Delineation of oil and water in heterogeneous carbonate formations can be challenging, especially in the presence of low resistivity formations and low mobility zones. Advanced wireline formation testers have traditionally been used in openhole logging for pressure profiles, coupled with downhole fluid analysis (DFA) and sampling for an integrated approach. It is often difficult to obtain well defined oil and water gradients with pressure measurements in tight formations, especially with probe-type tools. Straddle-packer modules are often used to enable flow from low mobility formations. However, the straddle-packer module has operational and differential pressure limitations, as well as a relatively large storage volume in the isolated interval. A field example of oil-water delineation is presented for a low resistivity, heterogeneous carbonate formation. Low formation fluid mobilities required the utilization of a new wireline tester module over the standard probe type tool. A newly designed fluid inlet module with multiple openings was utilized across the low mobility zones for the first time in the industry. This new module avoids issues associated with the interval volume of a dual-element straddle-packer-type tool and provides significantly faster clean up from the formation. In addition, minimized storage results in better Interval Pressure Transient Test data. Faster set/retract operation of this tool and a much higher pressure differential limit are additional advantages over existing dual packer tools. Several station measurements with mobilities of less than 0.1 mD/cP were conducted. This allowed oil to be identified across a low resistivity zone, leading to an increased oil column height in the field.

Results showed that more accurate oil-water delineation was provided using the new module along with high resolution optical fluid analyzers, identifying mobile oil from low resistivity carbonate zones. In addition, more accurate permeabilities for the tested zones were obtained through pressure transient data analysis.