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A new method for efficient fast-track evaluation and assessment of the re-engineering potential of mature fields

Total, Pau, France

Corresponding author: claude.mouret@total.com

The first 20% of the full text of this article appears below.

Many challenges must be faced when exploiting oil and gas fields. Mature fields throw up additional challenges which need to be examined in detail, so that the oil or gas which remains to be produced can be extracted in the most economical way. Initial production in mature fields often dates back to a time when techniques were not what they are at present. Consequently, the quantity, quality, and availability of data may vary considerably and often fall short of our expectations as geoscientists. As our aim is to maximize hydrocarbon recovery, optimize economics, and enhance the exploitation of vanishing natural resources, we must investigate field behavior and reservoir characteristics with the appropriate accuracy.

Processing and integrating all data as fully as possible is of paramount importance to maximize the amount and quality of information that can be extracted from any available data—whether it is numerical or qualitative. For instance, production rates strongly depend on the geologic characteristics, reservoir properties, and fluid composition of the field; knowledge of these three parameters enables production behavior to be understood, provided necessary precautions are taken. In addition, the possible effects of well activation or events on the surface network must be clarified using operations data records, and taken into account. In this way, production data can provide significant information on geology, and this additional knowledge can be used to refine the geologic model. In turn, the refined model improves interpretation of the dynamic behavior of the reservoir. Iterative cross-interpretations of all static and dynamic data and processing results provide better understanding of those reservoirs for which production history files are available.

This complex, iterative, workflow brings additional information on reservoir characteristics and performance. It often highlights previously unknown features which are present at a subseismic scale; these include lineaments, barriers of various kinds, vertically . . . [Full Text of this Article]