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Results
Abstract Inflow profiling has proved to be a major application of Distributed Temperature Sensor (DTS) systems. The real-time, downhole temperature data is analyzed by matching the measurements with values predicted by a well thermal model; reducing the uncertainty in the well's production parameters (e.g. permeability, water cut). The accuracy of the resulting inflow profile depends heavily on the accuracy of the temperature prediction model. Existing wellbore fluid temperature models were developed for conventional wells. This paper focuses on the modification of these temperature models for application to intelligent completions equipped with DTS & Inflow Control Valves. A published temperature prediction model was modified to analyze an intelligent well's geometry i.e. distributed inflow into an annulus, fluid mixing at multiple points etc. The new model was used to demonstrate the effect of water production in an oil and water production environment on the valve's mixing temperature and the tubing's temperature profile. Our results show that the temperature profile and the mixing valve temperature are over-estimated by current models that represent the inflow of each zone of a multizone I-Wells by a single inflow point. As expected, increasing the number of inflow points within each zone reduces this discrepancy. This over-estimation reduces the accuracy of inflow profile analysis calculated from the DTS data. Changes in valve temperature in single phase production in a multi-zone intelligent well can be used to indicate the fraction of the zone that is main contributor to zonal inflow e.g. a higher temperature indicates the lower portion on the pay zone is the main contributor and vice versa. A sensitivity study showed that the valve temperatures experience a unique profile depending on which zone is producing water. Introduction The geometrical complexities of an intelligent completion complicate the analysis of the temperature profile behavior across the completion interval. This paper investigates how the different flow paths should be modeled and discusses the resulting impact of the new model on the in the wellbore's predicted temperature profile. This new solution extends the enthalpy/energy balance temperature prediction model developed by Hasan & Kabir [1] for a conventional well to make it applicable to steady-state modeling of intelligent completions. The model extension is based on altering the initial and the boundary conditions that represent the intelligent well's completion. The annulus, and its static fluid, plays an important role in the transfer of heat from the tubing to the surrounding formation. The description of annular heat transfer is even more important when annular flow occurs, as is the case for an intelligent well. The natural, convection heat transfer process (caused by density variations in the annulus) changes to forced convection within the flowing fluid. Forced convection can either increase or decrease the heat transfer rate from the tubing to the formation; depending on the type of flow (turbulent or laminar) and the fluid's thermo-physical properties. Understanding the added complexities of the intelligent well has implications when DTS or any other temperature sensor data is being interpreted for the detection of fluid/flow anomalies or when the DTS data is being is matched with the modeled wellbore temperature for zonal flow allocation. Accounting for the various flow scenarios encountered in intelligent completions can help the engineer avoid misinterpretation of the available data. The cooler annulus fluid also directly influences the temperature profile by mixing with the warmer, produced tubing fluid at the ICV. The effect of the annulus has been studied before from the point of view of conventional wells. However, an intelligent completion offers a different scenario due to the varying inflow profile. Conventional well temperature modeling assumes that the inflow enters the well at a single point at the bottom of the completion. An intelligent completion is different, the inflow zone of the perforated interval or open-hole may have a length of many hundreds or even thousands feet.
- Research Report > New Finding (1.00)
- Overview > Innovation (0.74)
Abstract Value addition via real-time reservoir monitoring and optimisation is one of the main drivers for the increasing implementation of intelligent (I-)well completions. The benefits from these more expensive completions will be realized through increased reserves generated by increased drainage efficiency and reduction in well numbers and intervention frequency. A more rigorous exploitation of the real time production data is necessary to fully achieve this objective. We previously showed that water influx time and source could be detected in horizontal wells in real time 1. Extension of this technique will be shown to allow confident detection of water influx in vertical or deviated, multi-zone and/or multi-lateral I-well completions. The source of water influx into the well and the zonal fluid contribution will be quantified, allowing this unwanted fluid's production to be reduced. Knowledge of the influx time and source permits both production optimisation and improved reservoir sweep efficiency; processes that increase the well's productive life and reserves. It will be demonstrated that monitoring of the pressure drop, called dP trending in this paper, across multiple pressure sensors correctly located within a multi-zone vertical or deviated I-completion can identify the time and location of the water influx into the well. We will discuss the necessary conditions to ensure clear identification of these parameters. The concept of "Normalised Pressure Drop Signatures" will be introduced. It has proven to be particularly valuable for water influx detection and zonal flow rate monitoring purposes. The concept will be tested with data generated from a synthetic model of a 4-zone, deviated, I-well completion and with realfield data from an instrumented North Sea well. Introduction Reservoir Management includes the tasks of monitoring subsurface and surface data in order to control a fluid flood front's movement within a reservoir to maximize reserves and reduce production risks 2. The installation of advanced, complex completions has added a further dimension to the Reservoir Management process. Such I-completions provide the platform for real-time reservoir monitoring and reservoir control via both active 3 and proactive 4 management of the influx of unwanted fluids. Early water or gas breakthrough due to uneven fluid-front advance towards the well is observed in the higher permeability zones of heterogeneous and layered reservoirs. The need to reduce a well's excessive gas production includes the maintenance of the reservoir energy and the avoidance of exceeding the gas disposal capacity. The consequences of excessive water influx include 1, 2:Reduced well outflow performance as the increasing required tubing intake requirement reduces the well's outflow performance. Reduced well productivity index due to early onset of multiphase flow in the reservoir; Early installation of artificial lift, resulting in increased Capital and Operating Expenditure; Production problems with their associated increased well and surface facility costs from corrosion, scale formation, sand management issues, etc.; Environmental issues from the need to dispose of unnecessarily large, produced water volumes; Reduced well productive life and reserves.
- North America > United States (0.46)
- Europe > United Kingdom > North Sea (0.24)
- Europe > Norway > North Sea (0.24)
- (2 more...)