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The objective of this study was to characterize formation water resistivity (Rw) by validating water sample analyses, calibrating log derived Rw and mapping variations areal and vertically in order to reduce uncertainties regarding this property when determining water saturation (Sw) in the Tambaredjo oil field. Current calculations issued high Sw which originated low STOIIP and high actual oil recovery did not synchronize with the production of the field. A database with analyzed water sample and log-derived (Dielectric and Conventional logs) Rw data was created. Validation of the sample data was conducted by a Water Sample Analysis (WSA) tool, where the ionic balanced results were used. The log-derived Rw were normalized to the surface temperature and calibrated with the water sample analyzed Rw. To identify the initial Rw, groups of several wells (selected from the current produced water salinity maps) from total Tambaredjo Central Area (TCA) were made. With these initial Rw values the areal and reservoir distribution maps were determined and used for calculating the water saturation in the wells. Creating the WSA tool was very important to determine which samples were ionic balanced and were useful for further steps. These samples delivered different salinities which could clarify the water sources for the produced sand intervals. Three main groups of water sources were established based on the salinity; S-sands, T-sands and Cretaceous. Based on this classification, the log derived Rw were grouped and the salinities derived from the logs were compared with the produced water salinities retrieved from the Production Data Base. The log derived salinity that did not match the produced water salinity, the intervals from these logs were checked, re-selected and the salinity calculations were updated. Based on produced water salinity maps, well groups from the total TCA were created, comparing latest produced water salinity with initial ones. Assumptions were made of possible communications of water sources due to salinity values, where initial Rw did not match with the latest produced Rw. An initial Rw map was created and variable Rw proposed, instead of using a constant Rw for reservoir intervals of Tambaredjo oil field. Sw improves in all T-unit reservoirs of TCA from 41.9 to 40.4%, mainly in T1 and T2 sands (36.7% to 33.4%). In the T3 interval, Sw increases from 52.3 to 54.5% as formation water was found to be slightly fresher than originally estimated. Regarding stock tank oil initially in place (STOIIP) in TCA, with the variable Rw, it was estimated 265 MMSTB considering only T1 and T2 intervals. This is 17 MMSTB more than using the average value (Rw = 1.18ohm.m @ 67°F). The actual recovery is 14.2% and 14.9%, respectively, indicating that with the variable Rw, the actual recovery is closer to the expected primary recovery for this of field (10 to 13%) according to Ambastha (2008). Formation water salinity is a very important input in Sw equations. When geological features like top erosions, channel stacking or leaking seals are not tracked, and it is assumed that formation water resistivity is constant, water saturation calculations might not match production performances. This research proposes a methodology to identify sources of formation water mixture determining if a well was at initial reservoir conditions when it was logged, establishing Rw by areas.

This research proposed an alternative method for determining the saturation exponent (n) by finding the best correlations for the heterogeneity index using available core data and considering wettability changes. The log curves of the variable n were estimated, and the effect on the water saturation (Sw) calculations and the Stock Tank Oil Initially In Place (STOIIP) in the Tambaredjo (TAM) oil field was analyzed. Core data were employed to obtain the relationship between n and heterogeneity using cross-plots against several heterogeneity indices, reservoir properties, and pore throat size. After filtering the data, the clay volume (Vcl), shale volume, silt volume, basic petrophysical property index (BPPI), net reservoir index, pore grain volume ratio, and rock texture were defined as the best matches. Their modified/improved equations were applied to the log data and evaluated. The n related to Vcl was the best selection based on the criteria of depth variations and logical responses to the lithology. The Sw model in this field showed certain log readings (high resistivity [Rt] reading ≥ 500 ohm.m) that infer these intervals to be probable inverse-wet (oil-wet). The cross-plots (Rt vs. Vcl; Rt vs. density [RHOB]; Rt vs. total porosity [PHIT]) were used to discard the lithologies related to a high Rt (e.g., lignites and calcareous rocks) and to correct Sw when these resulted in values below the estimated irreducible water saturation (Swir). The Sw calculations using the Indonesian equation were updated to incorporate n as a variable (log curves), comparing it with Sw from the core data and previous calculations using a fixed average value (n = 1.82) from the core data. An integrated approach was used to determine n, which is related to the reservoir’s heterogeneity and wettability changes. The values of n for high Rt (n > 2) intervals ranged from 2.3 to 8.5, which is not close to the field average n value (1.82). Specific correlations were found by discriminating Swir (Swir < 15%), (Swir 15%–19%), and Swir (> 19%). The results showed that using n as a variable parameter improved Sw from 39.5% to 36.5% average in the T1 and T2 sands, showing a better fit than the core data average and increasing the STOIIP estimations by 6.81%. This represents now a primary oil recovery of 12.1%, closer to the expected value for these reservoirs. Although many studies have been done on n determination and its effect on Sw calculations, using average values over a whole field is still a common practice regardless of heterogeneity and wettability considerations. This study proposed a method to include the formation of heterogeneity and wettability changes in n determination, allowing a more reliable Sw determination as demonstrated in the TAM oil field in Suriname.

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