Models and Estimators for Flow of Topside Drilling Fluid

The reduction of risk and non-productive time in oil drilling is a key research interest in the oil and gas industry. The early detection of kick and loss is a crucial part in safe well control operations, thus, it plays a major role in this regard. Early kick and loss detection is done by incorporating the available pressure data of the bottom side of the well with the available data at the surface on the topside. The data on the topside is mainly the return flow rate and the mud pit level. There are advanced flow measurement techniques available for the clean flow going into the well, which is comparatively easy to measure. On the contrary, the return flow consists of drill cuttings and gases which makes flow measurement difficult and inaccurate. Although there exist many flow meters that can measure the return flow rate, most of the on-shore and off-shore oil rigs still use conventional drilling systems. These conventional drilling processes use intermittent or online return flow rate and density measurements together with mud pit levels for kick and loss detection. There are various flow meters used in these processes, but most of the time paddle flow sensors are used. These have comparatively less accuracy as well as repeatability. In most of the conventional oil rigs, this is just an indicator rather than a realtime flowmeter, thus early kick and loss detection cannot be expected. Advances in flow metering technology will provide accurate differential flow measurements. Therefore, the development of cost-effective, accurate and online sensors for early kick and loss detection is vital. The development of an efficient model based real-time estimator of the flow rate of the return flow using an open Venturi channel is studied in this research work, such that it can be used as a return flowmeter for early kick detection in conventional drilling. Different mathematical models are investigated for this purpose, and a suitable numerical solver for the models are developed based on the orthogonal collocation for real-time implementation. The effect of different types of drilling fluids and different geometries of channels are studied. The flow rate and various parameters like the friction factors are estimated in real-time using different estimators. The models and estimators are tested against a well-known numerical scheme and verified using experimental results from a test flow loop. Further, the combination of two kick detection indicators, the return flow rate and the active mud pit level, are investigated in a modeling environment. For this, a combined model which includes both the bottomside and the topside of an oil well drilling process is developed and simulated to study the behavior of these indicators for different drilling operation scenarios. The model is able to show the bottomside pressure dynamics and the corresponding topside flow dynamics at once. This gives rise to a complete closed-loop model of an oil well drilling. The drilling fluid losses that can occur during the removal of drill cuttings using the solid removal equipment are estimated from these models. With the availability of real-time estimation of drill fluid losses at the top side, the replenishing of the lost mud could potentially be automated

Adaptive Moving Horizon Estimator for Return Flow Rate Estimation using Fluid Levels of a Venturi Channel

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

Modeling and Analysis of Fluid Flow through A Non-Prismatic Open Channel with Application to Drilling

his 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

Model based flow measurement using venturi flumes for return flow during drilling

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 expensive and has some downsides. For instance there is a risk of blockage due to drill cuttings while measuring the discharge. The presence of gas and cuttings in the drilling fluid will also have a negative effect in the measurement i.e. for multi-phase fluid, the readings from Coriolis meters may not be accurate. A cheaper alternative would be to use an open channel for the measurement of the discharge from the return flowline. In this paper, a venturi rig is used as the open channel and modeled by the Saint Venant equations. Experimental verification of the simulation results show a promising behavior of the model based measurement of the return fluid flow

Modeling and Analysis of Fluid Flow through A Non-Prismatic Open Channel with Application to Drilling

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

Modeling and Analysis of Fluid Flow through A Non-Prismatic Open Channel with Application to Drilling

his 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.publishedVersio

A Flexible Model for Benchmarking the Energy Usage of Automotive Lithium-Ion Battery Cell Manufacturing

The increasing use of electric vehicle batteries in the world has a significant impact on both society and the environment. Thus, there is a need for the availability of transparent information on resource allocation. Battery manufacturing process details in this regard are not available in academia or the public. The available energy data on manufacturing has a high variation. Furthermore, different process steps have different energy and material demands. A process model can benchmark the energy usage, provide detailed process data, and compare various cell productions which in turn can be used in life-cycle assessment studies to reduce the variation and provide directions for improvements. Therefore, a cell manufacturing model is developed for the calculation of energy and material demands for different battery types, plant capacities, and process steps. The model consists of the main process steps, machines, intermediate products and building service units. Furthermore, the results are validated using literature values. For a case study of a 2 GWh plant that produces prismatic NMC333 cells, the total energy requirement on a theoretical and optimal basis is suggested to be 44.6Whinproduction/Whcellcapacity. This energy consumption in producing batteries is dominated by electrode drying, and dry room. Energy usage for a variety of cell types for a similar plant capacity shows that the standard deviation in the results is low (47.23±13.03Wh/Wh)

Towards accurate state-of-charge (SoC) estimation in Lithium-ion batteries

Energy storage systems (ESSs) are critically important for the future of electric vehicles. Despite this, the safety and management of ESSs require improvement. Battery management systems (BMSs) are vital components in ESS systems for Lithium-ion batteries (LIBs). One parameter that is included in the BMS is the state-of-charge (SoC) of the battery. SoC has become an active research area in recent years for battery electric vehicle (BEV) LIBs, yet there are some challenges: the LIB configuration is nonlinear, making it hard to model correctly; it is difficult to assess internal environments of a LIB (and this can be different in laboratory conditions compared to real-world conditions); and these discrepancies can lead to raising the instability of the LIB. Therefore, further advancement is required in order to have higher accuracy in SoC estimation in BEV LIBs. SoC estimation is a key BMS feature, and precise modeling and state estimation will improve stable operation. This review discusses current methods use in BEV LIB SoC modelling and estimation. The review culminates in a brief discussion of challenges in BEV LIB SoC prediction analysis

Study of an Industrial Electrode Dryer of a Lithium-Ion Battery Manufacturing Plant: Dynamic Modelling

A dynamic model for lithium-ion battery (LIB) electrode manufacturing and drying is developed in this paper. The model is intended for analysis of different drying technologies, energy requirement calculations, and optimization and control of the drying process. The model shows that the infrared drying is faster than the convective drying when the heat source temperature is the same. The energy required to evaporate the solvent can be reduced by gradually changing the hot air temperature. Drying is the most energy-intensive process in cell manufacturing, and the cell manufacturing process is the biggest contributor to greenhouse gas emissions in the LIB industry. Therefore, the presented model is useful for accurate estimation of the environmental impact as well as for identifying the appropriate measures to reduce energy requirements in the rapidly growing LIB industry