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Distributed acoustic sensing (DAS) technology is implemented to monitor downhole audible sounds for fracture diagnosis, leak detection and other applications. While DAS systems have the potential to enhance downhole flow monitoring, its use is currently limited to qualitative interpretation. Future applications of DAS such as distributed flow prediction require quantitative interpretation to determine flow rate, possibly of multiple phases, from acoustic data. In this paper we use signal processing techniques to determine flow rates from a simulated fractured well. Production into a 5 ½-inch well is simulated by injecting fluid into a fracture. The fracture was originally simulated with a piece of pipe filled with proppant, and then we used a pair of proppant-filled parallel plates with dimensions of 0.2 inch wide, eight inch high, and sixteen inch long, to represent a fracture. Liquid and gas were injected at varying rates into the fracture and into the well. The noise from production was recorded with a hydrophone within the wellbore. Through signal processing, the sound signal collected is transformed into the Fourier domain for insight into the sound spectrum. Experimental results show that frequency and sound intensity varies with the flow condition. The acoustic signal is sensitive to the flow rate and the type of fluid. The peak frequency indicates the phase of the fluid and its magnitude indicates the flow rate. The frequencies for gas production are in a range distinct from those for liquid production and the sound levels are related to the flow rate for both fluids. Experimental results also show that fracture geometry has an effect on the sound that is generated and sound from production can be used to identify fractures with restricted widths.
Distributed acoustic sensing (DAS) technology is implemented to monitor downhole audible sounds for fracture diagnosis, leak detection and other applications. While DAS systems have the potential to enhance downhole flow monitoring, its use is currently limited to qualitative interpretation. Future applications of DAS such as distributed flow prediction require quantitative interpretation to determine flow rate, possibly of multiple phases, from acoustic data. In this paper we use signal processing techniques to determine flow rates from a simulated fractured well. Production into a 5 ½-inch well is simulated by injecting fluid into a fracture. The fracture was originally simulated with a piece of pipe filled with proppant, and then we used a pair of proppant-filled parallel plates with dimensions of 0.2 inch wide, eight inch high, and sixteen inch long, to represent a fracture. Liquid and gas were injected at varying rates into the fracture and into the well. The noise from production was recorded with a hydrophone within the wellbore. Through signal processing, the sound signal collected is transformed into the Fourier domain for insight into the sound spectrum. Experimental results show that frequency and sound intensity varies with the flow condition. The acoustic signal is sensitive to the flow rate and the type of fluid. The peak frequency indicates the phase of the fluid and its magnitude indicates the flow rate. The frequencies for gas production are in a range distinct from those for liquid production and the sound levels are related to the flow rate for both fluids. Experimental results also show that fracture geometry has an effect on the sound that is generated and sound from production can be used to identify fractures with restricted widths.
In the past decade, Fiber-Optic (FO) based sensing has opened up opportunities for in-well reservoir surveillance in the oil and gas industry. Distributed Temperature Sensing (DTS) has been used in applications such as steam front monitoring in thermal EOR and injection conformance monitoring in waterflood projects using (improved) warmback analysis and FO based pressure gauges are deployed commonly. In recent years 1 significant progress has also been made to mature other, new FO based surveillance methods such as the application of Distributed Strain Sensing (DSS) for monitoring reservoir compaction and well deformation, multidrop Distributed Pressure Sensing (DPS) for fluid level determination, and Distributed Acoustic Sensing (DAS) for geophysical and production/injection profiling. For the latter application, numerous field surveys were conducted to develop the evaluation algorithms or workflows which convert the DAS noise recordings into flow rates from individual zones. The applicability of a new graphical user-interface has been expanded to include smart producers and injectors that allows the user to visualize (in real time), QC and evaluate the DAS data. Also, the evaluation methods for the use of DTS for warmback analysis have been significantly improved.There are still improvements to be made in enabling Distributed Sensing infrastructure, such as handling and evaluation of very large data volumes, seamless FO data transfer, the robustness & cost of the FO system installation in subsea installations, and the overall integration of FO surveillance into traditional workflows. It will take some time before all these issues are addressed but we believe that FO based applications will play a key role in future well and reservoir surveillance.In this paper we present a recent example of single-phase flow profiling using DAS. The example is from a long horizontal, smart polymer injector operated by Petroleum Development Oman (PDO).
In this paper, recent EOR field trials are discussed to demonstrate the value of in-well fiber optic (FO) applications. The trials are in a field in Oman that has been considered for an enhanced oil recovery (EOR) development. Polymer Flood and Steam Injection have been proposed as alternative EOR methods and both are being studied. A recent polymer injectivity test and steam trial were conducted in order to de-risk uncertainties in a full field development and this paper presents the application of FO in these EOR trials to help meet these objectives. The fiber optic approach is viewed as an alternative technology to production logging and it provides the option of real time acquisition. In one area of the field, a shut-in well was converted to a polymer injection well and utilized for a single well injection test (SWIT). The test was carried out for six months to quantify the inflow profiles and injectivity to the reservoir under matrix conditions. For the steam trial in another area of the field, three producers and one injector with FO were utilized to demonstrate the feasibility of a horizontal well steam development and to evaluate the requirement and effectiveness of injection conformance. FO analysis from both trials concluded that the Distributed Temperature Sensing (DTS) and Distributed Acoustic Sensing (DAS) combination can be successfully used for injection conformance profiling. DTS/DAS measurements were taken during the course of the polymer injection test. These indicated that conformance was incomplete from the onset and deteriorated during the course of the test, with a large proportion of fluids in-fluxing into the reservoir through a narrow section at the toe of the well. One of the main objectives from the steam trial was to measure and manage conformance along the horizontal steam injector. Use of FO helped demonstrate the importance of managing conformance in order to achieve satisfactory sweep efficiency. This paper explains how these new technologies play a key role in reducing the uncertainties in reservoir performance in EOR developments. The combination of FO (DTS and DAS) data sets allowed the interpretation of data gathered to complement each other and provide more comprehensive conclusions.
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