Compressor Computerized Performance Monitoring System CPMS

Background information Natural gas liquid (NGL) production facilities, typically, utilize turbo-expander-brake compressor (TE) to generate cold for C2+ separation from the natural gas by isentropic expansion of feed stream and use energy absorbed by expansion to compress residue gas. Experience shows that during operational phase TE can exposed to operation outside of design window that may lead to machine integrity loss and consequent impact on production. At the same time, there is a lack of performance indicators that help operator to monitor operating window of the machine and proactively identify performance deterioration. For instance, TE brake compressor side is always equipped with anti-surge protection system, including surge deviation alarms and trip. However, there is often gap in monitoring deviation from stonewall region. At the same time, in some of the designs (2×50% machines) likelihood of running brake compressor in stonewall is high during one machine trip or train start-up, turndown operating modes. Also, typical compressor performance monitoring systems does not have enough dynamic parameters that may indicate machine process process performance deterioration proactively (real-time calculation of actual polytrophic efficiency, absorbed power etc.) and help operator to take action before catastrophic failure occurs. In addition, typical compressor monitoring systems are based on assumed composition and fixed compressibility factor and do not reflect actual compositions variations that may affect machine performance monitoring. To overcome issues highlighted above, Hawiyah NGL (HNGL) team has developed computerized monitoring and advisory system to monitor the performance of turbo-expander-brake compressor, proactively, identify potentially unsafe conditions or performance deterioration and advice operators on taking necessary actions to avoid unscheduled deferment of production. Computerized performance monitoring system has been implemented in HNGL DCS (Yokogawa) and utilized by control room operators on day-to-day basis. Real-time calculation, analysis and outputs produced by performance monitoring system allow operator to understand how current operating condition are far from danger zone. Proactive deviation alarms and guide messages produce by the system in case of deviation help operators to control machine from entering unsafe region. Actual polytrophic efficiency, adsorbed power calculations provide machine condition status and allow identifying long-term performance deterioration trends.

Comparison of Z-Factor Correlations Using a Large PVT Dataset with Emphasis on the GERG-2008 EOS

The gas compressibility factor is an important property in reservoir simulation studies. It is directly linked to the gas formation volume factor and the gas density thereby impacting wellhead injection pressure, reservoir voidage, injectivity, as well as the tendency for gas gravity override to occur in the reservoir. ADNOC's PVT database contains experiments on almost 2,000 samples, of which more than 100 have been subject to advanced gas injection experiments. Z-factor data have been compiled from the liberated gas during DV experiments as well as from CCE experiments on reservoir gases, injection gases, and swollen fluid mixtures. Several of these mixtures are very rich in H2S, whereas pressure and temperature are in the range of 14.7-14,500 psia and 80-365 °F, respectively. We test several different methods for predicting the Z-factor, such as the industry-standard Hall-Yarborough method, in combination with various models for pseudo-critical pressure and temperature and including correction for non-hydrocarbon components. Other methods tested include the GERG-2008 model, considered to be state-of-the-art for predicting physical properties for well-described gas mixtures, as well as the well-known Peng-Robinson cubic equation of state. Based on close to 10,000 data points in our database, the GERG-2008 model typically predicts the Z-factor to be within 2% of the measured value, which is on par with the experimental uncertainty. However, for some rich gas condensate mixtures, the model gives larger errors because its parameters are only tuned to compositions with components up to C10. This is to our knowledge the first time that the GERG-2008 EOS has been compared to standard Z-factor correlations for such a large number of data points. If compositional information is available, we recommend using either the GERG-2008 model or the Hall-Yarborough model with pseudo-critical properties provided by Kay (1936). When compositions are not available, we find that the Standing correlation is more accurate than the Sutton model, also for sour mixtures.

The role of the critical compressibility factor in the equation of state for the critical fluid

Based on the literature data of PVT measurements, the amplitudes of the equations of the critical isotherm D0(Zk), the critical isochore Г0(Zk), the phase boundaries В0(Zk) are expressed in terms of the critical factor of compressibility of the substance Zk=PkVk/RTk in the entire fluctuation region near the critical point. By doing so, a phenomenological method has been used for calculating the values of the critical exponents of the fluctuation theory of phase transitions based on the introduction of small parameters into the equations of the fluctuation theory. It has been shown that, within the limits of the PVT measurement errors, these dependences D0(Zk) and В0(Zk) on the compressibility factor are linear, and Г0 practically does not depend on the compressibility factor Zk. The relationship of these amplitudes with the amplitudes a and k of the linear model of the system of parametric scale equations of state of substance near the critical point has been established. It has been shown that the dependences k(Zk) and а(Zk) are also linear in the entire fluctuation region near the critical point. The obtained dependences k(Zk) and а(Zk) agree with the known relationship between the amplitudes of the critical isotherm D0(Zk), critical isochore Г0(Zk), phase boundaries В0(Zk) Aerospace Institute of the National Academy of Sciences of Ukrainewithin the framework of the system of parametric scaling equations. The relations а(Zk), k(Zk) make it possible, on the basis of a linear model of the system of parametric scale equations of state of substance, to determine such important characteristics of the critical fluid as the temperature and field dependences of the correlation length Rc(T,m) and the fluctuation part of the thermodynamic potential Ф(T,m) in the entire fluctuation region near the critical point. Then, based on the form of the fluctuation part of the thermodynamic potential Ф(T,m)~Rc(T,m)-3, the results obtained allow one to calculate the field and temperature dependences of the thermodynamic quantities for a wide class of molecular liquids in the close vicinity of the critical point (DP<10-3, Dr<10-2, t<10-4), where precision experiments are significantly complicated, and its can also be used when choosing the conditions for the most effective practical application of the unique properties of the critical fluid in the newest technologies.

How to Improve Accuracy of a Kick Tolerance Model by Considering the Effects of Kick Classification, Frictional Losses, Pore Pressure Profile, and Influx Temperature

Summary Kick tolerance (KT) calculation is essential for a cost-effective well design and safe drilling operations. While most exploration and production operators have a similar definition of KT, the calculation is not consistent because of different assumptions that are made and the computational power of KT calculators. Dynamic multiphase drilling simulators usually provide KT estimates with a minimum number of assumptions. They are much more accessible nowadays for use in predicting the behavior of multiphase flow in drilling and well control operations. However, as far as we observed, the simulation services are mainly used for complex and marginal wells in which low KT may impose additional casing strings, unconventional costly drilling practices, or a high risk of major well control events. Thus, companies often use simplified steady-state models for relatively uncomplicated wells through their own KT calculation worksheets. This practice is usually justified by the misconception that simplified models are always conservative and give less KT than actual conditions. In contrast, some simplifications may lead to higher operational risks due to an overestimated KT, depending on well conditions and parameters. The primary objective of this work was to perform a quality assurance/quality control on KT calculation practices in Company P. Later on, based on our findings, we determined some solutions to improve accuracy in the simplified KT worksheets commonly used by engineers across the company. This became a driver for generating a new KT worksheet (Company Model), in particular for situations in which engineers do not have access to a kick simulator. However, it should not mislead readers about the requirements of the simulator for complex and low-KTwells. Quality assurance/quality control and subsequent investigations found that there are some important criteria and parameters that affect KT calculations, but they are missing in many simplified models or ignored by engineers because they are unaware of or lack adequate references. After reviewing relevant academic literature, common practices and assessing several off-the-shelf software programs, we generated a computer program using Visual Basic for applications to address KT sensitivity to different parameters in steady-state conditions. The newly developed program is based on a single gas bubble model that applies the effect of annular frictional losses, influx temperature, gas compressibility factor, well trajectory, and bottomhole assembly (BHA). Moreover, the program differentiates between swabbing and underbalanced conditions. A logical test is applied to determine the type of kick before computing the relevant influx volume. This kick classification concept is ignored in many KT models; this is a common mistake that leads to misleading results. The annular pressure loss (APL) parameter is sometimes assumed to be zero in KT spreadsheets, while as an additional stress load on the wellbore, it affects the kick budget and must be considered.

An Investigation into the Volumetric Flow Rate Requirement of Hydrogen Transportation in Existing Natural Gas Pipelines and Its Safety Implications

As an alternative to the construction of new infrastructure, repurposing existing natural gas pipelines for hydrogen transportation has been identified as a low-cost strategy for substituting natural gas with hydrogen in the wake of the energy transition. In line with that, a 342 km, 36″ natural gas pipeline was used in this study to simulate some technical implications of delivering the same amount of energy with different blends of natural gas and hydrogen, and with 100% hydrogen. Preliminary findings from the study confirmed that a three-fold increase in volumetric flow rate would be required of hydrogen to deliver an equivalent amount of energy as natural gas. The effects of flowing hydrogen at this rate in an existing natural gas pipeline on two flow parameters (the compressibility factor and the velocity gradient) which are crucial to the safety of the pipeline were investigated. The compressibility factor behaviour revealed the presence of a wide range of values as the proportions of hydrogen and natural gas in the blends changed, signifying disparate flow behaviours and consequent varying flow challenges. The velocity profiles showed that hydrogen can be transported in natural gas pipelines via blending with natural gas by up to 40% of hydrogen in the blend without exceeding the erosional velocity limits of the pipeline. However, when the proportion of hydrogen reached 60%, the erosional velocity limit was reached at 290 km, so that beyond this distance, the pipeline would be subject to internal erosion. The use of compressor stations was shown to be effective in remedying this challenge. This study provides more insights into the volumetric and safety considerations of adopting existing natural gas pipelines for the transportation of hydrogen and blends of hydrogen and natural gas.

A Comprehensive Review of Recent Advances in the Estimation of Natural Gas Compressibility Factor

Accurate prediction of gas compressibility factor is essential for the evaluation of gas reserves, custody transfer and design of surface equipment. Gas compressibility factor (Z) also known as gas deviation factor can be evaluated by experimental measurement, equation of state and empirical correlation. However, these methods have been known to be expensive, complex and of limited accuracy owing to the varying operating conditions and the presence of non-hydrocarbon components in the gas stream. Recently, newer correlations with extensive application over wider range of operating conditions and crude mixtures have been developed. Also, artificial intelligence is now being deployed in the evaluation of gas compressibility factor. There is therefore a need for a holistic understanding of gas compressibility factor vis-a-vis the cause-effect relations of deviation. This paper presents a critical review of current understanding and recent efforts in the estimation of gas deviation factor.

Adumbrative Heterodox Dictum of Wellbore Aggregates From Sapient Recovery Factor Penchants For Honed Field Praxis

Puissant field planning is increasingly becoming a sophisticated quandary with less emphasis on parametric synergy with reservoir spasmodic acuity. This conundrum leads to inaccurate harbinger of the required number of wells to be drilled for future field development programs from existing production and reservoir data particularly at pressures above the bubble point which is a major sobriety as orchestrated in most recent simulators. The aim of this erudition is to compendiously carry out astute predictive heterodox principles of wellbore aggregates from critical recovery factor parameters for savvy field planning. The main objectives are to glean and develop new propinquities for differential pressures (ΔP), rock compressibilities (Co) and oil formation volume factors (Bo) for predicting the number of wells to be drilled and recovery factors (RF) by equating the simulated results and the theoretical model (Ezekwe, 2010). To elucidate, metaphorize and ruminate new models. Reservoir and economic data was carefully simulated using FAST-FEKETE Evolution software for initial 40 future oil wells. Average results were mathematically correlated with recovery factor model to produce new correlations to quickly re-jig field planning efficiency. Results of matched and validated compressibility factors, differential reservoir pressures and oil formation volume factors were correlated with field data from Ezekwe (2011) model. Results of compressibility factor showed increasing similar 3rd order polynomial converging correlation for both models but gave slight divergence with increasing number of wells and RF. Results of differential pressures gave linearly increasing correlation with number of wells and RF while the new model had a cross-over point at 6435.64 psi for 2 wells but slightly increased divergently with number of wells and RF. Results of oil FVF gave a good similar regression (R2) of 0.999 while both models showed decreasing 3rd order polynomial correlation comparison with number of wells but with slight divergent disparity with increased RF. To further validate the potency of this study, detailed comprehensive paired sample test gave standard deviation, standard error of mean and degree of freedom of 0.00356, 0.0012 and 8 for compressibility factors; 324.7, 102.68 and 9 for differential pressure while the oil formation volume factor gave 0.0067, 0.0021 and 9. The predictions obtained by the new model showed appreciable degree of consistency and accuracy with number of wells and RF. This is perhaps largely hinged on the capacity to cogently infuse field data with theoretical and simulated models effectively. This study has clearly shown that no special technique or rigorous computational procedures is required to plan future number of wells to be drilled in a field or perhaps estimate the required RF. Sequel to this, further research is encouraged to inculcate more correlations based on comprehensive field validation studies to improve the efficacy of this model.

COMPARATIVE STUDY OF EMPIRICAL CORRELATIONS AND EQUATIONS OF STATE EFFECTIVENESS FOR COMPRESSIBILITY FACTOR OF NATURAL GAS DETERMINATION

Introduction: Today, there are four main groups of methods for calculating the compressibility factor of natural gas: experimental measurements, equations of state, empirical correlations, modern methods based on genetic algorithms, neural networks, atomistic modeling (Monte Carlo method and molecular dynamics). A correctly chosen method can improve the accuracy of calculating gas reserves and predicting its production and processing. Aim: To find the optimal methods for calculating the z-factor following the characteristic thermobaric conditions. Methods: To determine the best method for calculating the compressibility factor, the effectiveness of using various empirical correlations and equations of state to predict the compressibility factor of hydrocarbon systems (reservoir gases and separation gases) of various compositions were evaluated by comparing numerical results with experimental data. Results and Discussion: Based on 824 experimental values of the compressibility factor for 235 various gas mixtures in the pressure range from 0.1 to 94 MPa and temperatures from 273 to 437 K, the optimal equation of state and empirical correlation dependence for accurate z-factor prediction was found. It is shown that for all gas mixtures the Peng-Robinson equation of state with the shift parameter and Brusilovsky equation of state allow achieving best results. For these methods, the average absolute relative error does not exceed 2%. Among the correlation dependences, the best results are shown by the Sanjari and Nemati Lay; Heidaryan, Moghadasi and Rahimi correlations with an error not exceeding 3%. Conclusions: It was found that for the proposed methods, the reduced pressure has a more significant effect on the accuracy of the calculated values than the reduced temperature. It is shown that when studying acid gas mixtures with a carbon dioxide content of more than 10%, the equations of state better describe the phase behavior of the system in comparison with empirical correlations.