International Journal of Petroleum Technology
The International Journal of Petroleum Technology (IJPT) is the go-to resource for researchers, academics, and practitioners seeking to stay on the cutting edge of the rapidly evolving field of petroleum technology. This interdisciplinary, peer-reviewed platform is dedicated to publishing research and development works of the highest technical standards, with an appropriate balance of practice and theory across the broad topics of Petroleum and Oil Technology. IJPT encourages original research articles and insightful reviews in all aspects of the field, with a particular emphasis on the following areas of interest: Production of hydrocarbons, Petroleum Exploration (Drilling, Production and Flow), Single and Multiphase Fluid Flows in Porous Media, Physical-Chemical Properties and Rheological Behaviour, Petroleum Geochemistry, Petro Physics, Petroleum Economics, Petroleum Geology, Oil Refining and Process Engineering, Synthetic Fuel Technologies, Oil Shale Technology, Drilling, and Drilling Fluids. In addition to providing cross-learning between scientific and technological realms, IJPT also takes into account the public's concerns regarding environmental, health, and safety issues. This includes original investigations focused on the multiscale approach of the modern, sustainable green petroleum and oil technology that is set to be encountered in the factory of the future. Process intensification that requires new green technologies such as catalysts, green solvents, exchangers, reactors, and separation equipment is also covered in IJPT.
All the published articles are licensed under the terms of the Creative Commons Attribution Non-Commercial License (CC BY-NC 4.0) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
Evaluating the Role of Formation Temperature in Rate of Penetration Prediction Using Machine Learning: A Case Study from Niger Delta
Accurate prediction of Rate of Penetration (ROP) is critical for optimizing drilling efficiency and reducing costs in hydrocarbon exploration. Traditional ROP models often overlook formation temperature, despite its significant influence on rock mechanics and drilling fluid rheology, particularly in high-temperature sandstone reservoirs like those in the Niger Delta. This study employs three machine learning (ML) algorithms—Support Vector Regression (SVR), Random Forest (RF), and Artificial Neural Networks (ANN)—to evaluate the contribution of formation temperature to ROP prediction. A dataset of 1,200 drilling records from Niger Delta wells was used, incorporating parameters such as weight-on-bit (WOB), rotary speed (RPM), pump pressure, and formation temperature. Model performance was assessed using R², Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE), with ablation studies to isolate temperature’s impact. Inclusion of formation temperature improved ROP prediction accuracy across all models. The ANN achieved the highest performance (R² = 89.3%, RMSE = 0.387, MAE = 0.141), followed by RF (R² = 90.5%, RMSE = 2.737, MAE = 0.900) and SVR (R² = 87.8%, RMSE = 0.553, MAE = 0.169). Temperature omission led to significant performance degradation (R² reductions of 7–13%). Sensitivity analysis ranked temperature among the top three influential features. Formation temperature is a critical but underutilized parameter in ROP modeling. ML techniques, particularly ANN, demonstrate superior capability in capturing nonlinear temperature-dependent effects, offering actionable insights for real-time drilling optimization in thermally complex formations. This study provides a framework for integrating thermal data into predictive models to enhance drilling efficiency in the Niger Delta and analogous basins.
Copyright (c) 2025 Oserei Favour, Oluwaseun Taiwo, Izuchukwu Ojukwu, Ame Enosolease, Kelani Bello https://creativecommons.org/licenses/by-nc/4.0
Risk-Adjusted Real Options Valuation for Petroleum Investments: An Expected Utility–Based Decision Framework
Despite the growing use of decision analysis in oil and gas investments, the industry continues to underperform in generating consistent value. Conventional valuation methods often treat uncertainty as a risk to be minimized rather than an opportunity to be exploited, overlooking the strategic role of managerial flexibility, or real options. At the same time, they typically assume risk neutrality, which misrepresents the industry’s inherently risk-averse decision-making culture. Common risk measures such as value-at-risk fail to capture true preferences, leading to distorted valuations and suboptimal decisions. This study addresses these limitations by integrating Real Options Valuation (ROV) with Expected Utility Theory (EUT) to jointly incorporate flexibility and risk preferences into petroleum project evaluation. The contribution lies in a fully operational workflow that links influence-diagram structuring, probabilistic uncertainty modelling, and certainty-equivalent valuation within a recombining binomial decision tree. The framework is applied to a representative oil production project featuring divestment and buyout options. Risk aversion is represented through an exponential utility function, with project values expressed as certainty equivalents reflecting subjective risk tolerance. Findings show risk preferences fundamentally alter value and optimal strategy. A risk-neutral decision-maker values the project at $280.9 million, while one with a $20 million risk tolerance values it at $200.2 million. Strategically, the risk-neutral agent continues operations in 50% of scenarios, whereas the risk-averse agent divests in 75%. Sensitivity analysis identifies a tipping point near 30 million USD, beyond which choices converge toward risk neutrality. Overall, the proposed ROV–EUT framework delivers realistic, decision-consistent valuations and clarifies how flexibility protects downside exposure for conservative firms while enabling opportunity capture for more risk-tolerant ones.
Copyright (c) 2025 Rouholah Ahmadi https://creativecommons.org/licenses/by-nc/4.0
Drilling of the First Horizontal Well in Western Turkmenistan
Currently, the study of early horizontal drilling operations in Western Turkmenistan is of renewed interest, as it represents one of the first technological milestones in the region’s petroleum engineering history. The development and analysis of horizontal well drilling techniques in the early 1990s provided valuable insights into the practical implementation of new directional drilling technologies under complex geological and pressure conditions. This study presents a detailed technical and historical analysis of the first horizontal wells drilled in the Koturdepe field between 1990 and 1992. The paper examines the well design, drilling assemblies, drilling fluids, and directional control systems used, and evaluates their technical performance and economic impact. Unlike a purely historical report, this work emphasizes the scientific and engineering lessons learned from these early operations and discusses their relevance to modern drilling practices in Turkmenistan. The research also includes an economic comparison between horizontal and vertical wells, demonstrating how the initial cost premium of horizontal drilling was offset by significantly higher productivity. The results are of practical importance for optimizing drilling technologies in fields with abnormally high reservoir pressures and for applying these lessons to modern digital drilling systems.
Copyright (c) 2025 Annaguly Deryaev https://creativecommons.org/licenses/by-nc/4.0
Unveiling the Geological Mysteries: Tectonics, Evolution, and Hydrocarbon Play Types of the Andaman–Nicobar Basin from Seismic Data
The Andaman–Nicobar Basin, located at the convergent margin between the Indian and Eurasian plates, is one of the most tectonically dynamic and geologically complex frontier basins in the northeastern Indian Ocean. Utilizing over 23,500-line kilometers of newly acquired 2D seismic data (2021–2023) integrated with legacy datasets and well information, this study redefines the basin’s tectonic framework, stratigraphic evolution, and hydrocarbon potential. Seismic interpretation delineates a classic arc–trench–backarc system comprising the Andaman Trench, accretionary prism, volcanic arc, and backarc spreading centers, reflecting ongoing subduction and extensional tectonics. Paleo-flattening and facies analyses reveal a multi-phase evolution involving initial rifting in the Late Eocene–Oligocene, post-rift marine transgression with carbonate platform development, and Miocene to Recent inversion related to India–Eurasia collision. Four key hydrocarbon play types are identified: syn-rift clastic, early post-rift carbonate, early post-rift clastic, and late post-rift clastic systems, with reservoir porosity ranging from 12% to 25% and thickness up to 2.5 km. This work refines earlier tectono-stratigraphic models by delineating new structural highs, spreading centers, and untested plays in forearc and western backarc sectors. The results highlight promising exploration potential, particularly within early post-rift carbonate and late post-rift clastic plays, offering a robust framework for future hydrocarbon exploration in this frontier basin.
Basin stratigraphy and petroleum potential
Copyright (c) 2025 Surajit Gorain https://creativecommons.org/licenses/by-nc/4.0
Development of an ANN-Driven Empirical Equation for Real-Time Prediction of Natural Gas Flow through Surface Well Chokes
To maximize production efficiency, natural gas flow via surface well chokes must be optimized. The nonlinear character of this flow frequently causes problems for conventional empirical correlations and mechanistic models. To accurately forecast gas flow rates using field data, this study develops an Artificial Neural Network (ANN) model that considers temperature, gas gravity, choke size, and pressures. The main innovation is that the optimized network is used to derive an exact, closed-form empirical equation, going beyond the typical "black-box" use of ANN. This equation enables the estimation of flow rate in real-time without requiring the execution of the ANN model, providing engineers with a valuable tool at present. The 5-neuron optimized ANN demonstrated remarkable accuracy, with training and testing average absolute percentage errors (AAPE) below 2% and a correlation coefficient (R) over 0.99. When tested on unknown data, the resultant equation performed well (R=0.999, AAPE=2.78%), outperforming conventional techniques in terms of generalization and predictive power. By connecting data-driven analytics with field operational realities for well management, this research represents a significant leap forward.
Copyright (c) 2025 Ashraf Ahmed, Ahmed A. Mahmoud, Murtada A. Elhaj, Salaheldin Elkatatny https://creativecommons.org/licenses/by-nc/4.0
Exploration of White Hydrogen: Drawing Global Analogy to Unveil the Potential of the Andaman Basin's Sea Floor Spreading Center
Hydrogen is increasingly recognized as a critical element in the global energy transition, offering a path to decarbonize power generation, industry, and transportation. While green and blue hydrogen dominate current production strategies, natural hydrogen—commonly termed white hydrogen—remains largely underexplored despite its potential as a continuous, low-cost, and carbon-neutral energy resource. White hydrogen forms endogenously through geological processes, including serpentinization of ultramafic rocks, mantle-derived reactions, radiolysis, and organic matter decomposition. Global occurrences in cratonic shields, ophiolites, intracratonic basins, and mid-ocean ridges demonstrate the widespread yet underutilized nature of this resource. This study investigates the Andaman Basin, a tectonically active seafloor spreading center, as a prospective frontier for white hydrogen exploration. Integrating geological and seismic observations with the hydrogen system model, I evaluate the mechanisms controlling hydrogen generation, migration, and accumulation. Seismic data reveal structural and stratigraphic features conducive to serpentinization-driven hydrogen generation, fault-controlled migration pathways, and potential entrapment beneath marine shales. The study further identifies complementary targets in the western Andaman subduction zone. A strategic exploration framework combining play- and prospect-level investigations—including geophysical surveys, soil gas sampling, exploratory drilling, and laboratory analyses—is proposed to systematically delineate potential accumulations. The findings underline the scientific and economic promise of white hydrogen in the Andaman Basin, offering insights for sustainable energy development and informing global analogs in hydrogen exploration.
Formulation of a Water-Based Drilling Fluid with Natural Aloe Vera Additive for Enhancing Filtration Properties
The search for natural additives to improve the performance of water-based drilling fluids (WBDF) has been fueled by the growing need for environmentally friendly and sustainable drilling processes. The objective of this study is to examine the potential utilization of Aloe Vera (AV) powder as a natural additive in WBDF through an experimental analysis of filtration properties. All experimental studies adhered to the American Petroleum Institute (API) standard procedure in order to accomplish the objectives mentioned above. In this experiment, a mixture of water phase volume of (350 ml) and chemical components like xanthan gum (0.8 gm), sodium hydroxide (0.8 gm), bentonite (13 gm), and barite (18 gm) were used to prepare base mud. Samples 1, 2, and 3 are created using 0.25%, 0.5%, and 0.75% weight of aloe vera powder (size less than 150 µm) in relation to water volume, while sample 4 was created using 0.5% weight of aloe vera powder (size less than 212 µm) in relation to water volume. The standard cell is used in the low-pressure mud filtration test, which was conducted for 30 minutes at room temperature with an API condition of 100 psi. Based on the laboratory analysis, this study suggests that AV powder has the potential to be an environmentally beneficial additive for usage in specialized drilling environments rather than generalized drilling operations. Specially, the 0.5% concentration of AV powder with particle size less than 150 µm demonstrated improved fluid loss management for water-based drilling fluid. This study offers a comprehensive evaluation of its influence on the fluid's behavior, with a focus on the drilling fluid's filtration performance. The outcome of the experiment indicates that WBDF containing aloe vera is an economical and environmentally beneficial additive for reducing filtration loss and preventing significant fluid loss during drilling operations.
Copyright (c) 2025 Md. Siam Al-Mukit, Ahmed Elghoul, Mohammad Islam Miah, Travis Wiens https://creativecommons.org/licenses/by-nc/4.0
Genetic Algorithm Optimization of Crude Oil Pipeline Operations for Wax Control: A Case Study of CNPC-Niger Petroleum Company
Wax formation and deposition in crude oil pipelines pose a very significant challenge, such as flow restriction, increased cost of maintenance and potential shutdowns. The goals of this study are to reduce wax accumulation in the China National Petroleum Corporation-Niger Petroleum (CNPC-NP) pipeline network, which connects the Agadem oil fields to the SORAZ refinery, by optimizing critical operating conditions. The Reliability of Aspen HYSYS for analyzing wax behavior was validated by the simulation model that closely matched the real-world data, with a simulated flow rate of 182.49 m³/h with, only 0.27% higher than the actual 182 m³/h. The study suggested changing the operating condition using a genetic algorithm method of optimization, which indicates a slight increase in the pressure from 0.6 MPa to 0.65 MPa, while decreasing in temperature from 51°C to 48.5°C and a potential increase in the flow rate to 187.49 187.49 m³/h. Furthermore, the results of the optimization led to a decrease in wax thickness from 0.058 mm to 0.0409 mm, which indicated an improvement in pipeline operating conditions. Also, the economic analysis revealed, the total capital investment was roughly $3.3 million, and the annual operating expenses were estimated to be $2.4 million. The financial indicators include an Internal Rate of Return (IRR) of 9%, a Net Present Value (NPV) of $2.14 million and a Profitability Index (PI) of 1.99, all of which were higher than the IRR of the current CNPC-Niger Petroleum, which was 8%. The results show that the economic performance of the crude oil pipeline system can be improved, and wax formation risk can be effectively decreased by combining simulation-driven decision-making with strategic operational parameter adjustment.
Copyright (c) 2025 Maman I. Salissou, Usman Hassan, Ibrahim Ayuba, Ahmed M. Inuwa https://creativecommons.org/licenses/by-nc/4.0
Development of Biodiesel Production Strategies for Blending Purposes in Biorefineries: A Review
The rising demand for diesel fuel amidst declining fossil reserves, volatile oil prices, and stringent emission regulations has driven the expansion of biodiesel production. Biodiesel, primarily produced as fatty acid alkyl esters via catalytic transesterification of triglycerides, offers advantages over fossil diesel, including environmental friendliness, non-toxicity, and enhanced lubricity. However, its limited oxidation stability, energy density, and cold flow properties restrict blending ratios with conventional diesel to prevent engine performance issues. Alternative methods, such as hydrotreated vegetable oils (HVOs), face challenges related to hydrogen dependency and cost. This review explores current biomass-derived diesel production methods and proposes a cost-effective strategy for industrial-scale biodiesel with improved stability, energy content, and cold flow characteristics. This approach aims to enable higher blending ratios with mineral diesel, reducing dependency on finite fossil resources while promoting cleaner, renewable energy use.
Copyright (c) 2025 Standford Mirainashe Pedzisai, Joshua Gorimbo, Diankanua Nkazi https://creativecommons.org/licenses/by-nc/4.0
Integrated Surveillance and Reservoir Characterization Evaluation for Preliminary Water Injection Optimization Strategy of Carbonate Reservoir
The RS field is a green oil field that is in development stage with a carbonate reservoir as the interest zone. A Zone is one of the reservoir zones of the field with the highest oil reserve and has been produced since October 2019. A water injection program has been applied through one injection well since November 2020. The significant pressure decline is an indicator that the injection program in A Zone is not optimum in maintaining the reservoir pressure. There is no dynamic model for reservoir performance forecasting. Therefore, a further detail and comprehensive analysis through monitoring surveillance and reservoir characterization is required. The objective is to optimize the pressure maintenance program and to increase the oil recovery of A Zone in RS field. This study consists of three steps of analysis: the evaluation of existing water injection (pressure maintenance) surveillance; reservoir characterization evaluation; and 1-D reservoir simulation study. Surveillance analysis includes production and injection performance analysis; pressure performance analysis; voidage replacement ratio (VRR) analysis; Hall’s Plot analysis and Chan’s Diagnostic Plot analysis. Reservoir characterization evaluation includes remaining reserve evaluation; drive mechanism analysis; reservoir displacement profile phase based on fractional flow analysis (Buckley-Leverett); quality and reservoir heterogeneity; and reservoir pressure condition analysis. Material balance modelling is used as an initial simulation for optimization of injection wells and production performance prediction. Based on production prediction model material balance, if produced with VRR = 1, until the end of the contract (October 2039), the A Zone reservoir is capable of producing oil with a flow rate of 3038.36 BOPD; capable of maintaining reservoir pressure up to 1679.28 psig; water cut reservoir reached 77.82%; and cumulative oil production is 31.14MMSTB or equivalent to 12.50% of recovery factor.
Copyright (c) 2024 Redy Setiawan, Aris Buntoro, Boni Swadesi, Ferdinandus K. Latuan, Shaziera Omar, Ammar S.N. Murtaza https://creativecommons.org/licenses/by-nc/4.0
A Review of the Intrinsic Parameters Affecting the Elastic Characteristics of Heterogeneous Carbonate Reservoirs: Insights from Laboratory Assessments
This research provides an in-depth analysis of how various parameters such as mineralogy, density, porosity, temperature, pressure, and structural features impact the velocities of sonic waves in carbonate rocks. Our findings reveal that the mineral composition significantly influences the elastic behavior of these rocks. The density and elastic properties of minerals, especially clay minerals, play a crucial role in affecting porosity and predominant pore types. The porosity of carbonate reservoirs impacts their elastic properties, leading to variations in sonic wave velocities depending on the different pore types present. For a given porosity, the velocities can vary considerably due to the presence of diverse pore types within the pore space. Non-interconnected porosities with spherical or near-spherical shapes, along with microporosity, alter the effective elastic properties of the rock. Additionally, temperature affects the velocity-porosity relationship in rocks, with experimental results showing a decrease in P-wave velocity as temperature increases. Under reservoir conditions, wave velocity in carbonate rocks is influenced by factors such as confining pressure, temperature, gas saturation, and effective stress. Specifically, P-wave velocity increases with confining pressure as soft pores and cracks gradually close, enhancing the dry rock bulk shear modulus. Conversely, rising temperatures cause a slight decrease in velocities and an increase in attenuation. In conclusion, this study enhances our understanding of the physical properties and behavior of carbonate rocks under reservoir conditions, thereby contributing to the exploration and production of hydrocarbon resources.
Copyright (c) 2024 Seyed M. Hazaveie, Babak Aminshahidy, Mohammad Nikbin https://creativecommons.org/licenses/by-nc/4.0
A Novel Technique in Determining Mud Cake Permeability in SiO2 Nanoparticles and KCl Salt Water Based Drilling Fluid using Deep Learning Algorithm
The permeability of the mud cake formed at the formation-wellbore interface is an important factor in the designing of water-based drilling fluids. This study presents a novel approach to utilizing experimental thixotropic and rheological parameters of polymeric water-based drilling fluids having varying concentrations of SiO2 nanoparticles and KCl salt. A fully connected feed-forward multi-layered neural network, more commonly known as a Multilayer Perceptron (MLP) was developed to predict the mud cake permeability using input parameters such as SiO2 & KCl concentration, differential pressure, temperature, mud cake thickness, API LPLT and HPHT filter loss volume and spurt loss volume. The results suggested that the developed Multilayer Perceptron model effectively determined the mud cake permeability based on the input parameters of the WBDF mentioned above. The model converged on the global minima, minimizing the loss function using the Gradient descent algorithm. A higher Coefficient of Determination (R2) value i.e., 0.8781, and a lesser Root Mean Square Error (RMSE) value i.e., 0.04378 indicates the higher accuracy of the model. Pearson’s Coefficient of Correlation obtained via the heatmap indicates that mud cake permeability is strongly influenced by the differential pressure followed by filter loss volume, spurt loss volume, mud cake thickness, and temperature. Previous similar studies have focused on using machine learning algorithms, this study utilized a robust deep learning algorithm i.e., Multilayer Perceptron (MLP) neural network to simultaneously model the combined effects of SiO2 nanoparticles and KCl salt concentrations on mud cake permeability, offering an unprecedented level of accuracy in predicting key WBDF performance parameters.
Copyright (c) 2024 Muhammad A. Khan, Faiq A. Abbasi, Shaine M. Lalji, Syed I. Ali, Mei-Chun Li, Mujtaba Mateen, Muhammad Mustafa https://creativecommons.org/licenses/by-nc/4.0
Performance of the Petroleum Reservoir Under Waterflooding at the Petrochad Field in Mangara-Chad
The Mangara petroleum field is made up of three superimposed reservoirs (C, D, E) with approximately 2500 m depth. These are unconsolidated sandstone reservoirs with an underlying active aquifer. The petrophysical properties of the reservoirs are relatively good as it’s a self-sourced unconventional reservoir based on its organic richness characteristics unconventional resource opportunity as tight carbonate reservoir. Tank pressure is approximately 2900 psi, for an average temperature of 180°F. Of the 50 wells initially drilled, 23 are currently producing. The pressure is support by 04 injector wells, and daily production is estimated at approximately 12,000 bbl/d. To maximize oil production and minimize water production, the positions of injection wells were moved, which permitted to reduce the number of producing wells from 23 to 18. The result revealed that this scheme can maintained the pressure at desired levels of 2900 psi, until year 2040 and reversed the current trend in water production, which was 14,000 bbl/d. In the predicted scenarios, cumulative production will be maintain at 25,000 bbl/d with a daily production of around 18,000bbl of oil compared to formerly figure of 7000 bbl of water until 2040.
Copyright (c) 2024 Bakimbil Brahim, Samba K. Prosper, Roger D. Djoulde https://creativecommons.org/licenses/by-nc/4.0
Role of Underground Carbon Storage to Assist Reaching Net Zero by 2050: Perspectives on Petroleum Reservoirs
This article focuses on the critical role of sedimentary basins in underground carbon storage. Focusing on both depleted petroleum reservoirs, as well as sedimentary reservoirs in the field’s petroleum stratigraphy (associated sedimentary reservoirs), it highlights the importance of complete CO2 storage in saline aquifers associated with petroleum reservoirs. This paper provides a novel approach to the understanding of underground carbon sequestration (UCS) by combining the examination of target reservoirs and regulation of activities in these reservoirs. By combining this consideration of physical characteristics with legal issues arising from the regulation of UCS, and their application to emerging Australian UCS projects, this novel evaluation of the progress in UCS provides a unique insight into Australian existing and planned UCS Projects. The findings of the research indicate that depleted petroleum reservoirs are more suited to enhanced oil recovery techniques, while associated sandstone reservoirs (saline aquifers) of the same formation are more suited to UCS. The suitability of a reservoir should be considered in the regulation of UCS activities. The example of Australia presented in this paper demonstrates the difficulties in such regulation.
Carbon capture, utilization, and storage (CCUS)
Underground carbon dioxide sequestration (UCS)
Copyright (c) 2024 Tina Soliman Hunter https://creativecommons.org/licenses/by-nc/4.0
Reservoir Characterization Using Seismic Inversion Based on Sparse Layer Reflectivity and Hybrid Genetic Algorithms: A Comparative Case Study of Blackfoot, Canada
This research paper introduces a comparative case study on reservoir characterization through seismic inversion techniques. The study specifically explores sparse layer reflectivity and a hybrid approach involving genetic algorithms and pattern search. The research assesses the effectiveness of these methodologies in delineating subsurface properties, with a particular focus on acoustic impedance. Through meticulous analysis, the paper aims to identify the strengths and limitations of each method, considering factors such as parameter estimation precision, computational efficiency, and adaptability to complex geological structures. The findings contribute valuable insights for selecting optimal seismic inversion techniques in reservoir characterization, advancing our understanding of how the integration of sparse layer reflectivity and hybrid genetic algorithms can enhance subsurface imaging accuracy and reliability. The results obtained from our inversion process significantly enhance the interpretation of seismic data by providing detailed insights into the subsurface. Both the sparse layer reflectivity (SLR) and hybrid genetic algorithm (HGA) algorithms have exhibited outstanding performance when applied to real datasets. The inverted impedance section reveals notable low acoustic impedance ranging from 8000 to 8500 m/s g/cc. This distinct zone, identified as a reservoir (sand channel), is located within the time interval of 1040–1065 ms. Our observations indicate that HGA demonstrates superior correlation results not only in the vicinity of well locations but also over a broader spatial range, suggesting its potential to provide higher-resolution outcomes compared to SLR.
Copyright (c) 2023 Nitin Verma, Ravi Kant, Raghav Singh, Satya P. Maurya, Gopal Hema, Ajay P. Singh, Kumar H. Singh https://creativecommons.org/licenses/by-nc/4.0
Interpretation of Neural Network Models – New Insights of Estimating Static Bottom-Hole Pressures of Gas Wells in Nigerian Petroleum Provinces
Methods to determine static bottom-hole pressure (BHP) from surface measurements include the average temperature and z-factor method, the Sukkar-Cornell method, the Cullender-Smith method, and the Poettmann method. Among these methods, the Poettmann method is preferable in the petroleum industry but with a concern for software developers, as the integral values to determine the static BHP are tabular. In this study, neural network-based models to predict the integral values using pseudo-reduced pressures and temperatures were developed. The 2-3-1, 2-4-1, and 2-5-1 neural-based models had overall correlation coefficients (R) of 0.9974, 0.99835, and 0.99745, respectively, for the maximum-minimum normalization method and R of 0.99745, 0.99805, and 0.9992 for the clip-scaling method. Comparing the models' predictions with the Lagrangian interpolated values resulted in R of 0.99895 and 0.9995 for the maximum-minimum and clip-scaling-based models. Thus, the developed models can predict Poettmann's integral values without table look-up to estimate static BHP in gas wells.
Copyright (c) 2023 Clement E. Udoma, Anietie N. Okon, Stella U. Udoeyop, Wilfred C. Okologume https://creativecommons.org/licenses/by-nc/4.0
Rock Typing and Characterization of the Late Cretaceous Abu Roash "G" Reservoirs at East Alam El-Shawish Field, Western Desert, Egypt
Rock typing and petrophysical characterization play a vital role in constructing reservoir models for petroleum exploration and development. This study focuses on evaluating the petrophysical characteristics of the Late Cretaceous Abu Roash "G" Reservoirs at the East Alam El Shawish field in Egypt's Western Desert. The study involved five vertical wells and employed various techniques and analyses to investigate the reservoir. Lithology determination utilizing well logs and core analysis helps identify the lithology types and corresponding porosity of the Abu Roash "G" reservoirs. Sandstone and limestone lithologies with varying porosity ranges were identified, along with the influence of shale on neutron porosity values. Facies analysis of the Abu Roash "G" Member identified seven lithofacies types, categorized into shallow marine and deeper marine depositional environments. The petrophysical analysis involves evaluating gamma-ray logs, porosity, permeability, flow zone indicator (FZI), and reservoir quality index (RQI) values for each lithofacies type. This analysis classifies the core samples into seven reservoir rock types (RRT1 to RRT7) based on petrophysical attributes, providing a clear classification of the Abu Roash "G" reservoir interval. RRT1, RRT2, and RRT3 exhibit the highest reservoir quality, while RRT4 and RRT5 indicate moderate reservoir quality. RRT6 and RRT7 exhibit low reservoir quality due to unfavorable petrophysical behavior. The findings of this study provide valuable insights into the Abu Roash "G" reservoir, including its lithofacies, reservoir properties, and depositional environments. This knowledge is crucial for reservoir characterization and optimizing oil production strategies in the region.
Copyright (c) 2023 Marwan M. Sabry, Mohamed I. Abdel-Fattah, MohamedMohamed K. El-Shafie https://creativecommons.org/licenses/by-nc/4.0
Investigating the Impact of Pores on Rock Damage during Thermal Spalling Drilling
Numerous microcracks and pores in geological rock formations cause early flaws. High temperatures increase these fractures and pores, thermally damaging reservoir rocks and changing the rock failure mechanism. However, research on pores' high-temperature thermal spalling and fragmentation effects on heterogeneous rocks is sparse. This study built a finite element numerical model of heterogeneous granite rock thermal damage with pores based on rock thermal fracture theory and the Voronoi method and explored the mechanism under varied pore settings. The research's findings indicate that the application of high temperatures to local heterogeneous porous rocks results in a higher proportion of tensile damage. The proportion of shear damage and tensile damage constantly varies due to the changing position and shape of the pores. The rock's porosity has the effect of decreasing temperature in the direction of heat transfer while increasing the extent of temperature transfer along the pore parallel to the heating surface. The potential degree of damage increases as the density of pores increases, the distances between them decrease, and the pore lengths increase. The thermal damage resulting from heating in the vicinity of the pore is primarily localized in the area between the pore and the heated surface. This effect becomes more significant as the distance between them decreases. The findings of this study can serve as a theoretical framework for understanding the impact of rock pores on rock thermal fracturing and fragmentation in the thermal spalling-assisted development of deep oil and gas resources.
Copyright (c) 2023 Weiji Liu, Feilong Yang, Xiaohua Zhu https://creativecommons.org/licenses/by-nc/4.0
Selection and Application of Beam Pumping Unit for Heavy Oil Production
Beam pumping units were among the first and are still among the most widely used artificial lift systems. This study investigates the components of beam pumping units and the manufacturing mechanism and design procedure recommended by Recommended Practice and the QRod simulator. The API provides API RP 11L Recommended Practice to obtain the values and operating characteristics for each component in dimensionless form. A trial-and-error method is used during the design procedures to determine the best surface and subsurface equipment for a given well's data. When completing a well, the artificial lift method must be considered to ensure that the well is able to be produced at a satisfactory rate. Besides, the procedures created nine cases to compare the requirements of different production rates and depths for a heavy oil well with 14 APIs. A depth of 5,000 ft with a rate of 300 bbl/day and a depth of 7,000 ft with a rate of 500 bbl/day is the specific production rate and depths at which the well will produce. For 300 BBL/Day the tubing size selected was 2-7/8” OD, for this size the suitable plunger size is 2”, and the suitable stroke length was 74in. In cases 6, 8, and 9, all the simulated rod strings were unable to handle the stress imposed by the combination of high depth and high production rate. As a result, all designed systems will fail during production.
Copyright (c) 2023 Raddad S. Bahuda, Elhassan M. Abdallah, Yasir Mukhtar, Waqar A. Khan https://creativecommons.org/licenses/by-nc/4.0
Experimental Measurements to Study Correlations between Porosity, Absolute Permeability, and Capillary Pressure
Rock permeability is a measurement of how easily a fluid can flow through a rock while porosity is a measure of the rock’s storage capacity or its pore volume that is capable of holding fluids. In many cases correlations may exist between porosity and permeability, however, these correlations are usually derived for a certain formation, and therefore they do not exhibit general application or validity. Cross-plot of permeability versus porosity data, to create a porosity-permeability transform, is sometimes used to assign permeability values to areas of a reservoir where permeability data are unavailable. The capillary pressure curve is also used to predict rock absolute permeability. In the present work, porosity, absolute permeability, and capillary pressure were measured experimentally to investigate and establish new correlations between porosity, Klinkenberg-corrected permeability, and capillary pressure. Fifty-nine core plugs, obtained from two different fields located in Sirte basin, Libya, were utilized. Results indicate that porosity might be a reasonable estimator of permeability, as correlations between porosity and permeability were observed and empirical permeability equations based on porosity were established. Capillary pressure was observed to be overall inversely proportional to permeability, however, determined capillary pressure curves varied within the same formation.
Permeability-capillary pressure relationship
Copyright (c) 2023 Walid M. Mahmud, Adel M. Jaluta https://creativecommons.org/licenses/by-nc/4.0
Prediction of Petrophysical Properties using Post Stack Seismic Inversion and Geostatistical Techniques over F-3 Block, Netherlands - A Comparative Study
To estimate petrophysical parameters, seismic inversion techniques have been frequently used for estimating attributes like P-impedance, elastic impedance, S-impedance, density, Vp / Vs ratio, and gamma-ray logs from seismic and well-log data. These characteristics enable us to comprehend subsurface lithology for geo-seismic analysis, including its extent and shape. Four different post-stack inversion techniques, including bandlimited inversion (BLI), colored inversion (CI), maximum likelihood sparse spike inversion (MLSSI), and model-based inversion (MBI), have been applied to the post-stack seismic data from the F3 block in the Netherlands in this study. The objective is to compare the efficacy of these inversion methods over F3 block seismic data. For post-stack inversion, the data was inverted into a very high-resolution P-impedance volume. The analysis depicts that all four inversion methods provide mutually consistent subsurface information with marginally better MBI results. Furthermore, geostatistical techniques have been used intensively for further testifying the results obtained from post-stack inversion methods. The geostatistical techniques use seismic data-derived attributes and inverted impedance-derived attributes as input to estimate P-wave velocity, porosity, and density away from the boreholes. Two geostatistical methods namely probabilistic neural network (PNN) and multilayer feed-forward neural network (MLFN) are used for the analysis. Porosity, density, and P-wave velocity have been predicted using both techniques which highlighted different characteristics of the subsurface with very detailed information. The derived results show that reservoir properties have been better estimated with the combination of MBI and PNN techniques for F3 block data over the other methods used in this study.
Copyright (c) 2023 Prabodh K. Kushwaha, Raghav Singh, Satya P. Maurya, Piyush Rai https://creativecommons.org/licenses/by-nc/4.0
A Review on Fundamentals and Capturing Petroleum Fluid Hysteresis Through Experiments
Hysteresis is proven to have a significant role in petroleum fluids and other disciplines for better understanding and evaluation. This shows a need to be explicit about precisely what is meant by the word "hysteresis." For a long time, the term hysteresis has been used and has attracted the attention of most researchers and investigators. Despite its common usage, hysteresis is used in different disciplines to mean different things. Thus, hysteresis has many definitions depending on the book or paper's area of interest. While various definitions of the term 'hysteresis' have been suggested, this paper will focus on the definition in the oil and gas industry. Hysteretic impacts petroleum fluids either positively or negatively. Therefore, accurately estimating fluid properties curves is vital in evaluating hydrocarbon recovery processes. This paper addresses and discusses a comprehensive review of the hysteresis of different petroleum fluid properties and their applications. This paper reviews many fluid properties of hysteresis and investigates them experimentally. Numerous laboratory studies in hysteresis are present in the literature and critically reviewed and highlighted in this research. This paper aims to review the experimental processes of fluid hysteresis extensively. To satisfy this aim, this paper offers insights into and explanations for experiments that have been used in fluid hysteresis. The outcomes highlight some missing concepts of the existing models and experimental processes for fluid hysteresis. Furthermore, this paper tracks the current development of hysteresis and gives insight into the future trends in the application of hysteresis.
Copyright (c) 2023 Murtada Elhaj https://creativecommons.org/licenses/by-nc/4.0
Geo-Body and Geostatistical Modelling of Carbonate Reservoir Facies Architecture and Characterization
Carbonate reservoirs present significant challenges in characterizing and extracting hydrocarbons due to their low permeability, matrix heterogeneities, fractures, and dissolution patterns. Accurately predicting the facies architecture and reservoir properties in such complex formations has been a persistent challenge for geoscientists. This paper proposes an integrated approach that combines geo-body extraction and geostatistical modeling to accurately predict the facies architecture and reservoir properties in carbonate reservoirs. The methodology begins by generating 3D seismic root mean square amplitude (RMS) attributes, which are then used to extract geo-bodies along the pay sequences. The extracted geo-bodies are then subjected to geostatistical modeling to analyze reservoir properties to facilitate the optimization of drilling and production strategies. To validate the effectiveness of the proposed approach, a small field in the Mumbai offshore basin is chosen as a case study. This field is located on the Mumbai High-Deep Continental Shelf and exhibits westerly dipping structures. Structural mapping confirms the presence of an antiformal structure, with one particular well (D-8) at the crest showing the absence of hydrocarbons. The proposed approach mapped two seismic reflectors within the reservoir zones and generated window-based 3D seismic RMS attributes to extract three geo-bodies within the reservoir. Facies and property modeling revealed the presence of distinct non-reservoir facies with poor reservoir properties near dry wells (D-8, D-4, and D-7), which is in line with the production performance observed in the drilled wells. The proposed integrated approach of geo-body extraction and geostatistical modeling is effective in delineating the facies architecture and reservoir heterogeneity of carbonate reservoirs. It enables the identification of favorable reservoir facies and facilitates a comprehensive assessment of the remaining potential.
Copyright (c) 2023 Surajit Gorain https://creativecommons.org/licenses/by-nc/4.0
Feasibility of CO2 Injection for Enhance Oil Recovery: A Case Study in the KMJ Layer of HKY Field
Carbondioxide (CO2) injection is a very effective and proven technology for enhanced oil recovery (EOR). Minimum miscibility pressure (MMP) and oil swelling are two important factors of the CO2 gas displacement mechanism that occurs in the reservoir when CO2 injection is applied to enhance oil recovery. In this study, MMP determination between crude oil samples and CO2 gas has been conducted using three methods, i.e., empirical equation, correlations method, and laboratory experiment using slimtube. The determination of the swelling factor was conducted using a PVT cell, where recombined fluid is injected at the reservoir temperature. The MMP value from the empirical equation (2810 psig) is relatively close to the MMP value from the laboratory experiment (2807 psig), with a difference of 3 psig. The swelling test results show that the bubble point pressure and the swelling factor increase from 410 psig to 2200 psig and from 1.0 to 1.442, respectively, as the CO2 gas injection reaches 46.82% mole. Since the fracture pressure of the KMJ Layer in the HKY Field is 2200 psig and the MMP is 2807 psig, only immiscible CO2 flooding can be applied in the field because the CO2 MMP is higher than the fracture pressure.
Copyright (c) 2023 Dedy Kristanto, Hariyadi, Luky A. Yusgiantoro https://creativecommons.org/licenses/by-nc/4.0
Study on the Influence Law of Temperature Profile of Water Injection Well
Due to the lack of knowledge on the influence law of the temperature profile of layered water injection wells, it is still highly challenging to quantitatively diagnose the water injection profile of layered water injection wells using distributed optical fiber temperature sensing (DTS). In this paper, a temperature profile prediction model for layered water injection wells has been developed by considering the micro-thermal effect and non-isothermal reservoir seepage. The influence of various single-factor changes on the temperature profile of layered water injection wells is simulated and analyzed. Orthogonal experiment analysis results demonstrate that the sensitivity of different factors on wellbore temperature from strong to weak is the injection temperature of the water, injection time, water injection rate, wellbore diameter, formation thermal conductivity, wellbore trajectory, and the permeability of injection formations (Tinj＞t＞Qinj＞D＞Kt＞θ＞k). The injection temperature of water, injection time, and water injection rate are the dominant factors affecting the temperature profile of water injection wells. The results of this paper provide a theoretical foundation for the accurate evaluation of the water injection profile and water injection scheme optimization for the layered water injection wells.
The influence law of temperature profile
Copyright (c) 2023 Zhu Hanbin, Liu Wenqiang, Luo Hongwen, Li Haitao, Ma Hansong, Li Ying, Jiang Beibei, Xiang Yuxing, Zhang Qin https://creativecommons.org/licenses/by-nc/4.0
Determination of the Effect of Moringa oleifera Seed on the Rheological and Filtration Properties of Water Based Mud
A cost-effective and environmentally friendly biodegradable locally sourced alternative will be sought to reduce drilling fluid cost drilling operations. Moringa oleifera seed is a cheap, locally obtainable, and environmentally friendly additive. This study aims to determine the effect and suitability of locally processed Moringa oleifera seed powder (MSP) as an additive to improve the performance of water-based mud. The seeds were collected, prepared, and pulverized to a particle size of 75 microns. Varying concentrations (2.0, 4.0, 6.0, 8.0, and 10.0 g) of the MSP were used to treat a simple mud sample, and their properties were determined at varying temperatures (26°C, 40°C, 50°C, 60°C, 70°C) using American Petroleum Institute (API) standard procedures. Mud samples treated with Carboxymethyl cellulose (CMC) served as control. From the result, it was observed that the pH and the mud weight were not affected by MSP concentration. The mud sample plastic viscosity improved by 18% as MSP concentrations increased. The YP/PV ratios show an enhancement at all Moringa oleifera seed powder concentrations relative to the control mud except for the sharp decrease at 70°C. The test sample processed a greater fluid loss volume and filter cake thickness for all concentrations. The physical examination of the mud filter cake of the additive depicted that they have slippery, smooth, and soft mud cakes. The results elucidated MSP suitability in some traditional chemical materials in the oil and gas industry.
Copyright (c) 2022 Sarah A. Akintola, Ifeoluwa Oloyede, Adeyeye Emmanuel https://creativecommons.org/licenses/by-nc/4.0
Review of the Leak-off Tests with a Focus on Automation and Digitalization
The drilling and research communities are leading the way toward more digitally-controlled operations to ensure that the drilling process takes place as safely and gently as possible with the lowest possible carbon footprint. Today’s cutting-edge operations are run on large high-performance drilling installations where operations are largely run remotely from the driller’s operating station. Digitalization of the drilling process is the goal for performing drilling operations remotely from onshore. Leak-off test (LOT) or extended leak-off test (XLOT) plays a critical role in the petroleum industry. Therefore, recognizing all affecting parameters on LOT/XLOT and Formation integrity test (FIT) performance is vital. Because, in some cases, it is not possible to fully understand what happened during the test, having a deep insight into the LOT procedure is very important. One of the current study's main objectives is to thoroughly explain all stages of these tests and assemble all the significant parameters. Thus, many scientific papers on these tests were deeply reviewed and were classified into four main groups focusing on the application of LOT/XLOT (i) in stress estimation and geomechanical studies, (ii) concerning hydraulic fracturing, (iii) concerning wellbore stability, and (iv) numerical modeling, and then, the corresponding discussions were conducted. It was found that in-situ stress estimation is the most common application of the leak-off test. Moreover, considering the importance of LOT and the desire to digitize operations in the oil and gas industry, it was found that the automatic LOT/XLOT is a fully required approach. The primary purpose of this study, which is hence considered its main contribution, is to prepare a LOT flowchart that would set off the further code development tasks of the field. The fundamental code of the present study was written and checked using a real dataset in a Python environment. The results were satisfying and indicated a successful start, which lays a foundation for future automated LOT/XLOT tests.
Copyright (c) 2022 Elham Bakhshi, Behzad Elahifar, Abbas Shahrabadi, Naser Golsanami , Reza Khajenaeini https://creativecommons.org/licenses/by-nc/4.0
High Viscosity Oil Development Technology
The development of hard-to-recover reserves is now becoming a prerequisite for a successful oil business. Nevertheless, there is still no consensus on what reserves should be classified in this category and what benefits should be received by oil industry workers during their development. At the same time, it is the improvement of the tax system that can spur the development of new technologies for the extraction of “complex” oil and ensure the profitability of its production.
Well, Formation, Filtration, Hydraulic fracturing, Abnormally high pressure.
Copyright (c) 2020 International Journal of Petroleum Technology https://creativecommons.org/licenses/by-nc/4.0
Some Contradictions in the Multi-Layer Hele-Shaw Flow
An important problem concerning the Hele-Shaw displacements is to minimize the Saffman - Taylor instability. To this end, some constant viscosity fluid layers can be introduced in an intermediate region (I.R.) between the displacing fluids. However, we prove that very small (positive) values of the growth rates can be obtained only for a very large (unrealistic) I.R. On the contrary, when the I.R. length is constrained by certain conditions (for instance, geological), then the maximum value of the growth constants can not fall below a certain value, not depending on the number of layers. This maximum value is not so small.
Copyright (c) 2019 Gelu PASA https://creativecommons.org/licenses/by-nc/4.0
Evaluations on Compressibility Factor Calculation Methods for High-Pressure H2S-Containing Natural Gases
The compressibility factor is an essential parameter for natural gas exploitation and processing. The method based on the equation of state (EoS) represents the most popular method for compressibility factor calculations. In this paper, the accuracy of compressibility factor calculations for two traditional cubic-EoSs (Soave-Redlich-Kwong (SRK) EoS, the Peng–Robinson(PR) EoS), the Benedict–Webb–Rubin-Starling (BWRs) EoS, and the Cubic-Plus-Association (CPA) EoS are evaluated based on experimental data for high-pressure H2S-containing natural gases. A total of 234 sets of experimental compressibility factors are applied to validate the above four EoSs, which cover pressures from 70MPa to 131MPa. Results show that for the high-pressure and low H2S content natural gas (35MPa≤P<70MPa, H2S<0.3%), the BWRS EoS yields the best results among the above four EoSs. The average relative deviation (ARD) between the experimental results and the calculated values is 1.07%. For high-pressure and high H2S content natural gas (35MPa≤P<70MPa, H2S≥0.3%), the CPA EoS yields the best results with an ARD of 1.01%. For ultra-high-pressure natural gas (P≥70MPa) without H2S, the BWRS EoS gives the best results with an ARD of 0.32% and the maximum relative deviation is 1.50%.
Copyright (c) 2020 https://creativecommons.org/licenses/by-nc/4.0