Search Results (15)

Electric submersible pumps (ESPs) are critical for artificial lift operations; however, they are prone to frequent failures, often resulting in high operational costs and production downtime. Traditional ESP failure classifications are limited by lack of standardization and the conflation of failure modes with root causes. To address these limitations, this study proposes a new two-step integrated failure modes and root cause (IFMRC) classification system. The new framework clearly distinguishes between failure modes and root causes, providing a systematic, structured approach that enhances fault diagnosis and failure analysis and can lead to better failure prevention strategies. This methodology was validated using a case study of over 4000 ESP installations. The data came from Egypt’s Western Desert, covering a decade of operational data. The sources included ESP databases, workover records, and detailed failure investigation (DIFA) reports. The failure modes were categorized into electrical, mechanical, hydraulic, chemical, and operational types, while root causes were linked to environmental, design, operational, and equipment factors. Statistical analysis, in this case study, revealed that motor short circuits, low flow conditions, and cable short circuits were the most frequent failure modes, with excessive heat, scale deposition, and electrical grounding faults being the dominant root causes. This study underscores the importance of accurate root cause failure classification, robust data acquisition, and expanded failure diagnostics to improve ESP reliability. The proposed IFMRC framework addresses limitations in conventional taxonomies and facilitates ongoing enhancement of ESP design, operation, and maintenance in complex field conditions. Full article

Climate change has driven global awareness of environmental issues, leading to the adoption of clean technologies aimed at reducing Greenhouse Gas (GHG) emissions. An effective method to assess environmental mitigation is the quantification of the Product Carbon Footprint (PCF) in the Life Cycle Assessment (LCA) of production processes. In the oil extraction industry, artificial lift systems use electro submersible pumps (ESPs) that can now incorporate new operating principles based on permanent magnet motors (PMMs) and CanSystem (CS) as an alternative to traditional normal induction motors (NIMs) and can help lower the carbon footprint. This study compares the PCF of ESPs equipped with PMMs and CS versus NIMs, using LCA methodologies in accordance with ISO 14067:2018 for defining the Functional Unit (FU) and ISO 14064-1:2019 to calculate the GHG inventory and the amount of CO₂ equivalent per year. The analysis spans five key stages and 14 related activities. For ESPs with NIMs, this study calculated 999.9 kg of raw materials, 1491.66 kW/h for manufacturing and storage, and 5.77 × 10⁴ kW/h for use. In contrast, ESPs with PMMs and CS required 656 kg of raw materials and consumed 4.44 × 10⁴ kW/h during use, resulting in an 23% reduction in energy consumption. This contributed to an 21.9% decrease in the PCF. The findings suggest that PMMs and CS offer a sustainable solution for reducing GHG emissions in oil extraction processes globally. Full article

The suction-lifting system of cutter suction dredgers consumes a large amount of energy. Optimizing their performance is of great significance for enhancing the overall efficiency of dredgers. This study proposes the effective specific cutting energy, a new indicator suitable for evaluating the energy consumption of the cutting system of cutter suction dredgers. It reflects the cooperation state between the cutter system and the pump-pipe system and has important reference value for improving construction efficiency. The calculation method of the effective specific cutting energy is given, which is calculated by the cutter motor power, slurry concentration, and slurry flow rate. Based on the machine learning framework, a model framework for predicting the specific cutting energy according to the relevant parameters of the suction-lifting system is constructed. Real ship data from the cutter suction dredger “Changshi 12” are used for experiments. First, eigenvalue screening is carried out based on the dredging knowledge and mechanism, then outliers are removed, and finally data processing is performed using Spearman correlation coefficient and PCA dimensionality reduction techniques. Subsequently, five machine learning algorithms, such as RF and XGBoost, are used in combination with a grid search to find the optimal hyperparameters, and Lasso is used as the meta-learner to integrate the prediction results. The experimental results show that the Random Forest and Stacking models have high prediction accuracy for slurry concentration, cutter motor power, and slurry flow rate, verifying the feasibility of this method. Full article

Crawler cranes are mobile lifting equipment used in the process of hoisting goods. After the initial lifting, the crane may need a secondary lift due to adjustments in the position or height of the load. Addressing the common issue of load slipping during the secondary lift caused by hydraulic motor reversal, this study proposes a control strategy applicable to crawler crane secondary lifting. Initially establishing the dynamic characteristics of the secondary lift system, incorporating a delay coefficient, and matching motor pressure build-up with memory pressure, the strategy considers a variable pump input current control to identify the relationship between motor pressure build-up and brake release. Analyzing the dynamic characteristics of secondary lifting under different conditions, this study resolves the issue of hydraulic motor reversal during the second lift caused by heavy loads. The results of this study on crawler crane secondary lifting indicate that, when using a delay coefficient of 0.70 and releasing the brake, no slip phenomenon occurred during the secondary lift process under different load conditions, categorized as 200 tons, 600 tons, and 1000 tons. This ensures the stability and transition quality of the secondary lift, providing theoretical guidance for the control of the crawler crane secondary lifting. Full article

The electrical submersible pump (ESP) well system is widely used in the oil industry due to its advantages of high displacement and lift capability. However, it is associated with significant energy consumption. In order to conserve electrical energy and enhance the efficiency of petroleum companies, a deep learning-based energy consumption calculation method is proposed and utilized to optimize the most energy-efficient operating regime. The energy consumption of the ESP well system is precisely determined through the application of the Pearson correlation coefficient analysis method, which is utilized to examine the relationship between production parameters and energy usage. This process aids in identifying the input parameters of the model. Following this, an energy consumption prediction model is developed using the dual-stage attention-based recurrent neural network (DA-RNN) algorithm. To evaluate the accuracy of the DA-RNN model, a comparison of its errors is carried out in comparison to three other deep learning algorithms: Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), and Transform. Lastly, an orthogonal experiment is executed using the chosen model to pinpoint the most energy-efficient operating regime. Analysis of 325 ESP wells in the Bohai PL oil field indicated that ten parameters, including choke diameter, casing pressure, pump inlet pressure, pump outlet pressure, motor temperature, frequency, oil production, gas production, water production, and GOR significantly impact the energy consumption of the ESP well system. Consequently, these parameters were selected as input variables for the deep learning model. Due to the attention mechanisms employed in the encoding and decoding stages, the DA-RNN algorithm achieved the best performance during model evaluation and was chosen for constructing the energy consumption prediction model. Furthermore, the DA-RNN algorithm demonstrates better model generalization capabilities compared to the other three algorithms. Based on the energy consumption prediction model, the operating regime of the ESP system was optimized to save up to 12% of the maximum energy. The energy consumption of the ESP well system is affected by numerous parameters, and it is difficult to comprehensively evaluate and predict quantitatively. Thus, this work proposes a data-driven model based on the DA-RNN algorithm, which has a dual-stage attention mechanism to rapidly and accurately predict the energy consumption of the ESP well system. Optimization of production parameters using this model can effectively reduce energy consumption. Full article

The purpose of this research is to solve the complex long-distance and high-lift water supply engineering accident water hammer protection problem. Taking the Zhaojinzhuang water supply project as an example, based on the method of characteristics (MOC), the water hammer of the pumping station under the combined action of a water hammer relief valve, hydraulic-control butterfly valve, air vessel, air valve, and other water hammer protection measures is numerically simulated and calculated, and the effectiveness of the range method is analyzed, to ensure a waterproof hammer in pump stop accidents. The results show that the main factors affecting the effect of water hammer protection under the two-stage valve-closing parameters of the hydraulic-control butterfly valve are the fast-closing angle and the slow-closing time. The arrangement of the air vessel behind the pump can effectively increase the minimum water hammer pressure in the climbing section, and with the increase of the volume of the air vessel, the pump reverse speed and the maximum positive pressure increase slightly, but the overall water hammer protection effect is better. With the increase of the moment of inertia of the motor, the maximum positive pressure and minimum negative pressure of the pipeline still do not meet the requirements of the specification, and the modification cost is relatively large. The combination of the one-stage hydraulic-control butterfly valve, the air valve, the air vessel, and the water hammer relief valve can effectively reduce the volume of the air vessel. Under the optimal method, the maximum positive pressure head is 236.61 m, and the minimum negative pressure head is −3.18 m. Compared with the original method, the maximum positive pressure head is increased by 1.18%, the minimum negative pressure head is reduced by 95.78%, the maximum reverse speed of the pump is reduced by 100%, and the maximum reverse flow of the pump is reduced by 70.27%, meeting the requirements of water hammer protection. This is a safe and economical protection method. Full article

Submersible tubular pumps are an ideal choice for pump stations that require high flow rates and low lift. These pumps combine the unique features of submersible motors with axial flow pump technology, making them highly efficient and cost-effective. They have found extensive applications in China’s rapidly developing water conservancy industry. In this research, we focus on investigating the pressure pulsation characteristics of the internal bulb body in a specific pump station project in China. To conduct our analysis, we utilize a model of the submersible tubular pump and strategically position 18 monitoring points. These monitoring points cover various sections, including the impeller inlet and outlet, guide vane outlet, as well as the inlet, middle, and outlet sections of the bulb body segment. To calculate the unsteady flow of the system, we employ numerical simulation techniques. By combining the outcomes of model tests, we determine the pressure pulsation characteristics. The comparison of results reveals a remarkable similarity between the efficiency–head curves obtained from the numerical simulation and the model test. While the model test yields slightly higher head results, the numerical simulation indicates slightly higher efficiency values. This finding lends strong support to the reliability of numerical simulation results, which can provide valuable insights for the design and optimization of submersible tubular pumps. Overall, submersible tubular pumps demonstrate their suitability for pump stations with high flow rates and low lift requirements. The study of pressure pulsation characteristics within the bulb body contributes to a better understanding of their performance and facilitates their further application in the field of water conservancy engineering. Full article

Low-carbon energy transitions taking place worldwide are primarily driven by the integration of renewable energy sources such as wind and solar power. These variable renewable energy (VRE) sources require energy storage options to match energy demand reliably at different time scales. This article suggests using a gravitational-based energy storage method by making use of decommissioned underground mines as storage reservoirs, using a vertical shaft and electric motor/generators for lifting and dumping large volumes of sand. The proposed technology, called Underground Gravity Energy Storage (UGES), can discharge electricity by lowering large volumes of sand into an underground mine through the mine shaft. When there is excess electrical energy in the grid, UGES can store electricity by elevating sand from the mine and depositing it in upper storage sites on top of the mine. Unlike battery energy storage, the energy storage medium of UGES is sand, which means the self-discharge rate of the system is zero, enabling ultra-long energy storage times. Furthermore, the use of sand as storage media alleviates any risk for contaminating underground water resources as opposed to an underground pumped hydro storage alternative. UGES offers weekly to pluriannual energy storage cycles with energy storage investment costs of about 1 to 10 USD/kWh. The technology is estimated to have a global energy storage potential of 7 to 70 TWh and can support sustainable development, mainly by providing seasonal energy storage services. Full article

The impeller blades will continually strike the slurry mixture inside the pump, causing deterioration and a change in particle size. In this study, the degradation of mineral particles under various cycle times, rotational speeds, and flow rates is analyzed. The microscopic parameters of polymetallic nodules are calibrated by EDEM, and the transport of polymetallic nodules in the deep-sea lifting electric pump is simulated based on the coupled CFD-DEM solution of solid–liquid two-phase flow. The findings demonstrate that: the number of cycles through the pump has the greatest impact on particle degradation, and the number of fine particles significantly increases after the particles are impacted by the six-stage lifting electric pump several times; the higher the flow rate in the lifting electric pump, the faster the particles are dragged by the fluid, and the more easily the particles degrade; the faster the impeller speed of the lifting electric pump. Full article

Aiming at the parameters of the different displacements and related components of the variable-displacement asymmetric axial piston pump (VAPP) required by the energy-recovery system of excavator booms of different tonnages, a rapid multi-process parallel optimization method of complex hydraulic products based on a multi-core CPU was proposed for parameter matching. The parameter matching was used to reasonably select relevant parameters so that the excavator’s boom energy-recovery and utilization system can improve operational efficiency and energy-saving efficiency under the premise of satisfying the normal working conditions of the working mechanism, and achieving the purpose of serializing VAPP products. A multi-objective optimization model was put forward according to energy-saving efficiency and operational efficiency. First, the accuracy of the acceleration method of the CVODE, a solver for stiff and non-stiff ordinary differential equation (ODE) systems, was verified by a physical prototype test. The results showed that the test and simulation results were in good agreement. A particle swarm optimization algorithm (PSO) was used to optimize the main parameters of the boom energy-recovery system to obtain the appropriate energy-saving efficiency and obtain the VAPP displacement and related component parameters required by the energy-recovery system of excavator booms of different tonnages. The simulation results showed that a motor working condition was necessary in the guaranteed descending stage, and the process of lifting–descending–lifting was completed under the condition that the total time did not exceed a certain value. The energy-saving rates of the 7-ton (7T), 12-ton (12T), 20-ton (20T), and 30-ton (30T) excavator boom energy-recovery systems reached 29.8%, 35.3%, 31.25%, and 27.88%, respectively. In the eight-core CPU workstation under the simulation conditions, compared with the Simulation X platform simulation method, the simulation efficiency of the multi-core CPU parallel method was improved by more than 80 times. Full article

The polymetallic nodules in the deep-sea multi-stage lifting motor pump will undergo repeated impeller blade impact and fragmentation, which will change the particle size, thereby affecting the number of ores that can be recovered on the surface and the design parameters of the processing equipment. A new calculation method of degradation rate is proposed. The degradation model of multiple impacts of particles is improved to quantitatively calculate the final particle size distribution (PSD) of polymetallic nodules transported from the Clarion Clipperton Zone (CCZ) to the ground through a series of multi-stage lifting electric pumps. The newly proposed calculation method is obtained by analyzing the degradation of experimental data of polymetallic nodules when they pass through the six-stage lifting motor pump experimental system many times. The improved model is used to predict the PSD of the nodules after running for 10 min in the experimental system, and compared with the experimental test results, the deviation is small. The new method can estimate the change in PSD of nodules due to degradation during transportation, reducing design costs for land processing equipment. Full article

A hydraulic excavator (HE) is a typical piece of construction equipment and is widely used in various construction fields. However, the poor energy efficiency of HEs results in serious energy waste and has aroused the attention of researchers. Furthermore, rising fuel prices and increasing stringent waste gas emission legislation sparked demand for ways to improve energy efficiency. Recovering the otherwise wasted boom potential energy of a conventional HE by proper methods offers the potential to improve the fuel efficiency of HEs. In this paper, a mechanical energy recovery system consisting of a pump/motor and a flywheel is presented for HEs using a load sensing system. When the boom moves down, the boom potential energy is converted into mechanical energy by the boom cylinder and the pump/motor to accelerate the flywheel. When needed, the captured energy stored in the flywheel is converted back into a form of pressure energy to directly drive the boom cylinder up without throttling the main valve. In the lifting process, a compound circuit that consists of a throttling control circuit and a displacement control circuit is presented. A control strategy is proposed to optimize the energy recovery and reuse procedure. A 4-t HE is used as a study case to investigate the energy-saving potential of the proposed system. Numeric simulations show that the proposed system, when compared with a conventional load sensing system, can reduce as much as 48.9% energy consumption in a non-loaded cycle of boom lifting and lowering process. As to a fully loaded case, the energy-saving rate is 16.9%. This research indicates the flywheel-based scheme is promising for developing an energy-efficient fluid power system for HEs and reducing energy consumptions. Full article

While the world population is expected to reach 9 billion in 2050, in West Africa, it will more than double. This situation will lead to a high demand for cereals in the region. At the same time, farmers are experiencing yield losses due to erratic rainfall. To come up with a sound and effective solution, the available but limited water should be used to achieve high yields through irrigation. Therefore, full and deficit irrigation management strategies were evaluated. The expected profit that can be obtained by a smallholder farmer under a conventional irrigation system in the short-term of investment was also assessed considering rope and bucket, treadle pump, and motorized pump water-lifting methods. The study focused on maize in northern Togo. The framework used in this study consisted of (i) a weather generator for simulating long-term climate time series; (ii) the AquaCrop model, which was used to simulate crop yield response to water; and (iii) a problem-specific algorithm for optimal irrigation scheduling with limited water supply. Results showed high variability in rainfall during the wet season leading to significant variability in the expected yield under rainfed conditions. This variability was substantially reduced when supplemental irrigation was applied. This holds for the irrigation management strategies evaluated in the dry season. Farmers’expected net incomes were US$ 133.35 and 78.11 per hectare for treadle pump and rope and bucket methods, respectively, under 10% exceedance probability. The motorized pump method is not appropriate for smallholder farmers in the short run. Full article

In this experimental study, a Direct Driven Hydraulics (DDH) system of the closed circuit type was utilized for cyclic vertical actuation in heavy load material handling. The actuator was controlled by a speed-controlled fixed displacement pump. The high energy saving potential of this system has been demonstrated in previous studies by the authors, but the dynamic characteristics of the ramped and P-controlled base system were considered unsatisfactory. Therefore, the system was implemented with an open-loop S-curve control that utilized a pre-calculated RPM (revolutions per minute) profile for the electric motor in order to realize a smooth actuator and load transition as a function of time. The results indicate that S-curve control is exceptionally well suited for producing a controlled lifting–lowering rapid motion with a heavy load, while still keeping the actuator chamber pressures within acceptable limits. In comparison, the motion produced by P-control was characterized by large unwanted pressure peaks together with velocity fluctuations and vibrations at the end of the stroke. Using a combination of S-curve control and hydraulic load compensation, a mass of 1325 kg could be moved 0.26 m in less than 0.5 s. The load compensation reduced the energy consumption by 64%, which would allow downsizing the electric motor and enable cost-efficient DDH implementation. Full article

Deep geothermal energy systems employ electric submersible pumps (ESPs) in order to lift geothermal fluid from the production well to the surface. However, rough downhole conditions and high flow rates impose heavy strain on the components, leading to frequent failures of the pump system. As downhole sensor data is limited and often unrealible, a detailed and dynamical model system will serve as basis for deeper understanding and analysis of the overall system behavior. Furthermore, it allows to design model-based condition monitoring and fault detection systems, and to improve controls leading to a more robust and efficient operation. In this paper, a detailed state-space model of the complete ESP system is derived, covering the electrical, mechanical and hydraulic subsystems. Based on the derived model, the start-up phase of an exemplary yet realistic ESP system in the Megawatt range—located at a setting depth of 950 $\mathrm{m}$ and producing geothermal fluid of 140 ${}^{\circ }\mathrm{C}$ temperature at a rate of 0.145 ${\mathrm{m}}^3{\mathrm{s}}^{-1}$ —is simulated in MATLAB/Simulink. The simulation results show that the system reaches a stable operating point with realistic values. Furthermore, the effect of self-excitation between the filter capacitor and the motor inductor can clearly be observed. A full set of parameters is provided, allowing for direct model implementation and reproduction of the presented results. Full article