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Mature fields have a long production history file, and many other large data sets (static data, pressure, and so on). The challenge is often to select the most promising object (a field in a block, a reservoir in a multilayered field, or an area in a wide field). We present a global approach to solve this difficulty, that uses the concepts of Data Mining. It involves Sampling (gather the data, validate, and select the appropriate level of detail), Exploration (using a large set of graphical tools), Data Management (for production data, extracting production indicators), Modelisation (using for instance the hyperbolic oil production decline equation), and Aid to final decision. All along, graphical tools and multivariate statistical analysis are widely used and must be carefully designed. The whole of the approach requires a good geological and reservoir experience and a Reservoir and Geological Synthesis (RGS). Three field cases illustrate this fast track approach. Introduction Oil and gas companies have to face an ever increasing offer of fields for farm in, that have a long production history, because many fields were started in the 1960's, 80's and because the international market is more widely open. Companies portfolios include fields with a large number of wells — several hundreds or more — and several decades of production history. For these mature fields, extracting the most — or the best — of existing reserves is a must, for both the Companies and the countries with reserves. The remaining potential of these fields may be rather large. In some cases, it is necessary to solve all production-related difficulties that became apparent meanwhile the field was under production : insufficiently known heterogeneities, production mechanisms implemented with an unclear impact on production development, as for instance an insufficient reservoir pressure response to injection. In other cases, fields were developed with classical scenarios of natural depletion or water injection. The implementation of new techniques of EOR, or IOR, can sharply increase remaining reserves. Some papers have already been published about analytical evaluation methods for mature fields, that are not based on reservoir numerical simulations (Ref. 1 to 4). Recently, Albertoni and Lake (Ref. 5) have released a method to investigate well connections, on the basis of production rate fluctuations in five spot waterflood patterns. Multivariate linear regression method were applied. We now present a global methodology, based on our "Welfare" integrated software. Many types of data can be taken into account and subjected to statistical processing. Presentation of the method A noticeable part of today reservoir re-engineering activity is related, either to the selection of most promising zones, if one reservoir is concerned, or to most promising layers, when a multi-reservoir field is investigated. The challenge may even be to perform a fast track selection of a few fields among many. Each field has its own geological characteristics and its own development patterns and presents related difficulties in terms of performance, sectorisation, response to production mechanisms or location of untapped reserves. Petroleum engineers are facing a challenge which is comparable with those encountered in marketing, e.g. in the management of the relationship with the customer. Investing in the relation with a long-time customer is cheaper than acquiring new clients, and it can provide a lot of profit (Ref. 6). The most appropriate approach needs the personalisation of the relationship. So, the challenge is to extract the relevant information, concerning a small, but promising, part of customers in a market. Data Mining techniques are now currently used for this (Ref. 7).

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TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThe Well Intervention Profitability Evaluation Project was aimed at applying a BP Corporate methodology (WETS, Wellwork Evaluation Tracking System, SPE 30649) to TotalFinaElf's Mature Fields.

Due to the commingled production of reservoir and injected sea waters, the Dunbar Asset has had to face Barium sulphates scaling problems. In 2001, a post analysis was made over the entire past production history. This study was carried out by a team consisting of well productivity engineers, reservoir engineers and a production chemist from both Headquarters and the Affiliate. The analysis was directed at two different objectives:Fulfil an operational need: A water based pre-emptive treatment applied in 1997 on well D02 caused a substantial reduction in well productivity. This adverse effect led to major uncertainty in the planning and design of new treatments. The Affiliate wanted a complete analysis of this problem in order to come up with new procedures.Learn from Dunbar experience for future developments: Would it be possible, through a production history analysis, to look in detail at the scaling phenomena in order to pinpoint facts or identify engineering tools that could be of use in new development projects? And, as a feedback for future similar projects, could we assess what advantages a nano-filtration plant might have offered? Both the scaling process and the treatment impact were analysed. This was made easier by the fact we had available data from six production logging operations on a key well. In terms of modelling, Reveal model was used to assess physico- chemical related behaviours to be further exported into the Reservoir model. The results of this modelling were matched against actual production history. The paper will focus on the impact on well productivity of the scaling process as it was highlighted through the exercise. As a matter of fact, a relative manageable effect was observed after the first layer water breakthrough. The effect is much more severe after the second layer water breakthrough, which can create actual bridges into the tubing and consequently affect drastically the flow and can trap reserves from lowermost layers. As this method allowed playing back the history, it opens tracks for planning and dealing with the perforation strategy. In other words, it places the scaling prevention concern right in the middle of the reservoir engineers' type of expertise. Apart from technical consideration, the paper will also present quick economical issues. All scale related operating costs and production slowdowns have been compiled and weighted against the Capex and operating costs that would have represented a nano-filtration plant installed from the beginning. This consideration on economics is only meant as a reference point should we need to design developments in similar contexts, and still needs to be examined for any given project. Introduction Dunbar is an oil and gas field located in the UK sector of the North Sea. Its two main panels have been developed by water injection, with 9 producers and 4 injectors drilled during the first phase of the development. During that same period, 7 more wells were drilled to produce other panels under natural depletion. The reservoir pressure was initially 560 bars, to be maintained around 400 bar where water has been injected. The oil is very volatile oil (Bo=3v/v) The Injection water is pumped from Alwyn main platform The maximum WHIP at Dunbar is 270 bar at a maximum rate of 80000 b/d