Fluid typing identification is one of the greatest challenges in Sichuan Basin, China. To solve this problem, various borehole measurements are introduced by operators, such as nuclear magnetic resonance and array dielectric logs. These measurements are barely satisfactory in carbonate reservoirs of late Precambrian Dengying Formation, owing to their strict requirements of measurement environment, like high porosity, limited mud invasion and less heterogeneity. Besides, the production performance was not well corresponded with the conventional log responses due to the limited resolution of logs and strong heterogeneity of reservoirs. This manuscript illustrates an integrated workflow for reservoir characterization and fluid typing identification by high-resolution electrical image logs.
Core analysis of Dengying carbonate reservoirs demonstrate the main types of pore space are vugs, caves and fractures. However, they are selectively developed and randomly distributed both laterally and vertically, hence complex heterogeneity. Various attributes of the pore space can be extracted from the electrical image logs, including connectedness, surface proportion, secondary pore size and thickness of dissolution zones. High-resolution electrical image logs of more than 60 wells were used to set up the dominant dissolution facies window, 7 facies were summarized based on electrical image logs with calibration of core data, including cave, alveolate vug, stratiform vug, fracture-vug, isolated vug , massive dense and interbedded dense facies.
By detailed analyzing open-hole logs and well testing data, we found the deep lateral resistivity of formation was significantly affected by the reservoir framework, apart from fluid type. The resistivity of massive structure types is apparently higher than that of interbedded facies. The lower limit of deep resistivity for gas pay was 300 ohm.m in the past, which leaded to many misjudgments of fluid typing. Now the lower limit could be only 100 ohm.m if considering types of formation structures. Besides, the reservoirs with different dissolution types show various performance of production. The workflow introduced in this paper has noticeably improved the coincidence rate of petrophysical evaluation in carbonate reservoir of late Precambrian Dengying Formation.
The case study presents how to identify different dissolution facies by integrating high-resolution electrical image logs with core data calibration, and how to establish the fluid typing identification chart based on deep resistivity logs and formation structures. The methodology significantly lowers the uncertainty for fluid typing identification and gas production forecast in heterogeneous carbonate reservoirs.