bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Oil Polarity on Surfactant Foam Properties at Bulk and Macroscopic Scale
Authors: Balakirisnan A. , Jaafar M. Z. , Sidek M. A. , Yakasai F. , Nwaichi P I. , Ridzuan N. , Mahat S. Q. A. , Abbas A. H. , Ngouangna E. , Gbadamosi A. , Oseh J. O. , Gbonhinbor J. R. , Agi A. 
Published: August 2024

Abstract
Recent studies on oil-foam interaction using different types of oil were limited to the aspect of alkane chain length, density and viscosity of crude oil. However, oil polarity toward foam stability to predict the significant variable of the foam half-life and its evaluation in macroscopic oil displacement is still elusive in literature. In this study, the effect of oil polarity on foam properties at bulk and macroscopic scales was investigated. The effect of electrolytes on surfactant foam stability was studied. Subsequently, the foam stability in the presence of polar and non-polar oil was determined. Thereafter, the macroscopic oil displacement efficiency of surfactant foam was evaluated. Finally, a multivariate linear regression analysis was used to predict the significant variable of the foam half-life. The results indicate that cocamidopropyl betaine (CAPB) foam had better stability under the influence of oil polarity, with a half-life decrease of 8% in hexane oil compared to 86% by sodium dodecyl sulfate (SDS). Moreover, SDS foam flooding recovered 10% additional oil compared to 5% CAPB foam. However, oil recovery in the presence of pyridine decreased oil recovery of SDS and CAPB foam flooding to 6% and 3%, respectively. Likewise, mobility reduction factor (MRF) of SDS foam decreased by 74% compared to 39% by CAPB foam. However, both MRF of SDS and CAPB foam drop drastically by 81% and 90%, respectively in the presence of pyridine compared to hexadecane. Finally, the multivariate regression analysis indicates that surfactant is the most significant variable with a P value below 0.0001. The R2 proportion of variation in the response attributed to this model was 0.81, with a root mean square estimation of 5.2386.
Biohydrogen Production: A Review of Current Trends and Future Prospects
Authors: Umunnawuike C. , Mahat S. Q. A. , Ridzuan N. , Gbonhinbor J. , Agi A. 
Published: August 2024

Abstract
Growing concerns regarding climate change and fossil fuel depletion have spurred the development of clean and sustainable energy sources. Biohydrogen, a carbon-neutral fuel produced using biological processes, has emerged as a promising alternative to traditional fossil fuels. This review delves into the diverse landscape of biohydrogen production methods, encompassing light-dependent (photolysis, photofermentation) and light-independent (dark fermentation, microbial electrolysis) techniques. The study analyzes the advantages and limitations of each approach, exploring strategies for integrating these methods to enhance biohydrogen yield and optimize production efficiency. Additionally, the study discusses the critical role of various factors, including microbial selection, substrate utilization, and operational parameters, in maximizing hydrogen output. Furthermore, it assesses the potential of novel strategies like biomimetics and synthetic biology to further advance biohydrogen production. Finally, this study will showcase the economic considerations and challenges associated with large-scale biohydrogen production, outlining practical approaches for overcoming these hurdles and paving the way towards a sustainable future powered by biohydrogen.
Rheological and Filtration Property Enhancement of a Water-Based Drilling Mud Using Modified Graphene Nanoplatelets Derived from Kenaf Stem
Authors: Yahya M. N. , Norddin M. N. A. M , Ismail I. , Rasol A. A. A. , Oseh J. O. , Mohammed U. , Yakasai F. , Umunnawuike C. , Gbonhinbor J. , Agi A. 
Published: August 2024

Abstract
Drilling fluids’ rheological and filtration qualities have been discovered to be improved by graphene nanoplatelets (GNPs). Research has demonstrated that adding GNPs to water-based mud (WBM) can enhance its plastic viscosity (PV), yield point (YP), gel strength (GS), filtration loss (FL), and filter cake thickness (FCT). Their small particle size, excellent material dispersion, and thermal stability are the reasons behind the usage of GNPs in drilling fluid. Here, GNP from Kenaf stem was synthesized, and its surface was modified with nonionic surfactant triton-X100 to improve its dispersion in aqueous media. The synthesized nanomaterials were subjected to particle size distribution (PSD), energy dispersive X-ray analysis (EDX), and zeta potential analysis to confirm their elemental content, stability, and particle size. Critical analysis and a comparison of the properties of surface modified GNP (GNT) and synthesized GNP from Kenaf (GNK) were conducted in WBM formulations. The materials are stable, according to the zeta potential study, although the EDX results showed that surface modification reduced the oxygen-containing group in GNT. Better rheological properties were obtained by adding the synthesized materials to WBM as an additive. PV increased from 13.5 to 17cp, YP increased from 31 to 40 lb/100ft2, FL control performance improved from 12mL to 6.5mL, and FCT decreased from 2.60 to 1.20mm. It has been discovered that adding GNT to WBM enhances its rheological and filtration properties more effectively than adding GNK, which makes it a viable inclusion for drilling operations.
Revisiting Troubleshooted Drill Stem Test: Methodological Framework Incorporating Artificial Intelligence
Authors: Abbas A. H. , Serikov G. , Zhuniskenov Y. , Serikkali A. , Nyah F. , Ridzuan N. , Gbonhinbor J. , Agi A. 
Published: August 2024

AbstractDrill Stem Testing (DST) plays a crucial role in the petroleum industry, particularly in understanding a formation's behavior under production conditions. DST is instrumental in identifying critical reservoir engineering parameters such as permeability, skin factor, anisotropy, and vertical connectivity. These techniques are crucial for understanding reservoir behavior, optimizing production strategies, and making informed decisions regarding reservoir development. Despite its significance, DST faces challenges, primarily relating to the accuracy and reliability of the data obtained. The integrity of the data collected during DST is crucial, as inaccurate data, possibly resulting from fluctuated readings, can lead to suboptimal field development decisions. Many software offers pressure tie options to avoid errors if the data is not precise and reliable. Yet, the challenge is in the selection of effective data processing and analysis. The current study offers a detailed evaluation of DST data, using Kappa Software and analytical models, to assess permeability, pressure, well performance, and reservoir characteristics. The study incorporates the potential integration of Artificial Intelligence (AI) to enhance pressure reports as a preprocess analysis tool. AI applications could revolutionize DST data interpretation by quickly processing large datasets, identifying patterns, and providing accurate reservoir estimates. The methodological framework offers time reduction and improved noise filtering which leads to enhanced predictive insights into reservoir behavior. The use of AI in DST analysis promises a better use of noisy and troubleshooted DST data.
Snail Shells as Sustainable Remediation Agents: A Novel Approach to Removing Heavy Metals from Produced Water in the Oil and Gas Industry
Authors: Alumonah J. A. , Emeke C. , Ehihamen P. E. , Igwegbe C. A. , Onyechi K. 
Published: August 2024

Abstract
Global environmental standards mandate Oil and Gas producers to treat Produced Water (PW) before disposal. This can pose an economic conundrum as PW's low economic value does not justify the high cost of treatment.
This study explores the use of the adsorption capabilities of Achatina fulica snail shell particles in eliminating heavy metal contaminants from PW thus providing a better alternative without compromising industry standards. Through comprehensive optimization using response surface methodology and central composite design, various adsorption parameters such as temperature, adsorbent dosage, contact time, pH, and lead concentration were examined on wastewater samples. Lead nitrate content was measured as a heavy metal contaminant. The snail shell adsorbent underwent thorough characterization employing Scanning Electron Microscope (SEM), Energy- Disperse X-ray (EDX) analyses, and Fourier Transform Infra-Red Spectroscopy (FTIR). Atomic Absorption Spectrophotometry was employed for heavy metal analysis. Response Surface Methodology was employed to evaluate the adsorption of lead (II) ions on the bioadsorbent.
The snail shell bioadsorbent exhibited a composition rich in various organic compounds and results indicated that lead ion removal positively correlated with increasing lead concentration and pH, inversely correlated with escalating snail shell dosage, and exhibited a slight decrease with contact time. Furthermore, optimal conditions for achieving a 99.3167% adsorption percentage of lead ions were identified. This study underscores the sustainable nature and efficacy of snail shells as a remarkable adsorbent for mitigating heavy metal contamination, particularly relevant to the challenges posed by heavy metal contamination in produced water in the oil and gas industry.
Investigating the Optimal Conditions for Heavy Metal Removal from Oilfield Wastewater by Activated Carbons Using Response Surface Methodology
Authors: Ogidi Samuel , Yusuf Mistura , AYODELE EMMANUEL , Aladeitan Yetunde , Sanni Khadijah 
Published: August 2024

Abstract
Oilfield wastewater, also known as produced water, presents an environmental concern due to its high concentration of heavy metals. Effective treatment strategies are necessary to address this issue. In the Niger Delta oilfields and refineries, produced water is a waste stream containing hydrocarbons, heavy metals, and other pollutants. This research focuses on utilizing Response Surface Methodology (RSM) to optimise metals’ adsorption process using activated carbon. Activated carbon is well known for its ability to adsorb various substances. It is being explored for its potential to reduce heavy metal pollutants from the wastewater of the Field X oilfield. To enhance the adsorption capacity, coconut husk-based activated carbon is modified with oxide, an emerging material derived from graphite using the "wet impregnation technique." A systematic experimental design is employed to analyze how various factors influence adsorption. The data obtained is then subjected to response surface methodology (RSM) using Design Expert software for analysis. This study considers factors such as adsorbent dosage, contact time and temperature. The significance and impact of these operating factors on the removal percentage (%) of pollutants will be tested using ANOVA (analysis of variance) with a correlation coefficient (R2) while maintaining a significance level of p &lt; 0.05. The adsorption efficiency was determined by measuring final concentration, with a 93.59%, 99.01% and 96.38% reduction observed for Nickel, Cadmium and Lead respectively. The concentration values decreased from 0.6121 to 0.039 for Nickel, 0.9067 to 0.009 for Cadmium and 2.9044 to 0.104 for Lead. The findings from this study provide efficient approaches to tackle the environmental issues linked to heavy metal pollution in oilfield wastewater from field X. This will contribute towards promoting practices in the Nigerian oil and gas industry.
Effect of Oil Price on Carbon Dioxide Flooding of a Marginal Well
Authors: Ibe A. P. , Nwosi-Anele A. S. 
Published: August 2024

Abstract
The effects of oil price on the production of oil wells cannot be overstated especially in Nigeria where many wells are currently being termed marginal wells by the NUPRC and cannot be produced with primary recovery and soon enough even secondary recovery won't be enough to economically produce oil. This work aims to check the economic viability of CO2-enhanced oil recovery on marginal wells at different oil prices (current, high, and low). Using Eclipse software, CO2 injection in a marginal well was simulated. The resulting production data was put in an economical model at the three different oil prices and the breakeven oil price was found to be $48.59. A Monte Carlo risk analysis was carried out with 1000 iterations of randomly generated oil prices resulting in an average NPV of $364.84MM, the cash at risk of 95% resulted in $557.09MM and the probability of breaking even at the current fiscal regime and operating expenditure was 89%. A sensitivity analysis on the effect of certain parameters (Oil price, CO2 Cost, CAPEX, field OPEX) on the net present value was carried out to understand the components whose change would impact profitability the most, it was seen to be oil price. In conclusion, it was seen that while the oil price is the most crucial factor to be considered it is not the only factor, and as such cost-saving measures need to be applied in the field of OPEX. This work contributes to the existing work of the past by adding the use of CO2-enhanced oil recovery on a marginal well and checking its viability economically. However, further work can be done on this to improve the accuracy of the economic model.
Annular Velocity Effect on the Lifting of Sandstone Cutting Particles in Inclined Rotating Wellbore Pipes using Novel Hydroxyapatite Nanoparticles
Authors: Oseh J. O. , Norddin M. N. A. M. , Duru U. I. , Ridzuan N. , Onyejekwe I. A. , Odo J. E. , Ngouangna E. N. , Ismail I. , Gbadamosi A. O. , Yahya M. N. , Gbonhinbor J. , Agi A. 
Published: August 2024

Abstract
Deviated wellbore regions make cutting transport harder owing to the substantially low annular velocity distribution in these regions. This causes migrating cuttings to deposit on the lower borehole wall, creating cutting beds and thus resulting in drilling problems like pipe sticking. Water-based mud (WBM) that includes nanoparticles (NPs) to remove cuttings still needs further investigation due to the substantial drop in annular velocity of the mud in inclined boreholes. This research, therefore, employed a nanohydroxyapatite (nanoHAp) additive to improve the properties of WBM, including its cutting transport ratio (CTR). All the fluid performances of nanoHAp were compared with those of aluminium oxide NPs (nano-Al2O3). An inclined cutting rig simulator of 4.88 m long, 0.0609 m ID, and 0.0305 m OD was constructed. 0.4–2.0 g of nanoHAp and nano-Al2O3 were used to clean cutting particles that were 0.80–3.60 mm in diameter and at velocities of 1.5, 2.5, and 3.5 m/s and 120 rpm. The pipes were deviated at 40°, 50°, and 60°. The results indicate that nanoHAp particles are mostly 70–600 nm in size and thermally stable at 750 oC. Additionally, the fluid consistency index demonstrates that nanoHAp and nano-Al2O3 increased the viscosity of WBM of 2.114 Pa. s by 15 to 130% and 5.7 to 94.3%, respectively. Also, nano-HAp concentrations decreased the WBM fluid loss from 9.4 mL to 8.1–5.4 mL, and nano-Al2O3 concentrations decreased it to 8.9–8.2 mL. The CTR of all the fluid samples improves with an increase in concentration and annular velocity at all hole angles. NanoHAp increased the CTR by 10.0% to 31.4% at all concentrations, hole angles, and annular velocities, while nano-Al2O3increased it by 4.0% to 27.1%. A higher percentage of CTR was observed with pipe rotation compared to without pipe rotation. The drill pipe's orbiting motion and increasing axial velocity distribution have a positive effect on CTR. Compared with 40° and 60° deviations, 50° wellbore cuttings are the most difficult to clean, while 40° wellbore is the easiest. This research highlights the advantages of nanoHAp over industrial-based nano-Al2O3, offering options for selecting nanoHAp for drilling operations.
Strategies for Commercializing Compressed Natural Gas in Nigeria
Authors: Oruwari Humphrey , Obunwa Queen , Ahuchogu Joe 
Published: August 2024

Abstract
In this era of energy transition there is the need to commercialize the use of compressed natural gas (CNG) in Nigeria due to low carbon emission it generates. The widespread use of CNG as automotive fuel will serve as a transition fuel for sustainable energy transformation in Nigeria. Compressed Natural Gas (CNG) was first utilized as an automotive fuel by NNPC Ltd Gas Infrastructure Company (NGIC} a subsidiary of Nigerian National Petroleum Company Ltd under a pilot scheme over thirty (30) years ago. This scheme was part of NGIC's strategic efforts at promoting natural gas utilization and expanding the revenue base of the Company through commercialization of CNG. Despite NGIC's efforts, CNG is yet to be fully commercialized. The qualitative research method was adopted. Data for the study were collected through literature review and multiple case study of emerging countries that have promoted commercialization of CNG. Based on the analysis of the data and records, it was discovered that the target market for CNG is yet to be clearly defined. No economic incentive exists for vehicle conversion and establishment of CNG refueling stations. Cooperation between NNPC Gas Marketing Limited (NGML) and gas distribution companies which is critical in providing cost-effective gas infrastructures for CNG commercialization is nonexistent. In view of the above findings and conclusions, it is recommended that policy makers should: Promote the development of on-site refueling stations and/or locate public stations as close as possible to fleet vehicle owners. Partner with gas distribution companies through attractive revenue sharing (e.g., 50/50 split) as a strategy for promoting CNG market. Target fleet vehicles particularly those owned by existing gas users. Sell gas to CNG refueling station at a price lower than petrol price to encourage private investment in the station.
Production Forecasting in Gas Lifted Wells using Interpretable Machine Learning Techniques
Authors: Isehunwa S. O. , Awojinrin G. T. , Oluwatayo P. 
Published: August 2024

Abstract
Traditional techniques, such as decline curve analysis (DCA) and material balance, are industry-accepted standards for evaluating reservoir performance and estimating developed reserves. However, while these methods are reliable for estimating well productivity under natural flow conditions, accurate evaluation of gas lifted wells can be challenging due to the additional energy injected to augment mthe natural flow. Although attempts have been made to model gas lifted wells using machine learning (ML) techniques, these models provide little or no interpretability, thereby offering no clues to the underlying physical interactions behind their predictions. To address this issue, an empirical correlation was developed to predict gas lifted oil production rates using interpretable non-linear regression ML models.
Production data from four wells were obtained from literature, encompassing production periods both with and without gas lift. A Python program was written to train the ML models. A ridge regression model was trained on production data from three of the wells using this program. The coefficients and intercepts of the resulting model were extracted to generate an empirical correlation and its predictive performance was then statistically analyzed.
The performance of the derived empirical correlation was validated using production data from a new well, exhibiting a correlation coefficient of 0.96 and a root mean squared error of 27.55 STB. Analysis of predicted production rates under both natural and gas lifted flow conditions indicated that proper utilization of gas lift can increase developed reserves under natural flow by as much as 200%. The predicted production life of the well also increased significantly from 28 months under natural flow to 48 months with gas lift.
A non-linear empirical correlation has been developed and tested to predict the oil production rate in gas lifted wells. With slight modifications, this correlation and the workflow implemented here can be applied to other wells, providing a practical tool for forecasting oil production rates not only in gas lifted scenarios but for other artificial lift methods as well.
Design and Execution of Deepwater Jetting Operations – A Correlative Design Approach
Authors: Sakpa Ogaga , Igbeka Uche , Ojubanire Damilola , Okoli Ugo’ , Okwa Hope 
Published: August 2024

Abstract
Conductor jetting operations in deep water are vital in offshore drilling to securely install conductors and prevent subsidence. This paper details the meticulous procedures employed to ensure the successful jetting of conductors to the seabed for a deep water well in the offshore region of the Niger Delta in West Africa.
With meticulous planning, considering factors such as seabed composition, water depth, and conductor specifications. There were no advanced simulation tools to aid in predicting the ideal jetting parameters, thus the methodology employed in this study relies on non-site-specific data, calibrated through information/data obtained from the Gulf of Mexico.
During the operation, precise control and monitoring of jetting parameters are pivotal. Continuous monitoring of penetration depth, fluid pressure, and soil response facilitates real-time adjustments to optimize the jetting process. The application of appropriate back pressure assists in creating the requisite skin of friction, ensuring secure placement of the conductor.
Post-installation assessments, which include the confirmation of conductor alignment and embedment, are conducted to verify the integrity of the installed conductor. Additionally, long-term monitoring systems are often implemented to track subsidence and ensure the stability of the conductor installation over time.
This paper details the comprehensive procedures and stringent protocols integral to conductor jetting operations in deep water. The meticulous planning, precise execution, and post-installation assessments collectively contribute to ensuring the successful installation of conductors while mitigating the risks of subsidence, in challenging deep-water environments.
It also confirms that with the use of the right data set and correlation, it is possible to produce an efficient design.
Cost Benefit Analysis of Solar Panel System in Residential Buildings in Sokoto State, Nigeria
Authors: Stephen S. O. , Ataundaolu O. E. , Ikirigbe O. 
Published: August 2024

Abstract
In Nigeria, the current state of inadequate power supply necessitates the search for alternative energy sources. The urgency lies in finding a solution that is both clean and renewable, promoting green and sustainable development. This study focuses on evaluating the cost benefit of solar energy for residential buildings in Sokoto State, Nigeria. To assess the feasibility of solar energy, global solar radiation, clearness index, and sunshine hours based on analyses of weather conditions in Sokoto State were considered in the analyses. Notably, August exhibited the lowest solar radiation levels.
Quantitative analysis was conducted to ascertain the viability of solar panel systems as an energy solution for residential buildings in Sokoto State. Over a projected 25-year lifespan of the solar panels, the cumulative output production is estimated at 54.54 terra-watt hours. The return on investment (ROI) is calculated at an impressive 209%, indicating a payback period of just 9-10 years. Additionally, compared to other renewable energy sources, solar energy in residential buildings in Sokoto State stands to save more money, with a revenue of $3.55 billion. These findings highlight the significant potential and economic benefits of adopting solar power in Sokoto State. By embracing renewable energy solutions, Nigeria can address its pressing power supply challenges while fostering a sustainable and environmentally friendly future.