Rod Load Research Articles

A Well-Tested Pump Card Classification and Identification Algorithm Based on Time Series Analysis Techniques

Abstract To accurately identify the operational conditions of oil pumping wells, promptly monitor the working status of oil wells, expedite responses to sudden pumping well accidents, and ensure orderly production at the oil extraction site, this paper introduces a time segment-based oil pumping well condition identification algorithm. This method no longer relies on drawn dynamometer cards for condition identification. Instead, it solely utilizes sensor-provided polished rod displacement and load time series, aligning more closely with the data’s intrinsic nature. The algorithm is sufficiently lightweight, highly responsive, and does not require GPU resources, making it suitable for edge deployment. Furthermore, this approach provides evidence of the time continuity and numerical continuity of time series data. Compared to traditional identification methods, this approach maintains a high level of accuracy, offers a streamlined model, and is interpretable, presenting a novel perspective for oil pumping well condition identification.

An experimental platform for investigation of the Zeeman effect in strong magnetic fields.

An experimental platform is developed for the investigation of the Zeeman effect in strong magnetic fields. Mega-Gauss magnetic fields are generated by a 1 MA Zebra pulsed power machine using metal rod loads. A gas jet or CH oil on the load is the source of hydrogen. Excited hydrogen atoms are backlit by black body radiation from the rod load. Hydrogen absorption spectra are recorded with a grating spectrometer and intensified gated CCD camera. The experimental platform enables the observation of the quadratic Zeeman effect in hydrogen gas jets using the spectral shift of the central line in the Zeeman triplet. Other gases can be studied using the gas jet method.

Research on the Soft-Sensing Method of Indicator Diagram of Beam Pumping Unit.

An accurate calculation of the indicator diagram of a pumping unit is the key factor in analyzing the performance of an oilfield production and operation and in preparing and optimizing an oilfield development plan. Aiming at the problems of the poor stability of the conventional load-displacement sensor method and the wave equation method, owing to the influence of an alternating load on the force sensor and the difficulty in measuring the crank angle using the electrical parameter method, a new soft sensing method employing the input electrical parameters of the motor and the beam inclination has been proposed to obtain the indicator diagram. At first, this method is established based on the beam angle of the pumping unit, which is easily measured using the suspension point displacement mathematics calculation model and the torque factor. Subsequently, the electric motor input parameters, the parameters of the four-bar linkage, and the relationship between the polished rod load have been established. Finally, the motor and the beam angle of the measured electrical parameters have been substituted into the calculation of the suspension point displacement and load value and pull in accordance with the guidelines to eliminate the singularity mutation values. After processing the measured data through a Butterworth filter, the indicator diagram is obtained. The results of the engineering experiment and application show that the average relative error of the method is less than 3.95%, and the maximum relative error remains within 2% for 6 months, which verifies the stability of the soft sensing method.

Experimental Study on the Identification and Diagnosis of Dynamic Crack Propagation in the Piston Rods of Process Gas Compressors in Underground Gas Storage

Ensuring the reliability of process gas compressors is critical for underground gas storage, as piston rod fractures can lead to serious accidents, such as natural gas leaks or explosions. On-time monitoring and early detection play a vital role in preventing catastrophic consequences, minimising costs, and reducing production losses due to unplanned downtime. This study presents a novel accelerated life-testing method designed to replicate the fracture events of reciprocating compressor piston rods. By accelerating the induced crack initiation and propagation to the final fracture, comprehensive analyses of the fracture results are performed to reveal the piston rod fracture mechanism and the resulting secondary damage to the unit. The research further presents an innovative approach for identifying piston rod crack propagation by means of acoustic emission. Through kinetic analysis and time–frequency domain analysis, the study elucidates two mechanisms responsible for triggering crack signals during the compressor operation: the contact impact between the crosshead pin and the bearing due to the piston rod load reversal, and crack propagation occurring before the maximum tensile load is reached. In addition, the study identifies the piston rod crack expansion signal frequency band and achieves a high-sensitivity identification of crack dynamic growth by extracting signal sub-band features associated with crack propagation. Then, a prediction model of the fatigue crack growth rate was established based on the AE energy release rate, which provides a quantitative assessment of dynamic crack propagation during compression. This method aims to provide a maintenance strategy for piston rod fractures, thereby increasing the operational safety of critical dynamic equipment in underground gas storage.

Fracture mechanism and fault evolution of piston rod in hydrogen reciprocating compressor

Ensuring the reliable operation of reciprocating compressors is critical in the hydrogen industry chain. Piston rod fracture is one of the most serious failures in compressors, which makes it essential to investigate the mechanism of piston rod fracture under normal operating conditions. Here, a multi-body dynamics model was developed to analyse the operating posture and load pattern of the reciprocating assembly. A finite element model was then constructed to calculate the stress distribution of piston rod threads under cyclic tensile and compressive rod load, lateral force and piston drop. The model was validated by visualization of stress distribution via digital image correlation. The study identifies a propagation chain for fault evolution, and explains the mechanisms that induce fracture in cases from a failure source perspective. This work provides new insights into the fault mechanism of hydrogen reciprocating compressors and advances the theoretical framework for compressor condition monitoring and fault diagnosis.

Coupling Simulation of Longitudinal Vibration of Rod String and Multi-Phase Pipe Flow in Wellbore and Research on Downhole Energy Efficiency

The wellbore of a sucker–rod pumping well experiences a multi–phase flow consisting of oil, gas, and water. The flow pattern and pump discharge pressure are greatly impacted by oil well production, which in turn significantly affects the simulation results of longitudinal vibration in the sucker–rod string. When calculating the discharge pressure in a hydrostatic column containing both oil and water (HC), the pressure is not affected by the oil well’s production. This thereby avoids interference between vibrations in the sucker–rod string’s longitudinal direction and the flow from the wellbore. Considering the coupling characteristics between the longitudinal vibration of the sucker–rod string and the wellbore flow, a mathematical model of the sucker–rod pumping system (CMSRS) and a mathematical model of the downhole energy efficiency parameters were established. In detail, the CMSRS comprises two parts: the discharge pressure mathematical models of multi–phase flow dynamics (MD) and the wave equation of the longitudinal vibration of the sucker–rod string. A numerical simulation model of the sucker–rod pumping system was constructed based on a mathematical model. We compared the experimental results, the simulation results of the CMSRS and the simulation results of the sucker–rod string based on the oil–water two–phase hydrostatic column (SMSRS) and found good agreement, indicating the feasibility of the CMSRS. The simulation details show the following: (1) The HC model’s discharge pressure exceeds that of the MD model by more than 33.52%. The polished rod load for the CMSRS is 18.01% lower than that of the SMSRS, and the pump input power for the CMSRS is 36.23% lower than that of the SMSRS. (2) The effective power simulation model based on the energy balance relationship is essentially the same as the effective power calculated by the model based on multi–phase flow effective power. This validates the accuracy of the multi–phase flow effective power model. (3) The limitations of the industry standard effective power model are that (i) the effective head is the net lift height of the fluid in the wellbore reduced to the oil and water phases rather than the effective lift height based on the energy balance relationship and (ii) the power of the gas phase delivered by the pumping pump is disregarded, and only the effective power of the pump delivering the oil–water mixture is considered. (4) The influence of the wellbore parameters on the wellbore efficiency and sub–efficiency is systematically analyzed. The analysis results have an important significance in the guidance of energy saving in pumping wells.

Quantitative diagnosis of loose piston rod threads in reciprocating compressors for hydrogen storage and transport

Fracture of the piston rod yields catastrophic accidents in reciprocating hydrogen compressors, resulting in costly and time-consuming maintenance and developing the latest challenge to hydrogen safety and economy. The fracture-prone section is mostly located at the connecting thread of the crosshead or of the piston, mainly due to thread loosening and hereby insufficient preload followed by fatigue and fracture. Here, a novel quantitative diagnosis method for thread loosening of hydrogen reciprocating compressor piston rods was proposed. First, a finite element model of a single-throw reciprocating compressor was established to analyse the dynamic behaviour of the operating posture and load pattern at the crosshead and piston rod connecting thread. Further, the impact events triggered by crosshead displacement and rod load reversal events were identified to enhance the interpretability of the signal, thereby obtaining a loose-sensitive frequency band of 2–15 kHz and specific phase angle features. Next, the multi-band feature spectrum was formed using variational modal decomposition and data dimensionality reduction based on the Hilbert transform, which demonstrates satisfactory performance in the feature reservation as well as spectrum compression of acceleration signals in both the time and frequency domain. The proposed methodology was validated by experiments with various levels of thread loosening. The result indicated the multi-band feature spectrum feature was effective in quantitative loosening diagnosis with accurate and stable classification.

Intelligent Diagnosis Model of Working Conditions in Variable Torque Pumping Unit Wells Based on an Electric Power Diagram

Because of the problems, such as the lack of an electric power diagram atlas under different working conditions and the difficulty in intelligent diagnosis of variable torqued pumping unit wells, this paper proposes a diagnosis model of working conditions based on feature recognition. The mathematical relationship model between the polished rod load and motor output power is derived based on the analysis of geometric structure, motion law, and process of energy transformation and transfer of the variable torque pumping unit. It can calculate the electric power diagram based on a dynamometer card. On this basis, the electric power diagram atlas is created, and the feature analysis and eigenvalue extraction of the electric power diagrams under different working conditions are carried out to realize the direct diagnosis of the working conditions in the variable torque pumping unit wells. The application and analysis of examples show that the electric power diagram atlas created in this paper has good practicability, and the working condition diagnosis model accuracy is high. It can provide a theoretical basis and technical support for the intelligent diagnosis of oil production working conditions and improve the intellectual management level of the oilfield, which is conducive to reducing production management costs and improving the oilfield’s production efficiency and benefits.

Intelligent Method to Optimize the Frequency Modulation for Beam Pumping System Based on Deep Reinforcement Learning.

A mathematical simulation model of a beam pumping system with frequency conversion control is established, considering the influence of the real-time frequency variation on the motion law of a pumping unit, the longitudinal vibration of a sucker rod string, the crankshaft torque, and the motor power. On this basis, the key links such as state space, action space, and reward function are defined by using deep reinforcement learning theory, and an intelligent model to optimize the frequency modulation for a beam pumping system based on deep reinforcement learning is constructed. The simulation and field application results show that the frequency optimization model can significantly reduce the fluctuation amplitude of the polished rod load, crankshaft torque, motor power, and input power of the system, making the operation of the pumping system more stable and energy-saving. More importantly, the model can realize the independent learning and control of the corresponding parameters without manual intervention to ensure the normal operation of the system and improve the level of information and intelligent management of oil wells.

Effect of test configurations and loading protocols on performance of timber-concrete connectors

To examine the effect of test configurations and loading protocols on the performance of timber-concrete composite (TCC) shear connectors, a total of twenty-seven TCC shear connections with glued – in threaded steel rod (GIR) were designed to experience push-out tests. The experimental variables include rod diameter, test configurations (single - and double - shear), and loading protocols including the loading protocol (EN26891) and the displacement rate (0.5 mm/min, 2 mm/min, and 4 mm/min). The results indicate that both the test configurations and the displacement rates showed different influences on the performance of the shear connections. Most of the tested TCC shear connections with GIR mainly failed by the double – hinge yield mode of GIR. Double – shear specimens with 16 mm – diameter GIR exhibited a 49 % higher maximum load compared to the single – shear specimens. The slip modulus of the specimens tested at a displacement rate of 4 mm/min was about 40 % lower than that of the specimens tested at the displacement rates of 0.5 mm/min and 2 mm/min, respectively. Among the single-shear specimens, the 16 mm– diameter GIR showed the lowest ductility, by 65 % and 59 %, as compared to the 10 mm – and 12 mm – diameter specimens. Finally, theoretical analytical formulas were proposed to predict the load carrying capacity and the slip modulus of the TCC shear connections with GIR. The experimental slip modulus was also compared with the results obtained by existing calculation models.

Modeling the influence of rheology on smooth rod coating systems

Rod coating methods are of interest for the application of barrier coatings, especially at off-line facilities that may run at moderate speeds and narrow web widths. At lower line speeds and lower coating solids, it is difficult to achieve good coat weight control because of poor loading of the rod. While there is extensive literature available about blade and roll coating, there seems to be less reported on the rod loading of smooth rods to obtain various coat weights. Much of the work is around metering rods working on applicator rolls at high speeds that are associated with the metered size press, with a focus on ribbing instabilities. This work employs a simplified model, neglecting some complex features of rubber deformation and film split, to estimate the influence of the process parameters such as speed, rod diameter, viscosity, and rod loading on the coat weight obtained. As found in practice, at low speed and low viscosities, the coat weight-load curve is steep, leading to poor control of the coat weight and coat weight uniformity. If the viscosity is increased, the curve is modified, and control is possible with rod loading in a normal range. For shear thinning fluids described by the Carreau model, the power law index and other parameters need to be in the correct range to obtain the desired effect. Modeling predictions show a steeper dependence of coat weight with rod pressure when compared to pilot coater data. This may be caused by missing details in the mechanical loading of the rod related to tube pressure or from neglecting the impact of filter cake formation of the applied coating in the model.

Prediction of Particle Size Distribution of Mill Products Using Artificial Neural Networks

High energy consumption in size reduction operations is one of the most significant issues concerning the sustainability of raw material beneficiation. Thus, process optimization should be done to reduce energy consumption. This study aimed to investigate the applicability of artificial neural networks (ANNs) to predict the particle size distributions (PSDs) of mill products. PSD is one of the key sources of information after milling since it significantly affects the subsequent beneficiation processes. Thus, precise PSD prediction can contribute to process optimization and energy consumption reduction by avoiding over-grinding. In this study, coal particles (−2 mm) were ground with a rod mill under different conditions, and their PSDs were measured. The variables studied included volume% (vol.%) of feed (coal particle), vol.% rod load, and grinding time. Our supervised ANN models were developed to predict PSDs and trained by experimental data sets. The trained models were verified with the other experimental data sets. The results showed that the PSDs predicted by ANN fitted very well with the experimental data after the training. Root mean squared error (RMSE) was calculated for each milling condition, with results between 0.165 and 0.965. Also, the developed ANN models can predict the PSDs of ground products under different milling conditions (i.e., vol.% feed, vol.% rod load, and grinding time). The results confirmed the applicability of ANNs to predict PSD and, thus the potential contribution to reducing energy consumption by optimizing the grinding conditions.

Research on Seismic Wave Quality Factor of Marble Jointed Rock Mass under SHPB Impact

In order to quantitatively describe the energy dissipation law of jointed rock mass, we obtained the jointed cores in laboratory conditions using marble from the roof and floor of Jinchanghe Lead–zinc mine in Baoshan. The dissipative degree of stress wave in marble jointed rock mass is measured by introducing quality factor Qs parameter. Based on the experimental principle of Split Hopkinson Pressure rod loading device (SHPB), we proposed a three-wave energy method of incident wave, reflected wave and projected wave for calculating jointed rock samples’ quality factor Qs based on stress wave energy. Using the SHPB test system for multiple specimens taken from the same piece of rock mass shock compression experiment, the three groups of specimens under different loading conditions gained incident wave and reflected wave and transmission wave experimental data, using the method of stress wave energy to deal with stress wave data, and calculate the joint sample maximum storage energy, dissipation energy and Qs quality factors. The results show that: ① The non-destructive breaking time–history strain of Dali rock mass under impact load is obtained by SHPB dynamic test system; combined with the deformation energy and dissipation energy calculation principle of quality factor, six groups of Qs experimental values are obtained. Although the Qs experimental values are discrete, the overall deviation is small with an average of 43.07. ② AUTODYN-Code was used to simulate the damage and fracture characteristics of rock mass with different quality factors under explosive dynamic load. The results showed that the radius of rock mass compression shear damage area gradually increased with the increase in porosity, but it was not obvious.

Quadratic Zeeman effect in hydrogen at 2-3 MG magnetic fields.

The Zeeman effect is used for measurement of magnetic fields in astrophysical and laboratory plasmas. Magnetic fields in atmospheres of magnetic white dwarf stars are in the range 40 kG-1 GG. The quadratic Zeeman effect results in the additional split and shift of lines for magnetic fields >2 MG. Hydrogen Balmer lines were studied in magnetic fields delivered by a 1 MA pulse power generator. The magnetic field was generated by rod loads 0.8-1 mm in diameter. A droplet of CH oil on the load center was the source of hydrogen. A low ionized oil layer was backlit by blackbody emission from the rod with a temperature of 0.5-0.6 eV. Zeeman splitting of H-alpha and H-beta absorption lines were with a grating spectrometer. A spectral shift of the central component of the triplet indicated the quadratic Zeeman effect in hydrogen lines.

Dynamic analysis of the effect of mesh tension on the deployment process of loop antenna

In orbit deployment and profile maintenance are the most important functional requirements in the development of loop antenna If the antenna cannot be deployed in orbit, it will lose the signal transmission function, and the profile in orbit holding function is related to whether the antenna can stably transmit electromagnetic signals. The mesh tension (main mesh tension, rear mesh tension and tension arrays tension) is the key means to maintain the profile stability in orbit. At the same time, it is also closely related to the rod load and the maximum motor driving force in the process of antenna deployment. Based on the theory of flexible multi-body dynamics, the dynamic modeling of the deployment process of ten meter loop deployable antenna is established in this paper On this basis, the influence of mesh tension on the deployment dynamics of loop antenna is analyzed by using the control variable method, and its related variation law is obtained. This study can provide guidance for the tension adjustment in the profile adjustment stage of the ring antenna, so as to shorten the development cycle, and can also predict the deployment of the antenna in orbit.

Continuous Rod Load Monitoring to Assess Spinal Fusion Status-Pilot In Vivo Data in Sheep.

Background and Objectives: Spinal fusion is an effective and widely accepted intervention. However, complications such as non-unions and hardware failures are frequently observed. Radiologic imaging and physical examination are still the gold standards in the assessment of spinal fusion, despite multiple limitations including radiation exposure and subjective image interpretation. Furthermore, current diagnostic methods only allow fusion assessment at certain time points and require the patient’s presence at the hospital or medical practice. A recently introduced implantable sensor system for continuous and wireless implant load monitoring in trauma applications carries the potential to overcome these drawbacks, but transferability of the principle to the spine has not been demonstrated yet. Materials and Methods: The existing trauma sensor was modified for attachment to a standard pedicle-screw-rod system. Two lumbar segments (L2 to L4) of one Swiss white alpine sheep were asymmetrically instrumented. After facetectomy, three sensors were attached to the rods between each screw pair and activated for measurement. The sheep was euthanized 16 weeks postoperatively. After radiological assessment the spine was explanted and loaded in flexion-extension to determine the range of motion of the spinal segments. Sensor data were compared with mechanical test results and radiologic findings. Results: The sensors measured physiological rod loading autonomously over the observation period and delivered the data daily to bonded smartphones. At euthanasia the relative rod load dropped to 67% of the respective maximum value for the L23 segment and to 30% for the L34 segment. In agreement, the total range of motion of both operated segments was lower compared to an intact reference segment (L23: 0.57°; L34: 0.49°; intact L45: 4.17°). Radiologic assessment revealed fusion mass in the facet joint gaps and bilateral bridging bone around the joints at both operated segments. Conclusions: Observations of this single-case study confirm the basic ability of continuous rod load measurement to resolve the spinal fusion process as indicated by a declining rod load with progressing bone fusion. A strong clinical potential of such technology is eminent, but further data must be collected for final proof of principle.

Development of a variable-diameter threshing drum for rice combine harvester using MBD - DEM coupling simulation

According to different feeding rates, the threshing gap of rice combine harvester needs to be flexibly adjusted to prevent blockage. The research shows that the threshing performance of adjusting threshing gap by changing the drum diameter is better than that by changing the concave grid position, but there are few researches on the variable-diameter threshing drum. The objective of this paper was to specifically develop a variable-diameter threshing drum and a monitoring method for rice combine harvester to improve the threshing performance. The adjusting part of the variable-diameter threshing drum was consisted of two sets of the side and the middle adjustment mechanism, which were driven by hollow hydraulic cylinder. The three states (becoming larger, smaller and stationary) of drum diameter could be realized by the designed hydraulic actuating system. The mathematical model among the feeding rate, the threshing gap and the piston rod load force of hydraulic cylinder was deduced, and the MBD - DEM coupling simulation was carried out. Finally, a field experiment was carried out. As a result, the angle of guide rail was determined 30°. When the piston rod of hydraulic cylinder moved ±8.66 mm, the threshing gap would be adjusted ±5 mm. The field experiment showed that the feeding rate and the threshing gap had obvious influence on the piston rod load force, which was basically consistent with the results of the mathematical model and the coupling simulation. Therefore, the method of monitoring the piston rod load force is feasible and provides the basis for the research of an adaptive control system for combine harvester.

Cyclic Loading of Glued-In FRP Rods in Timber: Experimental and Analytical Study

The axial load capacity and stiffness of carbon fiber–reinforced polymer (CFRP) and glass fiber–reinforced polymer (GFRP) rods glued in timber is investigated under cyclic loading as the main design consideration for structures that experience load reversal (e.g., due to wind loading). Load cycles at 20%, 40%, 60%, and 80% of the ultimate load and three repetitions per load cycle were considered. The main parameters examined are the effect of FRP rod, anchorage length, and construction scenario. The construction scenarios represent full contact between timber faces, gaps in joints due to long-term effects (e.g., viscoelastic creep) and manufacturing tolerances, and contact with other materials. The GFRP rods exhibit 23% higher axial load capacity and 20% lower axial tensile stiffness than CFRP rods for an embedment length of 5D, where D = diameter of the rod. The axial load capacity of the GFRP rods tends to plateau with increasing bonded length at anchorage lengths greater than 10D. Small gaps significantly decrease the axial compressive stiffness of the glued-in FRP rods at the first load cycles and the axial stiffness varies along the bonded length. An analytical methodology is presented to describe the bond stress transfer mechanism and the progressive bond degradation. The analytical tensile slip values agree fairly well with the experimental results when debonding takes place at 80% of the ultimate load.

Electric Parameters Assist Rod-Pump Condition Diagnosis, Production Metering

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 204785, “Research and Application of Rod-Pump Working Condition Diagnosis and Virtual Production Metering Based on Electric Parameters,” by Ruidong Zhao, SPE, Cai Wang, and Hanjun Zhao, SPE, PetroChina, et al. The paper has not been peer reviewed. The conventional configurations of the Internet of Things (IoT) related to pumping wells include an electric parameter indicator and dynamometer. If working-condition diagnosis and virtual production metering of well pumping can be realized through electrical parameters, the need for dynamometers can be eliminated or reduced, with a potentially major effect on reducing investment and improving coverage of the IoT in oil wells. In the complete paper, an integrated multimodel diagnosis method is proposed. The diagnostic and virtual-production-metering method and software based on electrical parameters have been applied in many of the operator’s oil fields. Introduction In China, more than 90% of the more than 400,000 oil wells are sucker-rod-pump (SRP) wells. At present, with the popularity of IoT in the oil field, SRP wells have accumulated massive amounts of production and operation data such as polished rod load, displacement, and electric-motor-power parameters. The working performance diagnosis and production calculation for these wells mostly are based on dynamometer cards, whose IoT costs are relatively high and whose widespread applications are limited. In contrast, the acquisition of electric parameters is much cheaper and easier than is the case with dynamometer cards, but a lack of corresponding theories and efficient methods to make use of electric parameters persists. If a power curve can be transformed to a dynamometer card accurately in the same well working condition, well diagnosis and production calculation can be realized by the generated card. At present, few reports on transforming power curves to dynamometer cards exist. The approach to generate a dynamometer card from an electric power curve is to convert 1D timeseries data to 2D load and displacement-series data. Building the mathematical transformation model to generate cards from power curves is difficult because of uncertainties related to pumping units during working. Thus, transformation methods, by virtue of deep learning, seem more promising—specifically, transforming electric power to dynamometer cards by deep learning.

Analytic Solutions Help Predict Sucker-Rod-Pump Failure

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 200825, “Failure Prediction for SRP Using Analytic Solutions,” by Viorica Sirghii, SPE, Rudolf Konrad Fruhwirth, and Herbert Hofstaetter, University of Leoben, et al. The paper has not been peer reviewed. A method for prediction of sucker-rod-pump (SRP) failure based on improved, completely connected perceptron (ICCP) artificial neural networks (ANNs) is presented. Results are compared with historical wellbore data. The validity of the ANN model is proved to meet SRP failure prediction with a ±5% error, helping identify and prevent potential damage, reduce costs and risks, and optimize production. SRP Diagnosis To evaluate the performance of SRPs, dynamometer cards are used. The load on the top rod is measured and plotted in relation to the polished rod position as the pumping unit moves through each stroke cycle. The result is a surface card that illustrates the polished rod load vs. position (downhole diagnostics). To determine above-pump liquid accumulation, pump-filling efficiency, and displacement, the well’s producing and lifting efficiencies can be analyzed and quantified. Depending on the results, operational and equipment changes can be made to improve efficiency and production optimization. How the plunger picks up, holds, and releases the fluid load at each stroke can be seen in a dynamometer card’s shape. The most-common and most-harmful pump states are fluid pound, gas interference, and tagging. When the pump is not completely full, the rod string is damaged because of an excessive number of strokes.