bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unraveling Complex N-Paraffin Mixtures: T-Sep Method and Blended Polymer Base Wax Inhibitor for Resolving Wax Deposition in Pipeline
Authors: Makwashi N. , Yahya M. N. , Abdulkadir M. , Garb M. U. 
Published: August 2024

Abstract
Wax deposition, particularly in cold environments, poses a significant challenge in the oil and gas industry, often leading to solid blockages within pipelines. Chemical inhibitors have emerged as effective mitigation strategies, yet no single inhibitor can address all types of crude oil. This study investigates the performance of a novel blended polymer-based wax inhibitor in preventing precipitation and deposition in a pipeline flow rig with varying curvatures. Prior to the flow rig study, the composition of waxy crude oil was analyzed using the T-SEP® technique, enabling precise quantification of n-paraffin distribution and wax content, thereby resolving complex mixtures. Various commercial chemical inhibitors underwent initial screening, comparing properties such as pour point, wax appearance temperature, crystal morphology, and viscosity. Experiments conducted at different concentrations (500, 1000, 1300, 1500, and 1800 ppm) demonstrated a significant reduction in wax deposition. Specifically, at 1500 ppm concentration, 80% of the wax deposition problem was mitigated under adverse conditions of 15°C. At a higher temperature of 25°C (pour point) and a lower concentration (500 ppm), 100% wax prevention was achieved. In the laminar flow regime, 100% wax deposition prevention was observed at higher concentrations of 1000 and 1500 ppm at 30°C. These results highlight the promising performance of the blended polymer-based wax inhibitor in addressing wax deposition challenges in pipeline systems, highlighting the efficacy of the T-Sep method in resolving complex mixtures.
Reservoir Facies Heterogeneity Characterization: An Implication for Carbon Dioxide (CO2) Geo Sequestration Site Selection in the Akos Field Coastal Swamps Niger Delta
Authors: Muhyideen H. , Umaru A. O. , Abubakar M. T. 
Published: August 2024

Abstract
This study focuses on the characterization of the structural and stratigraphic heterogeneity of Cretaceous reservoirs within the Akos field using integrated seismic and well logs datasets. The main objective is to identify potential reservoir sands for effective CO2 sequestration. Using petrophysical analysis, fault modeling, and geostatistical methods, a comprehensive 3D facies and petrophysical property model was developed to understand the distribution of reservoir heterogeneity and its potential impact on CO2 sequestration. The study then utilizes the constructed 3D static model to analyze the spatio-temporal distribution of reservoir properties, particularly facies, porosity, and permeability, and their predictive influence on the performance of CO2 geo-sequestration projects in the reservoir case study. The performance of the projects was assessed using metrics such as storage capacity and fluid flow behavior during sequestration. This research investigated reservoir formation heterogeneity and its potential for CO2 sequestration in the field. The analysis focuses on four deep reservoirs within the Agbada Formation (Reservoir G, H, I, and J). These reservoirs have shown varying porosity, permeability, and water saturation across the field. The results obtained from this study indicate that the Akos field exhibits relatively high porosity and permeability reservoirs with moderate heterogeneity, and high structural stability, which makes it a suitable and low-risk area for CO2 sequestration, utilization, and storage (CCUS).
A Review on Innovative Methods of Plastic Waste-To-Energy Conversion for Sustainable Development
Authors: Adizue F. C. , Fidel-Anekwe T. H. , Osuofia A. C. 
Published: August 2024

Abstract
Millions of tons of plastic waste are generated annually, and it takes an astonishing 450 years for plastic to decompose. In Nigeria, tonnes of solid waste, including plastic, end up in landfills each year. Environmental pollution is aggravated by plastics pumped into drainages and water bodies. The accumulation of non-degradable waste worsens the impact of climate change and threatens environmental sustainability. Additionally, a significant percentage of plastic waste remains unrecycled. To address this, technologies converting plastic waste into energy have been developed. This study reviews these methods, presenting plastic waste as a renewable energy source. The aim is to diminish environmental waste impact and curb greenhouse gas emissions in line with sustainable development goals.
Advancing Drilling Safety: Automated Anomaly Detection in Well Control Using Machine Learning Techniques
Authors: Ifenaike A. O. , Oluwadare O. B. 
Published: August 2024

Abstract
The rise of anomalies like kicks, blowouts, lost circulation, and gas migration in drilling operations poses significant challenges to safety, environmental sustainability, and economic stability. Implementing frameworks for proactive monitoring and accurate anomaly detection is crucial to maintaining wellbore integrity, ensuring personnel safety, and minimizing environmental impact. This need is particularly acute in complex drilling environments, marked by intricate subsurface conditions and high costs, where unchecked anomalies can lead to severe consequences. Accordingly, this research emphasizes the importance of swiftly identifying and classifying such events, enabling timely interventions to prevent catastrophic outcomes and operational disruptions. This study introduces a multi-layered predictive model that effectively identifies and classifies well control anomalies, addressing the challenge of high false positive rates associated with existing research literature. This study utilizes a comprehensive dataset of historical well control incidents, including indicator parameters such as mud return rates, drilling fluid properties and wellbore pressure. The intelligent model is highly interpretable and outperforms existing counterparts in blind tests with a precision score of 0.918 and a low false positive rate of 2.38%, marking a significant advancement in intelligent anomaly prediction for drilling safety. This research improves traditional well control methods, which depend on equipment monitoring and slower responses, by employing real-time data analysis and machine learning. This shift provides drilling engineers with an advanced tool, enhancing safety and efficiency, and paving the way for more predictive and agile operations.
Effective Management of Electric Submersible Pumps: A Predictive Failure Analytics Approach
Authors: Shittu Ismail A. 
Published: August 2024

Abstract
Electric submersible pumps (ESPs) are considered one of the most widely used artificial lift methods. ESPs exhibit failures due to scale deposition, broken shafts and electrical causes. These failures leads to production interruptions that amount to thousands or millions of barrels of deferred oil production annually. The logistics of replacing an ESP is a complex and lengthy process and can affect well production and overall field economics. The ability to accurately detect the damaging events and anomalies that limit ESP run life is very helpful in making proactive operational decisions, workover scheduling and priotization, and reduce revenue loss. Although, ESP sensors, data collection and communication systems have improved in recent years, the industry still lacks a system that can monitor ESP health condition with the capability to accurately predict impending ESP failures. This paper presents a methodology using advanced machine learning to deploy neural network and extreme gradient boosting tree (XGBoost) in order to analyze real time sensor data to predict failures in ESPs. It provides a high degree of accuracy on historical ESP failures and contributes to an efficiency increase by cutting down on the time required to dismantle the pump system, inspect it and conduct failure analysis. The objective is achieved by applying the neural network model and its output is pipelined with an XG Boosting model for further prediction of the system status. This model is built on the previous ML approach used to detect emerging ESP failures, the Principal Component Analysis (PCA). PCA is used as an unsupervised Machine learning technique to identify hidden patterns and as a pre-processor for other algorithms. This PFA model is able to identify deeper functional relationship, dynamic changes and longer-term trends inferred from historical data with 80% precision and 60% recall on failures, and 15% false alarms. This paper describes how ESP monitoring and an enhanced predictive failure analytics approach increase production efficiency and eliminate deferments caused by ESP failures.
Evaluating the Potential of Natural Gas in Achieving the Nigeria Energy Transition Plan
Authors: Iwuchukwu E. E. 
Published: August 2024

Abstract
Carbon dioxide is a greenhouse gas that causes climate change. According to the Global Carbon Budget (2022), Nigeria ranked fourth in CO2emissions (136,986,780 tonnes) in Africa. Such high carbon emissions have exacerbated the effects of climate change in Nigeria. Increase in temperature, a result of climate change, is affecting millions of Nigerians without access to electricity and alterations in precipitation patterns threaten an under-performing agricultural sector. Desertification in the north and an increase in flooding incidents emphasized the need to reduce carbon emissions. Consequently, the Nigeria Energy Transition Plan (ETP) was launched in 2022 to reduce emissions in 5 key sectors: power, cooking, oil and gas, transport, and industry. According to the Nigeria ETP released, these sectors account for about 65% of Nigeria's emissions. Ultimately, aiming to achieve carbon neutrality by 2060.
This paper adopts an analytical model to determine the best strategy to implement natural gas in reducing emissions in the most carbon-intensive sectors according to the Nigeria ETP: power (48MtCO2e), transport (43MtCO2e), and cooking (40MtCO2e). Relevant data from the largest consumers of natural gas were extensively analyzed to evaluate the potential and efficiency of natural gas in reducing emissions in the power, transport, and cooking sector.
The results confirmed the potential of natural gas in reducing emissions in the power sector. The findings were adapted to Nigeria's energy consumption data to provide an alternative plan to reduce emissions in the transport and cooking sectors by optimizing natural gas utilization in the power sector. Hence, achieving the Nigeria Energy Transition Plan. With the huge investment required to achieve the Nigeria Energy Transition Plan, this study could provide an economical alternative to achieve carbon neutrality by reducing emissions in the transport and cooking sectors through improving natural utilization in the power sector.
Ensemble Machine Learning for Real-Time Sonic Log Prediction in Geothermal Exploration
Authors: Anthonio Umeh , Okereke Ndubuisi , Vincent Nwala , Blessing Ekeh 
Published: August 2024

Abstract
Geothermal energy represents a sustainable and renewable resource with the potential to significantly contribute to the global energy demand Manzella, 2017. Accurate subsurface characterization is essential for successful geothermal exploration and reservoir development. Sonic logs, providing information about subsurface rock properties and formation mechanics, play a crucial role in this characterization process. However, in real-time geothermal exploration, the traditional method involving the use of sensors is most times affected by the high subsurface temperature conditions, thereby returning missing sonic log values for some important depth intervals Joshi et al., 2023. Hence, in this study, an ensemble machine-learning approach was adopted for the real-time prediction of Sonic compressional (ΔTc) and Shear (ΔTs) logs. The ensemble method involved specifically, the Random Forest (RF), K-neighbors (KN), and support vector (SVM), to predict missing sonic log values Dietterich, 2000. By leveraging data from the Utah Forge project, input parameters such as Depth, Cartridge temperature, Caliper, Gamma-ray, Generalized Borehole temperature, Intermittent transit time, and Poison's Ratio Ma, 2019 were used to build the prediction model. The R2 and Root Mean Squared error (RMSE) were used as evaluation metrics between the predicted values and actual values. The results indicated that the developed sonic log models had good generalization on the test data set, as each individual models showed high R2 score above 0.9 and lower RMSE below 0.1, further optimization using ensemble voting regression indicated improved accuracy in model performance as overall R2 score and RMSE values rose above 0.9 and further below 0.01 respectively. In general, the SVM showed better accuracy in model performance on test data. Hence, the result of this study provides insights into the application of machine learning in the prediction of sonic logs and helps provide other associated inferences that can guide the decision-making process for geothermal drilling operations.
New Environmentally Improved Demulsifiers for Nigerian Oilfields
Authors: Oskarson Hans , Vieira F. , Dos Santos A. , Gogo U. , Janwoski S. 
Published: August 2024

Abstract
Resolving oilfield emulsions is crucial for downstream oilfield operations. Inefficient water separation from crude oil escalates production costs and can lead to issues like increased corrosion and limited capacity. In practice, chemical treatment using demulsifiers is one the most effective method for phase separation. Traditional demulsifiers often incorporate a mix of EO/PO (Ethylene Oxide/Propylene Oxide) based elements, phenol-formaldehyde resins, and diepoxides. However, due to stricter environmental and safety regulations, such as OSPAR (Oslo & Paris Convention) or similar ones in certain West African countries, there's a push for more sustainable oilfield solutions. In recent years, the industry has seen a rise in less harmful, environmentally friendly alternatives. These alternatives, built on biodegradable blocks with low aquatic toxicity, have less environmental impact. However, their application can be challenging due to cost, performance, and implementation issues.
Over the last few years, we have successfully developed a new range of demulsifier intermediates as sustainable alternatives to traditional demulsifier chemistries fulfilling regulatory requirements for offshore and onshore use. Apart from sustainable building-blocks the new demulsifiers are produced using a novel process, resulting in an improved cost-performance ratio.
In this article, we share the results of dehydration studies on North Sea, American, and Nigerian oil emulsions using our newly developed, environmentally friendly demulsifiers. We also demonstrate the outstanding dehydration treatment achieved by combining traditional EO/PO block polymers or resin-based demulsifiers with our innovative drier demulsifiers. Showcasing their synergistic effects.
Obtained results from the above three testing scenarios provided a good insight on the improvement of the water separation speed/time by more than 30%, synergic combination of newly developed demulsifiers had also an exceptionally good impact on the separated water quality.
We conducted classic demulsification tests to evaluate the performance of our newly developed formulations in various bottle testing scenarios. We will present the performance comparison of this new range of demulsifiers against, and in combination with, traditional demulsifiers under different conditions.
Exploring a Diversity of Inhibitor Chemistries to Address Oilfield Corrosion Challenges
Authors: Hellberg P. , Vieira F. , Taleat Z. , Moghaddam R. Nazari , Pangilinan K. , Santos A. Dos , Mostafa A. , Gogo U. , Oskarsson H. , Jankowski S. 
Published: August 2024

Abstract
Asset integrity issues related to corrosion during oil and gas production present significant challenges, including the risk of sleaks, operational shutdowns, and expensive repairs. To mitigate these risks, a comprehensive analysis is crucial to determine the optimal approach for corrosion protection. This article delves into the multifaceted challenges of corrosion inhibition in the oil and gas industry, exploring the most effective chemical solutions to meet these demands. The complexities of these challenges span various areas such as sweet and sour corrosion, severe brines, extreme temperature variations, high flow rates, multiphase flow, and diverse compatibility issues. Furthermore, there is an escalating demand for corrosion inhibitors that comply with certain environmental criteria like OSPAR. These features enable their use globally in ecologically sensitive areas, including the offshore regions of West Africa and subsea environments. We examined a total of six corrosion inhibitor chemistries, including two types of imidazolines, two types of phosphate esters, and two versions of a new class of amine–based oligomeric inhibitors. Additionally, we collected representative test data derived from different testing techniques for each of the chemicals studied. Moreover, we explored the potential to combine certain types of inhibitors to further enhance performance, illustrated by realistic examples. This approach was enabled by a wide array of testing capabilities, allowing us to evaluate the effectiveness of various corrosion inhibition methods under diverse conditions. These testing capabilities were crucial in the continuous quest to improve the durability and longevity of assets in the oil and gas industry. The summarized lab results offer valuable insights into the effectiveness of each chemistry type for each field condition or application assessed, providing a solid foundation for our future endeavors.
The Effect of Stakeholders Engagement on Corporate Social Responsibility Project Sustainability in Niger Delta
Authors: Oruwari Humphrey Otombosoba , Obunwa Queen , Ahuchogu Joe , Ayuba Salihu 
Published: August 2024

Abstract
The engagement of stakeholders affects project outcome hence it is believed that when the stakeholders has a stake in the corporate social responsibility process that the project will meet its set objectives and be sustainable. The objective of the study was to establish the effect of stakeholders engagement on corporate social responsibility projects in Niger Delta. Stakeholders engagement focused on inclusion on project identification, planning, implementing, monitoring and evaluation. The guiding framework of the study was anchored on the theory of system, stakeholders theory and contingency theory. The study methodology involve literature review and multiple case study of corporate social responsibility projects carried out by oil and gas Companies in Niger Delta region. Data was collected and analyzed thematically. The finding of the study revealed that the stakeholders were involved in the determination of the project site. there was consultation in determining the the site of the Corporate social responsibility project, timelines were agreed upon by the stakeholders, funds were released based on progress made and there were regular site visit. Also, it was revealed that stakeholders engagement in project identification, project planning, project implementation, project monitoring and evaluation contributes to sustainability of corporate social responsibility projects in Niger Delta. From the findings it was concluded that increased engagement of stakeholder in every aspect of corporate social responsibility project process enhanced the project sustainability. Based on the finding it is recommended that the stakeholders particularly the beneficiary should be included in all aspect of the project.
Friction Reducers in Alpha-Beta Gravel Packs: A Solution to Successfully Packing Narrow Fracture Window Wells
Authors: Deniga B. , B. Djouli L. , Beldongar M. 
Published: August 2024

Abstract
Openhole gravel pack completions excel in unconsolidated regions due to their high flow area and efficient recovery with a low drawdown. Openhole water packing, utilizing low-viscosity brines for proppant transport, relies on swift local velocities. In horizontal wells, the process unfolds in alpha and beta waves, depositing proppant from heel to toe and vice versa. This work explored, assessed, and implemented a solution to pressures related to the beta wave in openhole water pack completions, mitigating formation fracturing and incomplete packing.
Reviewing previous gravel pack downhole gauge data revealed pressure limitations during the beta wave, hindering complete annular packing in the open hole. Several pressure management options were considered, including pumping at lower rates (risking proppant settling and premature screenout), using lighter proppant, employing smaller washpipe, limiting openhole length (sacrificing recovery potential), and utilizing a friction reducer. Friction reducer proved to be effective in reducing beta wave friction pressure without compromising the well's potential or encountering the mentioned issues.
Two 8.5-in. inside diameter horizontal openhole wells, each with a length of 1,000 ft, were successfully completed with thorough annular packing. The gravel pack operations were considered successful, delivering the proppant design volume downhole without any signs of formation breakdown. The gravel pack carrier fluid exhibited favorable rheology, facilitating normal alpha and beta wave deposition, as reflected in corresponding pressure signatures.
In both cases, there was no formation breakdown, achieving a hard screenout surface pressure and successful proppant delivery. Subsequently, 29 additional openhole water packs were successfully deployed using this technology, producing results consistent with this study. The findings, combined with subsequent applications, confirm that friction reducers effectively address friction pressure challenges in openhole water packs.
Unique Zone Switching Technique Unlocks Barrels of Stranded Oil
Authors: Udofia I. , Chiedu O. , Orumwese S. , Ajentumobi M. 
Published: August 2024

Abstract
Getting oil and gas from some reserves using conventional technologies would afore-time have yielded unfavorable cost-benefit due to the challenge of excessive water production which could have resulted from a water coning situation from a previous perforation done. Today, the high prices of oil and natural gas have forced operators to go back into their reserves to uncover sections they would not previously have brought to the front of their job's sequence for the period. Every operator wants to achieve this safely, with minimal or no community exposure, environmental impact, and low costs. Studies and several techniques such as cementing of the perforation zone, plug, etc. that can be deployed via rig-based and coiled tubing possess the challenge of high cost, longer operational time and significant environmental impact. Zone switching practice is now the commonplace and the technologies used to achieve it is vast. Depending on the well configuration, completion, and plans, zone switching execution cost can be very minimal or get massively out of budget with varying results obtained. Zone switching in deviated and horizontal wells scenarios increases execution cost and reduces the chances of success, thus, finding the optimum point for cost and results is critical. The technique, dealt with in this paper, is an innovative and uncommon approach where an Isolation system that embeds a plug with a bi-directional anchor for permanent positioning, a healing system that keeps elastomer seated, with high expansion capabilities that enable it pass through small restrictions and set in casing diameters up to 3-1/2 times its run-in diameter, and a rig-less workover/well intervention solution deployed via E-line or slickline. This technique used to unlock a stranded reserve stated in this paper showed how using existing technologies of deployment, teamwork (between operator and service provider), planning and a new isolation system (Seal III Plug) can produce optimum results.