bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rock Compaction Fault Displacement Evidence from Analysis of Sub-Parallel Subsurface Strata
Authors: Rotimi Oluwatosin John , Zhenli Wang , Liang Yao , Onuh Charles Yunusa , Ogunkunle Temitope Fred , Oyeyemi Kehinde David 
Published: August 2020

Abstract
Sedimentary units often show compaction variation across fault blocks resulting from jarring vertical shortening; a common occurrence in growth fault system innate to the Niger Delta. Rock displacement traceable on slip surface with varied dip was mapped on 3D seismic data. Interpretation done on available well logs reveal existing zones of sand formation that fairly correlates with compaction patterns seen on seismic lines across fault blocks with reference to vertical deviations in horizons across fault planes. These anomalies were stochastically analyzed for its topology effects using Density logs from the field in an attempt to ascertain the influence of rock strata on fault displacement and how this translates to compaction patterns. It was discovered that the effect of differential compaction propelled by wobbly underlying rocks primarily drives the local complexities imaged on the seismic data as varied turgid deformation zones also prolific from computed seismic attributes.
Optimizing Technology Applications with Compatibility Challenges in Remote Operating Environments – A Niger Delta Case Study
Authors: Orogun Elisha , Erivwo Ochuko , Ideh Matthew , Okon Willie , Ageh Ebenezer 
Published: August 2020

Abstract
New Technology implementation brings intrinsic value to well delivery projects with enhanced capabilities for exploitation of hydrocarbon reserves. However, the planning of wells with new technology applications, especially in remote operating locations, comes with unique challenges of compatibility of existing equipment and unavailability of equipment required for the new technology system's deployment.
This paper presents a case study of an engineered approach to equipment modification and retrofitting of wellhead equipment to achieve the required compatibility with a new technology solution identified for a well as a pilot. The limiting conditions encountered in the new technology implementation as presented in the case study are discussed together with the analysis of available concepts to resolve the ensuing gaps and the engineering design of the retrofit solution. The approach not only resulted in significant cost savings but has attendant value creation benefits.
The methodology and thought process presented can be deployed to solve challenges that engineers are confronted with while planning, especially with new technology applications in remote operating environments as was used by OML 26 Asset in the installation of the first ESP artificial lift in the Ogini field.
Understanding the Science of Statistical Log Analysis: A Review of a Practical Workflow Application to Determine Mineral Volume Fraction
Authors: Eriavbe Francis Eseoghene , Okene Uzoamaka Ogochukwu 
Published: August 2020

Abstract
Conventional openhole log evaluation is typically done in a deterministic approach which leads to inherent uncertainty around the derived results based on the fixed assumptions made. This has historically stemmed from the fact that most of the porosity and saturation models utilized in the deterministic work flow were formulated long before the availability of computing processing power. With the advent of technology, statistical methods designed for quantitative formation evaluation of open-hole logs are now easily applicable.
Probabilistic log evaluations are generally done by solving simultaneous equations described by one or more interpretation models. Input log measurements and response parameters are used together with response equations to compute volumetric fractions results for formation components (minerals and fluids alike).
The system of equations built to conduct a volumetric analysis comprises tool parameters, minerals and fluid volumes and the tool responses parameters. The probabilistic workflow uses error minimizing or probabilities to solve a set of over-determined equations for the "best" answer. To achieve an over determined case, constraint equations are often imposed. Logging vendors usually offer this product as part of their service and software applications.
This paper analyses the typical workflow governing probabilistic evaluation methodologies and proposes a Python script based approach that enables the user to run a fast and simple mineral components evaluation based on porosity and basic input logs.
Data from a typical Niger Delta well is used to evaluate the workflow and the results are compared with a deterministic evaluation to see the added benefits.
Modelling Minimum Flow Rate Required for Unloading Liquid in Gas Wells
Authors: Fadairo Adesina , Adeyemi Gbadegesin , Ogunkunle Temitope , Lawal Oreoluwa , Oredeko Olugbenga 
Published: August 2020

Abstract
Liquid loading in gas well has been an interest in the Oil and Gas sector due to the reduction of ultimate recovery and also the reduction of production from such wells. Several authors have presented various models for predicting the beginning of liquid loading in a gas well, yet there are regular errors in the model outcomes. Turner et al. based his critical model on a presumption that liquid droplet is spherical and stays that way throughout the wellbore. Li’s model developed later on based on his postulation that droplets are flat in shape and stays that way throughout the wellbore. In reality, when producing in a gas well, under pressure variation, the liquid droplets alternate between sphere-shape and flat shape. Hence there is a need to incorporate the liquid droplet deformation coefficient in the liquid loading governing equation. The newly presented model considered deformation coefficient to justify irregular changes in liquid droplet due to pressure variation during the simultaneous flow of gas and liquid droplet in gas wells, therefore, predict the critical flowrate correctly as the droplet fluctuates between spherical and flat shape. The results from the newly developed model of the critical flowrate using test data provided by Coleman et al. show that the modified critical flowrate is closer to the test flow rate than the other existing models as the error obtained is -9.12688%.
Effects of Seabed Topography on the Fatigue Life of Steel Catenary Risers
Authors: Uche Amarachi , Okoro Franklin 
Published: August 2020

Abstract
This research work analysed the effects of seabed topography on the fatigue life of a steel catenary riser in the Gulf of Guinea. A fatigue analysis was carried out for two risers namely PFL-06 and PFL-11 on the Portside and starboard sides of an FPSO respectively. A fatigue analysis was run for a flat seabed and a 3-D seabed using Orcaflex’s 3-D seabed feature using the same set of input data. The metocean and environmental data were obtained from Field X riser design document. The fatigue life on the touch-down point for PFL-06 on a flat seabed was calculated as 267 years. On a 3-D modelled seabed, the fatigue life on the touch-down point of PFL-06 is 304 years. For riser PFL-11, the fatigue analysis gave 1231 years and 425 years for a flat and a 3-D seabed respectively. It was observed that since PFL-06 has an outer diameter of 0.324m and almost the same water depth, there was no much difference in the fatigue analysis for a flat seabed and a 3-D seabed. PFL-11 with a smaller outer diameter of 0.273m gave a far lower fatigue life of 425 years on the touch-down point for a 3-D seabed as against a fatigue life of 1231 years on a flat seabed. The maximum effective tension on the TDP for the two risers were lower for a 3-D seabed than a flat seabed. The research found out that assumptions of a flat seabed in the fatigue analysis of the touch down zone of steel catenary risers could have adverse effects in the analysis.
Effect of Microbial Activities on the Viscosity of Heavy crude in Niger Delta Field
Authors: Okotie Sylvester , Onyekonwu Mike Obi , Okpokwasili Gidoen 
Published: August 2020

Abstract
This study focuses on the post-recovery effect of Nigerian heavy crude viscosity in microbial enhanced oil recovery process. The technique involves the injection of exogenous hydrocarbon-degrading microbes with the required nutrients to guarantee the bacteria isolates produce the needed metabolites such as biosurfactants, biopolymer, etc. In this study, thirty- seven hydrocarbon-degrading bacteria were isolated from a hydrocarbon-contaminated soil samples from Gio, Tai Local Government Area in Ogoniland. Three of the bacterial isolates were selected and screened for biopolymer and biosurfactant production using Sudan black solution, oil spreading test, emulsification index, and haemolytic assay. The selected microbes were identified as Bacillus sp, Klebsiella sp & Pseudomonas sp by biochemical analysis. The selected microbes were exposed to ranges of salinity, pH, temperature, nutrient sources, and inoculum concentration to determine their optimum performance in reservoir conditions. The result showed the optimum parameter range for the three microbes: pH 7- 8, a temperature within 25 - 400C and salinity within 0.5% - 5%. The best nitrogen source was peptone while the best carbon source for Bacillus sp was glucose and glycerol for Pseudomonas sp and Klebsiella sp respectively. These optimum parameters were employed in the formulation of the nutrient broth used for the core flooding experiment. The core flooding setup was locally fabricated and calibrated. Fourteen microbial samples of pure and consortium were injected with carbon and nitrogen sources. The result showed an additional recovery range between 18.33% to 29.09% of the pore volume. The post-recovery analysis showed drastic transformation (reduction in viscosity) of the heavy crude to light hydrocarbon components by an average of 20.33% with glucose and 97.27% with peptone.
Prediction of Reservoir Saturation Pressure and Reservoir Type in a Niger Delta Field using Supervised Machine Learning ML Algorithms
Authors: Eyitayo Stella I. , Ekundayo Jamiu M. , Mumuney Eyitayo O. 
Published: August 2020

Abstract
Accurate knowledge of reservoir fluid properties, especially reservoir saturation pressures and reservoir type, is paramount for the estimation of reservoir volumetrics, well design and placement, well and reservoir performance management, field development planning and ultimately economic evaluation of the reservoir. However, most of the existing methods such as PVT fluid sampling, compositional grading, and empirical models have proven to be either ineffective or expensive and sometimes, leads to ungeneralizable results.
This paper discusses the application of machine learning (ML) techniques to develop a robust model for prediction of reservoir fluid properties such as saturation pressures in a Niger Delta Field and the subsequent classification of the reservoirs as under-saturated or saturated. Reservoir data including the PVT data, compositions (C1-C7+), temperature & pressure data, fluids contacts of known reservoir type were considered initially in order to train a model using a multi-features regression ML algorithms for the determination of the saturation pressure and a Two-class boosted decision ML algorithms to determine the determine the type of reservoir (saturated or undersaturated). Of the 34 parameters considered, it was found that the reservoir fluid composition has significant impact in determining the accuracy of the Pb-hypothesis. The key performance indicators such as MAE, RMSE, and RSE are within 0.02-0.05 and Co-efficient of determination of about 95% for Pb determination. When compared with the Standing, Glaso, Petrosky-Farshad etc. correlation, the AAE was significantly less than both cases. AAE for the Standing and Glaso correlations were respectively18.5% and 25.1% while that of the ML model was 2.3% using both the data from training set and test set. For the classification algorithms in determining type of reservoir, the model performed within the 73-100% accuracy, precision & recall. The Area under the curve (AUC) of the Receiver Operator Characteristic (ROC) chart of approximately 97% indicated the robustness of the model. The results showed that the use of a properly trained and accurately validated ML model can deliver better predictions of reservoir fluid properties and subsequent reservoir type when compared to conventional methods.
Bacterial Community Profiling and Predictive Functional Gene Analysis during Petroleum Biodegradation
Authors: Chikere Chioma Blaise , Ezekoye Charles Chibueze , Okpokwasili Gideon Chijioke 
Published: August 2020

Abstract
Bacterial functional diversity in crude oil-polluted site undergoing remediation by enhanced natural attenuation (RENA) was monitored over an 8-week period. Soil samples were collected from the polluted site (&gt;5,000mg/kg of TPH) at various phases of bioremediation while the control (unpolluted soil) was taken 80 meters away from the polluted site. Next generation sequencing on Illumina MiSeq platform was used to characterize the bacterial community composition. Functions of different operational taxonomic units (OTUs) and proportions of functional bacterial groups involved in each step of biodegradation were predicted using Kyoto encyclopaedia of genes and genomes (KEGG) and phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt). Principal component analysis (PCoA) of the functional genes was also carried out for statistical inferences. The predicted functional genes indicated the presence of genes responsible for benzoate, DDT, dioxin, fluorobenzoate, naphthalene, nitrotoluene, polyaromatic hydrocarbons, styrene, toluene and xylene degradation. Sample obtained post-bioremediation showed significant (P ≤ 0.05) differences in functional genes responsible for benzoate, xylene, ethyl benzene, valine, leucine and isoleucine, nitrotoluene, aminobenzoate and DDT degradation when compared with baseline (pre-remediation), polluted soil (PS) during remediation on days 0, 9, and 29. PCoA revealed that PS on days 0, 9, and baseline had similar functional genes spread while functional genes in PS days 29, 36 and 56 increased progressively with time. The top five known petroleum degrading bacterial phyla identified included Proteobacteria, Actinobacteria, Acidobacteria, Cyanobacteria and Firmicutes. The study area harboured a variety of bacteria with metabolic capacities for pollutant degradation. Functional genes related to petroleum degradation were widely distributed and found to be abundant especially in zones with higher pollution levels. Moreover, the study provided insights into in situ bacterial functional structures in crude oil-impacted site and unraveled the linkages between bacterial communities and environmental variables which are important in the application of bioremediation.
Core Residual Oil Analysis and Integration to the Dynamic Model
Authors: Cruz Mauro , Harrison Peter , Braga Jose , Martins Fernando , Sanuca Carlos 
Published: August 2020

ABSTRACT
Obtaining a core behind the flood front appears to be the most appropriate way to directly measure residual oil saturation. Conventional analysis based on resistivity logs requires the water salinity to be known. As the pore space behind the flood front contains a mix of formation, aquifer and injected water with significantly different salinities, water saturation calculated therefore will have a large uncertainty associated with it.
While e-line NMR and other conventional logs can give indirect estimates of residual saturation without any calibration, Direct measurements to overtake this challenge can only be carried out on a core. In this paper, we present a core behind flood front that was acquired in a BP Angola field. The core analysis provided a direct measure of the residual oil saturation throughout the cored interval providing information about vertical sweep efficiency as well as the value of the residual oil saturation.
The value added through the acquisition of core was considered to have reduced the risk of inefficient oil recovery by:
Understanding the efficiency of the sweep in channel edges Understanding rock properties behind the flood front Direct determination of residual oil saturation. Assuring reserves in place and Remaining Reservoir management strategy by Water injection strategy and Improve understanding of reservoir will lead to better depletion management – targeting of infill wells. Determine tertiary oil recovery techniques. Aid calibration of water and oil saturations in simulation models. Assist with production performance prediction and reduced surveillance. Opportunity to cut a behind the flood front core in channel edges facies (low NTG).
Efficient Formation Testing and Data Interpretation Using Advanced Probes and In-Situ Fluid Property Evaluation
Authors: Frank Søren , Robinson Anna , Ostroff Gary M. , Khong Chee Kin , Dunlap James , Roche Sebastien , Jackson Richard 
Published: August 2020

Abstract
Deepwater environments pose significant challenges in design and execution of comprehensive yet cost effective formation testing programs. For a recent deepwater appraisal well, pre-job modeling, advanced formation testing technologies, and in-situ fluid analysis were utilized to design and execute a formation testing program which provided significant improvement in the quality of data and fluid samples acquired, as well as significantly reduced time required for testing.
Multiple PVT and bulk samples were collected with an advanced focused sampling probe, providing an average pumping time of 3.5 hours per sampling depth with sample contamination as low as 1%. This compared favorably to nearly 9 hours per sample depth, double the volume of fluid pumped, and fluid contaminations of 8-14% observed in the previous appraisal well using an unfocused probe.
The low contamination improved the accuracy of real time Downhole Fluid Analysis (DFA) measurements such as density and viscosity, hydrocarbon composition and GOR performed with an advanced in-situ fluid analyzer. Fluorescence and reflectance detectors within the same tool were used to evaluate fluid phase state.
Another important component of the acquisition were several Interval Pressure Transient Tests (IPTT) performed to evaluate horizontal and vertical permeability. An advanced 3D radial probe was selected over a conventional Dual Packer to perform these tests. The 3D radial probe was more time-efficient, provided better quality buildup data including vertical interference data (VIT), and presented lower operational risk. Real time measurement of fluid viscosity enabled the immediate estimation of permeability. Zonal permeability and permeability anisotropy (kv/kh) for the tested intervals were interpreted from the pressure transient responses of the radial probe and observation probe
Economics and the Energy Sector in Nigeria
Authors: Nwatu Victor Okechukwu , Ezenwa Emmanuel Nnaemeka 
Published: August 2020

Abstract
The study examined the economics and energy sectors in Nigeria by analysing the development of energy sector in Nigeria, which includes crude oil, natural gas, electricity. The work focused on these energy resources; crude oil, natural gas and electricity given that they cover 80 percent of the energy mix in Nigeria. The study gave insight as it concerns dynamics, challenges, and regulation affecting the energy sector with recommendations that can foster economic growth.
Performance Evaluation of Natural Gas Value Chain in Nigeria
Authors: Ojaraida Lolo , Iledare Omowumi , Ajienka Joseph 
Published: August 2020

Abstract
Natural gas resource abounds significantly in Nigeria. Thus, the description of Nigeria as a prolific gas province with pockets of oil is not conjectural. However, little effort in terms of gas exploration and production is evident. This has made the gas sector a focal point with respect to resource development for sustainable energy and national development economy. This paper evaluates natural gas value chain in Nigeria. The purpose is to analyze the relative technical efficiency of the value chain of natural gas industry in Nigeria from 2013 to 2017. Data Envelopment Analysis (DEA), a deterministic tool for assessing the efficiencies of decision-making units, provides the fundamental framework applied to analyze the gas industry value chain in this paper. In addition, in order to incorporate data uncertainty, we adopted the uncertainty DEA plus tool to show that for the period under consideration, none of the gas value chain sector is technically efficient, albeit, in a relative sense. The midstream gas sector is the least efficient, while the downstream export gas sales is the most efficient. The DEA results suggest that for Nigeria to meet her economic growth aspirations and become an attractive gas-based industrial nation, pragmatic policy framework to maximize value creation across the gas chain sectors is required. In addition, harmonizing the domestic gas market and the export gas market will bring about value creation for sustainable national development.
Design of Extrusion Machine for Offshore Corrosion-Control Composite Wrap Material Manufacture
Authors: Adisa Ademola , Olatunji Oladipo , Brando Kenneth 
Published: August 2020

Abstract
From time immemorial, corrosion in the offshore environment of the oil and gas industry has consistently plagued smooth operations by introducing huge costs of corrosion control and non-productive time. The corrosion effect is even more pronounced on Deepwater structures such as pipelines, hull decks, handrails, gangways and so on, due to harsh marine environmental exposure. Due to the deteriorating effect of corrosion, the amount spent on surface protection could range from thousand to millions of dollars depending on the extent of corrosion damage. Apart from the repair costs, some of the offshore operations are entirely shutdown before commencement of corrosion control measures which contributes to production downtime and unscheduled volume loss. In this paper, a composite material is presented that is corrosion resistant and can withstand the expected pressure and temperature conditions in the offshore environment. This material extrudes from a specially designed machine that takes wood and plastic wastes as feedstocks in appropriate ratios depending on the area of application on the facility. Upon laboratory analysis, this material has a melting point of 400degF (204degC), and load testing also revealed that at typical offshore condition of pressure ≅ 50bars and at about 100degC, this material would be very suitable for corrosion control. Furthermore, from an economic standpoint, this composite material is extremely cheaper with a cost of 300 USD per foot of pipeline coating compared to about 2000 USD cost using conventional corrosion control materials. In addition, with the implementation of this process, we have realized that negative environmental contribution of plastic wastes to greenhouse gases (GHGs) will be greatly mitigated, reducing the overall levels to about 10%. In conclusion, a cost effective and an environmentally friendly corrosion protection composite wrap has been developed by recycling wood and plastics wastes.