Integration of Borehole Imaging, Openhole Logs, Nuclear-Magnetic-Resonance/Modular Dynamic Tester, and Advanced Production Logging as a Guide for Perforation Intervals Selection in Thin-Bedded Sands and Shales

Abstract

Specifying the perforation intervals and evaluating the productivity of thin-bedded sands and shales is crucial for well completion cost optimization. This requires the accurate identification of hydrocarbon-bearing sands and their contribution to production. Relying only on borehole-imaging tools to select the productive intervals is not suitable in this lithologic type because of the difficulty of permeability quantification. In this paper we present a technique to integrate the detection of hydrocarbon-bearing sands with water saturation information and an estimation of permeability. Hydrocarbon-bearing sands are detected by high-resolution resistivity from borehole-imaging tools combined with water saturation from openhole logs (OHL), and permeability from nuclear magnetic resonance (NMR) or a modular dynamic tester tool. We use the geostatistical concept of indicators to convert the inputs from these tools into binary data (0 and 1) based on the best selected cutoffs for those inputs, where a value of 1 means that location is good to perforate. The results of this integration are compared to the results from the production logging tool that is sensitive to the laminated sand units for evaluating its actual productivity. The best cutoffs to select for those parameters are in good agreement with the production logging tool results. The result is a set of optimized perforation intervals consistent with all the data. In addition to the certainty percent associated with the selection of perforation intervals. Three gas wells producing from the same formation were used to apply this technique. One of the three wells was used to select the best cutoffs. For the other two wells, we used the same cutoffs to select the best perforation intervals and determine the certainty associated with them. The correct selection of the perforation intervals from the two wells was confirmed with the production testing and production logging results. Introduction High-resolution resistivity (SRES) tools are essential to identify the hydrocarbon-bearing layers in thin-bedded formations. However, hydrocarbon-bearing layers are not necessarily productive layers. Recently it was noticed that exploration and production (E&P) companies are relying on the borehole imaging tools to identify the perforation intervals. However, we have noticed from the production logging results performed across these formations that relying only on one tool to select the perforation interval is not the best approach. We saw the need to integrate different tools to assist in selecting the perforation and assessing the uncertainty associated with this selection. The following parameters have great impact in selecting the perforation intervals in thin-bedded gas reservoirs:The high-resolution resistivity to detect the thin sand bedsThe permeability for the productivity of the sand bedsThe water saturation from conventional openhole log interpretation for the hydrocarbon in place quantification. The objective of this study was to select the perforation intervals based on the integration between these three parameters. Thus, it was important to know how we can integrate these independent parameters with completely different dimensions to select the correct perforation intervals. Since our objective was to select specific intervals for perforation, we used the concept of an indicator1 to get a vertical indicator map for each parameter. An indicator of 1 means the location is a good candidate for perforation, and 0 means it is not a good candidate. The indicator map of each parameter depends on the threshold or the cutoff values selected for each parameter that will be selected based on the production-logging tool for the key well.