bluuebunny/crossref_metadata_2025_split huggingface dataset:
From Reserves to Revenue: The Economic Dynamics of Nigeria's Natural Gas Export from 1999 - 2022
Authors: Udoudo Kufre Jerome 
Published: August 2024

Abstract
Nigeria's position as a major participant in the global energy market, especially via its natural gas exports, is crucial in this age of energy transition. Nigeria's enormous natural gas reserves have become an important part of the global gradual shift from conventional fossil fuels towards greener energy sources, providing a cleaner substitute for coal and oil. This study examined the economic impact of Nigeria's natural gas exports from 1999 to 2022, utilizing an Autoregressive Distributed Lag (ARDL) model to provide a detailed analysis. The methodology includes descriptive statistics, the Augmented Dickey-Fuller unit root test, the ARDL bounds test for co-integration, the Granger causality test, and diagnostic tests. The results suggested that natural gas exports have a significant and positive effect on Nigeria's economic growth at a 1% level of significance. However, the impact of crude oil exports is positive but not statistically significant. The analysis revealed that foreign direct investment exerts a noteworthy and favourable impact, with a significance level of 10%. Conversely, there exists an inverse correlation between natural gas prices and economic growth in Nigeria in the long term. The model's robustness and fitness are verified by diagnostic tests. In light of the substantial and positive long-term effects of natural gas exports on Nigeria's gross domestic product, it is recommended that natural gas exports be stimulated through increased infrastructure investment, enhanced export facilities, and the formation of favourable trade agreements. Moreover, the substantial positive impact of foreign direct investment on economic growth underscores the imperative for the Nigerian government to establish a more attractive investment climate through the provision of incentives to foreign investors, political stability, and enhanced legal frameworks.
The Impact of Energy Transition on Sustainability of Oil and Gas Development in Nigeria
Authors: Oruwari Humphrey Otombosoba , Obunwa Queen , Ahuchogu Joe , Ayuba Salihu 
Published: August 2024

Abstract
Nigeria, a major player in the global energy landscape, is confronted with the challenges and opportunities brought about by the ongoing energy transition. This study investigates the multifaceted impacts of the transition towards sustainable energy on the long-term sustainability of oil and gas development in Nigeria. This study aims to analyze how the global shift towards sustainable energy sources affects the sustainability paradigm of Nigeria's oil and gas sector. It seeks to identify the key factors affecting this impact, evaluating potential risks, and proposing strategies for fostering sustainability. The methodological framework of the study involves the use of literature review and a multidisciplinary approach, the study synthesizes data from existing scholarly literature, industry reports, and policy documents. The Political, Economic, Social, technological, legal and environmental/ecological (PESTLE) analyses was utilized. Case studies and empirical evidence are integrated to provide an understanding of the evolving dynamics in the context of Nigeria's energy landscape. The finding reveals that there will be a need for economic restructuring, environmental consideration, technological advancement/innovation, regulatory framework, political dynamics and social cultural shift. The transition towards sustainable energy sources is reshaping the dynamics of the oil and gas industry worldwide. As the global energy landscape evolves, Nigeria's oil and gas sector stands at a cross road. The impacts of the energy transition are complex, requiring proactive strategies for adaptation and sustainability. This study provides valuable insights for policymakers, investors, and researchers wishing to navigate and contribute to the sustainable development of Nigeria's oil and gas sector in the era of global energy transition.
Comparative Analysis of Techniques for Unit Operation Cost Computation in Hydrocarbon Assets with Multiple Products
Authors: Etim Ntietemi , Umoh Gabriel , Oko Christopher 
Published: August 2024

Abstract
One of the major challenges of the oil industry is the volatility of oil prices. To mitigate the impact of the oil price uncertainty, there are several techniques for monitoring the efficiency and profitability of an oil and gas asset, one of them being the Unit Operating Cost (UOC) analysis. The UOC is mathematically expressed as the ratio of total OPEX to the volume of hydrocarbon produced. This ratio is also the same for assets where both oil and gas are commercialised but would require a measure of equivalence of the various hydrocarbon types for the computation of the composite hydrocarbon volume. Some approaches have certain limitations, as the UOC computed does not reflect the actual performance that the cost-price margin presents. This paper provides a modified approach to derive accurate UOC for an asset commercialising multiple products - oil, wet gas, LPG, lean gas, NGLs, etc. Data from a field in the Niger Delta between 2019 to 2023 was used for this study. Two UOC economic models were built on a spreadsheet. One model considered the energy equivalence approach, and the other considered the price equivalence approach. The UOC results from both approaches were compared. The energy equivalence approach presented hydrocarbon volumes significantly higher than the price equivalence method ca. 62%. The corresponding UOC computed by the energy equivalence model was ca. 86% less than the price equivalence model. The sensitivity of oil price on the price equivalence model was investigated using the Monte Carlo sampling method. Results showed that lower UOC is driven by larger crude oil volumes and vice versa. Higher prices of crude oil do not favour lower UOC. This can be explained by the fact that higher prices create higher conversion factor which reduces the resulting barrel of oil equivalent. Higher volume and price for gas favours lower UOC. This research contributes to the ongoing dialogue surrounding UOC analysis and underscores the importance of adopting more sophisticated and economically rigorous methods in the evaluation of operational costs in the oil and gas sector. An analysis of operating costs and unit costs will allow industry to benchmark its performance over time in a clear, consistent and quantifiable way to ensure that cost benchmarking drives efficiencies into operations whilst maintaining high standards of health, safety and environmental management.
Unveiling the Potential of Random Undersampling in Geothermal Lithology Classification for Improved Geothermal Resource Exploration
Authors: Obika F. C. , Okereke N. U. , Eze F. M. , Ekeh B. C. 
Published: August 2024

Abstract
Lithology classification in geothermal exploration has been of great significance in the understanding of subsurface geology and geophysics, which can enhance the exploration and exploitation of geothermal resources. Alongside other known industrial means of classifying lithologies, the application of machine learning models has shown viable prospects in this regard. However, there seems to be poor accuracy in the performance of some of these models due to class imbalance associated with the lithologies to be classified. Hence, in this study, robust class imbalance handling techniques were investigated to efficiently classify lithology in a geothermal field. The investigated techniques which involved Synthetic Minority Oversampling Technique (SMOTE), Random Oversampling (RO), Random Undersampling (RU), and the Near Miss Undersampling (NMU) Techniques, were each employed with two ensemble bagging methods; Random Forest Classifier (RFC) and Balanced Bagging Classifier (BBC). F1 score was the key evaluation metric, as it considers both precision and recall, giving a more comprehensive picture of the models’ performance. It was observed that by leveraging real-time drilling data such as mud flow in, rate of penetration (ROP), surface torque, pump pressure and rotary speed as input parameters, RFC performed better with the resampling techniques than BBC did. Moreover, RFC combined with RU greatly outperformed other combination techniques in the prediction of the geothermal lithology with an F1 score of 93.6% for the minority class (Plutonic) and 99.3% for the majority class (Alluvium) on the testing dataset, while other combinations had F1 scores of less than 37%. This solution alongside other vital insights from this study, showed that class imbalance handling techniques can be efficiently adopted towards building more robust machine learning models for geothermal resource exploration with prevailing high temperature and unfavorable subsurface conditions that limit the use of known traditional methods.
Efficient Modeling and Simulation of Crude Oil Stabilization Processes: Integrating RSM and ASPEN HYSYS for Energy-Saving Modifications.
Authors: Olugbenga A. G. , Ochayi A. E. , Ogidi S. , Ikirigbe O. V. 
Published: August 2024

Abstract
The process of crude oil stabilization involves removing highly volatile hydrocarbons (methane, ethane, and propane) while increasing the fraction of heavier hydrocarbons in the fluid. After production, the dissolved gas in the crude oil must be eliminated to prevent shrinkage in storage tanks. Maintaining the Reid vapor pressure (RVP) within a range of 10-12 psia at atmospheric temperature is imperative. This study demonstrates the stabilization of crude oil through the recycling of condensate into the separator feeds. From a typical production, the fluid composition and process conditions were obtained on a real-time basis. Employing a data-driven methodology, Response Surface Methodology (RSM) and Aspen Hysys simulation software were utilized to optimize the stabilization process efficiently. The Aspen Hysys model accurately reproduces thermodynamic and mass transfer phenomena, providing the foundation for these investigations. Leveraging RSM's experimental design capabilities, key operational parameters such as flow rate, temperature, and pressure were systematically influenced by both energy consumption and RVP. Statistical analysis of RSM-generated data unveils intricate interdependencies and optimal parameter configurations, aiming to minimize energy consumption while meeting stringent product specifications. The integrated RSM-ASPEN HYSYS approach establishes a robust framework for optimizing crude oil stabilization. A Reid vapour pressure of 7.752 psia was obtained. Moreover, it boosts the economic competitiveness of the oil and gas industry by aligning practices with sustainability objectives.
Production Optimization in Oil and Gas Wells: A Gated Recurrent Unit Approach to Bottom Hole Flowing Pressure Prediction
Authors: Abdullahi B. A. , Ezeh M. C. 
Published: August 2024

Abstract
Production Optimization continues to be a priority in the energy space. Several means have been investigated, particularly machine learning in recent times. One of the aspects machine learning has aided is in the area of future bottomhole flowing pressure prediction (BHFP). It lets asset managers know potential problems and make proactive decisions to facilitate optimal production. This study explores the application of Gated Recurrent Units (GRUs) in oil and gas wells to estimate future BHFP by using optimal features. To properly evaluate the BHFP predictive capability of the GRU model, the model is compared with the use of Long Short-Term Memory (LSTM) networks since LSTM also keeps long-term memory, which aids time series prediction capabilities. Using historical well data, GRU and LSTM models were trained with an optimal number of features, selected by their importance from Recursive Feature Elimination. The results showed the GRU models performed better than LSTM models, averaging a 30% approximate decrease across error metrics. With the GRU forecasts enhanced by optimized features, production managers can make prompt, well-informed decisions. This, in turn, makes it easier to control reservoirs precisely, make proactive modifications to well operations, and cut down on expensive downtime.
A Practical Approach to Complex Wellhead Integrity Restoration: A Case Study Re-Heading of an Old Well
Authors: Olowu Babajide , Okonkwo Ngozi , Abadebenghan Nelson , Nnozuba Chiamaka 
Published: August 2024

Abstract
An integral wellhead system is a key component in maintaining sustainable production and a pollution free environment. The wellhead is a part of the well integrity envelope for the well, as it carries some of the safety critical equipment and applicable redundancies. It is designed, installed and maintained to ensure it remains an integral part of the production system throughout the lifecycle of the well on which it is installed. The industry has recorded huge successes in achieving this objective through standardization of wellhead specifications to meet the requirements of different service environments.
Despite best endeavours, there are instances where well integrity has been compromised in ageing wells with wellheads that were designed to specifications which are now obsolete, or wellheads that have experienced cavities and corrosion induced wellhead-casing connection failures amongst other defects. Furthermore, in challenging work environments such as the Niger Delta region of Nigeria, human factors such as vandalism of wellhead systems have made maintaining and restoring well integrity more prevalent.
In recent times, non-conventional remediations are deployed where the wells have been damaged to the extent that neither well established rig-less or rig-based intervention activities are possible. In these circumstances, the only viable option to restore well integrity is through de-heading damaged wellheads and installing a new one via a tie-back and re-heading process. The tie-back operation is highly specialized and safety critical with bespoke procedures for successful execution.
This paper focuses on a case study where a casing jack unit was used in challenging well control circumstances to de-head, tie-back all casings and dual completions tubing, followed by the installation of a new wellhead. It highlights the multi-disciplinary team approach, key considerations and mitigations deployed to carry out the operation in a controlled and safe manner to restore wellhead integrity.
Geotechnical Site Investigation for a Proposed Marginal Field Development in a Swamp Location
Authors: Osadipe B. , Adesokan I. , Olusola B. , Shittu A. , Ifediora A. 
Published: August 2024

Abstract
This study was carried out to investigate and determine the geotechnical parameters required for adequate design and positioning of structures and facilities in a swamp location. 106 samplings were carried out in the boreholes (both on land and over water) to obtain samples for laboratory analysis. In all the boreholes, 92 disturbed samples were collected using the split spoon sampler (SPT samples) and from the drilling spoils. These were properly labelled and placed in watertight bags to ensure sample integrity while undisturbed samples were collected using an open-tube sampler. Both ends of the tube were properly sealed, labelled and secured. Selected soil samples were analyzed and carried out in accordance with BS1377 for engineering properties. The moisture content for the clay layers ranges between 31% and 163% which indicates that the clay has a low to high moisture content typical of marine clays, The bulk unit weight of the clay ranges between 12.52kN/m3 and 19.44kN/m3. The results of the liquid limit show that the value ranges between 88% and 140% while the plastic limit ranges between 27% and 42% and the plasticity index ranges between 61% and 98%. The SPT N-values for the sand, ranging between 6 and 14 confirmed that the sand is loose to medium dense in compaction. The results of the investigation enabled the planning and design of structures required for asset development.
Evaluating the Rheological Properties of a Synthentic Based Mud Formulated from Avocado Pear Oil
Authors: Omoregbee Ogbemudia , Ayodele Emmanuel , Akintola Sarah 
Published: August 2024

Abstract
With the oil and gas sector increasingly focusing on deep offshore drilling in challenging conditions, there is a requirement to create drilling fluids that can perform exceptionally well in such environments. It is crucial to take into account the proper disposal of drilling fluid waste in compliance with environmental regulations. Synthetic-based muds have been suggested as a viable substitute for oil-based muds. Also, the majority of studies on synthetic-based muds have concentrated on base oils that are not indigenous to the area. This study investigates the characteristics of a synthetic-based mud derived from avocado pear oil, which is a readily available and abundant resource, and determines its appropriateness for utilisation in offshore drilling activities. Avocado pear oil was obtained, subjected to transesterification, and utilised in the creation of synthetic-based muds with oil-to-water ratios of 70:30, 75:25, and 80:20, respectively. After 24 hours, it was discovered that the electrical stability remained above 400 at temperatures of 1500 °F. The sample with an oil-water ratio of 80:20 exhibited the maximum plastic viscosity at 1500 °F after 24 hours, indicating superior rheological performance at high temperatures compared to the other samples. The sample with an oil-water ratio of 80:20 exhibited the most minimal mud filter cake in comparison to all other samples, making it the optimal choice for preventing formation damage. The pH level exceeded 8, indicating its suitability for drilling operations.
Characterizing the Retrograde Behaviour of Gas Condensate in Selected Niger Delta Reservoirs
Authors: Udo U. E. , Okologume W. C. , Mmata B. 
Published: August 2024

Abstract
Gas condensate reservoir fluid has a very complex hydrocarbon phase behaviour. In this study, retrograde gas condensate fluid in Niger Delta reservoirs was re-characterized. This was done through generation and re-definition of fluid properties for different gas condensate reservoir. To reduce the uncertainties and issues associated with recovery predictions, reserve estimation and multiphase flow, gas condensate were re-characterized into five different categories: near-critical, rich, mid-rich, lean and extremely lean condensates, with their respective phase diagrams. 250 reservoir samples were taken from over 120 fields in the Niger Delta region. Samples were all validated and restored to their respective reservoir conditions for a minimum of 24 hours with constant agitation so as to achieve homogeneity prior to the experiment. The experiments involved in the re-characterization include direct flash, gravimetric density, constant compositional expansion, and compositional analysis. Findings from experiments revealed that the gas-oil ratio (GOR) of a gas condensate ranges from 4780 to 401,490 SCF/STB, API gravity: 36–54 oAPI, reservoir density: 0.5170-0.1702 g/cm3, liquid dropout: 0.21–51.09, C7+ mol% &lt;12.5, and stock-tank liquid density: 0.7604-0.8571. Findings from this research show that some fluid properties in the Niger Delta region exhibit significant deviations from values established by other researchers. Investigations also revealed that near-critical condensates are rare, while mid-gas condensates are predominant in the Niger Delta region. The re-characterization of gas condensate fluids in the Niger Delta region presents numerous advantages, such as enhanced understanding of gas condensate fluid behaviour, optimized reserve estimation, maximized economic recovery, improved facility design and field management.
Machine Learning-Based Time Series Models as Alternatives to Short-Term Traditional Decline Curve Models for Hydrocarbon Reserve Estimation
Authors: Balakirisnan Alvin , Jaafar Mohd Zaidi , Sidek Mohd Akhmal , Yakasai Faruk , Nwaichi Peter Ikechukwu , Ridzuan Norida , Mahat Siti Qurratu’ Aini , Abass Azza Hashim , Ngouangna Eugene , Gbadamosi Afeez , Oseh Jeffrey Onuoma , Gbonhinbor Jeffrey Randy , Agi Augustine 
Published: August 2024

Abstract
This study evaluates the effectiveness of machine learning-based time series models as alternatives to short-term traditional decline curve models for estimating hydrocarbon reserves. To accurately estimate the hydrocarbons that can be economically recovered from a field, area, or region, the predicted quantities should closely match the actual observed quantities within the same period. In this study, two models were compared based on their Root Mean Square Deviation (RMSE) to solve the decline curve technique of reserve estimation – the traditional exponential model and the time series ML-based Recurrent Neural Network's Long Short-Term Memory (LSTM) model. The study results showed that the LSTM model outperformed the traditional exponential model, with an RMSE of 80.12 compared to 107.41 for reservoir K3, 30.24 to 141.52 for reservoir VII, and 80.56 to 169.81 for reservoir K5. These RMSE values indicate that the LSTM model had a better fit to observed data and thus had better goodness. Therefore, LSTMs serve as improved alternatives to short-term traditional decline curve models.
New Correlations for Predicting Niger Delta Oil Reservoirs Recovery Factors
Authors: Oyakhire B. , Onyekonwu M. , Okologume W. C. 
Published: August 2024

Abstract
The importance of estimating an asset's expected oil recovery factor (RF) cannot be overemphasized. It remains an essential step in asset valuation and can be achieved through several techniques including the use of correlations. This paper provides novel correlations for estimating RFs for oil reservoirs in the Greater Ughelli & Coastal Swamp depobelts of the Niger delta. Statistical multivariant regression method was employed in the development of the new RF correlations models using actual oil field data obtained in the early life of the fields in the Niger Delta. Eleven variables were gathered for each reservoir based on parameters identified to have influence or relationship with oil RF from literature. Data from 228 oil reservoirs were screened, only 69 oil reservoirs under water drive and solution gas drive in the Greater Ughelli depobelt and Coastal Swamp depobelt were found to have complete dataset valid for the study. The study showed that oil gravity and shrinkage factor are not statistically relevant in developing RF correlation for the Greater Ughelli depobelt under water drive and solution gas drive respectively. The developed correlations were validated with additional actual field data from the Niger Delta, and the new models’ results were compared with those obtained from Guthrie & Greenberger industrywide correlation and Onolemhemhen et al model developed for the Niger Delta. The new models provided better predictability and reliable results. The new correlations had coefficient of determination (R2) of not less than 0.68 with the field data while those of Guthrie & Greenberger and Onolemhemhen et al. models had R2 values less than 0.11. The new correlations are recommended for quick valuation of primary oil recovery from oil assets within the Greater Ughelli and Coastal Swamp depobelts of the Niger Delta as they provide more reliable estimates of oil RF for fields within the region.