TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractLiquid production can be a serious problem in gas wells if there is inadequate energy to lift the liquid from the well bore.
It is important to employ a good production injection strategy to optimize hydrocarbon recovery from a field. Reservoir constraints on the surface facility change as the field matures. It may be economical to revise the surface facility configurations rather than retaining the initial design of the surface facility to maintain the target production level of the field as reservoir conditions change. If reservoir pressure is not sufficient to maintain natural flow, there may be need for artificial lift mechanisms to keep the well flowing. Careful analysis of interdependence of the surface facility constraints and reservoir conditions are important in designing good quality production injection strategies for these circumstances. Coupled facility and reservoir simulations allow production optimization and determination of the impact of injection or disposal policies on reservoir management. Sometimes there are oscillations in computed production rates, which may be as a result from inaccurate treatment of a coupling algorithm, well management rules, optimization techniques, etc. Excessive fluctuations make the solution impractical to implement. In this paper, we examine the cause of well rate fluctuations in coupled simulations. We were able to keep oscillation levels at a very low level in our simulations by using a small coupling interval and by revising well management rules. We made case studies with reconfiguration of surface facility designs in two large fields to examine if those designs were capable of meeting the required production targets as the reservoir conditions change with time. Surface facility models were built using a commercially available software, which were coupled to Saudi Aramco's in-house reservoir simulator, POWERS. We examine scenarios where some facilities could be eliminated to reduce cost while maintaining required production target. We study the impact of reconfiguring the surface network and examine how surface constraints might change the overall production rate.
Characteristic of high pour point oil may cause problems in pipeline transportation if it is not handled carefully, especially in long and hillyterrain pipeline. It may form solid in ambient temperature, and further may cause pipe plugging along the line, especially in sloping pipe area. The pipeline is 20 inch diameter stretch 250 km from Tanjung oil field to oil refinery in Balikpapan, East Kalimantan Province of Indonesia. Alternatives of transportation had been considered, such as insulation line, heating, chemical, etc. Alternative chosen was transportation of mix fluid of the high pour point oil and water. Transportation of mix liquid may prevent accumulation of solid oil particle at places along the line and avoid pipe plugging, and the method was also considered low cost of investment and operation. Such method of transportation has been conducted since 1963 and reached peak pumping of 44.000 BOPD oil production. At present time total oil production has declined to only 7800 BOPD, and transportation of the oil production is conducted periodically 12 times a year in oil-water mixture of65% oil and 35% water, with total oil transported 250.000 Barrel per-pumping period. On year 2002 it was experienced an operational failure, when the pipeline was plugged caused by solid oil particle accumulation, causing interruption of pumping. An effort to remove the plugging has succeeded by conducting "rocking"method and injection of light oil, and such method was able to bring transportation to normal operation in considerably short time. A simple modelling approach of the high pour point crude oil transportation has been obtained using Multi Phase Flow Dynamic Model OLGA to study characteristic of the flow in pipeline through a hill, and predict critical operation conditions to avoid unexpected transportation failure in the future. Introduction Tanjung field is located in South Kalimantan province of Indonesia, it was discovered in 1937. Since the discovery it took some time to develop the field. Main problem was transportation of the oil production. At that time the field was located in the middle of Kalimantan deep forest, where no road access and infrastructure had been built. Other problem delaying the development of the field is the characteristic of the produced oil. Crude oil from the field was found have high wax content and high pour point. Pour point of the crude isabout 100 °F, while the ambient temperature is about 85 oF that will change the crude into solid phase at ambient temperature. Tanjung field is located about 240 km from the nearby Oil Refinery in Balikpapan, East Kalimantan Province. The refinery has enough capacity to process the oil production from Tanjung field. Transportation of the high pour point crude becomes a challenge, since it will solidify in ambient temperature, it may plug the line during transport. Other challenge is the characteristic of hilly terrain from the field location to the refinery. Alternatives of pipeline transport had been studied after field discovery such as insulation, heating the pipeline, and mix transport of crude and water. After laboratory study and field test, it was decided to transport the crude by mixing with water. This method was considered the most effective way of transportation since no heating and insulation required. The critical thing is mixing composition of crude and water, and also how to maintain the mix remainin its form from pipeline inlet to the outlet. If somehow the mix has been broken, water may leave the oil behind or vice versa, that may cause pluggingof pipeline. A combination right mixing of water and crude oil, and correct transportation procedure will be the key for the success of transportation.
This paper presents a workflow developed to integrate subsurface and surface network models for a huge carbonate oil reservoir overlain by a large gas-cap located in the Middle East region. The integrated model consists of separate standalone models connected through commercial software. The reservoir simulation model is compositional with nine-components and over 60 million-very-refined grid-cells. The reservoir simulation model runs on a state-of-the-art in-house simulator; GigaPOWERS. The surface production network model consists of five production networks in addition to a gas injection network, with detailed network and elevation profiles, to model the desert terrain found in the field. The surface network model implements compositional components — as in the reservoir simulation model to capture compositional variations — to evaluate the NGL recovery processes and lean gas injection options. The detailed elevation profiles of the desert terrain in the surface network model allow for an accurate evaluation of the fluid velocities in the pipelines. It also provides a back pressure profile for each and every well in the network. The integration of the reservoir simulation and surface network models helped in assessing the reservoir and well production strategies and their impact on the production facilities, such as the early detection of low velocity in the pipelines that could eventually reduce the potential of corrosion due to this factor, and avoiding producing at high GOR levels to prevent reaching or exceeding erosional velocity limits. The integrated modeling therefore allows for simultaneous reservoir management and surface production facility planning.
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