukwu S , Oriaku Timi O. 
Published: July 2019

Abstract
This study examines the levels of vehicular Carbon (IV) oxide (CO2) emissions in nine (9) selected locations characterised by high traffic congestion in Benin City Metropolis, Edo State, Nigeria. The contributory effects of these emission levels on climate change and air pollution were also assessed based on global standards. CO2 concentration measurements were conducted twice a day, four times a week, for a period of sixteen (16) weeks. Results showed that the highest average mean values were recorded at Ring Road, New Benin and Third East Circular Junctions with 1421 ppm, 1417ppm and 1171ppm respectively in the morning hours and 1767ppm, 1417ppm, 1217ppm respectively in the afternoon hours. Diurnal variations revealed significant statistical differences (P&lt;0.05) for CO2 emissions generated at different times of the day. Spatial variations in the CO2 data were also statistically significant (P&lt;0.05), with the highest mean concentrations of 1594ppm reported for Ring Road sampling station while New Benin and Five Junction sampling sites recorded mean CO2 emissions rates of 1417ppm and 745.8ppm respectively. The results showed that CO2 emission levels at these selected high traffic areas in Benin are approximately five times more than the internationally accepted safe limits of 350ppm for atmospheric CO2. However, these levels are less than the Occupational Safety and Health Administration (OSHA) permissible exposure limits of 5,000ppm. High vehicular exhaust emission which is the primary source of CO2 in the Benin city metropolis can be attributed to poor traffic handling and discipline; and low dilution and dispersion of the emitted CO2 due to prevalent low wind speeds in these study locations.
Production Optimization through Pressure Transient Analysis
Authors: Olufisayo Fagbowore , Anthony Oyewole 
Published: July 2019

Abstract
Intelligent field completions have seen more frequent deployment in the oil and gas industry in recent times. This is most likely due to the benefits that have been observed from real-time data acquisition, surveillance and optimization based on analysis of data gathered. With continuous acquisition of real-time data, analysis of the transient pressure and rate data can be used to understand changes in reservoir and well performance over time. The aim of this paper is to show how the evolution of parameters obtained from pressure transient analysis can be used to optimize well and reservoir performance.
Key parameters obtained from pressure transient analysis (PTA) are permeability, skin, reservoir pressure and information on boundaries depending on shut-in duration. Analyses are performed for all shut-ins of the completion, both planned shut-ins and unplanned shut-ins (emergency shutdowns - ESDs). The results of all these analyses are catalogued to provide an historical surveillance data which, when trended, can provide insight into the near-wellbore performance of a completion as well as the reservoir.
This paper demonstrates how Pressure Transient Analysis of real-time data was used in the Agbami Field to optimize production from the field. Two case studies are presented where analysis of transient pressure data was used to identify water injection front movement in a waterflooded reservoir and increasing near-wellbore damage due to fines migration. The results were used to optimize injection into a waterflooded reservoir to achieve a balance between maintaining reservoir pressure and optimizing voidage. In the case of continually increasing skin, the completion was stimulated with production increasing by a factor of 15.
Characterization of Potential Paraffin Wax Removing Bacteria for Sustainable Biotechnological Application
Authors: Okoye A. U. , Chikere C. B. , Okpokwasili G. C. 
Published: July 2019

Abstract
The presence of paraffin wax precipitation and deposition in tubing surfaces during production is one of the all-encompassing nuisances in oil and gas industry operations worldwide and it causes major production problems. The study aimed at acquiring novel insights into the bacterial community diversity capable of utilizing paraffin wax. Samples were collected from crude oil-polluted site in Gio Community, Tai Local Government Area, Niger Delta, Nigeria at depth of 0-0.5m (surface polluted soil [SPS]), 1m (sub surface polluted soil [SPSS]). GPS coordinate points for the North, South, East and West were N40 41′ 39″; N40 41′ 38″; N40 41′ 38″ and N40 41′ 37″ for latitudes respectively. Longitudes for the coordinates were E70 13′ 49″; E70 13′54″; E70 13′ 53″ and E70 13′ 54″ for North, respectively and unpolluted soil (UPS) taken 80m away from polluted site as control. All samples were transported to the laboratory within 6h at 4°C for analyses. Biodegradation screening was carried out using 2, 6-dichlorophenol indophenol (DCPIP) (redox potential +0.217 V) indicator to evaluate the biodegradation of hexadecane, paraffin oil and crude oil by axenic cultures of the bacteria isolated. GC-FID analysis for total petroleum hydrocarbons (TPH) were 22,146.65ppm for (surface polluted soil [SPS]), 14,087.80ppm (sub surface [SPSS]) and control soil (UPS) 479.67ppm respectively. Polycyclic aromatic hydrocarbons (PAHs) were 12,209.3ppm for SPS, 3,248.75ppm for SPSS and 22.72ppm for UPS. Total cultivable hydrocarbon utilizing bacterial count (TCHUB) for SPS, SPSS and UPS were 8.4 × 105cfu/g, 8.0 × 105cfu/g and 3.96 × 104cfu/g respectively. Pseudomonas spp., Bacillus spp., Acinetobacter sp. and Serratia sp. demonstrated higher biodegradability of paraffin wax than other 62 TCHUB isolated. These bacteria may probably represent an alternative green method for scale removal in the oil and gas sector.