Gas Tank Research Articles

Prediction and analysis on the effects of different inlet diameters of a hydrogen gas tank during fast fill using ANN by the neurofit technique

Prediction and analysis on the effects of different inlet diameters of a hydrogen gas tank during fast fill using ANN by the neurofit technique

Analysis of convection and boil-off in multi-scale membrane LNG tanks under sloshing excitations

The marine storage and transportation of liquefied natural gas (LNG) in membrane tanks involves complex thermodynamic responses, significantly affecting system operation reliability. The study investigates the coupled problem of heat transfer and sloshing in LNG tanks through small-scale experiments and simulations. A tank partially filled with R134a was analyzed under various non-isothermal sloshing excitations to examine the free surface, flow, and heat transfer. Changes in fluid temperature, wall temperature, and heat flux were measured under different sloshing frequencies, amplitudes, and filling levels. A Computational Fluid Dynamics (CFD) analysis was performed, considering heat flow in the insulation layer and phase changes in the membrane tank. The tank was assumed to be vented. A Volume-of-Fluid (VOF) model with a dynamic mesh provided insights into the effects of sloshing on heat transfer and flow. Model feasibility was confirmed by comparing simulation results with fluid sloshing experiments. An extended sloshing Nusselt number was calculated, and a correlation formula related to sloshing conditions was developed, allowing for a quantitative assessment of enhanced heat transfer. Simulations explored evaporation characteristics in various scales of LNG tanks under static and sloshing conditions. The results showed that the evaporation rate of LNG increases as the tank scale decreases, with sloshing significantly impacting LNG storage and transportation. The study enhances the understanding of heat transfer and flow evolution in LNG tanks, improving the accuracy of evaporation models and providing insights for optimizing tank design and operation under sloshing conditions.

Prediction of composite pressure vessels’ burst strength through machine learning

In Hydrogen Fuel Cell Electric Vehicles, hydrogen is stored as compressed gas in tanks made from carbon fiber composite. Tanks are designed to withstand 2.25 times the nominal working pressure. If low variability in tank strength can be demonstrated, this margin of safety could be reduced. This requires accurate prediction of the strength of the vessel and quantification of its uncertainty. In this work, several composite pressure vessels are manufactured using filament winding, and the parameters that control the winding and curing recorded as time signals. Process parameters include fiber tension, winding speed, liner pressure, fiber volume fraction, winding time and curing pressure. The vessels are tested for burst pressure. Several configurations are defined, where each manufacturing parameter is changed. The recorded manufacturing data are fed to machine learning(ML) algorithms and trained to predict the vessel’s burst pressure. These ML algorithms include neural networks, Gaussian process regression GPR, Kernel Principal Component Analysis-Lasso (kPCA-Lasso), and an Ensemble regressor. The KPCA-Lasso and GPR models show good correlation. The Ensemble regressor yields better results by combining the KPCA-Lasso and GPR models. The study demonstrates the potential of ML algorithms in predicting the burst pressure of carbon fiber vessels from the monitored manufacturing data.

A-349 Evaluation of i-STAT® Point of Care Blood Gas Cartridges and Competitor Blood Gas Devices Against Reference Standard for PCO2 and PO2

Abstract Background The i-STAT System provides laboratory quality results in minutes at the patient’s bedside. Accurate and rapid test results are critical for clinical decision making in the presence of blood gas disorders, including oxygenation and acid-base status, where the partial pressure oxygen (PO2) and partial pressure carbon dioxide (PCO2) are needed. The purpose of this study was to compare the analytical performance of the PO2 and PCO2 tests in the i-STAT G3+ and i-STAT CG8+ cartridges to the theoretical PO2 and PCO2 in prepared reference standards. Two other blood gas instruments, a benchtop device and a laboratory device were also compared to the reference PO2 and PCO2. Methods Venous whole blood samples were contrived using saturation tonometry with U.S. NIST (National Institute of Science and Technology) traceable gas tanks to prepare the reference standards, which were value assigned to theoretical PO2 or PCO2 levels based on the molar composition of the gas mixture used. Eleven levels spanning the reportable range of each PO2 (5 mmHg - 800 mmHg) and PCO2 (5 mmHg - 130 mmHg) were prepared and tested in duplicate on the i-STAT G3+ and i-STAT CG8+ cartridges, benchtop device, and the laboratory device. Passing-Bablok linear regression analysis was performed to evaluate the slope and correlation coefficient, comparing each blood gas device against the reference PO2 and PCO2 values. Study designs followed CLSI (Clinical and Laboratory Standards Institute) EP09C-ED3:2018, Measurement Procedure Comparison and Bias Estimation using Patient Samples, 3rd Edition. Passing-Bablok regression analysis was also performed for the i-STAT cartridges and benchtop device against the laboratory device. Results The regression analysis was performed against the reference standards. For PO2, slopes for the i-STAT cartridges ranged from 0.93 - 0.97, the slope for the benchtop device was 0.99, and the slope for the laboratory device was 0.97. Correlation coefficients for all devices were 1.00. For PCO2, slopes for the i-STAT cartridges ranged from 0.98 - 1.02, the slope for the benchtop device was 0.85, and the slope for the laboratory device was 1.01. Correlation coefficients were 1.00 for the i-STAT cartridges and laboratory device, and 0.99 for the benchtop device. The regression analysis was also performed against the laboratory device. For PO2, slopes for the i-STAT cartridges ranged from 0.96 - 1.00, and the slope for the benchtop device was 1.02. Correlation coefficients for all devices were 1.00. For PCO2, slopes for the i-STAT cartridges ranged from 0.97 - 1.01, and the slope for the benchtop device was 0.85. Correlation coefficients were 1.00 for the i-STAT cartridges and 0.99 for the benchtop device. Conclusions The study demonstrated that the i-STAT G3+ and i-STAT CG8+ cartridges used with the i-STAT System were shown to provide laboratory quality results within 2 minutes, showing good agreement to both reference standards and laboratory quality devices. For PCO2, the i-STAT System was shown to have better agreement to both theoretical reference standards and the laboratory device than the benchtop device. These studies were funded by Abbott Laboratories.

OPTIMIZATION SYSTEM FOR LOCAL CONTROL OF COMPRESSOR STATION

The article was devoted to the characteristics of using a compressor to process gas deposits. It is an important principle that the liquid is lifted to the surface of the earth by the energy of the gas compressed from the layer during processing. The structure of the well, the diameter of the exploitation belt, and the fountain pipes should be determined in such a way that there is little pressure in the well and in the trunk. Fountain pipes should not be lowered from the barrier to reducing pressure in the well's trunk and saving metal consumption. Depending on the daily gas volume of oil deposits, the gradient of pressure in the bed and the duration of the gas-water border should have been known. The change in those parameters depends primarily on the energy of the bed. The exploitation of the oil bed can lead to gas and flooding. The gas tank is the force that enables the liquid to move. In the compressor regime, however, the main energy is the energy of six gases. The compressor lifts the liquid to the surface of the earth, mainly because of air or gas. Keywords: gas compressor, field operation compress, compressor characteristics, formation water, wellbore pressure.

Temporal Volatility of Brent Oil Prices and Interrelation With Maritime Traffic Density in the Turkish Straits During COVID-19 Crisis

This research evaluated variations in Brent oil prices and the interrelation with maritime traffic density in the Turkish Straits during the COVID-19 pandemic. The number of commercial ships that made non-stop over passage through the Turkish Straits in the last 5 years, covering the COVID-19 -and post-pandemic periods with economic instabilities was investigated along with variables of vessel characteristics such as; gross tonnage, size and type of vessel loads. Results of the present study reveal that the maritime traffic density between 2019 and 2023, was influenced by the pandemic crisis, when harsh quarantine measures of lockdown and curfews in the first shock wave. In the aftermath, conflicts between Ukraine and Russia led to economic recession or upheaval with instabilities in Brent oil prices. For the period examined in this study, the number of non-stop over passage vessels and gross tonnages used the Turkish Straits were affected by the pandemic outbreak and Brent oil price variations. The number of vessels decreased by 5.22% from 84,871 to 80,440 during the epidemic in 2020, and by 5.38% from 43.342 to 42.340 during the global recession in 2022. Overall, the number of non-stop over passage vessels using the Turkish Straits between 2019 and 2023 declined by 1.15%, while the gross tonnage and ship length increased by 3.44% and 13.24%, respectively. In total, the number of non-specific tankers (TTA) and those carrying chemicals (TCH) increased by 2.92% and 10.97%, respectively, but a 13.25% decrease was noted for the liquefied petroleum gas (LPG) tankers over the 5 years. Considering that the world trade network is largely dependent on maritime transportation, identifying the changes in maritime transportation with the interrelation of Brent oil during global crises may provide important data for strategy building of best trade management with foresights to world economic crises.

Strength Performance Evaluations of Vehicle Cylindrical LPG Tanks

This study aims to examine and compare the strength performances of vehicle cylindrical liquefied petroleum gas (LPG) tanks produced and used in Turkey, taking into account European and Turkish Standards. The LPG tanks were subjected to burst and fatigue tests to explore their burst pressures and fatigue performances using both experimental and computer aided techniques. To investigate the strength of the tanks, a universal test bench was developed and calibrated for use in both burst and fatigue tests. The obtained experimental results in terms of burst and fatigue failure locations for each brand of tank are compared with the results obtained using finite element based simulations. Visual solid models in 3D were drawn in SolidWorks and then ANSYS software was used to perform Finite Element Analysis (FEA) simulations on those LPG cylinders to obtain the results, such as stresses, deformations, burst and fatigue failure locations. As a result of this comparison, it has been observed that some brands of cylindrical LPG tanks are more durable and safe for use in vehicles. Since the same standard requirements and the same commercial material are used in LPG tank production, it is revealed that some companies need to reconsider their design, manufacturing and especially welding processes. The results of this independent and objective study can also be used as a warning for LPG tank manufacturers and as a guide for their customers in choosing a safe product.

Numerical Study on the Influence of Various Design Variables on the Behavior Characteristics of Oil and Gas in Internal Floating Roof Tanks

Numerical Study on the Influence of Various Design Variables on the Behavior Characteristics of Oil and Gas in Internal Floating Roof Tanks

Dynamic tank-in-series modelling and simulation of gas-liquid interaction in trickle bed reactor designed for gas fermentation

Trickle bed reactors (TBR), historically utilized in petroleum processing and wastewater treatment, now extend their applicability in biological gas conversions, including syngas biomethanation for renewable methane production. Despite operational benefits, optimizing TBR design and scale-up demands a good understanding of the reactor's hydraulic behavior and mass transfer phenomena. This study's novelty is TBR's hydraulic characterization in respect to liquid and gas flowrates and simulation of the gas-liquid interaction by a dynamic gas-liquid transfer model. Residence time distribution (RTD) experiments in 220 mL lab- and 5000 mL pilot-scale TBRs with co-current flow of gas and liquid were conducted to determine the liquid and gas working volume and the number of tanks for a dynamic tank-in-series (TIS) model. RTD experiments revealed 2–6 tanks for varying liquid flowrate (constant gas flowrate) and 5–8 tanks for varying gas flowrate (constant liquid flowrate). A dimensionless equation, fitted to RTD experimental data, predicted the liquid working volume of a TBR at various liquid flowrates and reactor configurations. TBR simulation by TIS model considering 8 well mixed gas and liquid phase tanks connected in series, resulted in an excellent model validation with an R2 at 0.99. Finally, the model simulated the mass transfer kinetics of H2, CO, and CO2 in water under varying gas and liquid flowrates for lab- and pilot-scale TBRs. Simulation results showed increased dissolved gas concentration with higher gas flowrate (constant liquid flowrate) for both scales TBR. It was also noticeable that under constant gas flowrate, the dissolved gas concentration initially decreased (0.01 < ReL < 17), then increased (17 < ReL < 34), and again decreased (34 < ReL < 105). This behavior was the same for both scales TBR and revealed an optimum ReL value irrespective of TBR size.

Numerical study on dynamic response of a novel ribbed thin-walled UHPC box-type utility tunnel under gas explosion

At present, RC utility tunnels are widely used in urban utility tunnels. As a typical confined space, the complex load effect generated by the internal gas explosion of the gas tank of utility tunnel may lead to local damage or overall destruction of the structure of RC utility tunnel. Therefore, it is an important topic to improve the anti-explosion capability of the utility tunnel and ensure the normal operation of the utility tunnel after gas explosion. UHPC structure is considered to have excellent anti-explosion performance, so a ribbed thin-walled UHPC utility tunnel structure was proposed, which improved the overall stiffness and anti-explosion performance of the UHPC utility tunnel through the ribbed section. In view of the shortcomings of fluid-solid coupling method in gas simulation, Computational Fluid Dynamics (CFD) was used to calculate the overpressure distribution after gas explosion in UHPC utility tunnel. The accuracy of UHPC constitutive model and prestress simulation method was verified by testing results from the gas explosion on unbonded prestressed UHPC slab. The gas explosion damage mechanism of ribbed thin-walled UHPC utility tunnel, UHPC-NC combined utility tunnel and RC utility tunnel were comparatively analyzed. And the pre-fabricated stiffener height, UHPC slab thickness and UHPC strength were investigated on the anti-explosion performance of ribbed thin-walled UHPC utility tunnel against gas explosion. It is found that the UHPC strength needs to be enhanced dramatically to improve the blast resistance. The anti-explosion capability of utility tunnel can be effectively increased by increasing the rib height or increasing the thickness of the UHPC utility tunnel structure, and the damage pattern of the utility tunnel can also be changed from flexure-shear failure to bending failure. The results of the study can provide a reference for the damage analysis and anti-explosion design of ribbed thin-walled UHPC utility tunnels.

(Invited) A Hybrid Electrochemical and Catalytic Compression System for Direct Generation of High-Pressure Hydrogen at 350 Atmospheric Pressure

Hydrogen is becoming the center piece in the global de-carbonatization efforts in multiple industrial sectors. Gaseous hydrogen at high pressures in gas tanks is the most common approach for H2 storage, transportation and hydrogen refueling for fuel cell vehicles. Gaseous hydrogen at high pressures is also heavily used in the Haber process for ammonia production and hydro-cracking of heavy petroleum. In the long term, low-cost high pressure H2 will also play a critical role in the future long-duration grid storage for deep decarbonization and improved resilience.In this talk, I will share some recent development on a hybrid electrochemical/catalytic approach for direct generation of high-pressure H2 in collaboration with Pacific Northwest National Laboratory (PNNL). The hybrid system oxidizes water to oxygen at the anode, reduces V3+ to V2+ at the cathode, and stores proton in the catholyte during the “electrochemical charging” step. We demonstrated that the charged catholyte is then capable of generating H2 at >350 bar in the subsequent “catalytic discharging” step without any additional energy input. This concept leverages the electrochemical Nernst potential difference between the redox couple (V2+/3+) and the hydrogen evolution reaction and delivers a unique system that is capable of generating H2 at demand and at high pressure without any mechanical or electrochemical compression. We estimate a cost of <$0.19/kg-H2 for compression, representing >80% of the cost reduction compared to the traditional multi-stage compressor approach.

Effects of structure parameter and material property on thermal performance of on-board hydrogen storage tanks during fast refueling

As a power generation fuel, high-pressure hydrogen gas is widely used in transportation, and significantly contributed to development of hydrogen fuel cell electric vehicles. However, obvious temperature rise generated during fast refueling causes serious safety risk to reliable operation of fuel cell stacks. Therefore, it is necessary to conduct in-depth research on fast filling process. Based on safety reasons, the SAE J2601/ISO 15869 strictly regulates the maximum temperature limit of 85 °C in specifications for refueling hydrogen gas tanks. In this study, a 70 MPa, Type IV on-board hydrogen storage tank is adopted as the research object, and a 2-dimensional axisymmetric numerical model is established to study the temperature rise of the vapor within storage tanks during fast refueling. The Realizable k-ε turbulence model is employed to simulate high intensity turbulent fluctuation during fast filling. Considering the compressibility of vapor, the state of equation for real hydrogen gas is used by obtaining fluid thermodynamic properties from the National Institute of Standards and Technology database. Three groups of fast filling experiments are selected to validate the developed numerical model. The comparison result shows that the numerical model has good prediction ability on hydrogen fast refueling. The final mass average temperature differences between numerical results and experimental data are 2.6 K, 4.3 K, and 0.03 K, respectively. Based on the developed numerical model, the influences of structure parameters and material properties on the temperature rise of hydrogen storage tanks are investigated. The results indicate that the inlet diameter and wall thickness of the inner and outer layers of the storage tank have weaken impacts on the temperature rise during rapid charging, with the maximum temperature differences of 1.8 K, 0.74 K, and 0.54 K, respectively. Due to the influence of heat capacity, the material properties of different layers exhibit a similar variation trend. This work can deepen researchers' understanding of the temperature rise of on-board hydrogen storage tanks during fast filling, and provide technical references for the structural optimal design of tanks and rapid refueling at hydrogen stations.

Thermodynamic analysis and modeling of the filling process of a gas tanker by shipping LNG from a large-capacity storage facility with an upgraded submersible cryogenic pump

Thermodynamic analysis and modeling of the filling process of a gas tanker by shipping LNG from a large-capacity storage facility with an upgraded submersible cryogenic pump

Optimizing seismic performance: Integrating friction dampers into spherical liquid tanks

This study addresses the vital challenge of ensuring the safe storage of Liquid Natural Gas (LNG) in spherical tanks during seismic events, focusing on the crucial balance between meeting seis- mic performance criteria and mitigating economic losses due to potential operational disrup- tions from necessary retrofitting efforts. In response to this challenge, we present a case study on retrofitting an LNG tank near the North Anatolian Fault (NAF) line of Türkiye. Through a com- prehensive seismic evaluation, this study reveals inadequacies in the existing case's compliance with seismic criteria. It suggests a remedy involving the increased stiffness of lateral force-resist- ing members coupled with the utilization of friction dampers. Following the proposed stiffness increase achieved through retrofitting, our approach is fundamental to exploring alternative damping mechanisms designed to enhance the steel column-brace support structure. One of the key design challenges is the unique dynamic behavior of LNG, especially its sloshing during earthquakes, which necessitates a comprehensive understanding of fluid-structure interaction for accurate modeling and analysis. Through a series of transient analyses incorporating actions, we evaluate the effectiveness of the proposed retrofitting measures on the structure. Our findings introduce a feasible and efficient retrofitting strategy, marked by minimal operational interrup- tion, primarily by avoiding the extensive demolition and reconstruction typically required.

Prediction of BLEVE-induced response of road tunnel using Transformer network with modified self-attention (SAMT)

Road tunnels might be exposed to Boiling Liquid Expansion Vapor Explosion (BLEVE) due to the transportation of liquified gas tankers passing through road tunnels. An efficient and accurate prediction of the response of road tunnels under internal BLEVEs can facilitate the reliable BLEVE-resistant design and risk assessment of road tunnels. This study introduces an advanced deep-learning model that employs a Transformer-based architecture with a modified self-attention mechanism, termed as Self-Attention Modified Transformer (SAMT), to predict BLEVE-induced support rotation of tunnel structure, which is a common criterion in assessing reinforced concrete structure damage to blast loads. Unlike the Transformer with the traditional self-attention mechanism, the proposed SAMT effectively aggregates global information across all variables while mitigating undue dependencies among uncorrelated variables. Consequently, the proposed SAMT is better suited for processing tabular data with uncorrelated variables. The feasibility and advantages of the proposed SAMT are verified by extensive data generated using calibrated numerical models of box-shaped road tunnels subjected to internal BLEVEs. By comparing the performance of the proposed SAMT with the non-modified Transformer network (FT-Transformer) as well as two other typical deep learning networks, i.e., Multi-layer Perceptron (MLP) and Residual Network (ResNet), it is found that the SAMT offers higher prediction accuracy and robustness than the other three models in predicting BLEVE-induced support rotations of box-shaped road tunnels. The study demonstrates that the proposed SAMT is an effective tool for the prediction of BLEVE-induced support rotations of road tunnels.

DETECTION OF LPG VEHICLES IN RISKY AREAS WITH COMPUTER VISION TECHNIQUES

Vehicle use is becoming more widespread day by day due to the world population growth. Within the scope of intelligent transportation systems, the information technologies sector and the transportation sector work in an integrated manner to solve the problems caused by the increasing number of vehicles. Data obtained with sensors and cameras are analyzed with artificial intelligence-based information technologies and used in autonomous vehicles, security, traffic management, navigation and passenger information systems. Computer vision enables machines to extract meaningful patterns and relationships from images by combining image processing and deep learning technologies. Computer vision techniques are applied in many fields such as tourism, health, industry, defense, transportation, service, e-commerce, etc. The applications developed provide solutions to various challenges in the transportation sector. For vehicles using Liquified Petroleum Gas (LPG) fuel, the gases in LPG tanks are flammable and pose a potential explosion hazard, especially in certain areas in cities. Entry of LPG vehicles is prohibited in institutions and organizations such as hospitals, shopping malls, hotels that have indoor parking services. The control method of the ban is carried out by assigning a personnel and checking the vehicle trunks. In this study, LPG fueled vehicles were automatically detected using computer vision techniques. Vehicle image data captured by mobile cameras in different provinces in Turkey were trained and compared with four different deep learning models. As a result of training and performance tests on the models, the YOLOv8 model was more effective than the other models with an accuracy of 0.994 mAP and a speed of 11.6 ms. It has been shown to be a stable model in terms of real-time monitoring in real life. It is envisaged that the developed system can contribute to the applications of computer vision techniques as well as benefit the national economy, public life safety and environmental protection.

Analysis of damage and fracture characteristics for concrete subjected to cryogenic freeze-thaw cycles: An acoustic emission and digital image correlation study

This study examines concrete's performance under cryogenic (−170 °C) freeze-thaw cycles (CFTCs), inspired by the development of all-concrete liquefied natural gas (ACLNG) tanks. Focusing on plain concrete (PC) and concrete with 3 % volume content steel fiber (SFRC3), the impact of fibers and moisture content on concrete's damage and failure characteristics pre and post cryogenic exposure is investigated. The compressive strength variation laws of concrete before and after 10 CFTCs were summarized in air-dried and water-saturated condition. Acoustic emission (AE) and digital image correlation (DIC) techniques were employed in the study to delineate the variances in failure process and fracture characteristics attributed to cryogenic exposure. Findings indicate a decline in the compressive strength of both PC and SFRC3 post exposure, more pronounced in water-saturated condition. Post-cryogenic exposure, AE signals exhibit decreased activities. The failure process of concrete is categorized into four stages based on the trends of severity index Sr and historical index Hs, both of which diminished, reflecting reduced signal strength and rate of change. AE frequency-amplitude characteristics differs between PC and SFRC3 during failure, with significant reduction in high frequency signals in SFRC3, suggesting weakened fiber-matrix bonding and increased fracture scale. The rise in the number of shear cracks nearing failure is discerned from variations in rise angle (RA) and average frequency (AF), proposing the ratio of RA to AF equal to 15 as a precursor of concrete failure. The DIC analysis shows increased crack width and numbers in both PC and SFRC3 post exposure, along with localized spalling. SFRC3 can still effectively maintain the integrity without complete breakage despite severe cracks are generated.

Seismic Response Analysis of Underground Large Liquefied Natural Gas Tanks Considering the Fluid–Structure–Soil Interaction

Seismic Response Analysis of Underground Large Liquefied Natural Gas Tanks Considering the Fluid–Structure–Soil Interaction

Genomic and morphological characterization of Knufia obscura isolated from the Mars 2020 spacecraft assembly facility

Members of the family Trichomeriaceae, belonging to the Chaetothyriales order and the Ascomycota phylum, are known for their capability to inhabit hostile environments characterized by extreme temperatures, oligotrophic conditions, drought, or presence of toxic compounds. The genus Knufia encompasses many polyextremophilic species. In this report, the genomic and morphological features of the strain FJI-L2-BK-P2 presented, which was isolated from the Mars 2020 mission spacecraft assembly facility located at the Jet Propulsion Laboratory in Pasadena, California. The identification is based on sequence alignment for marker genes, multi-locus sequence analysis, and whole genome sequence phylogeny. The morphological features were studied using a diverse range of microscopic techniques (bright field, phase contrast, differential interference contrast and scanning electron microscopy). The phylogenetic marker genes of the strain FJI-L2-BK-P2 exhibited highest similarities with type strain of Knufia obscura (CBS 148926T) that was isolated from the gas tank of a car in Italy. To validate the species identity, whole genomes of both strains (FJI-L2-BK-P2 and CBS 148926T) were sequenced, annotated, and strain FJI-L2-BK-P2 was confirmed as K. obscura. The morphological analysis and description of the genomic characteristics of K. obscura FJI-L2-BK-P2 may contribute to refining the taxonomy of Knufia species. Key morphological features are reported in this K. obscura strain, resembling microsclerotia and chlamydospore-like propagules. These features known to be characteristic features in black fungi which could potentially facilitate their adaptation to harsh environments.

Analysis of Reservoir Properties and Quantification of Hydrocarbon Volumes Within LK Field, Niger Delta, Nigeria

This work analyzes and estimates the qualities and volumes of hydrocarbons in the identified reservoirs (Thin Sand and Sand B) of the LK field in the Niger Delta, Nigeria. The LK field is a promising hydrocarbon reservoir located at the border of the Greater Ughelli Depobelt in the Niger Delta Basin. The data utilized encompassed a 3D seismic survey, which was analyzed to delineate faults, identify stratigraphic horizons, and generate maps illustrating the time and depth structures within the subsurface. Well log data, including gamma ray, resistivity, and density/neutron measurements, were analyzed to evaluate and describe the petrophysical characteristics of the subsurface rock formations. The Thin Sand reservoir unit contains natural gas, while the Sand B reservoir is divided into two separate zones: the first zone (Z1) contains natural gas, and the second zone (Z2) contains oil. For Sand B, Z1, and Z2, the gross thicknesses are 13.16m and 57.46m, net thicknesses are 11.32m and 45.39m, NTGs are 0.86 and 0.79, shale volumes (Vsh) are 0.13 and 0.21, effective porosities (?e) are 0.28 and 0.21, water saturations (Sw) are 0.11 and 0.39, and hydrocarbon saturations (Sh) are 0.89 and 0.61, respectively. For the Thin Sand reservoir, the gross thickness is 6.00m, net thickness is 4.74m, NTG is 0.79, Vsh is 0.21, ?e is 0.23, Sw is 0.12, and Sh is 0.88. The stock tank oil initially in place (STOIIP) in the Sand B, Z2 reservoir is estimated to be 46.8 million barrels, with a recoverable oil volume of 9.4 million barrels, assuming a 20% recovery factor. The stock tank gas initially in place (STGIIP) is estimated at 10.4 billion cubic feet (Bcf) in the Thin Sand reservoir and 30.6 Bcf in the Sand B, Z1 reservoir, with recoverable gas volumes projected at 8.3 Bcf and 24.5 Bcf, respectively, assuming 80% recovery factors. After estimating the volume of hydrocarbons in the known reservoirs, significant and economic amounts of gas and oil for commercial purposes were discovered. However, this research study faces challenges such as uncertainty, unreliability, and varying scales due to different origins within the field. Further research using unconventional computational tools together with high-resolution simulating software is needed to produce more detailed and accurate results.