SPE 157996 Optimizing Water Injection Rates for a Water-flooding field Feilong Liu, Charlie Guthrie and David Shipley, Chevron Energy Technology Company
Copyright 2012, Society of Petroleum Engineers This paper was prepared for presentation at the SPE Annual Tec hnical Conference and Exhibition held in San Antonio, Texas, USA, 8-10 October 2012. This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The a bstract must contain conspicuous acknowledgment of SPE copyright.
Abstract Setting proper water injection rates for the injection wells is a key factor to successfully operate an oil field under water flooding. The success of such activity could (a) reduce water cycling at field, section and pattern levels; (b) improve water/oil ratio (WOR) and areal sweep efficiency; (c) improve oil production and recovery by directing water injection to specific zones and areas; and (d) r educe OPEX by improving water utilization. Typically, the onsite engineers adjust injection rates using heuristics. While this does improve performance we feel that a more systematic approach can be developed which will lead to further gains. In this paper, we present a systematic method, using the linear programming, to optimize the water injection target rates. In this method, the reservoir is considered to be a system which can be modeled as a collection of continuous-time impulse responses that convert injection rates into a production rate. A very simple two parameter parametric model, like diffusivity-filter, has been used to quantify the injector-producer continuous-time impulse responses channel model and the Extended Kalman Filter has been used to establish the allocation factors between injectors and producers in the water-flooded field. Subject to constraints, including the total available water amount, the maximum and minimum injection rates, the maximum total production fluid for a producer and a gauge setting, a linear programming optimizer has been applied to determine the optimized water injection rate, based on the established allocation factors. This method was pilot tested on a Chevron oilfield for 3 months. The decline curve for 6 months and for 2 months of historical oil production data have been calculated. The 3 month pilot test result indicated that the optimized oil production matches the historical 6-month decline curve very well with about 22% less total daily water injection. Also we saw about 2% incremental production above the historical 2month decline curve (again with about 22% less total daily
water injection). These results suggest that this systematic method may provide a way to optimize the water injection target rates.
I. Introduction Waterflooding is by far the most widely used secondary recovery method in the oil industry. As the name implies, waterflooding involves injecting water into an oil reservoir and driving the oil into the production well. Currently, waterflooding is responsible for a big portion of world oil production, and successful waterflood management i s hugely important to the world oil supply. Waterflood management is a broad topic involving a range of activities, some of which are performed only once or twice during the life of the waterflood; others are performed periodically based on analyses of recurring measurement data. Among which, setting water injection target rates for the injection wells is one of the key periodical activities. The success of such activity could (a) reduce water cycling at field, section and pattern levels; (b) improve water/oil ratio (WOR) trend and areal sweep efficiency; (c) improve oil production and recovery by directing water injection to specific zones and areas; and (d) reduce OPEX by targeted water utilization. Typically, the oil production in a waterflood field is constrained by a combination of the reservoir condition, flowing pipeline network and surface facilities. Adjusting the water injection rates can help control the oil production from the producer. Hence, how to determine the optimal water injection target rates, subject to all kind of constraints at the field, to maximize the oil production is important to the onsite engineers. However, due to the complex dynamic interaction between reservoir, injection wells, production wells and surface facilities, this is not an easy task. So far, some optimization approaches [2] on adjusting water injection rates have been proposed, but few of them have been piloted or applied in an operating field. The onsite engineers typically set rates using heuristics. What they regularly do is to look at the production history and bubble map, and then decide where to inject more water and where to inject less. These approaches, while helpful, leave r oom for further improvement. To overcome these difficulties, we propose a systematic method, using the linear programming, to optimize the water injection target rates in which [3-4]:
