bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design and Construction of Rotary Drilling Rig Prototype
Authors: Adeniyi Adekunle , Igbafe Anselm , Ebis Olokpa , Ogunyemi Adebayo , Yusuff Sikiru , Oyebode Oluwadare 
Published: August 2022

Abstract
Drilling in search for hydrocarbon is an essential component of exploration and production activities. Chemicals, Drill rig, Casing, Tubing, Drill pipes and bits are basic requirements to successfully drill a well. Rotary Drilling rig is very crucial among the basic requirements. A major function of rotary drilling rig, is continuous circulation of drilling fluid and removal of cuttings. Hence, this paper focused on the design and construction of drilling rig prototype, for training purposes in academic environment. Components were constructed from the most suitable materials obtained from metal scraps individually, and when put together forms an integrated system that enables the drilling process to make a well. The prototype was produced successfully. The mixing hopper, hoisting and the mud circulatory systems were fully incorporated and connected. The rig prototype was, in principle, to transport fluid from the mud pit up the stand pipe to the swivel via the rotary hose down the drill pipe to the annulus and back to the mud pit through the shale shaker, De-sander, De-gasser, De-silter units, via the mud return line. The drawworks is to lift the drill pipe and lower it back into the rotary table with the aid of the drawworks motor and a top drive system.
Hydrate Risk Management and Evaluation for Gas-Dominated Systems Using Machine Learning
Authors: Odutola Toyin Olabisi , Bassey Israel , Igbine Anita , Monday Celestine Udim 
Published: August 2022

Abstract
Advancements in oil and gas production have led to the exploration and production of hydrocarbons in unstable regions including offshore (deep & ultra-deep) reservoirs. As production increases, flow assurance continues to be a prevalent problem in wells and flowlines.
It is necessary to develop flow assurance analysis models for hydrate formation in gas pipelines. Analyses have shown the difference in thermodynamic and kinetic behaviors in the different hydrate phase systems (water, gas, oil). This study presents a data-driven gas hydrate diagnosis model for monitoring and risk evaluation in gas pipelines by performing, hydrate growth rate diagnosis for flow assurance in gas-dominated flow systems. Data used for learning was obtained from hydrate flow loop experiments performed under controlled gas-dominated flow conditions where thermodynamic conditions were obtained at each time step. Regression Algorithms were applied to develop a fit for a model to predict the hydrate risk level given thermodynamic conditions alongside the flow rate. The developed hydrate model was also applied to study the performance in flow operations. The ridge regression model showed the best performance among the models with a root mean squared error of 0.1682 and a correlation coefficient of 0.9595. The results obtained showed that the model can be deployed for use in a hydrate risk analysis endeavor, and the algorithm used in development can be further improved.
Fingerprint Analysis of Light Crude Oils from Niger Delta
Authors: Oshilike Ishioma , Mmata Bella , Ugwu Paschal , Otokpa Martins , Ibekwe Chidinma , Hilary Okeke , Onyekonwu Mike 
Published: August 2022

Abstract
Crude oil fingerprinting is a term applied to techniques that utilize geochemical analysis of hydrocarbon fluids composition to provide valuable information for well, reservoir and spill management. Analysis of crude oil fingerprints reveals a typical oil profile. Such a profile can provide information on formation history, type of carbon number preference during formation and route of migration. This study was undertaken using whole oil fingerprint and biomarkers of oils from twenty well strings from an onshore field in the Niger Delta Region. The aim was to evaluate light crude oils and determine thermal maturity, source rock quality, depositional environment and condensate correlation. The crude oil samples were analyzed using two major analytical techniques namely Gas Chromatography-Flame Ionization Detector (GC-FID) and Gas Chromatography-Mass Spectrometry (GC-MS). Evaluation of light hydrocarbon components was done using Mango parameters K1, K2, P2, P3 and N2 and the results revealed terrigenous organic matter input. Biomarker composition and pristane/phytane ratios in the range of 3.51 to 6.83 derived from GC results show that the source rock of the oils is made up of majorly terrestrial (type III) organic matter, deposited in a deltaic setting with prevailing oxic conditions. Maturity parameters calculated from Carbon Preference Indices between the range of 0.87 and 1.44 indicate the source is matured. The study provides key information on source characteristics that are applied to describe the type of petroleum prospects of a region. This study also provides information on condensate correlation, which has production implications such as application to production allocation.
An Insight into the Optimal Development of a Marginal Field – Pressure Complexity and Multiple Hydrocarbon Targets
Authors: Amakiri Samuel , Kalejaiye Derinsola , Erhiwha Elizabeth , Oviawe Uyi 
Published: August 2022

Abstract
Maximizing the end-life development of a marginal field with small pockets of undeveloped hydrocarbon could pose an unattractive venture, especially considering the attached economic value. The Well design and delivery approaches presented in this paper illustrate how available subsurface engineering tools and knowledge were deployed in the planning and execution phases of the Umuseti-7 development well. This well is an Oil and Gas "fault-scooping" producer tasked to bring the Umuseti main structure (OML 56) to complete life-cycle development by providing structurally high drainage points in its remaining viable reservoir accumulations and a dependable conduit for the realization of overarching field development ambitions.
This paper showcases the development strategy undertaken, challenges encountered, solutions employed, and lessons learned during the preparation and implementation stages of the Well delivery cycle. It demonstrates the simple well plan employed despite grueling subsurface complexities and the measured approach applied in drilling and completion program phases. Apt Well construction and depletion plans were developed, reliable materials, equipment, and tools deployed, and thorough "Industry Best Practice" processes followed (including Simultaneous Operations-SIMOPs) from project commencement to conclusion.
Results of the Umuseti-7 well show single-well near-term oil gains of about 2000 bopd (this represents a 70% increase in asset-controlled oil production capacity) and medium to long-term NAG gains of 5-15 MMscf/d. This Well project ultimately purposes to sustain this marginal asset’s (Umuseti/Igbuku field) oil production capability and propel its gas monetization drive.
Prospective Application of Carbon Capture and Storage: A Case Study of Field X in OML Y in the Niger Delta Basin
Authors: Momodu Ehigie , Kelechi Faith Mmesomachukwu , Soro Augustine , Shittu Saheed , Osime Kelechi Victoria , Olawunmi Emmanuel Oduyemi 
Published: August 2022

Abstract
The expansion of gas utilization systems, together with Nigeria's present climate objective, makes CCS a must-do for the country. The Niger Delta Basin has been identified as an excellent setting for carbon capture and storage (CCS), particularly in depleted reservoirs, according to a basin-wide evaluation. However, not all carbon-depleted reservoirs are appropriate for carbon storage. The suitability of the western Niger Delta basin for CCS is assessed in this research. This study looked at five reservoirs in the western section of the basin. The storage capability of the region's reservoirs was assessed using Screening Criteria for Carbon Storage, as well as well logs, seismic, reservoir properties and petrophysical data. These reservoirs are proven to fit several characteristics, including seismicity, size, faulting intensity, reservoir depth, maturity, hydrocarbon potentials, climate, and hydrogeology. The findings of this study may be used as a benchmark for identifying prospective storage locations within the basin and extended to other sedimentary basins.
Prediction of Scale Precipitation by Modelling its Thermodynamic Properties using Machine Learning Engineering
Authors: Ugoyah Joy Chiekumali , Ajienka Joseph Atubokiki , Wachikwu-Elechi Virtue Urunwo , Ikiensikimama Sunday Sunday 
Published: August 2022

Abstract
During oil and gas production, scaling is a flow assurance problem commonly experienced in most regions. For scale control to be effective and less expensive, accurate prediction of scaling immediately deposition commences is important. This paper provides a model for the prediction of Barium Sulphate (BaSO4) and Calcium Carbonate (CaCO3) oilfield scales built using machine learning. Thermodynamic and compositional properties including temperature, pressure, PH, CO2 mole fraction, Total Dissolved Solids (TDS), and ion compositions of water samples from wells where BaSO4 and CaCO3 scales were observed are analysed and used to train the machine learning model. The results of the modelling indicate that the Decision tree model that had an accuracy of 0.91 value using Area Under Curve (AUC) score, performed better in predicting scale precipitation in the wells than the other Decision tree models that had AUC scores of 0.88 and 0.87. The model can guide early prediction and control of scaling during oil and gas production operations.
Gas Hydrate Formation and Dissociation: Effect of Salinity of Formation Water in Subsea Flowline
Authors: Akhagbeme Joseph Emmanuel , Ajienka Joseph Atubokiki , Wachikwu-Elechi Virtue Urunwo , Ikiensikimama Sunday Sunday 
Published: August 2022

Abstract
The total dissolved solid (TDS) of formation water has an impact on its tendency to form or dissociate Gas Hydrate in gas production, handling and subsea transportation systems. The effect of salinity of formation water on hydrate formation and dissociation was studied in this paper. Two seawater samples (SW1 and SW2) of different salinities: 35.4g/L and 34.8g/L respectively, and synthetic seawater sample (SSW) were used. Afresh water sample was used for comparison. The SSW sample with a salinity of 36.0g/L experienced a longer onset time for hydrate to form, and dissociated quickly in this sample than the rest samples. The onset time for hydrate formation increased as formation water salt content increases and vice versa for dissociation. The 0.04 wt% concentration of the commercial kinetic hydrate inhibitor (PVCap) used, performed better for the hydrate inhibition experiment involving the SW1 by reducing pressure to 120 psi. This attained pressure at the end of the experiment was lesser than the values obtained with the rest concentrations. The 0.01 wt% concentration of PVCap reduced pressure to a lesser value when compared to the values obtained using other concentrations for the experiment conducted with SSW.
The Impact of the Petroleum Industry Act on the Economics of Small and Stranded Gas Fields in Nigeria
Authors: Adegun Adedamola , Mdondo Justine , Agbo Chidozie , Samuel Pheeyedi 
Published: August 2022

Abstract
Nigeria's vast natural gas resources of over 600tcf are largely undeveloped and spread across the Niger Delta, Dahomey, Anambra and Benue basins. The Niger Delta basin is more developed but has been largely constrained by ‘oil-centric’ fiscal policies, ambiguous regulatory direction, and the preponderance of small (low reserves) and stranded (distant from infrastructure) fields. The gas (LNG) export business has flourished in Nigeria because it has benefitted from fiscal and legal incentives exogenous to the existing legal framework until the Petroleum Industry Act.
With the enactment of the Petroleum Industry Act in 2021, the legal, fiscal and regulatory landscape of the industry changed. An omnibus legislation, it encompasses new ‘gas-centric’ policies, introduces targeted incentives, provides improved regulatory clarity and commercial steer particularly for the gas industry. The act created a distinct regulator for the gas industry, revised the incentives in the Associated/Non-Associated Gas Framework, detailed domestic pricing methodologies, reinforced government commitment to domestic supply obligation amongst others.
In this paper, we analysed the Petroleum Industry Act, detailed the key drivers for gas business and assessed the impact on the viability of small and stranded gas fields. We highlighted the impact of the new fiscal terms on gas projects compared to the erstwhile terms and identified opportunities for government and investors to maximise value and meet gas production targets.
Hybridized Probabilistic Machine Learning Ranking System for Lithological Identification in Geothermal Resources
Authors: Ekeopara Praise , Odo Jude , Obah Boniface , Nwankwo Valerian 
Published: August 2022

Abstract
Geothermal resources are characterized by hard rocks with very high temperatures making it difficult to implement conventional tools for petrophysical analysis such as lithological identification. Several computation and artificial intelligence models such as K-means clustering algorithms have been applied, however, these algorithms are limited to certain applications due to the available data utilized and high computation time. It is hence pertinent to consider a robust model that can meet up with these requirements.
In this study, a proposed hybrid machine learning probabilistic ranking system was developed which considered the integration of several pattern recognition algorithms in the identification of formation lithology. The ranking system leverages on the large volume of drilling and log data collected from conventional oil and gas operation to develop five embedded lithology identification models: K-means clustering, Hierarchical clustering using ward linkage, K-mode clustering, Birch, Mini-batch kmeans. The analysis was carried out using gamma ray logs, density logs, neutron porosity logs and Spontaneous potential as input parameters in building the lithology identification models while rate of penetration, surface RPM, Flow in, surface torque and pump pressure were utilized to predict the different lithologies using the different pattern recognition models as outputs. The output derived from the respective lithology identification models are further ranked based on a probabilistic approach to predict the actual lithology of the encountered formation. The results show that the implementation of the ranking system was effective in identifying the lithology of the drilled formation.
Evaluation and Comparison of the Hydrate Inhibition Tendency of Hydrogen using Unisim and Towler and Mokhatab's Correlation
Authors: Ekeowa Collins Sopuruchukwu , Ajienka Joseph Atubokiki , Wachikwu-Elechi Virtue Urunwo , Ikiensikimama Sunday Sunday 
Published: August 2022

Abstract
Hydrate formation in pipelines has been a serious flow assurance issue in the oil and gas industry hence several methods have been developed to predict the conditions which favor its formation in order to develop a proper mitigation plan to control its formation. This study evaluated the inhibition effect of hydrogen gas on a methane / methane gas mixture using UNISIM software and Towler & Mokhatab correlation. After which the effectiveness of this prediction method was determined by comparing their predictions with experimentally obtained data. The predictions of hydrate formation temperature of the methane / methane gas mixtures by Unisim and correlation all showed a decrease in their hydrate formation temperatures when mixed with hydrogen gas. An error evaluation on the two prediction methods showed that the UNISIM prediction has a better prediction than the correlation for all the methane / methane gas mixture because it predicted hydrate formation temperature closer to the experimental predictions.
Torque and Drag Calculations in Multilateral Wells
Authors: Etaje Darlington , Shor Roman , Lashkari Reza 
Published: August 2022

Abstract
Multilateral drilling technology has advanced to the point that it is now feasible to explore and extract resources from previously unprofitable reservoirs. It may also help to enhance field development management by allowing for more efficient fluid flow from the formation. Despite its various benefits, a multilateral well has some drawbacks and requires a significant amount of technical work to optimize drilling parameters and depth and well trajectory rise. The most critical issues occur for a fish-bone lateral when the turns are formed for each lateral. The measurements of WOB are complex and may be inaccurate, leading to torque and drag values that are miscalculated or misread. Currently, the soft-string model and the intermittent contact due to drillstring stiffness are used in torque and drag models. But they also have some limitations, such as the neglection of dimensional changes in the string components when assuming clearance of contact and the inability to fully model the irregularity of the actual well path when assuming complete contact throughout the wellbore. The suggested model is unique in its capacity to estimate precisely anticipate drillstring-wellbore contact forces and solve torque and drag parameters from surface to total depth using a conditional alternating use of the assumption that there is continuous contact of the wellbore wall and the drill string while turning to each lateral and clearance between the drill string and wellbore-wall when drilling through straight sections. The model shows how well path design calculation is done for multilateral wells. A non-constant curvature trajectory is built into the model. The unique procedure for calculating torque and drag in multi-lateral wells is explained with several actual field data tests.
Artificial Neural Networks for Geothermal Reservoirs: Implications for Oil and Gas Reservoirs
Authors: Dikeh Calista , Ikeokwu Chinaza , Egbe ThankGod Itua , Ochuba Murphy Nnamdi , Adekanye Moromoke , Anifowose Emmanuel , Okoroafor Esuru Rita 
Published: August 2022

Abstract
Subsurface numerical models take a significant time to build and run. For this reason, the energy industry has been looking towards proxy models that could reduce model computational time. With the advancement of artificial neural network algorithms, building proxy models has become more efficient, and has enabled quick forecasting and quick reservoir management decision-making.
In this study, we used a geothermal reservoir to evaluate the suitability of two deep learning algorithms, feed forward neural network and convolutional neural network, for proxy modeling. We used metrics such as the mean square error, losses, number of parameters for the model, and time to run, to compare the two deep learning algorithms.
From our study, we determined that the convolutional neural network resulted in less error than the feed forward network and used less hyperparameters. However, the feed forward network was significantly faster than the convolutional neural network. The process of building the proxy model shows how a similar approach can be followed for oil and gas reservoir modeling and demonstrates the feasibility of neural networks in subsurface reservoir modeling and forecasting.
Outcome Based Contracting: An Effective Approach to Achieving Cost Competitiveness in Well Construction Projects
Authors: Reginald-Ugwuadu Onyinye , Akanegbu Stanley , Eze Nnadozie , Ocho Uchechukwu , Okoronkwo Chuma 
Published: August 2022

Abstract
In the last decade, the volatility in the price of oil and gas have caused the industry to seek innovative ways of delivering profitable projects. This has been further challenged by safety and security risks and other considerations such as societal and political demands for an accelerated transition to a net-zero energy system. These complexities increasingly challenge energy companies to find ways of delivering projects within acceptable Value Investment Ratio (VIR), thus requiring that all components of the capital and operating expenditure are cost efficient.
According to EIA 2016 report, drilling and completions cost (including tangible and intangible costs) account for 60 – 80% of the total well cost across the onshore and offshore plays. Most well projects in onshore and shallow offshore fields in Nigeria are in remote and challenging environments with most equipment sourced abroad. Therefore, deploying innovative approaches to managing supply chain risks and aligning these with the overarching business objective is critical to achieving the desired value for both the operator and supplier.
This paper describes how the Operator developed its Outcome Based Contracting (OBC) model for Drilling and Completions Services as a fundamental lever in its Supply Chain transformation journey; highlighting the technical and commercial value realised in terms of capital efficiency and cost competitiveness both to the operator and supplier. OBC is a contracting model where the Operator pays the supplier for the outcome agreed and not the activities leading to the outcome. This approach inherently drives competitiveness as both parties partner to provide enablers in project scoping, technology and innovation as well as related supply chain strategies towards realistic and achievable outcomes. It is expected that this will contribute to the body of knowledge and adopted by other operators to improve their contracting process for maximum benefits to all parties.
Flare Gas to Energy Using Hydrogen Fuel Cell Solid Oxide Fuel Cells: The Nigerian Perspective
Authors: Ezechi Chinenye , Ndulue Chukwuemeka 
Published: August 2022

Abstract
Energy must be available and affordable to attain energy security as it is fundamental to human and economic development which drives virtually every aspect of the world economy. Globally, the energy demand is increasing; however, the increase is more significant for the African continent due to increased population, industrialization, and economic development. As a proactive measure, technology to meet the demand is crucial to find, develop, process and produce this energy.
One of the challenges of the African continent is gas flaring due to gas management solutions and cost-related issues. Based on the African Energy Portal, (Africa Energy Portal, 2020) Nigeria loses about $2.5 billion yearly from 178 flare sites (predominantly onshore sites) nationwide, ranking Nigeria the 7th country on the list of the most flared gas countries in the world. While this is a massive loss in revenue for the major stakeholders, it is also detrimental to public health.
While there are other complementary technologies available to help utilize more flared gas, the hydrogen fuel cell has proven to be more instrumental in the quest for acleaner and sustainable energy. With Europe as a frontline adopter, the sustainable energy benefits of a hydrogen fuel cell can be seen in its continuous development, deployment, and utilization in most of its countries. Africa, especially Nigeria has the potential to reduce gas flaring by 70%, (Africa Energy Portal, 2020) via the deployment and usage of fuel cells technologies in the conversion and utilization of flared gas to clean hydrogen gas, which can serve as alternative energy used in a wide range of applications across multiple sectors.
This paper focuses on the impact of gas flaring, and the application of evolving hydrogen fuel cell technology as a means of flare gas reduction and gas recovery through steam reforming of methane. It also discusses the constraints of implementing hydrogen fuel cells in Africa, using Nigeria's Oil and Gas Sector as a case study.