In this paper, we will share the recent work that was done to understand how bulk flow rates and fluid composition may be derived in single-phase and multi-phase flow by tracking the slopes (velocities) of coherent features detected using Distributed Acoustic Sensing (DAS). Both laboratory experiments and real field examples will be presented to demonstrate how velocity features can be detected and attributed to events such as slug flow or sound waves. Speed of Sound (SoS) analysis can in principle be used for determining changes in the fluid composition in multiphase flows, which provides opportunities to detect fluid interfaces and water or gas breakthrough. On the other hand, slowly moving features such as slugs or turbulent eddies can be used to derive bulk flow velocities, which may be used for injection or production profiling. The evaluation method directly derives velocities by Fourier transforming the raw DAS data in the temporal and spatial domains without applying any calibration steps. It can therefore be used to monitor flow in wells on a drive-by or continuous basis without a need for reference flow data.
This paper discusses the application of DAS for flow monitoring. While previous publications (Van der Horst et al (2013) focused on vertical and horizontal tight gas wells in North America, the focus here is on liquid producers and injectors in Brunei. Specifically, it was found that DAS has potential for zonal production and injection allocation across ICVs, monitoring interzonal inflow from the reservoir, monitoring artificial lift, tracking fluid transport through the well bore, detecting leaks, and monitoring wax build up or other types of deposition in the well.
leads to deformation, compaction, displacements, and stress change in the reservoir as well as in the surrounding rock. Such stress changes affect the acoustic-wave velocity and bulk density. This has two implications. It changes the contrast in acoustic impedance between reservoir and overburden, resulting in seismic amplitude changes at the top of the compacting reservoir. Secondly, it changes the traveltime of seismic reflection waves, leading to arrival-time delays (time shifts) of seismic data gathered in the repeat survey compared to data gathered in the base survey (Hatchell et al, 2004; Kenter et al, 2004; Stammeijer et al, 2004). Maps of time shifts can then indicate the areal distribution of reservoir compaction, and thus reveal the areal distribution of depletion. This could help to locate bypassed oil in undrained compartments, identify drilling targets and sidetracks, and avoid expensive infill wells. These interesting geophysical applications of reservoir mechanics justify questions about how accurate such geomechanical models really are. What is their sensitivity to the (natural) variation in input parameters like geologic structure and sedimentological detail, depletion pattern, and mechanical property distribution? This question is closely related to our ability to capture this variation in computer models via upscaling. Analytical models based on simplified reservoir shapes and linear elasticity show that the reservoir-compaction-induced stress change in the overburden is governed by the contrast in mechanical properties of the reservoir and the rock surrounding it, and by the reservoir shape and size with respect to its depth of burial (Geertsma, 1973; Segall, 1992). Memory and computational capacity of computers now allow numerical analysis with fine-scale (tens to hundreds of meters) geologic reality in geomechanical models. This paper describes two computer simulations with finite-element analysis to investigate the influence of proximity and structure of halite rocksalt and stiff chalk on reservoir-compaction-induced stress change in the overburden. Salt and chalk are abundant in many hydrocarbon basins. Salt is of particular interest because of its ability to trap hydrocarbons and perturb the stress field in adjacent sediments, with implications for pore pressure and fracture gradient prediction, and for reservoir monitoring with time shifts. Chalk contains a large amount of world oil reserves and, with its productivity often influenced by fracture systems, understanding its stress development is important.Model A: stacked sands bounded by salt. The size of the 3D geomechanical model was 19 ǂ 13 km laterally and 12 km in depth, and it had 142 100 elements. Boundaries of 18 producing unconsolidated ("loose") sands were upscaled to seven layers with a total vertical thickness of about 400 m (Figure 1). The sands have a porosity of 25-32% of bulk volume. Sand-specific estimates of vertical uniaxial-strain bulk volume compressibility (C uv ) range from 4 ǂ 10 -4 MPa to 1.6 ǂ 10 -3 MPa, based ...
Summary Fiber-optic (FO) -based sensing technologies such as distributed temperature sensing (DTS) or distributed acoustic sensing (DAS) for well surveillance are attractive because they offer a continuous collection of real-time downhole data without the need for well intervention, thus avoiding production deferment. An example is the application of DTS and DAS for gas lift performance monitoring in oil producers by measuring the thermal and acoustic effects from the flow of lift gas through the valves into the production tubing to determine the active, inactive, and possibly leaking valves, and, also, the unloading depth. An anomaly observed in DTS data of a deepwater Gulf of Mexico (GOM) gas lifted oil producer led to a significantly improved interpretation methodology that allows inferring both the lifting depths and the annular-fluid interface(s). These results were confirmed by DAS, by identifying gas flow through a valve in selected acoustic-frequency bands. The new insights have been applied to five wells in the GOM and Southeast Asia.
Fiber Optic (FO) sensing technology is an exciting and novel technique offering many advantages over traditional wellbore surveillance methods 1-3 . Multiple FO cables can be installed that can be designed for sensitivity to a wide variety of signals such as temperature, pressure 4-5 , strain 6-7 , sound 8 , and the presence of specific chemical compounds. Permanently installed FO cables enable a cost effective surveillance policy where data acquisition surveys can be conducted without well interventions, in real-time, at any time, and continuous along the entire well bore. The avoidance of well intervention eliminates production deferment and operational risks of conventional surveys. Frequent, time-lapse FO based surveys can provide critical reservoir surveillance data for production and recovery optimization.One instance of fiber-optic surveillance is Distributed Sensing, which uses the entire fiber as a sensing element. Recently, very good progress has been made in Distributed Acoustic Sensing (DAS) for hydraulic fracturing monitoring 9 , production profiling for commingled oil and gas producers, injection profiling for water injectors 10 , gas lift monitoring and the acquisition of wellbore seismic data such as Vertical Seismic Profile (VSP) surveys 11-12 . These applications are also seen to benefit from integration with other methods such as Distributed Temperature Sensing (DTS) and Distributed Pressure Sensing (DPS). In terms of wellbore surveillance, the possibility to monitor flow along the entire wellbore from FO sensing provides useful insights in the complex flow behavior in a well which can be used to optimize well performance.There are also many improvements to be made in the enabling Distributed Sensing infrastructure such as the handling and evaluation of very large data volumes and seamless FO data transfer, the robustness & cost of the FO system installation, and the overall integration of FO surveillance into the full workflows. It will take some time before all these issues are addressed but it is clear that FO based applications will play a key role in future well and reservoir surveillance.In this paper some examples of using DAS for Production Allocation are discussed. TX 75083-3836, U.S.A., fax +1-972-952-9435
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