Recovery Operations Research Articles

A chip thermal management method realizing integrated applications of cooling, power generation and heat flow measurement based on thermoelectric effect

Thermoelectric cooling, power generation and heat flow measurement are widely used in frontier domains while each of them is still in an isolated state. They are now widely used in fields such as electronic cooling, wearable device, sensors and so on. This paper proposes a method of thermoelectric effect combined with pulse width modulation (PWM) to achieve integrating thermoelectric applications. In a PWM cycle, the integration of thermoelectric applications makes it possible to realize three different operations of temperature control, energy recovery and heat flow measurement through a single thermoelectric module. The experimental results indicate that increasing the input voltage of the thermoelectric module extends the duration for power generation and heat flow measurement, while also enhancing the energy recovery rate. When the target temperature is higher than the ambient temperature, although the temperature control accuracy slightly decreases with the increase of the target temperature, the average temperature fluctuation range of the whole experimental group is −0.09∼+0.1℃ and energy recovery rate increases by 79.9 %. When the target temperature is lower than the ambient temperature, the system can still achieve efficient energy recovery. Applying the method to the computer central processing unit(CPU), the experimental results present that the heat dissipation of CPU can be monitored by measuring heat flow. Compared with the CPU + FPU working, the total power generation is increased by 0.285 W and energy recovery rate is increased by 78.3 % when the CPU is idle.

Exploring NRB Biofilm Adhesion and Biocorrosion in Oil/Water Recovery Operations Within Pipelines.

Microbially influenced corrosion represents a critical challenge to the integrity and durability of carbon steel infrastructure, particularly in environments conducive to biofilm formation by nitrate-reducing bacteria (NRB). This study investigated the impact of NRB biofilms on biocorrosion processes within oil/water recovery operations in Algerian pipelines. A comprehensive suite of experimental and analytical techniques, including microbial analysis, gravimetric methods, and surface characterization, were employed to elucidate the mechanisms of microbially influenced corrosion (MIC). Weight loss measurements revealed that carbon steel samples exposed to injection water exhibited a corrosion rate of 0.0125 mm/year, significantly higher than the 0.0042 mm/year observed in crude oil environments. The microbial analysis demonstrated that injection water harbored an average of (4.4 ± 0.56) × 106 cells/cm2 for sessile cells and (3.1 ± 0.25) × 105 CFU/mL for planktonic cells, in stark contrast to crude oil, which contained only (2.4 ± 0.34) × 103 cells/cm2 for sessile cells and (4.5 ± 0.12) × 102 CFU/mL for planktonic cells, thereby highlighting the predominant role of injection water in facilitating biofilm formation. Contact angle measurements of injection water on carbon showed 45° ± 2°, compared to 85° ± 4° for crude oil, suggesting an increased hydrophilicity associated with enhanced biofilm adhesion. Scanning electron microscopy further confirmed the presence of thick biofilm clusters and corrosion pits on carbon steel exposed to injection water, while minimal biofilm and corrosion were observed in the crude oil samples.

The Profitable Art of Managerial Responses to Online Reviews: A Justice-Based Investigation of Service Recovery and Firm-Level Operating Performance

ABSTRACT Building on the justice theory, managerial responses (MRs) to negative online reviews are investigated for their service recovery efficacy. MRs (>2,000) for 106 hotels were analyzed for interactional, procedural, and distributive justice and matched with their property-level room revenue, total revenue, and gross operating profit. Service recovery’s importance was empirically demonstrated via a negative association between negative reviews and performance outcomes and a positive association between MRs and performance outcomes. Justice-based MRs revealed differential impacts on performance outcomes: those with interactional justice were most effective in improving profitability. Findings further highlighted product positioning as a moderator. On one hand, interactional justice worked for lower-positioned hotels by being positively associated with total revenue. On the other hand, distributive justice backfired by being negatively associated with total revenue, suggesting that compensation in service recovery does not necessarily add value.

Self-Assembly-Activated Engineered Magnetic Biohybrids Loaded with Phosphotriesterase for Sustainable Decontamination and Detection of Organophosphorus Pesticides.

Phosphotriesterase (PTE) biodegradation of organophosphorus pesticides (OPs) is an efficient and environmentally friendly method. However, the instability and nonreusability of free PTE become the key factors restricting its practical application. In this study, a novel cross-linked magnetic hybrid nanoflower (CLMNF) was prepared. Molecular dynamics (MD) simulations were performed to further investigate the enhanced catalytic efficiency of the enzymes. The recovery rate of enzyme activity was 298% due to the large specific surface area and metal ion activation effect. More importantly, the immobilization scheme greatly improved the stability and reuse performance of the catalyst and simplified the recovery operation. CLMNFs retained 90.32% relative activity after 5 consecutive cycles and maintained 84.8% relative activity after 30 days at 25 °C. It has a good practical application prospect in the degradation and detection of OPs. Consequently, the immobilized enzyme as a biocatalyst has the characteristics of high efficiency, stability, safety, and easy separation, establishing the key step in a biodetoxification system to control organophosphorus contamination in food and the environment.

Experimental Study on Performance of Cotton Small Arch Shed Recovery Machine

Most of the small-arch-shed-recycling machines in China use manual disassembly and manual recycling, with low recycling efficiency and low mechanization. Therefore, this paper designs a small recovery machine for arch sheds, greatly improving the efficiency of the recycling of arch sheds, which can realize the lifting and collection of the arch shed rod and orderly recycling of the shed film. By performing univariate experimental studies in the field, on the basis of field experiments, we carried out an experimental analysis with machine speed and different soil moisture contents as the influencing factors and took the removal rate of the shed rod, the removal rate of the shed film, and the damage rate of seedlings as the test indexes. The test results show that the optimal parameter combination is a travel speed of 1.1 m/s, at which the operation effect is the best. The results show that under the optimal operation effect, the removal rate of the shed rod was 95.72%, the removal rate of the shed film was 98.63%, the seedling injury rate was only 2.11%, and the removal rate of the shed rod was only 4.01%, which met the requirements of the recovery operation of the arch shed and means that this approach is conducive to the recycling of the arch shed materials and the realization of sustainable development. In actual operation, the parameters should be adjusted according to the actual situation in the field to meet the different recovery needs of arch sheds.

Evaluating the damage of collapsed bridges using remote sensing technologies: Case study: Baltimore’s Francis Scott Key Bridge

Bridges are vital for linking communities and facilitating economic activity. However, in the face of disaster, like ship collisions pose a significant threat to bridge infrastructure, causing structural damage and potential safety hazards. Rapid and precise assessment of the damage is essential for effective emergency response and recovery operations. Remote sensing with near-real-time satellite imagery provides the disaster scenario. This paper presents a change detection using pre- and post-disaster satellite data for Baltimore’s Francis Scott Key Bridge to identify structural damage due to the collision of the ship with support pillars on 26 March 2024. Both optical and microwave satellite data were used from open data sources and analyzed based on geospatial techniques such as change detection and surface profiling. It is estimated that an 1100-meter span of bridge was affected due to this collision, which helped to estimate the damage and mobilize the rescue operations. It may need further validation from ground truth information. Hence, the current study emphasizes the potential of remote sensing satellite data to provide near-real-time impact on disaster analysis.

Evaluating fine tuned deep learning models for real-time earthquake damage assessment with drone-based images

Earthquakes pose a significant threat to life and property worldwide. Rapid and accurate assessment of earthquake damage is crucial for effective disaster response efforts. This study investigates the feasibility of employing deep learning models for damage detection using drone imagery. We explore the adaptation of models like VGG16 for object detection through transfer learning and compare their performance to established object detection architectures like YOLOv8 (You Only Look Once) and Detectron2. Our evaluation, based on various metrics including mAP, mAP50, and recall, demonstrates the superior performance of YOLOv8 in detecting damaged buildings within drone imagery, particularly for cases with moderate bounding box overlap. This finding suggests its potential suitability for real-world applications due to the balance between accuracy and efficiency. Furthermore, to enhance real-world feasibility, we explore two strategies for enabling the simultaneous operation of multiple deep learning models for video processing: frame splitting and threading. In addition, we optimize model size and computational complexity to facilitate real-time processing on resource-constrained platforms, such as drones. This work contributes to the field of earthquake damage detection by (1) demonstrating the effectiveness of deep learning models, including adapted architectures, for damage detection from drone imagery, (2) highlighting the importance of evaluation metrics like mAP50 for tasks with moderate bounding box overlap requirements, and (3) proposing methods for ensemble model processing and model optimization to enhance real-world feasibility. The potential for real-time damage assessment using drone-based deep learning models offers significant advantages for disaster response by enabling rapid information gathering to support resource allocation, rescue efforts, and recovery operations in the aftermath of earthquakes.

Trajectory Planning of a Mother Ship Considering Seakeeping Indices to Enhance Launch and Recovery Operations of Autonomous Drones

Trajectory Planning of a Mother Ship Considering Seakeeping Indices to Enhance Launch and Recovery Operations of Autonomous Drones

Evaluating the damage of collapsed bridges using remote sensing technologies: Case study: Baltimore’s Francis Scott Key Bridge

<p class="MsoNormal" style="line-height: 120%; layout-grid-mode: char; mso-layout-grid-align: none; margin: 12.0pt 0cm 6.0pt 147.4pt;"><span lang="EN-US" style="font-size: 10.0pt; line-height: 120%; mso-fareast-font-family: 'Times New Roman'; mso-font-kerning: 0pt; mso-fareast-language: JA; mso-no-proof: no;">Bridges are vital for linking communities and facilitating economic activity. However, in the face of disaster, like ship collisions pose a significant threat to bridge infrastructure, causing structural damage and potential safety hazards. Rapid and precise assessment of the damage is aid for effective emergency response and recovery operations. Remote sensing with near real-time satellite imagery provides the disaster scenario. This paper presents a change detection using pre and post-disaster satellite data for Baltimore’s Francis Scott Key Bridge to identify structural damage due to the collision of the ship with support pillars on 26 March 2024. Both optical and microwave satellite data were used from open data sources and analyzed based on geospatial techniques such as change detection and surface profiling. It is estimated that an 1100 m span of bridge was affected due to this collision, which helped to estimate the damage and mobilize the rescue operations. It may need further validation from ground truth information. Hence, the current study emphasizes the potential of remote sensing satellite data to provide near-real-time impact on disaster analysis.</span></p>

Produced Water from the Oil and Gas Industry as a Resource—South Kuwait as a Case Study

Produced Water (PW) represents the largest waste stream in the oil and gas industry. As a water resource and as a source of valuable minerals such as alkali salts, it is has been highly under-valued, especially in hyper-arid regions. The beneficial use of PW ranges from water reinjection to elevated oil recovery from reservoirs with almost instantaneous returns, to the extraction of minerals from PW, which involves a number of different processes and setups. The economic value of PW-derived end products offers alternative revenue sources, with market fluctuations and conditions different from those of the hydrocarbon market. The end products of water and industrial salt support local industries such as agriculture, reflecting positively on the gross domestic product (GDP). Furthermore, resource extraction from PW of the oil and gas industry helps countries augment their circular economy. In this regard, the economic feasibility of three scenarios—the use of PW for oil recovery, the use of PW as an alternate source of water and industrial salt, and a hybrid process of both—is explored. The results show that there is great potential for water reuse in Enhanced Oil Recovery operations, as well as in the reduction in freshwater consumption for oil- and gas-extraction operations in the state of Kuwait by up to 4.8 percent when PW generated by SK oilfields is considered, and by 42 percent if PW from all oilfields in Kuwait is reused in the same manner.

Automatic sucker rod pump fault diagnostics by transfer learning using googlenet integrated machine learning classifiers

Oil and gas extraction is vital for meeting the energy needs of a growing global population. Artificial lift (AL) systems play a crucial role in oilfields, especially when reservoir pressure is low. Among these systems, sucker rod pumps (SRPs) are extensively employed for onshore hydrocarbon recovery operations. However, SRPs are susceptible to mechanical failures and operational challenges arising from evolving reservoir conditions. This study proposes an approach for fault diagnosis in SRPs using real-time data from sensors and machine learning (ML) algorithms to detect anomalies and patterns associated with potential problems. The proposed method involves deep learning (DL) for automated feature extraction from dynamometer cards and error-correcting output codes (ECOC) model-based supervised machine learners for efficiently assessing the operational state of the SRP. By forecasting potential failures, preemptive measures can be taken to minimize downtime and reduce maintenance costs. The application of ML in the analysis of SRP provides a potential tool for diagnosing and predicting failures, improving productivity efficiency, and reducing downtime. Also, the accuracy of Convolutional Neural Networks (CNN) models was compared with that of CNN-ECOC model-based learners in this study, and the results demonstrated that integrating algorithms such as Support Vector Machine (SVM) and k-Nearest Neighbor (k-NN) with the network caused significant improvements in the accuracy; however, Decision Tree (DT) and Naive Bayes (NB) did not perform well in the pattern classification task. Specifically, the GoogLeNet model achieved improved accuracy of 96.40 % and 99.40 % when SVM and k-NN were integrated, respectively. Conversely, with DT and NB, the accuracies dropped to 66.30 % and 75.10 %, respectively.

Identifying and modelling the barriers to returns of end-of-life (EOL) heavy-duty machinery in Nigeria: A consumers’ perspective

EOL product returns has become more prevalently practiced in companies in developed nations as a response to government's strict regulations and customers' expectations. Correspondingly, there is a growing body of theoretical literature on the topic within this context as a crucial strategy to accelerate the development of the circular economy (CE). However, consumers' participation in EOL returns of heavy-duty machinery is immature in developing nations due to barriers, and studies are scarce on the analysis of the barriers. To fill this gap, this study aims to identify and analyze the barriers that hinder consumers' participation in EOL returns of heavy-duty machinery within a developing nation-Nigeria. Barriers were identified from published literature and experts' inputs and then, classified under technological, organizational, and environmental (supply chain) categories. Then, analysis was done via a methodology integrating interval-valued neutrosophic analytical hierarchy process (IVN-AHP) with multi-objective optimization on the basis of a ratio analysis plus the full multiplicative form (MULTIMOORA). Findings indicate that the environmental(supply chain) barriers rank the highest, followed by technological barriers. Specifically, consumers participation in EOL returns of heavy-duty machinery in Nigeria is mostly hindered by lack of regulations, lack of financial incentives, lack of skills, undeveloped reverse logistics system and poor access to facilities for recovery operations. Furthermore, we proposed some strategies to support stakeholders to mitigate the barriers. Thus, this study gives valuable guidelines to decision-makers to enable the transition to a CE paradigm in the heavy-duty sector within developing nations for utmost sustainability.

Electrochemical Cell Design and Operation for Copper Recovery from Chemical Mechanical Polishing Slurries

Copper (Cu) removal from chemical mechanical polishing (CMP) waste is critical to maintaining discharge compliance with local municipalities and the Environmental Protection Agency (EPA). Typical treatment of this waste stream has followed two conventions: either coagulant-based precipitation or ion exchange (IX).1 Many industries use iron-based coagulants for metal removal from wastewater to meet discharge compliance. However, the process is often cumbersome, requires long settling times and significant chemical utilization, and results in a sludge stream that must be shipped and disposed of properly, eliminating the possibility for metal recovery. Since the concentrations for Cu removal from CMP waste streams is normally low (<100 ppm), IX has generally been the preferred treatment method. Nevertheless, IX also has some negatives associated with the process. Hydrogen peroxide can and will damage the IX media, resulting in premature replacement. The industry has dealt with this impact by employing one-time use media, but this adjustment means that media is only used once before being shipped offsite for regeneration. This results in operational impacts due to the need for oversight of media replacement and also eliminates the ability for Cu to be recovered at the originating process site.In this talk, electrochemical methods to recover Cu from CMP wastewaters will be described. Electrochemical cell design and operation will be shown to provide Cu removal across wide ranges of concentration, and the depth of Cu separation (<2 ppm) and efficiency of the process will be discussed. The presence of hydrogen peroxide and its influence on the process will be evaluated. The removal and recovery of Cu will be shown in a complete cycle, demonstrating the ability to recover and reuse Cu directly at a process site. The impact of (1) pH, (2) chelator type, and (3) abrasive (SiO2) will also all be reviewed. Changes to the slurry, as analyzed pre- and post-electrochemical separation, will be characterized to determine possibilities for the reuse of the CMP slurry itself. Ultimately, the ability to design process systems using electrical input and minimal chemical additives to treat wastewater to municipal and EPA specifications while maximizing recycling efforts will be evaluated and presented.

The movement pattern changes of population following a disaster: Example of the Aegean Sea earthquake of October 2020

Unexpected seismic events can have a significant impact on our daily lives. Examining post-disaster population movement patterns contributes to disaster response and recovery operations. While most studies analyze population movement or displacement data, only a few examine multi-level movement patterns and consider public transportation demand. This paper aims to analyze changes in movement patterns following a major earthquake that severely affected İzmir in Türkiye, mainly using movement data from the Data for Good platform of Meta. According to the findings, on the first day following the earthquake, those traveling within İzmir considered the areas least damaged to be safer, despite the higher seismic intensity. The timeframe alignment between aftershock activity and the number of people traveling within İzmir suggests the routine movement pattern within the city was regained as the aftershocks decreased day by day. Unlike intra-city travel routines, there was an increase in the number of people moving to summer houses, located far from the center of İzmir. By November 2, 2020, three days after the earthquake, intra-city movements reached a new normal, as confirmed by public transportation use. However, intra-city travel patterns were impacted for approximately one month. This study reveals key findings from the evaluation of post-earthquake movements to improve disaster management decision making and aid crisis response and recovery operations.

Consensus Control of Heterogeneous Uncertain Multiple Autonomous Underwater Vehicle Recovery Systems in Scenarios of Implicit Reduced Visibility

This paper investigates consensus control in heterogeneous and uncertain multiple autonomous underwater vehicle (AUV) systems under implicit reduced visibility conditions. We address challenges such as environmental uncertainties and system nonlinearity by utilizing a unified connectivity approach to model low-visibility interactions and heterogeneous multi-AUV dynamics. Our main contributions include developing a feedback linearization model for heterogeneous multi-AUV systems that accounts for uncertainties, introducing an adaptive consensus controller based on relative positioning that effectively manages implicit visual interaction limitations and validating our strategies through stability analysis and numerical simulations. Our simulations demonstrate approximately a 60% improvement in accuracy compared to previous algorithms, highlighting the practical value of our approach in AUV recovery operations. These advancements provide a robust solution for consensus control in complex underwater environments.

A non‐ionic green surfactant extracted from the Anabasis setifera plant for improving bulk properties of CO2‐foam in the process of enhanced oil recovery from carbonate reservoirs

AbstractFoam, as a gas‐in‐liquid colloid, has a higher appearance viscosity than the one of both gas and liquid that form it. Adjusting the mobility ratio of the injected fluid–oil system and increasing gas diffusion in the foam injection process increase oil production. With these properties, foam as an injection fluid in fractured reservoirs has a major effect on oil production from the matrixes and prevents premature production of injection fluid. Surfactants are common foaming agents in injection water. Saponins are known as plant‐derived surfactants for forming stable foam. This feature, along with its cheap price and availability, can make them candidates for enhanced oil recovery (EOR) by the foam injection method. However, the utilization of CO2 as the gaseous phase in foam introduces additional machanisms of CO2 injection to the oil recovery operations. In this assessment, a non‐ionic green surfactant derived from the Anabasis setifera plant was used as a foaming agent, while CO2 served as the gas phase. A series of surface tension tests in CO2 environment were performed to determine the optimal concentration of the surfactant. Foaming tests were performed by a designed foam generator. The produced CO2‐foam was then injected into a fractured carbonate plug with six matrixes (with one horizontal and two vertical fractures). Based on the results, the water–CO2 surface tension was reduced to 20.549 mN/m. The optimum salinity based on the foam stability was 10,000 ppm. The half‐life of the foam was determined to be 40 min. Also, the foam characterization showed that the foamability of the surfactant was favourable for increasing oil production so that by secondary flooding, an oil recovery of more than 66% was achieved from the fractured carbonate plug.

Advancing Water Deoiling Efficiency in Petroleum Production: A Comprehensive Case Study of Hybrid Flotation Technology Integration

_ The efficient management of increasing water cuts in oil fields is paramount for sustaining profitability and minimizing environmental impact. This article presents a comprehensive case study conducted by Saudi Aramco, focusing on the integration of hybrid flotation technology into a gravity water/oil separator (WOSEP) to enhance deoiling efficiency and reduce operational costs and carbon emissions. The retrofit involved merging enhanced gravity separation with induced gas flotation (IGF) within the same vessel, resulting in significant improvements in deoiling capacity, outlet oil-in-water content reduction, and operational efficiency. Detailed insights into the design, operation, and performance of hybrid flotation systems are provided, offering valuable guidance for similar initiatives in the petroleum industry. Introduction Petroleum production facilities face escalating challenges with increasing water-production rates during crude-oil extraction, particularly in waterflooding operations for secondary oil recovery. This trend not only escalates operational costs but also intensifies environmental concerns, particularly regarding energy consumption and carbon emissions associated with water-handling processes. In response to these challenges, Saudi Aramco embarked on a pioneering initiative to enhance water-deoiling efficiency by integrating hybrid flotation technology into a conventional gravity WOSEP. This case study presents a comprehensive analysis of the design, implementation, and outcomes of this transformative project, offering valuable insights for the broader petroleum industry. Methodology The upgrade process commenced with an assessment of the existing WOSEP system and its operational challenges. Recognizing the impending capacity constraints and escalating oil-in-water content, Saudi Aramco’s engineering team opted for a holistic approach that combined enhanced gravity separation with IGF within the same vessel. The retrofit involved reconfiguring the internal components of the WOSEP to accommodate the hybrid flotation system, including the installation of advanced plate-pack internals for gravity separation and the integration of IGF cells for additional oil removal. Rigorous testing and optimization procedures were conducted to ensure seamless integration and optimal performance of the hybrid system. Gas/Oil Separation Plant Process Description In a typical gas/oil separation plant, the initial phase involves the extraction of crude oil, associated gas, and produced water from wells via a production manifold. These constituents are then directed to a three-phase separator, also known as a high-pressure production trap (HPPT). In the HPPT, free water droplets are separated from the oil through gravity separation, aided by demulsifier injection at the production header. The separated free water is discharged to a WOSEP, typically a gravity separator, for deoiling.

Performance analysis of ground source heat pump systems for constant temperature and humidity air conditioning in industrial buildings: a case study

Abstract The ground source heat pump (GSHP) system has gained widespread popularity for its provision of efficient and environmentally sustainable cooling and heating solutions for buildings. While the performance of GSHP systems has raised significant concerns, research predominantly focuses on residential and office buildings, leaving a gap in understanding their applicability in industrial settings with constant temperature and humidity air conditioning needs. This study aims to address this gap by evaluating the performance of a hybrid ground source heat pump (HGSHP) system implemented within a cigarette factory located in the hot summer and cold winter (HSCW) of China. Through a comprehensive analysis of operational data and long-term monitoring under three cooling conditions, essential parameters including water temperature characteristics, indoor temperature and humidity, system efficiency, power consumption, and soil temperature distribution were examined. The findings revealed that the weighted average coefficient of performance (COP) of the heat pumps (COPhp) and the whole system (COPsys) was decreased from 5.05 to 4.32 and 3.32 to 2.89, respectively. A positive correlation was observed between low cooling load high energy consumption, and low COP. The inlet temperature of the condenser exhibited a declining trend, which was attributed to the intermittent operation of condensation heat recovery. Furthermore, a comprehensive analysis of indoor temperature and humidity distribution within the controlled room was presented and found that almost all the rooms serviced by this system meet the specified design requirements. This research contributes to an enhanced understanding of the viability of HGSHP systems in industrial settings and provides valuable references for improving their energy efficiency and overall performance.

Design, construction, and testing of an exploding wire pulsed plasma system for generating shock waves in industrial applications

Exploding Wire Pulsed Plasma System (EWPPS) used in oil recovery operations has been construct and developed with an initial energy release of 1.5 kJ in a fusion laboratory. Recently, the final experiments have been carried out on the purpose device operating in microsecond time scale in air and fluid medium successfully. In this setup, a single wire feeder is used for tests. Also, to study and develop the shock waves caused by wire explosions in the industry, the diagnostic tools of voltage probe, current coil, pressure probe and photodiode have been used. Choosing the optimal material of wire is one of the basic factors in creating a suitable shock wave. In addition, the impact of wire inductance on discharge current, voltage, pressure and shock wave strength has been investigated by applying two sets of wires, refractory (Cu, Cu-Ni, and Steel) and non-refractory (W, W-Al, Mo). The results show that the strongest shock wave is produced while the transition from warm wire to dense plasma happens. The soft X-ray intensity of both wire series has been measured using a photodiode BPX-65 (<10 keV). The comparison shows higher X-ray intensity for non-refractory wires than that for refractory wires. In good agreement, the maximum value of the shock wave was 8.7 and 6.6 MPa for non-refractory metals with high inductance and refractory metals with low inductance, respectively.

Chichimene field T2 sand: a successful application of cycles in a water injection project on heavy crude oil, enabled by a novel smart selective completion system adapted for water injection

This paper presents the application of injection in cycles, assisted by the first smart selective completion system with remote valve operation. The completion system was installed in the Chichimene Field unit T2 (Fm. San Fernando). The results were compared with conventional water injection, technology that utilizes a simple selective completion system, in the aspects of recovery factor, water consumption, operation style, and others. The target unit has been subjected to selective water injection since 2016, this process consisted of injection of a controlled amount of water within 3-4 zones in equilibrium with the extractive system on producers wells to find a better crude oil movement and a commercial recovery factor. Despite this, the surveillance evidence suggests that some zones consume too much water due its high permeability (heterogeneity) and this impacts on high water cut on producers due to the (adverse mobility ratio), but also suggested that there is a better way to improve even more the recovery factor. This enhancement was enabled with a smart selective completion system by promoting a scheduled temporal closure of zones while production continues, achieving pressure-production restoration effects on the closed zones, allowing an efficiency increase of the vertical and areal sweep. To determine if this could work, a smart completion system was installed in one well in August 2019. During more than one year, the operation and interpretation of the DAS measuring tool (Continuous sound recording) was understood, from which injected water per zone is daily known, with this, the optimization of the injection rate per zone allowed enhancement of the production pattern behaviour. In February 2021, the injection cycles started on the well by zone, and to the current date, more than 25 monthly cycles have been done, increasing the recovery factor, with a considerable reduction in water and energy consumption, maintaining a continuous measurement of zone injection, this level of information has never been reached in the industry. The case study establishes a new frontier in the field of selective injection and in cycles as well, allowing an evolution step in water injection technology. This pilot combined in one design: selective injection, intelligent remote operate completions, continuous layer injection measuring by DAS, extra heavy oil WF, management of high permeability variations and it is aligned with the latest regulations in decarbonization (water and energy saving). From a reservoir point of view, it has never been there, a surveillance in injectors with this level of quality to enhance performance, and on the surface, this technology has allowed an important reduction in the use of wirelines for well operations and improve some well cleaning interventions with coiled tubing.