FUPRESpace
Welcome to FUPRESpace, The Institutional Repository of Federal University of Petroleum Resources. A collection of theses, articles, books, videos, images, lectures, papers, data sets, and all types of digital content originating from the Federal University of Petroleum Resources, Nigeria. This repository is managed by the University Library
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- This houses intellectual collections of Biochemistry Department
- This contains the intellectual works of the faculty members in the College of Computing
- This contains the intellectual works of the faculty members in the College of Engineering and Technology
- This contains the intellectual works of the faculty member in the College of Maritime and Offshore Studies.
- This contains the intellectual works of the faculty members in the College of Science
Recent Submissions
Evaluation of Residual Geo-mechanical Characteristics of Rocks from Akure, Ado Ekiti and Ikare-Akoko Quarries in Southwest Nigeria
(University of Port Harcourt, 2025) Oluwadero, T.A.; Osisanya, W.O.; Ajibade, F.Z.
The objective of this paper is to evaluate the Residual Geo-mechanical Characteristics of Rocks from Akure, Ado-Ekiti and Ikare-Akoko Quarries in Southwest Nigeria using appropriate standard techniques. Data obtained show that residual ultimate compressive strength (UCS) values under in-situ circumstances were, in order, 70.56 MPa, 72.9 MPa, and 76.27 MPa. It was shown that when the concentrations of acid and base in the immersion solution increased, the samples' UCS decreased. Compared to samples with coarser grains, those with finer grains (as determined by the microstructure analysis) retained a comparatively higher UCS value even after being submerged in an acidic and alkaline medium. The samples that were soaked in 0.75M, 1.5M, and 3.0M of acid and base showed varying degrees of deterioration during the second wetting cycle in the water medium, despite not being detected to be damaged during the first cycle. However, the durability was found to decrease much more when the medium was turned acidic and alkaline.
Integration of Heavy Metal Indexes and Health Risk Assessment in Groundwater Studies in Urban Area of Port Harcourt, Niger Delta Region of Nigeria
(Anchor University, 2024) Osisanya, W.O.; Akpeji, B. H.; Agho, I.O.; Saleh, S.A.; Oyanameh, O. E.
The Niger Delta region of Nigeria is faced with a serious environmental hazard from heavy metal (HM) pollution in groundwater, mostly as a result of local oil corporations' operations within the communities and its suburbs.. Physical characteristics such as pH, and Ec, heavy metals (Fe, Pb, Mn, As, Ni, Co, Cu, Zn, and Cr) were measured in 17 groundwater samples that were collected. The influence of heavy metals on groundwater chemistry is revealed by the principal component analysis (PCA) analysis results. According to the child population's dermal techniques, findings showed that 6 % of samples with low risk, 41 % with medium risk, and 51 % with high risk. Yet, 29 % of adults are at medium risk and 71 % of adults pose
insignificant to low risk. According to the evaluated Carcinogenic Risk (CR) scores of the groundwater samples that were considered in this study, there was a very high propensity to effect the development of cancer in consumers, including adults and children. The research area's Heacy Metal Pollution Index ( HPI) ranges from 7.15 to 63.08with an average value of 27.16 according to the HPI data. This suggests that there is generally safe water because the HPI throughout the research area is below 100. Fe was found to be positive in 12 (70.59%) samples (FET/01,02,03,07,08,10,11,12,14,15,16, and 17) and zero in 5 (29.41%) samples (FET/04/05/06/09,13) based on the results of the Quantification of Contamination (QoC).For Ni, 58.82% of samples (FET/01, 02, 03, 08, 09, 10, 11, 12, 14, and 16) had negative QoC
scores, while seven (41.18%) samples (FET/04, 05, 06, 07, 13, 15, and 17) had positive QoC
scores. These findings underscore the urgent need for continued groundwater monitoring and implementation of effective purification technologies before consumption to mitigate health risks associated with heavy metal contamination in the Niger Delta region.. The present investigation concluded that this location's groundwater needed to have its HM level measured
Studies of heavy metal in soil at Omoku, River State, Nigeria, using Pollution Indices and Potential Ecological Risk
(Anchor University, 2024) Osisanya, W.O.; Agho, I.O.; Ovri, A. A.; Eyankware, M.O.
This study used Atomic Absorption Spectrometry (AAS) to measure the levels of heavy metals (HM) in soil affected by oil spills in a few locations in River State, Southern Nigeria, in order to investigate the ecological dangers and pollution status of HM. This study examined the heavy metals iron (Fe), arsenic (As), lead (Pb), mercury (Hg), barium (Ba), vanadium (V), nickel (Ni), copper (Cu), zinc (Zn), and chromium (Cr). The study analyzed the outcomes of a heavy metal risk assessment index, which encompassed the level of contamination, the Geo-accumulation index (Igeo), and the prospective ecological risk assessment (ERI). Findings from the showed that Nemerow Pollution (PNI), Potential Ecological Risk Index (PERI), Degree of Contamination (Cdeg) ranges from 12.64 to 28.26, 2.40 to 518.48, and 17.63 to32.44 respectively. Results obtained from the study are considered to be fairly above the international standard at some locations. Deduction from the study suggested that human activities such farming, oil spillage, solid waste disposal, and automobile workshop were identified to be the primary contributors of heavy metal pollution in the soil (Cdeg) and PNI. As seen by the uncontaminated soil samples and the negligible effect of local human activity on the ERI, the Igeo results run counter to the ERI results. The Cdeg observation indicated that the soil was not very polluted.
MACHINE LEARNING APPLICATION FOR PREDICTION OF POROSITY AND PERMEABILITY LOGS: A CASE STUDY OF O-W FIELD NIGER DELTA
(Zibeline International Publishing., 2025-04) Osisanya, W.O.; Eze, U.S.; Ogugu, A.A.; Uti, L.O.
Predicting the porosity and permeability of hydrocarbon reservoirs is a key part of figuring out how much
fluid is retained and how much moves through them. However, the absence of conventional porosity logs
often complicates these predictions due to factors like borehole instability and logging challenges. This
research looks at how well three machine learning algorithms—Linear Regression (LR), Random Forest (RF), and Gradient Boosting (XGBoost)—can predict porosity and permeability from well-log data in the Niger Delta basin. The well-log data includes gamma ray, caliper, density, and compressional sonic logs. The goal of the study was to create and improve machine learning models that could guess the properties of a reservoir without using traditional porosity logs. To get better results, hyperparameters for RF and XGBoost were tweaked, and the models' work was checked using the coefficient of determination (R²) on training, validation, and blind testing datasets. Results indicated that XGBoost and RF outperformed LR in both porosity and permeability predictions, with R² values reaching 0.94–0.95 for porosity and 0.98–0.99 for permeability in test data. Blind testing further confirmed the robustness of the models, achieving R² values of 0.99 for porosity and 0.999 for permeability. This study adds to what is known in the oil industry by showing how machine learning techniques can be used to accurately predict key reservoir properties. These techniques can be used as a reliable alternative to traditional log data when they are not available, like in the Niger Delta basin. Furthermore, accurate prediction of reservoir properties can optimize operations and reduce uncertainties.
The Use of Acoustic Doppler Current Profiler (ADCP) to Determine the Water Velocity as Related to Sediment Deposition in Epe Lagoon, Lagos State, Nigeria
(European Centre for Research Training and Development UK, 2025-03-24) Iluobe, O.E.; Osisanya, W.O.; Saleh, S.A.
Sediment deposition poses significant challenges to marine transport, aquatic ecosystems, and hydrogeological exploration. This study investigates the integration of Acoustic Doppler Current Profiler (ADCP) data with grain size analysis to estimate sediment deposition velocities in a lagoonal environment. Data from ten ADCP measurements revealed varying velocities, with the highest at 7.70 ft/s and the lowest at 0.99 ft/s. Analysis of ADCP data indicated high velocity zones at depths of 21 to 27 ft and 12 to 19 ft, while low velocities were observed at shallow depths (up to 18 ft) and near the bottom at specific locations. Concurrent grain size analysis identified a predominance of coarse-grained sand, with varying degrees of sorting from moderately well to poorly sorted sediments. The results demonstrated that areas of high sediment velocity are associated with larger grain sizes, whereas low velocity zones correspond to finer grains. This study suggests optimal navigation routes for vessels around the lagoon’s middle and recommends dredging edges to mitigate sediment accumulation. These insights provide valuable guidance for sediment management, coastal engineering, and marine transportation safety.