Smart Well technology has seen rapid evolution in the last decade because of technological advancements. Proper knowledge of this technology, with some risk mitigating techniques, makes several benefits to an oil company including the capability of drilling longer horizontal and extended reach wells, particularly snake wells with great reduction in cleanup, reservoir management and water and gas breakthrough concerns. Even in some cases unexpected benefits have been discovered from this technology. Sensors are considered to be the heart of smart well completion. There are different types of sensors in the oil industry including wellbore internal sensors and casing external sensors. Some of these sensors are used for wellbore measurement and some for imaging the distribution of reservoir attributes away from the well. In this paper we will investigate all types of sensors either developed sensors and emerging sensors to measure pressure, temperature, flow Rate, noise, phase composition, pH, water cut, gas fraction and capacitance. However commonly used ones are P, T and flow rate sensors. Others are still emerging technologies. It is possible to use permanent sensors named pressure, resistivity, acoustic on outside wall of the casing as well to estimate permeability, porosity, saturation and monitor near wellbore water / flood front encroachment. Although Smart Well technology has shown several benefits but it possesses some challenges regarding their reliability and cost effectiveness and implementation phases. As a result, many companies tend to apply this technology with caution knowing that the cost of a smart completion can easily be three to four times more than a conventional completion. In this paper we present a comprehensive review of state-of-the-art Smart Well technology including all benefits, different types of sensors, challenges, economic consideration and application in fractured reservoir.
Simulating automated action of smart well components represents a challenge in forecasting performance of such wells, which is fundamental in their design decisions . For example, wells equipped with Inflow Control Valves (ICV) where zones have to be switched on, off or partially closed based on their performance relative to the rest of the wells/completions in the field which share the same surface network and facilities constraints.In this paper we present a study that has been carried out to justify installation of a surface controlled ICV in a group of wells in an off-shore Australian field with commingled production. The merit of surface controlled ICV versus uncontrolled commingled production has been compared. A numerical reservoir simulator has been used to model reservoir performance and production from individual zones. Also, well and production network has been simulated using a well and Production Network Flow Simulators. An interface "simulation manager" is used to facilitate information exchange between the two simulation programs and optimization of the process. Proper control of ICVs is simulated based on reservoir and well-bore simulation data which will result in maximum oil production of field network system resulting in higher recovery. Also, we have done typical economic analysis for smart well completion implementation. The results show that smart completion is viable for this field.
Simulating the automated action of smart well components represents a challenge in forecasting performance of such wells, and is fundamental to design decisions. Examples are wells equipped with inflow control valves (ICV), where zones have to be switched on, off or partially closed based on their performance relative to the rest of the wells/completions in the field, and where they share the same surface network and facilities constraints. This paper presents a study that has been carried out to justify installation of a surface controlled ICV in a group of wells in an offshore Australian field with commingled production. The merit of surface-controlled ICV versus uncontrolled commingled production has been compared. A numerical reservoir simulator program has been used to model reservoir performance and production from individual zones. Also, the wells and production network have been simulated using well flow simulator and a production network simulation software respectively. A simulation manager software is used to facilitate information exchange between the two simulation programs (production network and reservoir) and optimisation of the process. Proper control of ICVs is simulated based on reservoir and wellbore simulation data, which will result in maximum oil production of a field network system resulting in higher recovery. Also, we have done economic analysis for smart well completion implementation. The results of two aforementioned analyses (simulation study and economics) show that smart completion is viable for this field.
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