RJPGT 2024

Modeling the behavior of natural gas wells during exploitation is often an essential step in studying the evolution of natural gas production. However, the theoretical simulation models of wells placed on depleted deposits usually gave results different from the reality in the field. This was due to problems with the integrity of the productive strata, especially with the degree of sealing of the existing wells. The present work attempts to develop and carry out a rigorous research program of a deposit from the Sarmatian deposits of the Transylvania basin. In the paper it is presented a theoretical framework through which the behavior of the depleted field can be followed by discretizing the field and setting some discrete properties (in the case present the deposit pressure), which by expanding the modeling can serve to identify poorly drained areas, which can be exploited in the future, contributing to the increase of the final recovery factor. This discretization was achieved through the system of grid blocks, for which the average properties (temperature, pressure, permeability, etc.) and connectivity between them were modeled through the flow coefficients. The theoretical model applied to the particular deposit, which can be extended for future production provisions, by setting time intervals e.g. to a month/year instead of days and extending the grid over the entire surface of the field, not only for the central area, where the wells are grouped.

This paper aims to develop a machine learning-based model for oil production rate prediction. The significance of feature dimension reduction is addressed by applying well-established approaches like Principal Component Analysis (PCA) and the proposed physics-driven feature creation technique. The physics-driven features, derived from experience or analytical modeling, introduce physical relevance and improve model quality. The study focuses on oil production prediction using a dataset that includes reservoir permeability, wellbore skin, reservoir pressure, net pay thickness, water cut, and well-liquid production rate. Several machine learning techniques, such as SVM, k-NN, Decision Tree, Random Forest, and linear regression, were constructed using PCA feature selection. The models were tuned and validated using k-fold cross-validation. The same models were then built using physics-driven features, and their performance metrics were compared. The results show significant improvement when applying the proposed physics-driven feature creation, compared to PCA. Over 10-fold cross-validation, PCA improved the R² performance metric by 10% (from 70% to 77%), while physics-driven features increased it by 20% (from 70% to 90% on average). The Random Forest and linear regression models outperformed the others, particularly when built based on physics-driven features. Additionally, models based on physics-driven features exhibited less sensitivity to data splits for learning and testing, proving more reliable with better performance metrics compared to those using original features.

The Libwa field, located offshore the Democratic Republic of Congo (DRC), has significant potential for hydrocarbon exploitation, particularly in the southern part, which remains unexploited. Previous studies have identified various hydrocarbon exploitation opportunities in place, as measured by the volumes of oil in place (STOIIP). However, recent analysis by Perenco DRC highlights the need for additional volumes to meet current production levels in the northern part of the field. The Pinda reservoir, which forms an essential part of the Libwa field, has a porosity of between 15% and 19%. However, it has a very low permeability, averaging less than 2 millidarcies (mD). This low permeability makes it difficult to accurately assess porosity using seismic data, due to minor variations in the geological structure. Ongoing research is aimed at gaining a better understanding of the geological structure of the Libwa field and determining whether additional volumes of hydrocarbons exist in the southern part or in other areas of the field. Understanding the petrophysical characteristics is crucial to optimizing extraction strategies and assessing the economic potential of the reservoir.

The fundamental goal of this work is to investigate and explore the design and construction methods for an intelligent, adaptable and flexible level measurement system, based on IoT (Internet of Things) technology. This automatic data acquisition, transmission and processing system must allow the level of a substance to be measured in a non-intrusive manner. The system also ensures safe operation for personnel servicing the monitored process and allows customization of the presentation of data sets, in a variety of formats, with maximum relevance to the user. The level measurement system proposed in the paper bases its operation on the characteristics of ultrasonic sensors. The intelligent modules of the system process, based on software algorithms, the data from the sensors and communicate them to other microprocessor subsystems for conversions, storage and presentation of the results. This intelligent level measurement system uses two sensor subsystems, with different degrees of complexity, to monitor two reservoirs in a park. These subsystems communicate permanently with a central control unit, the CCU, which collects and processes in real time the data transmitted to it in a WiFi LAN. In order to increase the degree of adaptability of the intelligent system to the measurement needs, it is possible to resort to increasing the number of sensors, placed in various locations, in a park of tanks for the storage of petroleum products.

Indole chemistry is a fascinating and complex field. The foul-smelling indole molecule is the building block for various natural and chemical products. Moreover, some indole derivatives are vital pharmaceutical products or essential intermediates. Indole ring compounds are part of the class of aromatic heterocyclic compounds with one heteroatom, and the indole ring is the most widespread heterocycle. This paper presenting a rheological indole alkaloids from natural products. In this article, we analysed twelve formulations of the H/L (water-oil) or L/H (oil-water) emulsion type, carrying out a comparative study with alcoholic extracts of different concentrations of Vinca alkaloids obtained from the leaf and stem of the Vinca minor L. plant. This plant is collected to the Dobrogea area.

Since the discovery of hydrocarbon deposits in the DR Congo Coastal Basin in general, and in the Kinkasi field in particular, several development wells have been drilled with a view to optimising the economic value of the reserves evaluated. Despite the large number of wells drilled in this onshore area of the Coastal Basin and a multitude of development studies, it should be noted that production is stagnating at around 10,000 barrels per day. This report is a considerable contribution to addressing these major concerns. Certainly, with the advancement of technology through the creation of supercomputers and software, these reprocessings can prove important in that they can bring to light certain information that previously went unnoticed. As well as highlighting the importance of modelling the petrophysical parameters of a reservoir in the development of an oil field, this subject provides assistance to the Production Engineer, insofar as it makes it possible to visualise, from the desktop with some software such as Microsoft Excel 2010 for the calculation of certain data with a view to representing them in the form of tables and graphs, the Geographic Information System (ArcGis 10.3) for representing the study area and drawing up maps of the spatial distribution of porosity-neutron horizons, areas of interest that could be the subject of in-depth studies ((location of new wells).

The synthesis of mechanisms is a complex field of study that includes, in addition to the knowledge necessary for the correct configuration of working mechanisms and those necessary for their analysis, knowledge from the field of nonlinear programming that involves the calculation of the extrema of an objective function, possibly subject to some constraints. In this context, the dimensional synthesis of the mechanisms that involves the establishment of an optimal set of dimensions of the component elements to ensure the necessary precision of the operating parameters remains an always current field through its multiple applications. The paper presents a method of dimensional synthesis of a multi-contour mechanism for which certain values of the stroke of a component piston and the positions of the driving element of the mechanism in which the change of the direction of movement of the piston takes place are imposed. Through the dimensional synthesis of the analyzed mechanism, it is aimed that, in addition to the mentioned conditions, a minimum value of the sum of the lengths of the component elements is obtained. To achieve the optimal synthesis, the Sequential Quadratic Programming (SQP) method included in the Optimization package from the Maple program was used.

The use of Nusselt number correlation in the annular space of a tube-in-tube heat exchanger is a difficult task for researchers, since this correlation is deduced specifically for certain geometrical features. As such, researchers would usually only present limited areas of applicability. This paper presents the algorithm for establishing a new Nusselt number correlation for the annular space of a tube-in-tube heat exchanger with warm water flowing inside in counterflow with cold water in the annular space. The objective of the research was to establish the Nusselt number that allows the calculation of the partial convective heat transfer coefficient on the cold fluid side for a laminar flow regime. This correlation must be of the form: Nu = C·Rem·Prn. This was possible by processing the experimental data by applying the least squares method, as an optimization method. Five sets of experimental data were used for this study. A steel tube in tube heat exchanger was used for this work.

The optimal design of the structures from the component of the robotic mechanisms requires a good knowledge of the various parameters during their operation. Among them are mentioned the working parameters that give the position, speed and acceleration at the operational level of the robots, as well as at the level of the active joints from the component of the robotic mechanisms. This paper presents how a functional simulator of robotic active mechanisms called RobSim was created. The simulator allows the positional and kinematic analysis of active robotic mechanisms, regardless of their configuration and the number of component modules. The positional analysis is performed parametrically. A polynomial variation of the fifth degree was considered for the position parameters at the level of active joints. The simulator allows establishing the position and orientation at the operational level of the analyzed robotic mechanism, as well as the trajectory followed by the robot during operation. Also, the simulator allows establishing the speeds and accelerations both at the operational level of the robotic mechanisms, as well as at the level of the active joints in their component.

It is well known that with the increase in the class of mechanisms, the complexity of their analysis methods also increases accordingly. This is especially the case for mechanisms of class greater than four that contain kinematic groups whose structure includes deformable contours. The usefulness of these mechanisms is also given by their versatility due to the multiple configurations they can have during the kinematic work cycles. The present paper proposes a method for the positional analysis of a complex mechanism of the fourth class. First, the component independent contours of the mechanism are identified using the graph associated with it. Then, the system of equations containing the position parameters of the mechanism is established by projecting the associated vector contours on the axes of a conveniently chosen coordinate system. Solving the system of equations was done numerically, using the fsolve module included in the Maple program. The results obtained from solving the system of equations allowed the development of a functioning simulator of the analyzed mechanism. Finally, the variation curves of the position parameters on a kinematic cycle of operation are presented.

This paper focuses on investigating the reasons behind the low productivity of a confidentially named well, referred to as X102, in sandstone reservoirs. The objective is to enhance the well’s productivity through the implementation of acidizing techniques. The paper makes a significant contribution to the existing literature in this field by expanding the knowledge base and providing an economic analysis of acidizing oil wells. The assessment of the X102 well indicates that it exhibited initial productivity from the natural energy of the oil reservoir, demonstrating an oil flow rate of 307 barrels per day with a skin value of 35. After 3 years of production, the X102 well experienced a decline in productivity due to fines migration. Excel software was employed to process well completions, reservoirs, production, well tests, and economic data. The Horner plot slope was used to calculate the damage, Pipesim software extracted the initial profile of the X102 well, and StimCADE software facilitated the acidizing design. Following the implementation of acidizing, a reduction in fines flow was observed, resulting in a decrease in skin value from 35 to 5. The acid treatment successfully dissolved the fine particles, leading to an increased oil flow rate of 1006 barrels per day. Economically, acidizing proved suitable, generating a profit of $44,062,800 and achieving a return on investment in 89 days over a 2-year production period.

Energy is one of the most important components of a country's economy and development, and fossil fuels ensure 83.4 % of primary energy worldwide. One of the most debated facts nowadays is the influence of the fossil fuels used as a main energy source, on climate change, in fact the CO2 emissions released by these fuels. Therefore, alternative energy sources have been developed to reduce CO2 emissions, respectively the impact of greenhouse gases, on the environment. The present study proposes an objective evaluation of different types and sources of energy and a relevant method for assessment of the environmental impact of representative type of energy sources. Consequently, fossil fuels and alternative sources of energy, especially electricity, are evaluated by Life cycle assessment method. Specific power energy of each category of combustibles, as well as their specific emission of CO2, SOx and NOx, are highlighted and discussed. The study emphasized that the impact of different energy sources has to be attentively analyzed in order not to actually generate more serious environmental consequences.

This study explores the innovative use of nanobubbles in treating river and lake water, focusing on the removal of algae and other organic pollutants. The research combines a comprehensive literature analysis with the development and testing of an autonomous water treatment system based on ozone nanobubbles technology. The methodology includes designing for constructing a catamaran-type vessel equipped with gas separation systems, ozone generation, and nanobubbles production. Experimental results indicate significant efficiency of nanobubbles in algae removal, with over 90% reduction observed, and substantial improvement of water quality parameters such as dissolved oxygen and turbidity. The proposed system can treat approximately 66 m³ of water per hour, demonstrating the technology's potential for large-scale applications in water body management and restoration. This study contributes to the advancement of ecological and efficient water treatment methods, offering a viable alternative to conventional water quality management techniques in aquatic ecosystems. This study has no academic precision pretention in its application part: it evolved from the owner of the lake need of valuing its asset for business production and the author need of fishing passion and interest in solving the situation. Yet its findings are objective and accurate. It had no finance for equipment, works, laboratory analysis, or any other related activity. Data measurements was gathered with common water quality digital testers with 2% precision and did not follow the laboratory determination quality standards.

The study of isobaths characterization in the Cenomanian reservoir of the Muanda field focuses on optimizing petroleum resource management. Using geostatistical techniques and numerical analysis methods, the isobaths of the K, J, I and H layers were mapped. The K layer, the most superficial, is 44 meters thick, while the J and I layers reach 48 meters respectively. This research highlights the spatial variability of isobaths, a key factor in understanding the rapid depletion of the reservoir, which is mainly attributed to the presence of argillites. The lithological heterogeneity, characterized by high clay content, influences reservoir permeability, complicating fluid flow and, consequently, well productivity. The study also subdivided the reservoir into distinct zones according to clay content, revealing that the southwestern zone has a clay content of over 57.42%, while the southeastern zone is less clayey, with a content of less than 41.87%. The results underline the importance of a geostatistical approach to resource management, identifying target areas for potential interventions such as hydraulic fracturing. This study thus contributes to a better understanding of reservoir dynamics and to the formulation of appropriate strategies for the sustainable exploitation of petroleum resources in the Muanda region.

In a wastewater treatment plant (WWTP) there are several different, intricate processes with a dynamic and nonlinear behaviour. The fact that these processes are nonlinear, some of them having a high degree of nonlinearity, as is the wastewater pH neutralization process, comes with a number of problems related to their modelling and control. The identification of any method that can be used to simplify the modelling and control of such a high nonlinear process, it is a desideratum to ensure a quality effluent of the plant, because its water quality is affected by the treated wastewater discharged into it. The Deep Learning (DL) and Machine Learning (ML) techniques offer incredible solutions that can be explored in order to find out the optimal tool that can be used for wastewater pH treatment process modelling. In the present paper, seven DL solutions were implemented and tested in order to identify the most appropriate DL method for modelling this type of process, method that ensures the best result. The analysed DL methods are Feedforward Neural Networks (FNNs), Temporal Convolutional Networks (TCNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM), General Regression Neural Networks (GRNNs), Time Delay Neural Networks (TDNNs) and Deep Belief Networks (DBNs), being implemented using Python 3.9 software and Tensorflow. The analysis made with the mentioned DL methods, was based on knowing the flowrate of the acid reactant (which was maintained constant), the initial alkaline reactant flowrate in the treated solution, the initial pH level, and the desired pH level, with the final goal of predicting the required quantity of alkaline reactant flowrate necessary to obtain a neutral pH.

The Democratic Republic of Congo has significant hydrocarbon reserves in its subsoil. The western Congo sub-basin is less explored in terms of oil potential. This study contributes to enriching the subsoil geological data by highlighting geological structures of major interest for oil exploration. This sedimentary basin is located in the Congo-Central province of the Democratic Republic of Congo and represents the main hope for oil prospects. With regard to the potential of this basin, it is worth mentioning that the presence of source rocks, oil showings, the presence of anticlines and faults identified in this study constitute potential traps for hydrocarbons. To date, the Western Congo sub-basin has been relatively unexplored. The satellite data have been compared with the tectonic field model in order to highlight the structural patterns of this vast basin. This research is crucial for informing future exploration initiatives and unlocking the hydrocarbon potential of the region, thus contributing to the country’s economic development.

The objective of this paper is to realize an angular position control system with a direct current motor. For this purpose, an Arduino microcontroller board is used to control the LS-25GA370 DC motor. The L298N dual H-bridge motor driver is used to modulate the PWM signal and control the travel direction. PID (proportional, integral and derivative) control algorithms are used to generate the PWM output. To implement a PID controller, the tuning parameters of the controller, namely proportional gain, integral gain and derivative gain must be carefully determined. Since the system is nonlinear, the PID controller is the best choice to accomplish this task. The sensor used was a Hall type encoder. To test the system, a LabVIEW interface was used, which communicates with the Arduino Uno platform through the serial port. This technical solution, using PID controller, can be applied for robotic arm position control system and many other industrial applications.

Petrographic and petrophysical characterizations of the pre-salt Chela formation of the Nsiamfumu and Liawenda fields in the onshore Coastal Basin of the D.R. Congo it was performed. These characterizations, as part of the static modelling of the reservoirs, involved reading log measurements, thin-slice observations of rock samples taken from this formation, calculations and interpretation of logs, CPI (Computer Processed Interpretation) and DST (Drill Stem Testing) from well tests. The following observations were obtained: • Wells Lw-1: the formation is characterized by dolomitic limestone and micaceous black shale with a thickness of 34 m having heavy oil indices and an average porosity of 17% and a salinity greater than 300 gr/L; • Well Lw-2: the formation is characterized by islands of sand, coarse sandstone and a few quartz pebbles with a thickness of 10m showing evidence of light oil, gas and an average porosity of 24%; • Shaft Lw-3: the formation is dominated by micaceous shale and dolomite interbeds with a thickness of 14m showing little evidence of hydrocarbons, only salt water and residual oils; • Puits Ns-1: the formation is characterized by beige to grey dolomite, grey shale and white sand with a thickness of 6m showing evidence of light oil and an average porosity of 20%.

The paper presents the essential theoretical elements related to the construction and operation of numerical control machines, starting from a study of the theoretical aspects related to the design of a CNC typewriter. The block diagrams of the machine, the interconnections between the component blocks and the operation of the whole system are highlighted. The paper also describes the implementation of the typewriter. It starts from a detailed diagram of the wiring and connections between the component elements, up to the presentation and commentary of how to create the program for the microcontroller used. Finally, the testing and operation of this CNC is detailed, from the design of the drawing to its actual realization, with the help of the designed and implemented assembly. CNC systems allow the repetitive production of the same parts, exactly the same and without deviations. Unlike a human operator who cannot execute two identical parts, the repeatability achieved by machines with numerical controls is clearly superior, so the reproducibility component is ensured.

In this study, activated carbon was synthesised from corn cobs through a two-step process involving carbonization at 600°C within an airtight furnace and chemical activation utilising phosphoric acid. The resultant activated carbon derived from corn cobs demonstrated significant adsorption capabilities, with a substantial BET surface area of 860.500 m2/g and exhibiting favourable adsorption-desorption kinetics. These attributes position it as an exceptional precursor material to produce nanoporous carbon materials suitable for the storage of natural gas. Two distinct sample sizes, measuring 841 microns and 400 microns, were meticulously chosen for examination in this investigation. The findings derived from the adsorption of natural gas, quantified in terms of volume-based metrics, revealed a direct and positive correlation between increasing pressures and pore sizes, resulting in higher adsorption capacities. The experimental conditions encompassed a temperature range of 27°C to 40°C, and storage pressures spanning from as low as 3.5 psi to as high as 28 psi. The recorded adsorption capacities were observed to fall within the range of 1.3424 mmol/g to 4.3073 mmol/g. The adsorption capacity of natural gas exhibited sensitivity to variations in both pressure and temperature, with the highest recorded storage capacity of 4.3073 mmol/g occurring at a temperature of 27°C and a pressure of 23 psi. The findings of this study highlight the significant potential of utilising corncob-derived activated carbon as an adsorbent for natural gas storage. Recommendations for further optimization and integration of this technology into existing gas storage systems are discussed. This research advances the prospect of utilising agricultural waste materials for eco-friendly and cost-effective energy storage, contributing to the transition towards a greener energy landscape.

This article presents the world energy situation, the importance of energy transition, and it further designates hydrogen as a potential replacement for natural gas. Moreover, the paper specifies that the energy transition will be carried out gradually, sustained by conventional resources. Hydrogen can be mixed with natural gasses in current networks, but additional risks must be considered. These risks prove to be minimal in the distribution sector if the hydrogen fraction is kept within acceptable limits, and if optimal operation and safety measures are enforced. The behavior of the hydrogen-natural gas mixture, also called HENG , is studied based on distinguishing the physical and chemical properties of hydrogen and natural gas. In order to analyze the true behavior of the mixture in a distribution network, a numerical simulation was undertaken, whose analysis shows that there is a tight connection between the concentration of hydrogen in the system, consumption, and linepack , and the operational limits of the network must be established based on these data. Knowing the behavior, strategies and regulations can be drafted in order to safely exploit natural gas-hydrogen distribution networks. However, every distribution network has its own particularities, which is why additional studies both at theoretical as well as practical level, performed on real distribution networks, are needed.

In this paper, we analyze stimulation by hydraulic fracturing with the aim of establishing a relationship between fracture geometry and hydrocarbon drainage. Believes fracturing geometry is an effective means of predicting the productive capacity of a hydrocarbon reservoir and the productivity of a well stimulated by hydraulic fracturing is closely linked to the fracturing geometry. Demonstrate the impact of fracturing geometry on the productivity of a hydrocarbon reservoir. Characterize the different parameters of the fracturing geometry while determining the link between these parameters; highlight the difference between the productivity of the reservoir before and after fracturing and monitor the evolution of productivity in relation to this geometry.

Located on the Congolese (DRC) side of the Lemba depression, our study area is the part that was returned by "ex-Zaïrep", just east of the concession currently operated by Perenco rep. Open to oil and mining exploration, we brought back phosphate rock samples from the field, which were analyzed by the Commissariat Général à l'Energie Atomique (CGEA) using the ED- XRF Xepos III spectrometer. These analyses were used to characterize the geochemistry of the Kanzi and Mvuangu phosphates. The results of the Chemical Analyses (Oxides) and Chemical Elements are as follows: (1) Major oxides (%:) Al2O3 (21,21 – 17,24); SiO2 (14,85 – 30,40); P2O5 (19,48 -13,34 %) finally Fe2O3 (8,544 – 10,74 %), and other oxides with concentrations in mg/kg (MnO, ZnO, Rb2O, SrO, ZrO2, Nb2O5, Sb2O5, Ta2O5); (2) Major Chemical Elements (%): Aluminum (11.22- 9.124); Silicon (6.939-14.21); Phosphate (8.5-5.823 %) and several trace metallic elements that will be exposed in another soil and sediment matrix to assess the state of the environment prior to mining and petroleum activities. The origin of these metallic elements, including heavy metals, rare earths and radionuclides, is phosphate. Phosphate rocks, such as apatite, may contain heavy metals, rare earths and radionuclides in their mineral structure. The gravity anomaly map of the Lemba sub-basin, where the phosphate sites are located, clearly shows that the phosphates of Kanzi in the south and Mvuangu in the north are not located in the central deposits, but in the upper parts of the sub-basin. These areas are potentially anticlines, which are geological structures capable of containing hydrocarbons. This study is a contribution to our knowledge of the phosphate resource in Kanzi and Mvuangu, and contribute to understanding the geological structures capable of containing hydrocarbons. It is also an important contribution in the field of geochemistry and gravimetry.

This study evaluates the flexibility of a fiber-reinforced polymer (FRP) pipeline system, focusing on its ability to withstand various loads and stresses while maintaining structural integrity. Key aspects include analyzing FRP material properties, assessing pipe geometry, evaluating external and internal loads, and performing a flexibility analysis using CAESAR II software. The initial findings indicated that the stress levels exceeded permissible limits, necessitating adjustments in support positions and types. These adjustments successfully reduced stress levels to acceptable thresholds, ensuring reliable system performance. This study highlights the importance of meticulous design and continuous optimization to guarantee the safety and durability of FRP pipeline installations.

Mibale oil field considered a mature oil field, located offshore in the coastal basin of the DR Congo and discovered in 1973, has seen an evolution in its production since it began operation in 1976, starting from an initial rate of 10,000 BOPD with 3 producing wells to the current production of 5,905 BOPD from 14 wells. In 2021, the field had 393 MMstb of oil reserves in the reservoir. A thorough study of the production system was carried out, focusing on the five best producing wells, including well MIB-02. Despite traversing layers of the reservoir with high oil potential, the well is underperforming with a respective flow rate of 351 BOPD and a 60% WOR using an electric submersible pump. Following this low production, various studies were conducted, including the study on converting the activation method by proceeding with nodal analysis technique. The use of nodal analysis proved crucial in identifying the shortcomings of the production system, combining field history with analysis of production, well test, pressure, and completion data. The IPM Prosper software enabled a thorough analysis, revealing that MIB-02 had a production potential greater than its current performance. This performance was revealed after evaluation and interpretation of IPR, VLP curves and sensitivities of variables such as water cut and pressure at the first node. After interpreting these curves, the MIB-02 well had the production capacity of 4100.62 BOPD and 12463.9 BWPD. By converting the submersible electric pump activation mode to gas-lift and exploring various scenarios, production was improved with an oil flow rate of 1244.9 BOPD, water flow of 2539 BWPD, to a gas flow of 0.37346 MMscf/day and 67.1% water cut. Despite these improvements, excessive water production remains a challenge while also highlighting the complexity of the production system and the limitations of the analysis technique. Therefore, further studies can be envisaged by modeling and simulating the reservoir, considering well interventions and quantifying the remaining reserves today. This more comprehensive approach will enable a clearer vision and help decide the best optimization strategies for the Mibale field production system.