One of the costliest parts of field-scale reservoir studies is log analysis. A recent GRI project required a detailed study of a field with hundreds of wells. As part of this study all the well logs were to be analyzed by an engineer in order to identify net pay, porosity, and saturation. It soon became apparent that a considerable amount of time must be devoted to well log analysis in order to obtain consistent and high quality reservoir characteristics throughout the field. This was mainly due to the fact that logs for several wells were missing and many wells did not have the suite of logs that were necessary for analysis.

This paper presents a novel approach to reduce the cost of well log analysis while maintaining the quality of the analysis. The cost reduction is achieved by analyzing only a group of the wells in the field. Using the detailed analysis of this group of the well logs by an expert engineer, an intelligent software tool is built to learn and reproduce the analyzing capabilities of the engineer on the remaining wells.

This approach provides a means to increase the efficiency of the engineering team. It can decrease the time needed to analyze a large number of well logs while considerably reducing the project cost to the operator. It will provide means to attain well log analysis for wells that do not have all the necessary logs needed for the analysis. This is achieved by generating virtual wireline logs for these wells. Virtual intelligence techniques are used in construction of the intelligent software tool presented in this study.

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