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In an oil well drilling operation, a proper knowledge of the return fluid flowrate is necessary both for the stabilization of the bottom hole pressure of the well and also as a primary indication of a kick or loss. In practice, the drill fluid flowing through the return line is usually measured with Coriolis meters. However this method is both expe...
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... the top side, the mud is filtered and stored in tanks (mud pits) be- fore being pumped into the well again. Figure 1 shows a simplified schematic for such a system. The mud circulation has multiple purposes, the two most impor- tant being to retrieve the cuttings from the bottom of the well and to exert hydrostatic pressure against the walls of the well to prevent fluids from flowing into the well ( Bourgoyne et al., 1986). ...
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... oil industries, the measurement of the flow coming from the choke valve i.e. the drain back flow is measured directly using Coriolis meters. Figure 1 shows one type of installation using a Cori- olis meter but there are multiple variants. However, this type of equipment is both expensive and presents many challenges. ...
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... estimation or calculation of the discharge through the venturi flume using the mean of 16 sets of measurements of around 200 samples each for 8 dif- ferent discharges (two sets for each) is shown in Figure 10. In addition, the readings from the Coriolis meter is also plotted. ...
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... is worth mentioning that the Coriolis meter readings have not been used for the calculation or estimation of the discharge and are simply shown for reference. Figure 11 shows the estimation of the fluid flow rate through the channel from a single measurement set without any changes in the flow i.e. at the steady state. Here also the readings from the Coriolis meter is plot- ted as a reference value. ...
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... also the readings from the Coriolis meter is plot- ted as a reference value. Figure 12 shows the estimation of the fluid flow rate through the channel for two step changes in the fluid flow i.e. during transients. The delay caused by the moving average filter with 60 samples is shown in Fig- ure 12(a) and with 180 samples in Figure 12( Figure 12: Flow estimation after a step change filter introduces a larger delay in the estimation of the discharge despite the filtered signals being more smoother. ...
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... 12 shows the estimation of the fluid flow rate through the channel for two step changes in the fluid flow i.e. during transients. The delay caused by the moving average filter with 60 samples is shown in Fig- ure 12(a) and with 180 samples in Figure 12( Figure 12: Flow estimation after a step change filter introduces a larger delay in the estimation of the discharge despite the filtered signals being more smoother. ...
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... 12 shows the estimation of the fluid flow rate through the channel for two step changes in the fluid flow i.e. during transients. The delay caused by the moving average filter with 60 samples is shown in Fig- ure 12(a) and with 180 samples in Figure 12( Figure 12: Flow estimation after a step change filter introduces a larger delay in the estimation of the discharge despite the filtered signals being more smoother. ...
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... 12 shows the estimation of the fluid flow rate through the channel for two step changes in the fluid flow i.e. during transients. The delay caused by the moving average filter with 60 samples is shown in Fig- ure 12(a) and with 180 samples in Figure 12( Figure 12: Flow estimation after a step change filter introduces a larger delay in the estimation of the discharge despite the filtered signals being more smoother. ...
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... These equations use one level measurement from the channel and are developed for steady flows for specific geometrical channels. For nonprismatic channels, especially for Venturi channels, a steady flow equation based on the Bernoulli principle can be derived for two level measurements with several empirical coefficients that need to be tuned (Pirir et al., 2017;Chhantyal, 2018). Flume equations based on one level measurement and empirical coefficients developed for specific Venturi flumes that are designed according to the ISO 4359:2013 standards are available (International Organization for Standardization [ISO], 2013;Basu, 2019;Chhantyal, 2018;Baker, 2016). ...
... There are many numerical methods of high precision for solving the shallow water equations, but these usually take a considerable amount of computational time, which makes them not suitable for realtime applications. A model reduction method to calculate the fluid flow using these models with an application to oil well drilling process has been studied earlier (Jinasena et al., , 2017. These reduced order models have also been used for real-time estimation using various estimation methods . ...
... For this study, two collocation points are used for simplicity. The model reduction method is described in detail in (Jinasena et al., , 2017. ...
Real-time estimation of the return drilling fluid during oil well drilling is investigated in this study. Online fluid level measurements from a Venturi channel which can be placed on the return flowline is used with a model-based estimator. A reduced order, 1-D, mathematical equation is used for the open flow in the Venturi channel for Newtonian or non-Newtonian fluid types. The volumetric fluid flow rate is estimated using a moving horizon estimator in real-time. The friction factor is also estimated together with the fluid flow rate. The effect of the variation of the channel slope on the flow rate estimation induced by the vibration of the channel during its operation is also studied. The method requires only two level measurements in the Venturi channel together with the channel geometry. The method is validated using a laboratory scale Venturi flow system. The proposed method shows promising potential to be used as a real-time return flow rate measurement in conventional drilling systems.
... However, the return flow rate is quite difficult to measure because it contains the drill cuttings as well as dissolved gas. A novel approach of using a Venturi rig for this purpose is proposed in previous studies done by Pirir et al. (2017); Jinasena et al. (2017); Chhantyal et al. (2016). This is a low cost and an easy to maintain solution. ...
This paper presents the development and validation of a simplified dynamic model of a Venturi channel. The existing dynamic models on open channels are based on the open channel flow principles, which are the shallow water equations. Although there are analytical solutions available for steady state analysis, the numerical solution of these partial differential equations is challenging for dynamic flow conditions. There are many complete and detailed models and numerical methods available for open channel flows, however, these are usually computationally heavy. Hence they are not suitable for online monitoring and control applications, where fast estimations are needed. The orthogonal collocation method could be used to reduce the order of the model and could lead to simple solutions. The orthogonal collocation method has been used in many chemical engineering applications. Further, this has been used in prismatic open channel flow problems for control purposes, but no literature is published about its use for non-prismatic channels as per the author's knowledge. The models for non-prismatic channels have more non-linearity which is interesting to study. Therefore, the possibility of using the collocation method for determining the dynamic flow rate of a non-prismatic open channel using the fluid level measurements is investigated in this paper. The reduced order model is validated by comparing the simulated test case results with a well-developed numerical scheme. Further, a Bayesian sensitivity analysis is discussed to see the effect of parameters on the output flow rate.
