Using image logs to identify fluid types in tight carbonate reservoirs via apparent formation water resistivity spectrum

Abstract Hydrocarbon-bearing zone identification of tight reservoirs plays a crucial role in hydrocarbon exploration and development. However, tight carbonate reservoirs are generally characterized by complex lithology, low porosity, strong heterogeneity, and weak fluid logging responses, which present a major challenge to detect hydrocarbon-bearing zones using conventional methods. To address this challenge, this paper develops a new method defined as R wa spectrum, taking advantage of the high vertical resolution and borehole coverage of the image logs. The R wa spectra can be derived from the histogram distribution of the apparent resistivity values of formation water ( R wa ) in a sliding window, combining the Simandoux equation and the triple-porosity model. The results show that a very broad R wa spectrum with long tails corresponds to hydrocarbon-bearing zones, and the peak shape of it is flat. In contrast, the narrow R wa spectrum corresponds to water-bearing zones, and the peak shape of it is a sharp spike. Furthermore, two R wa spectrum parameters, namely AVERAGE (reflects the size of main peak values) and VARIANCE (reflects shape changes of the R wa spectra) are defined to quantificationally detect hydrocarbon-bearing zones. For oil zones in Yingxi field, the AVERAGE had a value higher than 10 and the VARIANCE was higher than 10. And for water zones, the AVERAGE had a value lower than 4.5 and the VARIANCE was lower than 5. The resistivity values decrease linearly with the increase in pyrite content of the reservoirs of high pyrite content, which disturbs the response to resistivity values from different fluid types (oil, gas or water). Hence, this method is suitable for the formation of no or little pyrite contents (lower than 0.2), and the case where the salinity value of drilling mud is similar to that of formation water. Moreover, the method has been validated by production test data, providing unusual perspectives on the identification of fluid types in tight carbonate reservoirs.