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).
In the Mahakam delta in East Kalimantan, TotalFinaElf E&P Indonésieoperates fields with numerous multi-layer reservoirs deposited within a deltaicenvironment. Formation waters in these reservoirs have very low salinities, which vary with depth and from reservoir to reservoir. When a field is inproduction, the evaluation and update of initial hydrocarbon net-pay is mademore difficult by depletion and fluid level changes, which are related tochannel reservoirs connectivity, both laterally and vertically. A new methodhas been developed, based on acoustic measurements, to help identify theoriginal gas net-pay. This method uses the fact that compressional acoustic waves travel slower ingas than in liquid whereas shear waves are not affected by fluids in the porespace. An empirical correlation is established between Vp/Vs ratio and shearslowness in known liquid-bearing sands. This correlation is used to predictVp/Vs over the whole logged interval. A large difference between predicted andmeasured Vp/Vs indicates the presence of gas. Since gas is very compressible, the effect is noticeable even at very low gas saturations, i.e., in gasreservoirs that have already been depleted, or even swept by water. The method was first tried in a mature oil field in order to distinguish gasfrom liquid and gave encouraging results. It was then applied in a gas fieldwhere a 3000-meter interval of dipole sonic log had been recorded in one well. Fluid status identified by this method was crosschecked against all other data(wireline logs, mud logs, wireline fluid samples) and against the geologicalmodel. The results helped confirm (or revise) the model, which, in turn, improves mapping, material balance calculations and optimization ofproduction. Based on numerous examples, the conclusion is that very good results areobtained in clean sands, especially where known water and gas bearing intervalsare available for calibration. The article also states the limitations of themethod, which can give ambiguous results in very shaly reservoirs and alsofails in deep reservoirs where porosity falls significantly below 15percent. Introduction In the Mahakam delta in East Kalimantan, several oil and gas fields werediscovered and are being developed, which contain numerous reservoirs depositedwithin a deltaic environment. Due to the complexity of such geologicalenvironment and the large number of reservoirs, the geological modeling is atricky process. When a field is in production, the evaluation and update ofinitial hydrocarbon in place is made more difficult by depletion and fluidlevel changes in wells and reservoirs, also in relation with complex reservoirgeometry and connectivity, both laterally and vertically. For each new infillwell the identification of the fluid status of each individual reservoir is ofprime importance for both initial static volumetrics review and reservoirproduction policy. Additionally, since formation waters in these reservoirshave varying salinities, which change with depth and from reservoir toreservoir, the definition of current fluid status is difficult. As aconsequence of all these factors the correlation and mapping process is evenmore complex and requires several levels of data integration. First, all geological and log data are integrated in order to provide ageological model, leading to volumetric estimation. The last stage ofintegration is the validation, with pressure and production data throughmaterial balance and/or reservoir simulation models (see Moge and Febvre,2001). Since in the present context commingled production in wells is common, production allocations are less accurate, and, even if the knowledge of thefield is improved with such an integrated process, uncertainty remains withinthe model. Therefore, any new data or method to better evaluate the status ofreservoir fluids - be it the initial or the current status - is useful tobetter position infill wells and manage a more efficient reservoir productionpolicy. Amongst many available tools, a new method has been developed, based onacoustic measurements, to help identify the original gas net-pay, to becompared with the current fluid status in the reservoir and help in the fieldreview.
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