La desinfección de aguas residuales domésticas es crucial para proteger la salud pública y el medio ambiente, ya que elimina patógenos y contaminantes que representan riesgos significativos. Implementar metodologías eficientes y sostenibles en este proceso es esencial para garantizar la seguridad del agua y su reutilización en diversos contextos. La radiación ultravioleta (UV) es un proceso de desinfección física ampliamente reconocido como una alternativa ecológica a los tratamientos químicos, ya que no altera las propiedades fisicoquímicas de los efluentes tratados ni genera subproductos nocivos. La luz UV inactiva los microorganismos dañando su material genético e impidiendo su reproducción. Este estudio evalúa la eficacia de un sistema de desinfección UV diseñado para el tratamiento de aguas residuales domésticas, utilizando métodos microbiológicos (recuento total de bacterias aerobias - RTBA) y moleculares (PCR cuantitativa en tiempo real - qPCR) como metodologías de recuento. Los resultados mostraron que la qPCR, dirigida al gen rpoB, detectó una mayor recuperación microbiana (2 log) en comparación con el RTAB, lo que pone de manifiesto su mayor sensibilidad. El estudio también evaluó el impacto de los sólidos en suspensión comparando las aguas residuales no filtradas (ARNF) y las aguas residuales filtradas (ARF) bajo dosis bajas (471 mW∙s/cm²), medias (941 mW·s/cm²) y altas (3722 mW·s/cm²) de UV a 254 nm. Las eficiencias de desinfección alcanzaron casi el 99% en todos los tratamientos, lo que indica que la concentración de sólidos (< 50mg/L) no afecta significativamente al rendimiento de la UV. La inactivación de E. coli, medida por el número más probable (NMP), alcanzó eficacias ≥99,9% en todos los casos. Los valores logarítmicos de inactivación oscilaron entre 2 y 4 para RTAB, NMP y qPCR, lo que confirma que las dosis UV más altas mejoran la inactivación microbiana. El estudio subraya las ventajas de la desinfección UV, incluida su eficacia, diseño compacto y rentabilidad en comparación con métodos químicos.
As conventional oil and gas resources approach the later stages of their development lifecycle, it is becoming increasingly clear that existing reserves are insufficient to sustain society's growing needs. Unconventional oil and gas reservoirs, however, boast substantial energy reserves. Should these resources be harnessed and developed efficiently, they have the potential to significantly augment the world's energy supply. Nevertheless, most unconventional oil and gas reservoirs are located within dense and highly heterogeneous strata, posing significant challenges for efficient exploitation with standard drilling equipment. Consequently, to enhance development of these reservoirs, research has been conducted using the liquid-pulsed discharge plasma technology to fracture rock formations. A key factor affecting this technology is the electrode part of the discharge structure. This paper focuses on the effects of three electrode parameters (electrode spacing, electrode shape, and electrode material) on the rock breaking technology by plasma liquid pulsed discharge . It is evidenced that changing the electrode parameters can effectively improve discharge characteristics and energy utilization, while reducing the technical cost, which has great development potential in unconventional reservoir reconstruction.
The geothermal gradient map of the Llanos Orientales Basin (Alfaro et al., 2009) shows a positive thermal anomaly in the south that has generated interest in harnessing the region's geothermal potential. Using 1D and 3D thermal models, three hydrocarbon reservoirs (Gachetá, Mirador, and Carbonera C7 Formations) were analyzed. The analysis identified four potential exploitation zones based on minimum temperature requirements for ORC coproduction plants: low (below 80°C), medium (above 80°C in one reservoir), high (two reservoirs above 80°C), and very high (all three reservoirs above 80°C, reaching 127°C in Gachetá). This reveals thermal gradients up to 79.8°C/km near southeastern basement paleo-highs. In the very high potential zone, the Apiay-4P well showed potential power generation of up to 700 kWe with a 10,000 B/D flow rate. A particularly promising area with high temperatures and multiple reservoir convergence was identified in the northwest. These findings provide valuable insights for future geothermal development projects in the Llanos Orientales region.
There are numerous industrial processes and energy generators that emit CO2 into the atmosphere, which are still in an incipient state of technological transition for their reduction. A global expanding alternative involves storing CO2 for long periods (> 1,000 years), in geological environments such as saline aquifers. Thus, studies on a semi-regional scale are fundamental to reduce the uncertainty regarding location of sites with the best storage capacities and high Chance of Successful. The use of Forward Stratigraphic Modeling (FSM) workflows to populate static models with properties is a time-versatile tool to evaluate the prospectivity of subsurface resources over large areas, as required for CO2 storage. These workflows, coupled to Common Risk Segment Analysis, have been applied in a basin with a long history of O&G exploration and production, the Middle Magdalena Valley basin in Colombia, proving their effectiveness in the selection of areas along prospective corridors to store CO2, in Mesozoic and Cenozoic formations. Preliminary estimates suggest that the Meso-Cenozoic formations in this part of the basin may reach a Theoretical CO2 Storage Capacity close to 830 GTon CO2 and an Effective CO2 Storage Capacity of 293 GTon CO2.
The Water Alternating Gas (WAG) process is a cyclic method of injecting alternating cycles of gas followed by water, repeating this process over multiple cycles. However, decision-making during the WAG process often involves critical choices that, at times, fall short of providing accurate and effective results. In recent years, the advent of Artificial Neural Networks (ANNs) has opened up promising opportunities to revamp Enhanced Oil Recovery (EOR) processes. This comprehensive review examines ANN-based methodologies for predicting performance of WAG injection projects. It starts with an overview of the WAG injection process, outlining its relevance in enhanced oil recovery. Subsequently, the study explores the architecture and complexity of ANNs, providing foundational insights into their functionality. The application of ANNs in developing predictive models for WAG injection is then analyzed, emphasizing their potential to enhance accuracy in forecasting WAG performance. Key aspects discussed include ANN-based WAG injection across various gas and rock types, the functions used in ANN WAG modeling, and the algorithms employed in ANN-based WAG simulations. Furthermore, the review highlights the challenges associated to implementing ANN-based predictive models in WAG projects. By synthesizing existing research, this study intends to provide valuable insights for petroleum engineers, particularly in understanding and applying ANN models for optimizing WAG injection strategies.
Available crude oil resources correspond mainly to heavy and extra-heavy crudes. In their production, these crudes can be transported as water-in-crude-oil emulsions, subjected to various temperature and pressure conditions, with droplets that may contain diluted gases. Hence, analyzing the influence of temperature, pressure, water content, and gas content (GOR) on the rheology and droplet size of water-in-crude-oil emulsions of a Colombian extra-heavy crude allows to estimate power consumption and potential net flows. Therefore, a composite-face-centered 24 factorial design of experiments was applied, using a capillary viscometer to measure shear stress, viscosity and pressure drop responses, as well as a light scattering laser analyzer to measure droplet size distribution. According to the results, the emulsions were stable at well operating levels specified for the variables temperature [150, 190] °F, pressure [1800, 3800] psi, brine content (W) [2, 30] %w and (GOR) [0, 120] ft3/bbl. Likewise, droplet size increase with GOR and/or W. The viscosity of the emulsions showed an increase with pressure and brine content. On the contrary, the viscosity of the emulsions reported a decrease with temperature, the GOR of the emulsions, and the flow rate of the test. Finally, the rheological behavior of the emulsions analyzed in this paper was determined to be pseudoplastic.
Recent research highlights a significant challenge in maintaining power quality in grid-connected wind energy systems. This challenge is further complicated by issues such as the lack of reactive power support and the high installation costs associated with power quality upkeep. To address these challenges, this study proposes an innovative solution in the form of a Genetic Improvised Fuzzy Logic PID controller based DSTATCOM. This controller not only effectively reduces overshooting but also demonstrates reduced voltage variation during dynamic conditions when compared to conventional Fuzzy Logic Control (FLC) methods. Furthermore, the Genetic Algorithm optimizes switching pulses for the Voltage Source Converter (VSC) in the Distribution Static Synchronous Compensator (DSTATCOM). The proposed model demonstrates its effectiveness by achieving a 2.06% reduction in Total Harmoni Distortion (THD). Rigorous simulations conducted in MATLAB/Simulink, and the results obtained from the proposed model highlight its potential to significantly enhance power quality in grid-connected wind energy systems.
The increasing global energy demand, depletion of petroleum reserves, volatile petroleum prices, and growing environmental concerns have accelerated the search for sustainable and clean energy sources. Biodiesel (methyl ester) was produced from scum oil (MESO) and waste vegetable oil (MEWVO) through transesterification using sodium hydroxide and methanol as catalysts and reactants. The composition of the methyl esters in MESO and MEWVO was analyzed using Gas Chromatography-Mass Spectrometry (GC-MS). Various methyl ester blends were prepared by adding pure diesel to MESO and MEWVO, and the best blend was selected for use in compression ignition (CI) engines. The performance, emission, and combustion characteristics of MESO-B20 and MEWVO-B20 blends were studied. Results showed that retarded injection timing (19° before TDC) significantly reduced ignition delay by 15% and improved brake thermal efficiency (BTE) by 6.4% compared to standard injection timing. The increase in injection pressure to 220 bar enhanced fuel atomization, leading to a 10% reduction in brake specific fuel consumption (BSFC) plus 5% reduction in exhaust gas temperature (EGT). These findings demonstrate that MESO-B20 and MEWVO-B20, with optimized injection parameters, are a viable alternative to conventional diesel in CI engines, showing improved combustion efficiency and emission reductions, particularly in CO and unburned hydrocarbons (HC), although there was increase in NOx emissions.. Further research is recommended to address NOx emissions and optimize biodiesel formulations for long-term engine performance.
This paper presents a novel V-nets-Based Alarm Management (VBAM) methodology designed to enhance supervision and safety in Green Hydrogen Plants (GHPs). The proposed approach integrates visual modeling and temporal pattern analysis to accurately detect and manage alarms, seeking to reduce false positives and optimize response times. The methodology starts with a Preliminary Hazard and Operability (HAZOP) analysis to identify potential hazards and critical operational conditions, which are the foundation for constructing V-nets that map the temporal relationships between discrete events. By systematically capturing event sequences and their interdependencies, the VBAM approach allows for early fault detection and a proactive alarm management system fit for varying operational scenarios. A case study of the EL30N Green Hydrogen Plant proves the efficacy of the VBAM methodology in reducing downtime, improving system safety, and enhancing overall operational efficiency. This work provides a comprehensive framework for addressing discrete event challenges in alarm management, paving the way for safer and more resilient practices in green hydrogen production. Future directions will include expanding the application of VBAM to other operational phases and incorporating real-time analytics for further performance optimization.
Mild oxidation reactions were induced over four different asphaltenes. Oxidation products were characterized via infrared spectroscopy to propose structural descriptors, taking advantage of the high sensitivity for detecting carbon oxygen vibrations in the infrared spectrum. Although no quantification over functional groups was performed, a good comparison between feedstock and products was achieved, after de-convoluting the FTIR spectra. It was confirmed that methyl groups are useful moieties on tracing the position of alkyl topologies over the n-heptane insoluble structures throughout oxidation reactions, as oxidation is more suitable on α-H of side alkyl chains. Considering this, it was inferred that the esters were the main functional groups formed under such oxidation conditions. The formation of lactones over aromatic nuclei was monitored through the slope of a parity plot with band intensity ranging between 1730cm-1 and 1230cm-1. TGA-MS and 1H-NMR analysis of raw n-heptane insolubles rendered valuable complementary information to confirm the structural attributes of the samples obtained by FTIR. The results from this research prove that handling oxidation selectivity over such complex hydrocarbon mixtures could have broader relevance for structural characterization purposes.
The environmental impact of fossil fuels and their limited availability increase the need for research into alternative energy sources. In this research, pyrolysis oil (PO) was obtained from waste sour cherry kernels. PO cannot be used directly as fuel in diesel engines because of its negative fuel properties, such as low energy density, high viscosity, high water content, and low cetane number. Therefore, PO was blended with diesel at various weight proportions (wt%) using n-butanol (NB) as co-solvent, and 2-ethylhexyl nitrate (2-EHN) as cetane improver. Blended fuels containing 40 wt% diesel i.e., D2 (Diesel 40% / PO 0% / NB 55% / 2-EHN %5), D3 (Diesel 40 / PO 5% / NB 50% / 2-EHN 5%) and D4 (Diesel 40% / PO 15% / NB 40% / 2-EHN 5%) were identified as optimal blend compositions regarding the physicochemical characteristics of fuel. These fuels were tested for engine performance and emission characteristics at engine speeds of 1500, 1800, 2400, 3000 and 3600 rpm under full engine load (10 Nm) in a single-cylinder diesel engine. All data (i.e. cylinder pressure, engine torque and performance changes, heat release rate, and emission characteristics) were recorded using a Kistler KiBox data acquisition system. The engine tests showed a decrease in NOx, HC and soot emissions when blended fuels (D2, D3 and D4) were compared to D1 (Diesel 100% / PO0% / NB 0% / 2-EHN 0%). The lower NOx emissions in the blended fuels are explained by the PO's water content. Water raises the specific heat capacity of the fuel-air mixture while reducing the internal cylindertemperature. Additionally, the high latent heat of evaporation of n-butanol may contribute to reduce NOx emissions. In addition, the decrease in HC emissions may be caused by the increase in the oxygen ratio of blended fuels, while the decrease in soot emissions may be caused by the low C/H ratio and high oxygen content of blended fuels. To conclude, blends of PO, diesel n-butanol, and 2-EHN can be used as biofuels in diesel engine applications.
Pursuant to the goals of sustainable development, and in line with current energy needs, it is increasingly necessary to create more energy-efficient processes, and reduce their carbon footprint. New energy-efficient technologies for heavy oil recovery must be developed, such as hybrid technologies, where some additives are used for steam injection processes. One of the hybrid technologies with good potential for energy-efficient heavy oil recovery is cyclic steam injection with solvents enhanced with nanocatalysts (HYB-SEN), which could also generate oil upgrading by pseudo-aquathermolysis reactions. According to the above, this research focused on evaluating the impact on the reduction of greenhouse gases of the hybrid steam technology with naphtha-based nanofluids concerning the conventional cyclic steam injection (CSS). For this purpose, a simulation model for conventional cyclic steam stimulation (CSS) called the CSS baseline was created, including the pseudo-aquathermolysis reaction and the reaction kinetics based on experimental tests such as thermogravimetric analysis (TGA), analysis of gases and fluids after coreflooding tests in the presence and absence of nanocatalysts, physicochemical characterization tests of crude oil, naphtha, among others, as well as fluid properties software. On the other hand, the reduction in the production of greenhouse gases by hybrid technology concerning the CSS baseline was calculated. The impact of the hybrid technology on the injection scenarios was determined through the proposed environmental indicators like energy efficiency, reduction of Basic Sediment and Water (BSW), and reduction of carbon footprint reflected in lower carbon-intensity, among others, by numerical simulation. The results of the hybrid technology with nanocatalysts simulation showed an increase in oil recovery of an additional 3756.5 Bbl of crude oil compared to the conventional technique and a reduction greater than 18% for the CO2 production compared to conventional cyclical steam injection. Further, the environmental impact analysis of the scenario concerning the baseline was evaluated, finding a positive impact on energy efficiency improvement, reduction of BSW, and reduction of carbon footprint reflected in lower carbon-intensity, among others. Additionally, hybrid technology results in an additional benefit with the use of raw materials such as naphtha in crude oil transportation, used at the field, which implies a reduction in their subsequent use due to the improvement of crude oil properties. The foregoing indicates that hybrid steam technology with naphtha-based nanomaterials not only generates positive impacts on oil recovery compared to the conventional technique, but also has a positive effect by enhancing energy efficiency and reducing carbon footprint.
The object of this paper was to analyze the non-volatile watersoluble fraction or dissolved organic matter (DOM) from production water associated with Cyclic Steam Stimulation (CSS) with preformed foams through high and ultra-high mass spectrometry. Using ESI FT-ICR MS, six naphthenic acids were identified and selected as new potential natural tracking agents. Subsequently, the DOM fractions were analyzed via ESI MSMS, through which semi-quantitative concentrations of these compounds were established for the samples. The results show that the DOM concentration monitored through ESI-MSMS allows for the correlation of changes during the cycles of steam+foam injection with the increases/decreases of oil production in three wells from the Cocorná Field, Colombia. This information becomes relevant for quality control of cyclic steam injection and, hence, for developing heavy oil mature fields. Thus, monitoring water-soluble petroleum compounds is presented as an affordable strategy and a promising tool to track changes in reservoirs subjected to water injection.
Currently, it is necessary to reduce CO2 emissions into the atmosphere. The oil industry in Colombia can contribute through CO2 injection processes in depleted fields. To achieve this, it is essential to have knowledge of the physicochemical interactions of CO2 with reservoir fluids. To integrate CO2, water and hydrocarbon phases, advanced models are required that capture the phenomenology of thermodynamic equilibrium. The CPA (Cubic-Plus-Association) equation of state is an equation that adds an associative term to model the interaction of water with the hydrocarbon and CO2 phase. In this work, the CO2 injection process is thermodynamically modeled in a depleted Colombian reservoir case study. There is a compositional fluid with a gradient of PVT properties in a vertical relief of 10,000 ft at a depletion condition of 2,000 psi @ 15,374 ft and an oil-water contact (OWC) at 17,000 ft. CO2 injections between 10 and 80 mol% were carried out, and through the CPA equation of state, the swelling conditions of the crude oil, the solubility of CO2 in the formation water and the pressurization of the system were evaluated. The associative parameters of the equation were taken from literature and estimated through molecular dynamics simulations of water-CO2-Hydrocarbon interactions. This thermodynamic modeling with an advanced equation of state and use of molecular dynamics simulations allowed us to simulate different CO2 injection scenarios in a compositional fluid. The development of these types of studies is key to carrying out successful CO2 injection processes focused on enhanced recovery (EOR) and CO2 storage in the porous medium in a Colombian-depleted compositional reservoir.
A fundamental process in the clean-fuels chain corresponds to the steam methane reforming (SMR), which generates the hydrogen needed for production of low-sulphur fuels. The identification of opportunities to increase hydrogen production involves the analysis of variables that affects heat supply in the SMR furnace (preheating and reaction section). This document presents the main results of an analysis of heat supply in an industrial SMR furnace based on both, data analysis and simulation with Aspen HYSYS. To such end, eight-year-process-operation data were collected and analysed with kmeans multivariate algorithm. The simulation was validated with pertinent design data and compared to process data. Next, the simulation was applied to explore the operating surface of the furnace to identify conditions with major hydrogen production. According to the results, the statistical analysis by kmeans divided the data into two operational modes that were representative for the furnace; one of them showed the major H2 production. Similarly, the simulation results suggested that the increase in H2 generation was stabilized with the highest values of both heat and natural gas, tending towards a steady state value.
CO2 flooding for oil recovery is a dynamic process that requires further investigation of oil-gas interface change characteristics, interfacial mass transfer processes, and oil-gas composition variation during both immiscible and miscible displacement. Understanding these factors is crucial for better comprehending their impact on CO2-enhanced oil recovery (EOR). This research used a jointly developed CO2 miscible visual flooding experimental apparatus to study the horizontal dynamic characteristics of CO2 and crude oil under different pressures and flow rates in visual slim tube. At 10 MPa, the stratification results of CO2 and crude oil indicate that the experiment is immiscible flooding. The contact angle (7.9°) between the two phases of CO2 and crude oil at the flow rate of 15 cm/min is larger than that (5.2°) at 1.5 cm/min, and the grey scale of CO2 increases at 100 cm/min. The quantity, individual content, and shape of the light and medium hydrocarbon components condensed on the inner wall of the tube vary with different flow rates. At 15 MPa, the appearance of the CO2 and crude oil transition interval proves that the experiment is miscible flooding. At different flow rates, the inclination angle and distribution of black stripes vary. The whole transition interval is divided into 6 intervals, and the transition interval lengthens with increasing fluid velocity. The experiments visually demonstrate the occurrence of the miscible phase, and identify experimental pressure and fluid flow rate as key factors influencing the miscibility of CO2 and crude oil.
The precipitation and destabilization of asphaltenes in mature oil fields pose significant challenges to the oil industry, leading to damage on the producing formation and the potential blockage of production facilities. Conventional removal and inhibition methods have proven to be costly and temporary, with no guarantee of preventing new asphaltene deposits. In this study, our focus is on the design and evaluation of a stable nanofluid composed of Fe3O4 (Magnetite) and GO (Graphene Oxide) nanocomposites as an effective asphaltene stabilization agent in Colombian crude oil. By functionalizing magnetite nanoparticles with graphene oxide, we achieved a significant improvement in their stability. Various surfactants were tested to enhance the nanoparticle stability, followed by viscosity modification using commercial additives to attain the desired stability. The stability of the nanofluid was thoroughly evaluated through Oliensis, SARA, flocculation, rheology, and physicochemical analyses. Additionally, fluid-fluid and fluid-rock interaction tests were conducted under reservoir conditions. The results demonstrated an impressive 48% reduction in asphaltene-induced damage and a positive change in wettability, leading to a remarkable 38% increase in the recovery factor observed in core analyses. This study provides a promising approach to mitigate asphaltene-related challenges in mature oil fields, ensuring formation integrity and enhancing production efficiency.
The management of produced water is a significant environmental challenge, particularly considering the goal to achieve 'Water Neutrality' by 2045, which requires the entire elimination of discharges into water bodies. In Colombia, discharged water currently accounts for over 30% of total water production, approximately 80 million m3, which adversely affect various ecosystems. Moreover, the economic implications are substantial, as each barrel of produced water represents a significant quantity of unextracted oil, impacting the fields' profitability. To address this issue, various stimulation methods have been used to mitigate water production. This study is intended to assess the efficacy of these techniques in reducing water production and improving environmental management. The Universidad Industrial de Santander, through its specialized services to the hydrocarbon industry, has conducted numerous assessments of relative permeability modifier (RPM) treatments across diverse scenarios and conditions. These evaluations have revealed high reduction in water permeabilities of up to 90%, effectively curbing water contributions from producer wells. This approach not only yields tangible benefits for companies by averting treatment costs, but also translates into environmental benefits through reduced water discharge. In this study, we leverage this expertise to assess the potential impact of RPM treatments on water production. By analyzing changes in relative permeability curves via reservoir simulation, we aim to estimate the prospective decrease in water production and, consequently, the reduction in oil industry discharges in Colombia prior to a widespread implementation of this technique.
The global automotive industry is currently undergoing a transformation driven by a number of factors, including environmental concerns, sustainability targets, and the advent of innovative technologies. The adoption of electric vehicles represents a pivotal aspect of this transformation, offering individual and corporate users in the car rental sector a significant alternative to traditional internal combustion engine vehicles. The economic and operational advantages of electric vehicles, coupled with the opportunity for car rental companies to fulfil their environmental responsibilities, are accelerating the transformation of the automotive industry. This study presents a case study on the utilization of electric vehicles for long-term car leasing companies for the purpose of providing corporate internal services. The aim is to provide a comprehensive evaluation of the issue from multiple perspectives. The objective of this paper is to provide a comprehensive overview of the concept of electric vehicle leasing, encompassing a range of considerations pertinent to decision-making. These include environmental sustainability, economic advantages, user experience, and operational efficiency.
The future of production in the Apiay field lies in the T2 formation, although it poses significant challenges, such as high fluid encrustation and heavy crude oil production. These issues have led to strong emulsion problems and operational issues with many wells' electro-submersible pumping systems (ESPs). In response, companies have decided that all wells with ESP equipment in the T2 formation should undergo downhole treatment using capillary scale inhibitors and fluidity improvers. However, due to operational and design constraints, some wells only have one capillary, making it difficult to prioritize and decide on a single treatment. Ecopetrol and ChampionX have collaborated to develop a new flow improver that can be applied with the scale inhibitor in the same capillary without causing incompatibility or affecting product performance. This innovative solution was implemented in five wells, using 600 ppm for the flow improver, and 25 ppm for the scale inhibitor, resulting in a significant increase in crude oil production by up to 79%, USD 55.000 in cost savings in capillary system installation, 29% energy savings, and reduced emissions. This successful application is innovative and unique in Colombia, and it sets an example for other fields facing similar challenges in the couuntry, offering a promising approach to leverage heavy crude oil production and transform the future of these fields.
