MPD and use of the AUSMV model to simulate and analyze propagation of pressure pulses.

Master's thesis in Petroleum engineeringOffshore drilling is one of our era’s most challenging operations in the petroleum industry. Conventional drilling methods face difficulty in certain prospects, such as drilling in deep water reservoirs and depleted offshore reservoirs. This is due to the narrow drilling window present in these types of reservoirs. There is a small margin between the pore pressure gradient and the fracture gradient which causes difficulty to drill with conventional methods. Managed pressure drilling (MPD) has emerged as a solution to many of the conventional drilling problems like kick scenarios, lost circulation, stuck pipe problems and drilling in depleted reservoirs. MPD provides us with precise control in these narrow margin wells by allowing drilling close to the pore-pressure gradient. The conventional drilling problems are either reduced or eliminated completely by using MPD technology. Most of MPD is executed by drilling in a closed well loop utilizing a Rotating Control Device (RCD) with a minimum of one drill string Non-Return Valve, and a Drilling Choke Manifold. The choke can be controlled manually or automatically. In today’s world the most common type is the automatic choke regulation. It requires PID controllers as a regulation technique, this is based on the difference between measured pressure vs required pressure. In addition to that, the automation process is supported by hydraulic simulator models. Wellbore control is very precise in MPD, assuming that the wellbore is sealed and able to contain the pressure. If this is the case, it is then possible to monitor the pressure throughout the wellbore in real time at the surface. Pressure changes are seen immediately in a closed system. MPD offers more precise control of the annular wellbore pressure profiles; hence influxes and losses are detected immediately. Safety of personnel and equipment during drilling is improved. Drilling economics is improved in MPD due to the reduction of drilling mud costs and reduction in non-productive time. The Drift Flux model is used in the petroleum industry among other things to evaluate transient flow responses of drilling operations. It has its roots in the laws of conservation for two phase flow, and its goal is to describe the characteristics of flow in pipes or wells. The AUSMV (Advection Upstream Splitting Method) scheme is a hybrid flux-vector splitting scheme. The AUSMV scheme is used in this thesis to simulate different scenarios concerning propagation of pressure pulses in a well. In the simulations we studied the pressure pulse propagation caused by pump start up and choke valve adjustments. It was demonstrated what effect friction has on the pulses and if the differences between having a one-phase and two-phase flow system. In the latter case, we also show how the gas volume content in the well affects the propagation velocities. Pressure pulse propagation caused by pump start up and choke valve adjustments is studied in the simulations with the help of the AUSMV scheme. Studying the propagation of pressure pulses generated by adjusting the choke, is of importance in MPD because situations arise where we have to increase the choke pressure to avoid kick. In a MPD system, presence of gas might easily occur since the system is designed for taking small gas kicks while drilling. Hence, in a long extended reach well, this is maybe an effect that one has to consider when working with an automated choke regulation system. After a given choke adjustment, one must give the well time to respond before an additional choke adjustment is introduced. The results of the simulations show that the sonic velocity depends both on gas fraction and pressure. If we operate with gas in a well, typically we find that the sonic velocity is reduced most at the top of the well. As the pressure increases with well depth, the sonic wave propagation velocity increases. Therefore, if we adjust the choke by making fast updates based on frequent measurements in long wells, there is a possibility that this “time lag” is a factor which must be taken into account. This will particularly apply to underbalanced drilling systems where we know there will be significant volumes of gas in the well

Using ensembles for accurate modelling of manufacturing processes in an IoT data-acquisition solution

The development of complex real-time platforms for the Internet of Things (IoT) opens up a promising future for the diagnosis and the optimization of machining processes. Many issues have still to be solved before IoT platforms can be profitable for small workshops with very flexible workloads and workflows. The main obstacles refer to sensor implementation, IoT architecture, and data processing, and analysis. In this research, the use of different machine-learning techniques is proposed, for the extraction of different information from an IoT platform connected to a machining center, working under real industrial conditions in a workshop. The aim is to evaluate which algorithmic technique might be the best to build accurate prediction models for one of the main demands of workshops: the optimization of machining processes. This evaluation, completed under real industrial conditions, includes very limited information on the machining workload of the machining center and unbalanced datasets. The strategy is validated for the classification of the state of a machining center, its working mode, and the prediction of the thermal evolution of the main machine-tool motors: the axis motors and the milling head motor. The results show the superiority of the ensembles for both classification problems under analysis and all four regression problems. In particular, Rotation Forest-based ensembles turned out to have the best performance in the experiments for all the metrics under study. The models are accurate enough to provide useful conclusions applicable to current industrial practice, such as improvements in machine programming to avoid cutting conditions that might greatly reduce tool lifetime and damage machine components.Projects TIN2015-67534-P (MINECO/FEDER, UE) of the Ministerio de Economía Competitividad of the Spanish Government and projects CCTT1/17/BU/0003 and BU085P17 (JCyL/FEDER, UE) of the Junta de Castilla y León, all of them co-financed through European-Union FEDER funds

Towards Self-Adaptive Discrete Event Simulation (SADES)

Systems that benefit from the ongoing use of simulation, often require considerable input by the modeller(s) to update and maintain the models. This paper proposes automating the evolution of the modelling process for discrete event simulation (DES) and therefore limiting the majority of the human modeller’s input to the development of the model. This mode of practice could be named Self-Adaptive Discrete Event Simulation (SADES). The research is driven from ideas emerging from simulation model reuse, automations in the modelling process, real time simulation, dynamic data driven application systems, autonomic computing and self-adaptive software systems. This paper explores some of the areas that could inform the development of SADES and proposes a modified version of the MAPE-K feedback control loop as a potential process. The expected outcome from developing SADES would be a simulation environment that is self-managing and more responsive to the analytical needs of real systems

Path optimization advisory and analytical tools for directional drilling

In directional drilling, well positioning and drilling instructions are planned based on human experiences and may require excessive computation and drilling times. Directional drilling process nowadays lacks optimization and automation to improve performance and efficiency. A path optimization advisor is developed with novel cost analysis, to support real-time directional drilling decisions. Spline in tension is used to simulated drilling path in the path optimization algorithms; more accurate and convenient for optimization purposes than commonly used survey calculation methods. The best valued path is solved using multi-loop optimization process, by determining the path with the lowest accumulated cost. Costs specified for each section are formulated and transformed into equal units. Actual drilling instruction is fitted to the optimal path with consideration of motor tendency and capabilities. The advisor developed using Matlab is validated that such a system can be used in real time directional drilling environments, to provide suggestions. Test cases using simulated drilling situation and historical data are tested for resulting instruction validation. Produced instruction and path results proved to be realistic and optimized based on specified cost functions. Comparing the optimized path with actual drilling instruction and survey drilled in historical cases, plan suggested by the path optimization advisor provides a better valued correction path.Petroleum and Geosystems Engineerin

An efficient model of drillstring dynamics

This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.jsv.2015.06.033High amplitude vibration regimes can cause significant damage to oilwell drillstrings: torsional stick-slip oscillation, forward whirl and backward whirl are each associated with different kinds of damage. There is a need for models of drillstring dynamics that can predict this variety of phenomena that are: efficient enough to carry out parametric studies; simple enough to provide insight into the underlying physics, and which retain sufficient detail to correlate to real drillstrings. The modelling strategy presented in this paper attempts to balance these requirements. It includes the dynamics of the full length of the drillstring over a wide bandwidth but assumes that the main nonlinear effects are due to spatially localised regions of strong nonlinearity, for example at the drillbit cutting interface and at stabilisers where the borehole wall clearance is smallest. The equations of motion can be formed in terms of this reduced set of degrees of freedom, coupled to the nonlinear contact laws and solved by time-domain integration. Two implementations of this approach are presented, using (1) digital filters and (2) a Finite Element model to describe the linear dynamics. Choosing a sampling period that is less than the group delay between nonlinear degrees of freedom results in a decoupled set of equations that can be solved very efficiently. Several cases are presented which demonstrate a variety of phenomena, including stick-slip oscillation; forward whirl and backward whirl. Parametric studies are shown which reveal the conditions which lead to high amplitude vibration regimes, and an analytic regime boundary is derived for torsional stick-slip oscillation. The digital filter and Finite Element models are shown to be in good agreement and are similarly computationally efficient. The digital filter approach has the advantage of more intuitive interpretation, while the Finite Element model is more readily implemented using existing software packages.The authors are grateful to industrial support and permission to publish this work, and would like to thank Prof Jim Woodhouse for technical contributions, and Dr Louis Kovalevski for assistance with the Finite Element model