ABSTRACT:

This paper introduces a new technique adopted by ENI E&P for reservoir analogues identification. The use of reservoir analogues becomes more and more attractive, particularly when no additional information is available for a certain area or field or the acquisition costs are very high. In this case, a valuable technique consists in understanding if reservoirs with similar characteristics have already been studied in the past, in order to assess useful information that can be applied to the study under exam.Within ENI E&P, analogues can be found by searching into many commercial databanks and, particularly, into the database of archived reservoir studies results and reports. This database is comprehensive of a wide set of parameters of many ENI E&P reservoirsThe advanced search tool developed in ENI E&P is based on a "most likely" query technique. This way, the user is presented with a rich result dataset even when few analogues are available in the databases, and no perfect matches exist with the user defined query. Moreover, a big advantage of the developed tool is to allow the recovery of information also from unstructured data sources, such us documents, reports and papers, by applying a "semantic analysis" search method.The real challenge of the ENI E&P tool consists in being capable of searching analogues through different heterogeneous data sources, both structured (databases) and unstructured (documents); analogues data can be used to overcome lack of data and uncertainties, resulting in a remarkable quality increase and time and cost saving.

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