TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThe Zeit Bay field reservoir units consist of sandstone and carbonates, partially overlaying a tilted block of fracture basement reservoir with a complex drive mechanism. A secondary recovery scheme of gas reinjection into the original gas cap was initiated to maintain reservoir energy and minimize pressure decline. Over 70 development wells are actively depleting the reservoir.

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractEnhancements in software, hardware, expertise, data collection and interpretation have continued to improve the industry's ability to build detailed 3D geologic and dynamic flow models of the subsurface and to take rational reservoir development decisions. There continues, however, to be much skepticism about the ability of the same process to contribute to day to day reservoir management and optimization of mature assets.This paper describes how a truly integrated approach can shorten the planning and study timeframe and reduce uncertainty for reservoir management in such mature assets. Also presented is a system which links on-line (real-time and near real-time) downhole, surface and corporate data to ensure that reservoir, well and facilities models are constantly updated to reflect actual operating conditions. Using this "always current" encapsulation of the production system (between reservoir and delivery point) we perform a wide range of tasks to manage the asset performance: surveillance activity planning, production optimization, facilities optimization and debottlenecking, production forecasting and allocation.The system integrates a number of existing software applications, and reduces the number of complex engineering tasks. It is being applied in a number of operational environments and the results of some are presented:• Workflow and examples for integrating dynamic simulation output with static model and production data. • Tool for waterflood pattern analysis and integration with well and production history• Live visualization of SCADA/DCS data via PI system and integration with reservoir understanding to provide a tool for accelerated identification of optimization potentialThis integration process has a very positive impact on reducing the processing time for each task, and the visualization formats assist communication within the multidisciplinary reservoir management team. Embedding these tools in the reservoir management and field development process aids decision making and accelerates production thereby increasing the value of these mature fields.

Ras Budran filed is a massive Nubian sandstone reservoir compartmentalized by major faults acting as partial barriers. Vertical communication is impeded by hydraulically sealing shale layers in the development of three main pressure regimes. A combined water injection and aquifer support the pressure. Pre-mature water breakthrough has been occurred in the middle of oil leg, which in turn limit the corrective action of the isolation of the watered out zones. 3D- geological and reservoir simulation model was constructed, based upon new reservoir characterization with the objective of improving the vertical definitions within the reservoir. The reservoir properties generated by deterministic interpretation for the new micro-zones. This paper presents the approach taken to match 17 years of production data in particular, via aquifer definition and fault communication. The history-matched model was then used to confidently check the production and injection well pattern and performance. The matched model then used to investigate the viability of infill wells to improve drainage pattern and sweep efficiency meanwhile increasing ultimate recovery. Introduction Ras Budran field (R/B) is located at the eastern coast of the Gulf of Suez area (Fig 1). The field was discovered in April 1978 and production started in Feb., 1983. Production is maintained by gas lifting while the pressure is supported by a combined water flooding and limited aquifer drive. There are 17 producing wells and 4 injectors over 3 offshore platforms. The field is relatively deep reservoir with the original oil water contact at 12350 ft-tvdss. Heavily under saturated reservoir with initial reservoir pressure of 5632 psia and the bubble point pressure 1200 psia. The structure contour map Fig. (2) shows the reservoir complexity. The reservoir is massive sandstone and the macro layers were defined from top to bottom as follows; Raha, Nubian III, IIB, IIA and Unit I. Unit IIA has a shale/sand streaks that work as a vertical hydraulic barrier between the upper and lower units. Lower Units of block, which called Unit I (LA), Upper units of block A (UA), Upper Units of block B (UB) and Upper Units of block C (UC). Fluid flow in the reservoir is directed from unit I to the juxtaposed upper reservoir units supported by water injection in unit I from injector A3b and direct aquifer support. Fluid flow in upper units of block A is only supported by the water injection through injectors A2, A1 and A9 respectively. Fig (3) illustrates the main cross section for the field. Due to the nature of Ras Budran reservoir and its dipping structure, peripheral injection pattern was proposed and implemented in the original field development plans in October 1985 through two wells A2a (Unit IIB+III+R), and A3b (Unit I). In January 1990, the system was upgraded with another injector A1 (Units IIB+III), to replace the poor injector A2a and finally, the last injector A9a (Units IIB+III+R) was brought on line in April 1992. The difference between formation and injection seawater salinity was used as a tool to monitor the flood front and the interblock communication. The field has already produced 80% from the estimated reserves. Modeling History: Because it will not be possible to capture the dynamics of a water flood project, in particular with high mobility ratios as in the case of Ras Budran, with single cell calculations. Reservoir simulation modeling is essential in order to optimize injection/production well patterns and to optimize sweep efficiency via the injection distribution.

The need for artificial lift is very common worldwide, nearly all reservoirs requires artificial lift at a certain stage of the field life. The decision of which artificial lift method to use is very important to the long-term profitability of the field. An improper decision of artificial lift can reduce production and increase the operating costs substantially. Once a decision has been made on the type to install on a well, it can rarely be altered whatever the method been selected. Ras Fanar Field is located on the western side of the central part of the Gulf of Suez about 3 km east of the city of Ras Gharib. Production commenced in January 1984 and a peak production rate of 20 MSTB/D was achieved in May 1984. The field was produced naturally for 14 years and the produced fluid contains up to 15% H2S and 11 % Co2 in the associated gas phase. It has been recognized that there is a need for artificial lift when water cuts increased and/or reservoir pressure decline. Studies carried out by SUCO concluded that ESP's are the most appropriate method and it was installed in 1996. The operating experience gained during the period 1996 to 1998 led to significant improvements, resulting in ESP run lives in excess of three years. The main problems during the initial phase of the project and the applied solutions, as well as critical operating factors will be described. This paper presents and discusses the operational challenges of the ESP in such highly aggressive environment and documents the success and failures. Introduction The Ras Fanar Field, Figure (1) was discovered in 1974 by Shell-BP-Deminex group. It was declared commercial and commenced production in 1984 with six wells drilled. Over two offshore Platforms with an average 8 MBOPD. Since early production, the field has shown a high production potential with a conservative reservoir pressure decline. Due to the relatively low reservoir pressure in the Ras Fanar field, some of the wells experienced lifting problems at water-cuts (~20%), which required nitrogen assistance to restore intermittent production. The reservoir fluid is a 30–32° API with a high sulfur content of about 1.9% by wt. The associated gas is sour containing about 12% H2S and 11% CO2 by volume at separator conditions. Reservoir Description The field comprises one reservoir, namely the Nullipore. It is a carbonate build up (reefal limestone) of the Miocene age. The reservoir is hydraulically communicated, with no sharp boundaries like shale's or anhydrite in between. The major and minor faults are all non-sealing, which results in having the same pressure regime in different wells throughout the field Figure (2) illustrates Structure contour map for RF field. The oil column is approximately 730 ft between the crest at 1900 ft-TVDss and the original OWC at 2430 ft-TVDss. The field always shows increasing oil potential, which resulted in upgrading the reserves several times. Overall 24 wells have been drilled by the end of 1995 in the Ras Fanar area.

Streamline simulation is an ideal reservoir management tool for mature waterfloods since it can identify unswept reserves, quickly evaluate multiple forecast scenarios, and provides novel information like well-pair interactions. The identification of well-pair interactions is particularly useful as it allows for pattern surveillance, quantifying offset production with injection volumes, and identifying efficient vs inefficient areas of injection. The Thuleilat heavy-oil field consists of 120 wells and is geologically complex with stacked reservoirs, multiple oil-water contacts, and numerous faults, making it difficult to identify well interactions and areas of unswept reserves. However, being a dead oil reservoir with the majority of production a result of injection, it is ideally suited for streamline simulation. Several opportunities were identified based on the streamline simulation. These opportunities, which generally apply to all waterfloods, could be divided into well rate target recommendations, pattern optimization, producer-injector conversions, and infill locations. Pattern optimization opportunities resulted in a 10% gain in the offset oil producers. In one of the pattern optimization activities three water injectors were identified for injection rate increase, followed by optimization activities in the associated oil producers which resulted in a significant oil gain. Other pattern optimization activities were to close in high gross rate wells and diverting the flow toward offsets oil producers. One of the trials was to close-in one of the producers in the central area for one week, which resulted in a measurable oil gain in 3 offset oil producer wells. The second activity was closing another producer in the northern sector for two weeks which resulted in an oil gain in 5 offset oil producers. Further use of the streamline model includes the assessment of unswept reservoirs for infill locations and the estimation of water cuts for development locations. Introduction Numerous authors have already shown the possibility of building complex history match streamline models for waterfloods.1–7 Many of these authors have also used their streamline models in a manner similar to finite-difference (FD) models for waterflood management, such as forecasting, testing infill locations, and identifying bypassed oil. Recently Thiele & Batycky9 showed how to use the novel information of well-pair connections from streamline simulation to improve flood performance. Specifically, alter well rates to increase oil production and reduce fluid cycling. However, there is little if any documented results of altering well rates based on streamline identified well-pairs, and what the outcomes were. The purpose of this paper is to show the results of implementing well rate changes to the Thuleilat field, based on a streamline model, and what changes to production actually occurred. The Thuleilat field is located on the eastern side of the South Oman basin approximately 200 km NE of Salalah Figure 1. This is a heavy oil field that has a STOIIP of some 96 Mln m3, and has been on production since 1987. Details of the geology and production of the field are described below.