bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling the Oil Viscosity of Nigerian Crudes Using Machine Learning
Authors: Adeeyo Y. A. , Osinaike A. A. 
Published: July 2023

Abstract
Oil viscosity is an important parameter for estimating the flow behavior of crude oil under varying pressure and temperature regimes encountered in the subsurface and surface components of the petroleum production system. Although experimental data provides the most accurate characterization of this property, obtaining such data in the laboratory is often time-consuming and expensive. Alternatively, one of several empirical correlations can be used, albeit with often poor generalization to samples from differing thermodynamic systems or crude oil types.
In this paper, we use a data-driven approach based on machine learning (ML) algorithms to create high-performing models for predicting the dead oil and bubblepoint oil viscosity of Nigerian crudes. Random Forest (RF) and Gradient Boosting (GB) ensembles, as well as Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) networks, are compared to several widely used correlations, and their performance is evaluated on a large dataset of crude oil samples collected from various Niger Delta oil fields. The ML models are built with minimal and easily accessible input parameters shared by the correlations, allowing for an objective assessment of their superiority to these correlations given the same input framework. These are reservoir temperature and oil API gravity for the dead oil viscosity modeling, and the solution gas-oil ratio and dead oil viscosity for the bubblepoint oil viscosity modeling. Furthermore, the model's reliability is tested by partitioning the dataset into training, validating, and testing sets, and optimal model configurations are achieved through Bayesian Optimization.
On the dead oil viscosity modeling task, we achieve a modest improvement over the best-performing correlation developed by Al-Khafaji (1987). The RF model's R2 and mean absolute error (MAE) scores on the testing data are 0.831 and 3.423, respectively, versus 0.809 and 4.439 for the correlation method. However, for the bubblepoint oil viscosity modeling, the improvement recorded using the RF model over the best-performing correlation developed by Beggs and Robinson (1975) is remarkable. In this case, the R2 and MAE scores for the RF model are 0.924 and 0.441, respectively, compared to 0.574 and 0.813 for the correlation method. As a result, our ML models have outperformed conventional correlations for modeling oil viscosity.
Ultimately, oil viscosity estimates from the developed ML models can provide a much more accurate characterization of the fluid behavior of Niger Delta crudes than the conventional correlations can. Furthermore, the ML models allow for continuous improvement of their generalization ability by introducing new data from various sources to the models.
Reservoir Characterization for Co2 Sequestration and Co2-Enhanced Oil Recovery Techniques in Maje Field, Offshore Niger-Delta, Nigeria.
Authors: Agunbiade T. O. , Oluwadare O. A. , Amusan R. O. 
Published: July 2023

ABSTRACT
The oil and gas industry is a significant contributor to carbon dioxide (CO2) emissions, which have a major impact on climate change. Geoscientists in the industry play a crucial role in mitigating climate change by identifying and evaluating potential CO2 storage sites, monitoring CO2 behavior after injection, and exploring CO2 enhanced oil recovery (EOR) techniques. CO2 -EOR involves injecting CO2 into depleted oil reservoirs to increase oil production. Reservoir characterization using well log and seismic data analysis helps determine storage capacity, containment, and injectivity of reservoirs for CO2 sequestration and EOR. In this study, two sand reservoirs (RES 1 and RES 2) were analyzed, with RES 2 being considered more suitable for CO2 sequestration and CO2 -EOR. The estimated storage capacity of the study area was approximately 40 million metric tons (MT). Assessments of fault sealing capacity and reservoir properties were conducted to validate storage potential. Further investigations and analysis by experts in different fields are necessary. The interpretation of seismic and well log data aids in generating geological and structural models, which provide necessary information for designing injection and production wells and analyzing the compatibility of CO2 -EOR techniques with the reservoir. Direct Air Capture and Rejection (DACR) technology is also highlighted as a beneficial carbon capture solution for developing countries like Nigeria, as it can help reduce carbon emissions from oil and gas operations while enhancing oil recovery in characterized reservoirs.
Enhancing Natural Gas Plant in Niger Delta Region: Using Wireless Sensor
Authors: Oruwari Humphrey Otombosoba , Oruwari Raymond Odum 
Published: July 2023

Abstract
This study evaluates designing and simulating wireless sensor network as a solution to enhance the operations of natural gas plant in a metering station in Niger Delta region. There are several problems in natural gas plants ranging from hydrate formation, condensate carryover to customer's facility, low equipment availability and so on. All the problems enumerated were due to inability of some units of the plant not linked online nor on Realtime basis. To solve these problems requires the use of transmitter to route process parameters in the respective plant units to the control room and display such parameters for online monitoring. As such, there are two basic options. Either the use of wired transmitters or wireless transmitters. Both technologies are great but considering the prevailing circumstances of an existing old gas plant in Niger Delta region, the cost of excavation to lay fresh signal cable will be relatively high. Hence, the choice of wireless transmitters was chosen. The methodology involved using literature review and case study of existing metering station gas plant in Niger Delta. The literature reviewed involved wired sensors network, wireless sensor network, and application of wireless sensor network. There was also comparison between wired fieldbuses, wireless network technologies and wired versus wireless fieldbuses. Matlab software was used to design wireless sensor network. The Matlab code was written such that it can read data from Microsoft Excel sheet into the program for analysis and simulation. K-means algorithm was used to cluster the sensor nodes data and determine the centroids of the clusters. The program when run will create sink node matrix, concatenate the cluster centroid, and sink matrices. The results of the software simulation and discussion show that the proposed wireless sensor network if implemented will solve the identified problems and therefore, enhanced the operations of the gas plant in the metering station.
Uncertainty Management for Well Planning and Execution; Case Study of New Drills in Tom Boy Field in the Swamp Niger Delta
Authors: Taiwo B. O. , Igiri T. Z. , Onyeji J. A. , Ohenhen Oduware , Olufisayo Fagbowore , Zen F. A. , Ayodele Asaolu , Aluba Oragwu , Clement Chukwuka 
Published: July 2023

Abstract
The Tom Boy field is one of the oldest fields in the Niger Delta Basin with more than 30 wells at the time of initiating infill development drilling campaign. The drilling campaign of 11 wells (10 producers and 1 Water Source) was planned to develop reservoirs that have not been produced and to optimize production from developed reservoirs. Numerous challenges were faced in the planning and execution phases for the infill drilling. Key uncertainties include, Structure, Stratigraphy, wellbore placement issues, current fluid saturation/contacts in the reservoirs, and wellbore instability issues as wells drilled through pressure-depleted reservoirs. Thus, this paper addressed how these uncertainties were managed during planning and execution of the drilling program.
Through integration of detailed Uncertainty Management Plan (UMP) during execution, the team eliminated the need for drilling pilot well in an instance; and in another scenario, successfully landed a horizontal well in a 10ft thick sand. The methodology used include deployment of improved technologies, proper planning, appropriate mud-weight design, history matched reservoir models, optimizing subsurface target locations for data acquisition and proper well sequencing on the drilling schedule was used to understand the current saturation in some target reservoirs and target the sweet spot in the reservoir. Pre-execution decision tree assisted with making quick real time decisions while drilling the landing and lateral hole sections based on the outcome of each uncertainty identified in the UMP signpost. Decision tree incorporated all information (earth model, seismic data, dips, local pre-drill model etc.) integrated with potential outcomes from real-time reservoir navigation data obtained from geosteering tools to aid well placement in an optimal position within clean sand. All wells were successfully drilled and completed in the sweet spot of target reservoirs to meet pre-drill production targets.
Successful Applications of a New Sand Screen Technology to Mitigate Water Injection Challenges, A Case Study for X Field, Nigeria
Authors: Ngerebara Justus , Alawode Olusiji , Hamzat Ismail , Wilson Ross , Anderson James , Moradi Mojtaba , Emifoniye Ejiro , Ugbor Ifeanyi , Okonkwo Ngozi 
Published: July 2023

Abstract
A number of techniques have been applied to improve the integrity and therefore long-term performance of injection wells to eventually enhance oil recovery in one of the fields in Nigeria.
Comprehensive data analysis suggested formation solids due to the phenomena of water hammer, backflow and crossflow are major integrity problems in several injection wells in the targeted field, especially with fines migration and accumulation inside the lower completion during sudden or prolonged well shut-in. Formation solids are normally resident in the reservoir during the steady injection but can be mobilized into the wellbore during sudden shut-ins due to powerful transient flow effects such as water Hammer, cross flow and backflow. This would result in high bottom hole injection pressure (BHIP), diminished or loss of injectivity, screen plugging and erosion of downhole equipment which may lead to the inability to maintain pressure support to pair producer. Therefore, an intervention, remediation, side-track or loss of wellbore may be deemed inevitable. Application of other technologies has proven unsuccessful in these wells for various reasons.
A new sand control technology specifically developed for such projects was chosen as the best option among all available alternatives based on a matrix of requirements for the new campaign. This technology which would be installed on the closest point to the sandface was chosen as it isolates the reservoir from wellbore during well shut in, constitute no obstruction to Intervention tools, provides full access to the lower completion sand face during injection and/or intervention without restriction or pressure drop, withstands well conditions for the entire well life, is compatible with SAS, GP completions and direct wrap or metal mesh screens and it is a low CAPEX solution compared to other alternatives.
Rigorous compatibility tests and practices including modelling, backflow, cross flow, erosion and plugging tests were performed to ensure that well completions and operations requirements were met for field X. The results from all studies were positive and successful and therefore the technology was approved to be installed in the wells.
The NRV technology has already been installed in 3 wells to date. In this paper, the pre-qualification studies, the full qualification test results and post-installation well performance would be discussed. Also, the lesson learnt from these installations will be shared.
The wells’ performance data shows that this completion technology has successfully delivered the target rate and desired performance so far and provided the field X team with a robust solution to mitigate the common issues with the injection wells while avoiding costly interventions.
Optimizing the Take-Off Valve Opening of a Self-Lift By-Pass Conduit: A Novel Approach to Severe Slugging Mitigation in Offshore Pipeline-Riser Systems
Authors: Okereke Ndubuisi Uchechukwu , Kara Fuat , Iloani Marcel , Okalla Christian , Kerunwa Anthony , Ogazi Isaac , Elendu Emmanuel , Mcphilemon Chijioke , Udeagbara Stephen Gekwu , Nwogu Ngozi Claribel , Nwanwe Chibuzo 
Published: July 2023

Abstract
Previous numerical simulation studies, suggests that active optimization of the take-off valve on a by-pass pipe connected to a pipeline-riser system, is critical to the effective deployment of the self-lift severe slugging mitigation technique. Hence, there are recommendations for further experimental studies on the effective deployment of the self-lift severe slugging mitigation approach. Generally, severe slugging has adverse effect on multiphase flow transportation along the pipeline-riser system, with a potential 50% drop in production.
Industry mostly relies on gas-lift, topsides choking and aggregation of high pressure wells as a means to manage severe slugging for typical deepwater oil fields. However, these methods have key disadvantages such as high volume of gas required for compression to mitigate severe slugging via gas-lift and the drop in production associated with topsides choking as a result of topsides choking being mainly effective at low valve opening.
This study investigated the deployment of self-lift severe slugging mitigation technique via a 4 feet × 7 feet pipeline-riser section, consisting of a 2 inches by-pass pipe diameter, with the take-off valve designed to operate in such a manner as to tap-off associated gas via the valve and injected via the injection valve until it is able to break liquid slugs within the riser column.
The results obtained from this experimental study indicated that severe slugging was better mitigated at between 50% - 70% valve opening of the take-off valve, while the injection valve was set at 50% valve opening, to compress air flowing as part of associated gas increased by 20%. Mitigation of severe slugging was observed with flow stabilization of the intermittent fluctuation at the outlet nozzle at the topsides of the riser section, which was set at about 30% opening. The results further revealed that self-lift could be adapted to mitigate slugging in a pipeline-riser section and also possibly deployed offshore.
Using Artificial Neural Network to Predict Gas Flare Volume, Gas Composition, and Temperature from Gaseous Emission.
Authors: Omion O. O. , Dosunmu A. 
Published: July 2023

Abstract
Gas emission from gas flaring is known to have deleterious effects on the environment and they constitute a major source of global warming. Flare gas volume, temperature, gas composition and other meteorological factors are major parameters in gas flaring processes. Using Artificial Neural Network, a model was developed to estimate gas flare volume, gas composition and flare temperature from gaseous pollutants using. Data used for the study were from oil prolific Niger-Delta region of Nigeria. Air quality index parameter, gas flared volume, temperature and composition between 2013-2017 were used in developing the ANN model using the Neural Training toolbox (nntool) of the Matrix Laboratory (R2019a MATLAB) mathematical software. An 8-6-3 network architecture was adopted. It consists of eight input parameters (suspended particulate matter, carbon monoxide, sulphur oxide, nitrogen oxide, volatile organic compounds, hydrogen sulphide, methane, and ammonia), six hidden layers and three output parameters (gas flared volume, gas composition and temperature) using 1286 dataset for each input and output parameter. Multiple-input multiple-output (MIMO) neural network using supervised learning algorithm (Levenberg-Marquardt) to train the network was adopted in model development. 75% (880 data points) of the data was set aside for the training of the model at its developmental stage, 10% for test data set and 15% for the validation data set. From the models’ prediction, it was observed that the developed model predicted excellently and performed well when tested with new set of data which was not a part of the developmental dataset with a coefficient of determination of 0.99999918, a root mean square error of 0.009029, an absolute average percentage relative error of 0.0362% for Gas Flare Volume, Composition and Temperature respectively. The outcome of this study presents a reliable and speedy tool for forecasting of gas flare volume, composition, and temperature in the absence of conventional methodologies.
An Integrated Approach for the Geologic Model Construction of a Miocene Turbidite Reservoir in the Akpo Field, Niger Delta.
Authors: O Okonkwo Glory , Chizea Chukwuka , Akhajeme Emmanuel , O Olagundoye Olatunbosun , Ogwogho Momodu , Spina Vincenzo , Onyeanuna Chinedu , Uwerikowe Gabriel , Fashanu Mobolaji , Enuma Christopher 
Published: July 2023

Abstract
Geologic model updates especially when driven by seismic data generally help for better field understanding, and in most cases, aid the targeting of nearby undeveloped prospects or infill opportunities and robust geosteering of infill wells for efficient drainage or sweep and well recovery optimization which help to prolong field life and maximize the returns on investment of mature fields.
The Akpo V & W reservoirs case study lie in the central part of the mature Akpo field. They are characterized by laterally offset stacked turbidite channels with dense network of faults.
This work illustrates the collaborative team effort performed through the integration of geoscience and reservoir engineering data in constructing the static model of the V & W reservoirs. This new model aims to address the uncertainties and limitations of the previous model, re-evaluate the volumes in place, better represent the dynamic behavior of the reservoirs to aid history match, forecast and optimize infill well placements within undrained areas to sustain production. This will in turn, improve the recovery factor and the management of the reservoirs.
The new model incorporates new petrophysical synthesis for all development wells, re-interpreted faults, horizons and AEs on a new seismic dataset (2018 4D M3 B98), Lithofacies trends from seismic reservoir characterization study, amongst others. Structural and property modelling results with QCs shows better respect of well, seismic data/trends and facies heterogeneities; giving rise to a more robust model that meets the specified objectives.
Extending the Frontiers of Well Clean-Up Through Microemulsion Fluids-Based Technology Application
Authors: Okoro Felix , Ayodele Bunmi , Anioke Chidiebere , Okolomma Emmanuel , Ibrahim Yahaya , Joseph Victor , Mohammed Olufemi , Mietei-Ileberi Catherine 
Published: July 2023

Abstract
In oil & gas development projects, the target is to clean-up and put well onstream as quickly as possible. Apart from the economic benefits of early production, timely clean-up and well kick-off ensures that drill-in fluids and other materials used during drilling and completions do not create irreversible damage to the near wellbore region of the reservoir. In the FENE field there were 12 wells completed but not on production for over 20 years due to security and contractual challenges. These wells were drilled with water-based mud and left with filtered Seawater post completion. Given that the drill-in fluids, Seawater, and other materials were left in the wells for a long time, significant damage was suspected for the wells. These damage mechanisms include mud invasion, in-situ emulsion and water or emulsion blockage in the production interval.
These identified damage mechanisms meant that the 12 wells require a dedicated clean-up with an optimal recipe to remove emulsion and other damages in the near wellbore. Conventional acid stimulation was initially proposed but was not endorsed due to suspected performance inefficiency and possible fluids-fluids incompatibility that could lead to further formation damage. After a comprehensive integrated review evaluating the potential damage mechanisms, a novel solution was identified which involves the use of a high-definition remediation fluid solution "a Micro-emulsion Fluid (MEF) Based Technology" to remove identified near wellbore damage. Prior to field execution, a rigorous laboratory test was performed with fluid samples from the wells and the result indicated good near-wellbore damage removal, reservoir fluids and Seawater compatibility.
The MEF based technology has so far been successfully deployed in 9 wells (with the remaining 3 wells in plan) and has effectively removed suspected near wellbore and formation damage. The wells are currently on production with a 33% increase in performance above plan. This technical paper explains the process of candidate treatment selection, solution design, job execution, and production gains from deploying MEF based solution on these 9 wells executed till date.
A Successful Foam Assisted Gas Lift Trial in a Matured Niger Delta Field
Authors: Okoro Felix , Arochukwu Elias , Abuah Nnamdi , Marcus Imowo , Nnanna Erasmus , Onuigbo-Nweze Chy , Eke Iheanyi 
Published: July 2023

Abstract
In the oil and gas business, continuous production optimization and enhancement is key for optimal field management. As a field depletes, water cut increases and oil rates decline. To maintain production, there is need to deploy artificial lift systems. The onshore FENE field is a matured Niger Delta field that has been in production for over 50 years. The field has wells that produces on natural flow and on gas lift. To improve field production, often requires optimization of the limited lift gas available to the gas lifted wells.
Foam Assisted gas lift (FAGL) technology involves the downhole injection of a liquid foamer to lighten the fluid column and reduce slippage, thus improving well vertical lift performance. The foamer can be delivered downhole via a pre-installed downhole chemical injection line where available or into a lift gas stream on surface. The application is expected to increase oil production and / or decrease gas lift requirement.
In Nigeria, a field trial was successfully carried out on two wells (Well-X and Well-Y) with water cuts greater than 60% in the onshore FENE field. The foaming agent was injected along with the lift gas via the A annulus of the wells. The field trial resulted in 280 bopd incremental net oil gain and a cumulative gain of 2510 bbls of oil for well-X and 120 bopd net oil gain and a cumulative gain of 832 bbls of oil for well-Y over the trial period of 9 and 7 days for well-X and well-Y respectively. There was also a significant reduction of water cut from an average of 76% to 66% and an estimated 25 - 35% savings in lift gas consumption. This paper details the candidate wells selection criteria, modelling details, foamers qualification, trial execution and post treatment results.