Accurate Reservoir Evaluation from Borehole Imaging Techniques and Thin Bed analysis. Case Studies in Shaly Sands and Complex Lithologies in Lower Eocene Sands, Block III, Lake Maracaibo, Venezuela
Authors: Coll Carolina , Rondon Luis , Cortiula Bice 
Published: December 2007

Accurate Reservoir Evaluation from Borehole Imaging Techniques and Thin Bed analysis. Case Studies in Shaly Sands and Complex Lithologies in Lower Eocene Sands, Block III, Lake Maracaibo, Venezuela.

Summary
Computer aided signal processing in combination with different types of quantitative log evaluation techniques is very useful for predicting reservoir quality in complex lithologies and will help to increase the confidence level to complete and produce a reservoir. The Lower Eocene Sands in Block III are one of the largest reservoirs in Block III and has been producing light oil since 1960. Analysis of Borehole Images shows the reservoir heterogeneity by the presence of massive sands with very few shale laminations and thinly bedded sands with numerous laminations. The effect of these shales creates a low resistivity that has been interpreted in most of the cases as water bearing sands. A reduction in porosity due to diagenetic processes has produced a high resistivity behavior. The presence of bed boundaries and shales is detected by the microconductivity curves of the Borehole imaging Tool which also allows for estimation of the percentage of shale in these sands. Interactive computer aided analysis and various images processing techniques are used to aid in log interpretation for estimating formation properties. Integration between these results, core information and production data was used for evaluating producibility of the reservoirs and to predict reservoir quality. A new estimation of the net pay thickness using this new technique is presented with the consequent improvement in the expectation of additional recovery. This methodology was successfully applied in a case by case study showing consistency in the area.

Introduction
The Lower Eocene Sands in Block III (Fig. 1) were discovered in 1962 by well VLC-363 in the eastern part of Lake Maracaibo. Early estimates suggest that 1.6 Billion stock tank barrels of oil were initially in place in the Lower Eocene Sands in Block III (Ref. 1).The initial recovery factor was calculated at 42 % and has produced 270 MMSTB while the remaining estimated reserves are calculated at 290 MMSTB. It was interpreted at the beginning of field exploitation that Lower Eocene sands were homogeneous (Ref. 1). Initially, the wells in the southern part had an average production of 4000 barrels per day of light oil. After ten years, the northern and eastern parts of the field where developed. These wells were troublesome, very costly and with very low production rates (Fig. 2). It became apparent that the reservoir was highly heterogeneous and complex. Production logging performed in some wells showed that only small intervals in the lithologic column were productive and that in some cases those intervals did not appear on standard logs as having the best potential. Any improvement in reservoir evaluation would require significative changes in the standard procedure followed for a normal homogeneous field. Effective reservoir characterization requires a successful integration of varied geological and petrophysical data that provides multiple benefits including increasing accuracy of reserves and well productivity estimates. Although high resolution well logging instruments have significantly contributed to improved reservoir description, the use of these increasingly remote and sophisticated methods makes it easy to forget that integration is the key to solving problems. High resolution electrical resistivity imaging is an important new tool in the field of petrophysics and is an important piece of information for core-log calibration. There are heterogeneous properties that can not be detected with a normal suite of log. These properties could control production of an interval due to restrictions in vertical flow through the sands. This paper describes how measured electrical images correlate with the porosity and permeability of the samples, and, in turn, with their petrographic characteristics.
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