--> Abstract: Mapping Tools Applied to Reservoir Efficiency Index (REI) Evaluation at Prospect/Basin Scale, by Consonni, Alberto; Ortenzi, Andrea; #90163 (2013)

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Mapping Tools Applied to Reservoir Efficiency Index (REI) Evaluation at Prospect/Basin Scale

Consonni, Alberto; Ortenzi, Andrea

The efficiency of a reservoir is a function of three main factors: the depositional environment, the initial mineralogical composition, and the post-depositional evolution during burial. The Reservoir Efficiency Index (REI) is a quantitative indicator of the quality of a clastic reservoir, it is calculated based on petrographic data, grain size distribution and sorting, cements amount and type, porosity, pore dimensions etc, using mathematical relationships for the determination of the relative importance of each parameter. Plotting the REI values, obtained on samples from a variety of clastic reservoirs, against permeability, a good correlation is obtained. This is a verification of the reliability of the methodology of REI calculation.

Considering one reservoir unit, at each well location multiple measures of REI can be performed, giving as a general result an estimation of REI as an interval of values. To extrapolate the REI outside the wells, data analysis suggests that different variables, available outside wells, may have a direct/inverse correlation with the REI, these variables can be used as trends for the REI determination. These variables describe sedimentological features (sand/shale ratio, reservoir thickness, …), diagenetic effects (depth, temperature, …), or in general may be a parameter that has a structural relationship with the reservoir quality as measured by REI.

Different mapping algorithms have been tested, in order to extrapolate data given as intervals using one or more trend variables given on map. In the presented case history, interval values of calculated REI at wells, and depth and temperature trends have been used. A particular type of kriging with uncertain data and external drift has been used. The algorithm tries in a first phase to estimate a REI point value for each well using the other wells and the trends. In a second phase these well REI values are extrapolated on the studied area using trends.

This procedure evolves and completes the REI evaluation being able to extrapolate values calculated at wells over an area of interest at lead to prospect scale, depending on the availability of the data.


AAPG Search and Discovery Article #90163©2013AAPG 2013 Annual Convention and Exhibition, Pittsburgh, Pennsylvania, May 19-22, 2013