The traditional method of measuring dynamic fluid level (DFL) is utilizing the echometer manually, which addresses the fundamental drawbacks of lacking the promptness and intensive workload. Real time calculation (RTC) of fluid level are achieved using installed sensors that simultaneously transmit acquired data, with the interval of ten minutes, to a office client that undertakes the generation and analysis of dynamometer cards. This paper proposes a new method to calculate the DFL. It takes the submerged pressure as a common solution node to analyze both the plunger load variation which is contributed by pump dynamometer and the pressure distribution in the annulus. Additionally, an approach to determine the density of fluid within the tube, according to the figures, such as maximum, minimum load of PR dynamometer card, the rod string combination and etc, has been established in order to analyze the fluid level accurately. Basing on the theory aforementioned, relying on the platform of Digitized Production Management, mining and integrating the available data, the system of monitoring the fluid level constantly has been developed. Considering the fluid level calculated by the downhole pressure as a standard, the results of more than 80 wells' computation reveal that the relative error of acoustic fluid level survey is up to 10.44%, however, the Dynamometer Card Method is merely 4.84%. Obviously, the latter improves the accuracy and reliability of the fluid level test and reduces significantly the workload of production technicians. Meanwhile, the recommendations for optimization of the well performance can be issued immediately. Case studies are presented showing analysis on a variety of wells. Introduction Dynamic fluid level, not only the significant index of revealing the ability of supplement in formation, but also the important data in dynamic analysis of oil production, is utilized to adjust the well system, estimate the reservoir pressure, affiliated determination of well performance[1]. At present, numerous techniques have been developed to measure the fluid level, among which the echometer(acoustic) method is the simple and widely used one. However, in practice, it is difficult to depend on this technique measuring the real time fluid level because the high cost of air gun and its life expectancy is short. In addition to the acoustic method, the fluid level can also be obtained by measuring the relationship between the casing pressure and time when the casing gas is vented into the air. Nevertheless, this approach is limited by the gas volume in the annulus[2]. The surface dynamometer card represents the polish rod load versus its position, which is usually measured by using a dynamometer. Proper analysis of the dynamometer card usually can be used to reveal the following results: the polish rod load at each point in the stroke cycle; minimum and maximum loads and stresses; whether the downhole pump valves are leaking and the extent of leaking; and the overall performance of the downhole pump[1–3]. Since 2008, with the development of the automatic monitoring system, which is called the platform of Digitized Production Management in Changiqng Oilfield, the surface dynamometer card can be transmitted to the office client by a wireless receiver or via WLAN with the interval of ten minutes. More specifically, the intelligent client transforms each surface dynamometer card into the corresponding pump dynamometer card, which is much more useful than the surface card because the latter reveals the load and position at the pump. To determine the condition of the pump, the calculated downhole card is compared with thousands of cards with known pump conditions using pattern recognition techniques. The pump conditions the system detects are full, incomplete pump, fluid pound, gas interference, standing valve leak, traveling valve leak, worn pump, and paraffin.
With the three-dimensional computational fluid dynamics method, the airflow effects over the huge telescope assemble is investigated in this article. The distributing of velocity field and natural convection are studied by modeling and simulating the turbulent airflow of the huge telescope. Numerical simulations show the best observation direction is the 90o angle between the main optics axis and the horizontal line in which the air velocity distribution is the least. And the air temperature distribution and uniformity around the telescope are also provided by simulation.
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